Alzheimer’s disease (AD), the most common form of dementia, is recognized as a heterogeneous disease with diverse pathophysiologic mechanisms. In this study, researchers from the Icahn School of Medicine at Mount Sinai interrogate the molecular heterogeneity of AD by analyzing 1543 transcriptomes across five brain regions in two AD cohorts using an integrative network approach. They identify three major molecular subtypes of AD corresponding to different combinations of multiple dysregulated pathways, such as susceptibility to tau-mediated neurodegeneration, amyloid-β neuroinflammation, synaptic signaling, immune activity, mitochondria organization, and myelination. Multiscale network analysis reveals subtype-specific drivers such as GABRB2, LRP10, MSN, PLP1, and ATP6V1A. The researchers further demonstrate that variations between existing AD mouse models recapitulate a certain degree of subtype heterogeneity, which may partially explain why a vast majority of drugs that succeeded in specific mouse models do not align with generalized human trials across all AD subtypes. Therefore, subtyping patients with AD is a critical step toward precision medicine for this devastating disease.
(A and B) WSCNA clustering dendrogram and topological overlap matrix (TOM) heatmap, showing three major classes (A, B, and C) and five subtypes annotated as A, B1, B2, C1, and C2, corresponding to the yellow, red, blue, turquoise, and orange clusters, respectively. (C) Number of samples in each subtype, control (CDR = 0) and mild cognitive impairment (MCI) (CDR = 0.5). (D) Gene expression profiles of all the samples in the PHG from the MSBB-AD cohort. The samples on the columns are grouped by subtype, and the genes on the rows are grouped by WINA module. FC, fold change. (E) Change in mean expression level of various gene pathways for each AD subtype in comparison with the normal control samples. AD-related pathways, representing differential expression from previous AD studies, are derived from the MSigDB. Sets are grouped by major area of biological activity.