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1.
Aging (Albany NY) ; 11(18): 7694-7706, 2019 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-31557729

RESUMO

Glucuronic acid is a metabolite of glucose that is involved in the detoxification of xenobiotic compounds and the structure/remodeling of the extracellular matrix. We report for the first time that circulating glucuronic acid is a robust biomarker of mortality that is conserved across species. We find that glucuronic acid levels are significant predictors of all-cause mortality in three population-based cohorts from different countries with 4-20 years of follow-up (HR=1.44, p=2.9×10-6 in the discovery cohort; HR=1.13, p=0.032 and HR=1.25, p=0.017, respectively in the replication cohorts), as well as in a longitudinal study of genetically heterogenous mice (HR=1.29, p=0.018). Additionally, we find that glucuronic acid levels increase with age and predict future healthspan-related outcomes. Together, these results demonstrate glucuronic acid as a robust biomarker of longevity and healthspan.

2.
Nat Commun ; 10(1): 3346, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31431621

RESUMO

Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18-109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.

3.
Sci Rep ; 9(1): 11623, 2019 Aug 12.
Artigo em Inglês | MEDLINE | ID: mdl-31406173

RESUMO

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10-6), methionine (p-value = 9.2 × 10-5), tyrosine (p-value = 2.1 × 10-4), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10-4), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10-4), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10-4). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

4.
Am J Clin Nutr ; 2019 Jun 04.
Artigo em Inglês | MEDLINE | ID: mdl-31161197

RESUMO

BACKGROUND: Food neophobia is considered a behavioral trait closely linked to adverse eating patterns and reduced dietary quality, which have been associated with increased risk of obesity and noncommunicable diseases. OBJECTIVES: In a cross-sectional and prospective study, we examined how food neophobia is associated with dietary quality, health-related biomarkers, and disease outcome incidence in Finnish and Estonian adult populations. METHODS: The study was conducted based on subsamples of the Finnish DIetary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) cohort (n = 2982; age range: 25-74 y) and the Estonian Biobank cohort (n = 1109; age range: 18-83 y). The level of food neophobia was assessed using the Food Neophobia Scale, dietary quality was evaluated using the Baltic Sea Diet Score (BSDS), and biomarker profiles were determined using an NMR metabolomics platform. Disease outcome information was gathered from national health registries. Follow-up data on the NMR-based metabolomic profiles and disease outcomes were available in both populations. RESULTS: Food neophobia associated significantly (adjusted P < 0.05) with health-related biomarkers [e.g., ω-3 (n-3) fatty acids, citrate, α1-acid glycoprotein, HDL, and MUFA] in the Finnish DILGOM cohort. The significant negative association between the severity of food neophobia and ω-3 fatty acids was replicated in all cross-sectional analyses in the Finnish DILGOM and Estonian Biobank cohorts. Furthermore, food neophobia was associated with reduced dietary quality (BSDS: ß: -0.03 ± 0.006; P = 8.04 × 10-5), increased fasting serum insulin (ß: 0.004 ± 0.0013; P = 5.83 × 10-3), and increased risk of type 2 diabetes during the ∼8-y follow-up (HR: 1.018 ± 0.007; P = 0.01) in the DILGOM cohort. CONCLUSIONS: In the Finnish and Estonian adult populations, food neophobia was associated with adverse alteration of health-related biomarkers and risk factors that have been associated with an increased risk of noncommunicable diseases. We also found that food neophobia associations with ω-3 fatty acids and associated metabolites are mediated through dietary quality independent of body weight.

5.
BMC Cancer ; 19(1): 557, 2019 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-31182048

RESUMO

BACKGROUND: Published genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aimed to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies. METHODS: Four different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) were compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors were studied in both cohorts. RESULTS: The metaGRS that combines two genetic risk scores (metaGRS2 - based on 75 and 898 Single Nucleotide Polymorphisms, respectively) had the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS2 corresponded to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10- 135) in the UK Biobank and accounting for family history marginally attenuated the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 7.8*10- 129). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS2 compared to women in the lowest 50% was 4.2 (95% CI 2.8 to 6.2, p = 8.1*10- 13). The different GRSs were only moderately correlated with each other and were associated with different known predictors of BC. The classification of genetic risk for the same individual varied considerably depending on the chosen GRS. CONCLUSIONS: We have shown that metaGRS2, that combined on the effects of more than 900 SNPs, provided best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS2 indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.

6.
Elife ; 82019 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-30642433

RESUMO

We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer - but not other cancers - explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

7.
J Epidemiol Community Health ; 73(3): 272-277, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30635435

RESUMO

BACKGROUND: We aim to investigate the predictive ability of PCE (Pooled Cohort Equations), QRISK2 and SCORE (Systematic COronary Risk Estimation) scoring systems for atherosclerotic cardiovascular disease (ASCVD) risk prediction in Estonia, a country with one of the highest ASCVD event rates in Europe. METHODS: Seven-year risk estimates were calculated in risk score-specific subsets of the Estonian Biobank cohort. Calibration was assessed by standardised incidence ratios (SIRs) and discrimination by Harrell's C-statistics. In addition, a head-to-head comparison of the scores was performed in the intersection of the three score-specific subcohorts. RESULTS: PCE, QRISK2 and SCORE risk estimates were calculated for 4356, 7191 and 3987 eligible individuals, respectively. During the 7-year follow-up, 220 hard ASCVD events (PCE outcome), 671 ASCVD events (QRISK2 outcome) and 94 ASCVD deaths (SCORE outcome) occurred among the score-specific subsets of the cohort. While PCE (SIR 1.03, 95% CI 0.90 to 1.18) and SCORE (SIR 0.99, 95% CI 0.81 to 1.21) were calibrated well for the cohort, QRISK2 underestimated the risk by 48% (SIR 0.52, 95% CI 0.48 to 0.56). In terms of discrimination, PCE (C-statistic 0.778) was inferior to QRISK2 (C-statistic 0.812) and SCORE (C-statistic 0.865). All three risk scores performed at similar level in the head-to-head comparison. CONCLUSION: Of three widely used ASCVD risk scores, PCE and SCORE performed at acceptable level, while QRISK2 underestimated ASCVD risk markedly. These results highlight the need for evaluating the accuracy of ASCVD risk scores prior to use in high-risk populations.

8.
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
9.
Nat Genet ; 50(11): 1505-1513, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-30297969

RESUMO

We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

10.
Biomark Med ; 2018 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-30191727

RESUMO

AIM: The aim of the study was to explore the effects of variants at 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) and kinesin family member 6 (KIF6) loci on a range of cardio-metabolic phenotypes. METHODS: We analyzed the range of variants within Genetics in Brisighella Health Study and KIF6 genes using an additive genetic model on 18 cardiometabolic phenotypes in a sample of 1645 individuals from the Genetics in Brisighella Health Study and replicated in 10,662 individuals from the Estonian Genome Center University of Tartu. RESULTS: We defined directly the effects of rs3846662:C>A at HMGCR on apoB levels. The analysis also confirmed effects of on low-density lipoprotein-cholesterol and total cholesterol levels. Variants in KIF6 gene did not reveal any associations with cardiometabolic phenotypes. CONCLUSION: This study highlights effect of HMGCR locus on assay-determined apoB levels, an infrequent measure of blood lipids in large studies.

11.
Int J Cardiol ; 272: 26-32, 2018 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-30121176

RESUMO

BACKGROUND: The purpose was to describe the treatment and outcomes of non-ST-elevation myocardial infarction (NSTEMI) in Estonia according to patients' estimated mortality risk by the Global Registry of Acute Coronary Events (GRACE) score and investigate if inequalities in treatment had an impact on prognosis. METHODS: We performed a linkage between Estonian Myocardial Infarction Registry, Population Registry and Estonian Health Insurance Fund. All NSTEMI patients 2012-2014 were stratified into low (<4%), intermediate (4-12%), or high (>12%) mortality risk according to GRACE. All-cause mortality and composite endpoint of death, recurrent myocardial infarction, stroke or unplanned revascularization were compared between optimally - defined as concomitant in-hospital use of medicines from recommended groups and coronary angiography - and suboptimally managed patients, using the Cox regression. RESULTS: Out of 3803 NSTEMI patients (median age 73 years, 44% women) 20% were classified into low, 35% into intermediate and 45% into high risk category. In these groups, respectively, 62%, 46% and 23% of patients received optimal in-hospital management. Over the mean follow-up of 2.4 years the association between suboptimal in-hospital management and outcomes was the following: in the low risk group mortality hazard ratio (HR) 1.6 (95% confidence interval 0.8-3.2), composite endpoint HR 1.2 (0.8-1.8); in the intermediate risk group mortality HR 2.4 (1.7-3.3), composite endpoint HR 1.8 (1.4-2.3); and in the high risk group mortality HR 2.2 (1.8-2.8), composite endpoint HR 1.6 (1.3-2.0). CONCLUSIONS: Higher risk NSTEMI patients received less guideline-recommended in-hospital management, which was associated with a worse prognosis.

12.
Alzheimers Dement ; 14(6): 723-733, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29519576

RESUMO

INTRODUCTION: Metabolite, lipid, and lipoprotein lipid profiling can provide novel insights into mechanisms underlying incident dementia and Alzheimer's disease. METHODS: We studied eight prospective cohorts with 22,623 participants profiled by nuclear magnetic resonance or mass spectrometry metabolomics. Four cohorts were used for discovery with replication undertaken in the other four to avoid false positives. For metabolites that survived replication, combined association results are presented. RESULTS: Over 246,698 person-years, 995 and 745 cases of incident dementia and Alzheimer's disease were detected, respectively. Three branched-chain amino acids (isoleucine, leucine, and valine), creatinine and two very low density lipoprotein (VLDL)-specific lipoprotein lipid subclasses were associated with lower dementia risk. One high density lipoprotein (HDL; the concentration of cholesterol esters relative to total lipids in large HDL) and one VLDL (total cholesterol to total lipids ratio in very large VLDL) lipoprotein lipid subclass was associated with increased dementia risk. Branched-chain amino acids were also associated with decreased Alzheimer's disease risk and the concentration of cholesterol esters relative to total lipids in large HDL with increased Alzheimer's disease risk. DISCUSSION: Further studies can clarify whether these molecules play a causal role in dementia pathogenesis or are merely markers of early pathology.

13.
Alzheimers Dement ; 14(6): 707-722, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29316447

RESUMO

INTRODUCTION: Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions. METHODS: We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined. RESULTS: We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors. DISCUSSION: Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia.

14.
Nat Commun ; 8(1): 910, 2017 10 13.
Artigo em Inglês | MEDLINE | ID: mdl-29030599

RESUMO

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.


Assuntos
Cadeias alfa de HLA-DQ/genética , Cadeias HLA-DRB1/genética , Estilo de Vida , Lipoproteína(a)/genética , Longevidade/genética , Alelos , Índice de Massa Corporal , Doença das Coronárias/sangue , Doença das Coronárias/etiologia , Educação , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Humanos , Resistência à Insulina/genética , Lipoproteínas HDL/sangue , Neoplasias Pulmonares/sangue , Neoplasias Pulmonares/genética , Obesidade/complicações , Obesidade/genética , Polimorfismo de Nucleotídeo Único , Fumar/efeitos adversos , Fatores Socioeconômicos
15.
BMJ ; 358: j3542, 2017 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-28855160

RESUMO

Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease.Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding.Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors.Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin.Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education.Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D).Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10-8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile.Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.


Assuntos
Doença das Coronárias/genética , Escolaridade , Estudo de Associação Genômica Ampla , Análise da Randomização Mendeliana , Doença das Coronárias/prevenção & controle , Europa (Continente)/etnologia , Feminino , Conhecimentos, Atitudes e Prática em Saúde , Humanos , Masculino , Estudos Observacionais como Assunto , Fatores de Risco , Classe Social
16.
BMC Public Health ; 18(1): 34, 2017 07 19.
Artigo em Inglês | MEDLINE | ID: mdl-28724413

RESUMO

BACKGROUND: Tobacco smoking is known to be the single largest cause of premature death worldwide. The aim of present study was to analyse the effect of smoking on general and cause-specific mortality in the Estonian population. METHODS: The data from 51,756 adults in the Estonian Genome Center of the University of Tartu was used. Information on dates and causes of death was retrieved from the National Causes of Death Registry. Smoking status, general survival, general mortality and cause-specific mortality were analysed using Kaplan-Meier estimator and Cox proportional hazards models. RESULTS: The study found that smoking reduces median survival in men by 11.4 years and in women by 5.8 years. Tobacco smoking produces a very specific pattern in the cause of deaths, significantly increasing the risks for different cancers and cardiovascular diseases as causes of death for men and women. This study also identified that external causes, such as alcohol intoxication and intentional self-harm, are more prevalent causes of death among smokers than non-smokers. Additionally, smoking cessation was found to reverse the increased risks for premature mortality. CONCLUSIONS: Tobacco smoking remains the major cause for losses of life inducing cancers and cardiovascular diseases. In addition to the common diseases, external causes also reduce substantially the years of life. External causes of death indicate that smoking has a long-term influence on the behaviour of smokers, provoking self-destructive behaviour. Our study supports the idea, that tobacco smoking generates complex harm to our health increasing mortality from both somatic and mental disorders.


Assuntos
Fumar/mortalidade , Adolescente , Adulto , Idoso , Intoxicação Alcoólica/epidemiologia , Doenças Cardiovasculares/mortalidade , Causas de Morte , Estônia/epidemiologia , Feminino , Humanos , Expectativa de Vida , Masculino , Pessoa de Meia-Idade , Mortalidade Prematura/tendências , Neoplasias/mortalidade , Prevalência , Modelos de Riscos Proporcionais , Comportamento Autodestrutivo/epidemiologia , Fatores Sexuais , Adulto Jovem
17.
PLoS One ; 12(7): e0179238, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28678847

RESUMO

Polygenic risk scores are gaining more and more attention for estimating genetic risks for liabilities, especially for noncommunicable diseases. They are now calculated using thousands of DNA markers. In this paper, we compare the score distributions of two previously published very large risk score models within different populations. We show that the risk score model together with its risk stratification thresholds, built upon the data of one population, cannot be applied to another population without taking into account the target population's structure. We also show that if an individual is classified to the wrong population, his/her disease risk can be systematically incorrectly estimated.


Assuntos
Doença das Coronárias/genética , Diabetes Mellitus Tipo 2/genética , Genética Populacional , Herança Multifatorial/genética , África , Américas , Ásia , Estônia , Europa (Continente) , Extremo Oriente , Frequência do Gene , Predisposição Genética para Doença/genética , Humanos , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Análise de Componente Principal , Medição de Risco/métodos , Medição de Risco/estatística & dados numéricos , Fatores de Risco
18.
Eur J Hum Genet ; 25(8): 988-994, 2017 08.
Artigo em Inglês | MEDLINE | ID: mdl-28537275

RESUMO

Genome-wide association studies have facilitated the discovery of thousands of loci for hundreds of phenotypes. However, the issue of missing heritability remains unsolved for most complex traits. Locus discovery could be enhanced with both improved power through multi-phenotype analysis (MPA) and use of a wider allele frequency range, including rare variants (RVs). MPA methods for single-variant association have been proposed, but given their low power for RVs, more efficient approaches are required. We propose multi-phenotype analysis of rare variants (MARV), a burden test-based method for RVs extended to the joint analysis of multiple phenotypes through a powerful reverse regression technique. Specifically, MARV models the proportion of RVs at which minor alleles are carried by individuals within a genomic region as a linear combination of multiple phenotypes, which can be both binary and continuous, and the method accommodates directly the genotyped and imputed data. The full model, including all phenotypes, is tested for association for discovery, and a more thorough dissection of the phenotype combinations for any set of RVs is also enabled. We show, via simulations, that the type I error rate is well controlled under various correlations between two continuous phenotypes, and that the method outperforms a univariate burden test in all considered scenarios. Application of MARV to 4876 individuals from the Northern Finland Birth Cohort 1966 for triglycerides, high- and low-density lipoprotein cholesterols highlights known loci with stronger signals of association than those observed in univariate RV analyses and suggests novel RV effects for these lipid traits.


Assuntos
Frequência do Gene , Estudo de Associação Genômica Ampla/métodos , Modelos Genéticos , Algoritmos , Colesterol/sangue , Colesterol/genética , Feminino , Predisposição Genética para Doença , Humanos , Masculino
19.
Nat Commun ; 8: 14977, 2017 04 26.
Artigo em Inglês | MEDLINE | ID: mdl-28443625

RESUMO

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.


Assuntos
Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Obesidade/genética , Locos de Características Quantitativas/genética , Fumar/genética , Adiposidade/genética , Adulto , Distribuição da Gordura Corporal , Índice de Massa Corporal , Epistasia Genética , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único , Circunferência da Cintura/genética , Relação Cintura-Quadril
20.
PLoS Genet ; 13(3): e1006643, 2017 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-28248954

RESUMO

Inappropriate activation or inadequate regulation of CD4+ and CD8+ T cells may contribute to the initiation and progression of multiple autoimmune and inflammatory diseases. Studies on disease-associated genetic polymorphisms have highlighted the importance of biological context for many regulatory variants, which is particularly relevant in understanding the genetic regulation of the immune system and its cellular phenotypes. Here we show cell type-specific regulation of transcript levels of genes associated with several autoimmune diseases in CD4+ and CD8+ T cells including a trans-acting regulatory locus at chr12q13.2 containing the rs1131017 SNP in the RPS26 gene. Most remarkably, we identify a common missense variant in IL27, associated with type 1 diabetes that results in decreased functional activity of the protein and reduced expression levels of downstream IRF1 and STAT1 in CD4+ T cells only. Altogether, our results indicate that eQTL mapping in purified T cells provides novel functional insights into polymorphisms and pathways associated with autoimmune diseases.

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