Genome-wide association study of iron traits and relation to diabetes in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL): potential genomic intersection of iron and glucose regulation?

Genetic variants contribute to normal variation of iron-related traits and may also cause clinical syndromes of iron deficiency or excess. Iron overload and deficiency can adversely affect human health. For example, elevated iron storage is associated with increased diabetes risk, although mechanisms are still being investigated. We conducted the first genome-wide association study of serum iron, total iron binding capacity (TIBC), transferrin saturation, and ferritin in a Hispanic/Latino cohort, the Hispanic Community Health Study/Study of Latinos (>12 000 participants) and also assessed the generalization of previously known loci to this population. We then evaluated whether iron-associated variants were associated with diabetes and glycemic traits. We found evidence for a novel association between TIBC and a variant near the gene for protein phosphatase 1, regulatory subunit 3B (PPP1R3B; rs4841132, β = -0.116, P = 7.44 × 10-8). The effect strengthened when iron deficient individuals were excluded (β = -0.121, P = 4.78 × 10-9). Ten of sixteen variants previously associated with iron traits generalized to HCHS/SOL, including variants at the transferrin (TF), hemochromatosis (HFE), fatty acid desaturase 2 (FADS2)/myelin regulatory factor (MYRF), transmembrane protease, serine 6 (TMPRSS6), transferrin receptor (TFR2), N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2), ABO blood group (ABO), and GRB2 associated binding protein 3 (GAB3) loci. In examining iron variant associations with glucose homeostasis, an iron-raising variant of TMPRSS6 was associated with lower HbA1c levels (P = 8.66 × 10-10). This association was attenuated upon adjustment for iron measures. In contrast, the iron-raising allele of PPP1R3B was associated with higher levels of fasting glucose (P = 7.70 × 10-7) and fasting insulin (P = 4.79 × 10-6), but these associations were not attenuated upon adjustment for TIBC-so iron is not likely a mediator. These results provide new genetic information on iron traits and their connection with glucose homeostasis

Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p −6 were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10−10). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10−8). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia

Multi-ethnic GWAS and meta-analysis of sleep quality identify MPP6 as a novel gene that functions in sleep center neurons

Poor sleep quality can have harmful health consequences. Although many aspects of sleep are heritable, the understandings of genetic factors involved in its physiology remain limited. Here, we performed a genome-wide association study (GWAS) using the Pittsburgh Sleep Quality Index (PSQI) in a multi-ethnic discovery cohort (n = 2868) and found two novel genome-wide loci on chromosomes 2 and 7 associated with global sleep quality. A meta-analysis in 12 independent cohorts (100 000 individuals) replicated the association on chromosome 7 between NPY and MPP6. While NPY is an important sleep gene, we tested for an independent functional role of MPP6. Expression data showed an association of this locus with both NPY and MPP6 mRNA levels in brain tissues. Moreover, knockdown of an orthologue of MPP6 in Drosophila melanogaster sleep center neurons resulted in decreased sleep duration. With convergent evidence, we describe a new locus impacting human variability in sleep quality through known NPY and novel MPP6 sleep genes.Peer reviewe

Genetic variation near IRS 1 is associated with adiposity and a favorable metabolic profile in U.S.Hispanics/Latinos: IRS1Variation, Adiposity, and Metabolic Profile

We examined associations of IRS1 genetic variation with adiposity and metabolic profile in US Hispanic/Latino individuals of diverse backgrounds

GWAS of QRS Duration Identifies New Loci Specific to Hispanic/Latino Populations

BACKGROUND: The electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored. METHODS: We performed a GWAS of QRS duration among Hispanic/Latino ancestry populations (n = 15,124) from four studies using 1000 Genomes imputed genotype data (adjusted for age, sex, global ancestry, clinical and study-specific covariates). Study-specific results were combined using fixed-effects, inverse variance-weighted meta-analysis. RESULTS: We identified six loci associated with QRS (P CONCLUSIONS: Our QRS duration GWAS, the first in Hispanic/Latino populations, identified two new loci, underscoring the utility of extending large scale genomic studies to currently under-examined populations

Correction: Exome Sequencing of Phenotypic Extremes Identifies CAV2 and TMC6 as Interacting Modifiers of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis

Discovery of rare or low frequency variants in exome or genome data that are associated with complex traits often will require use of very large sample sizes to achieve adequate statistical power. For a fixed sample size, sequencing of individuals sampled from the tails of a phenotype distribution (i.e., extreme phenotypes design) maximizes power and this approach was recently validated empirically with the discovery of variants in DCTN4 that influence the natural history of P. aeruginosa airway infection in persons with cystic fibrosis (CF; MIM219700). The increasing availability of large exome/genome sequence datasets that serve as proxies for population-based controls affords the opportunity to test an alternative, potentially more powerful and generalizable strategy, in which the frequency of rare variants in a single extreme phenotypic group is compared to a control group (i.e., extreme phenotype vs. control population design). As proof-of-principle, we applied this approach to search for variants associated with risk for age-of-onset of chronic P. aeruginosa airway infection among individuals with CF and identified variants in CAV2 and TMC6 that were significantly associated with group status. These results were validated using a large, prospective, longitudinal CF cohort and confirmed a significant association of a variant in CAV2 with increased age-of-onset of P. aeruginosa airway infection (hazard ratio = 0.48, 95% CI=[0.32, 0.88]) and variants in TMC6 with diminished age-of-onset of P. aeruginosa airway infection (HR = 5.4, 95% CI=[2.2, 13.5]) A strong interaction between CAV2 and TMC6 variants was observed (HR=12.1, 95% CI=[3.8, 39]) for children with the deleterious TMC6 variant and without the CAV2 protective variant. Neither gene showed a significant association using an extreme phenotypes design, and conditions for which the power of an extreme phenotype vs. control population design was greater than that for the extreme phenotypes design were explored

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets

Discovery of common and rare genetic risk variants for colorectal cancer.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.Goncalo R Abecasis has received compensation from 23andMe and Helix. He is currently an employee of Regeneron Pharmaceuticals. Heather Hampel performs collaborative research with Ambry Genetics, InVitae Genetics, and Myriad Genetic Laboratories, Inc., is on the scientific advisory board for InVitae Genetics and Genome Medical, and has stock in Genome Medical. Rachel Pearlman has participated in collaborative funded research with Myriad Genetics Laboratories and Invitae Genetics but has no financial competitive interest

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p