Multi-omics approaches to parkinsonism: genomic, proteomic, and non-coding RNA perspectives
S Anusha1, Sharanappa Gurikar1, S B Kavyashree1
1Department of Pharmacology, Faculty of Pharmacy, Sri Adichunchanagiri College of Pharmacy, Adichunchanagiri University, B. G. Nagara, Mandya, 571448, Karnataka, India.
None:
Parkinson's disease (PD) is a progressive neurodegenerative disorder with significant variability associated with substantial loss of dopaminergic neurons in the substantia nigra. Currently, there are limited opportunities for intervention. There is a lack of reliable biomarkers to identify patients with PD, which poses a challenge for clinicians. In this review, recent advances in PD biomarker research, including genomic, epigenomic, proteomic, and non-coding RNA, will be highlighted, with particular emphasis on integrating omics for precision medicine. In addition, the current understanding of PD pathogenesis will be covered, including the root cause of familial and sporadic PD, as well as other significant contributing pathogenic events such as the formation of α-synuclein aggregates, mitochondrial dysfunction, autophagy, oxidative stress, and neuroinflammation. Recent progress in proteomic biomarkers, including cerebrospinal fluid and blood biomarkers such as α-synuclein, Neurofilament-Light-Chain, and dopamine-associated proteomics, will be reviewed for their utility. Merging evidence on non-coding RNAs, including microRNAs, long non-coding RNAs, circular RNAs, and piRNAs, further supports the notion of non-coding RNAs' regulatory functions in PD pathogenesis and their potential as non-invasive biomarkers. Lastly, strategies that integrate multi-omics data through systems biology, machine learning, and artificial intelligence are presented as viable approaches to support improved patient diagnosis and stratification, as well as the identification of new drug targets for PD. However, challenges related to heterogeneity, reproducibility, and clinical translation continue to limit the implementation of multi-omics biomarkers in PD. Overall, integrative multi-omics approaches combined with advanced computational strategies may provide a more comprehensive framework for early diagnosis, patient stratification, and the development of disease-modifying therapies in PD.
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