Evidence map›Paper›PMID 42723774›Full record

ArticleFrontiers in immunology2026

Integrated multi-omics identification of m6A-SNP-related diagnostic biomarkers in amyotrophic lateral sclerosis.

Hongfen Wang, Bo Sun, Shiya Wang, Jing Pan, Rongrong Du, Xinyuan Pang, Jiongming Bai, Jinming Han, Jinli Feng

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Article in Frontiers in immunology, 2026. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Hongfen Wang *Senior Department of Neurology, Chinese People's Liberation Army General Hospital, Beijing, China.
Bo Sun *Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Shiya WangOutpatient Department of Zhantansi, Jingzhong Medical Zone, Chinese People's Liberation Army General Hospital, Beijing, China.
Jing PanDepartment of Respiratory and Critical Care Medicine, Second Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
Rongrong DuSenior Department of Neurology, Chinese People's Liberation Army General Hospital, Beijing, China.
Xinyuan PangSenior Department of Neurology, Chinese People's Liberation Army General Hospital, Beijing, China.
Jiongming BaiSenior Department of Neurology, Chinese People's Liberation Army General Hospital, Beijing, China.
Jinming HanDepartment of Neurology, Xuanwu Hospital, Beijing, China.
Jinli FengSenior Department of Neurology, Chinese People's Liberation Army General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Amyotrophic lateral sclerosis (ALS) lacks reliable and minimally invasive biomarkers for early diagnosis. m6A-associated single-nucleotide polymorphisms (m6A-SNPs) may influence RNA methylation and gene expression, offering opportunities to identify clinically relevant diagnostic markers. Methods: We integrated eQTLGen cis-eQTL data, RMVar m6A-SNP annotations, and ALS transcriptomic datasets to identify m6A-SNP-related genes. Random Forest and LASSO regression were combined to screen robust diagnostic markers. A nomogram was constructed and validated using independent cohorts. Immune infiltration, predicted m6A modification sites, and potential RBP-SNP interactions were assessed. Peripheral blood samples from ALS patients were used for exploratory validation of gene expression and global m6A levels. Results: We identified 109 ALS-associated m6A-SNP-related genes with cis-eQTL signals and narrowed these to seven candidate diagnostic markers (TMED5, OXR1, BRI3, FEM1C, SUZ12, EIF2AK4, and TJAP1). The seven-gene model outperformed the individual markers in the training cohort and retained moderate discrimination in the independent validation cohort. ALS samples showed differences in inferred immune-cell composition, including monocytes, neutrophils, and T-cell subsets. The selected SNP loci were located near predicted m6A sites and annotated RBP-binding regions. Exploratory clinical validation showed significant upregulation of FEM1C and SUZ12 at both mRNA and protein levels, accompanied by reduced global m6A modification. Conclusions: Through multi-omics integration and exploratory clinical validation, this study identifies m6A-SNP-related candidate markers associated with ALS. The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.

Indexed as

AdenosineAmyotrophic Lateral SclerosisPolymorphism, Single NucleotideBiomarkersEpitranscriptomeGene Expression ProfilingGenetic Predisposition to DiseaseHumansMultiomicsQuantitative Trait LociRNA MethylationAdenosineBiomarkersamyotrophic lateral sclerosisbiomarkersm6A-SNPmulti-omicsN6-methyladenosine

Identifiers

PMID42723774
PMCPMC13557987

What Socratic holds

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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 Socratic graph.