Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Qi, Ting; Wu, Yang; Zeng, Jian; Zhang, Futao; Xue, Anke; Jiang, Longda; Zhu, Zhihong; Kemper, Kathryn E.; Yengo, Loïc; Zheng, Zhili; Marioni, Riccardo E.; Montgomery, Grant W.; Deary, Ian J.; Wray, Naomi R.; Visscher, Peter M.; McRae, Allan F.; Yang, Jian

doi:10.1038/s41467-018-04558-1

Cited by 315 publications

(335 citation statements)

References 63 publications

Supporting

Mentioning

300

Contrasting

Order By: Relevance

“…In addition, as in TWAS, we could apply our method to and then combine the results from multiple tissues, or apply other more powerful and adaptive tests (Gusev et al 2016;Xu et al 2017). The issue with the choice of the tissue or cell type is similar to that in TWAS: a recent study (Qi et al 2018) has shown that, for brain-related traits, using blood cis-eQTL (with larger sample sizes) could gain power over using (smaller) brain eQTL data sets, while the genetic effects of cis-eQTL are highly correlated between independent brain and blood samples. Finally, although our application was focused on schizophrenia, the proposed method is quite general and applicable to other traits based on either individual-level or summary GWAS data.…”

Section: Discussionmentioning

confidence: 99%

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

Wu¹,

Pan

2018

Genetics

View full text Add to dashboard Cite

It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for "missing heritability." Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer-promoter interactions in high resolutions. Due to the well-known critical roles of enhancer-promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer-promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.

show abstract

Section: Discussionmentioning

confidence: 99%

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

Wu¹,

Pan

2018

Genetics

View full text Add to dashboard Cite

show abstract

“…To search for evidence of the functional effects of genetic variants associated with any of the three sedentary traits, we used multiple functional eQTL mapping. This was done using summary data based Mendelian randomization (SMR) 58 analysis (version 0.710) in data repositories from GTEx V7 59 , GTEx brain 60 , Brain-eMeta eQTL 60 and blood eQTL from Westra 61 and CAGE 62 . EQTL genes were considered as a candidate causal gene if they achieved a Bonferronicorrected significance of P < 0.05/187,747 = 2.66 × 10 −7 , passed the HEIDI test of P > 0.05 and if the lead variants of the eQTL genes were in LD (R 2 > 0.8) with the queried variants.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

et al. 2020

View full text Add to dashboard Cite

Leisure sedentary behaviours are associated with increased risk of cardiovascular disease, but whether this relationship is causal is unknown. The aim of this study is to identify genetic determinants associated with leisure sedentary behaviours and to estimate the potential causal effect on coronary artery disease (CAD). Genome wide association analyses of leisure television watching, leisure computer use and driving behaviour in the UK Biobank identify 145, 36 and 4 genetic loci (P < 1×10 −8 ), respectively. High genetic correlations are observed between sedentary behaviours and neurological traits, including education and body mass index (BMI). Two-sample Mendelian randomization (MR) analysis estimates a causal effect between 1.5 hour increase in television watching and CAD (OR 1.44, 95%CI 1.25-1.66, P = 5.63 × 10 −07 ), that is partially independent of education and BMI in multivariable MR analyses. This study finds independent observational and genetic support for the hypothesis that increased sedentary behaviour by leisure television watching is a risk factor for CAD.

show abstract

“…This strategy would have missed genes with a cis-eQTL effect in retina but not in blood. However, we considered that if cis-eQTL effects are similar across tissues 18,24 , using a blood eQTL data set of large sample size could increase the power of gene discovery in comparison to using a retina eQTL data set of small sample size. In addition, blood is much more accessible than retina so that the growth of eQTL data from blood is expected to be faster than that from retina, suggesting that the power of our analysis strategy could be substantially improved in the future by leveraging blood eQTL data sets with sample sizes of orders of magnitude larger than that used in this study 35 .…”

Section: Discussionmentioning

confidence: 99%

Towards the identification of causal genes for age-related macular degeneration

Cheng

Zhuang

Wen

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

18Age-related macular degeneration (AMD) is a leading cause of visual impairment in ageing 19 populations and has no radical treatment or prevention. Although genome-wide association studies 20 (GWAS) have identified many susceptibility loci for AMD, the underlying causal genes remain 21 elusive. Here, we prioritized nine putative causal genes by integrating expression quantitative trait 22 locus (eQTL) data from blood ( = 2,765) with AMD GWAS data (16,144 cases vs. 17,832 controls) 23 and replicated six of them using retina eQTL data ( = 523). Of the six genes, altering expression of 24 cnn2, sarm1 and bloc1s1 led to ocular phenotype, impaired vision and retinal pigment epithelium 25 (RPE) loss in zebrafish. Essential photoreceptor and RPE genes were downregulated in cnn2-and 26 sarm1-knockdown zebrafishes. Through integration of GWAS and eQTL data followed by functional 27 validation, our study reveals potential roles of CNN2, SARM1 and BLOC1S1 in AMD pathogenesis 28 and demonstrates an efficient platform to prioritise causal genes for human complex diseases. 29 2 Introduction 30 Age-related macular degeneration (AMD) is an incurable blinding disorder caused by dysfunction of the 31 retinal pigment epithelium (RPE) and progressive loss of photoreceptors in the macula 1 . It results in visual 32 impairment of central vision and disability of daily life activities, such as reading, walking and face 33recognition. The prevalence of AMD is 8.69% in the age range of 45-85 years globally, and it is projected 34 to affect 196 million people worldwide in 2020 2 . As such, AMD is highly endorsed as a major health and 35 social problem for both individuals and communities, especially in elderly populations 3 . 36 37 AMD is one of the most genetically well-defined complex diseases. Genome-wide association studies 38 (GWAS) with increasing sample sizes have identified 52 susceptibility loci which together explain more 39 than 50% of the heritability of liability 4-6 . These findings provide important clues for understanding the 40 genetic architecture of the disease, but the causal genes at those susceptibility loci and underlying 41 mechanisms remain largely unclear. For example, a nonsynonymous variant, CFH p. Arg1210Cys (allele 42 frequency = 0.00017 in ExAC), increases AMD risk by >20-fold 7 , but there has been no evidence showing 43 its functional impact on the regulation of gene expression, structural and functional integrity of the protein-44 coding region, or interplay with the genes nearby 8 . This is partly because of linkage disequilibrium (LD) 45 between single-nucleotide polymorphisms (SNPs) and causative variants that GWAS mapping resolution 9 . 46This could also be the reason that the trait-associated variants, especially those residing in non-coding 47

show abstract

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Cited by 315 publications

References 63 publications

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

Towards the identification of causal genes for age-related macular degeneration

Contact Info

Product

Resources

About