Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 228
Filtrar
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.
Nat Rev Genet ; 20(11): 693-701, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31455890

RESUMO

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

5.
Nat Commun ; 10(1): 3009, 2019 07 08.
Artigo em Inglês | MEDLINE | ID: mdl-31285442

RESUMO

Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a sample of more than 450,000 individuals from the UK Biobank and 1600 gene expression traits from a sample of 2000 individuals as well as across-tissue gene expression from the GTEx resource. We find approximately twice as much X-linked genetic variation across the UK Biobank traits in males (mean h2SNP = 0.63%) compared to females (mean h2SNP = 0.30%), confirming the predicted DC effect. Our DC estimates for complex traits and gene expression are consistent with a small proportion of genes escaping X-inactivation in a trait- and tissue-dependent manner. Finally, we highlight examples of biologically relevant X-linked heterogeneity between the sexes that bias DC estimates if unaccounted for.


Assuntos
Genes Ligados ao Cromossomo X/genética , Loci Gênicos/genética , Variação Genética/genética , Herança Multifatorial/genética , Inativação do Cromossomo X/genética , Conjuntos de Dados como Assunto , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Modelos Genéticos , Fenótipo , Fatores Sexuais
6.
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.

7.
Genetics ; 212(3): 905-918, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31123039

RESUMO

Expression QTL (eQTL) detection has emerged as an important tool for unraveling the relationship between genetic risk factors and disease or clinical phenotypes. Most studies are predicated on the assumption that only a single causal variant explains the association signal in each interval. This greatly simplifies the statistical modeling, but is liable to biases in scenarios where multiple local causal-variants are responsible. Here, our primary goal was to address the prevalence of secondary cis-eQTL signals regulating peripheral blood gene expression locally, utilizing two large human cohort studies, each >2500 samples with accompanying whole genome genotypes. The CAGE (Consortium for the Architecture of Gene Expression) dataset is a compendium of Illumina microarray studies, and the Framingham Heart Study is a two-generation Affymetrix dataset. We also describe Bayesian colocalization analysis of the extent of sharing of cis-eQTL detected in both studies as well as with the BIOS RNAseq dataset. Stepwise conditional modeling demonstrates that multiple eQTL signals are present for ∼40% of over 3500 eGenes in both microarray datasets, and that the number of loci with additional signals reduces by approximately two-thirds with each conditioning step. Although <20% of the peak signals across platforms fine map to the same credible interval, the colocalization analysis finds that as many as 50-60% of the primary eQTL are actually shared. Subsequently, colocalization of eQTL signals with GWAS hits detected 1349 genes whose expression in peripheral blood is associated with 591 human phenotype traits or diseases, including enrichment for genes with regulatory functions. At least 10%, and possibly as many as 40%, of eQTL-trait colocalized signals are due to nonprimary cis-eQTL peaks, but just one-quarter of these colocalization signals replicated across the gene expression datasets. Our results are provided as a web-based resource for visualization of multi-site regulation of gene expression and its association with human complex traits and disease states.

8.
Endocrinology ; 160(7): 1731-1742, 2019 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-31125048

RESUMO

Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance-based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall-Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

10.
Am J Nephrol ; 49(3): 193-202, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30808845

RESUMO

BACKGROUND: Serum urea level is a heritable trait, commonly used as a diagnostic marker for kidney function. Genome-wide association studies (GWAS) in East-Asian populations identified a number of genetic loci related to serum urea, however there is a paucity of data for European populations. METHODS: We performed a two-stage meta-analysis of GWASs on serum urea in 13,312 participants, with independent replication in 7,379 participants of European ancestry. RESULTS: We identified 6 genome-wide significant single nucleotide polymorphisms (SNPs) in or near 6 loci, of which 2 were novel (POU2AF1 and ADAMTS9-AS2). Replication of East-Asian and Scottish data provided evidence for an additional 8 loci. SNPs tag regions previously associated with anthropometric traits, serum magnesium, and urinary albumin-to-creatinine ratio, as well as expression quantitative trait loci for genes preferentially expressed in kidney and gastro-intestinal tissues. CONCLUSIONS: Our findings provide insights into the genetic underpinnings of urea metabolism, with potential relevance to kidney function.

11.
BMC Bioinformatics ; 20(1): 22, 2019 Jan 11.
Artigo em Inglês | MEDLINE | ID: mdl-30634901

RESUMO

BACKGROUND: Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. RESULTS: We developed Manhattan Harvester, a tool designed for "peak extraction" from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. CONCLUSIONS: We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available.


Assuntos
Gráficos por Computador , Interpretação Estatística de Dados , Mineração de Dados/métodos , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Genômica/métodos , Software , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único
12.
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
13.
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.

14.
Eur J Hum Genet ; 2018 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-30420678

RESUMO

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.

15.
Sci Rep ; 8(1): 15249, 2018 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-30323304

RESUMO

Using targeted NMR spectroscopy of 227 fasting serum metabolic traits, we searched for novel metabolic signatures of renal function in 926 type 2 diabetics (T2D) and 4838 non-diabetic individuals from four independent cohorts. We furthermore investigated longitudinal changes of metabolic measures and renal function and associations with other T2D microvascular complications. 142 traits correlated with glomerular filtration rate (eGFR) after adjusting for confounders and multiple testing: 59 in diabetics, 109 in non-diabetics with 26 overlapping. The amino acids glycine and phenylalanine and the energy metabolites citrate and glycerol were negatively associated with eGFR in all the cohorts, while alanine, valine and pyruvate depicted opposite association in diabetics (positive) and non-diabetics (negative). Moreover, in all cohorts, the triglyceride content of different lipoprotein subclasses showed a negative association with eGFR, while cholesterol, cholesterol esters (CE), and phospholipids in HDL were associated with better renal function. In contrast, phospholipids and CEs in LDL showed positive associations with eGFR only in T2D, while phospholipid content in HDL was positively associated with eGFR both cross-sectionally and longitudinally only in non-diabetics. In conclusion, we provide a wide list of kidney function-associated metabolic traits and identified novel metabolic differences between diabetic and non-diabetic kidney disease.

16.
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.

17.
Genome Biol ; 19(1): 139, 2018 09 21.
Artigo em Inglês | MEDLINE | ID: mdl-30241495

RESUMO

BACKGROUND: The genetic origins of Uralic speakers from across a vast territory in the temperate zone of North Eurasia have remained elusive. Previous studies have shown contrasting proportions of Eastern and Western Eurasian ancestry in their mitochondrial and Y chromosomal gene pools. While the maternal lineages reflect by and large the geographic background of a given Uralic-speaking population, the frequency of Y chromosomes of Eastern Eurasian origin is distinctively high among European Uralic speakers. The autosomal variation of Uralic speakers, however, has not yet been studied comprehensively. RESULTS: Here, we present a genome-wide analysis of 15 Uralic-speaking populations which cover all main groups of the linguistic family. We show that contemporary Uralic speakers are genetically very similar to their local geographical neighbours. However, when studying relationships among geographically distant populations, we find that most of the Uralic speakers and some of their neighbours share a genetic component of possibly Siberian origin. Additionally, we show that most Uralic speakers share significantly more genomic segments identity-by-descent with each other than with geographically equidistant speakers of other languages. We find that correlated genome-wide genetic and lexical distances among Uralic speakers suggest co-dispersion of genes and languages. Yet, we do not find long-range genetic ties between Estonians and Hungarians with their linguistic sisters that would distinguish them from their non-Uralic-speaking neighbours. CONCLUSIONS: We show that most Uralic speakers share a distinct ancestry component of likely Siberian origin, which suggests that the spread of Uralic languages involved at least some demic component.

19.
Eur J Med Genet ; 2018 Jul 18.
Artigo em Inglês | MEDLINE | ID: mdl-30031151

RESUMO

The pathogenesis of Hirschsprung disease is complex. Although the RET proto-oncogene is the most frequently affected gene in Hirschsprung disease, rare coding sequence variants explain only a small part of Hirschsprung disease cases. We aimed to assess the genetic background of Hirschsprung disease using a genome-wide association analysis combined with sequencing all RET exons in samples from 105 Hirschsprung disease cases (30 familial and 75 sporadic) and 386 controls. As expected, variants in or near RET showed the strongest overall association with Hirschsprung disease and the most statistically significant association was observed when using a recessive genetic model (rs2435357, NC_000010.10:g.43582056T > C; genotype TT, OR = 17.31, P = 1.462 × 10-21). Previously published associations in variants in SEMA (rs11766001, NC_000007.13:g.84145202A > C; allele C, OR = 2.268, P = 0.009533) and NRG1 (rs4541858, NC_000008.10:g.32410309A > G; allele G, OR = 1.567, P = 0.015; rs7835688, NC_000008.10:g.32411499G > C; allele C, OR = 1.567, P = 0.015) were also replicated in the genome-wide association analysis. Sequencing revealed a total of 12 exonic RET rare variants. Of these, eight amino acid changing rare variants and two frameshift variants caused or possibly caused Hirschsprung disease. Only a minority of the Hirschsprung disease cases (9/30 familial; 7/75 sporadic) carried one of the rare variants. Excluding the rare variant carriers from the genome-wide association analysis did not appreciably change the association of rs2435357 with Hirschsprung disease. We estimate that approximately two thirds of the sporadic cases may be statistically attributed to the recessive action of the common non-coding RET variants. Thus, even though most cases do not carry rare RET variants, combinations of rare variants and the common non-coding RET variant cause the majority of the cases in our population.

20.
Nat Genet ; 50(8): 1112-1121, 2018 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-30038396

RESUMO

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA