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1.
Blood Cells Mol Dis ; 86: 102504, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-32949984

RESUMO

In a recent clinical trial, the metabolite l-glutamine was shown to reduce painful crises in sickle cell disease (SCD) patients. To support this observation and identify other metabolites implicated in SCD clinical heterogeneity, we profiled 129 metabolites in the plasma of 705 SCD patients. We tested correlations between metabolite levels and six SCD-related complications (painful crises, cholecystectomy, retinopathy, leg ulcer, priapism, aseptic necrosis) or estimated glomerular filtration rate (eGFR), and used Mendelian randomization (MR) to assess causality. We found a potential causal relationship between l-glutamine levels and painful crises (N = 1278, odds ratio (OR) [95% confidence interval] = 0.68 [0.52-0.89], P = 0.0048). In two smaller SCD cohorts (N = 299 and 406), the protective effect of l-glutamine was observed (OR = 0.82 [0.50-1.34]), although the MR result was not significant (P = 0.44). We identified 66 significant correlations between the levels of other metabolites and SCD-related complications or eGFR. We tested these correlations for causality using MR analyses and found no significant causal relationship. The baseline levels of quinolinic acid were associated with prospectively ascertained survival in SCD patients, and this effect was dependent on eGFR. Metabolomics provide a promising approach to prioritize small molecules that may serve as biomarkers or drug targets in SCD.

3.
Nat Hum Behav ; 2020 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-32989287

RESUMO

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.

4.
J Clin Endocrinol Metab ; 105(10)2020 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-32652002

RESUMO

CONTEXT: Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness. OBJECTIVE: To identify genetic variants associated with GH responsiveness. DESIGN: Genome-wide association study (GWAS). SETTING: Cohorts from multiple academic centers and a clinical trial. PATIENTS: A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age. INTERVENTION: Association of more than 2 million variants was tested. MAIN OUTCOME MEASURES: Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness. RESULTS: No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score. CONCLUSIONS: We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height.

5.
Nature ; 582(7811): 234-239, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32499652

RESUMO

On average, Peruvian individuals are among the shortest in the world1. Here we show that Native American ancestry is associated with reduced height in an ethnically diverse group of Peruvian individuals, and identify a population-specific, missense variant in the FBN1 gene (E1297G) that is significantly associated with lower height. Each copy of the minor allele (frequency of 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). To our knowledge, this is the largest effect size known for a common height-associated variant. FBN1 encodes the extracellular matrix protein fibrillin 1, which is a major structural component of microfibrils. We observed less densely packed fibrillin-1-rich microfibrils with irregular edges in the skin of individuals who were homozygous for G1297 compared with individuals who were homozygous for E1297. Moreover, we show that the E1297G locus is under positive selection in non-African populations, and that the E1297 variant shows subtle evidence of positive selection specifically within the Peruvian population. This variant is also significantly more frequent in coastal Peruvian populations than in populations from the Andes or the Amazon, which suggests that short stature might be the result of adaptation to factors that are associated with the coastal environment in Peru.


Assuntos
Estatura/genética , Fibrilina-1/genética , Mutação de Sentido Incorreto , Seleção Genética , Feminino , Frequência do Gene , Estudo de Associação Genômica Ampla , Hereditariedade , Humanos , Índios Sul-Americanos/genética , Masculino , Microfibrilas/química , Microfibrilas/genética , Peru
6.
Hum Mol Genet ; 29(15): 2625-2636, 2020 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-32484228

RESUMO

The growth hormone and insulin-like growth factor (IGF) system is integral to human growth. Genome-wide association studies (GWAS) have identified variants associated with height and located near the genes in this pathway. However, mechanisms underlying these genetic associations are not understood. To investigate the regulation of the genes in this pathway and mechanisms by which regulation could affect growth, we performed GWAS of measured serum protein levels of IGF-I, IGF binding protein-3 (IGFBP-3), pregnancy-associated plasma protein A (PAPP-A2), IGF-II and IGFBP-5 in 838 children (3-18 years) from the Cincinnati Genomic Control Cohort. We identified variants associated with protein levels near IGFBP3 and IGFBP5 genes, which contain multiple signals of association with height and other skeletal growth phenotypes. Surprisingly, variants that associate with protein levels at these two loci do not colocalize with height associations, confirmed through conditional analysis. Rather, the IGFBP3 signal (associated with total IGFBP-3 and IGF-II levels) colocalizes with an association with sitting height ratio (SHR); the IGFBP5 signal (associated with IGFBP-5 levels) colocalizes with birth weight. Indeed, height-associated single nucleotide polymorphisms near genes encoding other proteins in this pathway are not associated with serum levels, possibly excluding PAPP-A2. Mendelian randomization supports a stronger causal relationship of measured serum levels with SHR (for IGFBP-3) and birth weight (for IGFBP-5) than with height. In conclusion, we begin to characterize the genetic regulation of serum levels of IGF-related proteins in childhood. Furthermore, our data strongly suggest the existence of growth-regulating mechanisms acting through IGF-related genes in ways that are not reflected in measured serum levels of the corresponding proteins.

7.
Int J Obes (Lond) ; 44(7): 1596-1606, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32467615

RESUMO

BACKGROUND: Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analysis (Mendelian randomization) to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals. METHODS: We expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS. RESULTS: We identified ten known metabolites that are more likely to be causes (e.g., alpha-hydroxybutyrate) or effects (e.g., valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g., glycine). Importantly, we also identified about five times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms. CONCLUSIONS: These findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

8.
Nature ; 583(7814): 122-126, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32461692

RESUMO

The cellular NADH/NAD+ ratio is fundamental to biochemistry, but the extent to which it reflects versus drives metabolic physiology in vivo is poorly understood. Here we report the in vivo application of Lactobacillus brevis (Lb)NOX1, a bacterial water-forming NADH oxidase, to assess the metabolic consequences of directly lowering the hepatic cytosolic NADH/NAD+ ratio in mice. By combining this genetic tool with metabolomics, we identify circulating α-hydroxybutyrate levels as a robust marker of an elevated hepatic cytosolic NADH/NAD+ ratio, also known as reductive stress. In humans, elevations in circulating α-hydroxybutyrate levels have previously been associated with impaired glucose tolerance2, insulin resistance3 and mitochondrial disease4, and are associated with a common genetic variant in GCKR5, which has previously been associated with many seemingly disparate metabolic traits. Using LbNOX, we demonstrate that NADH reductive stress mediates the effects of GCKR variation on many metabolic traits, including circulating triglyceride levels, glucose tolerance and FGF21 levels. Our work identifies an elevated hepatic NADH/NAD+ ratio as a latent metabolic parameter that is shaped by human genetic variation and contributes causally to key metabolic traits and diseases. Moreover, it underscores the utility of genetic tools such as LbNOX to empower studies of 'causal metabolism'.


Assuntos
Fígado/metabolismo , NAD/metabolismo , Estresse Fisiológico , Proteínas Adaptadoras de Transdução de Sinal/genética , Animais , Citosol/metabolismo , Modelos Animais de Doenças , Fatores de Crescimento de Fibroblastos/sangue , Variação Genética , Teste de Tolerância a Glucose , Humanos , Resistência à Insulina , Lactobacillus brevis/enzimologia , Lactobacillus brevis/genética , Masculino , Camundongos , Complexos Multienzimáticos/genética , Complexos Multienzimáticos/metabolismo , NADH NADPH Oxirredutases/genética , NADH NADPH Oxirredutases/metabolismo , Oxirredução , Triglicerídeos/sangue
9.
Nat Commun ; 11(1): 1467, 2020 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-32193382

RESUMO

Unhealthful dietary habits are leading risk factors for life-altering diseases and mortality. Large-scale biobanks now enable genetic analysis of traits with modest heritability, such as diet. We perform a genomewide association on 85 single food intake and 85 principal component-derived dietary patterns from food frequency questionnaires in UK Biobank. We identify 814 associated loci, including olfactory receptor associations with fruit and tea intake; 136 associations are only identified using dietary patterns. Mendelian randomization suggests our top healthful dietary pattern driven by wholemeal vs. white bread consumption is causally influenced by factors correlated with education but is not strongly causal for coronary artery disease or type 2 diabetes. Overall, we demonstrate the value in complementary phenotyping approaches to complex dietary datasets, and the utility of genomic analysis to understand the relationships between diet and human health.


Assuntos
Bancos de Espécimes Biológicos , Comportamento Alimentar , Estudos de Associação Genética , Genômica , Ingestão de Alimentos , Loci Gênicos , Estudo de Associação Genômica Ampla , Humanos , Padrões de Herança/genética , Análise da Randomização Mendeliana , Polimorfismo de Nucleotídeo Único/genética , Análise de Componente Principal , Receptores Odorantes/metabolismo , Fatores de Risco , Reino Unido
10.
Genet Med ; 22(2): 371-380, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31481752

RESUMO

PURPOSE: Clinicians and researchers must contextualize a patient's genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care. METHODS: Three of the nation's leading children's hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model. RESULTS: Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype-phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications. CONCLUSIONS: The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.

12.
Horm Res Paediatr ; 92(3): 186-195, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31865343

RESUMO

INTRODUCTION: Short stature is one of the most common reasons for referral to a pediatric endocrinologist and can result from many etiologies. However, many patients with short stature do not receive a definitive diagnosis. OBJECTIVE: To ascertain whether integrating targeted bioinformatics searches of electronic health records (EHRs) combined with genomic studies could identify patients with previously undiagnosed rare genetic etiologies of short stature. We focused on a specific rare phenotypic subgroup: patients with short stature and elevated IGF-I levels. METHODS: We performed a cross-sectional cohort study at three large academic pediatric healthcare networks. Eligible subjects included children with heights below -2 SD, IGF-I levels >90th percentile, and no known etiology for short stature. We performed a search of the EHRs to identify eligible patients. Patients were then recruited for phenotyping followed by exome sequencing and in vitro assays of IGF1R function. RESULTS: A total of 234 patients were identified by the bioinformatics algorithm with 39 deemed eligible after manual review (17%). Of those, 9 were successfully recruited. A genetic etiology was identified in 3 of the 9 patients including 2 novel variants in IGF1R and a de novo variant in CHD2. In vitro studies supported the pathogenicity of the IGF1R variants. CONCLUSIONS: This study provides proof of principle that patients with rare phenotypic subgroups can be identified based on discrete data elements in the EHRs. Although limitations exist to fully automating this approach, these searches may help find patients with previously unidentified rare genetic disorders.


Assuntos
Estatura/genética , Transtornos do Crescimento/genética , Fator de Crescimento Insulin-Like I/análise , Fenótipo , Adolescente , Criança , Pré-Escolar , Estudos de Coortes , Estudos Transversais , Proteínas de Ligação a DNA/genética , Registros Eletrônicos de Saúde , Feminino , Células HEK293 , Humanos , Masculino , Mutação de Sentido Incorreto , Receptor IGF Tipo 1/química , Receptor IGF Tipo 1/genética , Receptor IGF Tipo 1/fisiologia , Sequenciamento Completo do Exoma
13.
PLoS One ; 14(9): e0222445, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31560688

RESUMO

BACKGROUND: Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. METHODS AND RESULTS: Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10-8) and 5 suggestively (p < 1 × 10-6) significant loci, several of which have been previously linked to obesity-related phenotypes. CONCLUSIONS: We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.


Assuntos
Metaboloma , Obesidade/etiologia , Medição de Risco/métodos , Índice de Massa Corporal , Dieta , Exercício Físico , Feminino , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Obesidade/genética , Obesidade/metabolismo , Ganho de Peso/genética
14.
Am J Epidemiol ; 188(6): 991-1012, 2019 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-31155658

RESUMO

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).


Assuntos
Epidemiologia/organização & administração , Saúde Global , Metabolômica/organização & administração , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Biomarcadores , Índice de Massa Corporal , Criança , Métodos Epidemiológicos , Feminino , Comportamentos Relacionados com a Saúde , Testes Hematológicos , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Fatores Socioeconômicos , Adulto Jovem
15.
Am J Hum Genet ; 104(6): 1025-1039, 2019 06 06.
Artigo em Inglês | MEDLINE | ID: mdl-31056107

RESUMO

Genome-wide association studies (GWASs) are valuable for understanding human biology, but associated loci typically contain multiple associated variants and genes. Thus, algorithms that prioritize likely causal genes and variants for a given phenotype can provide biological interpretations of association data. However, a critical, currently missing capability is to objectively compare performance of such algorithms. Typical comparisons rely on "gold standard" genes harboring causal coding variants, but such gold standards may be biased and incomplete. To address this issue, we developed Benchmarker, an unbiased, data-driven benchmarking method that compares performance of similarity-based prioritization strategies to each other (and to random chance) by leave-one-chromosome-out cross-validation with stratified linkage disequilibrium (LD) score regression. We first applied Benchmarker to 20 well-powered GWASs and compared gene prioritization based on strategies employing three different data sources, including annotated gene sets and gene expression; genes prioritized based on gene sets had higher per-SNP heritability than those prioritized based on gene expression. Additionally, in a direct comparison of three methods, DEPICT and MAGMA outperformed NetWAS. We also evaluated combinations of methods; our results indicated that combining data sources and algorithms can help prioritize higher-quality genes for follow-up. Benchmarker provides an unbiased approach to evaluate any similarity-based method that provides genome-wide prioritization of genes, variants, or gene sets and can determine the best such method for any particular GWAS. Our method addresses an important unmet need for rigorous tool assessment and can assist in mapping genetic associations to causal function.


Assuntos
Algoritmos , Loci Gênicos , Estudo de Associação Genômica Ampla/métodos , Desequilíbrio de Ligação , Polimorfismo de Nucleotídeo Único , Benchmarking , Mapeamento Cromossômico , Humanos , Fenótipo
16.
Commun Biol ; 2: 119, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30937401

RESUMO

There is evidence that lower height is associated with a higher risk of coronary artery disease (CAD) and increased risk of type 2 diabetes (T2D). It is not clear though whether these associations are causal, direct or mediated by other factors. Here we show that one standard deviation higher genetically determined height (~6.5 cm) is causally associated with a 16% decrease in CAD risk (OR = 0.84, 95% CI 0.80-0.87). This causal association remains after performing sensitivity analyses relaxing pleiotropy assumptions. The causal effect of height on CAD risk is reduced by 1-3% after adjustment for potential mediators (lipids, blood pressure, glycaemic traits, body mass index, socio-economic status). In contrast, our data suggest that lung function (measured by forced expiratory volume [FEV1] and forced vital capacity [FVC]) is a mediator of the effect of height on CAD. We observe no direct causal effect of height on the risk of T2D.


Assuntos
Estatura/genética , Doença da Artéria Coronariana/epidemiologia , Doença da Artéria Coronariana/genética , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/genética , Pulmão/fisiologia , Análise da Randomização Mendeliana/métodos , Adulto , Idoso , Índice de Massa Corporal , Estudos de Coortes , Feminino , Volume Expiratório Forçado , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único/genética , Fatores de Risco , Reino Unido/epidemiologia , Capacidade Vital
17.
Nat Genet ; 51(4): 683-693, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30858613

RESUMO

Widespread linkage disequilibrium and incomplete annotation of cell-to-cell state variation represent substantial challenges to elucidating mechanisms of trait-associated genetic variation. Here we perform genetic fine-mapping for blood cell traits in the UK Biobank to identify putative causal variants. These variants are enriched in genes encoding proteins in trait-relevant biological pathways and in accessible chromatin of hematopoietic progenitors. For regulatory variants, we explore patterns of developmental enhancer activity, predict molecular mechanisms, and identify likely target genes. In several instances, we localize multiple independent variants to the same regulatory element or gene. We further observe that variants with pleiotropic effects preferentially act in common progenitor populations to direct the production of distinct lineages. Finally, we leverage fine-mapped variants in conjunction with continuous epigenomic annotations to identify trait-cell type enrichments within closely related populations and in single cells. Our study provides a comprehensive framework for single-variant and single-cell analyses of genetic associations.


Assuntos
Hematopoese/genética , Polimorfismo de Nucleotídeo Único/genética , Linhagem da Célula/genética , Cromatina/genética , Mapeamento Cromossômico/métodos , Epigenômica/métodos , Estudo de Associação Genômica Ampla/métodos , Humanos , Desequilíbrio de Ligação/genética , Fenótipo , Locos de Características Quantitativas/genética , Sequências Reguladoras de Ácido Nucleico/genética
18.
J Clin Endocrinol Metab ; 104(7): 2961-2970, 2019 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-30811542

RESUMO

CONTEXT: Mutations in melanocortin receptor (MC4R) are the most common cause of monogenic obesity in children of European ancestry, but little is known about their prevalence in children from the minority populations in the United States. OBJECTIVE: This study aims to identify the prevalence of MC4R mutations in children with severe early-onset obesity of African American or Latino ancestry. DESIGN AND SETTING: Participants were recruited from the weight management clinics at two hospitals and from the institutional biobank at a third hospital. Sequencing of the MC4R gene was performed by whole exome or Sanger sequencing. Functional testing was performed to establish the surface expression of the receptor and cAMP response to its cognate ligand α-melanocyte-stimulating hormone. PARTICIPANTS: Three hundred twelve children (1 to 18 years old, 50% girls) with body mass index (BMI) >120% of 95th percentile of Centers for Disease Control and Prevention 2000 growth charts at an age <6 years, with no known pathological cause of obesity, were enrolled. RESULTS: Eight rare MC4R mutations (2.6%) were identified in this study [R7S, F202L (n = 2), M215I, G252D, V253I, I269N, and F284I], three of which were not previously reported (G252D, F284I, and R7S). The pathogenicity of selected variants was confirmed by prior literature reports or functional testing. There was no significant difference in the BMI or height trajectories of children with or without MC4R mutations in this cohort. CONCLUSIONS: Although the prevalence of MC4R mutations in this cohort was similar to that reported for obese children of European ancestry, some of the variants were novel.


Assuntos
Afro-Americanos/genética , Hispano-Americanos/genética , Obesidade Pediátrica/genética , Receptor Tipo 4 de Melanocortina/genética , Adolescente , Idade de Início , Criança , Pré-Escolar , Feminino , Humanos , Lactente , Masculino , Mutação , Receptor Tipo 4 de Melanocortina/metabolismo , Índice de Gravidade de Doença
19.
PLoS Comput Biol ; 15(1): e1006734, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-30640898

RESUMO

Metabolomics is a powerful approach for discovering biomarkers and for characterizing the biochemical consequences of genetic variation. While untargeted metabolite profiling can measure thousands of signals in a single experiment, many biologically meaningful signals cannot be readily identified as known metabolites nor compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To overcome these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets and to generate metabolic pathway annotations for these signals. To pair up signals measured in different datasets, where retention times (RT) are often not comparable or even available, we implemented an imputation-based approach that only requires mass-to-charge ratios (m/z). As validation, we treated each shared known metabolite as an unmatched signal and showed that PAIRUP-MS correctly matched 70-88% of these metabolites from among thousands of signals, equaling or outperforming a standard m/z- and RT-based approach. We performed further validation using genetic data: the most stringent set of matched signals and shared knowns showed comparable consistency of genetic associations across datasets. Next, we developed a pathway reconstitution method to annotate unknown signals using curated metabolic pathways containing known metabolites. We performed genetic validation for the generated annotations, showing that annotated signals associated with gene variants were more likely to be enriched for pathways functionally related to the genes compared to random expectation. Finally, we applied PAIRUP-MS to study associations between metabolites and genetic variants or body mass index (BMI) across multiple datasets, identifying up to ~6 times more significant signals and many more BMI-associated pathways compared to the standard practice of only analyzing known metabolites. These results demonstrate that PAIRUP-MS enables analysis of unknown signals in a robust, biologically meaningful manner and provides a path to more comprehensive, well-powered studies of untargeted metabolomics data.


Assuntos
Biologia Computacional/métodos , Espectrometria de Massas/métodos , Metaboloma , Metabolômica/métodos , Idoso , Idoso de 80 Anos ou mais , Biomarcadores/análise , Biomarcadores/metabolismo , Bases de Dados Factuais , Humanos , Redes e Vias Metabólicas/fisiologia , Metaboloma/genética , Metaboloma/fisiologia
20.
Hum Mol Genet ; 28(1): 166-174, 2019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30239722

RESUMO

More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.


Assuntos
Adiposidade/genética , Distribuição da Gordura Corporal/métodos , Obesidade/genética , Tecido Adiposo/fisiologia , Adulto , Alelos , Índice de Massa Corporal , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Frequência do Gene/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Humanos , Masculino , Polimorfismo de Nucleotídeo Único/genética , Relação Cintura-Quadril
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