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1.
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).

2.
J Natl Cancer Inst ; 2019 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-31168595

RESUMO

BACKGROUND: Coffee has been consistently associated with lower risk of liver cancer and chronic liver disease, suggesting that coffee affects mechanisms underlying disease development. METHODS: We measured serum metabolites using untargeted metabolomics in 1:1 matched nested case-control studies of liver cancer (n = 221 cases) and fatal liver disease (n = 242 cases) in the ATBC cohort (N = 29,133). Associations between baseline coffee drinking and metabolites were identified using linear regression; conditional logistic regression models were used to identify associations with subsequent outcomes. RESULTS: Overall, 21 metabolites were associated with coffee drinking and also each subsequent endpoint; nine metabolites and trigonelline, a known coffee biomarker, were identified. Tyrosine and two bile acids, glycochenodeoxycholic acid (GCDCA) and glycocholic acid (GCA), were inversely associated with coffee but positively associated with both outcomes; odds ratios (ORs) comparing the 90th to 10th percentile (modeled on a continuous basis) ranged from 3.93 (95% CI = 2.00-7.74) for tyrosine to 4.95 (95% CI = 2.64-9.29) for GCA and from 4.00 (95% CI = 2.42-6.62) for GCA to 6.77 (95% CI = 3.62-12.65) for GCDCA for liver cancer and fatal liver disease, respectively. The remaining six metabolites and trigonelline were positively associated with coffee drinking but inversely associated with both outcomes; ORs ranged from 0.16 to 0.37. Associations persisted following diet-adjustment and for outcomes occurring >10 years after blood collection. CONCLUSIONS: A broad range of compounds were associated with coffee drinking, incident liver cancer and liver disease death over 27 years of follow-up. These associations provide novel insight into chronic liver disease and liver cancer etiology and support a possible hepatoprotective effect of coffee.

3.
Biometrics ; 75(3): 745-756, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-30859548

RESUMO

We propose a model for high dimensional mediation analysis that includes latent variables. We describe our model in the context of an epidemiologic study for incident breast cancer with one exposure and a large number of biomarkers (i.e., potential mediators). We assume that the exposure directly influences a group of latent, or unmeasured, factors which are associated with both the outcome and a subset of the biomarkers. The biomarkers associated with the latent factors linking the exposure to the outcome are considered "mediators." We derive the likelihood for this model and develop an expectation-maximization algorithm to maximize an L1-penalized version of this likelihood to limit the number of factors and associated biomarkers. We show that the resulting estimates are consistent and that the estimates of the nonzero parameters have an asymptotically normal distribution. In simulations, procedures based on this new model can have significantly higher power for detecting the mediating biomarkers compared with the simpler approaches. We apply our method to a study that evaluates the relationship between body mass index, 481 metabolic measurements, and estrogen-receptor positive breast cancer.

4.
Genet Epidemiol ; 43(5): 492-505, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30920058

RESUMO

Meta-analysis of multiple genome-wide association studies (GWAS) is effective for detecting single- or multimarker associations with complex traits. We develop a flexible procedure (subset testing and analysis of multiple phenotypes [STAMP]) based on mixture models to perform a region-based meta-analysis of different phenotypes using data from different GWAS and identify subsets of associated phenotypes. Our model framework helps distinguish true associations from between-study heterogeneity. As a measure of association, we compute for each phenotype the posterior probability that the genetic region under investigation is truly associated. Extensive simulations show that STAMP is more powerful than standard approaches for meta-analyses when the proportion of truly associated outcomes is between 25% and 50%. For other settings, the power of STAMP is similar to that of existing methods. We illustrate our method on two examples, the association of a region on chromosome 9p21 with the risk of 14 cancers, and the associations of expression of quantitative trait loci from two genetic regions with their cis-single-nucleotide polymorphisms measured in 17 tissue types using data from The Cancer Genome Atlas.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Estudos de Casos e Controles , Simulação por Computador , Humanos , Modelos Genéticos , Neoplasias/patologia , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas/genética
5.
Metabolomics ; 15(4): 48, 2019 Mar 16.
Artigo em Inglês | MEDLINE | ID: mdl-30879189

RESUMO

INTRODUCTION: Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile. OBJECTIVES: To assess the association between sleep and blood metabolites. METHODS: We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways. RESULTS: Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association). CONCLUSION: Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.

6.
Int J Cancer ; 145(12): 3231-3243, 2019 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-30779128

RESUMO

Impaired metabolism may play an important role in the pathogenesis of lethal prostate cancer, yet there is a paucity of evidence regarding the association. We conducted a large prospective serum metabolomic analysis of lethal prostate cancer in 523 cases and 523 matched controls nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Median time from baseline fasting serum collection to prostate cancer death was 18 years (maximum 30 years). We identified 860 known biochemicals through an ultrahigh-performance LC-MS/MS platform. Conditional logistic regression models estimated odds ratios (OR) and 95% confidence intervals of risk associated with 1-standard deviation (s.d.) increases in log-metabolite signals. We identified 34 metabolites associated with lethal prostate cancer with a false discovery rate (FDR) < 0.15. Notably, higher serum thioproline, and thioproline combined with two other cysteine-related amino acids and redox metabolites, cystine and cysteine, were associated with reduced risk (1-s.d. OR = 0.75 and 0.71, respectively; p ≤ 8.2 × 10-5 ). By contrast, the dipeptide leucylglycine (OR = 1.36, p = 8.2 × 10-5 ), and three gamma-glutamyl amino acids (OR = 1.28-1.30, p ≤ 4.6 × 10-4 ) were associated with increased risk of lethal prostate cancer. Cases with metastatic disease at diagnosis (n = 179) showed elevated risk for several lipids, including especially the ketone body 3-hydroxybutyrate (BHBA), acyl carnitines, and dicarboxylic fatty acids (1.37 ≤ OR ≤ 1.49, FDR < 0.15). These findings provide a prospective metabolomic profile of lethal prostate cancer characterized by altered biochemicals in the redox, dipeptide, pyrimidine, and gamma-glutamyl amino acid pathways, whereas ketone bodies and fatty acids were associated specifically with metastatic disease.

7.
EBioMedicine ; 39: 358-368, 2019 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-30579868

RESUMO

BACKGROUND: Endemic Burkitt lymphoma (eBL) is an aggressive childhood B-cell lymphoma linked to Plasmodium falciparum (Pf) malaria in sub-Saharan Africa. We investigated antibody reactivity to several human receptor-binding domains of the Pf erythrocyte membrane protein 1 (PfEMP1) that play a key role in malaria pathogenesis and are targets of acquired immunity to malaria. METHODS: Serum/plasma IgG antibody reactivity was measured to 22 Pf antigens, including 18 to PfEMP1 CIDR domains between cases and controls from two populations (149 eBL cases and 150 controls from Ghana and 194 eBL cases and 600 controls from Uganda). Adjusted odds ratios (aORs) for case-control associations were estimated by logistic regression. FINDINGS: There was stronger reactivity to the severe malaria associated CIDRα1 domains than other CIDR domains both in cases and controls. eBL cases reacted to fewer antigens than controls (Ghana: p = 0·001; Uganda: p = 0·03), with statistically significant lower ORs associated with reactivity to 13+ antigens in Ghana (aOR 0·39, 95% CI 0·24-0·63; pheterogeneity = 0·00011) and Uganda (aOR 0·60, 95% CI 0.41-0·88; pheterogeneity = 0·008). eBL was inversely associated with reactivity, coded as quartiles, to group A variant CIDRδ1 (ptrend = 0·035) in Ghana and group B CD36-binding variants CIDRα2·2 (ptrend = 0·006) and CIDRα2·4 (ptrend = 0·033) in Uganda, and positively associated with reactivity to SERA5 in Ghana (ptrend = 0·017) and Uganda (ptrend = 0·007) and group A CIDRα1·5 variant in Uganda only (ptrend = 0·034). INTERPRETATION: eBL cases reacted to fewer antigens than controls using samples from two populations, Ghana and Uganda. Attenuated humoral immunity to Pf EMP1 may contribute to susceptibility to low-grade malaria and eBL risk. FUNDING: Intramural Research Program, National Cancer Institute and National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services.


Assuntos
Linfoma de Burkitt/parasitologia , Imunoglobulina G/metabolismo , Malária Falciparum/imunologia , Plasmodium falciparum/metabolismo , Proteínas de Protozoários/imunologia , Adolescente , Anticorpos Antiprotozoários/metabolismo , Sítios de Ligação , Linfoma de Burkitt/imunologia , Estudos de Casos e Controles , Criança , Pré-Escolar , Feminino , Gana , Humanos , Lactente , Recém-Nascido , Modelos Logísticos , Masculino , Razão de Chances , Plasmodium falciparum/imunologia , Proteínas de Protozoários/química , Uganda
8.
Artigo em Inglês | MEDLINE | ID: mdl-29878065

RESUMO

Impaired metabolism may play a role in the development and lethality of prostate cancer, yet a comprehensive analysis of the interrelationships appears lacking. We measured 625 metabolites using ultrahigh performance LC/MS-GC/MS of prediagnostic serum from 197 prostate cancer cases in the ATBC Study (ages at diagnosis, 55-86 years). Cox proportional hazards models estimated associations between circulating metabolites and prostate cancer mortality for 1-standard deviation (SD) differences (log-metabolite scale), adjusted for age, year of diagnosis, and disease stage. Associations between metabolite chemical classes and survival were examined through pathway analysis, and Cox models assessed the relationship with a sterol/steroid metabolite principal component analysis factor score. Elevated serum N-oleoyl taurine was significantly associated with prostate cancer-specific mortality (HR=1.72 per 1-SD, p<0.00008, Bonferroni corrected threshold=0.05/625; HR=3.6 for highest vs lowest tertile, p<0.001). Pathway analyses revealed a statistically significant association between lipids and prostate cancer death (p<0.006, Bonferroni-corrected threshold=0.05/8), and sterol/steroid metabolites showed the strongest chemical sub-class association (p=0.0014, Bonferroni-corrected threshold=0.05/45). In the principal component analysis, a 1-SD increment in the sterol/steroid metabolite score increased the risk of prostate cancer death by 46%. Prediagnostic serum N-oleoyl taurine and sterol/steroid metabolites were associated with prostate cancer survival.

9.
Biol Psychiatry ; 83(9): 780-789, 2018 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-29628042

RESUMO

BACKGROUND: The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. METHODS: We conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects. RESULTS: In the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes. CONCLUSIONS: This study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample.

10.
Am J Epidemiol ; 2018 Jan 30.
Artigo em Inglês | MEDLINE | ID: mdl-29390044

RESUMO

Tobacco use, hypertension, hyperglycemia, overweight, and inactivity are leading causes of overall and cardiovascular disease (CVD) mortality worldwide, yet the relevant metabolic alterations responsible are largely unknown. We conducted a serum metabolomic analysis of 620 men in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (1985-2013). During 28 years of follow-up, there were 435 deaths (197 CVD and 107 cancer). The analysis included 406 known metabolites measured with ultra-high performance liquid chromatography/mass spectrometry-gas chromatography/mass spectrometry. Cox regression estimated mortality hazard ratios (HR) for a one standard-deviation difference in metabolite-signals, and we divided the data into training and test-sets, creating a metabolite risk score of the strongest metabolites in the former to test in the latter. The strongest associations with overall mortality were N-acetylvaline (HR=1.28; P<4.1×10-5, below Bonferroni statistical threshold), and dimethylglycine, 7-methylguanine, C-glycosyltryptophan, taurocholate, and N-acetyltryptophan (1.23≤HR≤1.32; 5×10-5≤P≤1×10-4). C-Glycosyltryptophan, 7-methylguanine, and 4-androsten-3beta,17beta-diol disulfate were statistically significantly associated with CVD mortality (1.49≤HR≤1.62, P<4.1×10-5). No metabolite was associated with cancer mortality at false discovery rate<0.1. Individuals with a one standard-deviation higher metabolite risk score had increased all-cause and CVD mortality in the test-set (HR=1.4, P=0.05; HR=1.8, P=0.003, respectively). The several serum metabolites and their composite risk score independently associated with all-cause and CVD mortality may provide potential leads regarding the molecular basis of mortality.

11.
Bioinformatics ; 34(9): 1506-1513, 2018 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-29194474

RESUMO

Motivation: Genome-wide association studies are now shifting focus from analysis of common to rare variants. As power for association testing for individual rare variants may often be low, various aggregate level association tests have been proposed to detect genetic loci. Typically, power calculations for such tests require specification of large number of parameters, including effect sizes and allele frequencies of individual variants, making them difficult to use in practice. We propose to approximate power to a varying degree of accuracy using a smaller number of key parameters, including the total genetic variance explained by multiple variants within a locus. Results: We perform extensive simulation studies to assess the accuracy of the proposed approximations in realistic settings. Using these simplified power calculations, we develop an analytic framework to obtain bounds on genetic architecture of an underlying trait given results from genome-wide association studies with rare variants. Finally, we provide insights into the required quality of annotation/functional information for identification of likely causal variants to make meaningful improvement in power. Availability and implementation: A shiny application that allows a variety of Power Analysis of GEnetic AssociatioN Tests (PAGEANT), in R is made publicly available at https://andrewhaoyu.shinyapps.io/PAGEANT/. Contact: nilanjan@jhu.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

12.
Am J Clin Nutr ; 106(4): 1131-1141, 2017 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-28855223

RESUMO

Background: High sodium intake is known to increase blood pressure and is difficult to measure in epidemiologic studies.Objective: We examined the effect of sodium intake on metabolites within the DASH (Dietary Approaches to Stop Hypertension Trial)-Sodium Trial to further our understanding of the biological effects of sodium intake beyond blood pressure.Design: The DASH-Sodium Trial randomly assigned individuals to either the DASH diet (low in fat and high in protein, low-fat dairy, and fruits and vegetables) or a control diet for 12 wk. Participants within each diet arm received, in random order, diets containing high (150 nmol or 3450 mg), medium (100 nmol or 2300 mg), and low (50 nmol or 1150 mg) amounts of sodium for 30 d (crossover design). Fasting blood samples were collected at the end of each sodium intervention. We measured 531 identified plasma metabolites in 73 participants at the end of their high- and low-sodium interventions and in 46 participants at the end of their high- and medium-sodium interventions (N = 119). We used linear mixed-effects regression to model the relation between each log-transformed metabolite and sodium intake. We also combined the resulting P values with Fisher's method to estimate the association between sodium intake and 38 metabolic pathways or groups.Results: Six pathways were associated with sodium intake at a Bonferroni-corrected threshold of 0.0013 (e.g., fatty acid, food component or plant, benzoate, γ-glutamyl amino acid, methionine, and tryptophan). Although 82 metabolites were associated with sodium intake at a false discovery rate ≤0.10, only 4-ethylphenylsufate, a xenobiotic related to benzoate metabolism, was significant at a Bonferroni-corrected threshold (P < 10-5). Adjustment for coinciding change in blood pressure did not substantively alter the association for the top-ranked metabolites.Conclusion: Sodium intake is associated with changes in circulating metabolites, including gut microbial, tryptophan, plant component, and γ-glutamyl amino acid-related metabolites. This trial was registered at clinicaltrials.gov as NCT00000608.


Assuntos
Dieta , Comportamento Alimentar , Hipertensão/sangue , Metaboloma/efeitos dos fármacos , Cloreto de Sódio na Dieta/farmacologia , Sódio na Dieta/farmacologia , Adolescente , Adulto , Idoso , Aminoácidos/sangue , Pressão Sanguínea , Estudos Cross-Over , Dieta com Restrição de Carboidratos , Dieta com Restrição de Gorduras , Dieta Hipossódica , Feminino , Frutas , Microbioma Gastrointestinal , Humanos , Hipertensão/dietoterapia , Masculino , Redes e Vias Metabólicas/efeitos dos fármacos , Pessoa de Meia-Idade , Extratos Vegetais/sangue , Cloreto de Sódio na Dieta/administração & dosagem , Sódio na Dieta/administração & dosagem , Verduras , Adulto Jovem
13.
Sci Rep ; 7(1): 10601, 2017 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-28878287

RESUMO

The role of retinol in the prevention of multifactorial chronic diseases remains uncertain, and there is sparse evidence regarding biological actions and pathways implicated in its effects on various outcomes. The aim is to investigate whether serum retinol in an un-supplemented state is associated with low molecular weight circulating metabolites. We performed a metabolomic analysis of 1,282 male smoker participants based on pre-supplementation fasting serum in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. We examined the association between 947 metabolites measured by ultra-high performance LC-MS/GC-MS and retinol concentration (from HPLC) using linear regression that estimated the difference in metabolite concentrations per unit difference in retinol concentration as standardized ß-coefficients and standard errors (SE). We identified 63 metabolites associated with serum retinol below the Bonferroni-corrected P-value (p < 5.3 × 10-5). The strongest signals were for N-acetyltryptophan (ß = 0.27; SE = 0.032; p = 9.8 × 10-17), myo-inositol (ß = 0.23; SE = 0.032; p = 9.8 × 10-13), and 1-palmitoylglycerophosphoethanolamine (ß = 0.22; SE = 0.032; p = 3.2 × 10-12). Several chemical class pathways were strongly associated with retinol, including amino acids (p = 1.6 × 10-10), lipids (p = 3.3 × 10-7), and cofactor/vitamin metabolites (3.3 × 10-7). The strongest sub-pathway association was for inositol metabolism (p = 2.0 × 10-14). Serum retinol concentration is associated with circulating metabolites in various metabolic pathways, particularly lipids, amino acids, and cofactors/vitamins. These interrelationships may have relevance to the biological actions of retinol, including its role in carcinogenesis.

14.
Metabolomics ; 13(5)2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-29657561

RESUMO

Introduction: Sleep plays an important role in cardiometabolic health. The sleep-wake cycle is partially driven by the endogenous circadian clock, which governs a range of metabolic pathways. The association between sleep and cardiometabolic health may be mediated by alterations of the human metabolome. Objectives: To better understand the biological mechanism underlying the association between sleep and health, we examined human plasma metabolites in relation to sleep duration and sleep timing. Methods: Using an untargeted approach, 329 fasting plasma metabolites were measured in 277 Chinese participants. We measured sleep timing (midpoint between bedtime and wake up time) using repeated time-use surveys (4 weeks during one year) and previous night sleep duration from questionnaires completed before sample donation. Results: We found 64 metabolites that were associated with sleep timing with a false discovery rate of 0.2 or lower, after adjusting for potential confounders. Notably, we found that later sleep timing was associated with higher levels of multiple metabolites in amino acid metabolism, including branched chain amino acids and their gamma-glutamyl dipeptides. We also found widespread associations between sleep timing and numerous metabolites in lipid metabolism, including bile acids, carnitines and fatty acids. In contrast, previous night sleep duration was not associated with plasma metabolites in our study. Conclusion: Sleep timing was associated with a large number of metabolites across a variety of biochemical pathways. Some metabolite associations are consistent with a relationship between late chronotype and adverse effects on cardiometabolic health.

15.
Am J Clin Nutr ; 105(2): 450-465, 2017 02.
Artigo em Inglês | MEDLINE | ID: mdl-28031192

RESUMO

BACKGROUND: Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality. OBJECTIVE: The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites. DESIGN: We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985-1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses. RESULTS: The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: -0.30 to 0.20; P = 6 × 10-15 to 8 × 10-6). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro- or micronutrients (e.g., percentages of protein and cholesterol). The lysolipid and food and plant xenobiotic pathways were most strongly associated with diet quality. CONCLUSIONS: Diet quality, measured by healthy diet indexes, is associated with serum metabolites, with the specific metabolite profile of each diet index related to the diet components used to score adherence. This trial was registered at clinicaltrials.gov as NCT00342992.


Assuntos
Biomarcadores/sangue , Dieta , Metabolômica , Idoso , Animais , Estudos de Casos e Controles , Estudos Transversais , Dieta Mediterrânea , Fibras na Dieta/administração & dosagem , Grão Comestível , Ingestão de Energia , Exercício , Jejum , Ácidos Graxos Insaturados/administração & dosagem , Finlândia , Peixes , Frutas , Humanos , Micronutrientes/administração & dosagem , Pessoa de Meia-Idade , Ensaios Clínicos Controlados Aleatórios como Assunto , Alimentos Marinhos , Inquéritos e Questionários , Verduras , alfa-Tocoferol/sangue , beta Caroteno/sangue
16.
Br J Cancer ; 115(9): 1087-1095, 2016 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-27673363

RESUMO

BACKGROUND: Two recent metabolomic analyses found serum lipid, energy, and other metabolites related to aggressive prostate cancer risk up to 20 years prior to diagnosis. METHODS: We conducted a serum metabolomic investigation of prostate cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that included annual serum total prostate-specific antigen measurement and digital rectal examination. This nested study included 380 cases diagnosed post-screening and 380 controls individually matched to cases on age, race, study centre, and blood-collection date (median time to diagnosis, 10 years (range 4.4-17 years)). Sera were analysed on a high-resolution accurate mass platform of ultrahigh-performance liquid and gas chromatography/mass spectroscopy that identified 695 known metabolites. Logistic regression conditioned on the matching factors estimated odds ratios (OR) and 95% confidence intervals of risk associated with an 80th percentile increase in the log-metabolite signal. RESULTS: Twenty-seven metabolites were associated with prostate cancer at P<0.05. Pyroglutamine, gamma-glutamylphenylalanine, phenylpyruvate, N-acetylcitrulline, and stearoylcarnitine showed the strongest metabolite-risk signals (ORs=0.53, 0.51, 0.46, 0.58, and 1.74, respectively; 0.001⩽P⩽0.006). Findings were similar for aggressive disease (peptide chemical class, P=0.03). None of the P-values were below the threshold of Bonferroni correction, however. CONCLUSIONS: A unique metabolomic profile associated with post-screening prostate cancer is identified that differs from that in a previously studied, unscreened population.


Assuntos
Biomarcadores Tumorais/sangue , Neoplasias Colorretais/diagnóstico , Detecção Precoce de Câncer/métodos , Neoplasias Pulmonares/diagnóstico , Metabolômica/métodos , Neoplasias Ovarianas/diagnóstico , Neoplasias da Próstata/diagnóstico , Idoso , Análise Química do Sangue/métodos , Estudos de Casos e Controles , Neoplasias Colorretais/sangue , Neoplasias Colorretais/patologia , Progressão da Doença , Feminino , Cromatografia Gasosa-Espectrometria de Massas , Humanos , Neoplasias Pulmonares/sangue , Neoplasias Pulmonares/patologia , Masculino , Programas de Rastreamento/métodos , Metaboloma , Pessoa de Meia-Idade , Neoplasias Ovarianas/sangue , Neoplasias Ovarianas/patologia , Neoplasias da Próstata/sangue , Neoplasias da Próstata/patologia
17.
Int J Epidemiol ; 45(5): 1421-1432, 2016 10.
Artigo em Inglês | MEDLINE | ID: mdl-26721601

RESUMO

BACKGROUND: Identifying circulating metabolites related to cigarette smoking may provide insight into the biological mechanisms of smoking-related diseases and the nature of addiction. However, previous studies are limited, generally small, and have largely targeted a priori metabolites. METHODS: We examined associations between cigarette smoking and metabolites using an untargeted metabolomics approach in 892 men and women from four studies including participants from Italy, USA, China and Finland. We examined associations between individual log-transformed metabolites and two key smoking phenotypes (current smoking status and cigarettes per day [cig/day]) using linear regression. Fixed-effect meta-analysis was used to combine results across studies. Strict Bonferroni thresholds were used as our significance criteria. We further examined associated metabolites with other metrics of smoking behaviuor (current versus former, former versus never, smoking duration and years since quitting) in the US study. RESULTS: We identified a total of 25 metabolites associated with smoking behaviours; 24 were associated with current smoking status and eight with cig/day. In addition to three well-established nicotine metabolites (cotinine, hydroxycotinine, cotinine N-oxide), we found an additional 12 xenobiotic metabolites involved in benzoatic (e.g. 3-ethylphenylsulphate) or xanthine metabolism (e.g. 1-methylurate), three amino acids (o-cresol sulphate, serotonin, indolepropionate), two lipids (scyllo-inositol, pregnenolone sulphate), four vitamins or cofactors [e.g. bilirubin (Z,Z)], and one carbohydrate (oxalate). CONCLUSIONS: We identified associations between cigarette smoking and a diverse range of metabolites. Our findings, with further validation in future studies, have implications regarding aetiology and study design of smoking-related diseases.


Assuntos
Biomarcadores/sangue , Fumar Cigarros/sangue , Fumar Cigarros/metabolismo , Metabolômica/métodos , Nicotina/metabolismo , Adulto , Idoso , Bilirrubina/sangue , China , Cresóis/sangue , Feminino , Finlândia , Humanos , Itália , Modelos Lineares , Masculino , Metanálise como Assunto , Pessoa de Meia-Idade , Estados Unidos
18.
BMC Proc ; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo): S11, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25519362

RESUMO

Grouping variants based on gene mapping can augment the power of rare variant association tests. Weighting or sorting variants based on their expected functional impact can provide additional benefit. We defined groups of prioritized variants based on systematic annotation of Genetic Analysis Workshop 18 (GAW18) single-nucleotide variants; we focused on variants detected by whole genome sequencing, specifically on the high-quality subset presented in the genotype files. First, we divided variants between coding and noncoding. Coding variants are fewer than 1% of the total and are more likely to have a biological effect than noncoding variants. Coding variants were further stratified into protein changing and protein damaging groups based on the effect on protein amino acid sequence. In particular, missense variants predicted to be damaging, splice-site alterations, and stop gains were assigned to the protein damaging category. Impact of noncoding variants is more difficult to predict. We decided to rely uniquely on conservation: we combined (a) the mammalian phastCons Conserved Element and (b) the PhyloP score, which identify conserved intervals and the single-nucleotide position, respectively. This reduced the noncoding variants to a number comparable to coding variants. Finally, using gene structure definition from the widely used RefSeq database, we mapped variants to genes to support association tests that require collapsing rare variants to genes. Companion GAW18 papers used these variant priority groups and gene mapping; one of these paper specifically found evidence of stronger association signal for protein damaging variants.

19.
BMC Proc ; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo): S77, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25519405

RESUMO

Pleiotropy, which occurs when a single genetic factor influences multiple phenotypes, is present in many genetic studies of complex human traits. Longitudinal family data, such as the Genetic Analysis Workshop 18 data, combine the features of longitudinal studies in individuals and cross-sectional studies in families, thus providing richer information about the genetic and environmental factors associated with the trait of interest. We recently proposed a Bayesian latent variable methodology for the study of pleiotropy, in the presence of longitudinal and family correlation. The purpose of this work is to evaluate the Bayesian latent variable method in a real data setting using the Genetic Analysis Workshop 18 blood pressure phenotypes and sequenced genotype data. To detect single-nucleotide polymorphisms with pleiotropic effect on both diastolic and systolic blood pressure, we focused on a set of 6 single-nucleotide polymorphisms from chromosome 3 that was reported in the literature to be significantly associated with either diastolic blood pressure or the binary hypertension trait. Our analysis suggests that both diastolic blood pressure and systolic blood pressure are associated with the latent hypertension severity variable, but the analysis did not find any of the 6 single-nucleotide polymorphisms to have statistically significant pleiotropic effect on both diastolic blood pressure and systolic blood pressure.

20.
BMC Proc ; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo): S9, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25519417

RESUMO

The focus of our work is to evaluate several recently developed pooled association tests for rare variants and assess the impact of different gene annotation methods and binning strategies on the analyses of rare variants under Genetic Analysis Workshop 18 real and simulated data settings. We considered the sample of 103 unrelated individuals with sequence data, genotypes of rare variants from chromosome 3, real phenotype of hypertension status and simulated phenotypes of systolic blood pressure (SBP) and diastolic blood pressure (DBP), and covariates of age, sex, and the interaction between age and sex. In the analysis of real phenotype data, we did not obtain significant results for any binning strategy; however, we observed a slight deviation of the p-values from the uniform distribution based on the protein-damaging variant grouping strategy. Evaluation of methods using simulated data showed lack of power even at the conservative level of 0.05 for most of the causal genes on chromosome 3. Nevertheless, analysis of MAP4 produced good power for all tests at various levels of the tests for both DBP and SBP. Our results also confirmed that Fisher's method is not only robust but can also improve power over individual pooled linear and quadratic tests and is often better than other robust tests such as SKAT-O.

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