The chromosome 3q25 genomic region is associated with measures of adiposity in newborns in a multi-ethnic genome-wide association study.

Newborns characterized as large and small for gestational age are at risk for increased mortality and morbidity during the first year of life as well as for obesity and dysglycemia as children and adults. The intrauterine environment and fetal genes contribute to the fetal size at birth. To define the genetic architecture underlying the newborn size, we performed a genome-wide association study (GWAS) in 4281 newborns in four ethnic groups from the Hyperglycemia and Adverse Pregnancy Outcome Study. We tested for association with newborn anthropometric traits (birth length, head circumference, birth weight, percent fat mass and sum of skinfolds) and newborn metabolic traits (cord glucose and C-peptide) under three models. Model 1 adjusted for field center, ancestry, neonatal gender, gestational age at delivery, parity, maternal age at oral glucose tolerance test (OGTT); Model 2 adjusted for Model 1 covariates, maternal body mass index (BMI) at OGTT, maternal height at OGTT, maternal mean arterial pressure at OGTT, maternal smoking and drinking; Model 3 adjusted for Model 2 covariates, maternal glucose and C-peptide at OGTT. Strong evidence for association was observed with measures of newborn adiposity (sum of skinfolds model 3 Z-score 7.356, P = 1.90×10⁻¹³, and to a lesser degree fat mass and birth weight) and a region on Chr3q25.31 mapping between CCNL and LEKR1. These findings were replicated in an independent cohort of 2296 newborns. This region has previously been shown to be associated with birth weight in Europeans. The current study suggests that association of this locus with birth weight is secondary to an effect on fat as opposed to lean body mass.

New susceptibility loci associated with kidney disease in type 1 diabetes.

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-ß1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Evaluating genetic risk for prostate cancer among Japanese and Latinos.

BACKGROUND: There have been few genome-wide association studies (GWAS) of prostate cancer among diverse populations. To search for novel prostate cancer risk variants, we conducted GWAS of prostate cancer in Japanese and Latinos. In addition, we tested prostate cancer risk variants and developed genetic risk models of prostate cancer for Japanese and Latinos. METHODS: Our first-stage GWAS of prostate cancer included Japanese (cases/controls = 1,033/1,042) and Latino (cases/controls = 1,043/1,057) from the Multiethnic Cohort (MEC). Significant associations from stage I (P < 1.0 × 10(-4)) were examined in silico in GWAS of prostate cancer (stage II) in Japanese (cases/controls = 1,583/3,386) and Europeans (cases/controls = 1,854/1,894). RESULTS: No novel stage I single-nucleotide polymorphism (SNP) outside of known risk regions reached genome-wide significance. For Japanese, in stage I, the most notable putative novel association was seen with 10 SNPs (P ≤ 8.0 × 10(-6)) at chromosome 2q33; however, this was not replicated in stage II. For Latinos, the most significant association was observed with rs17023900 at the known 3p12 risk locus (stage I: OR = 1.45; P = 7.01 × 10(-5) and stage II: OR = 1.58; P = 3.05 × 10(-7)). The majority of the established risk variants for prostate cancer, 79% and 88%, were positively associated with prostate cancer in Japanese and Latinos (stage I), respectively. The cumulative effects of these variants significantly influence prostate cancer risk (OR per allele = 1.10; P = 2.71 × 10(-25) and OR = 1.07; P = 1.02 × 10(-16) for Japanese and Latinos, respectively). CONCLUSION AND IMPACT: Our GWAS of prostate cancer did not identify novel genome-wide significant variants. However, our findings show that established risk variants for prostate cancer significantly contribute to risk among Japanese and Latinos.

Genetic variants associated with the white blood cell count in 13,923 subjects in the eMERGE Network.

White blood cell count (WBC) is unique among identified inflammatory predictors of chronic disease in that it is routinely measured in asymptomatic patients in the course of routine patient care. We led a genome-wide association analysis to identify variants associated with WBC levels in 13,923 subjects in the electronic Medical Records and Genomics (eMERGE) Network. We identified two regions of interest that were each unique to subjects of genetically determined ancestry to the African continent (AA) or to the European continent (EA). WBC varies among different ancestry groups. Despite being ancestry specific, these regions were identifiable in the combined analysis. In AA subjects, the region surrounding the Duffy antigen/chemokine receptor gene (DARC) on 1q21 exhibited significant association (p value = 6.71e-55). These results validate the previously reported association between WBC and of the regulatory variant rs2814778 in the promoter region, which causes the Duffy negative phenotype (Fy-/-). A second missense variant (rs12075) is responsible for the two principal antigens, Fya and Fyb of the Duffy blood group system. The two variants, consisting of four alleles, act in concert to produce five antigens and subsequent phenotypes. We were able to identify the marginal and novel interaction effects of these two variants on WBC. In the EA subjects, we identified significantly associated SNPs tagging three separate genes in the 17q21 region: (1) GSDMA, (2) MED24, and (3) PSMD3. Variants in this region have been reported to be associated with WBC, neutrophil count, and inflammatory diseases including asthma and Crohn's disease.

Quality control and quality assurance in genotypic data for genome-wide association studies.

Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium test P-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the "Gene Environment Association Studies" (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS.