ArticleBriefings in bioinformatics2022
Integrating multi-omics summary data using a Mendelian randomization framework.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The relationship between amino acids and gastroesophageal reflux disease: evidence from a mendelian randomization analysis combined with a meta-analysis.Frontiers in immunology · 2025Pooled it
- High Serum Monounsaturated Fatty Acids Levels May Increase Risk of Cardiovascular Disease: A Mendelian Randomization Study.Iranian journal of medical sciences · 2026Article
- Cell senescence-related pathogenic genes in sleep disorders: a multi-omics Mendelian randomization study.European archives of psychiatry and clinical neuroscience · 2026Article
- Macrophage polarization-related genes with potential causal roles in osteoporosis: a multi-omics Mendelian randomization study.Journal of orthopaedic surgery and research · 2026Article
- CCR1 as a potential regulator of neutrophil-mediated pathogenesis in post-acute ischemic stroke: a multi-omics Mendelian randomization.Clinical epigenetics · 2026Article
- Mitochondria-Related Pathogenic Genes in Paediatric Asthma: A Multi-Omics Mendelian Randomization Study.Journal of cellular and molecular medicine · 2026Article
- Unraveling the role of lipid metabolism in polycystic ovary syndrome through multi-omics Mendelian randomization.Journal of ovarian research · 2026Article
- Reactive astrocyte-related pathogenic genes in Parkinson's disease: A multi-omics Mendelian randomization study.Journal of Parkinson's disease · 2026Article
- An Integrative Genetic Strategy for Identifying Causal Genes at Quantitative Trait Loci in Chickens.Animals : an open access journal from MDPI · 2026Review
- Comment on "Multi-Omics Association Analysis of Mitochondrial Genes in Hypertrophic Scars: Application of Mendelian Randomization" [Letter].Journal of inflammation research · 2026Article
- Parallel Single-Tissue Summary-Data Mendelian Randomization and Functional Validation Identify the ARRDC1 Promoter SNP rs4494021 as a Genetic Marker Associated with Anxiety Disorders.Neuropsychiatric disease and treatment · 2026Article
- Genetically prioritized mitochondrial regulators of advanced renal failure: multi-omic Mendelian randomization and biological plausibility assessment in allograft fibrosis.Frontiers in immunology · 2026Article
- Integrating differential gene expression and Mendelian randomization analyses reveal novel gene for prognosis, immune response, and drug sensitivity in lung cancer.Discover oncology · 2025Article
- Pathogenic genes associated with immune-related genes in graves' disease: a multi-omics Mendelian randomization analysis.Scientific reports · 2025Article
- Multiomic Mendelian randomization analysis of metabolic gene methylation expression and protein levels in lung adenocarcinoma.Discover oncology · 2025Article
- The methylation site cg06972019 regulates the succinylation-related gene ENO1 to inhibit the occurrence of erectile dysfunction.Hereditas · 2025Article
- Multiomic insight into the involvement of cell aging related genes in the pathogenesis of endometriosis.Scientific reports · 2025Article
- metacp: a versatile software package for combining dependent or independent p-values.BMC bioinformatics · 2025Article
- Integrative Multi-Omics Approach for Improving Causal Gene Identification.Genetic epidemiology · 2025Article
- Deciphering the genetic interplay between depression and dysmenorrhea: a Mendelian randomization study.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Mendelian randomization is a versatile tool to identify the possible causal relationship between an omics biomarker and disease outcome using genetic variants as instrumental variables. A key theme is the prioritization of genes whose omics readouts can be used as predictors of the disease outcome through analyzing GWAS and QTL summary data. However, there is a dearth of study of the best practice in probing the effects of multiple -omics biomarkers annotated to the same gene of interest. To bridge this gap, we propose powerful combination tests that integrate multiple correlated $P$-values without assuming the dependence structure between the exposures. Our extensive simulation experiments demonstrate the superiority of our proposed approach compared with existing methods that are adapted to the setting of our interest. The top hits of the analyses of multi-omics Alzheimer's disease datasets include genes ABCA7 and ATP1B1.
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