Case report: Mutations in DNAJC30 causing autosomal recessive Leber hereditary optic neuropathy are common amongst Eastern European individuals.

Background: Leber Hereditary Optic Neuropathy (LHON) is the most common inherited mitochondrial disease characterized by bilateral, painless, subacute visual loss with a peak age of onset in the second to third decade. Historically, LHON was thought to be exclusively maternally inherited due to mutations in mitochondrial DNA (mtDNA); however, recent studies have identified an autosomal recessive form of LHON (arLHON) caused by point mutations in the nuclear gene, DNAJC30. Case Presentations: In this study, we report the cases of three Eastern European individuals presenting with bilateral painless visual loss, one of whom was also exhibiting motor symptoms. After a several-year-long diagnostic journey, all three patients were found to carry the homozygous c.152A>G (p.Tyr51Cys) mutation in DNAJC30. This has been identified as the most common arLHON pathogenic variant and has been shown to exhibit a significant founder effect amongst Eastern European individuals. Conclusion: This finding adds to the growing cohort of patients with arLHON and demonstrates the importance of DNAJC30 screening in patients with molecularly undiagnosed LHON, particularly in Eastern European individuals. It is of heightened translational significance as patients diagnosed with arLHON exhibit a better prognosis and response to therapeutic treatment with the co-enzyme Q10 analog idebenone.

Evaluation of the MACE force field architecture: From medicinal chemistry to materials science.

The MACE architecture represents the state of the art in the field of machine learning force fields for a variety of in-domain, extrapolation, and low-data regime tasks. In this paper, we further evaluate MACE by fitting models for published benchmark datasets. We show that MACE generally outperforms alternatives for a wide range of systems, from amorphous carbon, universal materials modeling, and general small molecule organic chemistry to large molecules and liquid water. We demonstrate the capabilities of the model on tasks ranging from constrained geometry optimization to molecular dynamics simulations and find excellent performance across all tested domains. We show that MACE is very data efficient and can reproduce experimental molecular vibrational spectra when trained on as few as 50 randomly selected reference configurations. We further demonstrate that the strictly local atom-centered model is sufficient for such tasks even in the case of large molecules and weakly interacting molecular assemblies.