Calame, DG;
Wong, JH;
Panda, P;
Nguyen, DT;
Leong, NCP;
Sangermano, R;
Patankar, SG;
... Nguyen, LN; + view all
(2025)
Biallelic variation in the choline and ethanolamine transporter FLVCR1 underlies a severe developmental disorder spectrum.
Genetics in Medicine
, 27
(1)
, Article 101273. 10.1016/j.gim.2024.101273.
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Efthymiou_FLVCR1 R1 6-20-24 clean copy.pdf Access restricted to UCL open access staff until 7 January 2026. Download (466kB) |
Abstract
Purpose: FLVCR1 encodes a solute carrier protein implicated in heme, choline, and ethanolamine transport. Although Flvcr1−/− mice exhibit skeletal malformations and defective erythropoiesis reminiscent of Diamond-Blackfan anemia (DBA), biallelic FLVCR1 variants in humans have previously only been linked to childhood or adult-onset ataxia, sensory neuropathy, and retinitis pigmentosa. Methods: We identified individuals with undiagnosed neurodevelopmental disorders and biallelic FLVCR1 variants through international data sharing and characterized the functional consequences of their FLVCR1 variants. Results: We ascertained 30 patients from 23 unrelated families with biallelic FLVCR1 variants and characterized a novel FLVCR1-related phenotype: severe developmental disorders with profound developmental delay, microcephaly (z-score −2.5 to −10.5), brain malformations, epilepsy, spasticity, and premature death. Brain malformations ranged from mild brain volume reduction to hydranencephaly. Severely affected patients share traits, including macrocytic anemia and skeletal malformations, with Flvcr1−/− mice and DBA. FLVCR1 variants significantly reduce choline and ethanolamine transport and/or disrupt mRNA splicing. Conclusion: These data demonstrate a broad FLVCR1-related phenotypic spectrum ranging from severe multiorgan developmental disorders resembling DBA to adult-onset neurodegeneration. Our study expands our understanding of Mendelian choline and ethanolamine disorders and illustrates the importance of anticipating a wide phenotypic spectrum for known disease genes and incorporating model organism data into genome analysis to maximize genetic testing yield.
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