Why not try to predict autism spectrum disorder with crucial biomarkers in cuproptosis signaling pathway?

Mitochondrial pathways of copper neurotoxicity: focus on mitochondrial dynamics and mitophagy

Copper (Cu) is essential for brain development and function, yet its overload induces neuronal damage and contributes to neurodegeneration and other neurological disorders. Multiple studies demonstrated that Cu neurotoxicity is associated with mitochondrial dysfunction, routinely assessed by reduction of mitochondrial membrane potential. Nonetheless, the role of alterations of mitochondrial dynamics in brain mitochondrial dysfunction induced by Cu exposure is still debatable. Therefore, the objective of the present narrative review was to discuss the role of mitochondrial dysfunction in Cu-induced neurotoxicity with special emphasis on its influence on brain mitochondrial fusion and fission, as well as mitochondrial clearance by mitophagy. Existing data demonstrate that, in addition to mitochondrial electron transport chain inhibition, membrane damage, and mitochondrial reactive oxygen species (ROS) overproduction, Cu overexposure inhibits mitochondrial fusion by down-regulation of Opa1, Mfn1, and Mfn2 expression, while promoting mitochondrial fission through up-regulation of Drp1. It has been also demonstrated that Cu exposure induces PINK1/Parkin-dependent mitophagy in brain cells, that is considered a compensatory response to Cu-induced mitochondrial dysfunction. However, long-term high-dose Cu exposure impairs mitophagy, resulting in accumulation of dysfunctional mitochondria. Cu-induced inhibition of mitochondrial biogenesis due to down-regulation of PGC-1α further aggravates mitochondrial dysfunction in brain. Studies from non-brain cells corroborate these findings, also offering additional evidence that dysregulation of mitochondrial dynamics and mitophagy may be involved in Cu-induced damage in brain. Finally, Cu exposure induces cuproptosis in brain cells due mitochondrial proteotoxic stress, that may also contribute to neuronal damage and pathogenesis of certain brain diseases. Based on these findings, it is assumed that development of mitoprotective agents, specifically targeting mechanisms of mitochondrial quality control, would be useful for prevention of neurotoxic effects of Cu overload.

Identification of Immune Infiltration and Iron Metabolism-Related Subgroups in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with a broad spectrum of symptoms and prognoses. Effective therapy requires understanding this variability. ASD children's cognitive and immunological development may depend on iron homoeostasis. This study employs a machine learning model that focuses on iron metabolism hub genes to identify ASD subgroups and describe immune infiltration patterns. A total of 97 control and 148 ASD samples were obtained from the GEO database. Differentially expressed genes (DEGs) and an iron metabolism gene collection achieved the intersection of 25 genes. Unsupervised cluster analysis determined molecular subgroups in individuals with ASD based on 25 genes related to iron metabolism. We assessed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, gene set variation analysis (GSVA), and immune infiltration analysis to compare iron metabolism subtype effects. We employed machine learning to identify subtype-predicting hub genes and utilized both training and validation sets to assess gene subtype prediction accuracy. ASD can be classified into two iron-metabolizing molecular clusters. Metabolic enrichment pathways differed between clusters. Immune infiltration showed that clusters differed immunologically. Cluster 2 had better immunological scores and more immune cells, indicating a stronger immune response. Machine learning screening identified SELENBP1 and CAND1 as important genes in ASD's iron metabolism signaling pathway. These genes express in the brain and have AUC values over 0.8, implying significant predictive power. The present study introduces iron metabolism signaling pathway indicators to predict ASD subtypes. ASD is linked to immune cell infiltration and iron metabolism disorders.