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1.
Genet Med ; 2019 Sep 04.
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.

2.
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.

3.
Am J Epidemiol ; 188(6): 991-1012, 2019 Jun 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).

4.
Am J Hum Genet ; 104(6): 1025-1039, 2019 Jun 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.

5.
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
6.
J Clin Endocrinol Metab ; 104(7): 2961-2970, 2019 Jul 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.

7.
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
8.
Am J Hum Genet ; 103(4): 522-534, 2018 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-30269813

RESUMO

The genetic causes of many Mendelian disorders remain undefined. Factors such as lack of large multiplex families, locus heterogeneity, and incomplete penetrance hamper these efforts for many disorders. Previous work suggests that gene-based burden testing-where the aggregate burden of rare, protein-altering variants in each gene is compared between case and control subjects-might overcome some of these limitations. The increasing availability of large-scale public sequencing databases such as Genome Aggregation Database (gnomAD) can enable burden testing using these databases as controls, obviating the need for additional control sequencing for each study. However, there exist various challenges with using public databases as controls, including lack of individual-level data, differences in ancestry, and differences in sequencing platforms and data processing. To illustrate the approach of using public data as controls, we analyzed whole-exome sequencing data from 393 individuals with idiopathic hypogonadotropic hypogonadism (IHH), a rare disorder with significant locus heterogeneity and incomplete penetrance against control subjects from gnomAD (n = 123,136). We leveraged presumably benign synonymous variants to calibrate our approach. Through iterative analyses, we systematically addressed and overcame various sources of artifact that can arise when using public control data. In particular, we introduce an approach for highly adaptable variant quality filtering that leads to well-calibrated results. Our approach "re-discovered" genes previously implicated in IHH (FGFR1, TACR3, GNRHR). Furthermore, we identified a significant burden in TYRO3, a gene implicated in hypogonadotropic hypogonadism in mice. Finally, we developed a user-friendly software package TRAPD (Test Rare vAriants with Public Data) for performing gene-based burden testing against public databases.

9.
Hum Mol Genet ; 2018 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-30239722

RESUMO

One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (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.

10.
J Clin Endocrinol Metab ; 103(9): 3155-3168, 2018 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-29982553

RESUMO

Context: In the last decade, genome-wide association studies (GWASs) have catalyzed our understanding of the genetics of height and have identified hundreds of regions of the genome associated with adult height and other height-related body measurements. Evidence Acquisition: GWASs related to height were identified via PubMed search and a review of the GWAS catalog. Evidence Synthesis: The GWAS results demonstrate that height is highly polygenic: that is, many thousands of genetic variants distributed across the genome each contribute to an individual's height. These height-associated regions of the genome are enriched for genes in known biological pathways involved in growth, such as fibroblast growth factor signaling, as well as for genes expressed in relevant tissues, such as the growth plate. GWASs can also uncover previously unappreciated biological pathways, such as the STC2/PAPPA/IGFBP4 pathway. The genes implicated by GWASs are often the same genes that are the genetic causes of Mendelian growth disorders or skeletal dysplasias, and GWAS results can provide complementary information about these disorders. Conclusions: Here, we review the rationale behind GWASs and what we have learned from GWASs for height, including how it has enhanced our understanding of the underlying biology of human growth. We also highlight the implications of GWASs in terms of prediction of adult height and our understanding of Mendelian growth disorders.

11.
Artigo em Inglês | MEDLINE | ID: mdl-30016152

RESUMO

Newborns with intrauterine growth-restriction are at increased risk of mortality and life-long co-morbidities. Insulin-like growth factor-II (IGF2) deficiency in humans as well as in mice leads to intrauterine growth restriction and decreased neonatal glycogen stores. The present study aims to further characterize the metabolic and transcriptional consequences of Igf2 deficiency in the newborn. We found that, despite being born significantly smaller than their wild-type (Igf2+/+) littermates, brain size was preserved in Igf2 knockout (Igf2-/-), consistent with nutritional deficiency. Histological and triglyceride analyses of newborn livers revealed that Igf2-/- mice are born with hepatic steatosis. Gene expression analysis in Igf2-/- newborn livers, showed an alteration of genes known to be dysregulated in chronic caloric restriction, including the most up-regulated gene - serine dehydratase. Multiple genes connected with lipid metabolism and/or hepatic steatosis were also up-regulated. Ingenuity Pathway Analysis confirmed that the biological functions most altered in livers of Igf2-/- newborns are related to lipid metabolism, with the top upstream regulator predicted to be the perixosome proliferator-activated receptor alpha, a master regulator of hepatic lipid and carbohydrate homeostasis. Together, our data indicate that Igf2 deficiency leads to a newborn phenotype strongly reminiscent of nutritional deficiency, including growth retardation, increased brain/body weight ratio, hepatic steatosis, and characteristic changes in hepatic gene expression. We propose that in addition to its growth factor proliferating functions, Igf2 may also regulate growth by altering the expression of genes that control nutrient metabolism in the newborn.

12.
Genet Med ; 2018 Apr 12.
Artigo em Inglês | MEDLINE | ID: mdl-29789557

RESUMO

PurposeTo evaluate the coverage and accuracy of whole-exome sequencing (WES) across vendors.MethodsBlood samples from three trios underwent WES at three vendors. Relative performance of the three WES services was measured for breadth and depth of coverage. The false-negative rates (FNRs) were estimated using the segregation pattern within each trio.ResultsMean depth of coverage for all genes was 189.0, 124.9, and 38.3 for the three vendor services. Fifty-five of the American College of Medical Genetics and Genomics 56 genes, but only 56 of 63 pharmacogenes, were 100% covered at 10 × in at least one of the nine individuals for all vendors; however, there was substantial interindividual variability. For the two vendors with mean depth of coverage >120 ×, analytic positive predictive values (aPPVs) exceeded 99.1% for single-nucleotide variants and homozygous indels, and sensitivities were 98.9-99.9%; however, heterozygous indels showed lower accuracy and sensitivity. Among the trios, FNRs in the offspring were 0.07-0.62% at well-covered variants concordantly called in both parents.ConclusionThe current standard of 120 × coverage for clinical WES may be insufficient for consistent breadth of coverage across the exome. Ordering clinicians and researchers would benefit from vendors' reports that estimate sensitivity and aPPV, including depth of coverage across the exome.Genetics in Medicine advance online publication, 12 April 2018; doi:10.1038/gim.2018.51.

13.
Cell Stem Cell ; 22(4): 575-588.e7, 2018 Apr 05.
Artigo em Inglês | MEDLINE | ID: mdl-29625070

RESUMO

While gene expression dynamics have been extensively cataloged during hematopoietic differentiation in the adult, less is known about transcriptome diversity of human hematopoietic stem cells (HSCs) during development. To characterize transcriptional and post-transcriptional changes in HSCs during development, we leveraged high-throughput genomic approaches to profile miRNAs, lincRNAs, and mRNAs. Our findings indicate that HSCs manifest distinct alternative splicing patterns in key hematopoietic regulators. Detailed analysis of the splicing dynamics and function of one such regulator, HMGA2, identified an alternative isoform that escapes miRNA-mediated targeting. We further identified the splicing kinase CLK3 that, by regulating HMGA2 splicing, preserves HMGA2 function in the setting of an increase in let-7 miRNA levels, delineating how CLK3 and HMGA2 form a functional axis that influences HSC properties during development. Collectively, our study highlights molecular mechanisms by which alternative splicing and miRNA-mediated post-transcriptional regulation impact the molecular identity and stage-specific developmental features of human HSCs.

14.
Am J Respir Crit Care Med ; 197(9): 1128-1135, 2018 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-29313715

RESUMO

RATIONALE: The effects of fluid administration during acute asthma exacerbation are likely unique in this patient population: highly negative inspiratory intrapleural pressure resulting from increased airway resistance may interact with excess fluid administration to favor the accumulation of extravascular lung water, leading to worse clinical outcomes. OBJECTIVES: Investigate how fluid balance influences clinical outcomes in children hospitalized for asthma exacerbation. METHODS: We analyzed the association between fluid overload and clinical outcomes in a retrospective cohort of children admitted to an urban children's hospital with acute asthma exacerbation. These findings were validated in two cohorts: a matched retrospective and a prospective observational cohort. Finally, ultrasound imaging was used to identify extravascular lung water and investigate the physiological basis for the inferential findings. MEASUREMENTS AND MAIN RESULTS: In the retrospective cohort, peak fluid overload [(fluid input - output)/weight] is associated with longer hospital length of stay, longer treatment duration, and increased risk of supplemental oxygen use (P values < 0.001). Similar results were obtained in the validation cohorts. There was a strong interaction between fluid balance and intrapleural pressure: the combination of positive fluid balance and highly negative inspiratory intrapleural pressures is associated with signs of increased extravascular lung water (P < 0.001), longer length of stay (P = 0.01), longer treatment duration (P = 0.03), and increased risk of supplemental oxygen use (P = 0.02). CONCLUSIONS: Excess volume administration leading to fluid overload in children with acute asthma exacerbation is associated with increased extravascular lung water and worse clinical outcomes.

15.
Clin Chem ; 64(1): 192-200, 2018 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-29295838

RESUMO

BACKGROUND: A fundamental precept of the carbohydrate-insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS: Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS: Higher genetically determined insulin-30 was strongly associated with higher BMI (ß = 0.098, P = 2.2 × 10-21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS: Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate-insulin model of obesity.

17.
J Allergy Clin Immunol ; 139(5): 1717-1718, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28274584
18.
Annu Rev Genomics Hum Genet ; 18: 31-44, 2017 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-28142260

RESUMO

In this interview, Kurt and Rochelle Hirschhorn talk with their son, Joel, about their research and collaborations, the early years of medical genetics, the development of genetic counseling, the challenges of being a woman in science, and new challenges and directions for the study of human genetics.


Assuntos
Genética Médica/história , Adenosina Desaminase/deficiência , Doença de Depósito de Glicogênio Tipo II , História do Século XX , História do Século XXI , Humanos , Doenças por Armazenamento dos Lisossomos , Estados Unidos , Síndrome de Wolf-Hirschhorn
19.
J Allergy Clin Immunol ; 140(3): 771-781, 2017 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-28188724

RESUMO

BACKGROUND: The relationship between allergy and autoimmune disorders is complex and poorly understood. OBJECTIVE: We sought to investigate commonalities in genetic loci and pathways between allergy and autoimmune diseases to elucidate shared disease mechanisms. METHODS: We meta-analyzed 2 genome-wide association studies on self-reported allergy and sensitization comprising a total of 62,330 subjects. These results were used to calculate enrichment for single nucleotide polymorphisms (SNPs) previously associated with autoimmune diseases. Furthermore, we probed for enrichment within genetic pathways and of transcription factor binding sites and characterized commonalities in variant burden on tissue-specific regulatory sites by calculating the enrichment of allergy SNPs falling in gene regulatory regions in various cells using Encode Roadmap DNase-hypersensitive site data. Finally, we compared the allergy data with those of all known diseases. RESULTS: Among 290 loci previously associated with 16 autoimmune diseases, we found a significant enrichment of loci also associated with allergy (P = 1.4e-17) encompassing 29 loci at a false discovery rate of less than 0.05. Such enrichment seemed to be a general characteristic for autoimmune diseases. Among the common loci, 48% had the same direction of effect for allergy and autoimmune diseases. Additionally, we observed an enrichment of allergy SNPs falling within immune pathways and regions of chromatin accessible in immune cells that was also represented in patients with autoimmune diseases but not those with other diseases. CONCLUSION: We identified shared susceptibility loci and commonalities in pathways between allergy and autoimmune diseases, suggesting shared disease mechanisms. Further studies of these shared genetic mechanisms might help in understanding the complex relationship between these diseases, including the parallel increase in disease prevalence.


Assuntos
Doenças Autoimunes/genética , Hipersensibilidade/genética , Estudo de Associação Genômica Ampla , Humanos , Polimorfismo de Nucleotídeo Único
20.
Am J Clin Nutr ; 105(3): 547-554, 2017 03.
Artigo em Inglês | MEDLINE | ID: mdl-28077380

RESUMO

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.


Assuntos
Dieta , Comportamento Alimentar , Metaboloma , Avaliação Nutricional , Estado Nutricional , Obesidade/metabolismo , Adolescente , Adulto , Aminoácidos/metabolismo , Biomarcadores/metabolismo , Índice de Massa Corporal , Peso Corporal , Manutenção do Peso Corporal , Estudos Cross-Over , Dieta com Restrição de Carboidratos , Dieta com Restrição de Gorduras , Dieta Redutora , Ingestão de Energia , Índice Glicêmico , Glicerídeos/metabolismo , Humanos , Metabolômica/métodos , Obesidade/dietoterapia , Cooperação do Paciente , Perda de Peso , Adulto Jovem
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