A map of the molecular network in the aging brain has been created a team of scientists from several leading research institutions in the ongoing quest for a successful treatment for Alzheimer’s disease.
Molecular networks are cellular and subcellular structures in an organism and the structures’ physical interaction between molecules, RNA, or proteins.
The researchers used their map to identify two new Alzheimer’s disease target genes — that is, genes that can be deleted, added, or modified, in the ongoing quest for a successful treatment for the disease. The research team is part of the Accelerating Medicines Program for Alzheimer’s disease (AMP-AD).
The AMP-AD program seeks to leverage advances in analytic methods and large-scale molecular profiles of the aging brain to identify novel therapeutic targets for Alzheimer’s disease. The molecular network team was led by principal investigators Dr. David A. Bennett at Rush University Medical Center in Chicago and Dr. Philip L. De Jager at Columbia University in New York.
More Diverse Population
The network described in the new study accounts for all older people, not just those that meet certain diagnostic guidelines. Further, it separates molecular events that lead to changes in brain tissue (pathology) from those involved in loss of cognitive function, which is the true target of therapeutic efforts.
“Prior network approaches had not considered the detailed change in cognitive state over time of older individuals. Instead, they had relied on comparisons of cases from a dementia clinic with volunteers who after their deaths came to autopsy without ever developing dementia. This does not capture the variability over time exhibited by a diverse population of older individuals,”
The burden of Alzheimer’s disease on our aging human populations is growing rapidly, but current therapeutic strategies targeting a small number of proteins have yet to yield a successful treatment.
Participants in these studies receive extensive medical testing and evaluation while alive and donate their brains to research upon their deaths. None of the participants had a diagnosis of dementia when they enrolled in the study, but some later developed it.
Schematic of the implementation of the module–trait network (MTN) method to prioritize modules and genes directly related to AD-related traits in our study. Credit: Sara Mostafavi, et al. CC-BY
The investigators created a unique resource that links molecular changes in nearly 500 older brains profiled in this study to both the individual trajectories of participants’ change in cognition over multiple years prior to death and detailed measures of Alzheimer’s disease and other common brain pathologies measured after death.
“We have a detailed picture of brain function before death and an extensive evaluation of the molecular features of each individual brain,”
De Jager said.
“Unlike traditional studies, all possible outcomes and molecular events are considered simultaneously, enabling us to prioritize a few large groups of genes that are most likely to lead directly to cognitive decline and/or brain pathology, instead of having to focus on a large list of individual genes,”
co-lead author Chris Gaiteri, Ph.D., also from the Rush Alzheimer’s Disease Center, noted.
“The strength of our analytic approach is that it makes no assumptions as far as what genes are important. While we find thousands of genes associated with cognitive decline, we do not simply go for the strongest gene. We find patterns that lead to cognitive decline and then prioritize a small subset of genes that appear to be driving these large-scale changes,”
added co-lead author, Sara Mostafavi, Ph.D., of the University of British Columbia.
Reduced Amyloid Beta Production
These so called “driver genes” are potentially excellent candidates or targets for developing Alzheimer’s disease therapies. However, statistical analyses are not enough.
Therefore co-investigator Tracy Young-Pearse, Ph.D., from Brigham and Women’s Hospital designed an experiment in which some of these target genes were perturbed to see if this change affected known molecules involved in Alzheimer’s disease.
“When they were altered in human astrocytes, a type of brain cell that plays a key role in maintaining brain function, two of the 14 genes predicted to be driver genes by the network displayed a reduction in the secretion of amyloid beta, a protein that contributes to the onset of Alzheimer’s disease,”
These two genes make proteins and the approach raises the possibility that finding drugs that affect those proteins could also lower the production of amyloid beta.
INPPL1 and PLXNB1 knockdown in human astrocytes significantly lowers Aβ42. Credit: Sara Mostafavi, et al. CC-BY
Dr. Bennett and his colleagues recently measured a number of the proteins in the network to see if they could replicate the predictions from the network map.
Needle In A Haystack
Using the network to predict the 14 driver genes itself was a scientific feat akin to finding the proverbial needle in a haystack, given that the brain map includes about 14,000 genes.
“This study is a milestone in the study of Alzheimer’s disease and the aging brain. We established a molecular network that not only predicts Alzheimer’s disease genes that can be validated experimentally but also can be repurposed to study very different molecular events involved in brain aging, such as stroke, and the fundamental function of the brain itself.”
said De Jager.
All data and network models were made available to share with the scientific community via the AMP-AD Knowledge Portal and the Rush Alzheimer’s Disease Center Resource Sharing Hub before the publication of the manuscript to enable other investigators to make us of the data and underlying observations for their own studies and to allow them to confirm the results of the study independently.
While the two genes identified as candidates by the network approach and its validation need further study before they can be used as the basis for drug development efforts, this report is an important milestone for AMP-AD Target Discovery program.