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1.  Sequence Variation in TMEM18 in Association with Body Mass Index: The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study 
Background
Genome-wide association studies (GWAS) 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 variation influencing BMI.
Methods and Results
We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from three 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 (MAF <1%) were analyzed using a burden test and the Sequence Kernel of Association Test (SKAT). Results from the three cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m2 higher for each copy of the G allele of SNP rs7596758 (MAF=29%, p=3.46 × 10−4) using a Bonferroni threshold of p <4.6 × 10−4). Analyses conditional on previous GWAS SNPs associated with BMI in the region led to attenuation of this signal and uncovered another independent (r2<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’ GWAS region.
Conclusions
Targeted sequencing around TMEM18 identified two novel BMI variants with possible regulatory function.
doi:10.1161/CIRCGENETICS.13.000067
PMCID: PMC4135723  PMID: 24951660
body mass index; genetic association; targeted resequencing; TMEM18
2.  Heritability of Prevalent Vertebral Fracture and Volumetric Bone Mineral Density and Geometry at the Lumbar Spine in Three Generations of the Framingham Study 
Genetic factors likely contribute to the risk for vertebral fractures; however, there are few studies on the genetic contributions to vertebral fracture (VFrx), vertebral volumetric bone mineral density (vBMD) and geometry. Also the heritability (h2) for VFrx and its genetic correlation with phenotypes contributing to VFrx risk have not been established. This study aims to estimate the h2 of vertebral fracture, vBMD and cross-sectional-area (CSA) derived from quantitative computed tomography (QCT) scans, and to estimate the extent to which they share common genetic association in adults of European ancestry from three generations of Framingham Heart Study (FHS) families. Members of the FHS families were assessed for VFrx by lateral radiographs or QCT lateral scout views at 13 vertebral levels (T4-L4) using Genant’s semi-quantitative (SQ) scale (grades 0–3). Vertebral fracture was defined as having at least 25% reduction in height of any vertebra. We also analyzed QCT scans at the L3 level for integral (In.BMD) and trabecular (Tb.BMD) vBMD and cross-sectional area (CSA). Heritability estimates were calculated, and bivariate genetic correlation analysis was performed, adjusting for various covariates. For VFrx, we analyzed 4,099 individuals (148 VFrx cases) including 2,082 women and 2,017 men from 3 generations. Estimates of crude and multivariable-adjusted h2 were 0.43 to 0.69 (P< 1.1×10−2). 3,333 individuals including 1,737 men and 1,596 women from 2 generations had VFrx status and QCT-derived vBMD and CSA information. Estimates of crude and multivariable-adjusted h2 for vBMD and CSA ranged from 0.27 to 0.51. In a bivariate analysis, there was a moderate genetic correlation between VFrx and multivariable-adjusted In.BMD (−0.22) and Tb.BMD (−0.29). Our study suggests vertebral fracture, vertebral vBMD and CSA in adults of European ancestry are heritable, underscoring the importance of further work to identify the specific variants underlying genetic susceptibility to vertebral fracture, bone density and geometry.
doi:10.1002/jbmr.1537
PMCID: PMC3375687  PMID: 22222934
vertebral fracture; bone mineral density; heritability; QCT
3.  The distribution of circulating microRNA and their relation to coronary disease 
F1000Research  2012;1:50.
Background: MicroRNAs (miRNAs) are small RNAs that regulate gene expression by suppressing protein translation and may influence RNA expression. MicroRNAs are detected in extracellular locations such as plasma; however, the extent of miRNA expression in plasma its relation to cardiovascular disease is not clear and many clinical studies have utilized array-based platforms with poor reproducibility.
Methods and Results: Initially, to define distribution of miRNA in human blood; whole blood, platelets, mononuclear cells, plasma, and serum from 5 normal individuals were screened for 852 miRNAs using high-throughput micro-fluidic quantitative RT-PCR (qRT-PCR). In total; 609, 448, 658, 147, and 178 miRNAs were found to be expressed in moderate to high levels in whole blood, platelets, mononuclear cells, plasma, and serum, respectively, with some miRNAs uniquely expressed. To determine the cardiovascular relevance of blood miRNA expression, plasma miRNA (n=852) levels were measured in 83 patients presenting for cardiac catheterization. Eight plasma miRNAs were found to have over 2-fold increased expression in patients with significant coronary disease (≥70% stenosis) as compared to those with minimal coronary disease (less than 70% stenosis) or normal coronary arteries. Expression of miR-494, miR-490-3p, and miR-769-3p were found to have significantly different levels of expression. Using a multivariable regression model including cardiovascular risk factors and medications, hsa-miR-769-3p was found to be significantly correlated with the presence of significant coronary atherosclerosis.
Conclusions: This study utilized a superior high-throughput qRT-PCR based method and found that miRNAs are found to be widely expressed in human blood with differences expressed between cellular and extracellular fractions. Importantly, specific miRNAs from circulating plasma are associated with the presence of significant coronary disease.
doi:10.12688/f1000research.1-50.v1
PMCID: PMC3752638  PMID: 24358814
4.  Vitamin D Status, Receptor Gene Polymorphisms, and Supplementation on Tuberculosis: A Systematic Review of Case-Control Studies and Randomized Controlled Trials 
Objective
To investigate the impacts of vitamin D status, supplementation and vitamin D receptor (VDR) gene polymorphisms on tuberculosis (TB).
Methods
We conducted a systematic review of published studies pertaining to case-control and randomized-control trials from 2002 to 2014 using the PubMed database.
Results and conclusion
Individuals with TB have lower vitamin D status than healthy individuals. Some VDR gene polymorphisms are associated with increased susceptibility to TB while others may not. Supplementation with vitamin D leads to improved clinical outcomes. However, further studies with a larger patient population and different ethnicities are needed to confirm these effects.
doi:10.1016/j.jcte.2014.08.001
PMCID: PMC4295520  PMID: 25599020
Vitamin D; Vitamin D Receptor; Polymorphism; Tuberculosis; Supplementation; Clinical Trials
5.  Multi-ethnic fine-mapping of 14 central adiposity loci 
Human Molecular Genetics  2014;23(17):4738-4744.
The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowing the signals remains necessary. Twelve of 14 loci identified in GIANT EA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Trans-ethnic analyses at five loci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86 and ITPR2-SSPN) substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role. Meta-analysis results for WHR were obtained from 77 167 EA participants from GIANT and 23 564 AA participants from the African Ancestry Anthropometry Genetics Consortium. For fine mapping we interrogated SNPs within ±250 kb flanking regions of 14 previously reported index SNPs from loci discovered in EA populations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality.
doi:10.1093/hmg/ddu183
PMCID: PMC4119415  PMID: 24760767
6.  New genetic loci link adipose and insulin biology to body fat distribution 
Shungin, Dmitry | Winkler, Thomas W | Croteau-Chonka, Damien C | Ferreira, Teresa | Locke, Adam E | Mägi, Reedik | Strawbridge, Rona J | Pers, Tune H | Fischer, Krista | Justice, Anne E | Workalemahu, Tsegaselassie | Wu, Joseph M.W. | Buchkovich, Martin L | Heard-Costa, Nancy L | Roman, Tamara S | Drong, Alexander W | Song, Ci | Gustafsson, Stefan | Day, Felix R | Esko, Tonu | Fall, Tove | Kutalik, Zoltán | Luan, Jian’an | Randall, Joshua C | Scherag, André | Vedantam, Sailaja | Wood, Andrew R | Chen, Jin | Fehrmann, Rudolf | Karjalainen, Juha | Kahali, Bratati | Liu, Ching-Ti | Schmidt, Ellen M | Absher, Devin | Amin, Najaf | Anderson, Denise | Beekman, Marian | Bragg-Gresham, Jennifer L | Buyske, Steven | Demirkan, Ayse | Ehret, Georg B | Feitosa, Mary F | Goel, Anuj | Jackson, Anne U | Johnson, Toby | Kleber, Marcus E | Kristiansson, Kati | Mangino, Massimo | Leach, Irene Mateo | Medina-Gomez, Carolina | Palmer, Cameron D | Pasko, Dorota | Pechlivanis, Sonali | Peters, Marjolein J | Prokopenko, Inga | Stančáková, Alena | Sung, Yun Ju | Tanaka, Toshiko | Teumer, Alexander | Van Vliet-Ostaptchouk, Jana V | Yengo, Loïc | Zhang, Weihua | Albrecht, Eva | Ärnlöv, Johan | Arscott, Gillian M | Bandinelli, Stefania | Barrett, Amy | Bellis, Claire | Bennett, Amanda J | Berne, Christian | Blüher, Matthias | Böhringer, Stefan | Bonnet, Fabrice | Böttcher, Yvonne | Bruinenberg, Marcel | Carba, Delia B | Caspersen, Ida H | Clarke, Robert | Daw, E Warwick | Deelen, Joris | Deelman, Ewa | Delgado, Graciela | Doney, Alex SF | Eklund, Niina | Erdos, Michael R | Estrada, Karol | Eury, Elodie | Friedrich, Nele | Garcia, Melissa E | Giedraitis, Vilmantas | Gigante, Bruna | Go, Alan S | Golay, Alain | Grallert, Harald | Grammer, Tanja B | Gräßler, Jürgen | Grewal, Jagvir | Groves, Christopher J | Haller, Toomas | Hallmans, Goran | Hartman, Catharina A | Hassinen, Maija | Hayward, Caroline | Heikkilä, Kauko | Herzig, Karl-Heinz | Helmer, Quinta | Hillege, Hans L | Holmen, Oddgeir | Hunt, Steven C | Isaacs, Aaron | Ittermann, Till | James, Alan L | Johansson, Ingegerd | Juliusdottir, Thorhildur | Kalafati, Ioanna-Panagiota | Kinnunen, Leena | Koenig, Wolfgang | Kooner, Ishminder K | Kratzer, Wolfgang | Lamina, Claudia | Leander, Karin | Lee, Nanette R | Lichtner, Peter | Lind, Lars | Lindström, Jaana | Lobbens, Stéphane | Lorentzon, Mattias | Mach, François | Magnusson, Patrik KE | Mahajan, Anubha | McArdle, Wendy L | Menni, Cristina | Merger, Sigrun | Mihailov, Evelin | Milani, Lili | Mills, Rebecca | Moayyeri, Alireza | Monda, Keri L | Mooijaart, Simon P | Mühleisen, Thomas W | Mulas, Antonella | Müller, Gabriele | Müller-Nurasyid, Martina | Nagaraja, Ramaiah | Nalls, Michael A | Narisu, Narisu | Glorioso, Nicola | Nolte, Ilja M | Olden, Matthias | Rayner, Nigel W | Renstrom, Frida | Ried, Janina S | Robertson, Neil R | Rose, Lynda M | Sanna, Serena | Scharnagl, Hubert | Scholtens, Salome | Sennblad, Bengt | Seufferlein, Thomas | Sitlani, Colleen M | Smith, Albert Vernon | Stirrups, Kathleen | Stringham, Heather M | Sundström, Johan | Swertz, Morris A | Swift, Amy J | Syvänen, Ann-Christine | Tayo, Bamidele O | Thorand, Barbara | Thorleifsson, Gudmar | Tomaschitz, Andreas | Troffa, Chiara | van Oort, Floor VA | Verweij, Niek | Vonk, Judith M | Waite, Lindsay L | Wennauer, Roman | Wilsgaard, Tom | Wojczynski, Mary K | Wong, Andrew | Zhang, Qunyuan | Zhao, Jing Hua | Brennan, Eoin P. | Choi, Murim | Eriksson, Per | Folkersen, Lasse | Franco-Cereceda, Anders | Gharavi, Ali G | Hedman, Åsa K | Hivert, Marie-France | Huang, Jinyan | Kanoni, Stavroula | Karpe, Fredrik | Keildson, Sarah | Kiryluk, Krzysztof | Liang, Liming | Lifton, Richard P | Ma, Baoshan | McKnight, Amy J | McPherson, Ruth | Metspalu, Andres | Min, Josine L | Moffatt, Miriam F | Montgomery, Grant W | Murabito, Joanne M | Nicholson, George | Nyholt, Dale R | Olsson, Christian | Perry, John RB | Reinmaa, Eva | Salem, Rany M | Sandholm, Niina | Schadt, Eric E | Scott, Robert A | Stolk, Lisette | Vallejo, Edgar E. | Westra, Harm-Jan | Zondervan, Krina T | Amouyel, Philippe | Arveiler, Dominique | Bakker, Stephan JL | Beilby, John | Bergman, Richard N | Blangero, John | Brown, Morris J | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chines, Peter S | Claudi-Boehm, Simone | Collins, Francis S | Crawford, Dana C | Danesh, John | de Faire, Ulf | de Geus, Eco JC | Dörr, Marcus | Erbel, Raimund | Eriksson, Johan G | Farrall, Martin | Ferrannini, Ele | Ferrières, Jean | Forouhi, Nita G | Forrester, Terrence | Franco, Oscar H | Gansevoort, Ron T | Gieger, Christian | Gudnason, Vilmundur | Haiman, Christopher A | Harris, Tamara B | Hattersley, Andrew T | Heliövaara, Markku | Hicks, Andrew A | Hingorani, Aroon D | Hoffmann, Wolfgang | Hofman, Albert | Homuth, Georg | Humphries, Steve E | Hyppönen, Elina | Illig, Thomas | Jarvelin, Marjo-Riitta | Johansen, Berit | Jousilahti, Pekka | Jula, Antti M | Kaprio, Jaakko | Kee, Frank | Keinanen-Kiukaanniemi, Sirkka M | Kooner, Jaspal S | Kooperberg, Charles | Kovacs, Peter | Kraja, Aldi T | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Lakka, Timo A | Langenberg, Claudia | Le Marchand, Loic | Lehtimäki, Terho | Lyssenko, Valeriya | Männistö, Satu | Marette, André | Matise, Tara C | McKenzie, Colin A | McKnight, Barbara | Musk, Arthur W | Möhlenkamp, Stefan | Morris, Andrew D | Nelis, Mari | Ohlsson, Claes | Oldehinkel, Albertine J | Ong, Ken K | Palmer, Lyle J | Penninx, Brenda W | Peters, Annette | Pramstaller, Peter P | Raitakari, Olli T | Rankinen, Tuomo | Rao, DC | Rice, Treva K | Ridker, Paul M | Ritchie, Marylyn D. | Rudan, Igor | Salomaa, Veikko | Samani, Nilesh J | Saramies, Jouko | Sarzynski, Mark A | Schwarz, Peter EH | Shuldiner, Alan R | Staessen, Jan A | Steinthorsdottir, Valgerdur | Stolk, Ronald P | Strauch, Konstantin | Tönjes, Anke | Tremblay, Angelo | Tremoli, Elena | Vohl, Marie-Claude | Völker, Uwe | Vollenweider, Peter | Wilson, James F | Witteman, Jacqueline C | Adair, Linda S | Bochud, Murielle | Boehm, Bernhard O | Bornstein, Stefan R | Bouchard, Claude | Cauchi, Stéphane | Caulfield, Mark J | Chambers, John C | Chasman, Daniel I | Cooper, Richard S | Dedoussis, George | Ferrucci, Luigi | Froguel, Philippe | Grabe, Hans-Jörgen | Hamsten, Anders | Hui, Jennie | Hveem, Kristian | Jöckel, Karl-Heinz | Kivimaki, Mika | Kuh, Diana | Laakso, Markku | Liu, Yongmei | März, Winfried | Munroe, Patricia B | Njølstad, Inger | Oostra, Ben A | Palmer, Colin NA | Pedersen, Nancy L | Perola, Markus | Pérusse, Louis | Peters, Ulrike | Power, Chris | Quertermous, Thomas | Rauramaa, Rainer | Rivadeneira, Fernando | Saaristo, Timo E | Saleheen, Danish | Sinisalo, Juha | Slagboom, P Eline | Snieder, Harold | Spector, Tim D | Stefansson, Kari | Stumvoll, Michael | Tuomilehto, Jaakko | Uitterlinden, André G | Uusitupa, Matti | van der Harst, Pim | Veronesi, Giovanni | Walker, Mark | Wareham, Nicholas J | Watkins, Hugh | Wichmann, H-Erich | Abecasis, Goncalo R | Assimes, Themistocles L | Berndt, Sonja I | Boehnke, Michael | Borecki, Ingrid B | Deloukas, Panos | Franke, Lude | Frayling, Timothy M | Groop, Leif C | Hunter, David J. | Kaplan, Robert C | O’Connell, Jeffrey R | Qi, Lu | Schlessinger, David | Strachan, David P | Thorsteinsdottir, Unnur | van Duijn, Cornelia M | Willer, Cristen J | Visscher, Peter M | Yang, Jian | Hirschhorn, Joel N | Zillikens, M Carola | McCarthy, Mark I | Speliotes, Elizabeth K | North, Kari E | Fox, Caroline S | Barroso, Inês | Franks, Paul W | Ingelsson, Erik | Heid, Iris M | Loos, Ruth JF | Cupples, L Adrienne | Morris, Andrew P | Lindgren, Cecilia M | Mohlke, Karen L
Nature  2015;518(7538):187-196.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10−8). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
doi:10.1038/nature14132
PMCID: PMC4338562  PMID: 25673412
7.  Meta-analysis of loci associated with age at natural menopause in African-American women 
Human Molecular Genetics  2014;23(12):3327-3342.
Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA.
doi:10.1093/hmg/ddu041
PMCID: PMC4030781  PMID: 24493794
8.  Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium 
Moayyeri, Alireza | Hsu, Yi-Hsiang | Karasik, David | Estrada, Karol | Xiao, Su-Mei | Nielson, Carrie | Srikanth, Priya | Giroux, Sylvie | Wilson, Scott G. | Zheng, Hou-Feng | Smith, Albert V. | Pye, Stephen R. | Leo, Paul J. | Teumer, Alexander | Hwang, Joo-Yeon | Ohlsson, Claes | McGuigan, Fiona | Minster, Ryan L. | Hayward, Caroline | Olmos, José M. | Lyytikäinen, Leo-Pekka | Lewis, Joshua R. | Swart, Karin M.A. | Masi, Laura | Oldmeadow, Chris | Holliday, Elizabeth G. | Cheng, Sulin | van Schoor, Natasja M. | Harvey, Nicholas C. | Kruk, Marcin | del Greco M, Fabiola | Igl, Wilmar | Trummer, Olivia | Grigoriou, Efi | Luben, Robert | Liu, Ching-Ti | Zhou, Yanhua | Oei, Ling | Medina-Gomez, Carolina | Zmuda, Joseph | Tranah, Greg | Brown, Suzanne J. | Williams, Frances M. | Soranzo, Nicole | Jakobsdottir, Johanna | Siggeirsdottir, Kristin | Holliday, Kate L. | Hannemann, Anke | Go, Min Jin | Garcia, Melissa | Polasek, Ozren | Laaksonen, Marika | Zhu, Kun | Enneman, Anke W. | McEvoy, Mark | Peel, Roseanne | Sham, Pak Chung | Jaworski, Maciej | Johansson, Åsa | Hicks, Andrew A. | Pludowski, Pawel | Scott, Rodney | Dhonukshe-Rutten, Rosalie A.M. | van der Velde, Nathalie | Kähönen, Mika | Viikari, Jorma S. | Sievänen, Harri | Raitakari, Olli T. | González-Macías, Jesús | Hernández, Jose L. | Mellström, Dan | Ljunggren, Östen | Cho, Yoon Shin | Völker, Uwe | Nauck, Matthias | Homuth, Georg | Völzke, Henry | Haring, Robin | Brown, Matthew A. | McCloskey, Eugene | Nicholson, Geoffrey C. | Eastell, Richard | Eisman, John A. | Jones, Graeme | Reid, Ian R. | Dennison, Elaine M. | Wark, John | Boonen, Steven | Vanderschueren, Dirk | Wu, Frederick C.W. | Aspelund, Thor | Richards, J. Brent | Bauer, Doug | Hofman, Albert | Khaw, Kay-Tee | Dedoussis, George | Obermayer-Pietsch, Barbara | Gyllensten, Ulf | Pramstaller, Peter P. | Lorenc, Roman S. | Cooper, Cyrus | Kung, Annie Wai Chee | Lips, Paul | Alen, Markku | Attia, John | Brandi, Maria Luisa | de Groot, Lisette C.P.G.M. | Lehtimäki, Terho | Riancho, José A. | Campbell, Harry | Liu, Yongmei | Harris, Tamara B. | Akesson, Kristina | Karlsson, Magnus | Lee, Jong-Young | Wallaschofski, Henri | Duncan, Emma L. | O'Neill, Terence W. | Gudnason, Vilmundur | Spector, Timothy D. | Rousseau, François | Orwoll, Eric | Cummings, Steven R. | Wareham, Nick J. | Rivadeneira, Fernando | Uitterlinden, Andre G. | Prince, Richard L. | Kiel, Douglas P. | Reeve, Jonathan | Kaptoge, Stephen K.
Human Molecular Genetics  2014;23(11):3054-3068.
Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n = 14 260), velocity of sound (VOS; n = 15 514) and BMD (n = 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n = 11 452) and new genotyping in 15 cohorts (de novo n = 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 × 10−8) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 × 10−14). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 × 10−6 also had the expected direction of association with any fracture (P < 0.05), including three SNPs with P < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, this GWA study reveals the effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with potential implications for better understanding of osteoporosis pathophysiology.
doi:10.1093/hmg/ddt675
PMCID: PMC4038791  PMID: 24430505
9.  Strategies to Design and Analyze Targeted Sequencing Data: The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study 
Background
Genome-wide association studies (GWAS) have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study aims to follow up GWAS signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular related traits.
Methods and Results
The study included 4,231 participants from three CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with one or more of 14 phenotypes. A total of 52,736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain p-values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied two approaches: collapsed aggregate statistics and joint analysis of variants using the Sequence Kernel Association Test.
Conclusions
We sequenced 77 genomic loci in participants from three cohorts. We established a set of filters to identify high-quality variants, and implemented statistical and bioinformatics strategies to analyze the sequence data, and identify potentially functional variants within GWAS loci.
doi:10.1161/CIRCGENETICS.113.000350
PMCID: PMC4176824  PMID: 24951659
genetics; epidemiology; CHARGE; sampling; targeted sequencing
10.  A randomized trial of the clinical utility of genetic testing for obesity: Design and implementation considerations 
Clinical trials (London, England)  2013;11(1):102-113.
Background
Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts. Currently, testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies. Despite the availability of this type of testing, there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses.
Purpose
We describe the key issues in the design and implementation of a randomized controlled trial examining the clinical utility of providing genetic risk information for obesity.
Methods
Participants are being recruited from the Coriell Personalized Medicine Collaborative, an ongoing, longitudinal research cohort study designed to determine the utility of personal genome information in health management and clinical decision-making. The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity, which are based on lifestyle risk factors. The trial employs a 2x2 factorial design in order to examine the effects of providing genetic risk information for obesity, alone or in combination with lifestyle risk information, on participants’ psychological responses, behavioral intentions, health behaviors, and weight.
Results
The factorial design generated four experimental arms based on communication of estimated risk to participants: 1) no risk feedback (control), 2) genetic risk only, 3) lifestyle risk only, 4) both genetic and lifestyle risk (combined). Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical standards and methodological rigor. Following the launch of the trial in September 2011, implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol. Although monitoring of these efforts is ongoing, initial observations show a doubling of enrollment and reduced attrition.
Limitations
The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months. This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases. This nesting in a larger study may attenuate the effects of obesity risk information and has implications for the generalizability of study findings.
Conclusions
This randomized trial examines value of obesity genetic information, both when provided independently and when combined with lifestyle risk assessment, to motivate individuals to engage in healthy lifestyle behaviors. Study findings will guide future intervention efforts to effectively communicate genetic risk information.
doi:10.1177/1740774513508029
PMCID: PMC3946398  PMID: 24216219
obesity; personalized medicine; clinical utility; genetic testing; risk assessment; enrollment strategies; differential attrition; randomized controlled trial
11.  Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins 
Postmus, Iris | Trompet, Stella | Deshmukh, Harshal A. | Barnes, Michael R. | Li, Xiaohui | Warren, Helen R. | Chasman, Daniel I. | Zhou, Kaixin | Arsenault, Benoit J. | Donnelly, Louise A. | Wiggins, Kerri L. | Avery, Christy L. | Griffin, Paula | Feng, QiPing | Taylor, Kent D. | Li, Guo | Evans, Daniel S. | Smith, Albert V. | de Keyser, Catherine E. | Johnson, Andrew D. | de Craen, Anton J. M. | Stott, David J. | Buckley, Brendan M. | Ford, Ian | Westendorp, Rudi G. J. | Eline Slagboom, P. | Sattar, Naveed | Munroe, Patricia B. | Sever, Peter | Poulter, Neil | Stanton, Alice | Shields, Denis C. | O’Brien, Eoin | Shaw-Hawkins, Sue | Ida Chen, Y.-D. | Nickerson, Deborah A. | Smith, Joshua D. | Pierre Dubé, Marie | Matthijs Boekholdt, S. | Kees Hovingh, G. | Kastelein, John J. P. | McKeigue, Paul M. | Betteridge, John | Neil, Andrew | Durrington, Paul N. | Doney, Alex | Carr, Fiona | Morris, Andrew | McCarthy, Mark I. | Groop, Leif | Ahlqvist, Emma | Bis, Joshua C. | Rice, Kenneth | Smith, Nicholas L. | Lumley, Thomas | Whitsel, Eric A. | Stürmer, Til | Boerwinkle, Eric | Ngwa, Julius S. | O’Donnell, Christopher J. | Vasan, Ramachandran S. | Wei, Wei-Qi | Wilke, Russell A. | Liu, Ching-Ti | Sun, Fangui | Guo, Xiuqing | Heckbert, Susan R | Post, Wendy | Sotoodehnia, Nona | Arnold, Alice M. | Stafford, Jeanette M. | Ding, Jingzhong | Herrington, David M. | Kritchevsky, Stephen B. | Eiriksdottir, Gudny | Launer, Leonore J. | Harris, Tamara B. | Chu, Audrey Y. | Giulianini, Franco | MacFadyen, Jean G. | Barratt, Bryan J. | Nyberg, Fredrik | Stricker, Bruno H. | Uitterlinden, André G. | Hofman, Albert | Rivadeneira, Fernando | Emilsson, Valur | Franco, Oscar H. | Ridker, Paul M. | Gudnason, Vilmundur | Liu, Yongmei | Denny, Joshua C. | Ballantyne, Christie M. | Rotter, Jerome I. | Adrienne Cupples, L. | Psaty, Bruce M. | Palmer, Colin N. A. | Tardif, Jean-Claude | Colhoun, Helen M. | Hitman, Graham | Krauss, Ronald M. | Wouter Jukema, J | Caulfield, Mark J.
Nature Communications  2014;5:5068.
Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.
Statins are effectively used to prevent and manage cardiovascular disease, but patient response to these drugs is highly variable. Here, the authors identify two new genes associated with the response of LDL cholesterol to statins and advance our understanding of the genetic basis of drug response.
doi:10.1038/ncomms6068
PMCID: PMC4220464  PMID: 25350695
12.  Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes 
Yaghootkar, Hanieh | Lamina, Claudia | Scott, Robert A. | Dastani, Zari | Hivert, Marie-France | Warren, Liling L. | Stancáková, Alena | Buxbaum, Sarah G. | Lyytikäinen, Leo-Pekka | Henneman, Peter | Wu, Ying | Cheung, Chloe Y.Y. | Pankow, James S. | Jackson, Anne U. | Gustafsson, Stefan | Zhao, Jing Hua | Ballantyne, Christie M. | Xie, Weijia | Bergman, Richard N. | Boehnke, Michael | el Bouazzaoui, Fatiha | Collins, Francis S. | Dunn, Sandra H. | Dupuis, Josee | Forouhi, Nita G. | Gillson, Christopher | Hattersley, Andrew T. | Hong, Jaeyoung | Kähönen, Mika | Kuusisto, Johanna | Kedenko, Lyudmyla | Kronenberg, Florian | Doria, Alessandro | Assimes, Themistocles L. | Ferrannini, Ele | Hansen, Torben | Hao, Ke | Häring, Hans | Knowles, Joshua W. | Lindgren, Cecilia M. | Nolan, John J. | Paananen, Jussi | Pedersen, Oluf | Quertermous, Thomas | Smith, Ulf | Lehtimäki, Terho | Liu, Ching-Ti | Loos, Ruth J.F. | McCarthy, Mark I. | Morris, Andrew D. | Vasan, Ramachandran S. | Spector, Tim D. | Teslovich, Tanya M. | Tuomilehto, Jaakko | van Dijk, Ko Willems | Viikari, Jorma S. | Zhu, Na | Langenberg, Claudia | Ingelsson, Erik | Semple, Robert K. | Sinaiko, Alan R. | Palmer, Colin N.A. | Walker, Mark | Lam, Karen S.L. | Paulweber, Bernhard | Mohlke, Karen L. | van Duijn, Cornelia | Raitakari, Olli T. | Bidulescu, Aurelian | Wareham, Nick J. | Laakso, Markku | Waterworth, Dawn M. | Lawlor, Debbie A. | Meigs, James B. | Richards, J. Brent | Frayling, Timothy M.
Diabetes  2013;62(10):3589-3598.
Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
doi:10.2337/db13-0128
PMCID: PMC3781444  PMID: 23835345
13.  Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction 
Background
The cardiac sodium channel SCN5A regulates atrioventricular and ventricular conduction. Genetic variants in this gene are associated with PR and QRS intervals. We sought to further characterize the contribution of rare and common coding variation in SCN5A to cardiac conduction.
Methods and Results
In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study (CHARGE), we performed targeted exonic sequencing of SCN5A (n=3699, European-ancestry individuals) and identified 4 common (minor allele frequency >1%) and 157 rare variants. Common and rare SCN5A coding variants were examined for association with PR and QRS intervals through meta-analysis of European ancestry participants from CHARGE, NHLBI’s Exome Sequencing Project (ESP, n=607) and the UK10K (n=1275) and by examining ESP African-ancestry participants (N=972). Rare coding SCN5A variants in aggregate were associated with PR interval in European and African-ancestry participants (P=1.3×10−3). Three common variants were associated with PR and/or QRS interval duration among European-ancestry participants and one among African-ancestry participants. These included two well-known missense variants; rs1805124 (H558R) was associated with PR and QRS shortening in European-ancestry participants (P=6.25×10−4 and P=5.2×10−3 respectively) and rs7626962 (S1102Y) was associated with PR shortening in those of African ancestry (P=2.82×10−3). Among European-ancestry participants, two novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening (P=3.35×10−7 and P=2.69×10−4 respectively), and rs6599230 was associated with PR shortening (P=2.67×10−5).
Conclusions
By sequencing SCN5A, we identified novel common and rare coding variants associated with cardiac conduction.
doi:10.1161/CIRCGENETICS.113.000098
PMCID: PMC4177904  PMID: 24951663
PR interval; QRS interval; genetics; sequencing; cohort
14.  Association of Levels of Fasting Glucose and Insulin with Rare Variants at the Chromosome 11p11.2-MADD Locus: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study 
Background
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3 and SPI1, has been associated in genome-wide association studies with fasting glucose (FG) and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced five gene regions at 11p11.2 to identify rare, potentially functional variants influencing FG or FI levels.
Method & Results
Sequencing (mean depth 38×) across 16.1kb in 3,566 non-diabetic individuals identified 653 variants, 79.9% of which were rare (MAF <1%) and novel. We analyzed rare variants in five gene regions with FI or FG using the Sequence Kernel Association Test (SKAT). At NR1H3, 53 rare variants were jointly associated with FI (p=2.73 × 10−3); of these, seven were predicted to have regulatory function and showed association with FI (p=1.28 × 10−3). Conditioning on two previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are more than two independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; MAF 0.00068), contributed 20.6% to the overall SKAT score at NR1H3, lies in intron 2 of NR1H3 and is a predicted binding site for FOXA1, a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.
Conclusion
Sequencing at 11p11.2- NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, appears to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.
doi:10.1161/CIRCGENETICS.113.000169
PMCID: PMC4066205  PMID: 24951664
fasting glucose; fasting insulin; chr11p11.2; target sequencing; next-generation sequencing
15.  Genome-wide association study of age at menarche in African-American women 
Human Molecular Genetics  2013;22(16):3329-3346.
African-American (AA) women have earlier menarche on average than women of European ancestry (EA), and earlier menarche is a risk factor for obesity and type 2 diabetes among other chronic diseases. Identification of common genetic variants associated with age at menarche has a potential value in pointing to the genetic pathways underlying chronic disease risk, yet comprehensive genome-wide studies of age at menarche are lacking for AA women. In this study, we tested the genome-wide association of self-reported age at menarche with common single-nucleotide polymorphisms (SNPs) in a total of 18 089 AA women in 15 studies using an additive genetic linear regression model, adjusting for year of birth and population stratification, followed by inverse-variance weighted meta-analysis (Stage 1). Top meta-analysis results were then tested in an independent sample of 2850 women (Stage 2). First, while no SNP passed the pre-specified P < 5 × 10−8 threshold for significance in Stage 1, suggestive associations were found for variants near FLRT2 and PIK3R1, and conditional analysis identified two independent SNPs (rs339978 and rs980000) in or near RORA, strengthening the support for this suggestive locus identified in EA women. Secondly, an investigation of SNPs in 42 previously identified menarche loci in EA women demonstrated that 25 (60%) of them contained variants significantly associated with menarche in AA women. The findings provide the first evidence of cross-ethnic generalization of menarche loci identified to date, and suggest a number of novel biological links to menarche timing in AA women.
doi:10.1093/hmg/ddt181
PMCID: PMC3723312  PMID: 23599027
16.  Comparing baseline and longitudinal measures in association studies 
BMC Proceedings  2014;8(Suppl 1):S84.
In recent years, longitudinal family-based studies have had success in identifying genetic variants that influence complex traits in genome-wide association studies. In this paper, we suggest that longitudinal analyses may contain valuable information that can enable identification of additional associations compared to baseline analyses. Using Genetic Analysis Workshop 18 data, consisting of whole genome sequence data in a pedigree-based sample, we compared 3 methods for the genetic analysis of longitudinal data to an analysis that used baseline data only. These longitudinal methods were (a) longitudinal mixed-effects model; (b) analysis of the mean trait over time; and (c) a 2-stage analysis, with estimation of a random intercept in the first stage and regression of the random intercept on a single-nucleotide polymorphism at the second stage. All methods accounted for the familial correlation among subjects within a pedigree. The analyses considered common variants with minor allele frequency above 5% on chromosome 3. Analyses were performed without knowledge of the simulation model. The 3 longitudinal methods showed consistent results, which were generally different from those found by using only the baseline observation. The gene CACNA2D3, identified by both longitudinal and baseline approaches, had a stronger signal in the longitudinal analysis (p = 2.65 × 10−7) compared to that in the baseline analysis (p = 2.48 × 10−5). The effect size of the longitudinal mixed-effects model and mean trait were higher compared to the 2-stage approach. The longitudinal results provided stable results different from that using 1 observation at baseline and generally had lower p values.
doi:10.1186/1753-6561-8-S1-S84
PMCID: PMC4143666  PMID: 25519412
17.  Common variants in and near IRS1 and subclinical cardiovascular disease in the Framingham Heart Study 
Atherosclerosis  2013;229(1):149-154.
Objective
Common variants at the 2q36.3-IRS1 locus are associated with insulin resistance (IR), type 2 diabetes (T2D) and coronary artery disease (CAD) in large-scale association studies. We tested the hypothesis that variants at this locus are associated with subclinical atherosclerosis traits.
Methods
We studied 2740 Framingham Heart Study participants (54.9% women; mean age 57.8 years) with measures of coronary artery or abdominal aortic calcium, internal and common carotid intimamedia thickness, and ankle-brachial index (ABI). We tested 1) four SNPs previously shown to be associated with IR (rs2972146, rs2943650), T2D (rs2943641) or CAD (rs2943634) and 2) any SNP at 2q36.3-IRS1, for association with subclinical atherosclerosis traits, adjusting for atherosclerosis risk factors. We set type 1 error rate for test 1) as 0.05/5 traits = P < 0.01, and for test 2) as 0.05 divided by the effective number of independent tests, divided by 5 for the number of traits analyzed.
Results
We found no association between the four known SNPs and subclinical atherosclerosis, but identified one SNP (rs10167219, r2 with rs2943634 = 0.07) at 2q36.3 that was significantly associated with ABI (corrected P = 0.009). However, rs10167219 was not associated with ABI (P = 0.70) in 35,404 participants in a published ABI association study.
Conclusion
Common variants at the 2q36.3-IRS1 locus were not associated with subclinical atherosclerosis traits in this study which was adequately powered to find associations with moderate effect size. Although IR and T2D may be mechanistically linked to CAD via subclinical atherosclerosis, an alternate mechanism for the IR-T2D-CAD associations at 2q36.3-IRS1 must be postulated.
doi:10.1016/j.atherosclerosis.2013.03.037
PMCID: PMC4040123  PMID: 23659870
IRS1; 2q36.3; Genetic association; Subclinical atherosclerosis; Ankle-brachial index
18.  META-ANALYSIS OF GENOME-WIDE STUDIES IDENTIFIES WNT16 AND ESR1 SNPS ASSOCIATED WITH BONE MINERAL DENSITY IN PREMENOPAUSAL WOMEN 
Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous SNPs of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n= 4,061 women, ages 20 to 45) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. Following imputation, age- and weight-adjusted BMD values were tested for association with each SNP. Association of a SNP in the WNT16 gene (rs3801387; p=1.7 × 10−9) and multiple SNPs in the ESR1/C6orf97 (rs4870044; p=1.3 × 10−8) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven Replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n=5,597 for femoral neck; 4,744 for lumbar spine). When the data from the Discovery and Replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p=1.3 × 10−11; ESR1/C6orf97 joint p= 1.4 × 10−10). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p< 1 × 10−5). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period.
doi:10.1002/jbmr.1796
PMCID: PMC3691010  PMID: 23074152
Bone mineral density; GWAS; premenopausal; meta-analysis; genetics
19.  Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function 
Chasman, Daniel I. | Fuchsberger, Christian | Pattaro, Cristian | Teumer, Alexander | Böger, Carsten A. | Endlich, Karlhans | Olden, Matthias | Chen, Ming-Huei | Tin, Adrienne | Taliun, Daniel | Li, Man | Gao, Xiaoyi | Gorski, Mathias | Yang, Qiong | Hundertmark, Claudia | Foster, Meredith C. | O'Seaghdha, Conall M. | Glazer, Nicole | Isaacs, Aaron | Liu, Ching-Ti | Smith, Albert V. | O'Connell, Jeffrey R. | Struchalin, Maksim | Tanaka, Toshiko | Li, Guo | Johnson, Andrew D. | Gierman, Hinco J. | Feitosa, Mary F. | Hwang, Shih-Jen | Atkinson, Elizabeth J. | Lohman, Kurt | Cornelis, Marilyn C. | Johansson, Åsa | Tönjes, Anke | Dehghan, Abbas | Lambert, Jean-Charles | Holliday, Elizabeth G. | Sorice, Rossella | Kutalik, Zoltan | Lehtimäki, Terho | Esko, Tõnu | Deshmukh, Harshal | Ulivi, Sheila | Chu, Audrey Y. | Murgia, Federico | Trompet, Stella | Imboden, Medea | Coassin, Stefan | Pistis, Giorgio | Harris, Tamara B. | Launer, Lenore J. | Aspelund, Thor | Eiriksdottir, Gudny | Mitchell, Braxton D. | Boerwinkle, Eric | Schmidt, Helena | Cavalieri, Margherita | Rao, Madhumathi | Hu, Frank | Demirkan, Ayse | Oostra, Ben A. | de Andrade, Mariza | Turner, Stephen T. | Ding, Jingzhong | Andrews, Jeanette S. | Freedman, Barry I. | Giulianini, Franco | Koenig, Wolfgang | Illig, Thomas | Meisinger, Christa | Gieger, Christian | Zgaga, Lina | Zemunik, Tatijana | Boban, Mladen | Minelli, Cosetta | Wheeler, Heather E. | Igl, Wilmar | Zaboli, Ghazal | Wild, Sarah H. | Wright, Alan F. | Campbell, Harry | Ellinghaus, David | Nöthlings, Ute | Jacobs, Gunnar | Biffar, Reiner | Ernst, Florian | Homuth, Georg | Kroemer, Heyo K. | Nauck, Matthias | Stracke, Sylvia | Völker, Uwe | Völzke, Henry | Kovacs, Peter | Stumvoll, Michael | Mägi, Reedik | Hofman, Albert | Uitterlinden, Andre G. | Rivadeneira, Fernando | Aulchenko, Yurii S. | Polasek, Ozren | Hastie, Nick | Vitart, Veronique | Helmer, Catherine | Wang, Jie Jin | Stengel, Bénédicte | Ruggiero, Daniela | Bergmann, Sven | Kähönen, Mika | Viikari, Jorma | Nikopensius, Tiit | Province, Michael | Ketkar, Shamika | Colhoun, Helen | Doney, Alex | Robino, Antonietta | Krämer, Bernhard K. | Portas, Laura | Ford, Ian | Buckley, Brendan M. | Adam, Martin | Thun, Gian-Andri | Paulweber, Bernhard | Haun, Margot | Sala, Cinzia | Mitchell, Paul | Ciullo, Marina | Kim, Stuart K. | Vollenweider, Peter | Raitakari, Olli | Metspalu, Andres | Palmer, Colin | Gasparini, Paolo | Pirastu, Mario | Jukema, J. Wouter | Probst-Hensch, Nicole M. | Kronenberg, Florian | Toniolo, Daniela | Gudnason, Vilmundur | Shuldiner, Alan R. | Coresh, Josef | Schmidt, Reinhold | Ferrucci, Luigi | Siscovick, David S. | van Duijn, Cornelia M. | Borecki, Ingrid B. | Kardia, Sharon L.R. | Liu, Yongmei | Curhan, Gary C. | Rudan, Igor | Gyllensten, Ulf | Wilson, James F. | Franke, Andre | Pramstaller, Peter P. | Rettig, Rainer | Prokopenko, Inga | Witteman, Jacqueline | Hayward, Caroline | Ridker, Paul M | Parsa, Afshin | Bochud, Murielle | Heid, Iris M. | Kao, W.H. Linda | Fox, Caroline S. | Köttgen, Anna
Human Molecular Genetics  2012;21(24):5329-5343.
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4–2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
doi:10.1093/hmg/dds369
PMCID: PMC3607468  PMID: 22962313
20.  Assessment of Gene-by-Sex Interaction Effect on Bone Mineral Density 
Liu, Ching-Ti | Estrada, Karol | Yerges-Armstrong, Laura M. | Amin, Najaf | Evangelou, Evangelos | Li, Guo | Minster, Ryan L. | Carless, Melanie A. | Kammerer, Candace M. | Oei, Ling | Zhou, Yanhua | Alonso, Nerea | Dailiana, Zoe | Eriksson, Joel | García-Giralt, Natalia | Giroux, Sylvie | Husted, Lise Bjerre | Khusainova, Rita I. | Koromila, Theodora | Kung, Annie WaiChee | Lewis, Joshua R. | Masi, Laura | Mencej-Bedrac, Simona | Nogues, Xavier | Patel, Millan S. | Prezelj, Janez | Richards, J Brent | Sham, Pak Chung | Spector, Timothy | Vandenput, Liesbeth | Xiao, Su-Mei | Zheng, Hou-Feng | Zhu, Kun | Balcells, Susana | Brandi, Maria Luisa | Frost, Morten | Goltzman, David | González-Macías, Jesús | Karlsson, Magnus | Khusnutdinova, Elza K. | Kollia, Panagoula | Langdahl, Bente Lomholt | Ljunggren, Östen | Lorentzon, Mattias | Marc, Janja | Mellström, Dan | Ohlsson, Claes | Olmos, José M. | Ralston, Stuart H. | Riancho, José A. | Rousseau, François | Urreizti, Roser | Van Hul, Wim | Zarrabeitia, María T. | Castano-Betancourt, Martha | Demissie, Serkalem | Grundberg, Elin | Herrera, Lizbeth | Kwan, Tony | Medina-Gómez, Carolina | Pastinen, Tomi | Sigurdsson, Gunnar | Thorleifsson, Gudmar | vanMeurs, Joyce B.J. | Blangero, John | Hofman, Albert | Liu, Yongmei | Mitchell, Braxton D. | O’Connell, Jeffrey R. | Oostra, Ben A. | Rotter, Jerome I | Stefansson, Kari | Streeten, Elizabeth A. | Styrkarsdottir, Unnur | Thorsteinsdottir, Unnur | Tylavsky, Frances A. | Uitterlinden, Andre | Cauley, Jane A. | Harris, Tamara B. | Ioannidis, John P.A. | Psaty, Bruce M. | Robbins, John A | Zillikens, M. Carola | vanDuijn, Cornelia M. | Prince, Richard L. | Karasik, David | Rivadeneira, Fernando | Kiel, Douglas P. | Cupples, L. Adrienne | Hsu, Yi-Hsiang
Background
Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed eQTL analysis and bioinformatics network analysis.
Methods
We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS-) and femoral neck (FN-) BMD, in 25,353 individuals from eight cohorts. In a second stage, we followed up the 12 top SNPs (P<1×10−5) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs.
Results
We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 & p-value = 3.0×10−5; female effect = −0.007 & p-value=3.3×10−2) and eleven suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (P<5×10−8) gene-by-sex interaction in the joint analysis of discovery and replication cohorts.
Conclusion
Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found influencing BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP.
doi:10.1002/jbmr.1679
PMCID: PMC3447125  PMID: 22692763
gene-by-sex; interaction; BMD; association; aging
21.  Genome-Wide Association of Body Fat Distribution in African Ancestry Populations Suggests New Loci 
Liu, Ching-Ti | Monda, Keri L. | Taylor, Kira C. | Lange, Leslie | Demerath, Ellen W. | Palmas, Walter | Wojczynski, Mary K. | Ellis, Jaclyn C. | Vitolins, Mara Z. | Liu, Simin | Papanicolaou, George J. | Irvin, Marguerite R. | Xue, Luting | Griffin, Paula J. | Nalls, Michael A. | Adeyemo, Adebowale | Liu, Jiankang | Li, Guo | Ruiz-Narvaez, Edward A. | Chen, Wei-Min | Chen, Fang | Henderson, Brian E. | Millikan, Robert C. | Ambrosone, Christine B. | Strom, Sara S. | Guo, Xiuqing | Andrews, Jeanette S. | Sun, Yan V. | Mosley, Thomas H. | Yanek, Lisa R. | Shriner, Daniel | Haritunians, Talin | Rotter, Jerome I. | Speliotes, Elizabeth K. | Smith, Megan | Rosenberg, Lynn | Mychaleckyj, Josyf | Nayak, Uma | Spruill, Ida | Garvey, W. Timothy | Pettaway, Curtis | Nyante, Sarah | Bandera, Elisa V. | Britton, Angela F. | Zonderman, Alan B. | Rasmussen-Torvik, Laura J. | Chen, Yii-Der Ida | Ding, Jingzhong | Lohman, Kurt | Kritchevsky, Stephen B. | Zhao, Wei | Peyser, Patricia A. | Kardia, Sharon L. R. | Kabagambe, Edmond | Broeckel, Ulrich | Chen, Guanjie | Zhou, Jie | Wassertheil-Smoller, Sylvia | Neuhouser, Marian L. | Rampersaud, Evadnie | Psaty, Bruce | Kooperberg, Charles | Manson, JoAnn E. | Kuller, Lewis H. | Ochs-Balcom, Heather M. | Johnson, Karen C. | Sucheston, Lara | Ordovas, Jose M. | Palmer, Julie R. | Haiman, Christopher A. | McKnight, Barbara | Howard, Barbara V. | Becker, Diane M. | Bielak, Lawrence F. | Liu, Yongmei | Allison, Matthew A. | Grant, Struan F. A. | Burke, Gregory L. | Patel, Sanjay R. | Schreiner, Pamela J. | Borecki, Ingrid B. | Evans, Michele K. | Taylor, Herman | Sale, Michele M. | Howard, Virginia | Carlson, Christopher S. | Rotimi, Charles N. | Cushman, Mary | Harris, Tamara B. | Reiner, Alexander P. | Cupples, L. Adrienne | North, Kari E. | Fox, Caroline S.
PLoS Genetics  2013;9(8):e1003681.
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.
Author Summary
Central obesity is a marker of body fat distribution and is known to have a genetic underpinning. Few studies have reported genome-wide association study (GWAS) results among individuals of predominantly African ancestry (AA). We performed a collaborative meta-analysis in order to identify genetic loci associated with body fat distribution in AA individuals using waist circumference (WC) and waist to hip ratio (WHR) as measures of fat distribution, with and without adjustment for body mass index (BMI). We uncovered 2 genetic loci potentially associated with fat distribution: LHX2 in association with WC-adjusted-for-BMI and at RREB1 for WHR-adjusted-for-BMI. Six of fourteen previously reported loci for waist in EA populations were significant in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). These findings reinforce the concept that there are loci for body fat distribution that are independent of generalized adiposity.
doi:10.1371/journal.pgen.1003681
PMCID: PMC3744443  PMID: 23966867
22.  Validated SNPs for eGFR and their associations with albuminuria 
Human Molecular Genetics  2012;21(14):3293-3298.
Albuminuria and reduced glomerular filtration rate are manifestations of chronic kidney disease (CKD) that predict end-stage renal disease, acute kidney injury, cardiovascular disease and death. We hypothesized that SNPs identified in association with the estimated glomerular filtration rate (eGFR) would also be associated with albuminuria. Within the CKDGen Consortium cohort (n= 31 580, European ancestry), we tested 16 eGFR-associated SNPs for association with the urinary albumin-to-creatinine ratio (UACR) and albuminuria [UACR >25 mg/g (women); 17 mg/g (men)]. In parallel, within the CARe Renal Consortium (n= 5569, African ancestry), we tested seven eGFR-associated SNPs for association with the UACR. We used a Bonferroni-corrected P-value of 0.003 (0.05/16) in CKDGen and 0.007 (0.05/7) in CARe. We also assessed whether the 16 eGFR SNPs were associated with the UACR in aggregate using a beta-weighted genotype score. In the CKDGen Consortium, the minor A allele of rs17319721 in the SHROOM3 gene, known to be associated with a lower eGFR, was associated with lower ln(UACR) levels (beta = −0.034, P-value = 0.0002). No additional eGFR-associated SNPs met the Bonferroni-corrected P-value threshold of 0.003 for either UACR or albuminuria. In the CARe Renal Consortium, there were no associations between SNPs and UACR with a P< 0.007. Although we found the genotype score to be associated with albuminuria (P= 0.0006), this result was driven almost entirely by the known SHROOM3 variant, rs17319721. Removal of rs17319721 resulted in a P-value 0.03, indicating a weak residual aggregate signal. No alleles, previously demonstrated to be associated with a lower eGFR, were associated with the UACR or albuminuria, suggesting that there may be distinct genetic components for these traits.
doi:10.1093/hmg/dds138
PMCID: PMC3491918  PMID: 22492995
23.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance 
Manning, Alisa K. | Hivert, Marie-France | Scott, Robert A. | Grimsby, Jonna L. | Bouatia-Naji, Nabila | Chen, Han | Rybin, Denis | Liu, Ching-Ti | Bielak, Lawrence F. | Prokopenko, Inga | Amin, Najaf | Barnes, Daniel | Cadby, Gemma | Hottenga, Jouke-Jan | Ingelsson, Erik | Jackson, Anne U. | Johnson, Toby | Kanoni, Stavroula | Ladenvall, Claes | Lagou, Vasiliki | Lahti, Jari | Lecoeur, Cecile | Liu, Yongmei | Martinez-Larrad, Maria Teresa | Montasser, May E. | Navarro, Pau | Perry, John R. B. | Rasmussen-Torvik, Laura J. | Salo, Perttu | Sattar, Naveed | Shungin, Dmitry | Strawbridge, Rona J. | Tanaka, Toshiko | van Duijn, Cornelia M. | An, Ping | de Andrade, Mariza | Andrews, Jeanette S. | Aspelund, Thor | Atalay, Mustafa | Aulchenko, Yurii | Balkau, Beverley | Bandinelli, Stefania | Beckmann, Jacques S. | Beilby, John P. | Bellis, Claire | Bergman, Richard N. | Blangero, John | Boban, Mladen | Boehnke, Michael | Boerwinkle, Eric | Bonnycastle, Lori L. | Boomsma, Dorret I. | Borecki, Ingrid B. | Böttcher, Yvonne | Bouchard, Claude | Brunner, Eric | Budimir, Danijela | Campbell, Harry | Carlson, Olga | Chines, Peter S. | Clarke, Robert | Collins, Francis S. | Corbatón-Anchuelo, Arturo | Couper, David | de Faire, Ulf | Dedoussis, George V | Deloukas, Panos | Dimitriou, Maria | Egan, Josephine M | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Eury, Elodie | Ferrucci, Luigi | Ford, Ian | Forouhi, Nita G. | Fox, Caroline S | Franzosi, Maria Grazia | Franks, Paul W | Frayling, Timothy M | Froguel, Philippe | Galan, Pilar | de Geus, Eco | Gigante, Bruna | Glazer, Nicole L. | Goel, Anuj | Groop, Leif | Gudnason, Vilmundur | Hallmans, Göran | Hamsten, Anders | Hansson, Ola | Harris, Tamara B. | Hayward, Caroline | Heath, Simon | Hercberg, Serge | Hicks, Andrew A. | Hingorani, Aroon | Hofman, Albert | Hui, Jennie | Hung, Joseph | Jarvelin, Marjo Riitta | Jhun, Min A. | Johnson, Paul C.D. | Jukema, J Wouter | Jula, Antti | Kao, W.H. | Kaprio, Jaakko | Kardia, Sharon L. R. | Keinanen-Kiukaanniemi, Sirkka | Kivimaki, Mika | Kolcic, Ivana | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Kyvik, Kirsten Ohm | Laakso, Markku | Lakka, Timo | Lannfelt, Lars | Lathrop, G Mark | Launer, Lenore J. | Leander, Karin | Li, Guo | Lind, Lars | Lindstrom, Jaana | Lobbens, Stéphane | Loos, Ruth J. F. | Luan, Jian’an | Lyssenko, Valeriya | Mägi, Reedik | Magnusson, Patrik K. E. | Marmot, Michael | Meneton, Pierre | Mohlke, Karen L. | Mooser, Vincent | Morken, Mario A. | Miljkovic, Iva | Narisu, Narisu | O’Connell, Jeff | Ong, Ken K. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Pankow, James S. | Peden, John F. | Pedersen, Nancy L. | Pehlic, Marina | Peltonen, Leena | Penninx, Brenda | Pericic, Marijana | Perola, Markus | Perusse, Louis | Peyser, Patricia A | Polasek, Ozren | Pramstaller, Peter P. | Province, Michael A. | Räikkönen, Katri | Rauramaa, Rainer | Rehnberg, Emil | Rice, Ken | Rotter, Jerome I. | Rudan, Igor | Ruokonen, Aimo | Saaristo, Timo | Sabater-Lleal, Maria | Salomaa, Veikko | Savage, David B. | Saxena, Richa | Schwarz, Peter | Seedorf, Udo | Sennblad, Bengt | Serrano-Rios, Manuel | Shuldiner, Alan R. | Sijbrands, Eric J.G. | Siscovick, David S. | Smit, Johannes H. | Small, Kerrin S. | Smith, Nicholas L. | Smith, Albert Vernon | Stančáková, Alena | Stirrups, Kathleen | Stumvoll, Michael | Sun, Yan V. | Swift, Amy J. | Tönjes, Anke | Tuomilehto, Jaakko | Trompet, Stella | Uitterlinden, Andre G. | Uusitupa, Matti | Vikström, Max | Vitart, Veronique | Vohl, Marie-Claude | Voight, Benjamin F. | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Watkins, Hugh | Wheeler, Eleanor | Widen, Elisabeth | Wild, Sarah H. | Willems, Sara M. | Willemsen, Gonneke | Wilson, James F. | Witteman, Jacqueline C.M. | Wright, Alan F. | Yaghootkar, Hanieh | Zelenika, Diana | Zemunik, Tatijana | Zgaga, Lina | Wareham, Nicholas J. | McCarthy, Mark I. | Barroso, Ines | Watanabe, Richard M. | Florez, Jose C. | Dupuis, Josée | Meigs, James B. | Langenberg, Claudia
Nature genetics  2012;44(6):659-669.
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
doi:10.1038/ng.2274
PMCID: PMC3613127  PMID: 22581228
24.  Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways 
Scott, Robert A | Lagou, Vasiliki | Welch, Ryan P | Wheeler, Eleanor | Montasser, May E | Luan, Jian’an | Mägi, Reedik | Strawbridge, Rona J | Rehnberg, Emil | Gustafsson, Stefan | Kanoni, Stavroula | Rasmussen-Torvik, Laura J | Yengo, Loïc | Lecoeur, Cecile | Shungin, Dmitry | Sanna, Serena | Sidore, Carlo | Johnson, Paul C D | Jukema, J Wouter | Johnson, Toby | Mahajan, Anubha | Verweij, Niek | Thorleifsson, Gudmar | Hottenga, Jouke-Jan | Shah, Sonia | Smith, Albert V | Sennblad, Bengt | Gieger, Christian | Salo, Perttu | Perola, Markus | Timpson, Nicholas J | Evans, David M | Pourcain, Beate St | Wu, Ying | Andrews, Jeanette S | Hui, Jennie | Bielak, Lawrence F | Zhao, Wei | Horikoshi, Momoko | Navarro, Pau | Isaacs, Aaron | O’Connell, Jeffrey R | Stirrups, Kathleen | Vitart, Veronique | Hayward, Caroline | Esko, Tönu | Mihailov, Evelin | Fraser, Ross M | Fall, Tove | Voight, Benjamin F | Raychaudhuri, Soumya | Chen, Han | Lindgren, Cecilia M | Morris, Andrew P | Rayner, Nigel W | Robertson, Neil | Rybin, Denis | Liu, Ching-Ti | Beckmann, Jacques S | Willems, Sara M | Chines, Peter S | Jackson, Anne U | Kang, Hyun Min | Stringham, Heather M | Song, Kijoung | Tanaka, Toshiko | Peden, John F | Goel, Anuj | Hicks, Andrew A | An, Ping | Müller-Nurasyid, Martina | Franco-Cereceda, Anders | Folkersen, Lasse | Marullo, Letizia | Jansen, Hanneke | Oldehinkel, Albertine J | Bruinenberg, Marcel | Pankow, James S | North, Kari E | Forouhi, Nita G | Loos, Ruth J F | Edkins, Sarah | Varga, Tibor V | Hallmans, Göran | Oksa, Heikki | Antonella, Mulas | Nagaraja, Ramaiah | Trompet, Stella | Ford, Ian | Bakker, Stephan J L | Kong, Augustine | Kumari, Meena | Gigante, Bruna | Herder, Christian | Munroe, Patricia B | Caulfield, Mark | Antti, Jula | Mangino, Massimo | Small, Kerrin | Miljkovic, Iva | Liu, Yongmei | Atalay, Mustafa | Kiess, Wieland | James, Alan L | Rivadeneira, Fernando | Uitterlinden, Andre G | Palmer, Colin N A | Doney, Alex S F | Willemsen, Gonneke | Smit, Johannes H | Campbell, Susan | Polasek, Ozren | Bonnycastle, Lori L | Hercberg, Serge | Dimitriou, Maria | Bolton, Jennifer L | Fowkes, Gerard R | Kovacs, Peter | Lindström, Jaana | Zemunik, Tatijana | Bandinelli, Stefania | Wild, Sarah H | Basart, Hanneke V | Rathmann, Wolfgang | Grallert, Harald | Maerz, Winfried | Kleber, Marcus E | Boehm, Bernhard O | Peters, Annette | Pramstaller, Peter P | Province, Michael A | Borecki, Ingrid B | Hastie, Nicholas D | Rudan, Igor | Campbell, Harry | Watkins, Hugh | Farrall, Martin | Stumvoll, Michael | Ferrucci, Luigi | Waterworth, Dawn M | Bergman, Richard N | Collins, Francis S | Tuomilehto, Jaakko | Watanabe, Richard M | de Geus, Eco J C | Penninx, Brenda W | Hofman, Albert | Oostra, Ben A | Psaty, Bruce M | Vollenweider, Peter | Wilson, James F | Wright, Alan F | Hovingh, G Kees | Metspalu, Andres | Uusitupa, Matti | Magnusson, Patrik K E | Kyvik, Kirsten O | Kaprio, Jaakko | Price, Jackie F | Dedoussis, George V | Deloukas, Panos | Meneton, Pierre | Lind, Lars | Boehnke, Michael | Shuldiner, Alan R | van Duijn, Cornelia M | Morris, Andrew D | Toenjes, Anke | Peyser, Patricia A | Beilby, John P | Körner, Antje | Kuusisto, Johanna | Laakso, Markku | Bornstein, Stefan R | Schwarz, Peter E H | Lakka, Timo A | Rauramaa, Rainer | Adair, Linda S | Smith, George Davey | Spector, Tim D | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Gudnason, Vilmundur | Kivimaki, Mika | Hingorani, Aroon | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Boomsma, Dorret I | Stefansson, Kari | van der Harst, Pim | Dupuis, Josée | Pedersen, Nancy L | Sattar, Naveed | Harris, Tamara B | Cucca, Francesco | Ripatti, Samuli | Salomaa, Veikko | Mohlke, Karen L | Balkau, Beverley | Froguel, Philippe | Pouta, Anneli | Jarvelin, Marjo-Riitta | Wareham, Nicholas J | Bouatia-Naji, Nabila | McCarthy, Mark I | Franks, Paul W | Meigs, James B | Teslovich, Tanya M | Florez, Jose C | Langenberg, Claudia | Ingelsson, Erik | Prokopenko, Inga | Barroso, Inês
Nature genetics  2012;44(9):991-1005.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
doi:10.1038/ng.2385
PMCID: PMC3433394  PMID: 22885924
25.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segrè, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian'an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John RB | Platou, Carl GP | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden89-, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922

Results 1-25 (38)