ABSTRACT
Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.
Subject(s)
Exome , Genetic Variation , Proteins , Humans , Alleles , Exome/genetics , Exome Sequencing , Gene Frequency , Genetic Variation/genetics , Heterozygote , Loss of Function Mutation/genetics , Mutation, Missense/genetics , Open Reading Frames/genetics , Proteins/genetics , RNA Splice Sites/genetics , Precision MedicineABSTRACT
The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.
Subject(s)
Exome Sequencing , Genome, Human , Genotype , Hispanic or Latino , Adult , Humans , Africa/ethnology , Americas/ethnology , Europe/ethnology , Gene Frequency/genetics , Genetics, Population , Genome, Human/genetics , Genotyping Techniques , Hispanic or Latino/genetics , Homozygote , Loss of Function Mutation/genetics , Mexico , Prospective StudiesABSTRACT
AIMS/HYPOTHESIS: Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. METHODS: A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-ßH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. RESULTS: CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-ßH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-ßH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. CONCLUSIONS/INTERPRETATION: Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin-Secreting Cells , Animals , Humans , Diabetes Mellitus, Type 2/genetics , Diabetes Mellitus, Type 2/metabolism , DNA-Binding Proteins/metabolism , Gene Expression , Glucose/metabolism , Induced Pluripotent Stem Cells/metabolism , Insulin/metabolism , Insulin-Secreting Cells/metabolism , Transcription Factors/genetics , Zebrafish/geneticsABSTRACT
There is particular interest in transcriptome-wide association studies (TWAS) gene-level tests based on multi-SNP predictive models of gene expression-for identifying causal genes at loci associated with complex traits. However, interpretation of TWAS associations may be complicated by divergent effects of model SNPs on phenotype and gene expression. We developed an iterative modeling scheme for obtaining multi-SNP models of gene expression and applied this framework to generate expression models for 43 human tissues from the Genotype-Tissue Expression (GTEx) Project. We characterized the performance of single- and multi-SNP models for identifying causal genes in GWAS data for 46 circulating metabolites. We show that: (A) multi-SNP models captured more variation in expression than did the top cis-eQTL (median 2-fold improvement); (B) predicted expression based on multi-SNP models was associated (false discovery rate < 0.01) with metabolite levels for 826 unique gene-metabolite pairs, but, after stepwise conditional analyses, 90% were dominated by a single eQTL SNP; (C) among the 35% of associations where a SNP in the expression model was a significant cis-eQTL and metabolomic-QTL (met-QTL), 92% demonstrated colocalization between these signals, but interpretation was often complicated by incomplete overlap of QTLs in multi-SNP models; and (D) using a "truth" set of causal genes at 61 met-QTLs, the sensitivity was high (67%), but the positive predictive value was low, as only 8% of TWAS associations (19% when restricted to colocalized associations at met-QTLs) involved true causal genes. These results guide the interpretation of TWAS and highlight the need for corroborative data to provide confident assignment of causality.
Subject(s)
Gene Expression Regulation , Genetic Predisposition to Disease , Metabolome , Models, Genetic , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Transcriptome , Genome-Wide Association Study , Humans , PhenotypeABSTRACT
Resolving the molecular processes that mediate genetic risk remains a challenge because most disease-associated variants are non-coding and functional characterization of these signals requires knowledge of the specific tissues and cell-types in which they operate. To address this challenge, we developed a framework for integrating tissue-specific gene expression and epigenomic maps to obtain "tissue-of-action" (TOA) scores for each association signal by systematically partitioning posterior probabilities from Bayesian fine-mapping. We applied this scheme to credible set variants for 380 association signals from a recent GWAS meta-analysis of type 2 diabetes (T2D) in Europeans. The resulting tissue profiles underscored a predominant role for pancreatic islets and, to a lesser extent, adipose and liver, particularly among signals with greater fine-mapping resolution. We incorporated resulting TOA scores into a rule-based classifier and validated the tissue assignments through comparison with data from cis-eQTL enrichment, functional fine-mapping, RNA co-expression, and patterns of physiological association. In addition to implicating signals with a single TOA, we found evidence for signals with shared effects in multiple tissues as well as distinct tissue profiles between independent signals within heterogeneous loci. Lastly, we demonstrated that TOA scores can be directly coupled with eQTL colocalization to further resolve effector transcripts at T2D signals. This framework guides mechanistic inference by directing functional validation studies to the most relevant tissues and can gain power as fine-mapping resolution and cell-specific annotations become richer. This method is generalizable to all complex traits with relevant annotation data and is made available as an R package.
Subject(s)
Diabetes Mellitus, Type 2/genetics , Gene Expression Regulation , Genetic Predisposition to Disease , Genome-Wide Association Study , Quantitative Trait Loci , Adipose Tissue/metabolism , Chromosome Mapping , Cluster Analysis , Computational Biology , Enhancer Elements, Genetic , Epigenomics , Genome, Human , Humans , Islets of Langerhans/metabolism , Linkage Disequilibrium , Liver/metabolism , Models, Statistical , Multifactorial Inheritance , Polymorphism, Single Nucleotide , Principal Component Analysis , ProbabilityABSTRACT
Top signals from genome-wide association studies (GWASs) of type 2 diabetes (T2D) are enriched with expression quantitative trait loci (eQTLs) identified in skeletal muscle and adipose tissue. We therefore hypothesized that such eQTLs might account for a disproportionate share of the heritability estimated from all SNPs interrogated through GWASs. To test this hypothesis, we applied linear mixed models to the Wellcome Trust Case Control Consortium (WTCCC) T2D data set and to data sets representing Mexican Americans from Starr County, TX, and Mexicans from Mexico City. We estimated the proportion of phenotypic variance attributable to the additive effect of all variants interrogated in these GWASs, as well as a much smaller set of variants identified as eQTLs in human adipose tissue, skeletal muscle, and lymphoblastoid cell lines. The narrow-sense heritability explained by all interrogated SNPs in each of these data sets was substantially greater than the heritability accounted for by genome-wide-significant SNPs (â¼10%); GWAS SNPs explained over 50% of phenotypic variance in the WTCCC, Starr County, and Mexico City data sets. The estimate of heritability attributable to cross-tissue eQTLs was greater in the WTCCC data set and among lean Hispanics, whereas adipose eQTLs significantly explained heritability among Hispanics with a body mass index ≥ 30. These results support an important role for regulatory variants in the genetic component of T2D susceptibility, particularly for eQTLs that elicit effects across insulin-responsive peripheral tissues.
Subject(s)
Diabetes Mellitus, Type 2/genetics , Phenotype , Quantitative Trait Loci/genetics , Adipose Tissue/chemistry , Analysis of Variance , Body Mass Index , Genome-Wide Association Study/statistics & numerical data , Humans , Linear Models , Mexican Americans/genetics , Mexico , Muscle, Skeletal/chemistry , Polymorphism, Single Nucleotide/genetics , Principal Component Analysis , TexasABSTRACT
The spirochaete bacterium Borrelia burgdorferisensu lato is the aetiologic agent of Lyme disease. Borrelia is transmitted to mammals through tick bite and is adapted to survive at tick and mammalian physiological temperatures. We have previously shown that B. burgdorferi can exist in different morphological forms, including the antibiotic-resistant biofilm form, in vitro and in vivo. B. burgdorferi forms aggregates in ticks as well as in humans, indicating potential of biofilm formation at both 23 and 37 °C. However, the role of various environmental factors that influence Borrelia biofilm formation remains unknown. In this study, we investigated the effect of tick (23 °C), mammalian physiological (37 °C) and standard in vitro culture (33 °C) temperatures with the objective of elucidating the effect of temperature on Borrelia biofilm phenotypes invitro using two B. burgdorferisensu stricto strains (B31 and 297). Our findings show increased biofilm quantity, biofilm size, exopolysaccharide content and enhanced adherence as well as reduced free spirochaetes at 37 °C for both strains, when compared to growth at 23 and 33 °C. There were no significant variations in the biofilm nano-topography and the type of extracellular polymeric substance in Borrelia biofilms formed at all three temperatures. Significant variations in extracellular DNA content were observed in the biofilms of both strains cultured at the three temperatures. Our results indicate that temperature is an important regulator of Borrelia biofilm development, and that the mammalian physiological temperature favours increased biofilm formation in vitro compared to tick physiological temperature and in vitro culture temperature.
Subject(s)
Biofilms , Borrelia burgdorferi/physiology , Lyme Disease/microbiology , Lyme Disease/physiopathology , Ticks/microbiology , Ticks/physiology , Animals , Body Temperature , Borrelia burgdorferi/genetics , HumansABSTRACT
The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.
ABSTRACT
Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity.
Subject(s)
Diabetes Mellitus, Type 2 , Induced Pluripotent Stem Cells , Liver Diseases , Nerve Tissue Proteins , Adult , Humans , Adaptor Proteins, Signal Transducing/genetics , Diabetes Mellitus, Type 2/genetics , Genetic Predisposition to Disease , Nerve Tissue Proteins/genetics , Obesity/complications , Obesity/genetics , ProteomicsABSTRACT
Background: Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-ßH1) and contrasted these maps with Hi-C maps in EndoC-ßH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.
ABSTRACT
BACKGROUND AND AIMS: HBV RNA in peripheral blood reflects HBV cccDNA transcriptional activity and may predict clinical outcomes. The prospective Melbourne HBV-STOP trial studied nucleot(s)ide analog discontinuation in HBeAg-negative non-cirrhotic participants with long-term virological suppression. Ninety-six weeks after stopping treatment, the proportion of participants with virological relapse (HBV DNA > 2000 IU/mL), biochemical relapse (ALT > 2 × ULN and HBV DNA > 2000 IU/mL), or hepatitis flare (ALT > 5 × ULN and HBV DNA > 2000 IU/mL) was 89%, 58%, and 38%, respectively. We evaluated the ability of serum HBV RNA levels to predict these outcomes. APPROACH RESULTS: HBV RNA levels were measured using the Roche cobas 6800/8800 HBV RNA Investigational Assay. Sixty-five participants had baseline and longitudinal off-treatment specimens available for RNA testing. HBV RNA was detectable at baseline in 25% of participants and was associated with a higher risk of biochemical relapse (81% vs. 51%, p value 0.04) and hepatitis flare (63% vs. 31%, p value 0.04). Participants who had undetectable serum HBV RNA as well as HBsAg ≤ 100 IU/mL at baseline were less likely to experience virological relapse (4 of 9, 44%) than participants with detectable HBV RNA and HBsAg level > 100 IU/mL (15/15, 100%; p value 0.0009). Off-treatment levels of HBV RNA were correlated with HBV DNA and were associated with the risk of hepatitis flare. CONCLUSIONS: Serum HBV RNA may be a useful biomarker for guiding clinical decision-making before stopping nucleot(s)ide analog therapy. Baseline HBV RNA and HBsAg levels are associated with the risk of clinical relapse, hepatitis flare, and disease remission off-treatment.
Subject(s)
Hepatitis B, Chronic , Nucleosides , Humans , Antiviral Agents/therapeutic use , DNA, Viral , Hepatitis B e Antigens , Hepatitis B Surface Antigens , Hepatitis B virus/genetics , Hepatitis B, Chronic/drug therapy , Nucleosides/therapeutic use , Prospective Studies , RNA , Symptom Flare UpABSTRACT
Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2, encoding the ß2 subunit of the α4ß2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2 in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56-0.76, P = 1.9 × 10-8). An independent common variant association in the protective direction ( rs2072659 ; OR = 0.96; CI = 0.94-0.98; P = 5.3 × 10-6) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that ß2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2 in the brain for the treatment of nicotine addiction.
Subject(s)
Nicotine , Tobacco Use Disorder , Humans , Animals , Mice , Smoking/genetics , Tobacco Use Disorder/genetics , Phenotype , Odds RatioABSTRACT
Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.
ABSTRACT
AIMS: Results of previous studies of abdominal adiposity and risk of vascular-metabolic mortality in Hispanic populations have been conflicting. We report results from a large prospective study of Mexican adults with high levels of abdominal adiposity. METHODS AND RESULTS: A total of 159 755 adults aged ≥35 years from Mexico City were enrolled in a prospective study and followed for 16 years. Cox regression, adjusted for confounders, yielded mortality rate ratios (RRs) associated with three markers of abdominal adiposity (waist circumference, waist-hip ratio, and waist-height ratio) and one marker of gluteo-femoral adiposity (hip circumference) for cause-specific mortality before age 75 years. To reduce reverse causality, deaths in the first 5 years of follow-up and participants with diabetes or other prior chronic disease were excluded. Among 113 163 participants without prior disease and aged 35-74 years at recruitment, all adiposity markers were positively associated with vascular-metabolic mortality. Comparing the top versus bottom tenth of the sex-specific distributions, the vascular-metabolic mortality RRs at ages 40-74 years were 2.32 [95% confidence interval (CI) 1.84-2.94] for waist circumference, 2.22 (1.71-2.88) for the waist-hip ratio, 2.63 (2.06-3.36) for the waist-height ratio, and 1.58 (1.29-1.93) for hip circumference. The RRs corresponding to each standard deviation (SD) higher usual levels of these adiposity markers were 1.34 (95% CI 1.27-1.41), 1.31 (1.23-1.39), 1.38 (1.31-1.45), and 1.18 (1.13-1.24), respectively. For the markers of abdominal adiposity, the RRs did not change much after further adjustment for other adiposity markers, but for hip circumference the association was reversed; given body mass index and waist circumference, the RR for vascular-metabolic mortality for each one SD higher usual hip circumference was 0.80 (0.75-0.86). CONCLUSIONS: In this study of Mexican adults, abdominal adiposity (and in particular the waist-height ratio) was strongly and positively associated with vascular-metabolic mortality. For a given amount of general and abdominal adiposity, however, higher hip circumference was associated with lower vascular-metabolic mortality.
Subject(s)
Adiposity , Obesity, Abdominal , Adult , Biomarkers , Body Mass Index , Female , Humans , Male , Mexico/epidemiology , Obesity/complications , Obesity, Abdominal/complications , Obesity, Abdominal/diagnosis , Prospective Studies , Risk Factors , Waist Circumference , Waist-Hip RatioABSTRACT
We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (ß = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.
Subject(s)
Diabetes Mellitus, Type 2 , MAP Kinase Kinase Kinases , Humans , Diabetes Mellitus, Type 2/genetics , Genetic Predisposition to Disease , Monocarboxylic Acid Transporters/genetics , Obesity/genetics , Prospective Studies , MAP Kinase Kinase Kinases/geneticsABSTRACT
Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10-09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin ßE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.
Subject(s)
Diabetes Mellitus, Type 2 , Inhibin-beta Subunits/genetics , Adipose Tissue , Adiposity/genetics , Diabetes Mellitus, Type 2/genetics , Exome/genetics , Humans , MutationABSTRACT
CONTEXT: Chronic kidney disease (CKD) and diabetes are associated with dyslipidemia, metabolic abnormalities, and atherosclerotic risk. Nuclear magnetic resonance (NMR) spectroscopy provides much more detail on lipoproteins than traditional assays. METHODS: In about 38 000 participants from the Mexico City Prospective Study, aged 35 to 84 years and not using lipid-lowering medication, NMR spectroscopy quantified plasma concentrations of lipoprotein particles, their lipidic compositions, and other metabolic measures. Linear regression related low estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2) to each NMR measure after adjustment for confounders and for multiplicity. Analyses were done separately for those with and without diabetes. RESULTS: Among the 38 081 participants (mean age 52 years, 64% women), low eGFR was present for 4.8% (306/6403) of those with diabetes and 1.2% (365/31 678) of those without diabetes. Among both those with and without diabetes, low eGFR was significantly associated with higher levels of 58 NMR measures, including apolipoprotein B (Apo-B), the particle numbers of most Apo-B containing lipoproteins, the cholesterol and triglycerides carried in these lipoproteins, several fatty acids, total cholines and phosphatidylcholine, citrate, glutamine, phenylalanine, ß-OH-butyrate, and the inflammatory measure glycoprotein-A, and significantly lower levels of 13 NMR measures, including medium and small high-density lipoprotein particle measures, very low-density lipoprotein particle size, the ratio of saturated:total fatty acids, valine, tyrosine, and aceto-acetate. CONCLUSIONS: In this Mexican population with high levels of adiposity and diabetes, low kidney function was associated with widespread alterations in lipidic and metabolic profiles, both in those with and without diabetes. These alterations may help explain the higher atherosclerotic risk experienced by people with CKD.
Subject(s)
Kidney Function Tests , Lipids/blood , Lipoproteins/blood , Magnetic Resonance Spectroscopy , Renal Insufficiency, Chronic/blood , Adult , Aged , Aged, 80 and over , Apolipoproteins B/blood , Atherosclerosis/ethnology , Atherosclerosis/etiology , Cholesterol/blood , Choline/blood , Diabetes Mellitus/blood , Diabetes Mellitus/ethnology , Fatty Acids/blood , Female , Glomerular Filtration Rate , Humans , Kidney/physiopathology , Linear Models , Male , Mexico , Middle Aged , Prospective Studies , Renal Insufficiency, Chronic/complications , Renal Insufficiency, Chronic/ethnology , TriglyceridesABSTRACT
BACKGROUND: Research is needed to determine the relevance of low-intensity daily smoking to mortality in countries such as Mexico, where such smoking habits are common. METHODS: Prospective study of 159 755 Mexican adults recruited from 1998-2004 and followed for cause-specific mortality to 1 January 2018. Participants were categorized according to baseline self-reported smoking status. Confounder-adjusted mortality rate ratios (RRs) at ages 35-89 were estimated using Cox regression, after excluding those with previous chronic disease (to avoid reverse causality). RESULTS: Among 42 416 men and 86 735 women aged 35-89 and without previous disease, 18 985 men (45%) and 18 072 women (21%) reported current smoking and 8866 men (21%) and 53 912 women (62%) reported never smoking. Smoking less than daily was common: 33% of male current smokers and 39% of female current smokers. During follow-up, the all-cause mortality RRs associated with the baseline smoking categories of <10 cigarettes per day (average during follow-up 4 per day) or ≥10 cigarettes per day (average during follow-up 10 per day), compared with never smoking, were 1.17 (95% confidence interval 1.10-1.25) and 1.54 (1.42-1.67), respectively. RRs were similar irrespective of age or sex. The diseases most strongly associated with daily smoking were respiratory cancers, chronic obstructive pulmonary disease and gastrointestinal and vascular diseases. Ex-daily smokers had substantially lower mortality rates than those who were current daily smokers at recruitment. CONCLUSIONS: In this Mexican population, low-intensity daily smoking was associated with increased mortality. Of those smoking 10 cigarettes per day on average, about one-third were killed by their habit. Quitting substantially reduced these risks.
Subject(s)
Smoking , Tobacco Smoking , Adult , Aged , Aged, 80 and over , Cause of Death , Female , Humans , Male , Mexico/epidemiology , Middle Aged , Prospective Studies , Smoking/epidemiologyABSTRACT
Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.