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Proteogenomic Analysis IDs Neutrophil Diseases Undiagnosed by Sequencing Alone

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NEW YORK (GenomeWeb) – An effort led by researchers at Munich's Dr. von Hauner Children's Hospital and the Technical University of Berlin demonstrates the ability of proteomics to guide and supplement clinical genomic analyses.

In a study published last month in Molecular and Cellular Proteomics, the scientists used mass spectrometry-based analysis of neutrophil granulocytes to identify mutated genes responsible for a pair of rare monogenic diseases.

The work provided an example of the clinical utility of proteogenomics, which, though a growing and emerging technology, has been rarely used to date to inform the diagnosis and treatment of actual patients.

Neutrophil granulocytes are a common form of white blood cells and a key part of the body's immune system. A variety of rare conditions can affect these cells, including a number of monogenic disorders. Genomic sequencing can be helpful in diagnosing these cases, said Christoph Klein, an author on the MCP study and a professor and clinician at Hauner Children's, but "there are a number of patients in whom we still struggle to make a definitive diagnosis."

This is due in part to the fact that granulocytes are challenging to work with and in part to the limitations of sequencing technology, Klein said.

"So, we decided that we needed to be smarter in our approach and add another omics dimension," he said.

While this might typically lead a researcher to look to the transcriptome, which can be assessed using RNA-seq, neutrophils are not very transcriptionally active, Klein said, and so he and his colleagues decided to add a proteomic analysis atop their genomic analysis.

This proteomic work was led by Juri Rappsilber, a proteomics researcher at the Technical University of Berlin and the University of Edinburgh and author on the study.

Rappsilber said that he was surprised when Klein approached him about the collaboration, noting that he typical tries to "stay clear of the entire medical field."

"I thought, why don't you just sequence, and be done with it?" he said. "But no assay is 100 percent accurate and adding another orthogonal [approach] on top of [sequencing] gives you a better answer."

"There are a handful of genes that are known to affect the function of specific granulocytes, and then there are about two dozen genetic defects that are known to affect the proper differentiation and maturation of those cells as well as their function," Klein said. "But even with that knowledge, there are still many patients in whom, even if you do exome sequencing and look at all these genes, you won't fund a clear player that can explain the disease."

"So, we thought, could we figure out patterns of certain proteins being more or less abundant in these cells?" he said. "And could that help us define and shed light on cases where we don't have a good answer?"

Rappsilber said he was also intrigued by the fact that the especially low level of correlation between RNA and protein in neutrophil granulocytes meant a proteomic analysis might be particularly useful in this sample type.

"If we could make a useful contribution anywhere, it should be in these cells," he said.

The researchers analyzed purified neutrophil granulocytes from 68 healthy individuals and 16 patients with monogenic granulocyte diseases, using data independent acquisition mass spec to quantify more than 4,000 proteins in each sample.

Rappsilber said that his lab does not typically use DIA mass spec but said that the fact that the neutrophil granulocyte proteome is dominated by a small number of very high abundance proteins led them to use that approach. Because DIA measures the same set of proteins in every sample, it isn't subject to the issues with stochastic sampling conventional shotgun proteomics struggles with, which can lead to frequent measurement of high abundance analytes and undersampling of low abundance ones.

As Rappsilber noted, that issue can be addressed by upfront fractionation of samples, but this makes for a lower throughput and more cumbersome workflow that is less well suited to clinical work.

Of the 16 patients with granulocyte disease, the underlying genetic mutation was known for 14, and in those patients the researchers used the proteomic data to identify proteins dysregulated by these mutations, finding in patients with mutations in the neutrophil elastase gene ELANE a wide range of proteins that showed changed expression. They said that this indicated that "these mutations may affect maturation of neutrophil granulocytes and initiate misfolded protein response and cellular stress mechanisms."

On the other hand, patients with confirmed leukocyte adhesion deficiency (LAD) and chronic granulomatous disease (CGD) exhibited expression changes in only a small number of proteins.

Klein said he and his colleagues are now using this proteomic data to identify novel mutations in novel genes that may contribute to neutrophil granulocyte diseases.

In two of the 16 patients, exome sequencing had not identified a genetic cause for their conditions, and here addition of proteomic data allowed the researchers to identify the associated mutations.

In the first case, the proteomic data showed underexpression of the protein NCF1, suggesting a mutation in that gene. NCF1 mutations are a common cause of chronic granulomatous disease, but sequencing of that gene is made challenging by the presence of two pseudogenes. Having identified NCF1 as the likely causative gene using proteomics, the researchers were able to go back and confirm this via more targeted sequencing.

In the second patient, the proteomic data indicated that the RAB27a gene was likely involved. The authors noted that mutations in this gene have been linked to Griscelli 2 syndrome, which matched the patient's phenotype of neutropenia and partial albinism, and using sequencing they were able to determine that the patient's mother was heterozygous for an RAB27a mutation that had not been covered by the initial sequencing reads.

As improvements in sequencing and proteomic analysis have made proteogenomics more feasible, interest in the technique has grown significantly, with the field seeing the launch of major initiatives like the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium and the Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) Network, which aims to build a system in which Veteran Affairs and Department of Defense cancer patients routinely undergo proteogenomic profiling with the goal of matching their tumor types to targeted therapies.

Work like the MCP study, where proteogenomic analysis is used to make diagnoses in actual patients is still a relative rarity, however.

"We don't do this routinely," Klein said. "We try to be ingenious is finding solutions for patients, but this is the first example where we have done a project combining genomics and proteomics, and I'm hopeful that further ones will follow."

Klein is president of the Care-for-Rare Foundation, an organization focused on studying rare disease in patients around the world, and he said that as systems biology approaches like the proteogenomic analysis used in the neutrophil granulocyte work matures it could prove useful for better understanding these patients' conditions.

"I think overall we are encouraged [by the study results] that it is timely to introduce the concept of systems biology more and more into the hospital for diagnosis and guiding therapy," he said. "But we also know and appreciate that this will be a long process and will require many careful studies."

Klein said that he currently has no plans to develop any sort of commercial offering based on the proteogenomic approach he and his colleagues used.

"I see this as the first successful step in the right direction, and we will move forward with our many colleagues around the world, but in a very disciplined way," he said.