New Research Identifies Three Different Subtypes of Alzheimer’s Disease

New Research Identifies Three Different Subtypes of Alzheimer’s Disease

New research into Alzheimer’s Disease suggests the disease is more diverse than previously thought and consists of at least three different subtypes, each of which presents differently in the brain.

The diversity of the disease may explain why it has been so challenging to find an effective treatment and why most drugs that have proved promising in mouse models do not align with generalized human trials, as they are not effective against all subtypes of the disease. Current mouse models for Alzheimer’s Disease only match a particular subset of Alzheimer’s Disease, but not all subtypes.

Alzheimer’s Disease is the most common form of dementia in the elderly. The disease affects around 50 million people worldwide and almost half of individuals over the age of 75. Alzheimer’s Disease involves progressive neurological decline and typically causes memory loss and cognitive dysfunction.

Alzheimer’s Disease patients typically have an accumulation of amyloid-beta (Aβ) peptide as extracellular plaques and hyperphosphorylated tau as intracellular neurofibrillary tangles (NFTs). The accumulation of Aβ and tau proteins are believed to trigger neuronal and synaptic loss in the cerebral cortex and hippocampus, and inflammation and degradation of the myelin that coats and protects nerve cells, resulting in the loss of brain function.

However, over the past few years, evidence has been growing that suggests Alzheimer’s Disease is a heterogeneous disease. New research also indicates these common pathophysiologic mechanisms may not be an early trigger of Alzheimer’s Disease in all patients.

For instance, around one third of patients diagnosed with Alzheimer’s Disease do not have an accumulation of Aβ and many individuals diagnosed with Alzheimer’s Disease show no cognitive impairment at postmortem biopsy. These findings suggest that there are multiple subtypes of Alzheimer’s Disease.

To explore these different subtypes, a team of researchers analyzed 1543 transcriptomes across five brain regions in two Alzheimer’s Disease cohorts and used RNA sequencing to profile the transcriptomes. The researchers identified three different molecular subtypes of Alzheimer’s Disease that correspond to different dysregulated pathways, such as amyloid-β neuroinflammation; susceptibility to tau-mediated neurodegeneration; amyloid-β neuroinflammation; synaptic signaling; immune activity; myelination; and mitochondria organization.

The different subtypes were not connected to disease severity or the age of the patients, and the molecular signatures were found in all brain regions, especially in the hippocampus which plays an important role in forming memories.

Only around one third of cases involved the Aβ and tau proteins that are typically associated with Alzheimer’s Disease, which suggests that the cognitive impairment experienced by patients is not dependent or fully assured by their accumulation in the brain. In other cases, there were opposite forms of gene regulation within molecules which caused complex changes in brain pathways and cell types. “It is more likely that Aβ and tau accumulation are often mediators or the end effects of neurodegeneration and inflammation, independent of hippocampal load,” explained the researchers.

Since only around a third of patients are likely to have the subtype of Alzheimer’s Disease reflected in mouse models of the disease, the treatments tested on those mouse models are unlikely to work for all patients. For some subtypes, rather than helping to reduce symptoms the drugs may actually exacerbate them. The different subtypes are likely to require specific treatments, so subtyping patients is important to determine whether treatment is likely to be effective and for mouse models to be developed for each of the subtypes to allow drugs to be developed that are specific to each.

You can read more about the study in the paper – Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets – which was recently published in Science Advances. DOI: 10.1126/sciadv.abb5398

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