Persistently low white blood cell count (WBC) and neutrophil count is a well-described phenomenon in persons of African ancestry, whose etiology remains unknown. We recently used admixture mapping to identify an approximately 1-megabase region on chromosome 1, where ancestry status (African or European) almost entirely accounted for the difference in WBC between African Americans and European Americans. To identify the specific genetic change responsible for this association, we analyzed genotype and phenotype data from 6,005 African Americans from the Jackson Heart Study (JHS), the Health, Aging and Body Composition (Health ABC) Study, and the Atherosclerosis Risk in Communities (ARIC) Study. We demonstrate that the causal variant must be at least 91% different in frequency between West Africans and European Americans. An excellent candidate is the Duffy Null polymorphism (SNP rs2814778 at chromosome 1q23.2), which is the only polymorphism in the region known to be so differentiated in frequency and is already known to protect against Plasmodium vivax malaria. We confirm that rs2814778 is predictive of WBC and neutrophil count in African Americans above beyond the previously described admixture association (P = 3.8×10−5), establishing a novel phenotype for this genetic variant.

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

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Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1 , but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5 . It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned 47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent with pedigree estimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and 0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.

OBJECTIVEPericardial adipose tissue (PAT), a regional fat depot that surrounds the heart, is associated with an unfavorable cardiometabolic risk factor profile. The associations among PAT, cardiometabolic risk factors, and coronary artery calcification (CAC) and abdominal aortic artery calcification (AAC) in African American populations have not been explored.RESEARCH DESIGN AND METHODSA total of 1,414 African Americans (35% men; mean ± SD age 58 ± 11 years) drawn from the Jackson Heart Study (JHS) underwent multidetector computed tomography assessment of abdominal visceral adipose tissue (VAT) and PAT between 2007 and 2009. Cardiometabolic risk factors, CAC, and AAC were examined in relation to increments of PAT and VAT.RESULTSPAT was significantly correlated with BMI, waist circumference, and VAT (r = 0.35, 0.46, and 0.69; all P < 0.0001). PAT (per 1-SD increase) was associated with elevated levels of systolic blood pressure (P < 0.04), fasting glucose, triglycerides, and C-reactive protein and lower levels of HDL (all P values<0.0001). PAT was also associated with metabolic syndrome (odds ratio [OR] 1.89; P < 0.0001), hypertension (1.48; P < 0.0006), and diabetes (1.40; P < 0.04); all associations were diminished after further adjustment for VAT (most P > 0.05). However, the association of PAT with CAC but not with AAC remained significant (OR 1.34 [95% CI 1.10–1.64]; P < 0.004) after multivariable and VAT adjustment.CONCLUSIONSPAT is significantly correlated with most cardiometabolic risk factors and CAC in the JHS cohort. The results suggest that PAT is an important VAT depot that may exert a local effect on the coronary vasculature.