A powerful conditional gene-based association approach implicated functionally important genes for schizophrenia

Li, Miaoxin; Jiang, Lin; Mak, Timothy Shin Heng; Kwan, Johnny S. H.; Xue, Changxi; Chen, Peikai; Leung, Hoi Yan; Cui, Liqian; Li, Tao; Sham, Pak C.

doi:10.1093/bioinformatics/bty682

Cited by 26 publications

(55 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The expression values at genes and transcripts are used to evaluate selective expression by a novel robust score. The GWAS p-values are used to detect susceptibility genes by a conditional gene-based association test we published recently [20]. The driver tissues are estimated by enrichment analysis of GWAS associated genes with selective expression.…”

Section: Resultsmentioning

confidence: 99%

“…LD is a tricky problem in GWAS for discriminating true susceptibility genes from indirectly associated genes. Li et al (2018) proposed a powerful statistical framework to isolate possible directly associated genes [20]. However, the original analysis was carried out according to a rank of statistical significance assuming the true susceptibility genes had the more significant p-values.…”

Section: Discussionmentioning

confidence: 99%

“…With the usage of expression data, we investigated the performance of the robust z-scores and three other metrics for prioritizing driver-tissues by GWAS-genes on the above proposed framework. In a large-scale Meta-GWAS study [27], 108 genes associated with schizophrenia detected by the conditional gene-based association analysis [20] were used as the benchmark dataset (See more in the method section and gene list in Excel Table S1). Table 1 shows the top five tissues enriched by the associated genes with selective expression detected by different approaches.…”

Section: Compare the Performance Of Different Selective Expression Mementioning

confidence: 99%

“…Finally, we asked how tissue-selectivity prioritization of a disease can be used to enhance detection of susceptibility genes in a post GWAS analysis. In the schizophrenia benchmark dataset, the selective expression ranking leads to ~30% different significant genes from the default statistical significance ranking in a conditional gene-based test [20]. Among the different significant genes, a rough in silico validation in PubMed shows the selective expression ranking results in more genes implicated in schizophrenia by literature than the statistical significance ranking (n=16 vs. 10, See details in Supplementary Excel Table 1).…”

Section: Tissue-selectivity Prioritization Enhances Detection Of Suscmentioning

confidence: 99%

“…The higher score, the more likely to be a susceptibility gene. The ranking score is then used to determine the order in a conditional gene-based association analysis [20]. Genes with higher ranking scores are given higher priority to enter the conditional procedure, which will have a higher chance of getting smaller p-values.…”

Section: Rank Genes By Tissue-selective Expression In Driver Tissuesmentioning

confidence: 99%

See 4 more Smart Citations

Estimating driver-tissues by robust selective expression of genes associated with complex diseases or traits

Jiang

Xue

Chen

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Running title: estimate tissue selective pathogen of complex diseases Abstract:The driver tissues or cell-types of many human diseases, in which susceptibility genes cause the diseases, remain elusive. We developed a framework to detect the causal-tissues of complex diseases or traits according to selective expression of disease-associated genes in genome-wide association study (GWAS). The core method of the framework is a new robust z-score to estimate genes' expression selectivity. Through extensive computing simulations and comparative analyses in a large-scale schizophrenia GWAS, we demonstrate the robust z-score is more sensitive than existing methods to detect multiple selectively expressed tissues, which further lead to the estimation of more biological sensible driver tissues. The effectiveness of this framework is further validated in five representative complex diseases with the usage of GWAS summary statistics and transcript-level expression in GTEx project. Finally, we also demonstrate that the prioritized tissues and the robust selective expression can enhance characterization of directly associated genes of a disease as well.Interesting results include the estimation of lung as a driver tissue of rheumatoid arthritis, consistent with clinical observations of morbidity between rheumatoid arthritis and lung diseases.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Compare the Performance Of Different Selective Expression Mementioning

confidence: 99%

Section: Tissue-selectivity Prioritization Enhances Detection Of Suscmentioning

confidence: 99%

Section: Rank Genes By Tissue-selective Expression In Driver Tissuesmentioning

confidence: 99%

See 3 more Smart Citations

Estimating driver-tissues by robust selective expression of genes associated with complex diseases or traits

Jiang

Xue

Chen

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Dissecting the high-resolution genetic architecture of complex phenotypes by accurately estimating gene-based conditional heritability

Miao,

Jiang,

Tang

et al. 2023

The American Journal of Human Genetics

View full text Add to dashboard Cite

Immune dysregulation in depression: Evidence from genome-wide association

Tubbs

Ding

Baum

et al. 2020

Brain, Behavior, & Immunity - Health

View full text Add to dashboard Cite

A strong body of evidence supports a role for immune dysregulation across many psychiatric disorders including depression, the leading cause of global disability. Recent progress in the search for genetic variants associated with depression provides the opportunity to strengthen our current understanding of etiological factors contributing to depression and generate novel hypotheses. Here, we provide an overview of the literature demonstrating a role for immune dysregulation in depression, followed by a detailed discussion of the immune-related genes identified by the most recent genome-wide meta-analysis of depression. These genes represent strong evidence-based targets for future basic and translational research which aims to understand the role of the immune system in depression pathology and identify novel points for therapeutic intervention.

show abstract

A powerful conditional gene-based association approach implicated functionally important genes for schizophrenia

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 26 publications

References 35 publications

Estimating driver-tissues by robust selective expression of genes associated with complex diseases or traits

Estimating driver-tissues by robust selective expression of genes associated with complex diseases or traits

Dissecting the high-resolution genetic architecture of complex phenotypes by accurately estimating gene-based conditional heritability

Immune dysregulation in depression: Evidence from genome-wide association

Contact Info

Product

Resources

About