Background: Multiple pathophysiological processes have been described in Alzheimer’s disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood, however. We tested the hypothesis that cerebrospinal fluid (CSF) integrative multi-omics analysis highlights novel interacting pathway alterations in AD.Methods: We performed multi-level CSF omics in a well-characterized cohort of older adults including subjects with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analysed applying Elastic-net regression and Multi-Omics Factor Analysis followed by pathway enrichment. Multivariate analysis was used to select best predictive models of AD pathology and cognitive decline.Results: Multi-omics integration identified five major dimensions of heterogenicity explaining the variance within the cohort and differentially associated with AD . Further analysis exposed multiple interactions between single ‘omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response and extracellular matrix signalling pathways in association with AD. Further, combinations of four selected molecules significantly improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1). Conclusions: Applying an integrative multi-omics approach we confirmed previously reported associations with AD pathology and report new molecular and pathways alterations. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.