Mitochondrial dysfunction is a key driver of neurological disorders due to the brain’s high energy demands and reliance on mitochondrial homeostasis. Despite advances in genetic characterization, the heterogeneity of mitochondrial diseases complicates diagnosis and treatment. Mitochondrial dysfunction spans a broad clinical spectrum, from early-onset encephalopathies to adult neurodegeneration, with phenotypic and genetic variability necessitating integrated models of mitochondrial neuropathology. Mutations in nuclear or mitochondrial DNA disrupt energy production, induce oxidative stress, impair mitophagy and biogenesis, and lead to neuronal degeneration and apoptosis. This narrative review provides a structured synthesis of current knowledge by classifying mitochondrial-related neurological disorders according to disrupted biochemical pathways, in order to clarify links between genetic mutations, metabolic impairments, and clinical phenotypes. More specifically, a pathway-oriented framework was adopted that organizes disorders based on the primary mitochondrial processes affected: oxidative phosphorylation (OXPHOS), pyruvate metabolism, fatty acid β-oxidation, amino acid metabolism, phospholipid remodeling, multi-system interactions, and neurodegeneration with brain iron accumulation. Genetic, clinical and molecular data were analyzed to elucidate shared and distinct pathophysiological features. A comprehensive table synthesizes genetic causes, inheritance patterns, and neurological manifestations across disorders. This approach offers a conceptual framework that connects molecular findings to clinical practice, supporting more precise diagnostic strategies and the development of targeted therapies. Advances in whole-exome sequencing, pharmacogenomic profiling, mitochondrial gene editing, metabolic reprogramming, and replacement therapy—promise individualized therapeutic approaches, although hurdles including heteroplasmy, tissue specificity, and delivery challenges must be overcome. Ongoing molecular research is essential for translating these advances into improved patient care and quality of life.

Inflammatory and immune-mediated skin diseases are increasingly recognized as disorders in which genetic susceptibility is shaped and sustained by environmentally responsive regulatory programs. Psoriasis, atopic dermatitis (AD), vitiligo, systemic sclerosis (SSc), lupus erythematosus (LE), and lichen planus (LP) are clinically distinct, yet they share chronic or relapsing inflammation, tissue remodeling, and limited durability of many current therapies. Because genetic variation alone cannot fully explain disease onset, flare dynamics, heterogeneity in severity, or lesion recurrence, epigenetic mechanisms have emerged as a plausible link between environmental exposures and stable disease phenotypes in skin. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNA networks, controls cell-type-specific transcription without altering the DNA sequence and may contribute to persistent inflammatory states and disease memory despite clinical improvement. The current review synthesizes primary preclinical and translational evidence on epigenetic-targeted therapeutic strategies across these conditions, focusing on interventions that modulate DNA methylation, histone acetylation and deacetylation, histone methylation, chromatin-associated regulatory proteins, and RNA-based approaches. We compare the maturity of therapeutic development across diseases, noting that research and intervention studies are concentrated in psoriasis and AD, whereas evidence for vitiligo, SSc, LE, and LP remains more limited and often derived from systemic or non-cutaneous models. Finally, we outline key gaps that currently restrict clinical translation and discuss why bridging them is essential for determining whether epigenetic modulation can move beyond proof-of-concept toward durable and clinically actionable interventions in inflammatory skin disease.

Lysosomal storage disorders (LSDs) represent a diverse group of inherited metabolic diseases in which impaired lysosomal function leads to progressive accumulation of undegraded substrates and widespread cellular dysfunction. Although traditionally classified according to the type of stored macromolecule, this substrate-based approach often fails to reflect the underlying molecular mechanisms. Recent advances in genetics and cell biology have prompted a shift toward functional classifications that group disorders by the lysosomal pathway disrupted—namely, enzymatic hydrolytic defects, transporter-related defects, biogenesis and signaling defects, and cross-organelle interaction abnormalities. This framework better captures disease complexity and provides a translational roadmap for precision medicine. The neurological system, with its high metabolic demands and vulnerability to impaired clearance mechanisms, is particularly affected, leading to clinical phenotypes ranging from developmental delay to severe neurodegeneration. Genomic technologies and multi-omics platforms have facilitated earlier diagnoses, revealed atypical variants, and informed the development of tailored therapies such as enzyme replacement, substrate reduction, chaperone-based approaches, and gene therapy. The current review proposes a cellular-pathway-oriented framework for classifying LSDs with neurological features and underscores how such an approach can assist in the development of personalized therapeutic strategies.

In this study, we apply machine learning to model the spatiotemporal dynamics of gene expression during early Drosophila embryogenesis. By optimizing model architecture, feature selection, and spatial grid resolution, we developed a predictive pipeline capable of accurately classifying active nuclei and forecasting their future distribution in time. We evaluated the model on two reporter constructs for the short gastrulation (sog) gene, sogD and sogD_∆Su(H), allowing us to assess its performance across distinct genetic contexts. The model achieved high accuracy on the wild-type sogD dataset, particularly along the dorsal–ventral (DV) axis during nuclear cycle 14 (NC14), and accurately predicted expression in the central regions of both wild-type and Suppressor of Hairless (Su(H)) mutant enhancers, sogD_∆Su(H). Bootstrap analysis confirmed that the model performed better in the central region than at the edges, where prediction accuracy dropped. Our previous work showed that Su(H) can act both as a repressor at the borders and as a stabilizer of transcriptional bursts in the center of the sog expression domain. This dual function is not unique to Su(H); other broadly expressed transcription factors also exhibit context-dependent regulatory roles, functioning as activators in some regions and repressors in others. These results highlight the importance of spatial context in transcriptional regulation and demonstrate the ability of machine learning to capture such nuanced behavior. Looking ahead, incorporating mechanistic features such as transcriptional bursting parameters into predictive models could enable simulations that forecast not just where genes are expressed but also how their dynamics unfold over time. This form of in silico enhancer mutagenesis would make it possible to predict the effects of specific binding site changes on both spatial expression patterns and underlying transcriptional activity, offering a powerful framework for studying cis-regulatory logic and modeling early developmental processes across diverse genetic backgrounds.

Cytoskeletal disorders affecting the nervous system are a diverse group of diseases that display a wide variety of clinical manifestations. Mutations in genes encoding cytoskeletal components disrupt the structural and functional integrity of this complex network, impairing normal development and function of the central and peripheral nervous systems. There are also certain diseases which lead to progressive neurodegeneration, and others which result from an interplay of multiple molecular pathways. This review outlines the primary cytoskeletal disorders affecting the nervous system. To provide a comprehensive overview, these diseases are categorized by their predominantly affected cytoskeletal component—namely microtubules, actin filaments, intermediate filaments, and cytoskeleton-associated proteins. Each category highlights the broader pathophysiological context of the underlying defect rather than an isolated structural disturbance. A deeper understanding of the complex pathophysiology of these disorders may contribute to the discovery of potential therapeutic targets, since current medical management primarily provides symptomatic relief or slows their progression.