ArticleJournal of human genetics2026
Clinical and molecular expansion of SSR4-CDG: an adult patient and pathogenic interpretation of an in-frame variant.
Article in Journal of human genetics, 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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Abstract
Congenital disorders of glycosylation (CDG) comprise a diverse group of inherited metabolic diseases caused by defects in glycan biosynthesis. SSR4-CDG is an ultra-rare X-linked disorder caused by pathogenic variants in SSR4, which encodes a subunit of the translocon-associated protein (TRAP) complex involved in endoplasmic reticulum N-linked glycosylation. To date, only a limited number of patients have been reported, and all previously reported pathogenic variants have been truncating or splice-altering variants. Here, we report two unrelated patients with SSR4-CDG identified by trio-based whole-exome sequencing. Patient 1 carried a de novo nonsense variant and presented with severe intellectual disability and autism spectrum disorder. Notably, he is currently alive at age 56, providing insight into the long-term clinical course of this condition. Patient 2 harbored a maternally inherited in-frame insertion-deletion variant that was initially classified as a variant of uncertain significance. He showed severe developmental delay, failure to thrive, epilepsy, and hyperkinetic movements. Repeat glycan analysis revealed a CDG type I pattern, transcript analysis demonstrated aberrant transcripts with an expanded deletion, and structural modeling suggested destabilization of the β-barrel domain of SSR4, together supporting reclassification as likely pathogenic. These findings expand the clinical and molecular spectrum of SSR4-CDG, including survival into adulthood and diverse neurological manifestations. Our study also illustrates the challenges in interpreting variants associated with subtle biochemical abnormalities and underscores the importance of integrating biochemical, genetic, transcript, and modeling-based structural assessment for accurate diagnosis of rare CDG subtypes.
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