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His research interests are focused on cardiovascular disease risk factors, atherosclerosis biomarkers, vascular and cell biology and functional genetics and epigenetics of complex traits and diseases. He has extensive experience in genome-wide association studies and related bioinformatics, as well as other omics and high density SNP maps and deep sequencing in population-based samples. T.L have a total over 1000 publications. T.L has actively participated in over 70 New England J Med, Science, Lancet, Nature, Nature  Genetics papers over the last 5 years, and his work in collaboration with many international consortia has led to the discovery of over 3500 novel genetic variants of complex traits. T.L  holds a patent on a novel diagnostic test to predict statin myopathy. Tampere is the coordinating partner in an EU Collaborative Project on Inflammation and Vascular Wall Remodeling (AtheroRemo: A total 11.7 million EUR for whole project) and partner in several other collaborative efforts within the European Union, Australia and in the US and Canada. T.L. is responsible investigator of the genetic part of The Cardiovascular Risk In Young Finns study (YFS) and The Finnish Cardiovascular study (FINCAVAS). T.L. is the leader of Tampere Vascular study (TVS) focusing on the use of “OMICS” techniques in the research of atherosclerosis and functional genetics. T.L have skills in traditional and problem based teaching methods of over 30 years as part of the Faculty of Medicine and Life Sciences of Tampere University, which has been nominated three times, as a Centre of Excellence in high level teaching by the Finnish Higher Education Evaluation Council. Professor Lehtimäki graduated both as MD and PhD in 1992 from the University of Tampere. He was nominated as senior lecturer (docent) in Medical Biochemistry, at the University of Tampere in 1996, Specialist in Clinical Chemistry in 1999 and a senior lecturer (docent) in Clinical Chemistry, University of East Finland in 2003. T.L. is a member of executive group of Finnish Medical Laboratories Ltd, the board of Finnish Laboratory Medicine Foundation and the board of Koululab Ltd. He has supervised over 60 thesis, master's thesis and medical advanced studies and being helping in other 50 thesis as a coauthor.  In addition TL is supervising of five post-doctoral studies and is a active (official) trainer and national examiner of Clinical Chemistry specialists. TL. has been involved in a national team of specialists since 2003 making national guidelines (Käypä hoito -suositus) for the prevention of dyslipidemias and cardiovascular diseases. T.L has been a member of the board of the Finnish Medical Association of Clinical Chemistry and is a member of the editorial board in five international Journals. T.L’s research group is well recognized and represented in over 35 international consortia. Please see http://www.uta.fi/med/en/research/clinicalchemistry/index.html. Professor Terho Lehtimäki is the recipient of the first annual Science Prize of the University of Tampere. T.L has served as as a grant panel member or active reviewer of applications for 13 international funders/charities. T.L is currently the board member of Finnish Laboratory Medicine Foundation. T.L  have served and serve as an active reviewer in international journals several times annually, altogether over 200 times in over 50 different international journals: New England J of Medicine (several times), The Lancet (several times), Circulation Res, Journal of American College of Cardiology, Atherosclerosis Thrombosis and Vascular Biology (over 20 times), Stroke, Eur Heart J, Atherosclerosis, Clinical Chemistry, PLOS Genetics. T.L have examined and given expert opinion from twelve (12) academic dissertations/doctoral theses and given his written expert opinion of professor/docent/senior lecturer/applications 12 times. T.L have served several times as opponent for doctoral dissertations and is a member of several different scientific societies. T.L have participated on boards and committees, management groups, organizing of scientific education or congress meetings (> 35 times). T.L is currently in a executive groups of 4 projects funded by TEKES – the Finnish Funding Agency for Innovation. TL has published ca. 965 original articles that have been cited over 60.000 times according google citation reports:<br />(http://www.scopus.com/http://scholar.google.com/citations). T.Ls<br />Hirsch (h)-index is 107.<br /><div class="js-profile-less-about u-linkUnstyled u-tcGrayDarker u-textDecorationUnderline u-displayNone">less</div></div></div><div class="suggested-academics-container"><div class="suggested-academics--header"><p class="ds2-5-body-md-bold">Related Authors</p></div><ul class="suggested-user-card-list"><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://independent.academia.edu/CostanMagnussen"><img class="profile-avatar u-positionAbsolute" border="0" alt="" src="//a.academia-assets.com/images/s200_no_pic.png" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://independent.academia.edu/CostanMagnussen">Costan Magnussen</a></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a 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href="https://www.academia.edu/35206639/Childhood_Physical_Environmental_and_Genetic_Predictors_of_Adult_Hypertension_The_Cardiovascular_Risk_in_Young_Finns_Study">Childhood Physical, Environmental, and Genetic Predictors of Adult Hypertension The Cardiovascular Risk in Young Finns Study</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki">Terho Lehtimäki</a>, <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/EeroJokinen">Eero Jokinen</a>, and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/SamuelGidding">Samuel Gidding</a></span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="74f1686d22721d8b9a1524ef0112c32f" class="wp-workCard--action" rel="nofollow" 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})(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "74f1686d22721d8b9a1524ef0112c32f" } } $('.js-work-strip[data-work-id=35206639]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206639,"title":"Childhood Physical, Environmental, and Genetic Predictors of Adult Hypertension The Cardiovascular Risk in Young Finns 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dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206622"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206622/Body_mass_index_and_depressive_symptoms_instrumental_variables_regression_with_genetic_risk_score"><img alt="Research paper thumbnail of Body mass index and depressive symptoms: instrumental-variables regression with genetic risk score" class="work-thumbnail" src="https://attachments.academia-assets.com/55066684/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206622/Body_mass_index_and_depressive_symptoms_instrumental_variables_regression_with_genetic_risk_score">Body mass index and depressive symptoms: instrumental-variables regression with genetic risk score</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The causal role of obesity in the development of depression remains uncertain. We applied instrum...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The causal role of obesity in the development of depression remains uncertain. We applied instrumentalvariables regression (Mendelian randomization) to examine the association of adolescent and adult body mass index (BMI) with adult depressive symptoms. Participants were from the Young Finns prospective cohort study (n = 1731 persons, 2844 person-observations), with repeated measurements of BMI and depressive symptoms (modified Beck's Depression Inventory). Genetic risk score of 31 single nucleotide polymorphisms previously identified as robust genetic markers of body weight was used as a proxy for variation in BMI. In standard linear regression analysis, higher adult depressive symptoms were predicted by higher adolescent BMI (B = 0.33, CI = 0.06-0.60, P = 0.017) and adult BMI (B = 0.47, CI = 0.32-0.63, P < 0.001). These associations were replicated in instrumental-variables analysis with genetic risk score as instrument (B = 1.96, CI = 0.03-3.90, P = 0.047 for adolescent BMI; B = 1.08, CI = 0.11-2.04, P = 0.030 for adult BMI). The association for adolescent BMI was significantly stronger in the instrumented analysis compared to standard regression (P = 0.04). These findings provide additional evidence to support a causal role for high BMI in increasing symptoms of depression. However, the present analysis also demonstrates potential limitations of applying Mendelian randomization when using complex phenotypes.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3196f961fd2e4f0e66613fdf7f1346d8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066684,"asset_id":35206622,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066684/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206622"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206622"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206622; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206608"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206608/Childhood_Nutrition_in_Predicting_Metabolic_Syndrome_in_Adults_The_Cardiovascular_Risk_in_Young_Finns_Study"><img alt="Research paper thumbnail of Childhood Nutrition in Predicting Metabolic Syndrome in Adults The Cardiovascular Risk in Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066671/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206608/Childhood_Nutrition_in_Predicting_Metabolic_Syndrome_in_Adults_The_Cardiovascular_Risk_in_Young_Finns_Study">Childhood Nutrition in Predicting Metabolic Syndrome in Adults The Cardiovascular Risk in Young Finns Study</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki">Terho Lehtimäki</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/RistoTelama">Risto Telama</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">OBJECTIVEdOur aim was to study the associations of childhood lifestyle factors (the frequency of ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">OBJECTIVEdOur aim was to study the associations of childhood lifestyle factors (the frequency of consumption of vegetables, fruit, fish, and meat, butter use on bread, and physical activity) with the metabolic syndrome (MetS) in adulthood.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4a4faca7803e30563706e42137976042" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066671,"asset_id":35206608,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066671/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206608"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206608"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206608; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206608]").text(description); $(".js-view-count[data-work-id=35206608]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206608; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206608']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "4a4faca7803e30563706e42137976042" } } $('.js-work-strip[data-work-id=35206608]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206608,"title":"Childhood Nutrition in Predicting Metabolic Syndrome in Adults The Cardiovascular Risk in Young Finns Study","internal_url":"https://www.academia.edu/35206608/Childhood_Nutrition_in_Predicting_Metabolic_Syndrome_in_Adults_The_Cardiovascular_Risk_in_Young_Finns_Study","owner_id":32256334,"coauthors_can_edit":true,"owner":{"id":32256334,"first_name":"Terho","middle_initials":null,"last_name":"Lehtimäki","page_name":"TerhoLehtimäki","domain_name":"uta-fi","created_at":"2015-06-16T10:56:46.405-07:00","display_name":"Terho Lehtimäki","url":"https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki"},"attachments":[{"id":55066671,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/55066671/thumbnails/1.jpg","file_name":"JaaskelainenP_Diabetes_Care._2012_35_1937-43.pdf","download_url":"https://www.academia.edu/attachments/55066671/download_file","bulk_download_file_name":"Childhood_Nutrition_in_Predicting_Metabo.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/55066671/JaaskelainenP_Diabetes_Care._2012_35_1937-43-libre.pdf?1511248361=\u0026response-content-disposition=attachment%3B+filename%3DChildhood_Nutrition_in_Predicting_Metabo.pdf\u0026Expires=1740611052\u0026Signature=InYnWl8izklbDN3ZBHpl7lRPQ9coD9D4ADryP8~-iw58ZRWupdQQG3C09VRyp~UBf5JLrDsr3DMI5hOBFW2OvcocGxt-WZEaDBDTP6M4GlGa-IgYP3nHSigaf-zXYqMsL~W1W2KLlQTVcje5oWxutEsGk-ZndqpAGfOdZNHHrKIFLUaGk1kbbMmsfmRII6jwoZD4f2xVatswO4Cj5xFaWeTHB42NGjH7s0VNhA4ym8gAUUox4TuYiAX7YrMUOdReQ4EUVWfQDKBlYMTa47oNhm4VQIjOWLdIpHgNT8KLdHTmIx~EZRE5AStjUoveB80xUx5J6dRhKsV6LLHf~Dkppw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206604"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206604/Neuropeptide_Y_polymorphism_increases_the_risk_for_asthma_in_overweight_subjects_protection_from_atherosclerosis_in_asthmatic_subjects_The_cardiovascular_risk_in_young_Finns_study"><img alt="Research paper thumbnail of Neuropeptide Y polymorphism increases the risk for asthma in overweight subjects; protection from atherosclerosis in asthmatic subjects – The cardiovascular risk in young Finns study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066662/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206604/Neuropeptide_Y_polymorphism_increases_the_risk_for_asthma_in_overweight_subjects_protection_from_atherosclerosis_in_asthmatic_subjects_The_cardiovascular_risk_in_young_Finns_study">Neuropeptide Y polymorphism increases the risk for asthma in overweight subjects; protection from atherosclerosis in asthmatic subjects – The cardiovascular risk in young Finns study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Aims: The role of neuropeptide Y (NPY) and its gene polymorphisms in the development of atheroscl...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Aims: The role of neuropeptide Y (NPY) and its gene polymorphisms in the development of atherosclerosis has become increasingly evident. In asthma, NPY has been shown to be involved as immunomodulator. In this study, we investigated the role of two functional NPY polymorphisms, NPY-Leu7Pro (rs16139) and NPY-399C/T (rs16147) and obesity for the development of asthma as well as atherosclerosis in asthmatic and non-asthmatic subjects. Also, we measured heart rate variability (HRV) and NPY in serum since these might contribute through these polymorphisms to both diseases. Methods and results: Thousand hundred and seventy six Finnish young adults were genotyped and three groups (G1-G3) were formed based on the observed diplotypes. The NPY-Pro7 allele always co-existed with the NPY-399T allele indicating complete linkage disequilibrium. Here we show that overweight (BMI P 25 kg/m 2 ) was associated with 2.5-fold increased risk for asthma in subjects with the NPY-399T allele without NPY-Pro7 allele (G2, n = 716). Overweight was also associated with increased atherosclerosis determined by carotid intima media thickness (cIMT), but asthma seemed to be more significant determinant than overweight in determing cIMT having a decreasing effect. NPY concentration in serum was diplotype-driven (G1 = 792.2(29.5), G2 = 849.0(18.9), G3 = 873.9(45.2) pg/ml) and correlated positively with cIMT in the group having NPY-Pro7 allele (G3, n = 142). However, the subjects with asthma had a negative NPY-cIMT relationship. Total HRV was increased in asthma and correlated negatively with cIMT irrespective of the NPY genotype. Conclusions: Overweight together with the NPY-399T allele without NPY-Pro7 allele was associated with increased risk for asthma. Atherosclerosis was decreased in subjects with asthma depending on the NPY genotype. The results reveal novel insights into the genetics and biology of the relationship of atherosclerosis and asthma.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0d78ecfa44e8f88130d2802329b0a03a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066662,"asset_id":35206604,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066662/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206604"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206604"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206604; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206594"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206594/Upstream_Transcription_Factor_1_USF1_Polymorphisms_Associate_with_Alzheimers_Disease_related_Neuropathological_Lesions_Tampere_Autopsy_Study"><img alt="Research paper thumbnail of Upstream Transcription Factor 1 (USF1) Polymorphisms Associate with Alzheimer's Disease-related Neuropathological Lesions: Tampere Autopsy Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066652/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206594/Upstream_Transcription_Factor_1_USF1_Polymorphisms_Associate_with_Alzheimers_Disease_related_Neuropathological_Lesions_Tampere_Autopsy_Study">Upstream Transcription Factor 1 (USF1) Polymorphisms Associate with Alzheimer's Disease-related Neuropathological Lesions: Tampere Autopsy Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The apolipoprotein E (APOE) gene associates with Alzheimer's disease (AD) and cholesterol levels....</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The apolipoprotein E (APOE) gene associates with Alzheimer's disease (AD) and cholesterol levels. Upstream transcription factor 1 (USF1) regulates lipid metabolism genes, including APOE, and the AD Ab-precursor protein. We investigated associations between 6 haplotype-tagging USF1 single-nucleotide polymorphisms (and haplotypes) and AD-related neuropathological lesions [senile plaques (SP), neurofibrillary tangles (NFT) ] in an autopsy series comprising 603 cases (ages 0-97, mean 62 years, 215 women) that died out-of-hospital. In age-and APOE-adjusted analyses, the minor G-allele of rs2774276, previously linked to elevated cholesterol, associated with late-stage burnt out SP among women and early non-neuritic SP among men. The G-allele of the previously unreported rs10908821 showed significant risk of having SP, especially neuritic and burnt out SP, among women but not men. USF1 haplotype GCGCAC carriers (risk alleles of rs2774276 and rs10908821) associated with SP risk, especially neuritic and late-stage burnt out SP, among women but not men. Younger CCGCAC carriers (risk allele of rs2774276 and protective of rs10908821) were more likely to have non-neuritic and diffuse SP. Conversely, USF1 CCGCAC haplotype carriers had lower NFT prevalence among 65+ year-olds. These results suggest USF1 has an independent but gender-and age-associated effect on AD-related brain lesion development.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f955ad4f0a386b4b1627d55c8553f875" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066652,"asset_id":35206594,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066652/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206594"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206594"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206594; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206589"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206589/Novel_Loci_for_Metabolic_Networks_and_Multi_Tissue_Expression_Studies_Reveal_Genes_for_Atherosclerosis"><img alt="Research paper thumbnail of Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis" class="work-thumbnail" src="https://attachments.academia-assets.com/55066644/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206589/Novel_Loci_for_Metabolic_Networks_and_Multi_Tissue_Expression_Studies_Reveal_Genes_for_Atherosclerosis">Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Association testing of multiple correlated phenotypes offers better power than univariate analysi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f54cb56b4f04a659283c4b07d43b0f8e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066644,"asset_id":35206589,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066644/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206589"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206589"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206589; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206543"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206543/Genetic_Profiling_Using_Genome_Wide_Significant_Coronary_Artery_Disease_Risk_Variants_Does_Not_Improve_the_Prediction_of_Subclinical_Atherosclerosis_The_Cardiovascular_Risk_in_Young_Finns_Study_the_Bogalusa_Heart_Study_and_the_Health_2000_Survey_A_Meta_Analysis_of_Three_Independent_Studies"><img alt="Research paper thumbnail of Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies" class="work-thumbnail" src="https://attachments.academia-assets.com/55066598/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206543/Genetic_Profiling_Using_Genome_Wide_Significant_Coronary_Artery_Disease_Risk_Variants_Does_Not_Improve_the_Prediction_of_Subclinical_Atherosclerosis_The_Cardiovascular_Risk_in_Young_Finns_Study_the_Bogalusa_Heart_Study_and_the_Health_2000_Survey_A_Meta_Analysis_of_Three_Independent_Studies">Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Genome-wide association studies (GWASs) have identified a large number of variants (S...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis -i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) -beyond classical risk factors.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cd64f6a9651377404afc113b287b011b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066598,"asset_id":35206543,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066598/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206543"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206543"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206543; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206491"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study"><img alt="Research paper thumbnail of Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066540/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study">Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Human cytomegalovirus (CMV) infection is associated with a higher risk of cardiovascular disease ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Human cytomegalovirus (CMV) infection is associated with a higher risk of cardiovascular disease in immunocompromised organ transplant patients. It has been linked with the pathogenesis of elevated arterial blood pressure. However, controversy exists as to whether CMV infection is associated with endothelial function, and little is known about its role as a potential risk factor for early atherosclerosis development at a young age. We aimed to discover if CMV antibody titres are associated with early vascular changes (carotid intima-media thickness, carotid artery distensibility and brachial artery flowmediated dilation), blood pressure elevation or other traditional cardiovascular risk factors. CMV antibody titres were measured in 1074 women and 857 men (aged 24-39 years) taking part in the Cardiovascular Risk in Young Finns study. CMV antibody titres were significantly higher in women compared to men. In men, high CMV antibody titres were associated directly with age (P < 0·001) and systolic (P = 0·053) and diastolic (P = 0·002) blood pressure elevation, and associated inversely with flow-mediated dilation (P = 0·014). In women, CMV antibody titres did not associate with any of the analysed parameters. In a multivariate regression model, which included traditional atherosclerotic risk factors, CMV antibody titres were independent determinants for systolic (P = 0·029) and diastolic (P = 0·004) blood pressure elevation and flow-mediated dilation (P = 0·014) in men. High CMV antibody titres are associated independently with blood pressure and brachial artery flow-mediated dilation in young men. This association supports the hypothesis that common CMV infection and/or an immune response to CMV may lead to impaired vascular function at a young age.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0849e6e693b87055e240e7412849e463" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066540,"asset_id":35206491,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066540/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206491"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206491"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206491; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206491]").text(description); $(".js-view-count[data-work-id=35206491]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206491; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206491']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "0849e6e693b87055e240e7412849e463" } } $('.js-work-strip[data-work-id=35206491]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206491,"title":"Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study","internal_url":"https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study","owner_id":32256334,"coauthors_can_edit":true,"owner":{"id":32256334,"first_name":"Terho","middle_initials":null,"last_name":"Lehtimäki","page_name":"TerhoLehtimäki","domain_name":"uta-fi","created_at":"2015-06-16T10:56:46.405-07:00","display_name":"Terho Lehtimäki","url":"https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki"},"attachments":[{"id":55066540,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/55066540/thumbnails/1.jpg","file_name":"HaaralaA_Clin_Exp_Immunol._2012_167_309-16.pdf","download_url":"https://www.academia.edu/attachments/55066540/download_file","bulk_download_file_name":"Relation_of_high_cytomegalovirus_antibod.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/55066540/HaaralaA_Clin_Exp_Immunol._2012_167_309-16-libre.pdf?1511246887=\u0026response-content-disposition=attachment%3B+filename%3DRelation_of_high_cytomegalovirus_antibod.pdf\u0026Expires=1740611052\u0026Signature=DWswHvwYNene0nOgxGbgIrNS0qN4ASF2mdGc8xdr~r39WX0hWDnGe1VPqkkxcQuJ7P0CIbC1xhxrg5kjZpQlyzqjMLmteRiGH6HdfvSWZCE7yNxKHgxByD1U1J8knl6cGRtHIJoZVjWjruthaEA5hGCipG0MS7hdv4BXeF4v6xZzzuNdNnNqP2RDjCMjNF4DSoRkV6ir44d8v-oTBNsJm~RjMie-4rUY2Ttn3OFPq4RwZkWkEWtX1Cbm539W7h6G48v6Hd4~7aAq7wTGSe9FORYeSJc1~ZRVLjgjyu9uy7XG-6Rr8eVWfNbW-jseQcX0axenTD~96dHKRejbhyWwlw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206479"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure"><img alt="Research paper thumbnail of Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure" class="work-thumbnail" src="https://attachments.academia-assets.com/55066526/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure">Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, t...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n FIN = 11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n = 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p FIN = 3.01E-05, p ICBP-GWAS = 0.0007, p ALL = 8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="43f4c7accf59a67577e8ca0681d4b49f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066526,"asset_id":35206479,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066526/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206479"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206479"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206479; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206479]").text(description); $(".js-view-count[data-work-id=35206479]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206479; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206479']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "43f4c7accf59a67577e8ca0681d4b49f" } } $('.js-work-strip[data-work-id=35206479]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206479,"title":"Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure","internal_url":"https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure","owner_id":32256334,"coauthors_can_edit":true,"owner":{"id":32256334,"first_name":"Terho","middle_initials":null,"last_name":"Lehtimäki","page_name":"TerhoLehtimäki","domain_name":"uta-fi","created_at":"2015-06-16T10:56:46.405-07:00","display_name":"Terho Lehtimäki","url":"https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki"},"attachments":[{"id":55066526,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/55066526/thumbnails/1.jpg","file_name":"GaalEI_PLoS_Genet._2012_8.pdf","download_url":"https://www.academia.edu/attachments/55066526/download_file","bulk_download_file_name":"Intracranial_Aneurysm_Risk_Locus_5q23_2.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/55066526/GaalEI_PLoS_Genet._2012_8-libre.pdf?1511246887=\u0026response-content-disposition=attachment%3B+filename%3DIntracranial_Aneurysm_Risk_Locus_5q23_2.pdf\u0026Expires=1740611052\u0026Signature=YPpSruhHIFXjcwXkZzUGYzN1awLch0SNeFBW-FfPjzvHZjHaC0t5VJFIJS135LHoC~vdSJYUBfPm0GRHGsqpCJ6-Lx4F7iTIFmFh6N5xD4K2O6dvl-Vj8sKFoap16Jj89lrrh33gTNxRUoa3sfC8R9VaDr4E7u16m2j198VoYRGs23u0RAbizobl94876DqfsHFAcoyJEEjFME02yTVO8QQWLqsqTAElR0aO-PNPJ6geSApIT8ruFprXnqOfeRLqNBCaKGooZ4O4y7KW3t6hi9IO9p7E8BWoTG-R7UOa~RVBJ1iHuokr8FNFqh--uvJdB0B8yU4RtHWcy6g7OLGViQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206461"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206461/Genome_wide_association_analysis_identifies_susceptibility_loci_for_migraine_without_aura"><img alt="Research paper thumbnail of Genome-wide association analysis identifies susceptibility loci for migraine without aura" class="work-thumbnail" src="https://attachments.academia-assets.com/55066508/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206461/Genome_wide_association_analysis_identifies_susceptibility_loci_for_migraine_without_aura">Genome-wide association analysis identifies susceptibility loci for migraine without aura</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Migraine without aura is the most common form of migraine, characterized by recurrent disabling h...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Migraine without aura is the most common form of migraine, characterized by recurrent disabling headache and associated autonomic symptoms. To identify common genetic variants for this migraine type, we analyzed genome-wide association data of 2,326 clinic-based German and Dutch patients and 4,580 population-matched controls. We selected SNPs from 12 loci with two or more SNPs with P-values < 1 × 10 −5 for follow-up in 2,508 patients and 2,652 controls. Two loci, i.e. 1q22 (MEF2D) and 3p24 (near TGFBR2) replicated convincingly (P = 4.9 × 10 −4 , P = 1.0 × 10 −4 , respectively). Meta-analysis of the discovery and replication data yielded two additional genome-wide significant (P < 5 × 10 −8 ) loci in PHACTR1 and ASTN2. In addition, SNPs in two previously reported migraine loci in or near TRPM8 and LRP1 significantly replicated. This study reveals the first susceptibility loci for migraine without aura, thereby expanding our knowledge of this debilitating neurological disorder.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="07b5f6e49f8db98be06504ee3366305b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066508,"asset_id":35206461,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066508/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206461"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206461"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206461; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206448]").text(description); $(".js-view-count[data-work-id=35206448]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206448; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206448']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206440"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206440/Indoleamine_2_3_Dioxygenase_Activation_and_Depressive_Symptoms_Results_From_the_Young_Finns_Study"><img alt="Research paper thumbnail of Indoleamine 2,3-Dioxygenase Activation and Depressive Symptoms: Results From the Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066487/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206440/Indoleamine_2_3_Dioxygenase_Activation_and_Depressive_Symptoms_Results_From_the_Young_Finns_Study">Indoleamine 2,3-Dioxygenase Activation and Depressive Symptoms: Results From the Young Finns Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Objective: To examine whether the activation of indoleamine 2,3-dioxygenase (IDO), an enzyme invo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Objective: To examine whether the activation of indoleamine 2,3-dioxygenase (IDO), an enzyme involved in serotonin production, is associated with depressive symptoms. Methods: The participants were 544 women and 442 men (aged 24Y39 years) from the population-based Young Finns Study who participated in a medical examination in 2001 (including IDO and depression) and 2007 (follow-up assessment for depression). Results: At baseline, IDO was associated with depressive symptoms (in the total cohort: B = 0.23, p G .001; women: B = 0.20, p = .007; men: B = 0.29, p = .002; p for interaction = .19). IDO at baseline was also associated with depressive symptoms at follow-up in women (B = 0.17, p = .03), which remained significant when adjusting for any of the biologic and behavioral risk factors. Adjusting for body mass index attenuated the association by 6%. In the final model including all baseline variables, none of the risk factors (except for baseline depressive symptoms) were associated with depressive symptoms at follow-up. Conclusions: These data suggest that IDO activity may be a risk factor for future depression especially in women. IDO-induced alterations in serotonergic function may offer one biologic explanation to the well-established associations between inflammation and depression. Key words: inflammation, longitudinal, depressive symptoms, serotonin, sex. IDO = indoleamine 2,3-dioxygenase; TRP = tryptophan; KYN = kynurenine; CRP = C-reactive protein; BDI = Beck Depression Inventory; BMI = body mass index.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d5897c7538e97a28473ed5f5788c706c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066487,"asset_id":35206440,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066487/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206440"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206440"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206440; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206429"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206429/Novel_Loci_for_Adiponectin_Levels_and_Their_Influence_on_Type_2_Diabetes_and_Metabolic_Traits_A_Multi_Ethnic_Meta_Analysis_of_45_891_Individuals"><img alt="Research paper thumbnail of Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals" class="work-thumbnail" src="https://attachments.academia-assets.com/55066476/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206429/Novel_Loci_for_Adiponectin_Levels_and_Their_Influence_on_Type_2_Diabetes_and_Metabolic_Traits_A_Multi_Ethnic_Meta_Analysis_of_45_891_Individuals">Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly her...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5610 28 -1.2610 243 ). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p,3610 24 ). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3610 23 , n = 22,044), increased triglycerides (p = 2.6610 214 , n = 93,440), increased waist-to-hip ratio (p = 1.8610 25 , n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4610 23 , n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDLcholesterol concentrations (p = 4.5610 213 , n = 96,748) and decreased BMI (p = 1.4610 24 , n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2835d08140862f7d4c3e162a4dcb7f56" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066476,"asset_id":35206429,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066476/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206429"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206429"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206429; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206407"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206407/A_Genome_Wide_Association_Meta_Analysis_of_Circulating_Sex_Hormone_Binding_Globulin_Reveals_Multiple_Loci_Implicated_in_Sex_Steroid_Hormone_Regulation"><img alt="Research paper thumbnail of A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation" class="work-thumbnail" src="https://attachments.academia-assets.com/55066456/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206407/A_Genome_Wide_Association_Meta_Analysis_of_Circulating_Sex_Hormone_Binding_Globulin_Reveals_Multiple_Loci_Implicated_in_Sex_Steroid_Hormone_Regulation">A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. (rs3779195, 7q21.3, p = 2.7610 208 ), and UGT2B15 (rs293428, 4q13.2, p = 5.5610 206 ). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5610 208 , women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sexdifferentiated or conditional analyses explained ,15.6% and ,8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3623ab2aff805f334ab5de2b99db5dd8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066456,"asset_id":35206407,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066456/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206407"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206407"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206407; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206392]").text(description); $(".js-view-count[data-work-id=35206392]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206392; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206392']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206358"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206358/A_genome_wide_association_meta_analysis_identifies_new_childhood_obesity_loci"><img alt="Research paper thumbnail of A genome-wide association meta-analysis identifies new childhood obesity loci" class="work-thumbnail" src="https://attachments.academia-assets.com/55066400/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206358/A_genome_wide_association_meta_analysis_identifies_new_childhood_obesity_loci">A genome-wide association meta-analysis identifies new childhood obesity loci</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Multiple genetic variants have been associated with adult obesity and a few with severe obesity i...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made to establish genetic influences on common early-onset obesity. We performed a North American-Australian-European collaborative metaanalysis of fourteen studies consisting of 5,530 cases (≥95 th percentile of body mass index (BMI)) and 8,318 controls (<50 th percentile of BMI) of European ancestry. Taking forward the eight novel signals yielding association with P < 5×10 −6 in to nine independent datasets (n = 2,818 cases and 4,083 controls) we observed two loci that yielded a genome wide significant combined P-value, namely near OLFM4 on 13q14 (rs9568856; P=1.82×10 −9 ; OR=1.22) and within HOXB5 on 17q21 (rs9299; P=3.54×10 −9 ; OR=1.14). Both loci continued to show association when including two extreme childhood obesity cohorts (n = 2,214 cases and 2,674 controls). Finally, these two loci yielded directionally consistent associations in the GIANT meta-analysis of adult BMI 1 .</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5aa5342471079baa88261f2faa4644aa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066400,"asset_id":35206358,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066400/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206358"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206358"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206358; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206622"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206622/Body_mass_index_and_depressive_symptoms_instrumental_variables_regression_with_genetic_risk_score"><img alt="Research paper thumbnail of Body mass index and depressive symptoms: instrumental-variables regression with genetic risk score" class="work-thumbnail" src="https://attachments.academia-assets.com/55066684/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206622/Body_mass_index_and_depressive_symptoms_instrumental_variables_regression_with_genetic_risk_score">Body mass index and depressive symptoms: instrumental-variables regression with genetic risk score</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The causal role of obesity in the development of depression remains uncertain. We applied instrum...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The causal role of obesity in the development of depression remains uncertain. We applied instrumentalvariables regression (Mendelian randomization) to examine the association of adolescent and adult body mass index (BMI) with adult depressive symptoms. Participants were from the Young Finns prospective cohort study (n = 1731 persons, 2844 person-observations), with repeated measurements of BMI and depressive symptoms (modified Beck's Depression Inventory). Genetic risk score of 31 single nucleotide polymorphisms previously identified as robust genetic markers of body weight was used as a proxy for variation in BMI. In standard linear regression analysis, higher adult depressive symptoms were predicted by higher adolescent BMI (B = 0.33, CI = 0.06-0.60, P = 0.017) and adult BMI (B = 0.47, CI = 0.32-0.63, P < 0.001). These associations were replicated in instrumental-variables analysis with genetic risk score as instrument (B = 1.96, CI = 0.03-3.90, P = 0.047 for adolescent BMI; B = 1.08, CI = 0.11-2.04, P = 0.030 for adult BMI). The association for adolescent BMI was significantly stronger in the instrumented analysis compared to standard regression (P = 0.04). These findings provide additional evidence to support a causal role for high BMI in increasing symptoms of depression. However, the present analysis also demonstrates potential limitations of applying Mendelian randomization when using complex phenotypes.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3196f961fd2e4f0e66613fdf7f1346d8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066684,"asset_id":35206622,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066684/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206622"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206622"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206622; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206608"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206608/Childhood_Nutrition_in_Predicting_Metabolic_Syndrome_in_Adults_The_Cardiovascular_Risk_in_Young_Finns_Study"><img alt="Research paper thumbnail of Childhood Nutrition in Predicting Metabolic Syndrome in Adults The Cardiovascular Risk in Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066671/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206608/Childhood_Nutrition_in_Predicting_Metabolic_Syndrome_in_Adults_The_Cardiovascular_Risk_in_Young_Finns_Study">Childhood Nutrition in Predicting Metabolic Syndrome in Adults The Cardiovascular Risk in Young Finns Study</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki">Terho Lehtimäki</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://independent.academia.edu/RistoTelama">Risto Telama</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">OBJECTIVEdOur aim was to study the associations of childhood lifestyle factors (the frequency of ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">OBJECTIVEdOur aim was to study the associations of childhood lifestyle factors (the frequency of consumption of vegetables, fruit, fish, and meat, butter use on bread, and physical activity) with the metabolic syndrome (MetS) in adulthood.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4a4faca7803e30563706e42137976042" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066671,"asset_id":35206608,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066671/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206608"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206608"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206608; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206608]").text(description); $(".js-view-count[data-work-id=35206608]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206608; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206608']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206604"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206604/Neuropeptide_Y_polymorphism_increases_the_risk_for_asthma_in_overweight_subjects_protection_from_atherosclerosis_in_asthmatic_subjects_The_cardiovascular_risk_in_young_Finns_study"><img alt="Research paper thumbnail of Neuropeptide Y polymorphism increases the risk for asthma in overweight subjects; protection from atherosclerosis in asthmatic subjects – The cardiovascular risk in young Finns study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066662/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206604/Neuropeptide_Y_polymorphism_increases_the_risk_for_asthma_in_overweight_subjects_protection_from_atherosclerosis_in_asthmatic_subjects_The_cardiovascular_risk_in_young_Finns_study">Neuropeptide Y polymorphism increases the risk for asthma in overweight subjects; protection from atherosclerosis in asthmatic subjects – The cardiovascular risk in young Finns study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Aims: The role of neuropeptide Y (NPY) and its gene polymorphisms in the development of atheroscl...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Aims: The role of neuropeptide Y (NPY) and its gene polymorphisms in the development of atherosclerosis has become increasingly evident. In asthma, NPY has been shown to be involved as immunomodulator. In this study, we investigated the role of two functional NPY polymorphisms, NPY-Leu7Pro (rs16139) and NPY-399C/T (rs16147) and obesity for the development of asthma as well as atherosclerosis in asthmatic and non-asthmatic subjects. Also, we measured heart rate variability (HRV) and NPY in serum since these might contribute through these polymorphisms to both diseases. Methods and results: Thousand hundred and seventy six Finnish young adults were genotyped and three groups (G1-G3) were formed based on the observed diplotypes. The NPY-Pro7 allele always co-existed with the NPY-399T allele indicating complete linkage disequilibrium. Here we show that overweight (BMI P 25 kg/m 2 ) was associated with 2.5-fold increased risk for asthma in subjects with the NPY-399T allele without NPY-Pro7 allele (G2, n = 716). Overweight was also associated with increased atherosclerosis determined by carotid intima media thickness (cIMT), but asthma seemed to be more significant determinant than overweight in determing cIMT having a decreasing effect. NPY concentration in serum was diplotype-driven (G1 = 792.2(29.5), G2 = 849.0(18.9), G3 = 873.9(45.2) pg/ml) and correlated positively with cIMT in the group having NPY-Pro7 allele (G3, n = 142). However, the subjects with asthma had a negative NPY-cIMT relationship. Total HRV was increased in asthma and correlated negatively with cIMT irrespective of the NPY genotype. Conclusions: Overweight together with the NPY-399T allele without NPY-Pro7 allele was associated with increased risk for asthma. Atherosclerosis was decreased in subjects with asthma depending on the NPY genotype. The results reveal novel insights into the genetics and biology of the relationship of atherosclerosis and asthma.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0d78ecfa44e8f88130d2802329b0a03a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066662,"asset_id":35206604,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066662/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206604"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206604"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206604; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206594"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206594/Upstream_Transcription_Factor_1_USF1_Polymorphisms_Associate_with_Alzheimers_Disease_related_Neuropathological_Lesions_Tampere_Autopsy_Study"><img alt="Research paper thumbnail of Upstream Transcription Factor 1 (USF1) Polymorphisms Associate with Alzheimer's Disease-related Neuropathological Lesions: Tampere Autopsy Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066652/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206594/Upstream_Transcription_Factor_1_USF1_Polymorphisms_Associate_with_Alzheimers_Disease_related_Neuropathological_Lesions_Tampere_Autopsy_Study">Upstream Transcription Factor 1 (USF1) Polymorphisms Associate with Alzheimer's Disease-related Neuropathological Lesions: Tampere Autopsy Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The apolipoprotein E (APOE) gene associates with Alzheimer's disease (AD) and cholesterol levels....</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The apolipoprotein E (APOE) gene associates with Alzheimer's disease (AD) and cholesterol levels. Upstream transcription factor 1 (USF1) regulates lipid metabolism genes, including APOE, and the AD Ab-precursor protein. We investigated associations between 6 haplotype-tagging USF1 single-nucleotide polymorphisms (and haplotypes) and AD-related neuropathological lesions [senile plaques (SP), neurofibrillary tangles (NFT) ] in an autopsy series comprising 603 cases (ages 0-97, mean 62 years, 215 women) that died out-of-hospital. In age-and APOE-adjusted analyses, the minor G-allele of rs2774276, previously linked to elevated cholesterol, associated with late-stage burnt out SP among women and early non-neuritic SP among men. The G-allele of the previously unreported rs10908821 showed significant risk of having SP, especially neuritic and burnt out SP, among women but not men. USF1 haplotype GCGCAC carriers (risk alleles of rs2774276 and rs10908821) associated with SP risk, especially neuritic and late-stage burnt out SP, among women but not men. Younger CCGCAC carriers (risk allele of rs2774276 and protective of rs10908821) were more likely to have non-neuritic and diffuse SP. Conversely, USF1 CCGCAC haplotype carriers had lower NFT prevalence among 65+ year-olds. These results suggest USF1 has an independent but gender-and age-associated effect on AD-related brain lesion development.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f955ad4f0a386b4b1627d55c8553f875" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066652,"asset_id":35206594,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066652/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206594"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206594"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206594; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206589"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206589/Novel_Loci_for_Metabolic_Networks_and_Multi_Tissue_Expression_Studies_Reveal_Genes_for_Atherosclerosis"><img alt="Research paper thumbnail of Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis" class="work-thumbnail" src="https://attachments.academia-assets.com/55066644/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206589/Novel_Loci_for_Metabolic_Networks_and_Multi_Tissue_Expression_Studies_Reveal_Genes_for_Atherosclerosis">Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Association testing of multiple correlated phenotypes offers better power than univariate analysi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f54cb56b4f04a659283c4b07d43b0f8e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066644,"asset_id":35206589,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066644/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206589"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206589"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206589; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206589]").text(description); $(".js-view-count[data-work-id=35206589]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206589; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206589']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206543"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206543/Genetic_Profiling_Using_Genome_Wide_Significant_Coronary_Artery_Disease_Risk_Variants_Does_Not_Improve_the_Prediction_of_Subclinical_Atherosclerosis_The_Cardiovascular_Risk_in_Young_Finns_Study_the_Bogalusa_Heart_Study_and_the_Health_2000_Survey_A_Meta_Analysis_of_Three_Independent_Studies"><img alt="Research paper thumbnail of Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies" class="work-thumbnail" src="https://attachments.academia-assets.com/55066598/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206543/Genetic_Profiling_Using_Genome_Wide_Significant_Coronary_Artery_Disease_Risk_Variants_Does_Not_Improve_the_Prediction_of_Subclinical_Atherosclerosis_The_Cardiovascular_Risk_in_Young_Finns_Study_the_Bogalusa_Heart_Study_and_the_Health_2000_Survey_A_Meta_Analysis_of_Three_Independent_Studies">Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Background: Genome-wide association studies (GWASs) have identified a large number of variants (S...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Background: Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis -i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) -beyond classical risk factors.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cd64f6a9651377404afc113b287b011b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066598,"asset_id":35206543,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066598/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206543"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206543"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206543; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206491"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study"><img alt="Research paper thumbnail of Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066540/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study">Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Human cytomegalovirus (CMV) infection is associated with a higher risk of cardiovascular disease ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Human cytomegalovirus (CMV) infection is associated with a higher risk of cardiovascular disease in immunocompromised organ transplant patients. It has been linked with the pathogenesis of elevated arterial blood pressure. However, controversy exists as to whether CMV infection is associated with endothelial function, and little is known about its role as a potential risk factor for early atherosclerosis development at a young age. We aimed to discover if CMV antibody titres are associated with early vascular changes (carotid intima-media thickness, carotid artery distensibility and brachial artery flowmediated dilation), blood pressure elevation or other traditional cardiovascular risk factors. CMV antibody titres were measured in 1074 women and 857 men (aged 24-39 years) taking part in the Cardiovascular Risk in Young Finns study. CMV antibody titres were significantly higher in women compared to men. In men, high CMV antibody titres were associated directly with age (P < 0·001) and systolic (P = 0·053) and diastolic (P = 0·002) blood pressure elevation, and associated inversely with flow-mediated dilation (P = 0·014). In women, CMV antibody titres did not associate with any of the analysed parameters. In a multivariate regression model, which included traditional atherosclerotic risk factors, CMV antibody titres were independent determinants for systolic (P = 0·029) and diastolic (P = 0·004) blood pressure elevation and flow-mediated dilation (P = 0·014) in men. High CMV antibody titres are associated independently with blood pressure and brachial artery flow-mediated dilation in young men. This association supports the hypothesis that common CMV infection and/or an immune response to CMV may lead to impaired vascular function at a young age.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0849e6e693b87055e240e7412849e463" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066540,"asset_id":35206491,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066540/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206491"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206491"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206491; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206491]").text(description); $(".js-view-count[data-work-id=35206491]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206491; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206491']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "0849e6e693b87055e240e7412849e463" } } $('.js-work-strip[data-work-id=35206491]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206491,"title":"Relation of high cytomegalovirus antibody titres to blood pressure and brachial artery flow-mediated dilation in young men: the Cardiovascular Risk in Young Finns Study","internal_url":"https://www.academia.edu/35206491/Relation_of_high_cytomegalovirus_antibody_titres_to_blood_pressure_and_brachial_artery_flow_mediated_dilation_in_young_men_the_Cardiovascular_Risk_in_Young_Finns_Study","owner_id":32256334,"coauthors_can_edit":true,"owner":{"id":32256334,"first_name":"Terho","middle_initials":null,"last_name":"Lehtimäki","page_name":"TerhoLehtimäki","domain_name":"uta-fi","created_at":"2015-06-16T10:56:46.405-07:00","display_name":"Terho Lehtimäki","url":"https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki"},"attachments":[{"id":55066540,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/55066540/thumbnails/1.jpg","file_name":"HaaralaA_Clin_Exp_Immunol._2012_167_309-16.pdf","download_url":"https://www.academia.edu/attachments/55066540/download_file","bulk_download_file_name":"Relation_of_high_cytomegalovirus_antibod.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/55066540/HaaralaA_Clin_Exp_Immunol._2012_167_309-16-libre.pdf?1511246887=\u0026response-content-disposition=attachment%3B+filename%3DRelation_of_high_cytomegalovirus_antibod.pdf\u0026Expires=1740611052\u0026Signature=DWswHvwYNene0nOgxGbgIrNS0qN4ASF2mdGc8xdr~r39WX0hWDnGe1VPqkkxcQuJ7P0CIbC1xhxrg5kjZpQlyzqjMLmteRiGH6HdfvSWZCE7yNxKHgxByD1U1J8knl6cGRtHIJoZVjWjruthaEA5hGCipG0MS7hdv4BXeF4v6xZzzuNdNnNqP2RDjCMjNF4DSoRkV6ir44d8v-oTBNsJm~RjMie-4rUY2Ttn3OFPq4RwZkWkEWtX1Cbm539W7h6G48v6Hd4~7aAq7wTGSe9FORYeSJc1~ZRVLjgjyu9uy7XG-6Rr8eVWfNbW-jseQcX0axenTD~96dHKRejbhyWwlw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206479"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure"><img alt="Research paper thumbnail of Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure" class="work-thumbnail" src="https://attachments.academia-assets.com/55066526/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure">Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, t...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n FIN = 11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n = 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p FIN = 3.01E-05, p ICBP-GWAS = 0.0007, p ALL = 8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="43f4c7accf59a67577e8ca0681d4b49f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066526,"asset_id":35206479,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066526/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206479"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206479"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206479; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206479]").text(description); $(".js-view-count[data-work-id=35206479]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206479; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206479']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "43f4c7accf59a67577e8ca0681d4b49f" } } $('.js-work-strip[data-work-id=35206479]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":35206479,"title":"Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure","internal_url":"https://www.academia.edu/35206479/Intracranial_Aneurysm_Risk_Locus_5q23_2_Is_Associated_with_Elevated_Systolic_Blood_Pressure","owner_id":32256334,"coauthors_can_edit":true,"owner":{"id":32256334,"first_name":"Terho","middle_initials":null,"last_name":"Lehtimäki","page_name":"TerhoLehtimäki","domain_name":"uta-fi","created_at":"2015-06-16T10:56:46.405-07:00","display_name":"Terho Lehtimäki","url":"https://uta-fi.academia.edu/TerhoLehtim%C3%A4ki"},"attachments":[{"id":55066526,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/55066526/thumbnails/1.jpg","file_name":"GaalEI_PLoS_Genet._2012_8.pdf","download_url":"https://www.academia.edu/attachments/55066526/download_file","bulk_download_file_name":"Intracranial_Aneurysm_Risk_Locus_5q23_2.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/55066526/GaalEI_PLoS_Genet._2012_8-libre.pdf?1511246887=\u0026response-content-disposition=attachment%3B+filename%3DIntracranial_Aneurysm_Risk_Locus_5q23_2.pdf\u0026Expires=1740611052\u0026Signature=YPpSruhHIFXjcwXkZzUGYzN1awLch0SNeFBW-FfPjzvHZjHaC0t5VJFIJS135LHoC~vdSJYUBfPm0GRHGsqpCJ6-Lx4F7iTIFmFh6N5xD4K2O6dvl-Vj8sKFoap16Jj89lrrh33gTNxRUoa3sfC8R9VaDr4E7u16m2j198VoYRGs23u0RAbizobl94876DqfsHFAcoyJEEjFME02yTVO8QQWLqsqTAElR0aO-PNPJ6geSApIT8ruFprXnqOfeRLqNBCaKGooZ4O4y7KW3t6hi9IO9p7E8BWoTG-R7UOa~RVBJ1iHuokr8FNFqh--uvJdB0B8yU4RtHWcy6g7OLGViQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206461"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206461/Genome_wide_association_analysis_identifies_susceptibility_loci_for_migraine_without_aura"><img alt="Research paper thumbnail of Genome-wide association analysis identifies susceptibility loci for migraine without aura" class="work-thumbnail" src="https://attachments.academia-assets.com/55066508/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206461/Genome_wide_association_analysis_identifies_susceptibility_loci_for_migraine_without_aura">Genome-wide association analysis identifies susceptibility loci for migraine without aura</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Migraine without aura is the most common form of migraine, characterized by recurrent disabling h...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Migraine without aura is the most common form of migraine, characterized by recurrent disabling headache and associated autonomic symptoms. To identify common genetic variants for this migraine type, we analyzed genome-wide association data of 2,326 clinic-based German and Dutch patients and 4,580 population-matched controls. We selected SNPs from 12 loci with two or more SNPs with P-values < 1 × 10 −5 for follow-up in 2,508 patients and 2,652 controls. Two loci, i.e. 1q22 (MEF2D) and 3p24 (near TGFBR2) replicated convincingly (P = 4.9 × 10 −4 , P = 1.0 × 10 −4 , respectively). Meta-analysis of the discovery and replication data yielded two additional genome-wide significant (P < 5 × 10 −8 ) loci in PHACTR1 and ASTN2. In addition, SNPs in two previously reported migraine loci in or near TRPM8 and LRP1 significantly replicated. This study reveals the first susceptibility loci for migraine without aura, thereby expanding our knowledge of this debilitating neurological disorder.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="07b5f6e49f8db98be06504ee3366305b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066508,"asset_id":35206461,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066508/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206461"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206461"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206461; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206448]").text(description); $(".js-view-count[data-work-id=35206448]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206448; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206448']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206440"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206440/Indoleamine_2_3_Dioxygenase_Activation_and_Depressive_Symptoms_Results_From_the_Young_Finns_Study"><img alt="Research paper thumbnail of Indoleamine 2,3-Dioxygenase Activation and Depressive Symptoms: Results From the Young Finns Study" class="work-thumbnail" src="https://attachments.academia-assets.com/55066487/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206440/Indoleamine_2_3_Dioxygenase_Activation_and_Depressive_Symptoms_Results_From_the_Young_Finns_Study">Indoleamine 2,3-Dioxygenase Activation and Depressive Symptoms: Results From the Young Finns Study</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Objective: To examine whether the activation of indoleamine 2,3-dioxygenase (IDO), an enzyme invo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Objective: To examine whether the activation of indoleamine 2,3-dioxygenase (IDO), an enzyme involved in serotonin production, is associated with depressive symptoms. Methods: The participants were 544 women and 442 men (aged 24Y39 years) from the population-based Young Finns Study who participated in a medical examination in 2001 (including IDO and depression) and 2007 (follow-up assessment for depression). Results: At baseline, IDO was associated with depressive symptoms (in the total cohort: B = 0.23, p G .001; women: B = 0.20, p = .007; men: B = 0.29, p = .002; p for interaction = .19). IDO at baseline was also associated with depressive symptoms at follow-up in women (B = 0.17, p = .03), which remained significant when adjusting for any of the biologic and behavioral risk factors. Adjusting for body mass index attenuated the association by 6%. In the final model including all baseline variables, none of the risk factors (except for baseline depressive symptoms) were associated with depressive symptoms at follow-up. Conclusions: These data suggest that IDO activity may be a risk factor for future depression especially in women. IDO-induced alterations in serotonergic function may offer one biologic explanation to the well-established associations between inflammation and depression. Key words: inflammation, longitudinal, depressive symptoms, serotonin, sex. IDO = indoleamine 2,3-dioxygenase; TRP = tryptophan; KYN = kynurenine; CRP = C-reactive protein; BDI = Beck Depression Inventory; BMI = body mass index.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d5897c7538e97a28473ed5f5788c706c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066487,"asset_id":35206440,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066487/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206440"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206440"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206440; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206429"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206429/Novel_Loci_for_Adiponectin_Levels_and_Their_Influence_on_Type_2_Diabetes_and_Metabolic_Traits_A_Multi_Ethnic_Meta_Analysis_of_45_891_Individuals"><img alt="Research paper thumbnail of Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals" class="work-thumbnail" src="https://attachments.academia-assets.com/55066476/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206429/Novel_Loci_for_Adiponectin_Levels_and_Their_Influence_on_Type_2_Diabetes_and_Metabolic_Traits_A_Multi_Ethnic_Meta_Analysis_of_45_891_Individuals">Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly her...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5610 28 -1.2610 243 ). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p,3610 24 ). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3610 23 , n = 22,044), increased triglycerides (p = 2.6610 214 , n = 93,440), increased waist-to-hip ratio (p = 1.8610 25 , n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4610 23 , n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDLcholesterol concentrations (p = 4.5610 213 , n = 96,748) and decreased BMI (p = 1.4610 24 , n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2835d08140862f7d4c3e162a4dcb7f56" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066476,"asset_id":35206429,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066476/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206429"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206429"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206429; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206407"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206407/A_Genome_Wide_Association_Meta_Analysis_of_Circulating_Sex_Hormone_Binding_Globulin_Reveals_Multiple_Loci_Implicated_in_Sex_Steroid_Hormone_Regulation"><img alt="Research paper thumbnail of A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation" class="work-thumbnail" src="https://attachments.academia-assets.com/55066456/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206407/A_Genome_Wide_Association_Meta_Analysis_of_Circulating_Sex_Hormone_Binding_Globulin_Reveals_Multiple_Loci_Implicated_in_Sex_Steroid_Hormone_Regulation">A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. (rs3779195, 7q21.3, p = 2.7610 208 ), and UGT2B15 (rs293428, 4q13.2, p = 5.5610 206 ). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5610 208 , women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sexdifferentiated or conditional analyses explained ,15.6% and ,8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3623ab2aff805f334ab5de2b99db5dd8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066456,"asset_id":35206407,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066456/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206407"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206407"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206407; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35206392]").text(description); $(".js-view-count[data-work-id=35206392]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35206392; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='35206392']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="35206358"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/35206358/A_genome_wide_association_meta_analysis_identifies_new_childhood_obesity_loci"><img alt="Research paper thumbnail of A genome-wide association meta-analysis identifies new childhood obesity loci" class="work-thumbnail" src="https://attachments.academia-assets.com/55066400/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/35206358/A_genome_wide_association_meta_analysis_identifies_new_childhood_obesity_loci">A genome-wide association meta-analysis identifies new childhood obesity loci</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Multiple genetic variants have been associated with adult obesity and a few with severe obesity i...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made to establish genetic influences on common early-onset obesity. We performed a North American-Australian-European collaborative metaanalysis of fourteen studies consisting of 5,530 cases (≥95 th percentile of body mass index (BMI)) and 8,318 controls (<50 th percentile of BMI) of European ancestry. Taking forward the eight novel signals yielding association with P < 5×10 −6 in to nine independent datasets (n = 2,818 cases and 4,083 controls) we observed two loci that yielded a genome wide significant combined P-value, namely near OLFM4 on 13q14 (rs9568856; P=1.82×10 −9 ; OR=1.22) and within HOXB5 on 17q21 (rs9299; P=3.54×10 −9 ; OR=1.14). Both loci continued to show association when including two extreme childhood obesity cohorts (n = 2,214 cases and 2,674 controls). Finally, these two loci yielded directionally consistent associations in the GIANT meta-analysis of adult BMI 1 .</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5aa5342471079baa88261f2faa4644aa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":55066400,"asset_id":35206358,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/55066400/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="35206358"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="35206358"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35206358; 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