TY - JOUR T1 - Sequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. JF - Circ Cardiovasc Genet Y1 - 2014 A1 - Liu, Ching-Ti A1 - Young, Kristin L A1 - Brody, Jennifer A A1 - Olden, Matthias A1 - Wojczynski, Mary K A1 - Heard-Costa, Nancy A1 - Li, Guo A1 - Morrison, Alanna C A1 - Muzny, Donna A1 - Gibbs, Richard A A1 - Reid, Jeffrey G A1 - Shao, Yaming A1 - Zhou, Yanhua A1 - Boerwinkle, Eric A1 - Heiss, Gerardo A1 - Wagenknecht, Lynne A1 - McKnight, Barbara A1 - Borecki, Ingrid B A1 - Fox, Caroline S A1 - North, Kari E A1 - Cupples, L Adrienne KW - Adult KW - Aged KW - Aging KW - Body Mass Index KW - Cohort Studies KW - Female KW - Genetic Association Studies KW - Genetic Variation KW - Genome-Wide Association Study KW - Genomics KW - Heart Diseases KW - Humans KW - Male KW - Membrane Proteins KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Sequence Analysis, DNA KW - Young Adult AB -

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.

VL - 7 IS - 3 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24951660?dopt=Abstract ER - TY - JOUR T1 - Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. JF - Mol Nutr Food Res Y1 - 2017 A1 - Smith, Caren E A1 - Follis, Jack L A1 - Dashti, Hassan S A1 - Tanaka, Toshiko A1 - Graff, Mariaelisa A1 - Fretts, Amanda M A1 - Kilpeläinen, Tuomas O A1 - Wojczynski, Mary K A1 - Richardson, Kris A1 - Nalls, Mike A A1 - Schulz, Christina-Alexandra A1 - Liu, Yongmei A1 - Frazier-Wood, Alexis C A1 - van Eekelen, Esther A1 - Wang, Carol A1 - de Vries, Paul S A1 - Mikkilä, Vera A1 - Rohde, Rebecca A1 - Psaty, Bruce M A1 - Hansen, Torben A1 - Feitosa, Mary F A1 - Lai, Chao-Qiang A1 - Houston, Denise K A1 - Ferruci, Luigi A1 - Ericson, Ulrika A1 - Wang, Zhe A1 - de Mutsert, Renée A1 - Oddy, Wendy H A1 - de Jonge, Ester A L A1 - Seppälä, Ilkka A1 - Justice, Anne E A1 - Lemaitre, Rozenn N A1 - Sørensen, Thorkild I A A1 - Province, Michael A A1 - Parnell, Laurence D A1 - Garcia, Melissa E A1 - Bandinelli, Stefania A1 - Orho-Melander, Marju A1 - Rich, Stephen S A1 - Rosendaal, Frits R A1 - Pennell, Craig E A1 - Kiefte-de Jong, Jessica C A1 - Kähönen, Mika A1 - Young, Kristin L A1 - Pedersen, Oluf A1 - Aslibekyan, Stella A1 - Rotter, Jerome I A1 - Mook-Kanamori, Dennis O A1 - Zillikens, M Carola A1 - Raitakari, Olli T A1 - North, Kari E A1 - Overvad, Kim A1 - Arnett, Donna K A1 - Hofman, Albert A1 - Lehtimäki, Terho A1 - Tjønneland, Anne A1 - Uitterlinden, André G A1 - Rivadeneira, Fernando A1 - Franco, Oscar H A1 - German, J Bruce A1 - Siscovick, David S A1 - Cupples, L Adrienne A1 - Ordovas, Jose M AB -

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.

ER - TY - JOUR T1 - Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis. JF - Diabetologia Y1 - 2018 A1 - McKeown, Nicola M A1 - Dashti, Hassan S A1 - Ma, Jiantao A1 - Haslam, Danielle E A1 - Kiefte-de Jong, Jessica C A1 - Smith, Caren E A1 - Tanaka, Toshiko A1 - Graff, Mariaelisa A1 - Lemaitre, Rozenn N A1 - Rybin, Denis A1 - Sonestedt, Emily A1 - Frazier-Wood, Alexis C A1 - Mook-Kanamori, Dennis O A1 - Li, Yanping A1 - Wang, Carol A A1 - Leermakers, Elisabeth T M A1 - Mikkilä, Vera A1 - Young, Kristin L A1 - Mukamal, Kenneth J A1 - Cupples, L Adrienne A1 - Schulz, Christina-Alexandra A1 - Chen, Tzu-An A1 - Li-Gao, Ruifang A1 - Huang, Tao A1 - Oddy, Wendy H A1 - Raitakari, Olli A1 - Rice, Kenneth A1 - Meigs, James B A1 - Ericson, Ulrika A1 - Steffen, Lyn M A1 - Rosendaal, Frits R A1 - Hofman, Albert A1 - Kähönen, Mika A1 - Psaty, Bruce M A1 - Brunkwall, Louise A1 - Uitterlinden, André G A1 - Viikari, Jorma A1 - Siscovick, David S A1 - Seppälä, Ilkka A1 - North, Kari E A1 - Mozaffarian, Dariush A1 - Dupuis, Josée A1 - Orho-Melander, Marju A1 - Rich, Stephen S A1 - de Mutsert, Renée A1 - Qi, Lu A1 - Pennell, Craig E A1 - Franco, Oscar H A1 - Lehtimäki, Terho A1 - Herman, Mark A AB -

AIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.

METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.

RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10-3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant.

CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.

TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).

VL - 61 IS - 2 ER - TY - JOUR T1 - Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. JF - Diabetes Y1 - 2020 A1 - Yaghootkar, Hanieh A1 - Zhang, Yiying A1 - Spracklen, Cassandra N A1 - Karaderi, Tugce A1 - Huang, Lam Opal A1 - Bradfield, Jonathan A1 - Schurmann, Claudia A1 - Fine, Rebecca S A1 - Preuss, Michael H A1 - Kutalik, Zoltán A1 - Wittemans, Laura Bl A1 - Lu, Yingchang A1 - Metz, Sophia A1 - Willems, Sara M A1 - Li-Gao, Ruifang A1 - Grarup, Niels A1 - Wang, Shuai A1 - Molnos, Sophie A1 - Sandoval-Zárate, América A A1 - Nalls, Mike A A1 - Lange, Leslie A A1 - Haesser, Jeffrey A1 - Guo, Xiuqing A1 - Lyytikäinen, Leo-Pekka A1 - Feitosa, Mary F A1 - Sitlani, Colleen M A1 - Venturini, Cristina A1 - Mahajan, Anubha A1 - Kacprowski, Tim A1 - Wang, Carol A A1 - Chasman, Daniel I A1 - Amin, Najaf A1 - Broer, Linda A1 - Robertson, Neil A1 - Young, Kristin L A1 - Allison, Matthew A1 - Auer, Paul L A1 - Blüher, Matthias A1 - Borja, Judith B A1 - Bork-Jensen, Jette A1 - Carrasquilla, Germán D A1 - Christofidou, Paraskevi A1 - Demirkan, Ayse A1 - Doege, Claudia A A1 - Garcia, Melissa E A1 - Graff, Mariaelisa A1 - Guo, Kaiying A1 - Hakonarson, Hakon A1 - Hong, Jaeyoung A1 - Ida Chen, Yii-Der A1 - Jackson, Rebecca A1 - Jakupović, Hermina A1 - Jousilahti, Pekka A1 - Justice, Anne E A1 - Kähönen, Mika A1 - Kizer, Jorge R A1 - Kriebel, Jennifer A1 - LeDuc, Charles A A1 - Li, Jin A1 - Lind, Lars A1 - Luan, Jian'an A1 - Mackey, David A1 - Mangino, Massimo A1 - Männistö, Satu A1 - Martin Carli, Jayne F A1 - Medina-Gómez, Carolina A1 - Mook-Kanamori, Dennis O A1 - Morris, Andrew P A1 - de Mutsert, Renée A1 - Nauck, Matthias A1 - Nedeljkovic, Ivana A1 - Pennell, Craig E A1 - Pradhan, Arund D A1 - Psaty, Bruce M A1 - Raitakari, Olli T A1 - Scott, Robert A A1 - Skaaby, Tea A1 - Strauch, Konstantin A1 - Taylor, Kent D A1 - Teumer, Alexander A1 - Uitterlinden, André G A1 - Wu, Ying A1 - Yao, Jie A1 - Walker, Mark A1 - North, Kari E A1 - Kovacs, Peter A1 - Ikram, M Arfan A1 - van Duijn, Cornelia M A1 - Ridker, Paul M A1 - Lye, Stephen A1 - Homuth, Georg A1 - Ingelsson, Erik A1 - Spector, Tim D A1 - McKnight, Barbara A1 - Province, Michael A A1 - Lehtimäki, Terho A1 - Adair, Linda S A1 - Rotter, Jerome I A1 - Reiner, Alexander P A1 - Wilson, James G A1 - Harris, Tamara B A1 - Ripatti, Samuli A1 - Grallert, Harald A1 - Meigs, James B A1 - Salomaa, Veikko A1 - Hansen, Torben A1 - Willems van Dijk, Ko A1 - Wareham, Nicholas J A1 - Grant, Struan Fa A1 - Langenberg, Claudia A1 - Frayling, Timothy M A1 - Lindgren, Cecilia M A1 - Mohlke, Karen L A1 - Leibel, Rudolph L A1 - Loos, Ruth Jf A1 - Kilpeläinen, Tuomas O AB -

Leptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10, n=3,901). Using analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity.

ER - TY - JOUR T1 - Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. JF - Am J Hum Genet Y1 - 2021 A1 - Graff, Mariaelisa A1 - Justice, Anne E A1 - Young, Kristin L A1 - Marouli, Eirini A1 - Zhang, Xinruo A1 - Fine, Rebecca S A1 - Lim, Elise A1 - Buchanan, Victoria A1 - Rand, Kristin A1 - Feitosa, Mary F A1 - Wojczynski, Mary K A1 - Yanek, Lisa R A1 - Shao, Yaming A1 - Rohde, Rebecca A1 - Adeyemo, Adebowale A A1 - Aldrich, Melinda C A1 - Allison, Matthew A A1 - Ambrosone, Christine B A1 - Ambs, Stefan A1 - Amos, Christopher A1 - Arnett, Donna K A1 - Atwood, Larry A1 - Bandera, Elisa V A1 - Bartz, Traci A1 - Becker, Diane M A1 - Berndt, Sonja I A1 - Bernstein, Leslie A1 - Bielak, Lawrence F A1 - Blot, William J A1 - Bottinger, Erwin P A1 - Bowden, Donald W A1 - Bradfield, Jonathan P A1 - Brody, Jennifer A A1 - Broeckel, Ulrich A1 - Burke, Gregory A1 - Cade, Brian E A1 - Cai, Qiuyin A1 - Caporaso, Neil A1 - Carlson, Chris A1 - Carpten, John A1 - Casey, Graham A1 - Chanock, Stephen J A1 - Chen, Guanjie A1 - Chen, Minhui A1 - Chen, Yii-der I A1 - Chen, Wei-Min A1 - Chesi, Alessandra A1 - Chiang, Charleston W K A1 - Chu, Lisa A1 - Coetzee, Gerry A A1 - Conti, David V A1 - Cooper, Richard S A1 - Cushman, Mary A1 - Demerath, Ellen A1 - Deming, Sandra L A1 - Dimitrov, Latchezar A1 - Ding, Jingzhong A1 - Diver, W Ryan A1 - Duan, Qing A1 - Evans, Michele K A1 - Falusi, Adeyinka G A1 - Faul, Jessica D A1 - Fornage, Myriam A1 - Fox, Caroline A1 - Freedman, Barry I A1 - Garcia, Melissa A1 - Gillanders, Elizabeth M A1 - Goodman, Phyllis A1 - Gottesman, Omri A1 - Grant, Struan F A A1 - Guo, Xiuqing A1 - Hakonarson, Hakon A1 - Haritunians, Talin A1 - Harris, Tamara B A1 - Harris, Curtis C A1 - Henderson, Brian E A1 - Hennis, Anselm A1 - Hernandez, Dena G A1 - Hirschhorn, Joel N A1 - McNeill, Lorna Haughton A1 - Howard, Timothy D A1 - Howard, Barbara A1 - Hsing, Ann W A1 - Hsu, Yu-Han H A1 - Hu, Jennifer J A1 - Huff, Chad D A1 - Huo, Dezheng A1 - Ingles, Sue A A1 - Irvin, Marguerite R A1 - John, Esther M A1 - Johnson, Karen C A1 - Jordan, Joanne M A1 - Kabagambe, Edmond K A1 - Kang, Sun J A1 - Kardia, Sharon L A1 - Keating, Brendan J A1 - Kittles, Rick A A1 - Klein, Eric A A1 - Kolb, Suzanne A1 - Kolonel, Laurence N A1 - Kooperberg, Charles A1 - Kuller, Lewis A1 - Kutlar, Abdullah A1 - Lange, Leslie A1 - Langefeld, Carl D A1 - Le Marchand, Loïc A1 - Leonard, Hampton A1 - Lettre, Guillaume A1 - Levin, Albert M A1 - Li, Yun A1 - Li, Jin A1 - Liu, Yongmei A1 - Liu, Youfang A1 - Liu, Simin A1 - Lohman, Kurt A1 - Lotay, Vaneet A1 - Lu, Yingchang A1 - Maixner, William A1 - Manson, JoAnn E A1 - McKnight, Barbara A1 - Meng, Yan A1 - Monda, Keri L A1 - Monroe, Kris A1 - Moore, Jason H A1 - Mosley, Thomas H A1 - Mudgal, Poorva A1 - Murphy, Adam B A1 - Nadukuru, Rajiv A1 - Nalls, Mike A A1 - Nathanson, Katherine L A1 - Nayak, Uma A1 - N'diaye, Amidou A1 - Nemesure, Barbara A1 - Neslund-Dudas, Christine A1 - Neuhouser, Marian L A1 - Nyante, Sarah A1 - Ochs-Balcom, Heather A1 - Ogundiran, Temidayo O A1 - Ogunniyi, Adesola A1 - Ojengbede, Oladosu A1 - Okut, Hayrettin A1 - Olopade, Olufunmilayo I A1 - Olshan, Andrew A1 - Padhukasahasram, Badri A1 - Palmer, Julie A1 - Palmer, Cameron D A1 - Palmer, Nicholette D A1 - Papanicolaou, George A1 - Patel, Sanjay R A1 - Pettaway, Curtis A A1 - Peyser, Patricia A A1 - Press, Michael F A1 - Rao, D C A1 - Rasmussen-Torvik, Laura J A1 - Redline, Susan A1 - Reiner, Alex P A1 - Rhie, Suhn K A1 - Rodriguez-Gil, Jorge L A1 - Rotimi, Charles N A1 - Rotter, Jerome I A1 - Ruiz-Narvaez, Edward A A1 - Rybicki, Benjamin A A1 - Salako, Babatunde A1 - Sale, Michèle M A1 - Sanderson, Maureen A1 - Schadt, Eric A1 - Schreiner, Pamela J A1 - Schurmann, Claudia A1 - Schwartz, Ann G A1 - Shriner, Daniel A A1 - Signorello, Lisa B A1 - Singleton, Andrew B A1 - Siscovick, David S A1 - Smith, Jennifer A A1 - Smith, Shad A1 - Speliotes, Elizabeth A1 - Spitz, Margaret A1 - Stanford, Janet L A1 - Stevens, Victoria L A1 - Stram, Alex A1 - Strom, Sara S A1 - Sucheston, Lara A1 - Sun, Yan V A1 - Tajuddin, Salman M A1 - Taylor, Herman A1 - Taylor, Kira A1 - Tayo, Bamidele O A1 - Thun, Michael J A1 - Tucker, Margaret A A1 - Vaidya, Dhananjay A1 - Van Den Berg, David J A1 - Vedantam, Sailaja A1 - Vitolins, Mara A1 - Wang, Zhaoming A1 - Ware, Erin B A1 - Wassertheil-Smoller, Sylvia A1 - Weir, David R A1 - Wiencke, John K A1 - Williams, Scott M A1 - Williams, L Keoki A1 - Wilson, James G A1 - Witte, John S A1 - Wrensch, Margaret A1 - Wu, Xifeng A1 - Yao, Jie A1 - Zakai, Neil A1 - Zanetti, Krista A1 - Zemel, Babette S A1 - Zhao, Wei A1 - Zhao, Jing Hua A1 - Zheng, Wei A1 - Zhi, Degui A1 - Zhou, Jie A1 - Zhu, Xiaofeng A1 - Ziegler, Regina G A1 - Zmuda, Joe A1 - Zonderman, Alan B A1 - Psaty, Bruce M A1 - Borecki, Ingrid B A1 - Cupples, L Adrienne A1 - Liu, Ching-Ti A1 - Haiman, Christopher A A1 - Loos, Ruth A1 - Ng, Maggie C Y A1 - North, Kari E AB -

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.

VL - 108 IS - 4 ER - TY - JOUR T1 - Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations. JF - Circ Genom Precis Med Y1 - 2021 A1 - Haslam, Danielle E A1 - Peloso, Gina M A1 - Guirette, Melanie A1 - Imamura, Fumiaki A1 - Bartz, Traci M A1 - Pitsillides, Achilleas N A1 - Wang, Carol A A1 - Li-Gao, Ruifang A1 - Westra, Jason M A1 - Pitkänen, Niina A1 - Young, Kristin L A1 - Graff, Mariaelisa A1 - Wood, Alexis C A1 - Braun, Kim V E A1 - Luan, Jian'an A1 - Kähönen, Mika A1 - Kiefte-de Jong, Jessica C A1 - Ghanbari, Mohsen A1 - Tintle, Nathan A1 - Lemaitre, Rozenn N A1 - Mook-Kanamori, Dennis O A1 - North, Kari A1 - Helminen, Mika A1 - Mossavar-Rahmani, Yasmin A1 - Snetselaar, Linda A1 - Martin, Lisa W A1 - Viikari, Jorma S A1 - Oddy, Wendy H A1 - Pennell, Craig E A1 - Rosendall, Frits R A1 - Ikram, M Arfan A1 - Uitterlinden, André G A1 - Psaty, Bruce M A1 - Mozaffarian, Dariush A1 - Rotter, Jerome I A1 - Taylor, Kent D A1 - Lehtimäki, Terho A1 - Raitakari, Olli T A1 - Livingston, Kara A A1 - Voortman, Trudy A1 - Forouhi, Nita G A1 - Wareham, Nick J A1 - de Mutsert, Renée A1 - Rich, Steven S A1 - Manson, JoAnn E A1 - Mora, Samia A1 - Ridker, Paul M A1 - Merino, Jordi A1 - Meigs, James B A1 - Dashti, Hassan S A1 - Chasman, Daniel I A1 - Lichtenstein, Alice H A1 - Smith, Caren E A1 - Dupuis, Josée A1 - Herman, Mark A A1 - McKeown, Nicola M AB -

BACKGROUND: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

METHODS: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

RESULTS: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; <0.0001), but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, =0.001) but not the lowest SSB consumers (=0.84; =0.0005).

CONCLUSIONS: Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.

VL - 14 IS - 4 ER - TY - JOUR T1 - Rare genetic variants explain missing heritability in smoking. JF - Nat Hum Behav Y1 - 2022 A1 - Jang, Seon-Kyeong A1 - Evans, Luke A1 - Fialkowski, Allison A1 - Arnett, Donna K A1 - Ashley-Koch, Allison E A1 - Barnes, Kathleen C A1 - Becker, Diane M A1 - Bis, Joshua C A1 - Blangero, John A1 - Bleecker, Eugene R A1 - Boorgula, Meher Preethi A1 - Bowden, Donald W A1 - Brody, Jennifer A A1 - Cade, Brian E A1 - Jenkins, Brenda W Campbell A1 - Carson, April P A1 - Chavan, Sameer A1 - Cupples, L Adrienne A1 - Custer, Brian A1 - Damrauer, Scott M A1 - David, Sean P A1 - de Andrade, Mariza A1 - Dinardo, Carla L A1 - Fingerlin, Tasha E A1 - Fornage, Myriam A1 - Freedman, Barry I A1 - Garrett, Melanie E A1 - Gharib, Sina A A1 - Glahn, David C A1 - Haessler, Jeffrey A1 - Heckbert, Susan R A1 - Hokanson, John E A1 - Hou, Lifang A1 - Hwang, Shih-Jen A1 - Hyman, Matthew C A1 - Judy, Renae A1 - Justice, Anne E A1 - Kaplan, Robert C A1 - Kardia, Sharon L R A1 - Kelly, Shannon A1 - Kim, Wonji A1 - Kooperberg, Charles A1 - Levy, Daniel A1 - Lloyd-Jones, Donald M A1 - Loos, Ruth J F A1 - Manichaikul, Ani W A1 - Gladwin, Mark T A1 - Martin, Lisa Warsinger A1 - Nouraie, Mehdi A1 - Melander, Olle A1 - Meyers, Deborah A A1 - Montgomery, Courtney G A1 - North, Kari E A1 - Oelsner, Elizabeth C A1 - Palmer, Nicholette D A1 - Payton, Marinelle A1 - Peljto, Anna L A1 - Peyser, Patricia A A1 - Preuss, Michael A1 - Psaty, Bruce M A1 - Qiao, Dandi A1 - Rader, Daniel J A1 - Rafaels, Nicholas A1 - Redline, Susan A1 - Reed, Robert M A1 - Reiner, Alexander P A1 - Rich, Stephen S A1 - Rotter, Jerome I A1 - Schwartz, David A A1 - Shadyab, Aladdin H A1 - Silverman, Edwin K A1 - Smith, Nicholas L A1 - Smith, J Gustav A1 - Smith, Albert V A1 - Smith, Jennifer A A1 - Tang, Weihong A1 - Taylor, Kent D A1 - Telen, Marilyn J A1 - Vasan, Ramachandran S A1 - Gordeuk, Victor R A1 - Wang, Zhe A1 - Wiggins, Kerri L A1 - Yanek, Lisa R A1 - Yang, Ivana V A1 - Young, Kendra A A1 - Young, Kristin L A1 - Zhang, Yingze A1 - Liu, Dajiang J A1 - Keller, Matthew C A1 - Vrieze, Scott AB -

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

ER - TY - JOUR T1 - Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. JF - Nat Genet Y1 - 2023 A1 - Chen, Fang A1 - Wang, Xingyan A1 - Jang, Seon-Kyeong A1 - Quach, Bryan C A1 - Weissenkampen, J Dylan A1 - Khunsriraksakul, Chachrit A1 - Yang, Lina A1 - Sauteraud, Renan A1 - Albert, Christine M A1 - Allred, Nicholette D D A1 - Arnett, Donna K A1 - Ashley-Koch, Allison E A1 - Barnes, Kathleen C A1 - Barr, R Graham A1 - Becker, Diane M A1 - Bielak, Lawrence F A1 - Bis, Joshua C A1 - Blangero, John A1 - Boorgula, Meher Preethi A1 - Chasman, Daniel I A1 - Chavan, Sameer A1 - Chen, Yii-der I A1 - Chuang, Lee-Ming A1 - Correa, Adolfo A1 - Curran, Joanne E A1 - David, Sean P A1 - Fuentes, Lisa de Las A1 - Deka, Ranjan A1 - Duggirala, Ravindranath A1 - Faul, Jessica D A1 - Garrett, Melanie E A1 - Gharib, Sina A A1 - Guo, Xiuqing A1 - Hall, Michael E A1 - Hawley, Nicola L A1 - He, Jiang A1 - Hobbs, Brian D A1 - Hokanson, John E A1 - Hsiung, Chao A A1 - Hwang, Shih-Jen A1 - Hyde, Thomas M A1 - Irvin, Marguerite R A1 - Jaffe, Andrew E A1 - Johnson, Eric O A1 - Kaplan, Robert A1 - Kardia, Sharon L R A1 - Kaufman, Joel D A1 - Kelly, Tanika N A1 - Kleinman, Joel E A1 - Kooperberg, Charles A1 - Lee, I-Te A1 - Levy, Daniel A1 - Lutz, Sharon M A1 - Manichaikul, Ani W A1 - Martin, Lisa W A1 - Marx, Olivia A1 - McGarvey, Stephen T A1 - Minster, Ryan L A1 - Moll, Matthew A1 - Moussa, Karine A A1 - Naseri, Take A1 - North, Kari E A1 - Oelsner, Elizabeth C A1 - Peralta, Juan M A1 - Peyser, Patricia A A1 - Psaty, Bruce M A1 - Rafaels, Nicholas A1 - Raffield, Laura M A1 - Reupena, Muagututi'a Sefuiva A1 - Rich, Stephen S A1 - Rotter, Jerome I A1 - Schwartz, David A A1 - Shadyab, Aladdin H A1 - Sheu, Wayne H-H A1 - Sims, Mario A1 - Smith, Jennifer A A1 - Sun, Xiao A1 - Taylor, Kent D A1 - Telen, Marilyn J A1 - Watson, Harold A1 - Weeks, Daniel E A1 - Weir, David R A1 - Yanek, Lisa R A1 - Young, Kendra A A1 - Young, Kristin L A1 - Zhao, Wei A1 - Hancock, Dana B A1 - Jiang, Bibo A1 - Vrieze, Scott A1 - Liu, Dajiang J KW - Biology KW - Drug Repositioning KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Humans KW - Polymorphism, Single Nucleotide KW - Tobacco Use KW - Transcriptome AB -

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

VL - 55 IS - 2 ER -