aiHumanoid Simulations Uncover Dominant-Negative Effects in HNRNPH2-Related Neurodevelopmental Disorders

HNRNPH2-related neurodevelopmental disorders (NDDs) encompass a spectrum of cognitive, motor, and systemic impairments driven by mutations in the HNRNPH2 gene. While these disorders have been linked to both gain-of-function (GOF) and loss-of-function (LOF) mutations, the precise mechanisms underlying their varied phenotypic features remain unclear. In this study, we employed advanced aiHumanoid simulations to conduct a virtual longitudinal analysis of HNRNPH2 mutations, spanning from birth through young adulthood. Our findings reveal that LOF mutations, particularly severe missense, and nonsense/frameshift mutations, exert dominant-negative effects that significantly impair neurodevelopmental outcomes. Through detailed comparison of mild versus severe mutations, we observed that severe LOF mutations lead to markedly worse cognitive, motor, and systemic deficits. These effects are compounded by the interference of mutant HNRNPH2 with the function of wild-type HNRNPH2 and potentially compensatory proteins such as HNRNPH1. Notably, our simulations indicate that the upregulation of HNRNPH1 observed in knockout models fails to compensate in the presence of dominant-negative mutations, highlighting a critical pathway disruption. This study not only elucidates the mechanistic basis of dominant-negative effects in HNRNPH2-related NDDs but also suggests new therapeutic avenues, including the enhancement of compensatory mechanisms and targeted inhibition of mutant HNRNPH2. The use of aiHumanoid simulations offers a powerful tool for predicting long-term outcomes and testing potential interventions, providing a robust platform for advancing the understanding and treatment of HNRNPH2-NDDs. Our findings underscore the importance of early diagnosis and intervention, particularly for patients with severe LOF mutations, and facilitate future research focused on mitigating the dominant-negative effects of these mutations.