Summary: Using large-scale RNA sequencing, researchers have delineated three distinct molecular subtypes of Alzheimer’s disease.
Source: Mount Sinai Hospital
Researchers at the Icahn School of Medicine at Mount Sinai have identified three major molecular subtypes of Alzheimer’s disease (AD) by analyzing RNA sequencing data. The findings clarify biological differences between groups of patients and could guide the development of more precise, targeted therapies.
This work was funded by the National Institute on Aging, part of the National Institutes of Health (NIH), and was published in Science Advances on January 6, 2021.
RNA is a genetic molecule that carries instructions for protein synthesis. RNA sequencing (RNA-seq) measures the types and quantities of RNA in a tissue sample, such as a brain region, and reveals which genes are active or dysregulated in disease.
Alzheimer’s disease is the most common cause of dementia, but it is biologically heterogeneous: patients vary widely in symptoms, rate of decline, and underlying pathology. Some individuals experience slow cognitive decline while others progress rapidly; some primarily lose recent memory while others show different cognitive impairments; some develop psychiatric symptoms such as psychosis or depression, and others do not. These clinical differences suggest that multiple molecular forms of AD exist, each driven by distinct biological processes.
“Such differences strongly suggest there are subtypes of AD with different biological and molecular factors driving disease progression,” said Bin Zhang, PhD, the study’s lead author, Director of the Center for Transformative Disease Modeling, and Professor of Genetics and Genomic Sciences at the Icahn School of Medicine.
To define these molecular subtypes, the team applied computational network analysis to integrate RNA-seq data with clinical and neuropathological measures across brain regions. They examined 1,543 transcriptomes from five brain regions in hundreds of deceased individuals with AD and in control samples. From this large dataset they identified three robust molecular subtypes that were reproducible across brain regions and across independent cohorts. These subtypes were independent of patient age and overall disease stage.
Each subtype corresponds to a characteristic combination of dysregulated pathways that lead to neurodegeneration. Key processes that varied across subtypes included susceptibility to tau-mediated neuronal damage, amyloid-beta–related inflammation, disruptions in synaptic signaling, immune system activation, mitochondrial organization, and myelination. Notably, classic neuropathological hallmarks—tau neurofibrillary tangles and amyloid-beta plaques—were prominent in some subtypes but not others, underscoring that the same pathological markers are not uniformly elevated across all AD cases.
While recent research has linked excessive immune response and neuroinflammation to Alzheimer’s, the new analysis showed that more than half of AD brains did not exhibit heightened immune activity compared with healthy brains. The study further identified subtype-specific molecular drivers—genes that appear to play a central role in each subtype’s pathology. Examples highlighted by the investigators include GABRB2, LRP10, MSN, PLP1, and ATP6V1A, each pointing to different mechanistic routes toward degeneration.
The researchers also compared these human molecular subtypes to commonly used AD animal models. They found that existing mouse models recapitulate aspects of particular human subtypes, but no single model captures all forms of the disease. This mismatch may help explain why many therapies that performed well in mice did not translate into broad success in clinical trials: animal studies and human trials may have been targeting different molecular subtypes or processes.
Although the subtyping was performed on postmortem brain tissue, the investigators emphasize that if future studies validate these subtypes, it should be possible to identify biomarkers and clinical features in living patients that correspond to each molecular subtype. Such biomarkers could enable earlier and more accurate diagnosis, subtype-specific monitoring, and targeted treatment selection.
“Our systematic identification and characterization of robust molecular subtypes of AD reveal many new signaling pathways that are dysregulated and pinpoint potential therapeutic targets,” said Dr. Zhang. “These results provide a foundation for developing better biomarkers for early prediction, studying causal mechanisms, and designing next-generation therapeutics and targeted clinical trials. Ultimately, this work advances the goal of precision medicine for Alzheimer’s disease. Remaining challenges include replication in larger cohorts, validation of subtype-specific targets and mechanisms, and discovery of peripheral biomarkers and clinical signatures linked to these molecular subtypes.”
This AD subtyping study is supported by the NIH National Institute on Aging and is part of the NIA-led Accelerating Medicines Partnership – Alzheimer’s Disease (AMP-AD) Target Discovery and Preclinical Validation program. That public–private partnership aims to shorten the time between discovery of candidate drug targets and development of new therapies for Alzheimer’s disease.
About this Alzheimer’s disease research news
Source: Mount Sinai Hospital
Contact: Lucia Lee – Mount Sinai Hospital
Image: The image is in the public domain
Original Research: Open access. “Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets” by Bin Zhang et al. Science Advances
Abstract
Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets
Alzheimer’s disease (AD) is a heterogeneous disorder with diverse pathophysiologic mechanisms. In this study, the authors analyzed 1,543 transcriptomes across five brain regions in two AD cohorts using an integrative network approach. They identified three major molecular subtypes of AD, each corresponding to different combinations of dysregulated pathways such as susceptibility to tau-mediated neurodegeneration, amyloid‑β–related neuroinflammation, synaptic signaling deficits, immune activity differences, mitochondrial organization changes, and altered myelination. Multiscale network analysis revealed subtype-specific driver genes including GABRB2, LRP10, MSN, PLP1, and ATP6V1A. The work also shows that variations among existing AD mouse models reflect aspects of this molecular heterogeneity, which may contribute to translational gaps between preclinical successes and human clinical trial outcomes. These findings emphasize that patient subtyping is a critical step toward precision medicine in Alzheimer’s disease.