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1.
BMC Med ; 18(1): 71, 2020 Mar 23.
Artigo em Inglês | MEDLINE | ID: mdl-32200763

RESUMO

BACKGROUND: Age at menarche has been associated with various health outcomes. We aimed to identify potential causal effects of age at menarche on health-related traits in a hypothesis-free manner. METHODS: We conducted a Mendelian randomization phenome-wide association study (MR-pheWAS) of age at menarche with 17,893 health-related traits in UK Biobank (n = 181,318) using PHESANT. The exposure of interest was the genetic risk score for age at menarche. We conducted a second MR-pheWAS after excluding SNPs associated with BMI from the genetic risk score, to examine whether results might be due to the genetic overlap between age at menarche and BMI. We followed up a subset of health-related traits to investigate MR assumptions and seek replication in independent study populations. RESULTS: Of the 17,893 tests performed in our MR-pheWAS, we identified 619 associations with the genetic risk score for age at menarche at a 5% false discovery rate threshold, of which 295 were below a Bonferroni-corrected P value threshold. These included potential effects of younger age at menarche on lower lung function, higher heel bone-mineral density, greater burden of psychosocial/mental health problems, younger age at first birth, higher risk of childhood sexual abuse, poorer cardiometabolic health, and lower physical activity. After exclusion of variants associated with BMI, the genetic risk score for age at menarche was related to 37 traits at a 5% false discovery rate, of which 29 were below a Bonferroni-corrected P value threshold. We attempted to replicate findings for bone-mineral density, lung function, neuroticism, and childhood sexual abuse using 5 independent cohorts/consortia. While estimates for lung function, higher bone-mineral density, neuroticism, and childhood sexual abuse in replication cohorts were consistent with UK Biobank estimates, confidence intervals were wide and often included the null. CONCLUSIONS: The genetic risk score for age at menarche was related to a broad range of health-related traits. Follow-up analyses indicated imprecise evidence of an effect of younger age at menarche on greater bone-mineral density, lower lung function, higher neuroticism score, and greater risk of childhood sexual abuse in the smaller replication samples available; hence, these findings need further exploration when larger independent samples become available.

2.
Int J Epidemiol ; 2019 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-31834381

RESUMO

BACKGROUND: A lack of genetic data across generations makes transgenerational Mendelian randomization (MR) difficult. We used UK Biobank and a novel proxy gene-by-environment MR to investigate effects of maternal smoking heaviness in pregnancy on offspring health, using participants' (generation one: G1) genotype (rs16969968 in CHRNA5) as a proxy for their mothers' (G0) genotype. METHODS: We validated this approach by replicating an established effect of maternal smoking heaviness on offspring birthweight. Then we applied this approach to explore effects of maternal (G0) smoking heaviness on offspring (G1) later life outcomes and on birthweight of G1 women's children (G2). RESULTS: Each additional smoking-increasing allele in offspring (G1) was associated with a 0.018 [95% confidence interval (CI): -0.026, -0.009] kg lower G1 birthweight in maternal (G0) smoking stratum, but no meaningful effect (-0.002 kg; 95% CI: -0.008, 0.003) in maternal non-smoking stratum (interaction P-value = 0.004). The differences in associations of rs16969968 with grandchild's (G2) birthweight between grandmothers (G0) who did, versus did not, smoke were heterogeneous (interaction P-value = 0.042) among mothers (G1) who did (-0.020 kg/allele; 95% CI: -0.044, 0.003), versus did not (0.007 kg/allele; 95% CI: -0.005, 0.020), smoke in pregnancy. CONCLUSIONS: Our study demonstrated how offspring genotype can be used to proxy for the mother's genotype in gene-by-environment MR. We confirmed the causal effect of maternal (G0) smoking on offspring (G1) birthweight, but found little evidence of an effect on G1 longer-term health outcomes. For grandchild's (G2) birthweight, the effect of grandmother's (G0) smoking heaviness in pregnancy may be modulated by maternal (G1) smoking status in pregnancy.

3.
PLoS Genet ; 15(10): e1008353, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31671092

RESUMO

Mendelian randomization (MR) is an established approach to evaluate the effect of an exposure on an outcome. The gene-by-environment (GxE) study design can be used to determine whether the genetic instrument affects the outcome through pathways other than via the exposure of interest (horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and can be conducted in UK Biobank using the PHESANT package. In this proof-of-principle study, we introduce the novel GxE MR-pheWAS approach, that combines MR-pheWAS with the use of GxE interactions. This method aims to identify the presence of effects of an exposure while simultaneously investigating horizontal pleiotropy. We systematically test for the presence of causal effects of smoking heaviness-stratifying on smoking status (ever versus never)-as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. We used PHESANT to test for the presence of effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by the strength of interaction between ever and never smokers. We replicated previously established effects of smoking heaviness, including detrimental effects on lung function. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify potential effects of an exposure, while simultaneously assessing whether results may be biased by horizontal pleiotropy.


Assuntos
Fumar Cigarros/epidemiologia , Biologia Computacional/métodos , Análise da Randomização Mendeliana/métodos , Envelhecimento da Pele/efeitos dos fármacos , Bancos de Espécimes Biológicos , Fumar Cigarros/efeitos adversos , Fumar Cigarros/genética , Interação Gene-Ambiente , Pleiotropia Genética , Humanos , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Estudo de Prova de Conceito , Reino Unido/epidemiologia
4.
PLoS Genet ; 15(2): e1007951, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30707692

RESUMO

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We performed a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n = 334 968), using the PHESANT open-source phenome scan tool. A subset of identified associations were followed up with a formal two-stage instrumental variable analysis in UK Biobank, to estimate the causal effect of BMI on these phenotypes. Of the 22 922 tests performed, our MR-pheWAS identified 587 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate. These included many previously identified causal effects, for instance, an adverse effect of higher BMI on risk of diabetes and hypertension. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS in circa 115,000 UK Biobank participants and replicated in a different subset of circa 223,000 UK Biobank participants. Our comprehensive MR-pheWAS identified potential causal effects of BMI on a large and diverse set of phenotypes. This included both previously identified causal effects, and novel effects such as a protective effect of higher BMI on feelings of nervousness.


Assuntos
Índice de Massa Corporal , Adiposidade/genética , Adulto , Idoso , Ansiedade/genética , Bancos de Espécimes Biológicos , Estudos de Coortes , Feminino , Estudos de Associação Genética , Predisposição Genética para Doença , Humanos , Masculino , Análise da Randomização Mendeliana , Pessoa de Meia-Idade , Fenótipo , Polimorfismo de Nucleotídeo Único , Estudos Prospectivos , Fatores de Risco , Reino Unido
5.
BMJ ; 362: k3788, 2018 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-30254091

RESUMO

OBJECTIVES: To investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and cardiometabolic health is causal. DESIGN: Two sample, bidirectional mendelian randomisation study. SETTING: Genetic data taken from various cohorts comprised of the general population (mostly individuals of European ancestry, plus a small proportion of other ancestries); follow-up analysis included individuals from the United Kingdom. PARTICIPANTS: Summary data were used from previous genome wide association studies (number of participants ranging from 83 198 to 339 224), which investigated traits related to cardiovascular or metabolic health, had the largest sample sizes, and consisted of the most similar populations while minimising sample overlap. A follow-up analysis included 337 112 individuals from the UK Biobank (54% female (n=181 363), mean age 56.87 years (standard deviation 8.00) at recruitment). MAIN OUTCOME MEASURES: Subjective wellbeing and 11 measures of cardiometabolic health (coronary artery disease; myocardial infarction; total, high density lipoprotein, and low density lipoprotein cholesterol; diastolic and systolic blood pressure; body fat; waist to hip ratio; waist circumference; and body mass index). RESULTS: Evidence of a causal effect of body mass index on subjective wellbeing was seen; each 1 kg/m2 increase in body mass index caused a -0.045 (95% confidence interval -0.084 to -0.006, P=0.02) standard deviation reduction in subjective wellbeing. Follow-up analysis of this association in an independent sample from the UK Biobank provided strong evidence of an effect of body mass index on satisfaction with health (ß=-0.035 unit decrease in health satisfaction (95% confidence interval -0.043 to -0.027) per standard deviation increase in body mass index, P<0.001). No clear evidence of a causal effect was seen between subjective wellbeing and the other cardiometabolic health measures, in either direction. CONCLUSIONS: These results suggest that a higher body mass index is associated with a lower subjective wellbeing. A follow-up analysis confirmed this finding, suggesting that the effect in middle aged people could be driven by satisfaction with health. Body mass index is a modifiable determinant, and therefore, this study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher body mass index on subjective wellbeing.


Assuntos
Adiposidade/genética , Doenças Cardiovasculares/genética , Doenças Cardiovasculares/metabolismo , Doença das Coronárias/genética , Análise da Randomização Mendeliana/métodos , Infarto do Miocárdio/genética , Tecido Adiposo/metabolismo , Pressão Sanguínea/genética , Pressão Sanguínea/fisiologia , Índice de Massa Corporal , HDL-Colesterol/metabolismo , LDL-Colesterol/metabolismo , Doença das Coronárias/metabolismo , Feminino , Estudo de Associação Genômica Ampla/métodos , Humanos , Masculino , Pessoa de Meia-Idade , Infarto do Miocárdio/metabolismo , Sístole/fisiologia , Reino Unido/epidemiologia , Circunferência da Cintura/fisiologia
6.
Gigascience ; 7(8)2018 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-30165448

RESUMO

Background: Identifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restricted access to much individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. Two state-of-the-art methods, metaCCA and LD score regression, provide an alternative approach to estimate phenotypic correlation using only genome-wide association study (GWAS) summary results. Results: Here, we present an integrated R toolkit, PhenoSpD, to use LD score regression to estimate phenotypic correlations using GWAS summary statistics and to utilize the estimated phenotypic correlations to inform correction of multiple testing for complex human traits using the spectral decomposition of matrices (SpD). The simulations suggest that it is possible to identify nonindependence of phenotypes using samples with partial overlap; as overlap decreases, the estimated phenotypic correlations will attenuate toward zero and multiple testing correction will be more stringent than in perfectly overlapping samples. Also, in contrast to LD score regression, metaCCA will provide approximate genetic correlations rather than phenotypic correlation, which limits its application for multiple testing correction. In a case study, PhenoSpD using UK Biobank GWAS results suggested 399.6 independent tests among 487 human traits, which is close to the 352.4 independent tests estimated using true phenotypic correlation. We further applied PhenoSpD to an estimated 5,618 pair-wise phenotypic correlations among 107 metabolites using GWAS summary statistics from Kettunen's publication and PhenoSpD suggested the equivalent of 33.5 independent tests for these metabolites. Conclusions: PhenoSpD extends the use of summary-level results, providing a simple and conservative way to reduce dimensionality for complex human traits using GWAS summary statistics. This is particularly valuable in the age of large-scale biobank and consortia studies, where GWAS results are much more accessible than individual-level data.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único , Software , Humanos , Desequilíbrio de Ligação , Modelos Genéticos
7.
Bioinformatics ; 34(16): 2856-2858, 2018 08 15.
Artigo em Inglês | MEDLINE | ID: mdl-29617950

RESUMO

Summary: Existing ways of accessing data from the Reactome database are limited. Either a researcher is restricted to particular queries defined by a web application programming interface (API) or they have to download the whole database. Reactome Pengine is a web service providing a logic programming-based API to the human reactome. This gives researchers greater flexibility in data access than existing APIs, as users can send their own small programs (alongside queries) to Reactome Pengine. Availability and implementation: The server and an example notebook can be found at https://apps.nms.kcl.ac.uk/reactome-pengine. Source code is available at https://github.com/samwalrus/reactome-pengine and a Docker image is available at https://hub.docker.com/r/samneaves/rp4/. Supplementary information: Supplementary data are available at Bioinformatics online.


Assuntos
Software , Bases de Dados Factuais , Humanos , Lógica
8.
Int J Epidemiol ; 47(1): 29-35, 2018 02.
Artigo em Inglês | MEDLINE | ID: mdl-29040602

RESUMO

Motivation: Epidemiological cohorts typically contain a diverse set of phenotypes such that automation of phenome scans is non-trivial, because they require highly heterogeneous models. For this reason, phenome scans have to date tended to use a smaller homogeneous set of phenotypes that can be analysed in a consistent fashion. We present PHESANT (PHEnome Scan ANalysis Tool), a software package for performing comprehensive phenome scans in UK Biobank. General features: PHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables. Implementation: The PHESANT phenome scan is implemented in R. PHESANT includes a novel Javascript D3.js visualization and accompanying Java code that converts the phenome scan results to the required JavaScript Object Notation (JSON) format. Availability: PHESANT is available on GitHub at [https://github.com/MRCIEU/PHESANT]. Git tag v0.5 corresponds to the version presented here.

9.
Int J Epidemiol ; 46(6): 1857-1870, 2017 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-29106580

RESUMO

Background: Analysis of physical activity usually focuses on a small number of summary statistics derived from accelerometer recordings: average counts per minute and the proportion of time spent in moderate-vigorous physical activity or in sedentary behaviour. We show how bigrams, a concept from the field of text mining, can be used to describe how a person's activity levels change across (brief) time points. These variables can, for instance, differentiate between two people spending the same time in moderate activity, where one person often stays in moderate activity from one moment to the next and the other does not. Methods: We use data on 4810 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC). We generate a profile of bigram frequencies for each participant and test the association of each frequency with body mass index (BMI), as an exemplar. Results: We found several associations between changes in bigram frequencies and BMI. For instance, a one standard deviation decrease in the number of adjacent minutes in sedentary then moderate activity (or vice versa), with a corresponding increase in the number of adjacent minutes in moderate then vigorous activity (or vice versa), was associated with a 2.36 kg/m2 lower BMI [95% confidence interval (CI): -3.47, -1.26], after accounting for the time spent in sedentary, low, moderate and vigorous activity. Conclusions: Activity bigrams are novel variables that capture how a person's activity changes from one moment to the next. These variables can be used to investigate how sequential activity patterns associate with other traits.


Assuntos
Índice de Massa Corporal , Exercício , Acelerometria , Criança , Feminino , Comportamentos Relacionados com a Saúde , Humanos , Modelos Lineares , Estudos Longitudinais , Masculino , Estudos Prospectivos , Comportamento Sedentário
10.
Inductive Log Program ; 9575: 137-151, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27478883

RESUMO

We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist.

11.
Int J Epidemiol ; 45(1): 266-77, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26659355

RESUMO

BACKGROUND: Risk-of-bias assessments are now a standard component of systematic reviews. At present, reviewers need to manually identify relevant parts of research articles for a set of methodological elements that affect the risk of bias, in order to make a risk-of-bias judgement for each of these elements. We investigate the use of text mining methods to automate risk-of-bias assessments in systematic reviews. We aim to identify relevant sentences within the text of included articles, to rank articles by risk of bias and to reduce the number of risk-of-bias assessments that the reviewers need to perform by hand. METHODS: We use supervised machine learning to train two types of models, for each of the three risk-of-bias properties of sequence generation, allocation concealment and blinding. The first model predicts whether a sentence in a research article contains relevant information. The second model predicts a risk-of-bias value for each research article. We use logistic regression, where each independent variable is the frequency of a word in a sentence or article, respectively. RESULTS: We found that sentences can be successfully ranked by relevance with area under the receiver operating characteristic (ROC) curve (AUC) > 0.98. Articles can be ranked by risk of bias with AUC > 0.72. We estimate that more than 33% of articles can be assessed by just one reviewer, where two reviewers are normally required. CONCLUSIONS: We show that text mining can be used to assist risk-of-bias assessments.


Assuntos
Viés , Mineração de Dados/métodos , Aprendizado de Máquina/estatística & dados numéricos , Literatura de Revisão como Assunto , Conjuntos de Dados como Assunto , Humanos , Modelos Logísticos , Curva ROC
12.
Sci Rep ; 5: 16645, 2015 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-26568383

RESUMO

Observational cohort studies can provide rich datasets with a diverse range of phenotypic variables. However, hypothesis-driven epidemiological analyses by definition only test particular hypotheses chosen by researchers. Furthermore, observational analyses may not provide robust evidence of causality, as they are susceptible to confounding, reverse causation and measurement error. Using body mass index (BMI) as an exemplar, we demonstrate a novel extension to the phenome-wide association study (pheWAS) approach, using automated screening with genotypic instruments to screen for causal associations amongst any number of phenotypic outcomes. We used a sample of 8,121 children from the ALSPAC dataset, and tested the linear association of a BMI-associated allele score with 172 phenotypic outcomes (with variable sample sizes). We also performed an instrumental variable analysis to estimate the causal effect of BMI on each phenotype. We found 21 of the 172 outcomes were associated with the allele score at an unadjusted p < 0.05 threshold, and use Bonferroni corrections, permutation testing and estimates of the false discovery rate to consider the strength of results given the number of tests performed. The most strongly associated outcomes included leptin, lipid profile, and blood pressure. We also found novel evidence of effects of BMI on a global self-worth score.


Assuntos
Índice de Massa Corporal , Estudo de Associação Genômica Ampla , Alelos , Dioxigenase FTO Dependente de alfa-Cetoglutarato , Pressão Sanguínea/genética , Criança , Estudos de Coortes , Feminino , Genótipo , Humanos , Leptina/genética , Lipídeos/sangue , Estudos Longitudinais , Masculino , Análise da Randomização Mendeliana , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Proteínas/genética
13.
BMJ Open ; 3(9): e003574, 2013 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-24071462

RESUMO

OBJECTIVES: The long-term consequences of maternal physical activity during pregnancy for offspring cardiovascular health are unknown. We examined the association of maternal self-reported physical activity in pregnancy (18 weeks gestation) with offspring cardiovascular risk factors at age 15. DESIGN: Prospective cohort study. SETTING: The Avon Longitudinal Study of Parents and Children (ALSPAC). PARTICIPANTS: 4665 maternal-offspring pairs (based on a sample with multiple imputation to deal with missing data) from the ALSPAC, a prospective cohort based in the South West of England with mothers recruited in pregnancy in 1991-1992. PRIMARY AND SECONDARY OUTCOME MEASURES: Offspring cardiovascular risk factors at age 15; body mass index (BMI), waist circumference, systolic blood pressure, diastolic blood pressure, glucose, insulin, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides. RESULTS: Greater maternal physical activity was associated with lower BMI, waist circumference, glucose and insulin in unadjusted analyses. The magnitude of associations was generally small with wide CIs, and most associations attenuated towards the null after adjusting for confounders. The strongest evidence of association after adjustment for confounders was for glucose, although the 95% CI for this association includes the null; a one SD greater physical activity during pregnancy was associated with a -0.013 mmol/L difference in offspring glucose levels (equivalent to approximately one-third of a SD; 95% CI -0.027 to 0.001 mmol/L). CONCLUSIONS: Our results suggest that maternal physical activity in pregnancy, measured at 18 weeks gestation, is unlikely to be an important determinant of later offspring cardiovascular health. There was some suggestion of association with offspring glucose, but given that all other associations (including insulin) were null after adjustment for confounders, this result should be interpreted with caution.

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