Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Circadian CLOCK gene polymorphisms in relation to sleep patterns and obesity in African Americans: findings from the Jackson heart study.

BACKGROUND: Circadian rhythms regulate key biological processes and the dysregulation of the intrinsic clock mechanism affects sleep patterns and obesity onset. The CLOCK (circadian locomotor output cycles protein kaput) gene encodes a core transcription factor of the molecular circadian clock influencing diverse metabolic pathways, including glucose and lipid homeostasis. The primary objective of this study was to evaluate the associations between CLOCK single nucleotide polymorphisms (SNPs) and body mass index (BMI). We also evaluated the association of SNPs with BMI related factors such as sleep duration and quality, adiponectin and leptin, in 2962 participants (1116 men and 1810 women) from the Jackson Heart Study. Genotype data for the selected 23 CLOCK gene SNPS was obtained by imputation with IMPUTE2 software and reference phase data from the 1000 genome project. Genetic analyses were conducted with PLINK RESULTS: We found a significant association between the CLOCK SNP rs2070062 and sleep duration, participants carriers of the T allele showed significantly shorter sleep duration compared to non-carriers after the adjustment for individual proportions of European ancestry (PEA), socio economic status (SES), body mass index (BMI), alcohol consumption and smoking status that reach the significance threshold after multiple testing correction. In addition, we found nominal associations of the CLOCK SNP rs6853192 with longer sleep duration and the rs6820823, rs3792603 and rs11726609 with BMI. However, these associations did not reach the significance threshold after correction for multiple testing. CONCLUSIONS: In this work, CLOCK gene variants were associated with sleep duration and BMI suggesting that the effects of these polymorphisms on circadian rhythmicity may affect sleep duration and body weight regulation in Africans Americans.

Polysomnographic predictors of blood pressure and hypertension: is one index best?

STUDY OBJECTIVES: Numerous indexes derived from polysomnography are available to characterize sleep-disordered breathing, with no consensus over which measures best predict clinical outcomes. This study addresses the relative merits of using alternative polysomnography indexes by characterizing the consistency and strength of the association of each index with blood pressure and hypertension. DESIGN: Cross-sectional analyses of the association of alternative polysomnography indexes with blood pressure and hypertension were performed in construction and validation data sets. Linear and logistic regression models were used to identify the best variable sets. PATIENTS: Data were obtained from 6433 men and women (age 62.9 +/- 11.0 years, 52.8% women) who participated in the Sleep Heart Health Study. RESULTS: In multivariable models, most indexes showed weak linear associations with systolic, with slightly stronger associations for diastolic blood pressure, and the log odds of hypertension. No single index showed consistent superiority over others. Systolic blood pressure, diastolic blood pressure, and hypertension each were associated with distinct sets of polysomnography variables. Slightly more-consistent associations were demonstrated for indexes that included hypopneas that were linked with either a 3% or 4% desaturation level than indexes that did not require hypopneas to have linked desaturation. For indexes that combined apneas and hypopneas, there was no evidence that linking obstructive apneas to desaturation or arousal altered prediction compared with counting all apneas. CONCLUSION: In summary, using a rigorous cross-validation assessment, we did not identify a clear superiority of any single index for blood pressure or hypertension prediction. Detailed analyses of alternative definitions of the respiratory disturbance index support current scoring guidelines, where desaturation criteria are recommended for hypopneas but not apneas.