By Zoë Leanza | September 15, 2022
A research group led by Panos Roussos from the Icahn School of Medicine at Mount Sinai in New York City, recently contributed genomic variants, gene expression, and epigenetic observations from microglia isolated from fresh autopsy and biopsy tissue of 150 adults with and without neurodegenerative disease.
Panos Roussos’ lab group in the Bronx, NY
These data, accompanied by the associated analyses, provide a unique and valuable resource for the study of Alzheimer’s disease and related dementias. The scale of the efforts associated with this resource is demonstrated by the large number of researchers contributing to the upcoming publication, with four first co-authors, Roman Kosoy, John Fullard, Biao Zeng and Jaroslav Bendl, and joint supervision by Gabriel Hoffman and Panos Roussos.
Microglia are the main immune cells in the brain implicated as the major players in Alzheimer’s disease. They function as the macrophages of the central nervous system, and are essential to maintain neurological health by pruning connections in the brain and removing damaged neurons. Dysregulated microglia, however, can contribute to the inflammatory progression of Alzheimer’s disease and related dementias.
“The question is how and when,” said first co-author Kosoy, “and if we want to treat Alzeimer’s disease – or even better, to prevent it – we need to know exactly how to nudge the microglia away from the disease-associated phenotype.”
Microglia are not easy to obtain. Isolating them requires access to fresh samples and specific cell sorting procedures. Most of the samples were autopsies obtained from brain donation programs at The Mount Sinai/JJ Peters VA Medical Center NIH Brain and Tissue Repository (NBTR) in the Bronx, NY and Rush University Medical Center/Rush Alzheimer’s Disease Center (RADC) in Chicago, IL. Additional samples came from biopsies collected at Mount Sinai Hospital from patients undergoing emergency treatment for stroke injury or Parkinson’s disease. “After somebody dies you have to process the brain very fast or the microglia will die,” Kosoy said, “when we get fresh samples, immediately the people in our group, guided by John Fullard, have to spend a whole day working on it – it’s like a 10 to 12 hour process, and sometimes we get more than one sample in a day.”
Given these challenges, many researchers instead analyze genome-wide association studies (GWAS), but the data are often too nonspecific to identify specific causal genes. Others opt to study different immune cells, such as macrophages or monocytes. Those can be useful proxies, Kosoy said, “but they’re still just a model for the microglia, which are effectively irreplaceable when it comes to thorough analysis and investigation of Alzheimer’s disease.”
The newly contributed data, accessible through the AD Knowledge Portal, help characterize these irreplaceable cells. The data available include ATAC-seq data (for determining chromatin accessibility), RNA-seq data (for characterizing transcriptomes), Hi-C data (for visualizing genomes in 3-D), and SNP array data (for detecting genomic variation). Genetic regulation datasets generated by Biao Zeng provide detailed information of how chromatin accessibility and transcriptome may be mediated, while transcriptional factor analyses by Jaroslav Bendl describe contribution of specific transcription regulating proteins.
“By combining all this data,” Kosoy said, “we can describe which genomic regions are important for the regulation of the genes that express microglia, and examine how they integrate with relevant genetic variants.”
Roussos and colleagues availed their work to the scientific community to prompt secondary data use, hoping to expedite the identification of genes and regions that could influence disease-relevant gene expression. “If people don’t use it’s wasted, right?,” Kosoy said, “The whole point of science is that we discover something and we allow other people to benefit from this discovery.”
Kosoy, R., Fullard, J.F., Zeng, B. et al. Genetics of the human microglia regulome refines Alzheimer’s disease risk loci. Nat Genet 54, 1145–1154 (2022). https://doi.org/10.1038/s41588-022-01149-1.
Study Data: https://doi.org/10.7303/syn26207321.