@article {1359, title = {Association between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Feb 01}, pages = {100-12}, abstract = {

BACKGROUND: Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.

METHODS AND RESULTS: Continuous ABI and PAD (ABI <=0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ≈2.5 million single nucleotide polymorphisms (SNPs) in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed effects inverse variance weighted meta-analyses. There were a total of 41 692 participants of European ancestry (≈60\% women, mean ABI 1.02 to 1.19), including 3409 participants with PAD and with genome-wide association study data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β=-0.006, P=2.46{\texttimes}10(-8)). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16 717). The association for rs10757269 strengthened in the combined discovery and replication analysis (P=2.65{\texttimes}10(-9)). No other SNP associations for ABI or PAD achieved genome-wide significance. However, 2 previously reported candidate genes for PAD and 1 SNP associated with coronary artery disease were associated with ABI: DAB21P (rs13290547, P=3.6{\texttimes}10(-5)), CYBA (rs3794624, P=6.3{\texttimes}10(-5)), and rs1122608 (LDLR, P=0.0026).

CONCLUSIONS: Genome-wide association studies in more than 40 000 individuals identified 1 genome wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for coronary artery disease are associated with ABI.

}, keywords = {Adult, Age Factors, Aged, Aged, 80 and over, Alleles, Ankle Brachial Index, Chromosomes, Human, Pair 9, Cohort Studies, Cyclin-Dependent Kinase Inhibitor p15, Female, Genome-Wide Association Study, Genotype, HapMap Project, Humans, Logistic Models, Male, Middle Aged, Peripheral Vascular Diseases, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sex Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.961292}, author = {Murabito, Joanne M and White, Charles C and Kavousi, Maryam and Sun, Yan V and Feitosa, Mary F and Nambi, Vijay and Lamina, Claudia and Schillert, Arne and Coassin, Stefan and Bis, Joshua C and Broer, Linda and Crawford, Dana C and Franceschini, Nora and Frikke-Schmidt, Ruth and Haun, Margot and Holewijn, Suzanne and Huffman, Jennifer E and Hwang, Shih-Jen and Kiechl, Stefan and Kollerits, Barbara and Montasser, May E and Nolte, Ilja M and Rudock, Megan E and Senft, Andrea and Teumer, Alexander and van der Harst, Pim and Vitart, Veronique and Waite, Lindsay L and Wood, Andrew R and Wassel, Christina L and Absher, Devin M and Allison, Matthew A and Amin, Najaf and Arnold, Alice and Asselbergs, Folkert W and Aulchenko, Yurii and Bandinelli, Stefania and Barbalic, Maja and Boban, Mladen and Brown-Gentry, Kristin and Couper, David J and Criqui, Michael H and Dehghan, Abbas and den Heijer, Martin and Dieplinger, Benjamin and Ding, Jingzhong and D{\"o}rr, Marcus and Espinola-Klein, Christine and Felix, Stephan B and Ferrucci, Luigi and Folsom, Aaron R and Fraedrich, Gustav and Gibson, Quince and Goodloe, Robert and Gunjaca, Grgo and Haltmayer, Meinhard and Heiss, Gerardo and Hofman, Albert and Kieback, Arne and Kiemeney, Lambertus A and Kolcic, Ivana and Kullo, Iftikhar J and Kritchevsky, Stephen B and Lackner, Karl J and Li, Xiaohui and Lieb, Wolfgang and Lohman, Kurt and Meisinger, Christa and Melzer, David and Mohler, Emile R and Mudnic, Ivana and Mueller, Thomas and Navis, Gerjan and Oberhollenzer, Friedrich and Olin, Jeffrey W and O{\textquoteright}Connell, Jeff and O{\textquoteright}Donnell, Christopher J and Palmas, Walter and Penninx, Brenda W and Petersmann, Astrid and Polasek, Ozren and Psaty, Bruce M and Rantner, Barbara and Rice, Ken and Rivadeneira, Fernando and Rotter, Jerome I and Seldenrijk, Adrie and Stadler, Marietta and Summerer, Monika and Tanaka, Toshiko and Tybjaerg-Hansen, Anne and Uitterlinden, Andr{\'e} G and van Gilst, Wiek H and Vermeulen, Sita H and Wild, Sarah H and Wild, Philipp S and Willeit, Johann and Zeller, Tanja and Zemunik, Tatijana and Zgaga, Lina and Assimes, Themistocles L and Blankenberg, Stefan and Boerwinkle, Eric and Campbell, Harry and Cooke, John P and de Graaf, Jacqueline and Herrington, David and Kardia, Sharon L R and Mitchell, Braxton D and Murray, Anna and M{\"u}nzel, Thomas and Newman, Anne B and Oostra, Ben A and Rudan, Igor and Shuldiner, Alan R and Snieder, Harold and van Duijn, Cornelia M and V{\"o}lker, Uwe and Wright, Alan F and Wichmann, H-Erich and Wilson, James F and Witteman, Jacqueline C M and Liu, Yongmei and Hayward, Caroline and Borecki, Ingrid B and Ziegler, Andreas and North, Kari E and Cupples, L Adrienne and Kronenberg, Florian} } @article {6626, title = {Fine Mapping and Identification of BMI Loci in African Americans.}, journal = {Am J Hum Genet}, volume = {93}, year = {2013}, month = {2013 Oct 3}, pages = {661-71}, abstract = {

Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8~{\texttimes} 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6~{\texttimes} 10(-8)) and DHX34 (rs4802349, p = 1.2~{\texttimes} 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.

}, keywords = {Adult, African Americans, Aged, Aged, 80 and over, Body Mass Index, Female, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Young Adult}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2013.08.012}, author = {Gong, Jian and Schumacher, Fredrick and Lim, Unhee and Hindorff, Lucia A and Haessler, Jeff and Buyske, Steven and Carlson, Christopher S and Rosse, Stephanie and B{\r u}zkov{\'a}, Petra and Fornage, Myriam and Gross, Myron and Pankratz, Nathan and Pankow, James S and Schreiner, Pamela J and Cooper, Richard and Ehret, Georg and Gu, C Charles and Houston, Denise and Irvin, Marguerite R and Jackson, Rebecca and Kuller, Lew and Henderson, Brian and Cheng, Iona and Wilkens, Lynne and Leppert, Mark and Lewis, Cora E and Li, Rongling and Nguyen, Khanh-Dung H and Goodloe, Robert and Farber-Eger, Eric and Boston, Jonathan and Dilks, Holli H and Ritchie, Marylyn D and Fowke, Jay and Pooler, Loreall and Graff, Misa and Fernandez-Rhodes, Lindsay and Cochrane, Barbara and Boerwinkle, Eric and Kooperberg, Charles and Matise, Tara C and Le Marchand, Lo{\"\i}c and Crawford, Dana C and Haiman, Christopher A and North, Kari E and Peters, Ulrike} } @article {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {

BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} }