UCSF Lab Readies Launch of Metagenomic NGS Test for Infectious Disease

SAN FRANCISCO (GenomeWeb) – Researchers at the University of California, San Francisco are preparing to launch a clinical metagenomic next-generation sequencing-based test next month for meningitis and encephalitis, according to Charles Chiu, director of UCSF's Viral Diagnostics and Discovery Center.

Chiu, whose lab has been developing and validating the test over the last couple of years, discussed his team's progress at Cambridge Healthtech Intstitute's Molecular Medicine Tri-Conference here this week. In addition, he provided updates on another infectious disease sequencing project the lab is working on to develop a better test for Lyme disease based on targeted RNA sequencing.

Chiu's lab has been developing the metagenomic infectious disease test for the last couple of years. In June 2016, the group began a prospective clinical utility and cost-effectiveness study under a project called Precision Diagnosis of Acute Infectious Diseases (PDAID), which has been funded by the California Initiative to Advance Precision Medicine with support from the Sandler, William F. Bowes Jr., and Charles and Helen Schwab Foundations, as well as in-kind support from UCSF. As part of the project, researchers are testing cerebrospinal fluid from 300 patients who have been hospitalized due to a suspected infectious agent.

Seven hospitals are participating, including UCSF, UC Davis, UCLA, the Children's Hospital Los Angeles, Children's Hospital of Denver, St. Jude's Children Hospital, and Children's National Medical Center. Patient samples are sent to UCSF for analysis. UC Berkeley will be doing the cost-benefit analysis.

In a presentation, Chiu said that the researchers plan to submit the study results for publication in a peer-reviewed journal soon. Preliminary analyses have been "very promising," he said in an interview following the presentation. "It's safe to say that we've been able to use the test to make diagnoses as well as to use it as a rule out for infectious causes" of the patient's illness, he said.

Metagenomic sequencing is performed on an Illumina HiSeq and test results are reported in patients' medical records. In addition, as part of the study, the researchers put in place a clinical microbial sequencing board modeled after molecular tumor boards, Chiu said.

The clinical test will be run out of UCSF's Clinical Microbiology Laboratory, and the team is now working on a number of improvements in order to scale up testing service, Chiu said.

For instance, he said, one important aspect will be to streamline the lab processes with robotics and automation for sample processing. Currently, for the research study, about eight to 10 samples are processed per week, but the goal is to eventually reach a capacity of 100 samples per week for clinical testing.

In addition, another important aspect will be to make testing sustainable. Currently, the project is being funded through research grants and foundation money, but a clinical test will need to pay for itself. Chiu said that he's already generated a test code in order to bill for the assay, which he anticipates will be around $2,200. The lab is also considering licensing its informatics pipeline, SURPI+, a clinical version of a pipeline it developed in 2014 specifically to identify pathogens from metagenomic sequence data.

The team is also aiming to reduce the turnaround time of the assay to 72 hours from sample receipt, Chiu said. The turnaround time for the research study has been longer, he said, closer to seven to 10 days due to the time it takes to enroll and consent patients, as well as time the researchers have spent discussing results on the clinical microbiology board.

And finally, Chiu said that he is in discussions with the US Food and Drug Administration about the requirements for approval.

Chiu said the researchers are also working on future iterations of the test including expanding its indications to fever and sepsis, and performing add-on analyses like antimicrobial resistance profiling, which would likely be a reflex test for those patients whose initial test is positive.

In addition, the researchers have been evaluating RNA extracted from patient samples to see how gene expression data could complement the metagenomic test. There is some evidence, he said, that certain pathogens have identifiable patterns of gene expression, which could help confirm a diagnosis or disambiguate findings where multiple potential pathogens are identified. The current test has the potential of detecting "bystander" pathogens that aren't responsible for the patient's illness, Chiu said. But, RNA-seq data could help determine whether a specific pathogen is really the cause of the illness.

His group has also made progress on a study to identify gene expression signatures that could become a better way to diagnose acute Lyme disease. Chiu's lab has been sequencing the transcriptomes of patient samples from the Study of Lyme Disease Immunology and Clinical Events (SLICE) led by Johns Hopkins University. Lyme disease diagnostic tests currently rely on a two-tiered approach that measure antibodies, but these tests are not very sensitive particularly early on because the individual has not yet produced a detectable response. Last year, Chiu and his collaborators published a study in mBio that identified 670 genes with elevated expression in Lyme disease and 390 genes with lower levels of expression in the Lyme disease patient.

Chiu said that since then, the group has been able to use machine learning algorithms to whittle down the list of genes to around 100. Chiu said the group is now looking at validating a test that includes a rule-in and rule-out component based on the genes that are most highly expressed and least expressed, respectively, compared to non-Lyme disease. Both gene sets could be analyzed at the same time, he said, eliminating the current tiered approach to testing. Chiu said that the panels have been locked down and the researchers are in the midst of a validation study that should be completed in the next several months. The earliest a clinical test could be available would likely be one year, he said.

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