ArticleScientific reports2019
Genome-wide human brain eQTLs: In-depth analysis and insights using the UKBEC dataset.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Brain multi-omic Mendelian randomisation to identify novel drug targets for gliomagenesis.Human molecular genetics · 2025Pooled it
- The X chromosome's influences on the human brain.Science advances · 2025Article
- Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis.American journal of human genetics · 2024Article
- Regulatory elements inGenetics in medicine open · 2024Article
- Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis.bioRxiv : the preprint server for biology · 2023Article
- Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes.Molecular psychiatry · 2023Article
- Network pharmacology and bioinformatics approach reveals the therapeutic mechanism of action of curcumin in Alzheimer disease.Metabolic brain disease · 2023Article
- Brain region-specific effects of nearly fixed sapiens-derived alleles.BMC genomic data · 2022Article
- Genetic control of the human brain proteome.American journal of human genetics · 2021Article
- MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies.PLoS genetics · 2021Article
- Author Correction: Genome-wide human brain eQTLs: In-depth analysis and insights using the UKBEC dataset.Scientific reports · 2020Article
- Comparison Between Expression Microarrays and RNA-Sequencing Using UKBEC Dataset Identified aFrontiers in neurology and neuroscience research · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the complexity of the human brain transcriptome architecture is one of the most important human genetics study areas. Previous studies have applied expression quantitative trait loci (eQTL) analysis at the genome-wide level of the brain to understand the underlying mechanisms relating to neurodegenerative diseases, primarily at the transcript level. To increase the resolution of our understanding, the current study investigates multi/single-region, transcript/exon-level and cis versus trans-acting eQTL, across 10 regions of the human brain. Some of the key findings of this study are: (i) only a relatively small proportion of eQTLs will be detected, where the sensitivity is under 5%; (ii) when an eQTL is acting in multiple regions (MR-eQTL), it tends to have very similar effects on gene expression in each of these regions, as well as being cis-acting; (iii) trans-acting eQTLs tend to have larger effects on expression compared to cis-acting eQTLs and tend to be specific to a single region (SR-eQTL) of the brain; (iv) the cerebellum has a very large number of eQTLs that function exclusively in this region, compared with other regions of the brain; (v) importantly, an interactive visualisation tool (Shiny app) was developed to visualise the MR/SR-eQTL at transcript and exon levels.
Identifiers
What OpenQuestion holds
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.