Liquid liver biopsy
Background: The definitive diagnostic test for nonalcoholic steatohepatitis (NASH) is liver biopsy, which carries risks and cannot be used for frequent monitoring. There is no single non-invasive method that can accurately and simultaneously capture steatosis, inflammation, hepatocyte ballooning and fibrosis, the four major pathologic components assessed by biopsy. We show that large scale proteomics has promise as an alternative to liver biopsies in clinical trials or longitudinal studies of NASH.
Methods: Using modified-aptamer proteomics, we scanned ~5,000 proteins in each of 2,852 serum samples from the NASH CRN*, including 636 participants from a natural history cohort and longitudinal samples from the PIVENS (pioglitazone, vitamin E and placebo) and the FLINT (obeticholic acid and placebo) clinical trials, for a total of ~15 million protein measurements. Liver biopsy results were modeled with measured proteins using machine learning methods independently for each biopsy component.
Results: Results for the four protein models in training/paired validation were: fibrosis (AUC 0.92/0.85); steatosis (AUC 0.95/0.79), inflammation (AUC 0.83/0.72), and ballooning (AUC 0.87/0.83). A concurrent positive score for steatosis, inflammation and ballooning predicted the biopsy diagnosis of NASH with an accuracy of 73%. When applied longitudinally, model scores predicted decreasing biopsy scores in the active groups vs. stable for placebo and differential pharmacodynamic effects were evident on each model component.
Conclusions: Serum protein scanning is the first technique to capture four components of the liver biopsy individually and noninvasively. The four models were sufficiently sensitive and precise to characterize the time-course and extent of three drug mechanisms. Concurrent positive results from the protein models had performance characteristics of “rule-out” tests for diagnosis of NASH. These tests may assist in new drug development and medical intervention decisions.
PosterUtility of proteomic trajectories of cardiovascular risk and cardiorespiratory fitness to monitor adverse health states throughout post-COVID-19 illness
Cardiovascular involvement is a prominent observation in patients during the acute phase of COVID-19 infection, as well as in convalescence. However, the etiology, trajectory, and underlying biology of cardiac dysfunction across the spectrum of COVID-19 illness is not fully understood. To address this, the CISCO-19 study (NCT04403607) was formed to investigate the multisystem effects of COVID-19 from hospitalized patients
PosterIdentifying genetic and environmental influences on proteins associated with age, cardiovascular risk, and other endpoints using the SomaScan® Assay
Protein quantitative trait locus pQTL studies identify genetic variants that are statistically associated with protein levels Results from the growing number of pQTL studies can be combined with genome wide association studies to identify proteins that underlie the genetic risk of disease, thus revealing the mechanisms of disease and potential drug targets.
PosterSomaScan® Platform confirmation and performance validation
The SomaScan® Platform for proteomic profiling uses 7288 (7K) SOMAmer® reagents, single stranded DNA aptamers, to 6596 unique Human Protein Targets. The modified aptamer binding reagents1, SomaScan assay2, its performance characteristic for 5k3 and 7k4 content sets, and specificity5,6,7 to human targets have been previously described. We combine profiles of validation and performance metrics with orthogonal confirmation of specificity from published literature to provide a comprehensive view of the specificity and utility of the SomaScan Platform.