NEW YORK – Comparisons of gene expression and protein quantitative trait loci reveal post-translational modifications that may drive the occurrence and development of Alzheimer's disease.
Carlos Cruchaga, a professor of psychiatry at Washington University who studies the biology of neurodegenerative disease, recently described how he has used SomaLogic's SomaScan technology to uncover approximately 2,300 protein quantitative trait loci (pQTLs) and 400 proteins implicated in Alzheimer's disease in samples of cerebrospinal fluid (CSF), brain tissue, and plasma.
Cruchaga presented his work in a SomaLogic-sponsored talk at the American Society of Human Genetics annual meeting in Los Angeles last week. The work also builds upon prior results published last year in Nature Neuroscience.
"We are identifying many more pQTLs, from 200 to [now] 2,300, that we are using for Alzheimer's-related disease but that can be leveraged for other diseases as well," Cruchaga told GenomeWeb.
Many of these proteins, he contends, may even be causal to the disease and are implicated in other neurological disorders such as Parkinson's and stroke.
Most studies investigating the molecular origins of Alzheimer's and related illness, Cruchaga explained, focus on genetic variation, such as in genome-wide association studies (GWAS). While these studies have uncovered numerous biomarkers of disease and shed light on disease mechanisms, they tend to fall short of identifying the functional variants and genes that drive GWAS signals.
To address this gap, Cruchaga and his colleagues compared the overlap between gene expression QTLs (eQTLs) and pQTLs.
"What we found is that a lot of the protein QTLs are not expression QTLs [and] are not splicing QTLs," Cruchaga said.
This finding highlights differences in post-transcriptional and/or post-translational regulation, pointing toward additional regulatory mechanism for protein levels.
"We are filling the gap between the disease variant and [its] effect on protein levels," Cruchaga added.
The majority of work to understand how post-translational modifications affect Alzheimer's disease has focused on tau and other key Alzheimer's-related proteins. While efforts to understand the disease on a broader proteomic level are underway, the most common current approaches rely on mass spectrometry and affinity-based methods, making Cruchaga's approach somewhat unique.
Nicholas Seyfried, a professor of biochemistry and neurology at Emory University, whose research interests align with Cruchaga's, praised the latter's lab for doing "an outstanding job of integrating genomics and proteomics to define protein levels across tissues that are under genetic control."
Beyond discovering the small overlap between eQTLs and pQTLs, Seyfried said that one of Cruchaga's key findings is that the majority of cis-pQTLs (genetic variations that act on local genes) are shared across tissues whereas trans-QTLs (those acting on distant genes and genes found on different chromosomes) appear more likely tissue-specific.
"This is an important approach as it provides promising targets for further mechanistic and therapeutic studies," Seyfried said.
Seyfried's own lab has pursued an approach analogous to Cruchaga's, using mass spectrometry integrated with GWAS data to analyze cis- and trans-acting transcripts and proteins that can exert pleiotropic influence on both neurodegenerative and psychiatric disorders.
Interestingly and in line with Cruchaga's research, Seyfried's team discovered a significant overlap between putatively causal proteins in several neurodegenerative and psychiatric disorders, suggesting a shared pathophysiology, in addition to their known shared epidemiological risk.
An expanded pool of potentially causative neurodegeneration-associated proteins provides fertile terrain for drug repositioning efforts, which could ideally speed the search for effective therapies, and for improved prognostics, as disease-associated pQTLs could serve as biomarkers for disease progression.
Cruchaga has already identified 25 candidate drug repositioning molecules for future investigation in Alzheimer's, as well as in Parkinson's disease and ALS.
SomaLogic's aptamer-based SomaScan assay, which can analyze approximately 7,000 proteins simultaneously, proved a key technology in enabling Cruchaga's research.
"A main advantage of SomaScan is the outstanding coverage of the plasma proteome," said Seyfried, "which is challenging using MS-based techniques due to the large dynamic range in protein abundance."
Despite this challenge, Seyfried noted that the two approaches can still deliver complementary results. A recent study by Erik Johnson, another Emory University researcher, for instance, which was recently accepted by the journal Alzheimer's Research and is available as a preprint on BioRxiv, directly compared SomaScan and tandem mass-spectrometry, as well as Olink's Proximity Extension Assay, and showed good correlation in CSF with more variability in plasma across the platforms.
While Cruchaga agrees that the SomaScan "is one of the best platforms" for the studies he conducts, he acknowledged that the way it annotates results is one limitation. Essentially, he explained, proteins are annotated to corresponding genes but not individual transcripts or epitopes, which matter in assessing the sort of protein modifications that Cruchaga investigates.
"Sometimes it's not clear what proteoform we're messing with," Cruchaga said.
Another limitation to Cruchaga's approach is the challenge of determining the specific cell types and tissues that disease-associated pQTLs come from. Cruchaga's team uses a digital deconvolution method to link pQTLs and corresponding gene expression to specific tissues and cell types but this is complicated in liquid samples such as CSF and plasma, wherein many diverse cells secrete proteins into the medium.
Echoing this challenge, Seyfried mentioned that his own research indicates that there is nearly 70 percent overlap between proteins identified in the CSF and in brain tissue, many of which can be linked to specific cell types in the brain.
"Ideally you would like to pinpoint exactly which cell types may be driving these signals in peripheral biofluids," he said.
Cruchaga's group currently has two papers detailing his findings in the publication pipeline. One, concerning Alzheimer's molecular signatures identified through multiomics approaches, has been accepted by Science Translational Medicine, and a second that goes into more detail on the 2,300 Alzheimer's-related pQTLs presented at ASHG is now being drafted.
Cruchaga has patented the pQTL and drug repositioning prediction models that he and his colleagues have developed, although he said that he's not currently working on any commercial applications.