bims-humivi Biomed News
on Human mito-nuclear genetic interplay
Issue of 2026–08–30
two papers selected by
Mariangela Santorsola, Università di Pavia



  1. Neurol Genet. 2026 Aug;12(4): e200411
       Background and Objectives: Mitochondrial DNA (mtDNA) disorders exhibit striking clinical variability that is poorly explained by known factors such as variant heteroplasmy, age, or sex. Nuclear genetic modifiers likely play a significant role in this heterogeneity. We aimed to characterize the nature of nuclear genetic involvement for 2 common syndromic presentations of the common pathogenic mtDNA variant, m.3243A>G: mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) and maternally inherited diabetes and deafness (MIDD).
    Methods: We assembled a multicenter cohort of clinically ascertained carriers of m.3243A>G (total n = 488), identifying 198 individuals across 76 pedigrees suitable for genetic linkage analysis. We investigated 4 clinical features characteristic of MELAS and MIDD: diabetes, hearing impairment, stroke-like episodes, and encephalopathy. Haseman-Elston regression-based genetic linkage analysis was performed to identify regions of the nuclear genome cosegregating with these features. The effects of m.3243A>G heteroplasmy, age, and sex were accounted for using logistic regression; empirical significance thresholds were determined through feature-specific gene-dropping simulations. Association analyses were performed in 247 individuals using single-variant (SAIGE) and gene-based approaches (SAIGE-GENE+ and MAGMA) to refine candidate loci within a significant linkage region.
    Results: We identified significant genetic linkage to encephalopathy (chromosome 7q22; LOD = 3.72), and regions suggestive of genetic linkage on chromosomes 1, 5, 6, 11, and 13, for encephalopathy and stroke-like episodes. No linkage was identified for diabetes or hearing impairment. Association analysis within the chromosome 7 region identified variant rs62500792 (intergenic between SDHAF3 and TAC1) with the lowest p value (3.7 × 10-5), yet no variants reached the proportional significance threshold (5.3 × 10-6). Gene-based analyses highlighted PLOD3 (p = 3.9 × 10-3) and IMMP2L (p = 6.4 × 10-3) as candidates, as each showed the strongest gene-level signals within the linkage region across complementary burden-testing methods, although neither reached corrected significance thresholds.
    Discussion: The nuclear genetic architecture modifying m.3243A>G differs across clinical features. Severe neurologic features (encephalopathy and stroke-like episodes) may be influenced by a small number of nuclear genes with relatively large effect sizes, whereas the nuclear contribution to diabetes and hearing impairment appears more polygenic. This study highlights the value of large, well-characterized patient cohorts in identifying modifier loci and advancing knowledge of the mechanisms underlying phenotypic variability in mtDNA disease.
    DOI:  https://doi.org/10.1212/NXG.0000000000200411
  2. Curr Issues Mol Biol. 2026 Jul 24. pii: 753. [Epub ahead of print]48(8):
      Increasing evidence shows that epistasis, defined as interactive effects between genetic loci, may contribute to the missing heritability of cancer. However, systematic genome-wide epistasis identification in cancer remains challenging. Here, by leveraging genotype and clinical data from 380,983 samples in the UK Biobank, we identified 202,032 candidate epistatic single nucleotide polymorphism (epiSNP) pairs associated with cancer risk across 16 cancer types. Notably, multivariable Cox regression identified 123 epiSNP pairs with significant interaction effects on overall survival, suggesting that interaction-level genetic signals can provide prognostic information beyond individual SNP effects. Through functional analysis of the 202,032 candidate epiSNP pairs, we identified 7152 pairs supported by gene co-expression data and 12,326 pairs with protein-protein interaction (PPI) evidence. By mapping epiSNP pairs to corresponding gene pairs and then linking these gene pairs to drug-target databases, we identified 1040 epistatic gene pairs with FDA-approved drug-target records. Additionally, through KM survival analysis of the candidate epiSNP pairs, we detected 7068 pairs significantly associated with patient overall survival. Finally, we constructed an open-access database, EpiSNPdb, to facilitate cancer epistasis research.
    Keywords:  database; epistasis; pan-cancer; single nucleotide polymorphism
    DOI:  https://doi.org/10.3390/cimb48080753