Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 22
Filtrar
1.
Nat Commun ; 11(1): 4912, 2020 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-32999275

RESUMO

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.


Assuntos
Glicemia/genética , Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Ilhotas Pancreáticas/metabolismo , Locos de Características Quantitativas , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Animais , Glicemia/metabolismo , Linhagem Celular Tumoral , Estudos de Coortes , Diabetes Mellitus Tipo 2/sangue , Diacilglicerol Quinase/genética , Diacilglicerol Quinase/metabolismo , Elementos Facilitadores Genéticos , Feminino , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla , Humanos , Masculino , Camundongos , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , RNA-Seq , Análise de Sequência de DNA , Proteína 2 Semelhante ao Fator 7 de Transcrição/genética , Proteína 2 Semelhante ao Fator 7 de Transcrição/metabolismo , Adulto Jovem
2.
Am J Hum Genet ; 107(4): 670-682, 2020 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-32910913

RESUMO

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.

3.
Artigo em Inglês | MEDLINE | ID: mdl-32944759

RESUMO

CONTEXT: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta cell glucose sensitivity. OBJECTIVE: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies. DESIGN: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and non-diabetic subjects from 6 independent cohorts (n=5,706). Beta-cell glucose sensitivity was calculated from mixed-meal and oral glucose tolerance tests, and its associations between known glycaemia related SNPS and GWAS SNPs were estimated using linear regression models. RESULTS: Beta-cell glucose sensitivity was moderately heritable (h 2 ranged between 34 to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P-value=2.64x10 -9) and rs9368219 in the CDKAL1 (P-value=3.15x10 -9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity. CONCLUSION: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta cell glucose sensitivity.

4.
Nat Rev Genet ; 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32860016

RESUMO

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

5.
Diabetes ; 2020 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-32826294

RESUMO

A growing number of genetic loci have been shown to influence individual predisposition to type 2 diabetes (T2D). Despite longstanding interest in understanding whether non-linear interactions between these risk-variants additionally influence T2D-risk, the ability to detect significant gene-gene interaction (GGI) effects has to date been limited. To increase power to detect GGI effects, we combined recent advances in the fine-mapping of causal T2D-risk variants with the increased sample size available within UK Biobank (375,736 unrelated European participants, including 16,430 T2D cases). In addition to conventional single variant-based analysis, we employed a complementary polygenic score-based approach which included partitioned T2D-risk scores that capture biological processes relevant to T2D pathophysiology. Nevertheless, we found no evidence in support of GGI effects influencing T2D-risk. The present study was powered to detect interactions between common variants with odds ratios >1.2, so these findings place limits on the contribution of GGIs to the overall heritability of T2D.

6.
EBioMedicine ; 58: 102932, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32763829

RESUMO

BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. FINDINGS: A higher Tpred score was associated with healthier diets high in wholegrain (ß=3.36 g, 95% CI 0.31, 6.40 and ß=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (ß=-75.53 kcal, 95% CI -144.71, -2.35 and ß=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (ß=-0.92 g, 95% CI -1.56, -0.28 and ß=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (ß=0.07 mmol/L, 95% CI 0.03, 0.1), (ß=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (ß=-0.1 mmol/L, 95% CI -0.2, -0.03), (ß=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (ß=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (ß=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (ß=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (ß=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (ß=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (ß=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. INTERPRETATION: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. FUNDING: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies.

7.
Nature ; 582(7811): 240-245, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32499647

RESUMO

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.


Assuntos
Grupo com Ancestrais do Continente Asiático/genética , Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Aldeído-Desidrogenase Mitocondrial/genética , Alelos , Anquirinas/genética , Índice de Massa Corporal , Estudos de Casos e Controles , Europa (Continente)/etnologia , Proteínas do Olho/genética , Extremo Oriente/etnologia , Feminino , Estudo de Associação Genômica Ampla , Proteínas de Homeodomínio/genética , Humanos , Masculino , Proteínas do Tecido Nervoso/genética , RNA Mensageiro/análise , Fatores de Transcrição/genética , Transcrição Genética
8.
Nat Commun ; 11(1): 2797, 2020 06 03.
Artigo em Inglês | MEDLINE | ID: mdl-32493999

RESUMO

Fat distribution is an independent cardiometabolic risk factor. However, its molecular and cellular underpinnings remain obscure. Here we demonstrate that two independent GWAS signals at RSPO3, which are associated with increased body mass index-adjusted waist-to-hip ratio, act to specifically increase RSPO3 expression in subcutaneous adipocytes. These variants are also associated with reduced lower-body fat, enlarged gluteal adipocytes and insulin resistance. Based on human cellular studies RSPO3 may limit gluteofemoral adipose tissue (AT) expansion by suppressing adipogenesis and increasing gluteal adipocyte susceptibility to apoptosis. RSPO3 may also promote upper-body fat distribution by stimulating abdominal adipose progenitor (AP) proliferation. The distinct biological responses elicited by RSPO3 in abdominal versus gluteal APs in vitro are associated with differential changes in WNT signalling. Zebrafish carrying a nonsense rspo3 mutation display altered fat distribution. Our study identifies RSPO3 as an important determinant of peripheral AT storage capacity.


Assuntos
Adipócitos/citologia , Adipócitos/metabolismo , Distribuição da Gordura Corporal , Peptídeos e Proteínas de Sinalização Intracelular/metabolismo , Trombospondinas/metabolismo , Proteínas de Peixe-Zebra/metabolismo , Adipócitos/efeitos dos fármacos , Tecido Adiposo/metabolismo , Adiposidade/genética , Adulto , Alelos , Animais , Biomarcadores/metabolismo , Diferenciação Celular/efeitos dos fármacos , Linhagem Celular , Tamanho Celular/efeitos dos fármacos , Doxiciclina/farmacologia , Feminino , Regulação da Expressão Gênica/efeitos dos fármacos , Glucose/metabolismo , Humanos , Peptídeos e Proteínas de Sinalização Intracelular/genética , Masculino , Pessoa de Meia-Idade , Mutação/genética , Polimorfismo de Nucleotídeo Único/genética , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Caracteres Sexuais , Células-Tronco/metabolismo , Trombospondinas/genética , Relação Cintura-Quadril , Via de Sinalização Wnt/efeitos dos fármacos , Peixe-Zebra/genética , Proteínas de Peixe-Zebra/genética
9.
Diabetes Care ; 43(7): 1617-1635, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32561617

RESUMO

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

10.
Diabetologia ; 63(9): 1671-1693, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32556613

RESUMO

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

11.
Mol Genet Genomics ; 295(4): 1013-1026, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32363570

RESUMO

Obesity, a risk factor for multiple diseases (e.g. diabetes, hypertension, cancers) originates through complex interactions between genes and prevailing environment (food habit and lifestyle) that varies across populations. Indians exhibit a unique obesity phenotype with high abdominal adiposity for a given body weight compared to matched white populations suggesting presence of population-specific genetic and environmental factors influencing obesity. However, Indian population-specific genetic contributors for obesity have not been explored yet. Therefore, to identify potential genetic contributors, we performed a two-staged genome-wide association study (GWAS) for body mass index (BMI), a common measure to evaluate obesity in 5973 Indian adults and the lead findings were further replicated in 1286 Indian adolescents. Our study revealed novel association of variants-rs6913677 in BAI3 gene (p = 1.08 × 10-8) and rs2078267 in SLC22A11 gene (p = 4.62 × 10-8) at GWAS significance, and of rs8100011 in ZNF45 gene (p = 1.04 × 10-7) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped genetic data of identified signals with their DNA methylation patterns in 236 Indian individuals and performed methylation quantitative trait loci (meth-QTL) analysis. Further, functional roles of discovered variants and underlying genes were speculated using publicly available gene regulatory databases (ENCODE, JASPAR, GeneHancer, GTEx). The identified variants in BAI3 and SLC22A11 genes were found to dictate methylation patterns at unique CpGs harboring critical cis-regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were located in repressive chromatin, active enhancer, and active chromatin regions, respectively, in human subcutaneous adipose tissue in ENCODE database. Additionally, these genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, GTEx portal identify rs8100011 as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue (p = 1.6 × 10-7), and ZNF45 gene expression in skeletal muscle of Indian subjects showed an inverse correlation with BMI indicating its possible role in obesity. In conclusion, our study discovered 3 novel population-specific functional genetic variants (rs6913677, rs2078267, rs8100011) in 2 novel (SLC22A11 and ZNF45) and 1 earlier reported gene (BAI3) for BMI in Indians. Our study decodes key genomic loci underlying obesity phenotype in Indians that may serve as prospective drug targets in future.


Assuntos
Estudo de Associação Genômica Ampla , Fatores de Transcrição Kruppel-Like/genética , Obesidade/genética , Transportadores de Ânions Orgânicos Sódio-Independentes/genética , Proteínas Repressoras/genética , Adolescente , Adulto , Grupo com Ancestrais do Continente Asiático/genética , Índice de Massa Corporal , Metilação de DNA , Feminino , Interação Gene-Ambiente , Predisposição Genética para Doença , Humanos , Índios Norte-Americanos/genética , Masculino , Obesidade/patologia , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas/genética , Sequências Reguladoras de Ácido Nucleico/genética , Adulto Jovem
12.
Artigo em Inglês | MEDLINE | ID: mdl-32395877

RESUMO

OBJECTIVE AND CONTEXT: Maturity onset diabetes of the young due to variants in HNF1A (HNF1A-MODY) is the most common form of monogenic diabetes. Individuals with HNF1A-MODY usually have a lean phenotype which contrasts with type 2 diabetes (T2DM). Data from hepatocytes derived from Hnf1a knock-out mice demonstrated dysregulation of 11ß-hydroxysteroid dehydrogenase type 1 (11ß-HSD1), which regulates glucocorticoid availability and action in target tissues, together with 11ß-HSD2 and steroid A-ring reductases, 5α- and 5ß-reductase. We proposed that altered glucocorticoid metabolism might underpin some of the phenotypic differences between patients with HNF1A-MODY and those with T2DM. DESIGN: A retrospective matched cohort study. PATIENTS AND MEASUREMENTS: 24-hours urine steroid metabolome profiling was carried out by gas chromatography-mass spectrometry in 35 subjects with HNF1A-MODY, 35 individuals with T2DM and 35 healthy controls matched for age, sex and BMI. The steroid metabolites were expressed as µg/L in all groups and measured in mid-morning urine in diabetic subjects and 24-hour urine collection in healthy controls. Hence, only ratios were compared not the individual steroids. Established ratios of glucocorticoid metabolites were used to estimate 11ß-HSD1/2 and 5α- and 5ß-reductase activities. RESULTS: While 11ß-HSD1 activity was similar in all groups, 11ß-HSD2 activity was significantly lower in subjects with HNF1A-MODY and T2DM than in healthy controls. The ratio of 5ß- to 5α-metabolites of cortisol was higher in subjects with HNF1A-MODY than in T2DM and healthy controls, probably due to increased activity of the 5ß-reductase (AKR1D1) in HNF1A-MODY. CONCLUSIONS: This is the first report of steroid metabolites in HNF1A-MODY. We have identified distinct differences in steroid metabolism pathways in subjects with HNF1A-MODY that have the potential to alter steroid hormone availability. Further studies are required to explore whether these changes link to phenotype.

15.
Cell ; 181(4): 832-847.e18, 2020 May 14.
Artigo em Inglês | MEDLINE | ID: mdl-32304665

RESUMO

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Molecular analyses of human and murine samples define microenvironmental consequences of obesity that foster tumorigenesis rather than new driver gene mutations, including significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant beta cell expression of the peptide hormone cholecystokinin (Cck) in response to obesity and show that islet Cck promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment and implicate endocrine-exocrine signaling beyond insulin in PDAC development.

16.
Nat Med ; 26(2): 252-258, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-32042192

RESUMO

Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22-1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33-1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76-0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses.


Assuntos
Diabetes Mellitus Tipo 2/sangue , Síndrome do Ovário Policístico/sangue , Testosterona/sangue , Testosterona/farmacologia , Bancos de Espécimes Biológicos , Biomarcadores/sangue , Composição Corporal , Neoplasias da Mama/sangue , Neoplasias da Mama/genética , Análise por Conglomerados , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/genética , Neoplasias do Endométrio/sangue , Neoplasias do Endométrio/genética , Estradiol/sangue , Feminino , Estudo de Associação Genômica Ampla , Genótipo , Haplótipos , Humanos , Masculino , Análise da Randomização Mendeliana , Razão de Chances , Fenótipo , Síndrome do Ovário Policístico/etiologia , Síndrome do Ovário Policístico/genética , Polimorfismo de Nucleotídeo Único , Neoplasias da Próstata/sangue , Neoplasias da Próstata/genética , Fatores Sexuais , Software , Reino Unido
17.
Diabetologia ; 63(4): 744-756, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32002573

RESUMO

AIMS/HYPOTHESIS: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). METHODS: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. RESULTS: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. CONCLUSIONS/INTERPRETATION: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

18.
Elife ; 92020 Jan 27.
Artigo em Inglês | MEDLINE | ID: mdl-31985400

RESUMO

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

19.
Nature ; 577(7789): 179-189, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31915397

RESUMO

A primary goal of human genetics is to identify DNA sequence variants that influence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition.


Assuntos
Variação Genética , Animais , Testes Genéticos , Genômica , Genótipo , Humanos , Fenótipo , Doenças Raras/genética
20.
Am J Hum Genet ; 106(2): 188-201, 2020 02 06.
Artigo em Inglês | MEDLINE | ID: mdl-31978332

RESUMO

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.


Assuntos
Regulação da Expressão Gênica , Predisposição Genética para Doença , Metaboloma , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Transcriptoma , Estudo de Associação Genômica Ampla , Humanos , Fenótipo
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA