MOCR-DB: The Multi-Omics Causal Resource Database for Genetic Correlation, Causal Inference, and Functional Interpretation
Chen, Hongwei ; Fan, Bingjie ; Chen, Huiyao ; Chen, Yongkun ; Shu, Yuelong and Zhang, Haoyang LU
(2026)
In Phenomics
- Abstract
- Genome-wide association studies (GWAS) have revealed extensive polygenic signals and overlapping genetic architectures across human traits, creating a need for resources that connect trait-level genetic relationships with gene-level functional evidence. Here, we developed the Multi-Omics Causal Resource Database (MOCR-DB), an interactive platform that integrates large-scale GWAS summary statistics from UK Biobank, FinnGen, and the COVID-19 Host Genetics Initiative with molecular quantitative trait locus (QTL) datasets. In total, 613 traits with significant heritability were retained and harmonized using the Unified Medical Language System. MOCR-DB integrates phenotype-to-phenotype analyses, including genetic correlation and Mendelian... (More)
- Genome-wide association studies (GWAS) have revealed extensive polygenic signals and overlapping genetic architectures across human traits, creating a need for resources that connect trait-level genetic relationships with gene-level functional evidence. Here, we developed the Multi-Omics Causal Resource Database (MOCR-DB), an interactive platform that integrates large-scale GWAS summary statistics from UK Biobank, FinnGen, and the COVID-19 Host Genetics Initiative with molecular quantitative trait locus (QTL) datasets. In total, 613 traits with significant heritability were retained and harmonized using the Unified Medical Language System. MOCR-DB integrates phenotype-to-phenotype analyses, including genetic correlation and Mendelian randomization, with phenotype-to-gene analyses based on QTL-informed summary-data-based Mendelian randomization analysis (SMR) within a single searchable and interactive framework. The platform supports exploration of cross-trait genetic correlations, putative causal relationships, and candidate functional gene associations. An AI-assisted module provides concise plain-language summaries to help contextualize statistical findings. As a case study, we examined obesity and COVID-19 severity, where genetically predicted obesity showed a stronger association with critical COVID-19 and lung eQTL-based SMR analyses revealed distinct immune- and neuronal-related molecular patterns across severity groups. MOCR-DB thus provides a unified and accessible resource for investigating shared genetic architectures and prioritized functional gene candidates across complex traits, supporting the generation of reproducible and biologically interpretable hypotheses. The database is publicly available at https://chenhongwei.net/public/MOCRdb/. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3b429099-0b44-4136-96eb-8979fa518498
- author
- Chen, Hongwei
; Fan, Bingjie
; Chen, Huiyao
; Chen, Yongkun
; Shu, Yuelong
and Zhang, Haoyang
LU
- organization
- publishing date
- 2026
- type
- Contribution to journal
- publication status
- epub
- subject
- in
- Phenomics
- publisher
- Springer
- external identifiers
-
- scopus:105048704648
- ISSN
- 2730-583X
- DOI
- 10.1007/s43657-026-00338-w
- language
- English
- LU publication?
- yes
- id
- 3b429099-0b44-4136-96eb-8979fa518498
- alternative location
- https://link.springer.com/10.1007/s43657-026-00338-w
- date added to LUP
- 2026-08-28 10:07:39
- date last changed
- 2026-09-23 14:36:48
@article{3b429099-0b44-4136-96eb-8979fa518498,
abstract = {{Genome-wide association studies (GWAS) have revealed extensive polygenic signals and overlapping genetic architectures across human traits, creating a need for resources that connect trait-level genetic relationships with gene-level functional evidence. Here, we developed the Multi-Omics Causal Resource Database (MOCR-DB), an interactive platform that integrates large-scale GWAS summary statistics from UK Biobank, FinnGen, and the COVID-19 Host Genetics Initiative with molecular quantitative trait locus (QTL) datasets. In total, 613 traits with significant heritability were retained and harmonized using the Unified Medical Language System. MOCR-DB integrates phenotype-to-phenotype analyses, including genetic correlation and Mendelian randomization, with phenotype-to-gene analyses based on QTL-informed summary-data-based Mendelian randomization analysis (SMR) within a single searchable and interactive framework. The platform supports exploration of cross-trait genetic correlations, putative causal relationships, and candidate functional gene associations. An AI-assisted module provides concise plain-language summaries to help contextualize statistical findings. As a case study, we examined obesity and COVID-19 severity, where genetically predicted obesity showed a stronger association with critical COVID-19 and lung eQTL-based SMR analyses revealed distinct immune- and neuronal-related molecular patterns across severity groups. MOCR-DB thus provides a unified and accessible resource for investigating shared genetic architectures and prioritized functional gene candidates across complex traits, supporting the generation of reproducible and biologically interpretable hypotheses. The database is publicly available at https://chenhongwei.net/public/MOCRdb/.}},
author = {{Chen, Hongwei and Fan, Bingjie and Chen, Huiyao and Chen, Yongkun and Shu, Yuelong and Zhang, Haoyang}},
issn = {{2730-583X}},
language = {{eng}},
publisher = {{Springer}},
series = {{Phenomics}},
title = {{MOCR-DB: The Multi-Omics Causal Resource Database for Genetic Correlation, Causal Inference, and Functional Interpretation}},
url = {{http://dx.doi.org/10.1007/s43657-026-00338-w}},
doi = {{10.1007/s43657-026-00338-w}},
year = {{2026}},
}