Multi-omics integration in disease research

Neurodegenerative diseases, marked by complex molecular mechanisms and diverse clinical features, challenge conventional research approaches. This chapter emphasizes the value of multi-omics integration in understanding the biology of Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis (ALS). Genomic studies reveal risk variants such as APOE ε4 in Alzheimer's and rare mutations in familial forms. Transcriptomics highlights gene expression changes, including synaptic dysfunction in early Parkinson's and alternative splicing errors in TARDBP-related ALS. Proteomics identifies key protein aggregates like amyloid beta and alpha-synuclein, along with modifications such as hyperphosphorylated tau that correlate with cognitive decline. Metabolomics uncovers metabolic alterations, including mitochondrial dysfunction in Parkinson's and lipid peroxidation in ALS, which contribute to disease progression. By combining these layers with high-throughput tools like single-cell sequencing, spatial transcriptomics, and mass spectrometry, researchers can reconstruct molecular networks linking genetic risk, gene regulation, protein dysfunction, and metabolic imbalance. This approach enables patient stratification into molecular subtypes, such as neuroinflammatory clusters defined by microglial gene signatures and cytokine expression. Biomarkers from blood and cerebrospinal fluid allow for minimally invasive disease monitoring. Despite challenges such as data heterogeneity and limited standardization, multi-omics approaches support biomarker discovery and therapeutic development. Integrating these datasets with neuroimaging and digital tools enhances diagnostic precision and guides targeted interventions, such as antisense therapies for SOD1-linked ALS. Multi-omics integration is thus a critical foundation for advancing personalized strategies in neurodegenerative disease research.