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Biallelic ABCA13 Loss-of-Function Variants in a Child With Neurodevelopmental Delay: A Case Report.

ABCA13 encodes ATP-binding cassette subfamily A member 13, one of the largest members of the ABC transporter family. Rare ABCA13 variants have been reported in neuropsychiatric and neurodevelopmental phenotypes, including schizophrenia, bipolar disorder, autism spectrum disorder, intellectual disability, and developmental delay; however, the mode of inheritance remains uncertain, and most published cases have focused on heterozygous variants in the context of a possible dominant or susceptibility model. We report a 5-year-old boy with neurodevelopmental delay, skeletal foot deformities, nonspecific dysmorphic features, convergent strabismus, and behavioral abnormalities. Initial genome sequencing analysis was nondiagnostic. Reanalysis after 6 months identified two rare predicted loss-of-function variants in ABCA13 in trans: c.2510del, p.(Leu837TyrfsTer21), a frameshift variant, and c.12064C>T, p.(Arg4022Ter), a nonsense variant previously reported in a patient with unexplained intellectual disability. The identification of compound heterozygous predicted loss-of-function variants supports the possibility that biallelic disruption of ABCA13 may contribute to neurodevelopmental disease, whereas previously reported heterozygous variants may represent incompletely penetrant risk alleles, susceptibility factors, or candidate findings rather than fully penetrant dominant causes. This case expands the emerging clinical and genetic spectrum associated with ABCA13 and supports further evaluation of a recessive model in patients with intellectual disability and neurodevelopmental delay.

ABCA13

Integrating machine learning and GWAS for variant prioritization in the INCIPE cohort highlights ABC transporter genes in chronic kidney disease.

INTRODUCTION: Chronic kidney disease (CKD) is a major public health challenge, affecting approximately 674 million people worldwide and representing one of the fastest-growing causes of mortality. Since CKD is frequently asymptomatic in its early stages, the identification of novel genetic biomarkers may improve early detection and risk stratification. Genome-Wide Association Studies (GWAS) have identified numerous genetic loci associated with CKD and related traits; however, their performance is often limited in small and imbalanced cohorts, where reduced statistical power increases both false-positive and false-negative findings. Machine learning (ML) approaches can complement conventional GWAS by prioritizing biologically relevant genetic signals from high-dimensional genomic data. METHODS: In this study, we implemented a nested ensemble (NCBC) model composed of an undersampler and a CatBoostClassifier (CBC) to prioritize candidate genetic variants associated with CKD in the INCIPE cohort. Prioritized variants were functionally annotated and evaluated through enrichment analyses, GTEx gene expression profiling, and protein-protein interaction network analyses. Genes identified by the CKDGen Consortium were analysed as an external reference set and used to validate the biological relevance of the prioritized results. RESULTS: The NCBC model outperformed conventional ML classifiers, achieving a ROC AUC score of 87.77%, compared to 50%-53% for the other evaluated models. Among the prioritized genes, 56.25% showed protein-protein interactions with genes previously reported by the CKDGen Consortium, whereas only 1.9% of randomly generated gene sets showed interactions. DISCUSSION: Our study demonstrates that the NCBC model improves the prioritization of biologically plausible candidate variants in a small and imbalanced CKD cohort. Functional analyses suggested ABC transporter-related genes, including ABCA13, ABCA4, and ABCC4 genes, as promising candidate for future validation, with ABCA4 showing substantial expression in kidney tissues. Overall, these findings support the integration of ML with GWAS to prioritize candidate genes and investigate the genetic architecture of complex diseases.

SNP prioritization