Evidence map›Paper›PMID 34293285›Full record

ArticleAmerican journal of human genetics2021

Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms.

Tongwu Zhang, Jiyeon Choi, Ramile Dilshat, Berglind Ósk Einarsdóttir, Michael A Kovacs, Mai Xu, Michael Malasky, Salma Chowdhury, Kristine Jones, D Timothy Bishop and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Functional characterization of the 9q34.13 locus identifiesbioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Genetic effects on the skin methylome in healthy older twins.American journal of human genetics · 2024
    Article
  9. eQTL studies: from bulk tissues to single cells.Journal of genetics and genomics = Yi chuan xue bao · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 5 institutions in 4 countries.

Tongwu ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Jiyeon ChoiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Ramile DilshatDepartment of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
Berglind Ósk EinarsdóttirDepartment of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
Michael A KovacsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Mai XuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Michael MalaskyCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Salma ChowdhuryCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Kristine JonesCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
D Timothy BishopLeeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds LS9 7TF, UK.
Alisa M GoldsteinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Mark M IlesLeeds Institute for Data Analytics, School of Medicine, University of Leeds, Leeds LS9 7TF, UK.
Maria Teresa LandiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Matthew H LawStatistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia; School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia.
Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Eiríkur SteingrímssonDepartment of Biochemistry and Molecular Biology, BioMedical Center, Faculty of Medicine, University of Iceland, Sturlugata 8, 101 Reykjavik, Iceland.
Kevin M BrownDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA. Electronic address: kevin.brown3@nih.gov.
Division of Cancer Epidemiology and GeneticsNational Cancer Institute · USUniversity of Iceland · ISUniversity of Leeds · GBQueensland University of Technology · AU

Funding

Laboratory of Translational GenomicsZIACP010201 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI PROKUNINA-OLSSON, LIUDMILA · 2010 to 2025
$91.2M
Genetic Epidermiology of MelanomaR01CA083115 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BISHOP, DAVID TIMOTHY, ELDER, DAVID ERIC · 2001 to 2017
$13.0M
Cancer Research UK 19167Cancer Research UK C588/A19167NCI NIH HHS R01 CA083115
6 · The paper itself

Abstract

Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.

Indexed as

Gene Regulatory NetworksQuantitative Trait LociAllelesAtlases as TopicChromatinChromosome MappingDNA MethylationGene Expression RegulationGenetic Predisposition to DiseaseGenome, HumanGenome-Wide Association StudyHumansInfant, NewbornInterferon Regulatory Factor-4Interferon Regulatory FactorsMaleChromatinInterferon Regulatory Factor-4Interferon Regulatory FactorscolocalizationDNA methylationgenome-wide association studyGWASIRF4mediation analysismelanocytemelanomamethylome-wide association studyMWASQTLquantitative trait locitrans-QTL

Identifiers

PMID34293285
PMCPMC8456160
OpenAlexW3185703904

What OpenQuestion holds

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Registered trials

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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.