Evidence map›Paper›PMID 37768517›Full record

ArticleGenes & genomics2023

Identification of genomic-wide genetic links between cutaneous melanoma and obesity-related physical traits via cFDR.

Shen Lin, Runnan Shen, Jingqian Huang, Yanhan Liu, Hongpeng Li, Qingfang Xu

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Article in Genes & genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors at 1 institution in 1 country.

Shen Lin *Department of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Runnan Shen *Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
Jingqian HuangDepartment of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Yanhan LiuZhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
Hongpeng LiDepartment of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Qingfang XuDepartment of Dermato-Venereology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. xqf69@163.com.
Sun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81773340Natural Science Foundation of Guangdong Province 2021A1515012622Natural Science Foundation of Guangdong Province 2022A1515012451
6 · The paper itself

Abstract

backgroundBoth epidemiological and clinical studies have suggested the comorbidity between cutaneous melanoma (CM) and obesity-related physical traits. However, it remains unclear about their shared genetic architecture.

objectiveTo determine the shared genetic architecture between CM and obesity-related physical traits through conditional false discovery rate (cFDR) analysis.

methodQuantile-quantile plots were firstly built to assess the pleiotropic enrichment of shared single nucleotide polymorphisms between CM and each trait. Then, cFDR and conjunctional cFDR (ccFDR) were used to identify the shared risk loci between CM and each trait. Moreover, the functional evaluation of shared risk genes was carried out through analyses of expression quantitative trait loci (eQTL), Kyoto Encyclopedia of Genes and Genomes and gene ontology, respectively. Finally, single-cell sequence analysis was performed to locate the expression of eQTL-mapped genes in tissues.

resultsSuccessive pleiotropic enrichment was found between CM and 5 obesity-related traits or height. 24 shared risk loci were identified between CM and 13 traits except appendicular lean mass using ccFDR analysis, with 17 novel and 4 validated loci. The functions of ccFDR-identified and eQTL-mapped genes were revealed to be mainly involved in cellular senescence, proliferation, meiotic nuclear division, cell cycle, and the metabolism of lipid, cholesterol and glucose. Single-cell sequence analysis showed that keratinocytes contribute to the occurrence and aggressiveness of CM through secreting paracrine cytokines.

conclusionOur findings demonstrate the significant genetic correlation between CM and obesity-related physical traits, which may provide a novel genetical basis for the pathogenesis and treatment of CM.

Indexed as

MelanomaSkin NeoplasmsCutaneous Malignant MelanomaGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansObesityQuantitative Trait LociConditional false discovery rateCutaneous melanomaObesityPleiotropy

Identifiers

PMID37768517
OpenAlexW4387116140

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