Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rises rapidly to 2–3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions that pinpoint the locations of genes previously associated with hematological cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer prior to DNA sampling, those without a prior diagnosis have an estimated 10-fold higher risk of a subsequent hematological cancer (95% confidence interval = 6–18).

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a "genetic-analysis group" variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.

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. This system includes some new approaches that (1) combine analysis of allelic probe

We performed a multistage genome-wide association study of melanoma. In a discovery cohort of 1804 melanoma cases and 1026 controls, we identified loci at chromosomes 15q13.1 (HERC2/OCA2 region) and 16q24.3 (MC1R) regions that reached genome-wide significance within this study and also found strong evidence for genetic effects on susceptibility to melanoma from markers on chromosome 9p21.3 in the p16/ARF region and on chromosome 1q21.3 (ARNT/LASS2/ANXA9 region). The most significant single-nucleotide polymorphisms (SNPs) in the 15q13.1 locus (rs1129038 and rs12913832) lie within a genomic region that has profound effects on eye and skin color; notably, 50% of variability in eye color is associated with variation in the SNP rs12913832. Because eye and skin colors vary across European populations, we further evaluated the associations of the significant SNPs after carefully adjusting for European substructure. We also evaluated the top 10 most significant SNPs by using data from three other genome-wide scans. Additional in silico data provided replication of the findings from the most significant region on chromosome 1q21.3 rs7412746 (P = 6 × 10(-10)). Together, these data identified several candidate genes for additional studies to identify causal variants predisposing to increased risk for developing melanoma.

Y, et al. (2019) Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations. PLoS Genet 15(12): e1008500.

Maternal metabolism during pregnancy impacts the developing fetus, affecting offspring birth weight and adiposity. This has important implications for metabolic health later in life (e.g., offspring of mothers with pre-existing or gestational diabetes mellitus have an increased risk of metabolic disorders in childhood). To identify genetic loci associated with measures of maternal metabolism obtained during an oral glucose tolerance test at ∼28 weeks’ gestation, we performed a genome-wide association study of 4,437 pregnant mothers of European (n = 1,367), Thai (n = 1,178), Afro-Caribbean (n = 1,075), and Hispanic (n = 817) ancestry, along with replication of top signals in three additional European ancestry cohorts. In addition to identifying associations with genes previously implicated with measures of glucose metabolism in nonpregnant populations, we identified two novel genome-wide significant associations: 2-h plasma glucose and HKDC1, and fasting C-peptide and BACE2. These results suggest that the genetic architecture underlying glucose metabolism may differ, in part, in pregnancy.

GWASTools is an R/Bioconductor package for quality control and analysis of genome-wide association studies (GWAS). GWASTools brings the interactive capability and extensive statistical libraries of R to GWAS. Data are stored in NetCDF format to accommodate extremely large datasets that cannot fit within R's memory limits. The documentation includes instructions for converting data from multiple formats, including variants called from sequencing. GWASTools provides a convenient interface for linking genotypes and intensity data with sample and single nucleotide polymorphism annotation.

The plasma glycoprotein von Willebrand factor (VWF) exhibits fivefold antigen level variation across the normal human population determined by both genetic and environmental factors. Low levels of VWF are associated with bleeding and elevated levels with increased risk for thrombosis, myocardial infarction, and stroke. To identify additional genetic determinants of VWF antigen levels and to minimize the impact of age and illness-related environmental factors, we performed genome-wide association analysis in two young and healthy cohorts (n = 1,152 and n = 2,310) and identified signals at ABO (P < 7.9E-139) and VWF (P < 5.5E-16), consistent with previous reports. Additionally, linkage analysis based on sibling structure within the cohorts, identified significant signals at chromosome 2q12-2p13 (LOD score 5.3) and at the ABO locus on chromosome 9q34 (LOD score 2.9) that explained 19.2% and 24.5% of the variance in VWF levels, respectively. Given its strong effect, the linkage region on chromosome 2 could harbor a potentially important determinant of bleeding and thrombosis risk. The absence of a chromosome 2 association signal in this or previous association studies suggests a causative gene harboring many genetic variants that are individually rare, but in aggregate common. These results raise the possibility that similar loci could explain a significant portion of the "missing heritability" for other complex genetic traits.genome-wide association study | linkage study | venous thromboembolic disease | von Willebrand disease | quantitative trait loci V on Willebrand factor (VWF) is a multimeric plasma glycoprotein that plays a central role in hemostasis by acting as a molecular bridge tethering platelets to injured endothelium and as a carrier molecule for coagulation factor VIII (1). Quantitative or qualitative deficiencies in VWF lead to von Willebrand Disease (VWD), the most common inherited bleeding disorder, with an estimated prevalence of 0.002-0.01% worldwide (1, 2). Type I VWD is characterized by mild to moderate bleeding and low circulating VWF levels. This form of VWD is generally associated with haploinsufficiency for VWF and is characterized by incomplete penetrance. In contrast, elevated levels of plasma VWF are an independent risk factor for venous thromboembolic disease (3), myocardial infarction (4), stroke (5, 6), and also complicate anticoagulant management (7).Plasma VWF levels vary by approximately fivefold in healthy populations and are influenced by both environmental and inherited factors. Increased levels of VWF occur with advancing age (8), may rise acutely because of inflammation or infection, and may serve as a surrogate marker for endothelial dysfunction and atherosclerosis (9-11). Estimates for the heritability of plasma VWF levels in the general population from previous family-based studies range from 32-75%. A 1985 study in Norwegian twins reported the heritability of VWF at 66%, with 30% of this effect attributable to ABO blood type (12). More recent studies estimated the heritabil...