An integration of large-scale datasets across species and methods by a team of researchers from MIT and Harvard Medical School has identified potential new drug targets for Alzheimer’s disease (AD) that look to address other aspects of the disease beyond the most prevalent focus on amyloid plaques. The findings, published in Nature Communications, come as researchers and drug developers increasingly are looking for alternatives to amyloid plaque-targeting drugs which, thus far, have shown limited effects in slowing the cognitive decline in AD patients.

“All the evidence that we have indicates that there are many different pathways involved in the progression of Alzheimer’s. It is multifactorial, and that may be why it’s been so hard to develop effective drugs,” said senior author Ernest Fraenkel, PhD, a professor in health sciences and technology at MIT. “We will need some kind of combination of treatments that hit different parts of this disease.”

Current Alzheimer’s drugs such as aducanumab and lecanemab, were developed to target amyloid beta plaques in the brain, the hallmark feature of AD pathology. But their limited efficacy has led to a growing recognition that amyloid plaques may be only one part of a more complex disease process. “One possibility is that maybe there’s more than one cause of Alzheimer’s, and that even in a single person, there could be multiple contributing factors,” Fraenkel said. “So, even if the amyloid hypothesis is correct… you need to know what those other factors are.”

For this new study, researchers in the Fraenkel lab conducted a large-scale, unbiased genetic screen in fruit flies to identify genes that accelerate age-related neurodegeneration. This screen, the largest of its kind in Drosophila, revealed about 200 genes implicated in AD. While some of these targets were already known, including genes for the amyloid precursor protein and presenilins, this study used computational network modeling to connect these and many newly implicated genes to specific biological pathways.

“We have integrated results from the largest reported forward genetic screen for age-related neurodegeneration mutants with multi-omic data from Alzheimer’s disease patients and Alzheimer’s disease relevant models to computationally and experimentally define pathways controlling neurodegeneration,” the researchers wrote.

Using data from proteomics, phosphoproteomics, metabolomics, and expression quantitative trait loci (eQTLs) in human neurons and fruit flies, the team identified two pathways of particular interest. One involved in RNA modification, and the other DNA damage repair, mechanisms not previously considered in Alzheimer’s pathology.

In the RNA modification pathway, the researchers identified that reduced expression of the genes MEPCE and HNRNPA2B1 made neurons more vulnerable to tau toxicity. These findings were confirmed in both Drosophila and human induced pluripotent stem cell (iPSC)-derived neurons.

The second pathway involves the genes CSNK2A1 and NOTCH1, both of which have been previously associated with AD. The new research, however, links them specifically to DNA damage repair. The researchers found that the loss of these genes leads to accumulation of DNA damage via separate damaging mechanisms. “Our study suggests that the CSNK2A1 and NOTCH1 pathways should also be explored for potential approaches to prevent DNA damage-associated neurodegeneration,” the researchers wrote.

This study builds on decades of genetic and molecular work in AD, including earlier Drosophila models of tauopathy and amyloid beta toxicity. Prior research using smaller-scale screens and GWAS had provided candidate genes but often failed to directly connect them to cellular mechanisms. The screening method used for this research were key to broadening the understanding of the underlying role played by these genes.

“Our genetic screen was intentionally broad, with genes knocked down in a pan-neuronal pattern to maximize recovery of neurodegeneration hits. The comprehensiveness of the screen reduced the need for computational methods to expand the number of genes of interest. Rather, the role of computational was to prioritize the genes and to generate hypotheses explaining the mechanisms by which these genes influenced neuronal health,” the researchers wrote.

The implications of this work could be far reaching. The identification of new pathways aside from amyloid plaques suggests new potential therapeutic targets for combination therapies. Importantly, the new researchers show the need to develop new and different experimental systems to help advance effective therapies for AD.

“The search for Alzheimer’s drugs will get dramatically accelerated when there are very good, robust experimental systems,” Fraenkel said. “We’re coming to a point where a couple of really innovative systems are coming together… then I think we’ll have some breakthroughs.”

Next steps along line of inquiry will focus on using iPSC-derived human neurons from AD patients to further investigate whether modulating these new targets can reverse or prevent neurodegeneration. The researchers also suggest expanding network analyses to other brain regions and non-neuronal cell types, which may yield additional targets relevant not only to Alzheimer’s, but other age-related neurodegenerative disorders.