Genome-wide association analysis of red blood cell traits in African Americans: the COGENT Network

ArticleinHuman Molecular Genetics 22(12) · March 2013with18 Reads
DOI: 10.1093/hmg/ddt087 · Source: PubMed
Laboratory red blood cell (RBC) measurements are clinically important, heritable and differ among ethnic groups. To identify genetic variants that contribute to RBC phenotypes in African Americans (AAs), we conducted a genome-wide association study in up to ∼16 500 AAs. The alpha-globin locus on chromosome 16pter [lead SNP rs13335629 in ITFG3 gene; P < 1E-13 for hemoglobin (Hgb), RBC count, mean corpuscular volume (MCV), MCH and MCHC] and the G6PD locus on Xq28 [lead SNP rs1050828; P < 1E - 13 for Hgb, hematocrit (Hct), MCV, RBC count and red cell distribution width (RDW)] were each associated with multiple RBC traits. At the alpha-globin region, both the common African 3.7 kb deletion and common single nucleotide polymorphisms (SNPs) appear to contribute independently to RBC phenotypes among AAs. In the 2p21 region, we identified a novel variant of PRKCE distinctly associated with Hct in AAs. In a genome-wide admixture mapping scan, local European ancestry at the 6p22 region containing HFE and LRRC16A was associated with higher Hgb. LRRC16A has been previously associated with the platelet count and mean platelet volume in AAs, but not with Hgb. Finally, we extended to AAs the findings of association of erythrocyte traits with several loci previously reported in Europeans and/or Asians, including CD164 and HBS1L-MYB. In summary, this large-scale genome-wide analysis in AAs has extended the importance of several RBC-associated genetic loci to AAs and identified allelic heterogeneity and pleiotropy at several previously known genetic loci associated with blood cell traits in AAs.
    • "The leucine-rich repeat-containing 16A (LRRC16A) gene encodes a protein called capping protein ARP2/3 and myosin-I linker (CARMIL), which plays an important role in cell-shape changes and motility [1]. A common variant of LRRC16A gene has been previously reported to be associated with nephrolithiasis [2], platelet count [3], and hemoglobin [4]. In addition, a meta-analysis of genome-wide association studies (GWAS) has revealed an association between serum uric acid (SUA) levels and rs742132, a single nucleotide polymorphism (SNP) in LRRC16A [5]. "
    [Show abstract] [Hide abstract] ABSTRACT: Gout is a common disease resulting from hyperuricemia which causes acute arthritis. Recently, genome-wide association studies revealed an association between serum uric acid levels and a common variant of leucine-rich repeat-containing 16A (LRRC16A) gene. However, it remains to be clarified whether LRRC16A contributes to the susceptibility to gout. In this study, we investigated the relationship between rs742132 in LRRC16A and gout. A total of 545 Japanese male gout cases and 1,115 male individuals as a control group were genotyped. rs742132 A/A genotype significantly increased the risk of gout, conferring an odds ratio of 1.30 (95 % CI 1.05–1.60; p = 0.015). LRRC16A encodes a protein called capping protein ARP2/3 and myosin-I linker (CARMIL), which serves as an inhibitor of the actin capping protein (CP). CP is an essential element of the actin cytoskeleton, which binds to the barbed end of the actin filament and regulates its polymerization. In the apical membrane of proximal tubular cells in the human kidney, the urate-transporting multimolecular complex (urate transportsome) is proposed to consist of several urate transporters and scaffolding proteins, which interact with the actin cytoskeleton. Thus, if there is a CARMIL dysfunction and regulatory disability in actin polymerization, urate transportsome may be unable to operate appropriately. We have shown for the first time that CARMIL/LRRC16A was associated with gout, which could be due to urate transportsome failure. Electronic supplementary material The online version of this article (doi:10.1007/s13577-013-0081-8) contains supplementary material, which is available to authorized users.
    Article · Dec 2013
  • [Show abstract] [Hide abstract] ABSTRACT: Introduction Red cell distribution width (RDW) has been associated with venous thromboembolism (VTE), but whether RDW is a predictor of first event of VTE is unknown. We investigated the association between RDW and incidence of first event of VTE in a population-based cohort. Materials and Methods RDW was measured in 27 042 subjects (aged 45–73 years, 60.6% women), without previous history of VTE or cancer within 5 years before follow-up, who participated in the Malmö Diet and Cancer study during 1991–1996. Incidence of VTE was identified from the patient register and the cause of death register during a mean follow-up of 13.8 years and studied in relation to RDW. Results During follow-up, 991 subjects (57.5% women) were affected by VTE (pulmonary embolism or deep venous thrombosis of the lower limbs). After adjustment for potential confounding factors the hazard ratios (HR) for VTE for the second, third and fourth RDW quartiles 1.15 (95% confidence interval 0.94–1.41), 1.41 (1.14–1.73), 1.74 (1.38–2.21), respectively, were compared with the bottom quartile of RDW. In the multivariate model subjects with the top 5% of RDW values compared with the bottom quartile had an even higher risk (HR = 2.51, 1.78–2.54). In receiver operating characteristic (ROC) analysis, the male specific area under the ROC curve (AUC) for RDW was 0.57 (95% CI 0.54–0.59). The female specific AUC was 0.56 (95% CI 0.53–0.58). Conclusions RDW was found to be associated with long-term incidence of first event of VTE among middle-aged subjects.
    Article · Nov 2013
  • [Show abstract] [Hide abstract] ABSTRACT: Genome-wide association studies (GWAS) have identified reproducible genetic associations with hundreds of human diseases and traits. The vast majority of these associated single nucleotide polymorphisms (SNPs) are non-coding, highlighting the challenge in moving from genetic findings to mechanistic and functional insights. Nevertheless, large-scale (epi)genomic studies and bioinformatic analyses strongly suggest that GWAS hits are not randomly distributed in the genome but rather pinpoint specific biological pathways important for disease development or phenotypic variation. In this review, we focus on GWAS discoveries for the three main blood cell types: red blood cells, white blood cells and platelets. We summarize the knowledge gained from GWAS of these phenotypes and discuss their possible clinical implications for common (e.g., anemia) and rare (e.g., myeloproliferative neoplasms) human blood-related diseases. Finally, we argue that blood phenotypes are ideal to study the genetics of complex human traits because they are fully amenable to experimental testing.
    Full-text · Article · Mar 2014
Show more