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1.
J Diabetes Complications ; : 107842, 2021 Jan 09.
Artigo em Inglês | MEDLINE | ID: mdl-33468396

RESUMO

AIMS: To examine candidate insulin resistance single nucleotide polymorphisms (SNPs) for associations with glycemic control, insulin resistance, BMI, and complications in an observational type 1 diabetes (T1D) cohort: the Pittsburgh Epidemiology of Diabetes Complications (EDC) study. METHODS: In 422 European-ancestry participants, we assessed associations using additive models between 15 candidate SNPs and 25-year mortality, cardiovascular disease, microalbuminuria, overt nephropathy and proliferative retinopathy, and 25-year mean HbA1c, estimated glucose disposal rate (eGDR, inverse measure of insulin resistance), and BMI. RESULTS: The A allele of rs12970134 was associated with higher mean HbA1c (ß = +0.34 ±â€¯0.09, p = 0.00009) and nominally associated with worse eGDR (p = 0.02). Further analyses suggest the HbA1c association may be modified by diabetes therapy regimen: rs12970134 AA genotype was associated with higher HbA1c under non-intensive therapy conditions (<3 insulin injections/day or monitoring blood glucose<3 times/day [p = 0.004]), but not under intensive therapy (≥3 injections/day or insulin pump and monitoring glucose≥3 times/day [p = 0.71]). There were no significant associations between any SNPs and BMI or complications. CONCLUSIONS: rs12970134, near MC4R, is strongly associated with HbA1c in this cohort. Further exploration of this genomic region is warranted, as it may hold promise for discovering new therapeutic targets to improve glycemic control in T1D.

2.
J Diabetes ; 13(2): 143-153, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33124145

RESUMO

BACKGROUND: The Environmental Determinants of the Diabetes in the Young (TEDDY) study has prospectively followed, from birth, children at increased genetic risk of type 1 diabetes. TEDDY has collected heterogenous data longitudinally to gain insights into the environmental and biological mechanisms driving the progression to persistent islet autoantibodies. METHODS: We developed a machine learning model to predict imminent transition to the development of persistent islet autoantibodies based on time-varying metabolomics data integrated with time-invariant risk factors (eg, gestational age). The machine learning was initiated with 221 potential features (85 genetic, 5 environmental, 131 metabolomic) and an ensemble-based feature evaluation was utilized to identify a small set of predictive features that can be interrogated to better understand the pathogenesis leading up to persistent islet autoimmunity. RESULTS: The final integrative machine learning model included 42 disparate features, returning a cross-validated receiver operating characteristic area under the curve (AUC) of 0.74 and an AUC of ~0.65 on an independent validation dataset. The model identified a principal set of 20 time-invariant markers, including 18 genetic markers (16 single nucleotide polymorphisms [SNPs] and two HLA-DR genotypes) and two demographic markers (gestational age and exposure to a prebiotic formula). Integration with the metabolome identified 22 supplemental metabolites and lipids, including adipic acid and ceramide d42:0, that predicted development of islet autoantibodies. CONCLUSIONS: The majority (86%) of metabolites that predicted development of islet autoantibodies belonged to three pathways: lipid oxidation, phospholipase A2 signaling, and pentose phosphate, suggesting that these metabolic processes may play a role in triggering islet autoimmunity.

4.
Artigo em Inglês | MEDLINE | ID: mdl-33332990

RESUMO

Parental health influences embryonic development and susceptibility to disease in the offspring. We investigated whether maternal voluntary running during gestation could protect the offspring from the adverse effects of maternal or paternal high-fat diet (HF) in mice. We performed transcriptomic and whole-genome DNA methylation analyses in female offspring skeletal muscle as well as targeted DNA methylation analysis of the peroxisome proliferator-activated receptor γ coactivator-1α (Pgc-1α) promoter in the both male and female adult offspring. Maternal HF resulted in impaired metabolic homeostasis in male offspring at 9 months of age, while both male and female offspring were negatively impacted by paternal HF. Maternal exercise during gestation completely mitigated these metabolic impairments. Female adult offspring from obese male or female parent had skeletal muscle transcriptional profiles enriched in genes regulating inflammation and immune responses, whereas maternal exercise resulted in a transcriptional profile similar to offspring from normal chow fed parents. Maternal HF, but not paternal HF, resulted in hypermethylation of the Pgc-1α promoter at CpG -260, which was abolished by maternal exercise. These findings demonstrate the negative consequences of maternal and paternal HF for the offspring's metabolic outcomes later in life possibly through different epigenetic mechanisms, and maternal exercise during gestation mitigates the negative consequences.

5.
J Endocr Soc ; 4(11): bvaa121, 2020 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-33150273

RESUMO

Glucocorticoids have multiple therapeutic benefits and are used both for immunosuppression and treatment purposes. Notwithstanding their benefits, glucocorticoid use often leads to hyperglycemia. Owing to the pathophysiologic overlap in glucocorticoid-induced hyperglycemia (GIH) and type 2 diabetes (T2D), we hypothesized that genetic variation in glucocorticoid pathways contributes to T2D risk. To determine the genetic contribution of glucocorticoid action on T2D risk, we conducted multiple genetic studies. First, we performed gene-set enrichment analyses on 3 collated glucocorticoid-related gene sets using publicly available genome-wide association and whole-exome data and demonstrated that genetic variants in glucocorticoid-related genes are associated with T2D and related glycemic traits. To identify which genes are driving this association, we performed gene burden tests using whole-exome sequence data. We identified 20 genes within the glucocorticoid-related gene sets that are nominally enriched for T2D-associated protein-coding variants. The most significant association was found in coding variants in coiled-coil α-helical rod protein 1 (CCHCR1) in the HLA region (P = .001). Further analyses revealed that noncoding variants near CCHCR1 are also associated with T2D at genome-wide significance (P = 7.70 × 10-14), independent of type 1 diabetes HLA risk. Finally, gene expression and colocalization analyses demonstrate that variants associated with increased T2D risk are also associated with decreased expression of CCHCR1 in multiple tissues, implicating this gene as a potential effector transcript at this locus. Our discovery of a genetic link between glucocorticoids and T2D findings support the hypothesis that T2D and GIH may have shared underlying mechanisms.

6.
PLoS One ; 15(11): e0230035, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33186364

RESUMO

BACKGROUND: Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. METHODS AND RESULTS: Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. CONCLUSION: This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.


Assuntos
Envelhecimento/genética , Doença da Artéria Coronariana/genética , Grupo com Ancestrais do Continente Europeu/genética , Loci Gênicos , Estudo de Associação Genômica Ampla , Infarto do Miocárdio/genética , Polimorfismo de Nucleotídeo Único , Doença da Artéria Coronariana/epidemiologia , Doença da Artéria Coronariana/mortalidade , Estudos Transversais , Europa (Continente)/epidemiologia , Humanos , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/mortalidade , Estudos Prospectivos
7.
Sci Rep ; 10(1): 19193, 2020 11 05.
Artigo em Inglês | MEDLINE | ID: mdl-33154504

RESUMO

Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10-8) and three regions, 1q21.3 (MRPS21-PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10-8) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

8.
Diabetologia ; 63(11): 2260-2269, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32797243

RESUMO

The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. Graphical abstract.

9.
J Clin Endocrinol Metab ; 105(12)2020 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-32772088

RESUMO

CONTEXT: Crosstalk through receptor ligand interactions at the maternal-fetal interface is impacted by fetal sex. This affects placentation in the first trimester and differences in outcomes. Sexually dimorphic signaling at early stages of placentation are not defined. OBJECTIVE: Investigate the impact of fetal sex on maternal-fetal crosstalk. DESIGN: Receptors/ligands at the maternal-fetal surface were identified from sexually dimorphic genes between fetal sexes in the first trimester placenta and defined in each cell type using single-cell RNA-Sequencing (scRNA-Seq). SETTING: Academic institution. SAMPLES: Late first trimester (~10-13 weeks) placenta (fetal) and decidua (maternal) from uncomplicated ongoing pregnancies. MAIN OUTCOME MEASURES: Transcriptomic profiling at tissue and single-cell level; immunohistochemistry of select proteins. RESULTS: We identified 91 sexually dimorphic receptor-ligand pairs across the maternal-fetal interface. We examined fetal sex differences in 5 major cell types (trophoblasts, stromal cells, Hofbauer cells, antigen-presenting cells, and endothelial cells). Ligands from the CC family chemokine ligand (CCL) family were most highly representative in females, with their receptors present on the maternal surface. Sexually dimorphic trophoblast transcripts, Mucin-15 (MUC15) and notum, palmitoleoyl-protein carboxylesterase (NOTUM) were also most highly expressed in syncytiotrophoblasts and extra-villous trophoblasts respectively. Gene Ontology (GO) analysis using sexually dimorphic genes in individual cell types identified cytokine mediated signaling pathways to be most representative in female trophoblasts. Upstream analysis demonstrated TGFB1 and estradiol to affect all cell types, but dihydrotestosterone, produced by the male fetus, was an upstream regulator most significant for the trophoblast population. CONCLUSIONS: Maternal-fetal crosstalk exhibits sexual dimorphism during placentation early in gestation.

10.
Nat Genet ; 52(9): 969-983, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32839606

RESUMO

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.


Assuntos
Predisposição Genética para Doença/genética , Variação Genética/genética , Genoma/genética , LDL-Colesterol/genética , Simulação por Computador , Estudo de Associação Genômica Ampla/métodos , Humanos , Modelos Genéticos , Anotação de Sequência Molecular/métodos , Fenótipo , Sequenciamento Completo do Genoma/métodos
11.
Lancet Respir Med ; 8(7): 696-708, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32649918

RESUMO

BACKGROUND: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. METHODS: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth. FINDINGS: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74-1·88] and non-European (1·42 [1·34-1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56-9·72) in European ancestry and 4·83 (3·45-6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79-0·81] vs 0·76 [0·75-0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern. INTERPRETATION: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth. FUNDING: US National Institutes of Health, Wellcome Trust.


Assuntos
Doença Pulmonar Obstrutiva Crônica/epidemiologia , Doença Pulmonar Obstrutiva Crônica/genética , Adulto , Estudos de Casos e Controles , Estudos de Coortes , Feminino , Volume Expiratório Forçado , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Doença Pulmonar Obstrutiva Crônica/diagnóstico , Fatores de Risco , Capacidade Vital
12.
Stroke ; 51(8): 2454-2463, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32693751

RESUMO

BACKGROUND AND PURPOSE: Stroke is a complex disease with multiple genetic and environmental risk factors. Blacks endure a nearly 2-fold greater risk of stroke and are 2× to 3× more likely to die from stroke than European Americans. METHODS: The COMPASS (Consortium of Minority Population Genome-Wide Association Studies of Stroke) has conducted a genome-wide association meta-analysis of stroke in >22 000 individuals of African ancestry (3734 cases, 18 317 controls) from 13 cohorts. RESULTS: In meta-analyses, we identified one single nucleotide polymorphism (rs55931441) near the HNF1A gene that reached genome-wide significance (P=4.62×10-8) and an additional 29 variants with suggestive evidence of association (P<1×10-6), representing 24 unique loci. For validation, a look-up analysis for a 100 kb region flanking the COMPASS single nucleotide polymorphism was performed in SiGN (Stroke Genetics Network) Europeans, SiGN Hispanics, and METASTROKE (Europeans). Using a stringent Bonferroni correction P value of 2.08×10-3 (0.05/24 unique loci), we were able to validate associations at the HNF1A locus in both SiGN (P=8.18×10-4) and METASTROKE (P=1.72×10-3) European populations. Overall, 16 of 24 loci showed evidence for validation across multiple populations. Previous studies have reported associations between variants in the HNF1A gene and lipids, C-reactive protein, and risk of coronary artery disease and stroke. Suggestive associations with variants in the SFXN4 and TMEM108 genes represent potential novel ischemic stroke loci. CONCLUSIONS: These findings represent the most thorough investigation of genetic determinants of stroke in individuals of African descent, to date.


Assuntos
Afro-Americanos/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único/genética , Acidente Vascular Cerebral/genética , Afro-Americanos/etnologia , Estudos de Coortes , Predisposição Genética para Doença/etnologia , Humanos , Acidente Vascular Cerebral/etnologia
13.
Diabetes Obes Metab ; 22(11): 1976-1984, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32687239

RESUMO

AIM: To investigate the role of the gut microbiome in regulating key insulin homeostasis traits (insulin sensitivity, insulin secretion and insulin clearance) whose dysfunction leads to type 2 diabetes (T2D). MATERIALS AND METHODS: The Microbiome and Insulin Longitudinal Evaluation Study (MILES) focuses on African American and non-Hispanic white participants aged 40-80 years without diabetes. Three study visits are planned (at baseline, 15 and 30 months). Baseline measurements include assessment of the stool microbiome and administration of an oral glucose tolerance test, which will yield indexes of insulin sensitivity, insulin secretion and insulin clearance. The gut microbiome profile (composition and function) will be determined using whole metagenome shotgun sequencing along with analyses of plasma short chain fatty acids. Additional data collected include dietary history, sociodemographic factors, health habits, anthropometry, medical history, medications and family history. Most assessments are repeated 15 and 30 months following baseline. RESULTS: After screening 875 individuals, 129 African American and 224 non-Hispanic white participants were enrolled. At baseline, African American participants have higher blood pressure, weight, body mass index, waist and hip circumferences but similar waist-hip ratio compared with the non-Hispanic white participants. On average, African American participants are less insulin-sensitive and have higher acute insulin secretion and lower insulin clearance. CONCLUSIONS: The longitudinal design and robust characterization of potential mediators will allow for the assessment of glucose and insulin homeostasis and gut microbiota as they change over time, improving our ability to discern causal relationships between the microbiome and the insulin homeostasis traits whose deterioration determines T2D, setting the stage for future microbiome-directed therapies to prevent and treat T2D.

14.
Diabetes Care ; 43(7): 1617-1635, 2020 07.
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.

15.
EBioMedicine ; 56: 102803, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32512511

RESUMO

BACKGROUND: Sleep Disordered Breathing (SDB) is associated with a wide range of pathophysiological changes due, in part, to hypoxemia during sleep. We sought to identify gene transcription associations with measures of SDB and hypoxemia during sleep, and study their response to treatment. METHODS: In two discovery cohorts, Framingham Offspring Study (FOS; N = 571) and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 580), we studied gene expression in peripheral blood mononuclear cells in association with three measures of SDB: Apnea Hypopnea Index (AHI); average oxyhemoglobin saturation (avgO2) during sleep; and minimum oxyhemoglobin saturation (minO2) during sleep. Associated genes were used for analysis of gene expression in the blood of 15 participants with moderate or severe obstructive sleep apnea (OSA) from the Heart Biomarkers In Apnea Treatment (HeartBEAT) trial. These genes were studied pre- and post-treatment (three months) with continuous positive airway pressure (CPAP). We also performed Gene Set Enrichment Analysis (GSEA) on all traits and cohort analyses. FINDINGS: Twenty-two genes were associated with SDB traits in both MESA and FOS. Of these, lower expression of CD1D and RAB20 was associated with lower avgO2 in MESA and FOS. CPAP treatment increased the expression of these genes in HeartBEAT participants. Immunity and inflammation pathways were up-regulated in subjects with lower avgO2; i.e., in those with a more severe SDB phenotype (MESA), whereas immuno-inflammatory processes were down-regulated following CPAP treatment (HeartBEAT). INTERPRETATION: Low oxygen saturation during sleep is associated with alterations in gene expression and transcriptional programs that are partially reversed by CPAP treatment.

16.
Diabetologia ; 63(9): 1671-1693, 2020 09.
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.

17.
Circ Genom Precis Med ; 13(4): e002772, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32510982

RESUMO

BACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels. METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered. RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (PCSK9, LPA, LPL, LIPG, ANGPTL4, APOB, APOC3, and CD300LG) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (P=6.65×10-6 for the interaction test) and replicated at nominal significance level (P=0.013) in SMC5. CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

18.
Nature ; 581(7809): 444-451, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32461652

RESUMO

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.


Assuntos
Doença/genética , Variação Genética , Genética Médica/normas , Genética Populacional/normas , Genoma Humano/genética , Grupos de Populações Continentais/genética , Feminino , Testes Genéticos , Técnicas de Genotipagem , Humanos , Masculino , Pessoa de Meia-Idade , Mutação , Polimorfismo de Nucleotídeo Único/genética , Padrões de Referência , Seleção Genética , Sequenciamento Completo do Genoma
19.
Proteomics ; 20(12): e1900278, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32386347

RESUMO

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.

20.
FASEB J ; 34(6): 7330-7344, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32304342

RESUMO

Our understanding of the molecular mechanisms underlying adaptations to resistance exercise remains elusive despite the significant biological and clinical relevance. We developed a novel voluntary mouse weightlifting model, which elicits squat-like activities against adjustable load during feeding, to investigate the resistance exercise-induced contractile and metabolic adaptations. RNAseq analysis revealed that a single bout of weightlifting induced significant transcriptome responses of genes that function in posttranslational modification, metabolism, and muscle differentiation in recruited skeletal muscles, which were confirmed by increased expression of fibroblast growth factor-inducible 14 (Fn14), Down syndrome critical region 1 (Dscr1) and Nuclear receptor subfamily 4, group A, member 3 (Nr4a3) genes. Long-term (8 weeks) voluntary weightlifting training resulted in significantly increases of muscle mass, protein synthesis (puromycin incorporation in SUnSET assay) and mTOR pathway protein expression (raptor, 4e-bp-1, and p70S6K proteins) along with enhanced muscle power (specific torque and contraction speed), but not endurance capacity, mitochondrial biogenesis, and fiber type transformation. Importantly, weightlifting training profound improved whole-body glucose clearance and skeletal muscle insulin sensitivity along with enhanced autophagy (increased LC3 and LC3-II/I ratio, and decreased p62/Sqstm1). These data suggest that resistance training in mice promotes muscle adaptation and insulin sensitivity with simultaneous enhancement of autophagy and mTOR pathway.

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