ReviewHuman molecular genetics2022
Quantitative trait locus (xQTL) approaches identify risk genes and drug targets from human non-coding genomes.
Review in Human molecular genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Causal variants in animal genomes: approaches to identification, phenotypic impact, and implications for selective breeding.BMC genomics · 2026Review
- Cell-type-specific causal effects of CEBPD in CD8 + S100B + Tcells and ZFP36 in monocytes modulate the protective and risk phenotypes in psoriasis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- PRISM-xQTL: Pleiotropic Relationships Integrated with System-level Multiomic QTL analysis for causal genes and molecular mediators in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- [Mendelian Randomization Analysis of Potential Molecular Targets for Type 2 Airway Inflammatory Diseases].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Article
- Identifying the causal role and therapeutic potential of immune-related genes in bladder cancer: a Mendelian randomization study.Discover oncology · 2025Article
- Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations.Molecular psychiatry · 2025Article
- Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations.medRxiv : the preprint server for health sciences · 2024Article
- Article
- Human Molecular Genetics Review Issue 2022.Human molecular genetics · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Advances and reduction of costs in various sequencing technologies allow for a closer look at variations present in the non-coding regions of the human genome. Correlating non-coding variants with large-scale multi-omic data holds the promise not only of a better understanding of likely causal connections between non-coding DNA and expression of traits but also identifying potential disease-modifying medicines. Genome-phenome association studies have created large datasets of DNA variants that are associated with multiple traits or diseases, such as Alzheimer's disease; yet, the functional consequences of variants, in particular of non-coding variants, remain largely unknown. Recent advances in functional genomics and computational approaches have led to the identification of potential roles of DNA variants, such as various quantitative trait locus (xQTL) techniques. Multi-omic assays and analytic approaches toward xQTL have identified links between genetic loci and human transcriptomic, epigenomic, proteomic and metabolomic data. In this review, we first discuss the recent development of xQTL from multi-omic findings. We then highlight multimodal analysis of xQTL and genetic data for identification of risk genes and drug targets using Alzheimer's disease as an example. We finally discuss challenges and future research directions (e.g. artificial intelligence) for annotation of non-coding variants in complex diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.