bims-meglyc 2026-10-18 papers

Issue of 2026–10–18
four papers selected by
Silvia Radenkovic, UMC Utrecht

Mol Genet Metab. 2026 Oct 08. pii: S1096-7192(26)00572-X. [Epub ahead of print]149(3): 110289

A quantitative disorder-phenotype atlas of inherited metabolic disorders reveals shared symptom spaces and group-specific hotspots.

Nenad Blau, Jerry Vockley, Carlos R Ferreira.

BACKGROUND: Inherited metabolic disorders (IMDs) are classified by pathway and gene, but their multisystemic presentation complicates phenotype-first diagnosis.
METHODS: Using a frozen IEMbase export, we analyzed expert-curated disorder-level phenotype annotations for 1737 IMDs across 21 phenotype domains, 24 disorder groups, and 122 subgroups. We quantified annotation frequency, multi-domain burden, and group-domain enrichment using binomial z-scores, with clustering, principal component analysis, and bipartite networks for higher-order structure. Primary analyses were age-independent; age coverage was assessed exploratorily.
RESULTS: Disorders involved a mean of 4.01 ± 2.54 phenotypic categories. Neurologic involvement was annotated in 70.5%, followed by Eye (38.3%) and Other (34.7%). Enrichment identified hotspots, including endocrine metabolic disorders → Endocrine (z ≈ 12.6) and congenital disorders of glycosylation → Dysmorphic/Skeletal (z ≈ 10.3/8.0), with glycosylation and mitochondrial phenotype clouds. Age-specific information was available for 98.7% of disorders in at least one interval, but only 28.9% spanned all five.
CONCLUSIONS: This first-generation knowledgebase-level atlas quantifies reported disorder-level phenotype architecture rather than patient-level prevalence or natural history. It provides a scalable framework for phenotype standardization, diagnostic navigation, targeted curation, and future integration of age, variants, treatment, and real-world evidence.

Keywords: Disease atlas; Enrichment hotspots; ICIMD; IEMbase; Inborn errors of metabolism; Inborn metabolic diseases; Inherited metabolic disorders; Knowledgebase; Landscape; Mendelian disorders; Nosology; Phenotype domains

DOI: https://doi.org/10.1016/j.ymgme.2026.110289

Angew Chem Int Ed Engl. 2026 Oct 15. e1827729

Proximity-Induced Protein Deglycosylation by Endogenous O-GlcNAcase.

Haixing Xu, Bowen Ma, Yunpeng Huang, Jialin Liu, Billy Wai-Lung Ng.

O-GlcNAcylation is an important post-translational modification that regulates numerous cellular processes, yet tools enabling selective removal of O-GlcNAc from individual proteins via endogenous O-GlcNAcase (OGA) in living cells remain limited. Here, we report De-O-GlcNAcylation-targeting chimeras (DOGTACs), a chemically induced proximity strategy that selectively reduces O-GlcNAc from target proteins by recruiting endogenous OGA. Initial designs incorporating potent competitive OGA inhibitors efficiently engaged OGA but failed to induce de-O-GlcNAcylation, revealing that catalytic competence is essential for productive proximity-driven editing. By attenuating inhibitor potency while retaining OGA engagement, we developed optimized DOGTACs that promote concentration- and time-dependent, target-specific de-O-GlcNAcylation in living cells without perturbing global O-GlcNAc levels. Furthermore, we successfully applied DOGTAC to additional target proteins including FKBP12F36V fused proteins and endogenous CK2α across different cell lines. Besides, we found DOGTAC (R)-C4 treatment could reduce the stability of FKBP12F36V fused-NUP98-KDM5A in cells. Collectively, this work established attenuated competitive inhibitors as recruitment modules for catalytic enzyme engagement and a novel strategy, DOGTAC, for targeted de-O-GlcNAcylation via endogenous OGA recruitment in living cells.

Keywords: O‐GlcNAcylation; bifunctional molecules; enzymes; inhibitors; protein modification

DOI: https://doi.org/10.1002/anie.1827729

J Inherit Metab Dis. 2026 Nov;49(6): e70259

Revisiting Inherited Metabolic Diseases (IMDs) Through the Lens of Selective Autophagy.

Marianna Maddaluno, Laura Cinque, Viviana Cetrangolo, Chiara De Leonibus.

Selective autophagy is increasingly recognized as a fundamental quality-control mechanism that complements bulk autophagy by enabling the targeted degradation of specific intracellular cargos, including mitochondria, endoplasmic reticulum (ER), lipid droplets, glycogen, peroxisomes, ferritin, ribosomes, and protein aggregates. Cargo selectivity is mediated by selective autophagy receptors (SARs), which link damaged or superfluous substrates to the autophagic machinery through LC3/GABARAP interactions, thereby coordinating cargo sequestration. Recent studies have revealed substantial mechanistic differences between bulk and selective autophagy, highlighting the specialized signaling pathways, receptor networks, and transcriptional programs that regulate selective cargo clearance. Dysregulation of these pathways has emerged as a key contributor to the pathogenesis of inherited metabolic diseases (IMDs), a heterogeneous group of genetic disorders characterized by defective metabolism and multisystem involvement. This review summarizes the molecular mechanisms underlying major forms of selective autophagy, including mitophagy, pexophagy, glycophagy, lipophagy, ER-phagy, and ferritinophagy. It also discusses their relevance across IMD classes, such as mitochondrial disorders, lysosomal storage disorders, and peroxisomal diseases, among many others. Furthermore, selective autophagy is highlighted as a potential therapeutic target, with modulation of autophagy receptors and signaling pathways offering promising strategies to restore cellular homeostasis and improve disease manifestations in IMDs.

Keywords: bulk autophagy; inherited metabolic diseases (IMDs); selective autophagy; selective autophagy cargos (SACs); selective autophagy receptors (SARs)

DOI: https://doi.org/10.1002/jimd.70259