OSCA: a tool for omic-data-based complex trait analysis

Zhang, Futao; Chen, Wenhan; Zhu, Zhihong; Zhang, Qian; Deary, Ian J.; Wray, Naomi R.; Visscher, Peter M.; McRae, Allan F.; Yang, Jian

doi:10.1101/445163

Cited by 13 publications

(19 citation statements)

References 65 publications

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“…Specifically, we used the Levene's median test implemented in OSCA 98 . Following the guidelines of Wang et al, we (1) adjusted 25OHD levels for selected covariates (see below), (2) removed outliers more than 5 SD from the mean, and (3) standardised the residuals to have mean 0 and variance 1.…”

Section: Proxy-environment Vqtl and Seasonal Analysismentioning

confidence: 99%

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration

Revez

Tian

Qiao

et al. 2019

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AbstractVitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identified 143 independent loci in 112 1-Mb regions providing new insights into the physiology of vitamin D and implicating genes involved in (a) lipid and lipoprotein metabolism, (b) dermal tissue properties, and (c) the sulphonation and glucuronidation of 25OHD. Mendelian randomization models found no robust evidence that 25OHD concentration had causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes had (direct or indirect) causal effects on 25OHD concentration, clarifying the relationship between 25OHD status and health.

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Section: Proxy-environment Vqtl and Seasonal Analysismentioning

confidence: 99%

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration

Revez

Tian

Qiao

et al. 2019

Preprint

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“…Age was scaled to have mean 0 and variance 1. The MOMENT method was used to test for associations between the traits of interest and DNAm at individual probes [12].…”

Section: Epigenome-wide Association Studiesmentioning

confidence: 99%

An epigenome-wide association study of sex-specific chronological ageing

McCartney

Hillary

Zhang

et al. 2019

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IntroductionAdvanced age is associated with cognitive and physical decline, and is a major risk factor for a multitude of disorders including neurodegenerative diseases such as Alzheimer’s disease. There is also a gap in life-expectancy between males and females. DNA methylation differences have been shown to be associated with both age and sex. Here, we investigate age-by-sex differences in DNA methylation in an unrelated cohort of 2,586 individuals between the ages of 18 and 87 years.MethodsGenome-wide DNA methylation was measured on the Illumina HumanMethylationEPIC beadchip in a subset of unrelated individuals from the Generation Scotland cohort. Mixed linear model-based analyses were performed to investigate the relationship between DNA methylation and an interaction term between age and sex, as well as chronological age.ResultsAt a genome-wide significance level of P < 3.6 × 10−8, 14 loci were associated with the age-by-sex interaction term, the majority of which were X-linked (n = 12). Seven of these loci were annotated to genes. The site with the greatest difference mapped to GAGE10, an X-linked gene. Here, DNA methylation levels remained stable across the male adult age range (DNA methylation x age r = 0.02), but decreased across female adult age range (DNA methylation x age r = −0.61). The seven age-by-sex-associated genes were enriched among differentially-expressed genes in lung, liver, testis and blood.ConclusionThe majority of differences in age-associated DNA methylation trajectories between sexes are present on the X-chromosome. Several of these differences occur within genes which have implicated in multiple cancers, schizophrenia and systemic lupus erythematosus.

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“…), the only consequence being a less powerful hence conservative test (Bates et al, 2015; Crainiceanu and Ruppert, 2004; Pinheiro and Bates, 2000). Such test is implemented in OSCA (Zhang et al, 2019), as well as in GCTA (Yang et al, 2011).…”

Section: Methodsmentioning

confidence: 99%

“…Here, we introduce a set of analyses that leverages large sample sizes to fully exploit the spatial resolution of MRI images using linear mixed models (LMM) implemented in the OSCA software tool (Zhang et al, 2019). Our high-resolution approach (i.e.…”

Section: Introductionmentioning

confidence: 99%

Widespread associations between grey matter structure and the human phenome

Couvy‐Duchesne

Strike

Zhang

et al. 2019

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The recent availability of large-scale neuroimaging cohorts (here the UK Biobank [UKB] and the Human Connectome Project [HCP]) facilitates deeper characterisation of the relationship between phenotypic and brain architecture variation in humans. We tested the association between 654,386 vertex-wise measures of cortical and subcortical morphology (from T1w and T2w MRI images) and behavioural, cognitive, psychiatric and lifestyle data. We found a significant association of grey-matter structure with 58 out of 167 UKB phenotypes spanning substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains (UKB discovery sample: N=9,888). Twenty-three of the 58 associations replicated (UKB replication sample: N=4,561; HCP, N=1,110). In addition, differences in body size (height, weight, BMI, waist and hip circumference, body fat percentage) could account for a substantial proportion of the association, providing possible insight into previous MRI case-control studies for psychiatric disorders where case status is associated with body mass index. Using the same linear mixed model, we showed that most of the associated characteristics (e.g. age, sex, body size, diabetes, being a twin, maternal smoking, body size) could be significantly predicted using all the brain measurements in out-of-sample prediction. Finally, we demonstrated other applications of our approach including a Region Of Interest (ROI) analysis that retain the vertex-wise complexity and ranking of the information contained across MRI processing options. Highlights Our linear mixed model approach unifies association and prediction analyses for highly dimensional vertex-wise MRI data Grey-matter structure is associated with measures of substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains Body size (height, weight, BMI, waist and hip circumference) is an important source of covariation between the phenome and grey-matter structure Grey-matter scores quantify grey-matter based risk for the associated traits and allow to study phenotypes not collected The most general cortical processing (“fsaverage” mesh with no smoothing) maximises the brain-morphometricity for all UKB phenotypes

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OSCA: a tool for omic-data-based complex trait analysis

Cited by 13 publications

References 65 publications

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration

An epigenome-wide association study of sex-specific chronological ageing

Widespread associations between grey matter structure and the human phenome

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