To determine whether the identified loci were also associated with any of 22 cardio-metabolic traits, we obtained association data from meta-analysis consortia DIAGRAM (T2D)58 (link), CARDIoGRAM-C4D (CAD)59 (link), ICBP (SBP, DBP)60 (link), GIANT (BMI, height)36 ,37 , GLGC (HDL, LDL, and TG)61 (link), MAGIC (fasting glucose, fasting insulin, fasting insulin adjusted for BMI, and two-hour glucose)62 (link)-64 (link), ADIPOGen (BMI-adjusted adiponectin)65 (link), CKDgen (urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), and overall CKD)66 (link),67 (link), ReproGen (age at menarche, age at menopause)68 (link),69 (link), and GEFOS (bone mineral density)70 (link); others provided association data for IgA nephropathy71 (link) (also Kiryluk K, Choi M, Lifton RP, Gharavi AG, unpublished data) and for endometriosis (stage B cases only)72 (link). Proxies (r2>0.80 in CEU) were used when an index SNP was unavailable.
We also searched the National Human Genome Research Institute (NHGRI) GWAS Catalog for previous SNP-trait associations near our lead SNPs73 (link). We supplemented the catalog with additional genome-wide significant SNP-trait associations from the literature13 (link),70 (link),74 (link)-80 (link). We used PLINK to identify SNPs within 500 kb of lead SNPs using 1000 Genomes Project Pilot I genotype data and LD (r2) values from CEU81 (link),82 (link); for rs7759742, HapMap release 22 CEU data81 (link),83 (link) were used. All SNPs within the specified regions were compared with the NHGRI GWAS Catalog16 .