Tissue-specific expression and regulation of congenital disorders of glycosylation genes: A GTEx-based in silico study.

Authors

Cátia J Neves, António Gomes, Rita A Lourenço, Mariana Barbosa, Ana R Grosso, Paula A Videira

Published in

Molecular genetics and metabolism reports. Volume 48. Pages 101336. Epub Jul 08, 2026.

Abstract

Congenital disorders of glycosylation (CDGs) are rare metabolic diseases characterized by clinical heterogeneity, yet the molecular basis for their tissue-specific manifestations remains poorly understood. Because affected tissues are rarely accessible for biopsy, the baseline transcriptional and regulatory landscape of CDG-causative genes in healthy human tissues offers a valuable, complementary perspective on tissue vulnerability. Here, we performed an in silico study of the expression, allelic regulation, expression quantitative trait loci (eQTLs), and associations with immune cell compositions of 12 CDG-causative genes across healthy human tissues using multi-omics datasets from the Adult GTEx project. The selected panel includes the most prevalent multisystem CDGs (PMM2-, ALG6-, ALG1-, SLC35A2-, ALG13-, SRD5A3-, MAN1B1-, DPAGT1-CDG), three immune-relevant CDGs classified as inborn errors of immunity (MOGS-, PGM3-, VPS13B-CDG), and the autosomal recessive form of GNE-CDG (GNE-CDG (ar); GNE myopathy) as a tissue-restricted contrast. CDG-causative genes were broadly but heterogeneously expressed, with substantial inter-individual variation. Tissues frequently affected in the corresponding disorders did not consistently display the highest baseline gene expression, underscoring that higher gene expression alone is a poor indicator of tissue susceptibility. Allele-specific analyses revealed five distinct allelic expression patterns across individuals and identified tissue-specific deviations from balanced biallelic expression for several genes, most notably SRD5A3, PGM3, VPS13B, and GNE. Tissue-specific eQTLs affecting CDG genes were frequently located in intronic enhancers of unrelated genes or intergenic regions, revealing a complex, predominantly distal regulatory architecture. Several eQTLs overlapped GWAS Catalog traits and ClinVar entries relevant to the corresponding CDG phenotypes, including PMM2 eQTLs associated with reduced PMM2 gene levels. Finally, correlations between CDG-causative gene expression and immune cell composition recapitulated known immune phenotypes from blood and suggested additional tissue-dependent roles for glycosylation in immune modulation, that warrant functional validation. Together, these findings demonstrate that CDG-causative genes operate within diverse transcriptional, allelic, and regulatory contexts across human tissues. Our in silico framework provides an interpretable candidates and foundational reference for interpreting tissue vulnerability in CDG and underscore the need for global analyses to fully understand organ-specific disease mechanisms.

PMID:
42472049
Bibliographic data and abstract were imported from PubMed on 19 Jul 2026.

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