Understanding Alzheimer’s disease is like navigating a dense jungle filled with various plants and animals. Apart from the well-known features of the disease, such as amyloid pathology and tau-related neurodegeneration, there are many other molecular alterations and pathway dysregulations that remain poorly understood. These complex interactions and variations between individuals make diagnosis, treatment, and drug design challenging. Thankfully, scientists have developed high-throughput ‘omics’ approaches, which are like multifunctional tools capable of exploring the intricate web of changes happening within the disease. By integrating data from different omics methods, these approaches provide a more comprehensive understanding of the disease’s molecular signatures and interactions at various biological levels. This allows researchers to delve deeper into the underlying mechanisms of Alzheimer’s. In this review, we delve into the different multi-omics tools and approaches available and how they have been used in AD research so far. We explore how these approaches can uncover molecular alterations related to core features of AD and their interplay with other pathological alterations. Furthermore, we investigate whether these discovered changes have clinical relevance, impacting cognition, neuropsychiatric symptoms, and disease progression. Lastly, we highlight the potential for multi-omics approaches to identify novel biomarkers for diagnosis and personalized intervention strategies in Alzheimer’s. Grab your binoculars and venture into the exciting world of multi-omics research to unravel the mysteries of Alzheimer’s!

Beyond the core features of Alzheimer’s disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput “omics” comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.

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