%0 Journal Article %J Diabetes Care %D 2010 %T Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies. %A Nettleton, Jennifer A %A McKeown, Nicola M %A Kanoni, Stavroula %A Lemaitre, Rozenn N %A Hivert, Marie-France %A Ngwa, Julius %A van Rooij, Frank J A %A Sonestedt, Emily %A Wojczynski, Mary K %A Ye, Zheng %A Tanaka, Tosh %A Garcia, Melissa %A Anderson, Jennifer S %A Follis, Jack L %A Djoussé, Luc %A Mukamal, Kenneth %A Papoutsakis, Constantina %A Mozaffarian, Dariush %A Zillikens, M Carola %A Bandinelli, Stefania %A Bennett, Amanda J %A Borecki, Ingrid B %A Feitosa, Mary F %A Ferrucci, Luigi %A Forouhi, Nita G %A Groves, Christopher J %A Hallmans, Göran %A Harris, Tamara %A Hofman, Albert %A Houston, Denise K %A Hu, Frank B %A Johansson, Ingegerd %A Kritchevsky, Stephen B %A Langenberg, Claudia %A Launer, Lenore %A Liu, Yongmei %A Loos, Ruth J %A Nalls, Michael %A Orho-Melander, Marju %A Renstrom, Frida %A Rice, Kenneth %A Riserus, Ulf %A Rolandsson, Olov %A Rotter, Jerome I %A Saylor, Georgia %A Sijbrands, Eric J G %A Sjogren, Per %A Smith, Albert %A Steingrímsdóttir, Laufey %A Uitterlinden, André G %A Wareham, Nicholas J %A Prokopenko, Inga %A Pankow, James S %A van Duijn, Cornelia M %A Florez, Jose C %A Witteman, Jacqueline C M %A Dupuis, Josée %A Dedoussis, George V %A Ordovas, Jose M %A Ingelsson, Erik %A Cupples, L Adrienne %A Siscovick, David S %A Franks, Paul W %A Meigs, James B %K Adult %K Aged %K Blood Glucose %K Edible Grain %K European Continental Ancestry Group %K Fasting %K Female %K Genetic Loci %K Genome-Wide Association Study %K Genotype %K Humans %K Insulin %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %X

OBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.

RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.

RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.

CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

%B Diabetes Care %V 33 %P 2684-91 %8 2010 Dec %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/20693352?dopt=Abstract %R 10.2337/dc10-1150 %0 Journal Article %J Diabetes %D 2011 %T Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis. %A Kanoni, Stavroula %A Nettleton, Jennifer A %A Hivert, Marie-France %A Ye, Zheng %A van Rooij, Frank J A %A Shungin, Dmitry %A Sonestedt, Emily %A Ngwa, Julius S %A Wojczynski, Mary K %A Lemaitre, Rozenn N %A Gustafsson, Stefan %A Anderson, Jennifer S %A Tanaka, Toshiko %A Hindy, George %A Saylor, Georgia %A Renstrom, Frida %A Bennett, Amanda J %A van Duijn, Cornelia M %A Florez, Jose C %A Fox, Caroline S %A Hofman, Albert %A Hoogeveen, Ron C %A Houston, Denise K %A Hu, Frank B %A Jacques, Paul F %A Johansson, Ingegerd %A Lind, Lars %A Liu, Yongmei %A McKeown, Nicola %A Ordovas, Jose %A Pankow, James S %A Sijbrands, Eric J G %A Syvänen, Ann-Christine %A Uitterlinden, André G %A Yannakoulia, Mary %A Zillikens, M Carola %A Wareham, Nick J %A Prokopenko, Inga %A Bandinelli, Stefania %A Forouhi, Nita G %A Cupples, L Adrienne %A Loos, Ruth J %A Hallmans, Göran %A Dupuis, Josée %A Langenberg, Claudia %A Ferrucci, Luigi %A Kritchevsky, Stephen B %A McCarthy, Mark I %A Ingelsson, Erik %A Borecki, Ingrid B %A Witteman, Jacqueline C M %A Orho-Melander, Marju %A Siscovick, David S %A Meigs, James B %A Franks, Paul W %A Dedoussis, George V %K Blood Glucose %K Cation Transport Proteins %K Cohort Studies %K Humans %K Polymorphism, Single Nucleotide %K Zinc %K Zinc Transporter 8 %X

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.

RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.

RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.

CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

%B Diabetes %V 60 %P 2407-16 %8 2011 Sep %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/21810599?dopt=Abstract %R 10.2337/db11-0176 %0 Journal Article %J PLoS Genet %D 2013 %T Genome-wide association of body fat distribution in African ancestry populations suggests new loci. %A Liu, Ching-Ti %A Monda, Keri L %A Taylor, Kira C %A Lange, Leslie %A Demerath, Ellen W %A Palmas, Walter %A Wojczynski, Mary K %A Ellis, Jaclyn C %A Vitolins, Mara Z %A Liu, Simin %A Papanicolaou, George J %A Irvin, Marguerite R %A Xue, Luting %A Griffin, Paula J %A Nalls, Michael A %A Adeyemo, Adebowale %A Liu, Jiankang %A Li, Guo %A Ruiz-Narvaez, Edward A %A Chen, Wei-Min %A Chen, Fang %A Henderson, Brian E %A Millikan, Robert C %A Ambrosone, Christine B %A Strom, Sara S %A Guo, Xiuqing %A Andrews, Jeanette S %A Sun, Yan V %A Mosley, Thomas H %A Yanek, Lisa R %A Shriner, Daniel %A Haritunians, Talin %A Rotter, Jerome I %A Speliotes, Elizabeth K %A Smith, Megan %A Rosenberg, Lynn %A Mychaleckyj, Josyf %A Nayak, Uma %A Spruill, Ida %A Garvey, W Timothy %A Pettaway, Curtis %A Nyante, Sarah %A Bandera, Elisa V %A Britton, Angela F %A Zonderman, Alan B %A Rasmussen-Torvik, Laura J %A Chen, Yii-Der Ida %A Ding, Jingzhong %A Lohman, Kurt %A Kritchevsky, Stephen B %A Zhao, Wei %A Peyser, Patricia A %A Kardia, Sharon L R %A Kabagambe, Edmond %A Broeckel, Ulrich %A Chen, Guanjie %A Zhou, Jie %A Wassertheil-Smoller, Sylvia %A Neuhouser, Marian L %A Rampersaud, Evadnie %A Psaty, Bruce %A Kooperberg, Charles %A Manson, JoAnn E %A Kuller, Lewis H %A Ochs-Balcom, Heather M %A Johnson, Karen C %A Sucheston, Lara %A Ordovas, Jose M %A Palmer, Julie R %A Haiman, Christopher A %A McKnight, Barbara %A Howard, Barbara V %A Becker, Diane M %A Bielak, Lawrence F %A Liu, Yongmei %A Allison, Matthew A %A Grant, Struan F A %A Burke, Gregory L %A Patel, Sanjay R %A Schreiner, Pamela J %A Borecki, Ingrid B %A Evans, Michele K %A Taylor, Herman %A Sale, Michèle M %A Howard, Virginia %A Carlson, Christopher S %A Rotimi, Charles N %A Cushman, Mary %A Harris, Tamara B %A Reiner, Alexander P %A Cupples, L Adrienne %A North, Kari E %A Fox, Caroline S %K Adiposity %K African Continental Ancestry Group %K Body Fat Distribution %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Obesity %K Polymorphism, Single Nucleotide %K Waist-Hip Ratio %X

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 × 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.

%B PLoS Genet %V 9 %P e1003681 %8 2013 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/23966867?dopt=Abstract %R 10.1371/journal.pgen.1003681 %0 Journal Article %J Am J Clin Nutr %D 2013 %T Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. %A Tanaka, Toshiko %A Ngwa, Julius S %A van Rooij, Frank J A %A Zillikens, M Carola %A Wojczynski, Mary K %A Frazier-Wood, Alexis C %A Houston, Denise K %A Kanoni, Stavroula %A Lemaitre, Rozenn N %A Luan, Jian'an %A Mikkilä, Vera %A Renstrom, Frida %A Sonestedt, Emily %A Zhao, Jing Hua %A Chu, Audrey Y %A Qi, Lu %A Chasman, Daniel I %A de Oliveira Otto, Marcia C %A Dhurandhar, Emily J %A Feitosa, Mary F %A Johansson, Ingegerd %A Khaw, Kay-Tee %A Lohman, Kurt K %A Manichaikul, Ani %A McKeown, Nicola M %A Mozaffarian, Dariush %A Singleton, Andrew %A Stirrups, Kathleen %A Viikari, Jorma %A Ye, Zheng %A Bandinelli, Stefania %A Barroso, Inês %A Deloukas, Panos %A Forouhi, Nita G %A Hofman, Albert %A Liu, Yongmei %A Lyytikäinen, Leo-Pekka %A North, Kari E %A Dimitriou, Maria %A Hallmans, Göran %A Kähönen, Mika %A Langenberg, Claudia %A Ordovas, Jose M %A Uitterlinden, André G %A Hu, Frank B %A Kalafati, Ioanna-Panagiota %A Raitakari, Olli %A Franco, Oscar H %A Johnson, Andrew %A Emilsson, Valur %A Schrack, Jennifer A %A Semba, Richard D %A Siscovick, David S %A Arnett, Donna K %A Borecki, Ingrid B %A Franks, Paul W %A Kritchevsky, Stephen B %A Lehtimäki, Terho %A Loos, Ruth J F %A Orho-Melander, Marju %A Rotter, Jerome I %A Wareham, Nicholas J %A Witteman, Jacqueline C M %A Ferrucci, Luigi %A Dedoussis, George %A Cupples, L Adrienne %A Nettleton, Jennifer A %K Alleles %K Atherosclerosis %K Body Mass Index %K Dietary Carbohydrates %K Dietary Fats %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Fibroblast Growth Factors %K Follow-Up Studies %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Life Style %K Obesity %K Polymorphism, Single Nucleotide %K Prospective Studies %K Quantitative Trait Loci %K Surveys and Questionnaires %X

BACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.

OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.

DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.

RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)).

CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

%B Am J Clin Nutr %V 97 %P 1395-402 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23636237?dopt=Abstract %R 10.3945/ajcn.112.052183 %0 Journal Article %J J Nutr %D 2013 %T Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies. %A Hruby, Adela %A Ngwa, Julius S %A Renstrom, Frida %A Wojczynski, Mary K %A Ganna, Andrea %A Hallmans, Göran %A Houston, Denise K %A Jacques, Paul F %A Kanoni, Stavroula %A Lehtimäki, Terho %A Lemaitre, Rozenn N %A Manichaikul, Ani %A North, Kari E %A Ntalla, Ioanna %A Sonestedt, Emily %A Tanaka, Toshiko %A van Rooij, Frank J A %A Bandinelli, Stefania %A Djoussé, Luc %A Grigoriou, Efi %A Johansson, Ingegerd %A Lohman, Kurt K %A Pankow, James S %A Raitakari, Olli T %A Riserus, Ulf %A Yannakoulia, Mary %A Zillikens, M Carola %A Hassanali, Neelam %A Liu, Yongmei %A Mozaffarian, Dariush %A Papoutsakis, Constantina %A Syvänen, Ann-Christine %A Uitterlinden, André G %A Viikari, Jorma %A Groves, Christopher J %A Hofman, Albert %A Lind, Lars %A McCarthy, Mark I %A Mikkilä, Vera %A Mukamal, Kenneth %A Franco, Oscar H %A Borecki, Ingrid B %A Cupples, L Adrienne %A Dedoussis, George V %A Ferrucci, Luigi %A Hu, Frank B %A Ingelsson, Erik %A Kähönen, Mika %A Kao, W H Linda %A Kritchevsky, Stephen B %A Orho-Melander, Marju %A Prokopenko, Inga %A Rotter, Jerome I %A Siscovick, David S %A Witteman, Jacqueline C M %A Franks, Paul W %A Meigs, James B %A McKeown, Nicola M %A Nettleton, Jennifer A %K Blood Glucose %K Female %K Genetic Loci %K Humans %K Insulin %K Magnesium %K Male %K Polymorphism, Single Nucleotide %K Trace Elements %K TRPM Cation Channels %X

Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.

%B J Nutr %V 143 %P 345-53 %8 2013 Mar %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/23343670?dopt=Abstract %R 10.3945/jn.112.172049 %0 Journal Article %J Nat Genet %D 2013 %T A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. %A Monda, Keri L %A Chen, Gary K %A Taylor, Kira C %A Palmer, Cameron %A Edwards, Todd L %A Lange, Leslie A %A Ng, Maggie C Y %A Adeyemo, Adebowale A %A Allison, Matthew A %A Bielak, Lawrence F %A Chen, Guanjie %A Graff, Mariaelisa %A Irvin, Marguerite R %A Rhie, Suhn K %A Li, Guo %A Liu, Yongmei %A Liu, Youfang %A Lu, Yingchang %A Nalls, Michael A %A Sun, Yan V %A Wojczynski, Mary K %A Yanek, Lisa R %A Aldrich, Melinda C %A Ademola, Adeyinka %A Amos, Christopher I %A Bandera, Elisa V %A Bock, Cathryn H %A Britton, Angela %A Broeckel, Ulrich %A Cai, Quiyin %A Caporaso, Neil E %A Carlson, Chris S %A Carpten, John %A Casey, Graham %A Chen, Wei-Min %A Chen, Fang %A Chen, Yii-der I %A Chiang, Charleston W K %A Coetzee, Gerhard A %A Demerath, Ellen %A Deming-Halverson, Sandra L %A Driver, Ryan W %A Dubbert, Patricia %A Feitosa, Mary F %A Feng, Ye %A Freedman, Barry I %A Gillanders, Elizabeth M %A Gottesman, Omri %A Guo, Xiuqing %A Haritunians, Talin %A Harris, Tamara %A Harris, Curtis C %A Hennis, Anselm J M %A Hernandez, Dena G %A McNeill, Lorna H %A Howard, Timothy D %A Howard, Barbara V %A Howard, Virginia J %A Johnson, Karen C %A Kang, Sun J %A Keating, Brendan J %A Kolb, Suzanne %A Kuller, Lewis H %A Kutlar, Abdullah %A Langefeld, Carl D %A Lettre, Guillaume %A Lohman, Kurt %A Lotay, Vaneet %A Lyon, Helen %A Manson, JoAnn E %A Maixner, William %A Meng, Yan A %A Monroe, Kristine R %A Morhason-Bello, Imran %A Murphy, Adam B %A Mychaleckyj, Josyf C %A Nadukuru, Rajiv %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Wu, Suh-Yuh %A Leske, M Cristina %A Neslund-Dudas, Christine %A Neuhouser, Marian %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogunniyi, Adesola %A Ogundiran, Temidayo O %A Ojengbede, Oladosu %A Olopade, Olufunmilayo I %A Palmer, Julie R %A Ruiz-Narvaez, Edward A %A Palmer, Nicholette D %A Press, Michael F %A Rampersaud, Evandine %A Rasmussen-Torvik, Laura J %A Rodriguez-Gil, Jorge L %A Salako, Babatunde %A Schadt, Eric E %A Schwartz, Ann G %A Shriner, Daniel A %A Siscovick, David %A Smith, Shad B %A Wassertheil-Smoller, Sylvia %A Speliotes, Elizabeth K %A Spitz, Margaret R %A Sucheston, Lara %A Taylor, Herman %A Tayo, Bamidele O %A Tucker, Margaret A %A Van Den Berg, David J %A Edwards, Digna R Velez %A Wang, Zhaoming %A Wiencke, John K %A Winkler, Thomas W %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yang, James J %A Levin, Albert M %A Young, Taylor R %A Zakai, Neil A %A Cushman, Mary %A Zanetti, Krista A %A Zhao, Jing Hua %A Zhao, Wei %A Zheng, Yonglan %A Zhou, Jie %A Ziegler, Regina G %A Zmuda, Joseph M %A Fernandes, Jyotika K %A Gilkeson, Gary S %A Kamen, Diane L %A Hunt, Kelly J %A Spruill, Ida J %A Ambrosone, Christine B %A Ambs, Stefan %A Arnett, Donna K %A Atwood, Larry %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Blot, William J %A Borecki, Ingrid B %A Bottinger, Erwin P %A Bowden, Donald W %A Burke, Gregory %A Chanock, Stephen J %A Cooper, Richard S %A Ding, Jingzhong %A Duggan, David %A Evans, Michele K %A Fox, Caroline %A Garvey, W Timothy %A Bradfield, Jonathan P %A Hakonarson, Hakon %A Grant, Struan F A %A Hsing, Ann %A Chu, Lisa %A Hu, Jennifer J %A Huo, Dezheng %A Ingles, Sue A %A John, Esther M %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kardia, Sharon L R %A Kittles, Rick A %A Goodman, Phyllis J %A Klein, Eric A %A Kolonel, Laurence N %A Le Marchand, Loïc %A Liu, Simin %A McKnight, Barbara %A Millikan, Robert C %A Mosley, Thomas H %A Padhukasahasram, Badri %A Williams, L Keoki %A Patel, Sanjay R %A Peters, Ulrike %A Pettaway, Curtis A %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Rotimi, Charles N %A Rybicki, Benjamin A %A Sale, Michèle M %A Schreiner, Pamela J %A Signorello, Lisa B %A Singleton, Andrew B %A Stanford, Janet L %A Strom, Sara S %A Thun, Michael J %A Vitolins, Mara %A Zheng, Wei %A Moore, Jason H %A Williams, Scott M %A Ketkar, Shamika %A Zhu, Xiaofeng %A Zonderman, Alan B %A Kooperberg, Charles %A Papanicolaou, George J %A Henderson, Brian E %A Reiner, Alex P %A Hirschhorn, Joel N %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %K African Americans %K Body Mass Index %K Case-Control Studies %K Gene Frequency %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Obesity %K Polymorphism, Single Nucleotide %X

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

%B Nat Genet %V 45 %P 690-6 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23583978?dopt=Abstract %R 10.1038/ng.2608 %0 Journal Article %J Hum Mol Genet %D 2014 %T FTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals. %A Qi, Qibin %A Kilpeläinen, Tuomas O %A Downer, Mary K %A Tanaka, Toshiko %A Smith, Caren E %A Sluijs, Ivonne %A Sonestedt, Emily %A Chu, Audrey Y %A Renstrom, Frida %A Lin, Xiaochen %A Ängquist, Lars H %A Huang, Jinyan %A Liu, Zhonghua %A Li, Yanping %A Asif Ali, Muhammad %A Xu, Min %A Ahluwalia, Tarunveer Singh %A Boer, Jolanda M A %A Chen, Peng %A Daimon, Makoto %A Eriksson, Johan %A Perola, Markus %A Friedlander, Yechiel %A Gao, Yu-Tang %A Heppe, Denise H M %A Holloway, John W %A Houston, Denise K %A Kanoni, Stavroula %A Kim, Yu-Mi %A Laaksonen, Maarit A %A Jääskeläinen, Tiina %A Lee, Nanette R %A Lehtimäki, Terho %A Lemaitre, Rozenn N %A Lu, Wei %A Luben, Robert N %A Manichaikul, Ani %A Männistö, Satu %A Marques-Vidal, Pedro %A Monda, Keri L %A Ngwa, Julius S %A Perusse, Louis %A van Rooij, Frank J A %A Xiang, Yong-Bing %A Wen, Wanqing %A Wojczynski, Mary K %A Zhu, Jingwen %A Borecki, Ingrid B %A Bouchard, Claude %A Cai, Qiuyin %A Cooper, Cyrus %A Dedoussis, George V %A Deloukas, Panos %A Ferrucci, Luigi %A Forouhi, Nita G %A Hansen, Torben %A Christiansen, Lene %A Hofman, Albert %A Johansson, Ingegerd %A Jørgensen, Torben %A Karasawa, Shigeru %A Khaw, Kay-Tee %A Kim, Mi-Kyung %A Kristiansson, Kati %A Li, Huaixing %A Lin, Xu %A Liu, Yongmei %A Lohman, Kurt K %A Long, Jirong %A Mikkilä, Vera %A Mozaffarian, Dariush %A North, Kari %A Pedersen, Oluf %A Raitakari, Olli %A Rissanen, Harri %A Tuomilehto, Jaakko %A van der Schouw, Yvonne T %A Uitterlinden, André G %A Zillikens, M Carola %A Franco, Oscar H %A Shyong Tai, E %A Ou Shu, Xiao %A Siscovick, David S %A Toft, Ulla %A Verschuren, W M Monique %A Vollenweider, Peter %A Wareham, Nicholas J %A Witteman, Jacqueline C M %A Zheng, Wei %A Ridker, Paul M %A Kang, Jae H %A Liang, Liming %A Jensen, Majken K %A Curhan, Gary C %A Pasquale, Louis R %A Hunter, David J %A Mohlke, Karen L %A Uusitupa, Matti %A Cupples, L Adrienne %A Rankinen, Tuomo %A Orho-Melander, Marju %A Wang, Tao %A Chasman, Daniel I %A Franks, Paul W %A Sørensen, Thorkild I A %A Hu, Frank B %A Loos, Ruth J F %A Nettleton, Jennifer A %A Qi, Lu %K Adult %K African Americans %K Aged %K Alleles %K Asian Continental Ancestry Group %K Body Mass Index %K Dietary Carbohydrates %K Dietary Fats %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Female %K Gene Frequency %K Humans %K Male %K Middle Aged %K Obesity %K Polymorphism, Single Nucleotide %K Proteins %X

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 × 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 × 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.

%B Hum Mol Genet %V 23 %P 6961-72 %8 2014 Dec 20 %G eng %N 25 %1 http://www.ncbi.nlm.nih.gov/pubmed/25104851?dopt=Abstract %R 10.1093/hmg/ddu411 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T Sequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. %A Liu, Ching-Ti %A Young, Kristin L %A Brody, Jennifer A %A Olden, Matthias %A Wojczynski, Mary K %A Heard-Costa, Nancy %A Li, Guo %A Morrison, Alanna C %A Muzny, Donna %A Gibbs, Richard A %A Reid, Jeffrey G %A Shao, Yaming %A Zhou, Yanhua %A Boerwinkle, Eric %A Heiss, Gerardo %A Wagenknecht, Lynne %A McKnight, Barbara %A Borecki, Ingrid B %A Fox, Caroline S %A North, Kari E %A Cupples, L Adrienne %K Adult %K Aged %K Aging %K Body Mass Index %K Cohort Studies %K Female %K Genetic Association Studies %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Heart Diseases %K Humans %K Male %K Membrane Proteins %K Middle Aged %K Polymorphism, Single Nucleotide %K Sequence Analysis, DNA %K Young Adult %X

BACKGROUND: Genome-wide association studies for body mass index (BMI) previously identified a locus near TMEM18. We conducted targeted sequencing of this region to investigate the role of common, low-frequency, and rare variants influencing BMI.

METHODS AND RESULTS: We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from 3 community-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, and Framingham Heart Study), including 200 adults selected for high BMI. We examined the association between BMI and variants identified in the region from nucleotide position 586 432 to 677 539 (hg18). Rare variants (minor allele frequency, <1%) were analyzed using a burden test and the sequence kernel association test. Results from the 3 cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m(2) higher for each copy of the G allele of single-nucleotide polymorphism rs7596758 (minor allele frequency, 29%; P=3.46×10(-4)) using a Bonferroni threshold of P<4.6×10(-4). Analyses conditional on previous genome-wide association study single-nucleotide polymorphisms associated with BMI in the region led to attenuation of this signal and uncovered another independent (r(2)<0.2), statistically significant association, rs186019316 (P=2.11×10(-4)). Both rs186019316 and rs7596758 or proxies are located in transcription factor binding regions. No significant association with rare variants was found in either the exons of TMEM18 or the 3' genome-wide association study region.

CONCLUSIONS: Targeted sequencing around TMEM18 identified 2 novel BMI variants with possible regulatory function.

%B Circ Cardiovasc Genet %V 7 %P 344-9 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24951660?dopt=Abstract %R 10.1161/CIRCGENETICS.13.000067 %0 Journal Article %J Am J Clin Nutr %D 2015 %T Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. %A Fretts, Amanda M %A Follis, Jack L %A Nettleton, Jennifer A %A Lemaitre, Rozenn N %A Ngwa, Julius S %A Wojczynski, Mary K %A Kalafati, Ioanna Panagiota %A Varga, Tibor V %A Frazier-Wood, Alexis C %A Houston, Denise K %A Lahti, Jari %A Ericson, Ulrika %A van den Hooven, Edith H %A Mikkilä, Vera %A Kiefte-de Jong, Jessica C %A Mozaffarian, Dariush %A Rice, Kenneth %A Renstrom, Frida %A North, Kari E %A McKeown, Nicola M %A Feitosa, Mary F %A Kanoni, Stavroula %A Smith, Caren E %A Garcia, Melissa E %A Tiainen, Anna-Maija %A Sonestedt, Emily %A Manichaikul, Ani %A van Rooij, Frank J A %A Dimitriou, Maria %A Raitakari, Olli %A Pankow, James S %A Djoussé, Luc %A Province, Michael A %A Hu, Frank B %A Lai, Chao-Qiang %A Keller, Margaux F %A Perälä, Mia-Maria %A Rotter, Jerome I %A Hofman, Albert %A Graff, Misa %A Kähönen, Mika %A Mukamal, Kenneth %A Johansson, Ingegerd %A Ordovas, Jose M %A Liu, Yongmei %A Männistö, Satu %A Uitterlinden, André G %A Deloukas, Panos %A Seppälä, Ilkka %A Psaty, Bruce M %A Cupples, L Adrienne %A Borecki, Ingrid B %A Franks, Paul W %A Arnett, Donna K %A Nalls, Mike A %A Eriksson, Johan G %A Orho-Melander, Marju %A Franco, Oscar H %A Lehtimäki, Terho %A Dedoussis, George V %A Meigs, James B %A Siscovick, David S %K Blood Glucose %K Cohort Studies %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hyperglycemia %K Hyperinsulinism %K Insulin %K Insulin Resistance %K Insulin-Secreting Cells %K Meat %K Meat Products %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %X

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

%B Am J Clin Nutr %V 102 %P 1266-78 %8 2015 Nov %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/26354543?dopt=Abstract %R 10.3945/ajcn.114.101238 %0 Journal Article %J Hum Mol Genet %D 2015 %T Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. %A Nettleton, Jennifer A %A Follis, Jack L %A Ngwa, Julius S %A Smith, Caren E %A Ahmad, Shafqat %A Tanaka, Toshiko %A Wojczynski, Mary K %A Voortman, Trudy %A Lemaitre, Rozenn N %A Kristiansson, Kati %A Nuotio, Marja-Liisa %A Houston, Denise K %A Perälä, Mia-Maria %A Qi, Qibin %A Sonestedt, Emily %A Manichaikul, Ani %A Kanoni, Stavroula %A Ganna, Andrea %A Mikkilä, Vera %A North, Kari E %A Siscovick, David S %A Harald, Kennet %A McKeown, Nicola M %A Johansson, Ingegerd %A Rissanen, Harri %A Liu, Yongmei %A Lahti, Jari %A Hu, Frank B %A Bandinelli, Stefania %A Rukh, Gull %A Rich, Stephen %A Booij, Lisanne %A Dmitriou, Maria %A Ax, Erika %A Raitakari, Olli %A Mukamal, Kenneth %A Männistö, Satu %A Hallmans, Göran %A Jula, Antti %A Ericson, Ulrika %A Jacobs, David R %A van Rooij, Frank J A %A Deloukas, Panos %A Sjogren, Per %A Kähönen, Mika %A Djoussé, Luc %A Perola, Markus %A Barroso, Inês %A Hofman, Albert %A Stirrups, Kathleen %A Viikari, Jorma %A Uitterlinden, André G %A Kalafati, Ioanna P %A Franco, Oscar H %A Mozaffarian, Dariush %A Salomaa, Veikko %A Borecki, Ingrid B %A Knekt, Paul %A Kritchevsky, Stephen B %A Eriksson, Johan G %A Dedoussis, George V %A Qi, Lu %A Ferrucci, Luigi %A Orho-Melander, Marju %A Zillikens, M Carola %A Ingelsson, Erik %A Lehtimäki, Terho %A Renstrom, Frida %A Cupples, L Adrienne %A Loos, Ruth J F %A Franks, Paul W %K Adult %K Body Mass Index %K Case-Control Studies %K Diet, Western %K Epistasis, Genetic %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Obesity %K Polymorphism, Single Nucleotide %X

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

%B Hum Mol Genet %V 24 %P 4728-38 %8 2015 Aug 15 %G eng %N 16 %1 http://www.ncbi.nlm.nih.gov/pubmed/25994509?dopt=Abstract %R 10.1093/hmg/ddv186 %0 Journal Article %J Diabetes Care %D 2015 %T Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits. %A Dashti, Hassan S %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Garaulet, Marta %A Gottlieb, Daniel J %A Hruby, Adela %A Jacques, Paul F %A Kiefte-de Jong, Jessica C %A Lamon-Fava, Stefania %A Scheer, Frank A J L %A Bartz, Traci M %A Kovanen, Leena %A Wojczynski, Mary K %A Frazier-Wood, Alexis C %A Ahluwalia, Tarunveer S %A Perälä, Mia-Maria %A Jonsson, Anna %A Muka, Taulant %A Kalafati, Ioanna P %A Mikkilä, Vera %A Ordovas, Jose M %K Adult %K Alleles %K Blood Glucose %K Circadian Rhythm Signaling Peptides and Proteins %K Cohort Studies %K Diabetes Mellitus, Type 2 %K Diet, Fat-Restricted %K European Continental Ancestry Group %K Fasting %K Female %K Gene-Environment Interaction %K Humans %K Insulin Resistance %K Male %K Middle Aged %K Multicenter Studies as Topic %K Observational Studies as Topic %K Phenotype %K Polymorphism, Single Nucleotide %K Sleep %K Waist Circumference %X

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS: We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h).

CONCLUSIONS: Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

%B Diabetes Care %V 38 %P 1456-66 %8 2015 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/26084345?dopt=Abstract %R 10.2337/dc14-2709 %0 Journal Article %J J Gerontol A Biol Sci Med Sci %D 2015 %T Genome-Wide Association Study and Linkage Analysis of the Healthy Aging Index. %A Minster, Ryan L %A Sanders, Jason L %A Singh, Jatinder %A Kammerer, Candace M %A Barmada, M Michael %A Matteini, Amy M %A Zhang, Qunyuan %A Wojczynski, Mary K %A Daw, E Warwick %A Brody, Jennifer A %A Arnold, Alice M %A Lunetta, Kathryn L %A Murabito, Joanne M %A Christensen, Kaare %A Perls, Thomas T %A Province, Michael A %A Newman, Anne B %K Aging %K Apolipoproteins E %K Forkhead Transcription Factors %K Genetic Linkage %K Genome-Wide Association Study %K Humans %K Longevity %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %X

BACKGROUND: The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems.

METHODS: We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted for mortality risk in 3,140 individuals selected for familial longevity from the Long Life Family Study. The genome-wide association study used the Long Life Family Study as the discovery cohort and individuals from the Cardiovascular Health Study and the Framingham Heart Study as replication cohorts.

RESULTS: There were no genome-wide significant findings from the genome-wide association study; however, several single-nucleotide polymorphisms near ZNF704 on chromosome 8q21.13 were suggestively associated with the HAI in the Long Life Family Study (p < 10(-) (6)) and nominally replicated in the Cardiovascular Health Study and Framingham Heart Study. Linkage results revealed significant evidence (log-odds score = 3.36) for a quantitative trait locus for mortality-optimized HAI in women on chromosome 9p24-p23. However, results of fine-mapping studies did not implicate any specific candidate genes within this region of interest.

CONCLUSIONS: ZNF704 may be a potential candidate gene for studies of the genetic underpinnings of longevity.

%B J Gerontol A Biol Sci Med Sci %V 70 %P 1003-8 %8 2015 Aug %G ENG %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/25758594?dopt=Abstract %R 10.1093/gerona/glv006 %0 Journal Article %J Circ Cardiovasc Genet %D 2016 %T Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis. %A Natarajan, Pradeep %A Bis, Joshua C %A Bielak, Lawrence F %A Cox, Amanda J %A Dörr, Marcus %A Feitosa, Mary F %A Franceschini, Nora %A Guo, Xiuqing %A Hwang, Shih-Jen %A Isaacs, Aaron %A Jhun, Min A %A Kavousi, Maryam %A Li-Gao, Ruifang %A Lyytikäinen, Leo-Pekka %A Marioni, Riccardo E %A Schminke, Ulf %A Stitziel, Nathan O %A Tada, Hayato %A van Setten, Jessica %A Smith, Albert V %A Vojinovic, Dina %A Yanek, Lisa R %A Yao, Jie %A Yerges-Armstrong, Laura M %A Amin, Najaf %A Baber, Usman %A Borecki, Ingrid B %A Carr, J Jeffrey %A Chen, Yii-Der Ida %A Cupples, L Adrienne %A de Jong, Pim A %A de Koning, Harry %A de Vos, Bob D %A Demirkan, Ayse %A Fuster, Valentin %A Franco, Oscar H %A Goodarzi, Mark O %A Harris, Tamara B %A Heckbert, Susan R %A Heiss, Gerardo %A Hoffmann, Udo %A Hofman, Albert %A Išgum, Ivana %A Jukema, J Wouter %A Kähönen, Mika %A Kardia, Sharon L R %A Kral, Brian G %A Launer, Lenore J %A Massaro, Joseph %A Mehran, Roxana %A Mitchell, Braxton D %A Mosley, Thomas H %A de Mutsert, Renée %A Newman, Anne B %A Nguyen, Khanh-Dung %A North, Kari E %A O'Connell, Jeffrey R %A Oudkerk, Matthijs %A Pankow, James S %A Peloso, Gina M %A Post, Wendy %A Province, Michael A %A Raffield, Laura M %A Raitakari, Olli T %A Reilly, Dermot F %A Rivadeneira, Fernando %A Rosendaal, Frits %A Sartori, Samantha %A Taylor, Kent D %A Teumer, Alexander %A Trompet, Stella %A Turner, Stephen T %A Uitterlinden, André G %A Vaidya, Dhananjay %A van der Lugt, Aad %A Völker, Uwe %A Wardlaw, Joanna M %A Wassel, Christina L %A Weiss, Stefan %A Wojczynski, Mary K %A Becker, Diane M %A Becker, Lewis C %A Boerwinkle, Eric %A Bowden, Donald W %A Deary, Ian J %A Dehghan, Abbas %A Felix, Stephan B %A Gudnason, Vilmundur %A Lehtimäki, Terho %A Mathias, Rasika %A Mook-Kanamori, Dennis O %A Psaty, Bruce M %A Rader, Daniel J %A Rotter, Jerome I %A Wilson, James G %A van Duijn, Cornelia M %A Völzke, Henry %A Kathiresan, Sekar %A Peyser, Patricia A %A O'Donnell, Christopher J %X

BACKGROUND: -The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease (CHD). We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent CHD.

METHODS AND RESULTS: -We studied a total of 25,109 European ancestry and African-American participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52,869 with common carotid intima media thickness (CIMT) measured by ultrasonography within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Participants were genotyped for 247,870 DNA sequence variants (231,539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and CIMT. APOB p.Arg3527Gln was associated with four-fold excess CAC (P = 3×10(-10)). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC (P = 1×10(-12)) and 1.4% reduced CIMT (P = 4×10(-14)) in carriers compared with non-carriers. In secondary analyses conditioning on LDL cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for CHD (OR 0.77; P = 1×10(-11)).

CONCLUSIONS: -Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities as well as clinical CHD.

%B Circ Cardiovasc Genet %8 2016 Nov 21 %G eng %R 10.1161/CIRCGENETICS.116.001572 %0 Journal Article %J PLoS Genet %D 2017 %T Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium. %A Ng, Maggie C Y %A Graff, Mariaelisa %A Lu, Yingchang %A Justice, Anne E %A Mudgal, Poorva %A Liu, Ching-Ti %A Young, Kristin %A Yanek, Lisa R %A Feitosa, Mary F %A Wojczynski, Mary K %A Rand, Kristin %A Brody, Jennifer A %A Cade, Brian E %A Dimitrov, Latchezar %A Duan, Qing %A Guo, Xiuqing %A Lange, Leslie A %A Nalls, Michael A %A Okut, Hayrettin %A Tajuddin, Salman M %A Tayo, Bamidele O %A Vedantam, Sailaja %A Bradfield, Jonathan P %A Chen, Guanjie %A Chen, Wei-Min %A Chesi, Alessandra %A Irvin, Marguerite R %A Padhukasahasram, Badri %A Smith, Jennifer A %A Zheng, Wei %A Allison, Matthew A %A Ambrosone, Christine B %A Bandera, Elisa V %A Bartz, Traci M %A Berndt, Sonja I %A Bernstein, Leslie %A Blot, William J %A Bottinger, Erwin P %A Carpten, John %A Chanock, Stephen J %A Chen, Yii-Der Ida %A Conti, David V %A Cooper, Richard S %A Fornage, Myriam %A Freedman, Barry I %A Garcia, Melissa %A Goodman, Phyllis J %A Hsu, Yu-Han H %A Hu, Jennifer %A Huff, Chad D %A Ingles, Sue A %A John, Esther M %A Kittles, Rick %A Klein, Eric %A Li, Jin %A McKnight, Barbara %A Nayak, Uma %A Nemesure, Barbara %A Ogunniyi, Adesola %A Olshan, Andrew %A Press, Michael F %A Rohde, Rebecca %A Rybicki, Benjamin A %A Salako, Babatunde %A Sanderson, Maureen %A Shao, Yaming %A Siscovick, David S %A Stanford, Janet L %A Stevens, Victoria L %A Stram, Alex %A Strom, Sara S %A Vaidya, Dhananjay %A Witte, John S %A Yao, Jie %A Zhu, Xiaofeng %A Ziegler, Regina G %A Zonderman, Alan B %A Adeyemo, Adebowale %A Ambs, Stefan %A Cushman, Mary %A Faul, Jessica D %A Hakonarson, Hakon %A Levin, Albert M %A Nathanson, Katherine L %A Ware, Erin B %A Weir, David R %A Zhao, Wei %A Zhi, Degui %A Arnett, Donna K %A Grant, Struan F A %A Kardia, Sharon L R %A Oloapde, Olufunmilayo I %A Rao, D C %A Rotimi, Charles N %A Sale, Michèle M %A Williams, L Keoki %A Zemel, Babette S %A Becker, Diane M %A Borecki, Ingrid B %A Evans, Michele K %A Harris, Tamara B %A Hirschhorn, Joel N %A Li, Yun %A Patel, Sanjay R %A Psaty, Bruce M %A Rotter, Jerome I %A Wilson, James G %A Bowden, Donald W %A Cupples, L Adrienne %A Haiman, Christopher A %A Loos, Ruth J F %A North, Kari E %X

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.

%B PLoS Genet %V 13 %P e1006719 %8 2017 Apr 21 %G eng %N 4 %R 10.1371/journal.pgen.1006719 %0 Journal Article %J PLoS One %D 2017 %T Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts. %A Mozaffarian, Dariush %A Dashti, Hassan S %A Wojczynski, Mary K %A Chu, Audrey Y %A Nettleton, Jennifer A %A Männistö, Satu %A Kristiansson, Kati %A Reedik, Mägi %A Lahti, Jari %A Houston, Denise K %A Cornelis, Marilyn C %A van Rooij, Frank J A %A Dimitriou, Maria %A Kanoni, Stavroula %A Mikkilä, Vera %A Steffen, Lyn M %A de Oliveira Otto, Marcia C %A Qi, Lu %A Psaty, Bruce %A Djoussé, Luc %A Rotter, Jerome I %A Harald, Kennet %A Perola, Markus %A Rissanen, Harri %A Jula, Antti %A Krista, Fischer %A Mihailov, Evelin %A Feitosa, Mary F %A Ngwa, Julius S %A Xue, Luting %A Jacques, Paul F %A Perälä, Mia-Maria %A Palotie, Aarno %A Liu, Yongmei %A Nalls, Nike A %A Ferrucci, Luigi %A Hernandez, Dena %A Manichaikul, Ani %A Tsai, Michael Y %A Kiefte-de Jong, Jessica C %A Hofman, Albert %A Uitterlinden, André G %A Rallidis, Loukianos %A Ridker, Paul M %A Rose, Lynda M %A Buring, Julie E %A Lehtimäki, Terho %A Kähönen, Mika %A Viikari, Jorma %A Lemaitre, Rozenn %A Salomaa, Veikko %A Knekt, Paul %A Metspalu, Andres %A Borecki, Ingrid B %A Cupples, L Adrienne %A Eriksson, Johan G %A Kritchevsky, Stephen B %A Bandinelli, Stefania %A Siscovick, David %A Franco, Oscar H %A Deloukas, Panos %A Dedoussis, George %A Chasman, Daniel I %A Raitakari, Olli %A Tanaka, Toshiko %K Adult %K Aged %K Cohort Studies %K Docosahexaenoic Acids %K Eicosapentaenoic Acid %K Europe %K European Continental Ancestry Group %K Female %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Seafood %K United States %X

BACKGROUND: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

OBJECTIVE: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

DESIGN: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

RESULTS: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.

CONCLUSIONS: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

%B PLoS One %V 12 %P e0186456 %8 2017 %G eng %N 12 %R 10.1371/journal.pone.0186456 %0 Journal Article %J Mol Nutr Food Res %D 2017 %T Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. %A Smith, Caren E %A Follis, Jack L %A Dashti, Hassan S %A Tanaka, Toshiko %A Graff, Mariaelisa %A Fretts, Amanda M %A Kilpeläinen, Tuomas O %A Wojczynski, Mary K %A Richardson, Kris %A Nalls, Mike A %A Schulz, Christina-Alexandra %A Liu, Yongmei %A Frazier-Wood, Alexis C %A van Eekelen, Esther %A Wang, Carol %A de Vries, Paul S %A Mikkilä, Vera %A Rohde, Rebecca %A Psaty, Bruce M %A Hansen, Torben %A Feitosa, Mary F %A Lai, Chao-Qiang %A Houston, Denise K %A Ferruci, Luigi %A Ericson, Ulrika %A Wang, Zhe %A de Mutsert, Renée %A Oddy, Wendy H %A de Jonge, Ester A L %A Seppälä, Ilkka %A Justice, Anne E %A Lemaitre, Rozenn N %A Sørensen, Thorkild I A %A Province, Michael A %A Parnell, Laurence D %A Garcia, Melissa E %A Bandinelli, Stefania %A Orho-Melander, Marju %A Rich, Stephen S %A Rosendaal, Frits R %A Pennell, Craig E %A Kiefte-de Jong, Jessica C %A Kähönen, Mika %A Young, Kristin L %A Pedersen, Oluf %A Aslibekyan, Stella %A Rotter, Jerome I %A Mook-Kanamori, Dennis O %A Zillikens, M Carola %A Raitakari, Olli T %A North, Kari E %A Overvad, Kim %A Arnett, Donna K %A Hofman, Albert %A Lehtimäki, Terho %A Tjønneland, Anne %A Uitterlinden, André G %A Rivadeneira, Fernando %A Franco, Oscar H %A German, J Bruce %A Siscovick, David S %A Cupples, L Adrienne %A Ordovas, Jose M %X

SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.

METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.

CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

%B Mol Nutr Food Res %8 2017 Sep 21 %G eng %R 10.1002/mnfr.201700347 %0 Journal Article %J Am J Hum Genet %D 2018 %T A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. %A Sung, Yun J %A Winkler, Thomas W %A de Las Fuentes, Lisa %A Bentley, Amy R %A Brown, Michael R %A Kraja, Aldi T %A Schwander, Karen %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Kilpeläinen, Tuomas O %A Richard, Melissa A %A Noordam, Raymond %A Aslibekyan, Stella %A Aschard, Hugues %A Bartz, Traci M %A Dorajoo, Rajkumar %A Liu, Yongmei %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert Vernon %A Tajuddin, Salman M %A Tayo, Bamidele O %A Warren, Helen R %A Zhao, Wei %A Zhou, Yanhua %A Matoba, Nana %A Sofer, Tamar %A Alver, Maris %A Amini, Marzyeh %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Giulianini, Franco %A Goel, Anuj %A Harris, Sarah E %A Hartwig, Fernando Pires %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Kuhnel, Brigitte %A Leander, Karin %A Lee, Wen-Jane %A Lin, Keng-Hung %A 'an Luan, Jian %A McKenzie, Colin A %A Meian, He %A Nelson, Christopher P %A Rauramaa, Rainer %A Schupf, Nicole %A Scott, Robert A %A Sheu, Wayne H H %A Stančáková, Alena %A Takeuchi, Fumihiko %A van der Most, Peter J %A Varga, Tibor V %A Wang, Heming %A Wang, Yajuan %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Alfred, Tamuno %A Amin, Najaf %A Arking, Dan %A Aung, Tin %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Braund, Peter S %A Brody, Jennifer A %A Broeckel, Ulrich %A Cabrera, Claudia P %A Cade, Brian %A Caizheng, Yu %A Campbell, Archie %A Canouil, Mickaël %A Chakravarti, Aravinda %A Chauhan, Ganesh %A Christensen, Kaare %A Cocca, Massimiliano %A Collins, Francis S %A Connell, John M %A de Mutsert, Renée %A de Silva, H Janaka %A Debette, Stephanie %A Dörr, Marcus %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Evangelou, Evangelos %A Faul, Jessica D %A Fisher, Virginia A %A Forouhi, Nita G %A Franco, Oscar H %A Friedlander, Yechiel %A Gao, He %A Gigante, Bruna %A Graff, Misa %A Gu, C Charles %A Gu, Dongfeng %A Gupta, Preeti %A Hagenaars, Saskia P %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hofman, Albert %A Howard, Barbara V %A Hunt, Steven %A Irvin, Marguerite R %A Jia, Yucheng %A Joehanes, Roby %A Justice, Anne E %A Katsuya, Tomohiro %A Kaufman, Joel %A Kerrison, Nicola D %A Khor, Chiea Chuen %A Koh, Woon-Puay %A Koistinen, Heikki A %A Komulainen, Pirjo %A Kooperberg, Charles %A Krieger, Jose E %A Kubo, Michiaki %A Kuusisto, Johanna %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lim, Sing Hui %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Jingmin %A Liu, Kiang %A Liu, Yeheng %A Loh, Marie %A Lohman, Kurt K %A Long, Jirong %A Louie, Tin %A Mägi, Reedik %A Mahajan, Anubha %A Meitinger, Thomas %A Metspalu, Andres %A Milani, Lili %A Momozawa, Yukihide %A Morris, Andrew P %A Mosley, Thomas H %A Munson, Peter %A Murray, Alison D %A Nalls, Mike A %A Nasri, Ubaydah %A Norris, Jill M %A North, Kari %A Ogunniyi, Adesola %A Padmanabhan, Sandosh %A Palmas, Walter R %A Palmer, Nicholette D %A Pankow, James S %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Raitakari, Olli T %A Renstrom, Frida %A Rice, Treva K %A Ridker, Paul M %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Sabanayagam, Charumathi %A Salako, Babatunde L %A Sandow, Kevin %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Seshadri, Sudha %A Sever, Peter %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya X %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yuan, Jian-Min %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Chen, Yii-Der Ida %A de Faire, Ulf %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Forrester, Terrence %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo Lessa %A Hung, Yi-Jen %A Jonas, Jost B %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Lehtimäki, Terho %A Liang, Kae-Woei %A Magnusson, Patrik K E %A Newman, Anne B %A Oldehinkel, Albertine J %A Pereira, Alexandre C %A Redline, Susan %A Rettig, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Kamatani, Yoichiro %A Laurie, Cathy C %A Bouchard, Claude %A Cooper, Richard S %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Kritchevsky, Stephen B %A Levy, Daniel %A O'Connell, Jeff R %A Psaty, Bruce M %A van Dam, Rob M %A Sims, Mario %A Arnett, Donna K %A Mook-Kanamori, Dennis O %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A Fornage, Myriam %A Rotimi, Charles N %A Province, Michael A %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Reiner, Alex P %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Caulfield, Mark J %A Elliott, Paul %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Cupples, L Adrienne %A Rao, Dabeeru C %A Chasman, Daniel I %X

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).

%B Am J Hum Genet %V 102 %P 375-400 %8 2018 Mar 01 %G eng %N 3 %R 10.1016/j.ajhg.2018.01.015 %0 Journal Article %J Nat Commun %D 2018 %T Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function. %A Wyss, Annah B %A Sofer, Tamar %A Lee, Mi Kyeong %A Terzikhan, Natalie %A Nguyen, Jennifer N %A Lahousse, Lies %A Latourelle, Jeanne C %A Smith, Albert Vernon %A Bartz, Traci M %A Feitosa, Mary F %A Gao, Wei %A Ahluwalia, Tarunveer S %A Tang, Wenbo %A Oldmeadow, Christopher %A Duan, Qing %A de Jong, Kim %A Wojczynski, Mary K %A Wang, Xin-Qun %A Noordam, Raymond %A Hartwig, Fernando Pires %A Jackson, Victoria E %A Wang, Tianyuan %A Obeidat, Ma'en %A Hobbs, Brian D %A Huan, Tianxiao %A Gui, Hongsheng %A Parker, Margaret M %A Hu, Donglei %A Mogil, Lauren S %A Kichaev, Gleb %A Jin, Jianping %A Graff, Mariaelisa %A Harris, Tamara B %A Kalhan, Ravi %A Heckbert, Susan R %A Paternoster, Lavinia %A Burkart, Kristin M %A Liu, Yongmei %A Holliday, Elizabeth G %A Wilson, James G %A Vonk, Judith M %A Sanders, Jason L %A Barr, R Graham %A de Mutsert, Renée %A Menezes, Ana Maria Baptista %A Adams, Hieab H H %A van den Berge, Maarten %A Joehanes, Roby %A Levin, Albert M %A Liberto, Jennifer %A Launer, Lenore J %A Morrison, Alanna C %A Sitlani, Colleen M %A Celedón, Juan C %A Kritchevsky, Stephen B %A Scott, Rodney J %A Christensen, Kaare %A Rotter, Jerome I %A Bonten, Tobias N %A Wehrmeister, Fernando César %A Bossé, Yohan %A Xiao, Shujie %A Oh, Sam %A Franceschini, Nora %A Brody, Jennifer A %A Kaplan, Robert C %A Lohman, Kurt %A McEvoy, Mark %A Province, Michael A %A Rosendaal, Frits R %A Taylor, Kent D %A Nickle, David C %A Williams, L Keoki %A Burchard, Esteban G %A Wheeler, Heather E %A Sin, Don D %A Gudnason, Vilmundur %A North, Kari E %A Fornage, Myriam %A Psaty, Bruce M %A Myers, Richard H %A O'Connor, George %A Hansen, Torben %A Laurie, Cathy C %A Cassano, Patricia A %A Sung, Joohon %A Kim, Woo Jin %A Attia, John R %A Lange, Leslie %A Boezen, H Marike %A Thyagarajan, Bharat %A Rich, Stephen S %A Mook-Kanamori, Dennis O %A Horta, Bernardo Lessa %A Uitterlinden, André G %A Im, Hae Kyung %A Cho, Michael H %A Brusselle, Guy G %A Gharib, Sina A %A Dupuis, Josée %A Manichaikul, Ani %A London, Stephanie J %X

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.

%B Nat Commun %V 9 %P 2976 %8 2018 Jul 30 %G eng %N 1 %R 10.1038/s41467-018-05369-0 %0 Journal Article %J PLoS One %D 2018 %T Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. %A Feitosa, Mary F %A Kraja, Aldi T %A Chasman, Daniel I %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Bentley, Amy R %A Brown, Michael R %A Schwander, Karen %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Dorajoo, Rajkumar %A Fisher, Virginia %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Wojczynski, Mary K %A Alver, Maris %A Boissel, Mathilde %A Cai, Qiuyin %A Campbell, Archie %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Laguzzi, Federica %A Luan, Jian'an %A Matoba, Nana %A Nolte, Ilja M %A Padmanabhan, Sandosh %A Riaz, Muhammad %A Rueedi, Rico %A Robino, Antonietta %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Vitart, Veronique %A Wang, Yajuan %A Ware, Erin B %A Warren, Helen R %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Boerwinkle, Eric %A Borecki, Ingrid %A Broeckel, Ulrich %A Brown, Morris %A Brumat, Marco %A Burke, Gregory L %A Canouil, Mickaël %A Chakravarti, Aravinda %A Charumathi, Sabanayagam %A Ida Chen, Yii-Der %A Connell, John M %A Correa, Adolfo %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Deng, Xuan %A Ding, Jingzhong %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Eppinga, Ruben N %A Evangelou, Evangelos %A Faul, Jessica D %A Felix, Stephan B %A Forouhi, Nita G %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gigante, Bruna %A Gu, C Charles %A Gu, Dongfeng %A Hagenaars, Saskia P %A Hallmans, Göran %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Howard, Barbara V %A Ikram, M Arfan %A John, Ulrich %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lin, Shiow %A Liu, Jianjun %A Liu, Jingmin %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Nalls, Mike A %A Nelson, Christopher P %A Sotoodehnia, Nona %A Norris, Jill M %A O'Connell, Jeff R %A Palmer, Nicholette D %A Perls, Thomas %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Roll, Kathryn %A Rose, Lynda M %A Rosendaal, Frits R %A Rotter, Jerome I %A Schmidt, Carsten O %A Schreiner, Pamela J %A Schupf, Nicole %A Scott, William R %A Sever, Peter S %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Turner, Stephen T %A Uitterlinden, André G %A Vollenweider, Peter %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya Xing %A Wei, Wen Bin %A Williams, Christine %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Jonas, Jost Bruno %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Kutalik, Zoltán %A Laakso, Markku %A Laurie, Cathy C %A Leander, Karin %A Lehtimäki, Terho %A Study, Lifelines Cohort %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Polasek, Ozren %A Porteous, David J %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Bouchard, Claude %A Christensen, Kaare %A Evans, Michele K %A Gudnason, Vilmundur %A Horta, Bernardo L %A Kardia, Sharon L R %A Liu, Yongmei %A Pereira, Alexandre C %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Gauderman, W James %A Zhu, Xiaofeng %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Rotimi, Charles N %A Cupples, L Adrienne %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Kooperberg, Charles %A Palmas, Walter %A Rice, Kenneth %A Morrison, Alanna C %A Elliott, Paul %A Caulfield, Mark J %A Munroe, Patricia B %A Rao, Dabeeru C %A Province, Michael A %A Levy, Daniel %X

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.

%B PLoS One %V 13 %P e0198166 %8 2018 %G eng %N 6 %R 10.1371/journal.pone.0198166 %0 Journal Article %J Nat Genet %D 2019 %T A catalog of genetic loci associated with kidney function from analyses of a million individuals. %A Wuttke, Matthias %A Li, Yong %A Li, Man %A Sieber, Karsten B %A Feitosa, Mary F %A Gorski, Mathias %A Tin, Adrienne %A Wang, Lihua %A Chu, Audrey Y %A Hoppmann, Anselm %A Kirsten, Holger %A Giri, Ayush %A Chai, Jin-Fang %A Sveinbjornsson, Gardar %A Tayo, Bamidele O %A Nutile, Teresa %A Fuchsberger, Christian %A Marten, Jonathan %A Cocca, Massimiliano %A Ghasemi, Sahar %A Xu, Yizhe %A Horn, Katrin %A Noce, Damia %A van der Most, Peter J %A Sedaghat, Sanaz %A Yu, Zhi %A Akiyama, Masato %A Afaq, Saima %A Ahluwalia, Tarunveer S %A Almgren, Peter %A Amin, Najaf %A Arnlöv, Johan %A Bakker, Stephan J L %A Bansal, Nisha %A Baptista, Daniela %A Bergmann, Sven %A Biggs, Mary L %A Biino, Ginevra %A Boehnke, Michael %A Boerwinkle, Eric %A Boissel, Mathilde %A Bottinger, Erwin P %A Boutin, Thibaud S %A Brenner, Hermann %A Brumat, Marco %A Burkhardt, Ralph %A Butterworth, Adam S %A Campana, Eric %A Campbell, Archie %A Campbell, Harry %A Canouil, Mickaël %A Carroll, Robert J %A Catamo, Eulalia %A Chambers, John C %A Chee, Miao-Ling %A Chee, Miao-Li %A Chen, Xu %A Cheng, Ching-Yu %A Cheng, Yurong %A Christensen, Kaare %A Cifkova, Renata %A Ciullo, Marina %A Concas, Maria Pina %A Cook, James P %A Coresh, Josef %A Corre, Tanguy %A Sala, Cinzia Felicita %A Cusi, Daniele %A Danesh, John %A Daw, E Warwick %A de Borst, Martin H %A De Grandi, Alessandro %A de Mutsert, Renée %A de Vries, Aiko P J %A Degenhardt, Frauke %A Delgado, Graciela %A Demirkan, Ayse %A Di Angelantonio, Emanuele %A Dittrich, Katalin %A Divers, Jasmin %A Dorajoo, Rajkumar %A Eckardt, Kai-Uwe %A Ehret, Georg %A Elliott, Paul %A Endlich, Karlhans %A Evans, Michele K %A Felix, Janine F %A Foo, Valencia Hui Xian %A Franco, Oscar H %A Franke, Andre %A Freedman, Barry I %A Freitag-Wolf, Sandra %A Friedlander, Yechiel %A Froguel, Philippe %A Gansevoort, Ron T %A Gao, He %A Gasparini, Paolo %A Gaziano, J Michael %A Giedraitis, Vilmantas %A Gieger, Christian %A Girotto, Giorgia %A Giulianini, Franco %A Gögele, Martin %A Gordon, Scott D %A Gudbjartsson, Daniel F %A Gudnason, Vilmundur %A Haller, Toomas %A Hamet, Pavel %A Harris, Tamara B %A Hartman, Catharina A %A Hayward, Caroline %A Hellwege, Jacklyn N %A Heng, Chew-Kiat %A Hicks, Andrew A %A Hofer, Edith %A Huang, Wei %A Hutri-Kähönen, Nina %A Hwang, Shih-Jen %A Ikram, M Arfan %A Indridason, Olafur S %A Ingelsson, Erik %A Ising, Marcus %A Jaddoe, Vincent W V %A Jakobsdottir, Johanna %A Jonas, Jost B %A Joshi, Peter K %A Josyula, Navya Shilpa %A Jung, Bettina %A Kähönen, Mika %A Kamatani, Yoichiro %A Kammerer, Candace M %A Kanai, Masahiro %A Kastarinen, Mika %A Kerr, Shona M %A Khor, Chiea-Chuen %A Kiess, Wieland %A Kleber, Marcus E %A Koenig, Wolfgang %A Kooner, Jaspal S %A Körner, Antje %A Kovacs, Peter %A Kraja, Aldi T %A Krajcoviechova, Alena %A Kramer, Holly %A Krämer, Bernhard K %A Kronenberg, Florian %A Kubo, Michiaki %A Kuhnel, Brigitte %A Kuokkanen, Mikko %A Kuusisto, Johanna %A La Bianca, Martina %A Laakso, Markku %A Lange, Leslie A %A Langefeld, Carl D %A Lee, Jeannette Jen-Mai %A Lehne, Benjamin %A Lehtimäki, Terho %A Lieb, Wolfgang %A Lim, Su-Chi %A Lind, Lars %A Lindgren, Cecilia M %A Liu, Jun %A Liu, Jianjun %A Loeffler, Markus %A Loos, Ruth J F %A Lucae, Susanne %A Lukas, Mary Ann %A Lyytikäinen, Leo-Pekka %A Mägi, Reedik %A Magnusson, Patrik K E %A Mahajan, Anubha %A Martin, Nicholas G %A Martins, Jade %A März, Winfried %A Mascalzoni, Deborah %A Matsuda, Koichi %A Meisinger, Christa %A Meitinger, Thomas %A Melander, Olle %A Metspalu, Andres %A Mikaelsdottir, Evgenia K %A Milaneschi, Yuri %A Miliku, Kozeta %A Mishra, Pashupati P %A Mohlke, Karen L %A Mononen, Nina %A Montgomery, Grant W %A Mook-Kanamori, Dennis O %A Mychaleckyj, Josyf C %A Nadkarni, Girish N %A Nalls, Mike A %A Nauck, Matthias %A Nikus, Kjell %A Ning, Boting %A Nolte, Ilja M %A Noordam, Raymond %A O'Connell, Jeffrey %A O'Donoghue, Michelle L %A Olafsson, Isleifur %A Oldehinkel, Albertine J %A Orho-Melander, Marju %A Ouwehand, Willem H %A Padmanabhan, Sandosh %A Palmer, Nicholette D %A Palsson, Runolfur %A Penninx, Brenda W J H %A Perls, Thomas %A Perola, Markus %A Pirastu, Mario %A Pirastu, Nicola %A Pistis, Giorgio %A Podgornaia, Anna I %A Polasek, Ozren %A Ponte, Belen %A Porteous, David J %A Poulain, Tanja %A Pramstaller, Peter P %A Preuss, Michael H %A Prins, Bram P %A Province, Michael A %A Rabelink, Ton J %A Raffield, Laura M %A Raitakari, Olli T %A Reilly, Dermot F %A Rettig, Rainer %A Rheinberger, Myriam %A Rice, Kenneth M %A Ridker, Paul M %A Rivadeneira, Fernando %A Rizzi, Federica %A Roberts, David J %A Robino, Antonietta %A Rossing, Peter %A Rudan, Igor %A Rueedi, Rico %A Ruggiero, Daniela %A Ryan, Kathleen A %A Saba, Yasaman %A Sabanayagam, Charumathi %A Salomaa, Veikko %A Salvi, Erika %A Saum, Kai-Uwe %A Schmidt, Helena %A Schmidt, Reinhold %A Schöttker, Ben %A Schulz, Christina-Alexandra %A Schupf, Nicole %A Shaffer, Christian M %A Shi, Yuan %A Smith, Albert V %A Smith, Blair H %A Soranzo, Nicole %A Spracklen, Cassandra N %A Strauch, Konstantin %A Stringham, Heather M %A Stumvoll, Michael %A Svensson, Per O %A Szymczak, Silke %A Tai, E-Shyong %A Tajuddin, Salman M %A Tan, Nicholas Y Q %A Taylor, Kent D %A Teren, Andrej %A Tham, Yih-Chung %A Thiery, Joachim %A Thio, Chris H L %A Thomsen, Hauke %A Thorleifsson, Gudmar %A Toniolo, Daniela %A Tönjes, Anke %A Tremblay, Johanne %A Tzoulaki, Ioanna %A Uitterlinden, André G %A Vaccargiu, Simona %A van Dam, Rob M %A van der Harst, Pim %A van Duijn, Cornelia M %A Velez Edward, Digna R %A Verweij, Niek %A Vogelezang, Suzanne %A Völker, Uwe %A Vollenweider, Peter %A Waeber, Gérard %A Waldenberger, Melanie %A Wallentin, Lars %A Wang, Ya Xing %A Wang, Chaolong %A Waterworth, Dawn M %A Bin Wei, Wen %A White, Harvey %A Whitfield, John B %A Wild, Sarah H %A Wilson, James F %A Wojczynski, Mary K %A Wong, Charlene %A Wong, Tien-Yin %A Xu, Liang %A Yang, Qiong %A Yasuda, Masayuki %A Yerges-Armstrong, Laura M %A Zhang, Weihua %A Zonderman, Alan B %A Rotter, Jerome I %A Bochud, Murielle %A Psaty, Bruce M %A Vitart, Veronique %A Wilson, James G %A Dehghan, Abbas %A Parsa, Afshin %A Chasman, Daniel I %A Ho, Kevin %A Morris, Andrew P %A Devuyst, Olivier %A Akilesh, Shreeram %A Pendergrass, Sarah A %A Sim, Xueling %A Böger, Carsten A %A Okada, Yukinori %A Edwards, Todd L %A Snieder, Harold %A Stefansson, Kari %A Hung, Adriana M %A Heid, Iris M %A Scholz, Markus %A Teumer, Alexander %A Köttgen, Anna %A Pattaro, Cristian %K Chromosome Mapping %K European Continental Ancestry Group %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Glomerular Filtration Rate %K Humans %K Inheritance Patterns %K Kidney Function Tests %K Phenotype %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Quantitative Trait, Heritable %K Renal Insufficiency, Chronic %K Uromodulin %X

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

%B Nat Genet %V 51 %P 957-972 %8 2019 06 %G eng %N 6 %R 10.1038/s41588-019-0407-x %0 Journal Article %J Am J Epidemiol %D 2019 %T Multi-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. %A de Vries, Paul S %A Brown, Michael R %A Bentley, Amy R %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Schwander, Karen %A Kraja, Aldi T %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Deng, Xuan %A Dorajoo, Rajkumar %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Evangelou, Evangelos %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Laguzzi, Federica %A Lee, Joseph H %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Riaz, Muhammad %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Ballantyne, Christie %A Boerwinkle, Eric %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Connell, John M %A de Faire, Ulf %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Ding, Jingzhong %A Dominiczak, Anna F %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Fisher, Virginia %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Ghanbari, Mohsen %A Giulianini, Franco %A Grabe, Hans J %A Grove, Megan L %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Howard, Barbara V %A Ikram, M Arfan %A Jacobs, David R %A Johnson, Craig %A Jonas, Jost Bruno %A Kammerer, Candace M %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Koistinen, Heikki A %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Steve B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lemaitre, Rozenn N %A Li, Yize %A Liang, Jingjing %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Mosley, Thomas H %A Mukamal, Kenneth J %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A Sotoodehnia, Nona %A O'Connell, Jeff R %A Palmer, Nicholette D %A Pazoki, Raha %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Reiner, Alex P %A Rice, Treva K %A Rich, Stephen S %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Blair H %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tan, Nicholas %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A van Heemst, Diana %A Vuckovic, Dragana %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Yujie %A Wang, Zhe %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yu, Bing %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Penninx, Brenda %A Pereira, Alexandre C %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Zheng, Wei %A Elliott, Paul %A North, Kari E %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Liu, Ching-Ti %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Kardia, Sharon L R %A Zhu, Xiaofeng %A Rotimi, Charles N %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Liu, Jingmin %A Rotter, Jerome I %A Gauderman, W James %A Province, Michael A %A Munroe, Patricia B %A Rice, Kenneth %A Chasman, Daniel I %A Cupples, L Adrienne %A Rao, Dabeeru C %A Morrison, Alanna C %X

An individual'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 multi-ancestry 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 five ancestry groups. Genetic main and interaction effects were jointly assessed by 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 Stage 1 and Stage 2, 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 (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.

%B Am J Epidemiol %8 2019 Jan 29 %G eng %R 10.1093/aje/kwz005 %0 Journal Article %J Nat Genet %D 2019 %T Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. %A Bentley, Amy R %A Sung, Yun J %A Brown, Michael R %A Winkler, Thomas W %A Kraja, Aldi T %A Ntalla, Ioanna %A Schwander, Karen %A Chasman, Daniel I %A Lim, Elise %A Deng, Xuan %A Guo, Xiuqing %A Liu, Jingmin %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Baker, Jenna %A Chen, Guanjie %A Aschard, Hugues %A Bartz, Traci M %A Ding, Jingzhong %A Dorajoo, Rajkumar %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Zhao, Wei %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Hung, Yi-Jen %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Leander, Karin %A Lin, Keng-Hung %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Prins, Bram %A Riaz, Muhammad %A Robino, Antonietta %A Said, M Abdullah %A Schupf, Nicole %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Tzung-Dau %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Xiang, Yong-Bing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Adeyemo, Adebowale %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Arzumanyan, Zorayr %A Aung, Tin %A Ballantyne, Christie %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Broeckel, Ulrich %A Brown, Morris %A Cade, Brian E %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Christensen, Kaare %A Concas, Maria Pina %A Connell, John M %A de Las Fuentes, Lisa %A de Silva, H Janaka %A de Vries, Paul S %A Doumatey, Ayo %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Floyd, James S %A Forouhi, Nita G %A Forrester, Terrence %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gharib, Sina A %A Gigante, Bruna %A Giulianini, Franco %A Grabe, Hans J %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Ikram, M Arfan %A Jia, Yucheng %A Joehanes, Roby %A Johnson, Craig %A Jonas, Jost Bruno %A Justice, Anne E %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Liang, Jingjing %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Lohman, Kurt K %A Louie, Tin %A Luzzi, Anna %A Mägi, Reedik %A Mahajan, Anubha %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Morris, Andrew P %A Murray, Alison D %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Papanicolau, George J %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raitakari, Olli T %A Reiner, Alex P %A Renstrom, Frida %A Rice, Treva K %A Rich, Stephen S %A Robinson, Jennifer G %A Rose, Lynda M %A Rosendaal, Frits R %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Tiemeier, Henning %A Turner, Stephen T %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Heming %A Wang, Lan %A Wang, Lihua %A Wei, Wen Bin %A Williams, Christine A %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Young, Kristin %A Yu, Caizheng %A Yuan, Jian-Min %A Zhou, Jie %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Cooper, Richard S %A de Faire, Ulf %A Deary, Ian J %A Elliott, Paul %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Juang, Jyh-Ming Jimmy %A Kamatani, Yoichiro %A Kammerer, Candace M %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Laurie, Cathy C %A Lee, I-Te %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Pereira, Alexandre C %A Rauramaa, Rainer %A Redline, Susan %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Jun-Sing %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zeggini, Eleftheria %A Zheng, Wei %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Province, Michael A %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Franceschini, Nora %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Rao, Dabeeru C %A Rotimi, Charles N %A Cupples, L Adrienne %X

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.

%B Nat Genet %V 51 %P 636-648 %8 2019 Apr %G eng %N 4 %R 10.1038/s41588-019-0378-y %0 Journal Article %J Am J Hum Genet %D 2021 %T Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. %A Graff, Mariaelisa %A Justice, Anne E %A Young, Kristin L %A Marouli, Eirini %A Zhang, Xinruo %A Fine, Rebecca S %A Lim, Elise %A Buchanan, Victoria %A Rand, Kristin %A Feitosa, Mary F %A Wojczynski, Mary K %A Yanek, Lisa R %A Shao, Yaming %A Rohde, Rebecca %A Adeyemo, Adebowale A %A Aldrich, Melinda C %A Allison, Matthew A %A Ambrosone, Christine B %A Ambs, Stefan %A Amos, Christopher %A Arnett, Donna K %A Atwood, Larry %A Bandera, Elisa V %A Bartz, Traci %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Bielak, Lawrence F %A Blot, William J %A Bottinger, Erwin P %A Bowden, Donald W %A Bradfield, Jonathan P %A Brody, Jennifer A %A Broeckel, Ulrich %A Burke, Gregory %A Cade, Brian E %A Cai, Qiuyin %A Caporaso, Neil %A Carlson, Chris %A Carpten, John %A Casey, Graham %A Chanock, Stephen J %A Chen, Guanjie %A Chen, Minhui %A Chen, Yii-der I %A Chen, Wei-Min %A Chesi, Alessandra %A Chiang, Charleston W K %A Chu, Lisa %A Coetzee, Gerry A %A Conti, David V %A Cooper, Richard S %A Cushman, Mary %A Demerath, Ellen %A Deming, Sandra L %A Dimitrov, Latchezar %A Ding, Jingzhong %A Diver, W Ryan %A Duan, Qing %A Evans, Michele K %A Falusi, Adeyinka G %A Faul, Jessica D %A Fornage, Myriam %A Fox, Caroline %A Freedman, Barry I %A Garcia, Melissa %A Gillanders, Elizabeth M %A Goodman, Phyllis %A Gottesman, Omri %A Grant, Struan F A %A Guo, Xiuqing %A Hakonarson, Hakon %A Haritunians, Talin %A Harris, Tamara B %A Harris, Curtis C %A Henderson, Brian E %A Hennis, Anselm %A Hernandez, Dena G %A Hirschhorn, Joel N %A McNeill, Lorna Haughton %A Howard, Timothy D %A Howard, Barbara %A Hsing, Ann W %A Hsu, Yu-Han H %A Hu, Jennifer J %A Huff, Chad D %A Huo, Dezheng %A Ingles, Sue A %A Irvin, Marguerite R %A John, Esther M %A Johnson, Karen C %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kang, Sun J %A Kardia, Sharon L %A Keating, Brendan J %A Kittles, Rick A %A Klein, Eric A %A Kolb, Suzanne %A Kolonel, Laurence N %A Kooperberg, Charles %A Kuller, Lewis %A Kutlar, Abdullah %A Lange, Leslie %A Langefeld, Carl D %A Le Marchand, Loïc %A Leonard, Hampton %A Lettre, Guillaume %A Levin, Albert M %A Li, Yun %A Li, Jin %A Liu, Yongmei %A Liu, Youfang %A Liu, Simin %A Lohman, Kurt %A Lotay, Vaneet %A Lu, Yingchang %A Maixner, William %A Manson, JoAnn E %A McKnight, Barbara %A Meng, Yan %A Monda, Keri L %A Monroe, Kris %A Moore, Jason H %A Mosley, Thomas H %A Mudgal, Poorva %A Murphy, Adam B %A Nadukuru, Rajiv %A Nalls, Mike A %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Neslund-Dudas, Christine %A Neuhouser, Marian L %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogundiran, Temidayo O %A Ogunniyi, Adesola %A Ojengbede, Oladosu %A Okut, Hayrettin %A Olopade, Olufunmilayo I %A Olshan, Andrew %A Padhukasahasram, Badri %A Palmer, Julie %A Palmer, Cameron D %A Palmer, Nicholette D %A Papanicolaou, George %A Patel, Sanjay R %A Pettaway, Curtis A %A Peyser, Patricia A %A Press, Michael F %A Rao, D C %A Rasmussen-Torvik, Laura J %A Redline, Susan %A Reiner, Alex P %A Rhie, Suhn K %A Rodriguez-Gil, Jorge L %A Rotimi, Charles N %A Rotter, Jerome I %A Ruiz-Narvaez, Edward A %A Rybicki, Benjamin A %A Salako, Babatunde %A Sale, Michèle M %A Sanderson, Maureen %A Schadt, Eric %A Schreiner, Pamela J %A Schurmann, Claudia %A Schwartz, Ann G %A Shriner, Daniel A %A Signorello, Lisa B %A Singleton, Andrew B %A Siscovick, David S %A Smith, Jennifer A %A Smith, Shad %A Speliotes, Elizabeth %A Spitz, Margaret %A Stanford, Janet L %A Stevens, Victoria L %A Stram, Alex %A Strom, Sara S %A Sucheston, Lara %A Sun, Yan V %A Tajuddin, Salman M %A Taylor, Herman %A Taylor, Kira %A Tayo, Bamidele O %A Thun, Michael J %A Tucker, Margaret A %A Vaidya, Dhananjay %A Van Den Berg, David J %A Vedantam, Sailaja %A Vitolins, Mara %A Wang, Zhaoming %A Ware, Erin B %A Wassertheil-Smoller, Sylvia %A Weir, David R %A Wiencke, John K %A Williams, Scott M %A Williams, L Keoki %A Wilson, James G %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yao, Jie %A Zakai, Neil %A Zanetti, Krista %A Zemel, Babette S %A Zhao, Wei %A Zhao, Jing Hua %A Zheng, Wei %A Zhi, Degui %A Zhou, Jie %A Zhu, Xiaofeng %A Ziegler, Regina G %A Zmuda, Joe %A Zonderman, Alan B %A Psaty, Bruce M %A Borecki, Ingrid B %A Cupples, L Adrienne %A Liu, Ching-Ti %A Haiman, Christopher A %A Loos, Ruth %A Ng, Maggie C Y %A North, Kari E %X

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

%B Am J Hum Genet %V 108 %P 564-582 %8 2021 Apr 01 %G eng %N 4 %R 10.1016/j.ajhg.2021.02.011 %0 Journal Article %J Commun Biol %D 2022 %T Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals. %A Winkler, Thomas W %A Rasheed, Humaira %A Teumer, Alexander %A Gorski, Mathias %A Rowan, Bryce X %A Stanzick, Kira J %A Thomas, Laurent F %A Tin, Adrienne %A Hoppmann, Anselm %A Chu, Audrey Y %A Tayo, Bamidele %A Thio, Chris H L %A Cusi, Daniele %A Chai, Jin-Fang %A Sieber, Karsten B %A Horn, Katrin %A Li, Man %A Scholz, Markus %A Cocca, Massimiliano %A Wuttke, Matthias %A van der Most, Peter J %A Yang, Qiong %A Ghasemi, Sahar %A Nutile, Teresa %A Li, Yong %A Pontali, Giulia %A Günther, Felix %A Dehghan, Abbas %A Correa, Adolfo %A Parsa, Afshin %A Feresin, Agnese %A de Vries, Aiko P J %A Zonderman, Alan B %A Smith, Albert V %A Oldehinkel, Albertine J %A De Grandi, Alessandro %A Rosenkranz, Alexander R %A Franke, Andre %A Teren, Andrej %A Metspalu, Andres %A Hicks, Andrew A %A Morris, Andrew P %A Tönjes, Anke %A Morgan, Anna %A Podgornaia, Anna I %A Peters, Annette %A Körner, Antje %A Mahajan, Anubha %A Campbell, Archie %A Freedman, Barry I %A Spedicati, Beatrice %A Ponte, Belen %A Schöttker, Ben %A Brumpton, Ben %A Banas, Bernhard %A Krämer, Bernhard K %A Jung, Bettina %A Åsvold, Bjørn Olav %A Smith, Blair H %A Ning, Boting %A Penninx, Brenda W J H %A Vanderwerff, Brett R %A Psaty, Bruce M %A Kammerer, Candace M %A Langefeld, Carl D %A Hayward, Caroline %A Spracklen, Cassandra N %A Robinson-Cohen, Cassianne %A Hartman, Catharina A %A Lindgren, Cecilia M %A Wang, Chaolong %A Sabanayagam, Charumathi %A Heng, Chew-Kiat %A Lanzani, Chiara %A Khor, Chiea-Chuen %A Cheng, Ching-Yu %A Fuchsberger, Christian %A Gieger, Christian %A Shaffer, Christian M %A Schulz, Christina-Alexandra %A Willer, Cristen J %A Chasman, Daniel I %A Gudbjartsson, Daniel F %A Ruggiero, Daniela %A Toniolo, Daniela %A Czamara, Darina %A Porteous, David J %A Waterworth, Dawn M %A Mascalzoni, Deborah %A Mook-Kanamori, Dennis O %A Reilly, Dermot F %A Daw, E Warwick %A Hofer, Edith %A Boerwinkle, Eric %A Salvi, Erika %A Bottinger, Erwin P %A Tai, E-Shyong %A Catamo, Eulalia %A Rizzi, Federica %A Guo, Feng %A Rivadeneira, Fernando %A Guilianini, Franco %A Sveinbjornsson, Gardar %A Ehret, Georg %A Waeber, Gérard %A Biino, Ginevra %A Girotto, Giorgia %A Pistis, Giorgio %A Nadkarni, Girish N %A Delgado, Graciela E %A Montgomery, Grant W %A Snieder, Harold %A Campbell, Harry %A White, Harvey D %A Gao, He %A Stringham, Heather M %A Schmidt, Helena %A Li, Hengtong %A Brenner, Hermann %A Holm, Hilma %A Kirsten, Holgen %A Kramer, Holly %A Rudan, Igor %A Nolte, Ilja M %A Tzoulaki, Ioanna %A Olafsson, Isleifur %A Martins, Jade %A Cook, James P %A Wilson, James F %A Halbritter, Jan %A Felix, Janine F %A Divers, Jasmin %A Kooner, Jaspal S %A Lee, Jeannette Jen-Mai %A O'Connell, Jeffrey %A Rotter, Jerome I %A Liu, Jianjun %A Xu, Jie %A Thiery, Joachim %A Arnlöv, Johan %A Kuusisto, Johanna %A Jakobsdottir, Johanna %A Tremblay, Johanne %A Chambers, John C %A Whitfield, John B %A Gaziano, John M %A Marten, Jonathan %A Coresh, Josef %A Jonas, Jost B %A Mychaleckyj, Josyf C %A Christensen, Kaare %A Eckardt, Kai-Uwe %A Mohlke, Karen L %A Endlich, Karlhans %A Dittrich, Katalin %A Ryan, Kathleen A %A Rice, Kenneth M %A Taylor, Kent D %A Ho, Kevin %A Nikus, Kjell %A Matsuda, Koichi %A Strauch, Konstantin %A Miliku, Kozeta %A Hveem, Kristian %A Lind, Lars %A Wallentin, Lars %A Yerges-Armstrong, Laura M %A Raffield, Laura M %A Phillips, Lawrence S %A Launer, Lenore J %A Lyytikäinen, Leo-Pekka %A Lange, Leslie A %A Citterio, Lorena %A Klaric, Lucija %A Ikram, M Arfan %A Ising, Marcus %A Kleber, Marcus E %A Francescatto, Margherita %A Concas, Maria Pina %A Ciullo, Marina %A Piratsu, Mario %A Orho-Melander, Marju %A Laakso, Markku %A Loeffler, Markus %A Perola, Markus %A de Borst, Martin H %A Gögele, Martin %A Bianca, Martina La %A Lukas, Mary Ann %A Feitosa, Mary F %A Biggs, Mary L %A Wojczynski, Mary K %A Kavousi, Maryam %A Kanai, Masahiro %A Akiyama, Masato %A Yasuda, Masayuki %A Nauck, Matthias %A Waldenberger, Melanie %A Chee, Miao-Li %A Chee, Miao-Ling %A Boehnke, Michael %A Preuss, Michael H %A Stumvoll, Michael %A Province, Michael A %A Evans, Michele K %A O'Donoghue, Michelle L %A Kubo, Michiaki %A Kähönen, Mika %A Kastarinen, Mika %A Nalls, Mike A %A Kuokkanen, Mikko %A Ghanbari, Mohsen %A Bochud, Murielle %A Josyula, Navya Shilpa %A Martin, Nicholas G %A Tan, Nicholas Y Q %A Palmer, Nicholette D %A Pirastu, Nicola %A Schupf, Nicole %A Verweij, Niek %A Hutri-Kähönen, Nina %A Mononen, Nina %A Bansal, Nisha %A Devuyst, Olivier %A Melander, Olle %A Raitakari, Olli T %A Polasek, Ozren %A Manunta, Paolo %A Gasparini, Paolo %A Mishra, Pashupati P %A Sulem, Patrick %A Magnusson, Patrik K E %A Elliott, Paul %A Ridker, Paul M %A Hamet, Pavel %A Svensson, Per O %A Joshi, Peter K %A Kovacs, Peter %A Pramstaller, Peter P %A Rossing, Peter %A Vollenweider, Peter %A van der Harst, Pim %A Dorajoo, Rajkumar %A Sim, Ralene Z H %A Burkhardt, Ralph %A Tao, Ran %A Noordam, Raymond %A Mägi, Reedik %A Schmidt, Reinhold %A de Mutsert, Renée %A Rueedi, Rico %A van Dam, Rob M %A Carroll, Robert J %A Gansevoort, Ron T %A Loos, Ruth J F %A Felicita, Sala Cinzia %A Sedaghat, Sanaz %A Padmanabhan, Sandosh %A Freitag-Wolf, Sandra %A Pendergrass, Sarah A %A Graham, Sarah E %A Gordon, Scott D %A Hwang, Shih-Jen %A Kerr, Shona M %A Vaccargiu, Simona %A Patil, Snehal B %A Hallan, Stein %A Bakker, Stephan J L %A Lim, Su-Chi %A Lucae, Susanne %A Vogelezang, Suzanne %A Bergmann, Sven %A Corre, Tanguy %A Ahluwalia, Tarunveer S %A Lehtimäki, Terho %A Boutin, Thibaud S %A Meitinger, Thomas %A Wong, Tien-Yin %A Bergler, Tobias %A Rabelink, Ton J %A Esko, Tõnu %A Haller, Toomas %A Thorsteinsdottir, Unnur %A Völker, Uwe %A Foo, Valencia Hui Xian %A Salomaa, Veikko %A Vitart, Veronique %A Giedraitis, Vilmantas %A Gudnason, Vilmundur %A Jaddoe, Vincent W V %A Huang, Wei %A Zhang, Weihua %A Wei, Wen Bin %A Kiess, Wieland %A März, Winfried %A Koenig, Wolfgang %A Lieb, Wolfgang %A Gào, Xīn %A Sim, Xueling %A Wang, Ya Xing %A Friedlander, Yechiel %A Tham, Yih-Chung %A Kamatani, Yoichiro %A Okada, Yukinori %A Milaneschi, Yuri %A Yu, Zhi %A Stark, Klaus J %A Stefansson, Kari %A Böger, Carsten A %A Hung, Adriana M %A Kronenberg, Florian %A Köttgen, Anna %A Pattaro, Cristian %A Heid, Iris M %K Creatinine %K Diabetes Mellitus %K Diabetic Nephropathies %K Genome-Wide Association Study %K Glomerular Filtration Rate %K Humans %K Kidney %X

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (n = 178,691, n = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

%B Commun Biol %V 5 %P 580 %8 2022 Jun 13 %G eng %N 1 %R 10.1038/s42003-022-03448-z %0 Journal Article %J Front Genet %D 2023 %T Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. %A de Las Fuentes, Lisa %A Schwander, Karen L %A Brown, Michael R %A Bentley, Amy R %A Winkler, Thomas W %A Sung, Yun Ju %A Munroe, Patricia B %A Miller, Clint L %A Aschard, Hugo %A Aslibekyan, Stella %A Bartz, Traci M %A Bielak, Lawrence F %A Chai, Jin Fang %A Cheng, Ching-Yu %A Dorajoo, Rajkumar %A Feitosa, Mary F %A Guo, Xiuqing %A Hartwig, Fernando P %A Horimoto, Andrea %A Kolcic, Ivana %A Lim, Elise %A Liu, Yongmei %A Manning, Alisa K %A Marten, Jonathan %A Musani, Solomon K %A Noordam, Raymond %A Padmanabhan, Sandosh %A Rankinen, Tuomo %A Richard, Melissa A %A Ridker, Paul M %A Smith, Albert V %A Vojinovic, Dina %A Zonderman, Alan B %A Alver, Maris %A Boissel, Mathilde %A Christensen, Kaare %A Freedman, Barry I %A Gao, Chuan %A Giulianini, Franco %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Kuhnel, Brigitte %A Laguzzi, Federica %A Li, Xiaoyin %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Poveda, Alaitz %A Rauramaa, Rainer %A Riaz, Muhammad %A Robino, Antonietta %A Sofer, Tamar %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Verweij, Niek %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhan, Yiqiang %A Amin, Najaf %A Arking, Dan E %A Ballantyne, Christie %A Boerwinkle, Eric %A Brody, Jennifer A %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Chai, Xiaoran %A Chen, Yii-Der Ida %A Chen, Xu %A Chitrala, Kumaraswamy Naidu %A Concas, Maria Pina %A de Faire, Ulf %A de Mutsert, Renée %A de Silva, H Janaka %A de Vries, Paul S %A Do, Ahn %A Faul, Jessica D %A Fisher, Virginia %A Floyd, James S %A Forrester, Terrence %A Friedlander, Yechiel %A Girotto, Giorgia %A Gu, C Charles %A Hallmans, Göran %A Heikkinen, Sami %A Heng, Chew-Kiat %A Homuth, Georg %A Hunt, Steven %A Ikram, M Arfan %A Jacobs, David R %A Kavousi, Maryam %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Komulainen, Pirjo %A Langefeld, Carl D %A Liang, Jingjing %A Liu, Kiang %A Liu, Jianjun %A Lohman, Kurt %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Milaneschi, Yuri %A Nauck, Matthias %A Nelson, Christopher P %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pereira, Alexandre C %A Perls, Thomas %A Peters, Annette %A Polasek, Ozren %A Raitakari, Olli T %A Rice, Kenneth %A Rice, Treva K %A Rich, Stephen S %A Sabanayagam, Charumathi %A Schreiner, Pamela J %A Shu, Xiao-Ou %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Starr, John M %A Strauch, Konstantin %A Tai, E Shyong %A Taylor, Kent D %A Tsai, Michael Y %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Ya-Xing %A Wei, Wen-Bin %A Wilson, Gregory %A Xuan, Deng %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Becker, Diane M %A Bonnefond, Amélie %A Bowden, Donald W %A Cooper, Richard S %A Deary, Ian J %A Divers, Jasmin %A Esko, Tõnu %A Franks, Paul W %A Froguel, Philippe %A Gieger, Christian %A Jonas, Jost B %A Kato, Norihiro %A Lakka, Timo A %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A North, Kari E %A Ntalla, Ioanna %A Penninx, Brenda %A Samani, Nilesh J %A Snieder, Harold %A Spedicati, Beatrice %A van der Harst, Pim %A Völzke, Henry %A Wagenknecht, Lynne E %A Weir, David R %A Wojczynski, Mary K %A Wu, Tangchun %A Zheng, Wei %A Zhu, Xiaofeng %A Bouchard, Claude %A Chasman, Daniel I %A Evans, Michele K %A Fox, Ervin R %A Gudnason, Vilmundur %A Hayward, Caroline %A Horta, Bernardo L %A Kardia, Sharon L R %A Krieger, Jose Eduardo %A Mook-Kanamori, Dennis O %A Peyser, Patricia A %A Province, Michael M %A Psaty, Bruce M %A Rudan, Igor %A Sim, Xueling %A Smith, Blair H %A van Dam, Rob M %A van Duijn, Cornelia M %A Wong, Tien Yin %A Arnett, Donna K %A Rao, Dabeeru C %A Gauderman, James %A Liu, Ching-Ti %A Morrison, Alanna C %A Rotter, Jerome I %A Fornage, Myriam %X

Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant ( < 5 × 10) and suggestive ( < 1 × 10) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (), brain (), and liver () biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

%B Front Genet %V 14 %P 1235337 %8 2023 %G eng %R 10.3389/fgene.2023.1235337