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Hinderhofer, K.

Publications and source records attributed to Hinderhofer, K..

2 recordsLinked to original sources

Multi-omics profiling reveals MAGEL2-driven defects in human corticogenesis shared across Prader-Willi and Schaaf-Yang syndromes.

The human cortex acquires its advanced cognitive capacity through tightly regulated developmental programs, disruption of which underlies neurodevelopmental disorders such as Schaaf-Yang syndrome (SYS) and Prader-Willi syndrome (PWS). While SYS results from pathogenic variants in the imprinted gene MAGEL2, PWS arises from chromosomal deletions, imprinting defects or uniparental disomy encompassing the MAGEL2 locus. However, the contribution of MAGEL2 to disease pathogenesis and human corticogenesis is not fully understood. Here, we performed integrated transcriptomic, proteomic, and ubiquitinomic profiling of cortical neurons derived from CRISPR/Cas9-engineered isogenic human pluripotent stem cells (hiPSC) modeling SYS and PWS. Beyond PWS-specific signatures including dysregulated ribosomal processes, we identified MAGEL2-dependent defects shared across both disorders. These include reduced progenitor proliferation, accelerated neuronal maturation, impaired migration and adhesion, as well as abnormal synaptic development, collectively linking PWS and SYS at the level of cortical development. Notably, these phenotypes partially overlap with those observed in other neurodevelopmental disorders, suggesting that MAGEL2 governs core pathways broadly vulnerable in disease. Together, our findings establish MAGEL2 as a key regulator of human cortical development, provide a unifying mechanistic framework for SYS and PWS, accessible via a web-based platform.

neuroscience↗

Identification and prioritisation of causal variants in human genetic disorders from exome or whole genome sequencing data

With genome sequencing entering the clinics as diagnostic tool to study genetic disorders, there is an increasing need for bioinformatics solutions that enable precise causal variant identification in a timely manner.\n\nBackgroundWorkflows for the identification of candidate disease-causing variants perform usually the following tasks: i) identification of variants; ii) filtering of variants to remove polymorphisms and technical artifacts; and iii) prioritization of the remaining variants to provide a small set of candidates for further analysis.\n\nMethodsHere, we present a pipeline designed to identify variants and prioritize the variants and genes from trio sequencing or pedigree-based sequencing data into different tiers.\n\nResultsWe show how this pipeline was applied in a study of patients with neurodevelopmental disorders of unknown cause, where it helped to identify the causal variants in more than 35% of the cases.\n\nConclusionsClassification and prioritization of variants into different tiers helps to select a small set of variants for downstream analysis.

bioinformatics↗