Evidence map›Paper›PMID 40956437›Full record

ArticleInternational journal of legal medicine2026

Retrospective analysis-based prioritization and degradation pattern characterization of sudden unexplained death susceptibility genes.

Qi Shen, Zhimin Wang, Junyi Lin, Liliang Li, Suhua Zhang, Shouyu Wang, Chengtao Li

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Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Qi ShenSchool of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, China.
Zhimin WangDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Junyi LinDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Liliang LiDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
Suhua ZhangInstitute of Forensic Science, Fudan University, Shanghai, 200032, China.
Shouyu WangDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China. shouyu_wang@fudan.edu.cn.ORCID http://orcid.org/0000-0002-6082-2028
Chengtao LiInstitute of Forensic Science, Fudan University, Shanghai, 200032, China. lichengtao@fudan.edu.cn.ORCID http://orcid.org/0000-0001-6852-9144

Funding

National Natural Science Foundation of China 82101971National Natural Science Foundation of China 82293650National Natural Science Foundation of China 82293654Natural Science Foundation of Shanghai 25ZR1402096Opening Project of Shanghai Key Laboratory of Crime Scene Evidence 2018XCWZK21
6 · The paper itself

Abstract

Genetic factors are known to have important roles in sudden unexplained death (SUD) of apparently healthy individuals. Currently, molecular autopsy is considered an effective diagnostic tool in the multidisciplinary management of SUD. Recent studies highlighted the contribution of regulatory variants to complex genetic disorders. Pathogenic variants within the untranslated regions of SUD susceptibility genes were also identified in certain cases. However, the functional validation of pathogenic variants outside of the coding regions remains challenging. As the most direct method, transcriptome analysis could be performed at the same time with molecular autopsy to identify the abnormal expression of SUD susceptibility genes, while the post-mortem degradation of mRNA in myocardial tissues has made it difficult to interpret the transcriptome profiling results. In this study, we performed a retrospective analysis-based prioritization of SUD susceptibility genes based on the distribution of pathogenic genetic variants in previous studies with molecular autopsy findings reported. After gene prioritization, we analyzed the transcriptome data of 432 left ventricle tissues with different sampling time intervals from the Genotype-Tissue Expression database, in order to characterize the degradation pattern of prioritized SUD susceptibility genes. Furthermore, RNA degradation difference between unfrozen and thawed samples was investigated. We demonstrated that with proper segmentation of genes according to their degradation patterns, a partial least squares-discriminant analysis could effectively recognize the expression difference of targeted genes between normal samples and simulated SUD cases. Taken together, our findings presented a strategy for the interpretation of RNA profiling results during the forensic investigation of SUD.

Indexed as

Death, SuddenGenetic Predisposition to DiseaseRNA StabilityTranscriptomeFemaleGene Expression ProfilingHeart VentriclesHumansMaleMyocardiumRetrospective StudiesRNA, MessengerRNA, MessengerMolecular autopsyPost-mortem degradationSudden unexplained deathSupervised clustering analysis.Transcriptome profiling

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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.