This review focuses on the transition from single-omics to integrative multi-omics analysis, which helps overcome the constraints of individual omics strategies and provides a more systematic understanding of PD pathogenesis.
Abstract
Parkinson’s Disease (PD) is a common neurodegenerative disorder that has been widely investigated using omics approaches over 2020–2025. This review focuses on the transition from single-omics to integrative multi-omics analysis, which helps overcome the constraints of individual omics strategies and provides a more systematic understanding of PD pathogenesis. Key topics include the elucidation of core mechanisms (mitochondrial dysfunction, lipid metabolic disturbance, α-synucleinopathy, and gut–brain axis impairment), the development of biomarkers (shifting from invasive cerebrospinal fluid samples to less invasive plasma/urine panels with improved performance), and the identification of potential interventional targets (signaling pathways, key molecules, and gut microbiota). Technical advances include refined single-omics detection, AI-assisted multi-omics integration, and the emergence of multi-center large cohorts. Despite notable progress, major challenges remain, including limited sample diversity, insufficient technical standardization, and gaps between basic research and clinical translation. Future directions should prioritize the establishment of multi-center longitudinal biobanks, high-sensitivity detection methods, and clinical translation through precision subtyping and targeted intervention. Integrative multi-omics has significantly advanced PD research from fragmented studies to a more systematic framework, providing a foundation for early diagnosis and precision therapy. Further efforts are needed to address current limitations and translate findings into clinical benefit for PD patients.
BACKGROUND
Parkinson's disease (PD) is a rapidly growing global health concern, with aging populations driving increasing prevalence. While neuronal degeneration is a hallmark, emerging evidence implicates chronic neuroinflammation as a key contributor to disease progression. Despite its recognized importance, the cellular sources, functional heterogeneity, and actionable mechanisms of inflammation in the human substantia nigra remain poorly understood, limiting the development of precise diagnostic biomarkers and therapeutic interventions.
METHODS
We integrated single-nucleus RNA sequencing (snRNA-seq) from postmortem substantia nigra with bulk transcriptomic datasets (GSE133101, GSE7621) across multiple cohorts. Using Harmony-based batch correction, cell-type annotation, microglia-specific re-clustering (resolution = 0.1), pseudotime trajectory inference, weighted gene co-expression network analysis (WGCNA), and machine learning, we mapped the neuroinflammatory landscape of PD at single-cell resolution. Diagnostic performance was assessed via receiver operating characteristic (ROC) curve analysis (AUC >0.7), and druggable targets were prioritized through molecular docking and 100-ns molecular dynamics (MD) simulations.
RESULTS
Microglia emerged as the principal immune driver of PD-associated inflammation. Six transcriptionally distinct microglial subpopulations were identified, with Micro1 enriched for antigen presentation, complement activation, and early pseudotime states. An 8-gene microglia-preferential signature (HSPA6, SERPINH1, CHORDC1, P4HA1, HSPH1, IER5, SLC38A2, and FKBP4), associated with ER stress, protein folding, and immune activation, achieved robust diagnostic performance (AUC >0.9) across cohorts. Gene set enrichment analysis revealed convergence on proteostasis and innate immune pathways, and pan-cellular activation patterns indicated a systemic, non-cell-autonomous inflammatory environment. MD simulations confirmed the structural stability of the FKBP4-SAR260301 complex, highlighting its therapeutic potential.
CONCLUSIONS
By indicating microglial functional heterogeneity and defining a validated, biologically grounded diagnostic signature, this study advances the mechanistic understanding of PD neuroinflammation. This study transforms neuroinflammation from a correlative hallmark to a mechanistically actionable axis, providing an urgently needed roadmap for inflammation-informed precision medicine in PD.
Lei Yang, Lu Wang, Jiaxing Guo et al.· Parkinsonism & Related Disor...· 0 citations
Background: Parkinson’s disease (PD) is the fastest-growing neurological disorder globally. Traditional diagnosis, which relies on motor symptoms, is associated with a 15–24% error rate and occurs after significant loss of dopaminergic neurons. Early biomarker identification is essential for biological redefinition of PD and timely intervention.Objective: To synthesize evidence from the past five years on minimally invasive biomarkers and assess whether multimodal panels offer greater diagnostic precision than single tests.Methods: A systematic review of PubMed and Scopus (January 2021–January 2026) was conducted per PRISMA guidelines, including meta-analyses and original studies on α-synuclein seed amplification assays (SAA), neuronally derived extracellular vesicles (LIEVs), neurofilament light chain (NfL), and advanced imaging (OCT-A, MRI).Results: SAA exhibited 96% sensitivity in GBA1 mutation carriers and 98.6% in hyposmic individuals with dopaminergic deficits, but only 67.5% in LRRK2 carriers. Serum LIEV-associated α-synuclein distinguished prodromal cases with high precision (AUC=0.91). NfL predicted functional decline (OR=2.54) up to five years before diagnosis. Advanced neuroimaging and skin RT-QuIC tests showed diagnostic accuracies from 82% to 100%.Conclusion: PD diagnosis is shifting from clinical observation to biological profiling. Multimodal biomarker panels integrating molecular, microvascular, and imaging data provide the most precise risk stratification, enabling timely, targeted neuroprotective interventions by rehabilitation specialists.
Aliaksandr Kryshtofik, J. Grygorowicz, Gabriela Faria et al.· Quality in Sport· 0 citations
Atherosclerosis is a leading global cause of disability and mortality, with a rising trend of early onset across populations. Its pathogenesis is multifactorial, encompassing multiple interconnected pathways including dyslipidemia, inflammation, and immune dysregulation. Current therapeutic strategies targeting lipoproteins are insufficient to address disease progression, and there remains an urgent unmet clinical need to further elucidate its pathogenic mechanisms, refine diagnostic approaches, and identify novel therapeutic targets. In recent years, the vigorous development of omics technology has provided help for in-depth investigation of the pathogenesis of diseases and search for new diagnosis and treatment targets. The application of multi-omics analysis has elevated atherosclerotic research to a new tier, yielding high-quality findings that further unravel atherogenic molecular mechanisms. These findings provide critical theoretical and translational groundwork for developing novel diagnostics, targeted therapies, and robust early risk stratification tools. In this review, we summarize integrated multi-omics applications in atherosclerosis, and outline novel perspectives for prospective therapeutic strategies.
The urgent need for reliable biomarkers, early diagnosis, and multidisciplinary disease-modifying strategies for future therapeutic interventions is highlighted, with particular emphasis on challenges associated with bench-to-bedside translation.
Jeewanjot Singh, Subhi Sharma, Prabhjot Singh et al.· Advances in Modern Biomedici...· 0 citations