Publications

BACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10-8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance.

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN (P = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN (P = 1.82 × 10-13) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (P = 5.6 × 10-238), hypertension (P = 2.8 × 10-50), diabetes (P = 3.6 × 10-7), and hyperlipidemia (P = 6.3 × 10-5). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN (P = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN (P = 1.82 × 10-13) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (P = 5.6 × 10-238), hypertension (P = 2.8 × 10-50), diabetes (P = 3.6 × 10-7), and hyperlipidemia (P = 6.3 × 10-5). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN (P = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN (P = 1.82 × 10-13) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (P = 5.6 × 10-238), hypertension (P = 2.8 × 10-50), diabetes (P = 3.6 × 10-7), and hyperlipidemia (P = 6.3 × 10-5). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

BACKGROUND: Hypertension and diabetes have been associated with inefficient arsenic metabolism, primarily through studies undertaken in populations exposed through drinking water. Recently, rice has been recognized as a source of arsenic exposure, but it remains unclear whether populations with high rice consumption but no known water exposure are at risk for the health problems associated with inefficient arsenic metabolism.

METHODS: The relationships between arsenic metabolism efficiency (% inorganic arsenic, % monomethylarsenate and % dimethylarsinate in urine) and three hypertension- and seven diabetes-related traits were estimated among 12 609 participants of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). A two-sample Mendelian randomization approach incorporated genotype-arsenic metabolism relationships from literature, and genotype-trait relationships from HCHS/SOL, with a mixed-effect linear model. Analyses were stratified by rice consumption and smoking.

RESULTS: Among never smokers with high rice consumption, each percentage point increase in was associated with increases of 1.96 mmHg systolic blood pressure (P = 0.034) and 1.85 mmHg inorganic arsenic diastolic blood pressure (P = 0.003). Monomethylarsenate was associated with increased systolic (1.64 mmHg/percentage point increase; P = 0.021) and diastolic (1.33 mmHg/percentage point increase; P = 0.005) blood pressure. Dimethylarsinate, a marker of efficient metabolism, was associated with lower systolic (-0.92 mmHg/percentage point increase; P = 0.025) and diastolic (-0.79 mmHg/percentage point increase; P = 0.004) blood pressure. Among low rice consumers and ever smokers, the results were consistent with no association. Evidence for a relationship with diabetes was equivocal.

CONCLUSIONS: Less efficient arsenic metabolism was associated with increased blood pressure among never smokers with high rice consumption, suggesting that arsenic exposure through rice may contribute to high blood pressure in the Hispanic/Latino community.

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health.

Polygenic risk scores (PRSs) are weighted sums of risk allele counts of single-nucleotide polymorphisms (SNPs) associated with a disease or trait. PRSs are typically constructed based on published results from Genome-Wide Association Studies (GWASs), and the majority of which has been performed in large populations of European ancestry (EA) individuals. Although many genotype-trait associations have generalized across populations, the optimal choice of SNPs and weights for PRSs may differ between populations due to different linkage disequilibrium (LD) and allele frequency patterns. We compare various approaches for PRS construction, using GWAS results from both large EA studies and a smaller study in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL, n = 12 , 803 ). We consider multiple approaches for selecting SNPs and for computing SNP weights. We study the performance of the resulting PRSs in an independent study of Hispanics/Latinos from the Women's Health Initiative (WHI, n = 3 , 582 ). We support our investigation with simulation studies of potential genetic architectures in a single locus. We observed that selecting variants based on EA GWASs generally performs well, except for blood pressure trait. However, the use of EA GWASs for weight estimation was suboptimal. Using non-EA GWAS results to estimate weights improved results.

BACKGROUND: Hypertension and diabetes have been associated with inefficient arsenic metabolism, primarily through studies undertaken in populations exposed through drinking water. Recently, rice has been recognized as a source of arsenic exposure, but it remains unclear whether populations with high rice consumption but no known water exposure are at risk for the health problems associated with inefficient arsenic metabolism.

METHODS: The relationships between arsenic metabolism efficiency (% inorganic arsenic, % monomethylarsenate and % dimethylarsinate in urine) and three hypertension- and seven diabetes-related traits were estimated among 12 609 participants of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). A two-sample Mendelian randomization approach incorporated genotype-arsenic metabolism relationships from literature, and genotype-trait relationships from HCHS/SOL, with a mixed-effect linear model. Analyses were stratified by rice consumption and smoking.

RESULTS: Among never smokers with high rice consumption, each percentage point increase in was associated with increases of 1.96 mmHg systolic blood pressure (P = 0.034) and 1.85 mmHg inorganic arsenic diastolic blood pressure (P = 0.003). Monomethylarsenate was associated with increased systolic (1.64 mmHg/percentage point increase; P = 0.021) and diastolic (1.33 mmHg/percentage point increase; P = 0.005) blood pressure. Dimethylarsinate, a marker of efficient metabolism, was associated with lower systolic (-0.92 mmHg/percentage point increase; P = 0.025) and diastolic (-0.79 mmHg/percentage point increase; P = 0.004) blood pressure. Among low rice consumers and ever smokers, the results were consistent with no association. Evidence for a relationship with diabetes was equivocal.

CONCLUSIONS: Less efficient arsenic metabolism was associated with increased blood pressure among never smokers with high rice consumption, suggesting that arsenic exposure through rice may contribute to high blood pressure in the Hispanic/Latino community.

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health.