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1.
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.

2.
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).

3.
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.

4.
Genet Med ; 2018 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-30270359

RESUMO

PURPOSE: Large-scale, population-based biobanks integrating health records and genomic profiles may provide a platform to identify individuals with disease-predisposing genetic variants. Here, we recall probands carrying familial hypercholesterolemia (FH)-associated variants, perform cascade screening of family members, and describe health outcomes affected by such a strategy. METHODS: The Estonian Biobank of Estonian Genome Center, University of Tartu, comprises 52,274 individuals. Among 4776 participants with exome or genome sequences, we identified 27 individuals who carried FH-associated variants in the LDLR, APOB, or PCSK9 genes. Cascade screening of 64 family members identified an additional 20 carriers of FH-associated variants. RESULTS: Via genetic counseling and clinical management of carriers, we were able to reclassify 51% of the study participants from having previously established nonspecific hypercholesterolemia to having FH and identify 32% who were completely unaware of harboring a high-risk disease-associated genetic variant. Imaging-based risk stratification targeted 86% of the variant carriers for statin treatment recommendations. CONCLUSION: Genotype-guided recall of probands and subsequent cascade screening for familial hypercholesterolemia is feasible within a population-based biobank and may facilitate more appropriate clinical management.

5.
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).

6.
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
7.
Genet Med ; 19(3): 322-329, 2017 03.
Artigo em Inglês | MEDLINE | ID: mdl-27513194

RESUMO

PURPOSE: Using effect estimates from genome-wide association studies (GWAS), we identified a genetic risk score (GRS) that has the strongest association with type 2 diabetes (T2D) status in a population-based cohort and investigated its potential for prospective T2D risk assessment. METHODS: By varying the number of single-nucleotide polymorphisms (SNPs) and their respective weights, alternative versions of GRS can be computed. They were tested in 1,181 T2D cases and 9,092 controls of the Estonian Biobank cohort. The best-fitting GRS was chosen for the subsequent analysis of incident T2D (386 cases). RESULTS: The best fit was provided by a novel doubly weighted GRS that captures the effect of 1,000 SNPs. The hazard for incident T2D was 3.45 times (95% CI: 2.31-5.17) higher in the highest GRS quintile compared with the lowest quintile, after adjusting for body mass index and other known predictors. Adding GRS to the prediction model for 5-year T2D risk resulted in continuous net reclassification improvement of 0.324 (95% CI: 0.211-0.444). In addition, a significant effect of the GRS on all-cause and cardiovascular mortality was observed. CONCLUSION: The proposed GRS would improve the accuracy of T2D risk prediction when added to the currently used set of predictors.Genet Med 19 3, 322-329.


Assuntos
Diabetes Mellitus Tipo 2/genética , Testes Genéticos/métodos , Alelos , Índice de Massa Corporal , Estudos de Coortes , Diabetes Mellitus Tipo 2/prevenção & controle , Diabetes Mellitus Tipo 2/terapia , Feminino , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Medicina de Precisão/métodos , Estudos Prospectivos , Fatores de Risco
8.
Proc Natl Acad Sci U S A ; 113(47): 13366-13371, 2016 11 22.
Artigo em Inglês | MEDLINE | ID: mdl-27799538

RESUMO

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.


Assuntos
Escolaridade , Estudos de Associação Genética/métodos , Variação Genética , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Bases de Dados Genéticas , Estônia , Feminino , Humanos , Longevidade , Masculino , Pessoa de Meia-Idade , Herança Multifatorial , Pais , Escócia , Reino Unido
9.
Circ Cardiovasc Genet ; 9(3): 279-86, 2016 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-27103211

RESUMO

BACKGROUND: Cardiovascular risk factors tend to aggregate. The biological and predictive value of this aggregation is questioned and genetics could shed light on this debate. Our aims were to reappraise the impact of risk factor confluence on ischemic heart disease (IHD) risk by testing whether genetic risk scores (GRSs) associated with these factors interact on an additive or multiplicative scale, and to determine whether these interactions provide additional value for predicting IHD risk. METHODS AND RESULTS: We selected genetic variants associated with blood pressure, body mass index, waist circumference, triglycerides, type-2 diabetes mellitus, high-density lipoprotein and low-density lipoprotein cholesterol, and IHD to create GRSs for each factor. We tested and meta-analyzed the impact of additive (synergy index) and multiplicative (ßinteraction) interactions between each GRS pair in 1 case-control (n=6042) and 4 cohort studies (n=17 794) and evaluated the predictive value of these interactions. We observed 2 multiplicative interactions: GRSLDL·GRSTriglycerides (ßinteraction=-0.096; SE=0.028) and nonpleiotropic GRSIHD·GRSLDL (ßinteraction=0.091; SE=0.028). Inclusion of these interaction terms did not improve predictive capacity. CONCLUSIONS: The confluence of low-density lipoprotein cholesterol and triglycerides genetic risk load has an additive effect on IHD risk. The interaction between low-density lipoprotein cholesterol and IHD genetic load is more than multiplicative, supporting the hazardous impact on atherosclerosis progression of the combination of inflammation and increased lipid levels. The capacity of risk factor confluence to improve IHD risk prediction is questionable. Further studies in larger samples are warranted to confirm and expand our results.


Assuntos
Dislipidemias/sangue , Dislipidemias/genética , Isquemia Miocárdica/genética , Polimorfismo de Nucleotídeo Único , Pressão Sanguínea/genética , Índice de Massa Corporal , Estudos de Casos e Controles , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/genética , Dislipidemias/epidemiologia , Estudos de Associação Genética , Marcadores Genéticos , Predisposição Genética para Doença , Humanos , Hipertensão/epidemiologia , Hipertensão/genética , Hipertensão/fisiopatologia , Lipídeos/sangue , Isquemia Miocárdica/diagnóstico , Isquemia Miocárdica/epidemiologia , Isquemia Miocárdica/fisiopatologia , Obesidade/epidemiologia , Obesidade/genética , Fenótipo , Medição de Risco , Fatores de Risco , Circunferência da Cintura/genética
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