Publications by authors named "Tuomo Rankinen"

162 Publications

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Mol Psychiatry 2021 Apr 15. Epub 2021 Apr 15.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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http://dx.doi.org/10.1038/s41380-021-01087-0DOI Listing
April 2021

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

PLoS One 2020 7;15(5):e0230815. Epub 2020 May 7.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230815PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205201PMC
August 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2021 Jun 5;26(6):2111-2125. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
June 2021

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Nat Commun 2019 11 12;10(1):5121. Epub 2019 Nov 12.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands.

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
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http://dx.doi.org/10.1038/s41467-019-12958-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851116PMC
November 2019

Association of Dimethylguanidino Valeric Acid With Partial Resistance to Metabolic Health Benefits of Regular Exercise.

JAMA Cardiol 2019 07;4(7):636-643

Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

Importance: Metabolic responses to exercise training are variable. Metabolite profiling may aid in the clinical assessment of an individual's responsiveness to exercise interventions.

Objective: To investigate the association between a novel circulating biomarker of hepatic fat, dimethylguanidino valeric acid (DMGV), and metabolic health traits before and after 20 weeks of endurance exercise training.

Design, Setting, And Participants: This study involved cross-sectional and longitudinal analyses of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a 20-week, single-arm endurance exercise clinical trial performed in multiple centers between 1993 and 1997. White participants with sedentary lifestyles who were free of cardiometabolic disease were included. Metabolomic tests were performed using a liquid chromatography, tandem mass spectrometry method on plasma samples collected before and after exercise training in the HERITAGE study. Metabolomics and data analysis were performed from August 2017 to May 2018.

Exposures: Plasma DMGV levels.

Main Outcome And Measures: The association between DMGV levels and measures of body composition, plasma lipids, insulin, and glucose homeostasis before and after exercise training.

Results: Among the 439 participants included in analyses from HERITAGE, the mean (SD) age was 36 (15) years, 228 (51.9%) were female, and the median (interquartile range) body mass index was 25 (22-28). Baseline levels of DMGV were positively associated with body fat percentage, abdominal visceral fat, very low-density lipoprotein cholesterol, and triglycerides, and inversely associated with insulin sensitivity, low-density lipoprotein cholesterol, high-density lipoprotein size, and high-density lipoprotein cholesterol (range of β coefficients, 0.17-0.46 [SEs, 0.026-0.050]; all P < .001, after adjusting for age and sex). After adjusting for age, sex, and baseline traits, baseline DMGV levels were positively associated with changes in small high-density lipoprotein particles (β, 0.14 [95% CI, 0.05-0.23]) and inversely associated with changes in medium and total high-density lipoprotein particles (β, -0.15 [95% CI, -0.24 to -0.05] and -0.19 [95% CI, -0.28 to -0.10], respectively), apolipoprotein A1 (β, -0.14 [95% CI, -0.23 to -0.05]), and insulin sensitivity (β, -0.13; P = 3.0 × 10-3) after exercise training.

Conclusions And Relevance: Dimethylguanidino valeric acid is an early marker of cardiometabolic dysfunction that is associated with attenuated improvements in lipid traits and insulin sensitivity after exercise training. Levels of DMGV may identify individuals who require additional therapies beyond guideline-directed exercise to improve their metabolic health.
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http://dx.doi.org/10.1001/jamacardio.2019.1573DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6551586PMC
July 2019

A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure.

Hum Mol Genet 2019 08;28(15):2615-2633

Icelandic Heart Association, Kopavogur, Iceland.

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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http://dx.doi.org/10.1093/hmg/ddz070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644157PMC
August 2019

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.

Nat Genet 2019 04 29;51(4):636-648. Epub 2019 Mar 29.

Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA.

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
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http://dx.doi.org/10.1038/s41588-019-0378-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467258PMC
April 2019

Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions.

Am J Epidemiol 2019 06;188(6):1033-1054

Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom.

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.
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http://dx.doi.org/10.1093/aje/kwz005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545280PMC
June 2019

LDL triglycerides, hepatic lipase activity, and coronary artery disease: An epidemiologic and Mendelian randomization study.

Atherosclerosis 2019 03 28;282:37-44. Epub 2018 Dec 28.

Mannheim Institute of Public Health, Mannheim Medical Faculty, University of Heidelberg, Ludolf-Krehl-Straße 7-11, 68167, Mannheim, Germany.

Background And Aims: High concentrations of low density lipoprotein (LDL) triglycerides have been associated with prevalent angiographic coronary artery disease. The present analysis was designed to investigate the association of LDL triglycerides with cardiovascular mortality and to explore possible mechanisms that may link LDL triglycerides to cardiovascular risk.

Methods: LDL triglycerides were measured in 3140 participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. They were prospectively followed for cardiovascular mortality (median duration 9.9 years). Genome wide association data for LDL triglycerides were available for 2900 LURIC participants. Genetic data and measurements of hepatic lipase activity were available for 478 participants of the HERITAGE Family study. Genome wide association data for cardiovascular disease were available for 184,305 participants of the CARDIoGRAMplusC4D consortium.

Results: There was a continuous positive association between LDL triglycerides and cardiovascular mortality (hazard ratio for 5th vs. 1st quintile = 2.53, p < 0.001) and this association was similar in males and females. Genome wide association analysis in LURIC revealed that LDL triglycerides were strongly associated with variation in the hepatic lipase region (p < 10 for rs1800588 and rs10468017). The LDL triglyceride raising alleles in rs1800588 and rs10468017 were associated with low hepatic lipase activity in HERITAGE and increased cardiovascular risk in CARDIoGRAMplusC4D. Two-sample Mendelian randomization analysis (HERITAGE and CARDIoGRAMplusC4D) using rs1800588 and rs10468017 as instrumental variable suggested that low hepatic lipase activity may cause increased cardiovascular risk (p = 0.013).

Conclusions: Low hepatic lipase activity may link high LDL triglycerides to increased cardiovascular risk.
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http://dx.doi.org/10.1016/j.atherosclerosis.2018.12.024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6401295PMC
March 2019

Plasma Steroids are Not Associated with Resting and Exercise Blood Pressure.

Int J Sports Med 2018 Dec 5;39(13):967-971. Epub 2018 Oct 5.

Pennington Biomedical Research Center, Human Genomics Laboratory, Baton Rouge, United States.

We investigated the associations between steroid hormones and resting and exercise blood pressure in the sedentary state and in response to an exercise program controlling for sex, body mass, ethnicity, age, oral contraceptives, hormone therapy, smoking and alcohol intake in subjects from the HERITAGE Family Study.: In the sedentary state, 267 men (28% Blacks) and 301 women (37% Blacks) were available, and 241 men and 254 women completed the exercise program. Fourteen steroid hormones and sex hormone-binding globulin concentrations were assayed in a fasted state. Statistical significance was set at a Bonferroni adjusted p<0.0001. After controlling for the various covariates, only testosterone came close to a significant correlation with exercise systolic blood pressure at 50 W (r=-0.21, P=0.0006) in men. No other correlations with resting and exercise blood pressure traits were found at baseline. There were significant changes in blood pressure in response to the exercise program, but none of the correlations with baseline plasma steroids reached statistical significance. Plasma steroids do not correlate with resting and exercise blood pressure in sedentary adults and do not associate with blood pressure changes in response to a 20-week endurance exercise program.
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http://dx.doi.org/10.1055/a-0660-0121DOI Listing
December 2018

Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium.

Mol Psychiatry 2019 12 9;24(12):1920-1932. Epub 2018 Jul 9.

Department of Clinical Chemistry, Fimlab Laboratories, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.
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http://dx.doi.org/10.1038/s41380-018-0079-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326896PMC
December 2019

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

PLoS One 2018 18;13(6):e0198166. Epub 2018 Jun 18.

Icelandic Heart Association, Kopavogur, Iceland.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198166PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005576PMC
January 2019

Plasma steroids, body composition, and fat distribution: effects of age, sex, and exercise training.

Int J Obes (Lond) 2018 07 5;42(7):1366-1377. Epub 2018 Mar 5.

Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA.

Background/objectives: Plasma steroid hormone levels vary between men and women, but their associations with BMI and adiposity are controversial. Furthermore, little is known about the role of exercise programs on the relationship between steroid hormones and adiposity. This report evaluates these relationships for plasma levels of adrenal, gonadal, and conjugated steroids with body composition and fat distribution in sedentary men and women, aged 17-65 years, and their responses to an exercise program.

Subjects/methods: In the sedentary state, 270 men (29% Blacks) and 304 women (34% Blacks) from the HERITAGE Family Study were available. Among them, 242 men and 238 women completed a 20-week fully standardized exercise program. Fourteen steroid hormones and SHBG concentrations were assayed in a fasted state and were compared for their associations with adiposity in men and women and in response to the exercise program. Covariates adjusted for in partial correlation analysis were age, ancestry, menopause status (women), and oral contraceptives/hormone replacement treatment status (women) at baseline, as well as baseline value of the trait for the training response. Differences among normal weight, overweight, and obese subjects were also considered. Statistical significance was set at P < 0.0001.

Results: Baseline levels of dihydrotesterone (DHT), 17 hydroxy progesterone (OHPROG), sex hormone-binding globulin (SHBG), and testosterone (TESTO) were negatively associated with fat mass and abdominal fat (P < 0.0001) in men and for SHBG in women (P < 0.0001). TESTO was not correlated with fat-free mass in men or women, but was significantly associated with % fat-free mass in men. No association was detected between baseline steroid hormone levels and changes in adiposity traits in response to 20 weeks of exercise.

Conclusion: In men, low DHT, OHPROG, SHBG, and TESTO were associated with higher adiposity and abdominal and visceral fat. A similar adiposity profile was observed in women with low SHBG.
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http://dx.doi.org/10.1038/s41366-018-0033-1DOI Listing
July 2018

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

Am J Hum Genet 2018 03 15;102(3):375-400. Epub 2018 Feb 15.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA.

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).
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http://dx.doi.org/10.1016/j.ajhg.2018.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985266PMC
March 2018

Adropin: An endocrine link between the biological clock and cholesterol homeostasis.

Mol Metab 2018 02 30;8:51-64. Epub 2017 Dec 30.

Department of Pharmacology and Physiology, Saint Louis University School of Medicine, Saint Louis University, St. Louis, MO, USA. Electronic address:

Objective: Identify determinants of plasma adropin concentrations, a secreted peptide translated from the Energy Homeostasis Associated (ENHO) gene linked to metabolic control and vascular function.

Methods: Associations between plasma adropin concentrations, demographics (sex, age, BMI) and circulating biomarkers of lipid and glucose metabolism were assessed in plasma obtained after an overnight fast in humans. The regulation of adropin expression was then assessed in silico, in cultured human cells, and in animal models.

Results: In humans, plasma adropin concentrations are inversely related to atherogenic LDL-cholesterol (LDL-C) levels in men (n = 349), but not in women (n = 401). Analysis of hepatic Enho expression in male mice suggests control by the biological clock. Expression is rhythmic, peaking during maximal food consumption in the dark correlating with transcriptional activation by RORα/γ. The nadir in the light phase coincides with the rest phase and repression by Rev-erb. Plasma adropin concentrations in nonhuman primates (rhesus monkeys) also exhibit peaks coinciding with feeding times (07:00 h, 15:00 h). The ROR inverse agonists SR1001 and the 7-oxygenated sterols 7-β-hydroxysterol and 7-ketocholesterol, or the Rev-erb agonist SR9009, suppress ENHO expression in cultured human HepG2 cells. Consumption of high-cholesterol diets suppress expression of the adropin transcript in mouse liver. However, adropin over expression does not prevent hypercholesterolemia resulting from a high cholesterol diet and/or LDL receptor mutations.

Conclusions: In humans, associations between plasma adropin concentrations and LDL-C suggest a link with hepatic lipid metabolism. Mouse studies suggest that the relationship between adropin and cholesterol metabolism is unidirectional, and predominantly involves suppression of adropin expression by cholesterol and 7-oxygenated sterols. Sensing of fatty acids, cholesterol and oxysterols by the RORα/γ ligand-binding domain suggests a plausible functional link between adropin expression and cellular lipid metabolism. Furthermore, the nuclear receptors RORα/γ and Rev-erb may couple adropin synthesis with circadian rhythms in carbohydrate and lipid metabolism.
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http://dx.doi.org/10.1016/j.molmet.2017.12.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985041PMC
February 2018

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

PLoS Genet 2017 Apr 27;13(4):e1006528. Epub 2017 Apr 27.

Estonian Genome Center, University of Tartu, Tartu, Estonia.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
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http://dx.doi.org/10.1371/journal.pgen.1006528DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5407576PMC
April 2017

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Nat Commun 2017 04 26;8:14977. Epub 2017 Apr 26.

Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Australia.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
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http://dx.doi.org/10.1038/ncomms14977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414044PMC
April 2017

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.

Nat Commun 2016 11 23;7:13357. Epub 2016 Nov 23.

Department of Kinesiology, Laval University, Québec, Québec, Canada G1V 0A6.

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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http://dx.doi.org/10.1038/ncomms13357DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114527PMC
November 2016

FTO genotype and weight loss: systematic review and meta-analysis of 9563 individual participant data from eight randomised controlled trials.

BMJ 2016 Sep 20;354:i4707. Epub 2016 Sep 20.

The Miriam Hospital and the Alpert School of Medicine, Brown University, Providence, USA.

Objective:  To assess the effect of the FTO genotype on weight loss after dietary, physical activity, or drug based interventions in randomised controlled trials.

Design:  Systematic review and random effects meta-analysis of individual participant data from randomised controlled trials.

Data Sources:  Ovid Medline, Scopus, Embase, and Cochrane from inception to November 2015.

Eligibility Criteria For Study Selection:  Randomised controlled trials in overweight or obese adults reporting reduction in body mass index, body weight, or waist circumference by FTO genotype (rs9939609 or a proxy) after dietary, physical activity, or drug based interventions. Gene by treatment interaction models were fitted to individual participant data from all studies included in this review, using allele dose coding for genetic effects and a common set of covariates. Study level interactions were combined using random effect models. Metaregression and subgroup analysis were used to assess sources of study heterogeneity.

Results:  We identified eight eligible randomised controlled trials for the systematic review and meta-analysis (n=9563). Overall, differential changes in body mass index, body weight, and waist circumference in response to weight loss intervention were not significantly different between FTO genotypes. Sensitivity analyses indicated that differential changes in body mass index, body weight, and waist circumference by FTO genotype did not differ by intervention type, intervention length, ethnicity, sample size, sex, and baseline body mass index and age category.

Conclusions:  We have observed that carriage of the FTO minor allele was not associated with differential change in adiposity after weight loss interventions. These findings show that individuals carrying the minor allele respond equally well to dietary, physical activity, or drug based weight loss interventions and thus genetic predisposition to obesity associated with the FTO minor allele can be at least partly counteracted through such interventions.

Systematic Review Registration:  PROSPERO CRD42015015969.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168036PMC
http://dx.doi.org/10.1136/bmj.i4707DOI Listing
September 2016

An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group.

Genet Epidemiol 2016 07 27;40(5):404-15. Epub 2016 May 27.

Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom.

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.
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http://dx.doi.org/10.1002/gepi.21978DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911246PMC
July 2016

Advances in Exercise, Fitness, and Performance Genomics in 2015.

Med Sci Sports Exerc 2016 10;48(10):1906-16

1Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC; 2The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY; 3Universidad Europea and Research Institute, Hospital 12 de Octubre (i+12), Madrid, SPAIN; 4Faculty of Medicine, Department of Kinesiology, Laval University, Ste-Foy, Québec, CANADA; 5Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD; 6Department of Sport Medicine, Humboldt University and Charité University School of Medicine, Berlin, GERMANY; and 7Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA.

This review of the exercise genomics literature encompasses the highest-quality articles published in 2015 across seven broad topics: physical activity behavior, muscular strength and power, cardiorespiratory fitness and endurance performance, body weight and adiposity, insulin and glucose metabolism, lipid and lipoprotein metabolism, and hemodynamic traits. One study used a quantitative trait locus for wheel running in mice to identify single nucleotide polymorphisms (SNPs) in humans associated with physical activity levels. Two studies examined the association of candidate gene ACTN3 R577X genotype on muscular performance. Several studies examined gene-physical activity interactions on cardiometabolic traits. One study showed that physical inactivity exacerbated the body mass index (BMI)-increasing effect of an FTO SNP but only in individuals of European ancestry, whereas another showed that high-density lipoprotein cholesterol (HDL-C) SNPs from genome-wide association studies exerted a smaller effect in active individuals. Increased levels of moderate-to-vigorous-intensity physical activity were associated with higher Matsuda insulin sensitivity index in PPARG Ala12 carriers but not Pro12 homozygotes. One study combined genome-wide and transcriptome-wide profiling to identify genes and SNPs associated with the response of triglycerides (TG) to exercise training. The genome-wide association study results showed that four SNPs accounted for all of the heritability of △TG, whereas the baseline expression of 11 genes predicted 27% of △TG. A composite SNP score based on the top eight SNPs derived from the genomic and transcriptomic analyses was the strongest predictor of ΔTG, explaining 14% of the variance. The review concludes with a discussion of a conceptual framework defining some of the critical conditions for exercise genomics studies and highlights the importance of the recently launched National Institutes of Health Common Fund program titled "Molecular Transducers of Physical Activity in Humans."
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http://dx.doi.org/10.1249/MSS.0000000000000982DOI Listing
October 2016

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk.

Nat Commun 2016 Feb 1;7:10495. Epub 2016 Feb 1.

Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK.

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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http://dx.doi.org/10.1038/ncomms10495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740398PMC
February 2016

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Nat Commun 2016 Feb 1;7:10494. Epub 2016 Feb 1.

Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachussetts 02215, USA.

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
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http://dx.doi.org/10.1038/ncomms10494DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740377PMC
February 2016

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

PLoS One 2016 29;11(1):e0147330. Epub 2016 Jan 29.

MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdom.

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147330PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732768PMC
July 2016

The effects of exercise on the lipoprotein subclass profile: A meta-analysis of 10 interventions.

Atherosclerosis 2015 Dec 17;243(2):364-72. Epub 2015 Oct 17.

Pennington Biomedical Research Center, Baton Rouge, LA, USA.

Objective: The goal was to examine lipoprotein subclass responses to regular exercise as measured in 10 exercise interventions derived from six cohorts.

Methods: Nuclear magnetic resonance spectroscopy was used to quantify average particle size, total and subclass concentrations of very low-density lipoprotein, low-density lipoprotein, and high-density lipoprotein particles (VLDL-P, LDL-P, and HDL-P, respectively) before and after an exercise intervention in 1555 adults from six studies, encompassing 10 distinct exercise programs: APOE (N = 106), DREW (N = 385), GERS (N = 79), HERITAGE (N = 715), STRRIDE I (N = 168) and II (N = 102). Random-effects meta-analyses were performed to evaluate the overall estimate of mean change across the unadjusted and adjusted mean change values from each exercise group.

Results: Meta-analysis of unadjusted data showed that regular exercise induced significant decreases in the concentration of large VLDL-P, small LDL-P, and medium HDL-P and mean VLDL-P size, with significant increases in the concentration of large LDL-P and large HDL-P and mean LDL-P size. These changes remained significant in meta-analysis with adjustment for age, sex, race, baseline body mass index, and baseline trait value.

Conclusions: Despite differences in exercise programs and study populations, regular exercise produced putatively beneficial changes in the lipoprotein subclass profile across 10 exercise interventions. Further research is needed to examine how exercise-induced changes in lipoprotein subclasses may be associated with (concomitant changes in) cardiovascular disease risk.
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http://dx.doi.org/10.1016/j.atherosclerosis.2015.10.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663138PMC
December 2015

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

PLoS Genet 2015 Oct 1;11(10):e1005378. Epub 2015 Oct 1.

HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
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http://dx.doi.org/10.1371/journal.pgen.1005378DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4591371PMC
October 2015

Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors?

Circ Res 2015 Feb;116(5):909-22

From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore.

Clustering of obesity, coronary artery disease, and cardiovascular disease risk factors is observed in epidemiological studies and clinical settings. Twin and family studies have provided some supporting evidence for the clustering hypothesis. Loci nearest a lead single nucleotide polymorphism (SNP) showing genome-wide significant associations with coronary artery disease, body mass index, C-reactive protein, blood pressure, lipids, and type 2 diabetes mellitus were selected for pathway and network analyses. Eighty-seven autosomal regions (181 SNPs), mapping to 56 genes, were found to be pleiotropic. Most pleiotropic regions contained genes associated with coronary artery disease and plasma lipids, whereas some exhibited coaggregation between obesity and cardiovascular disease risk factors. We observed enrichment for liver X receptor (LXR)/retinoid X receptor (RXR) and farnesoid X receptor/RXR nuclear receptor signaling among pleiotropic genes and for signatures of coronary artery disease and hepatic steatosis. In the search for functionally interacting networks, we found that 43 pleiotropic genes were interacting in a network with an additional 24 linker genes. ENCODE (Encyclopedia of DNA Elements) data were queried for distribution of pleiotropic SNPs among regulatory elements and coding sequence variations. Of the 181 SNPs, 136 were annotated to ≥ 1 regulatory feature. An enrichment analysis found over-representation of enhancers and DNAse hypersensitive regions when compared against all SNPs of the 1000 Genomes pilot project. In summary, there are genomic regions exerting pleiotropic effects on cardiovascular disease risk factors, although only a few included obesity. Further studies are needed to resolve the clustering in terms of DNA variants, genes, pathways, and actionable targets.
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http://dx.doi.org/10.1161/CIRCRESAHA.116.302888DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4416656PMC
February 2015
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