Predicting COPD & emphysema prognosis with biomarkers identified through next-gen proteomics
Chronic obstructive pulmonary diseases, like emphysema, make breathing difficult and may not be properly diagnosed until significant progression has occurred. With proteomics, it is possible to get early insight into disease status and progression to inform treatment. While our genotype does not change if we start smoking, the circulating proteins in our body can. Also, several approved therapies for these diseases target proteins, making protein biomarkers an excellent tool for diagnosis, intervention, and developing future drug targets.
Chronic obstructive pulmonary disease (COPD) is an umbrella term for diseases characterized by injury to the airways, airspaces, and lung vasculature – usually caused by tobacco smoke and/or air pollution exposure. These include emphysema and chronic bronchitis. COPD makes breathing difficult for the millions of people who have this disease, and is the third leading cause of death worldwide, causing 3.23 million deaths in 20191. While there is no cure for COPD, it can be treated to improve quality of life when diagnosed properly. Diagnosis can be inconsistent depending on disease progression which varies from patient to patient and occurs over several years. This emphasizes the need for biomarkers. Currently, there are no drugs to slow disease progression2 and without the right biomarkers, it is difficult to identify people at high risk of disease progression.
Biomarkers are indicators of biological processes. A diagnostic biomarker for instance, can help distinguish healthy people from those with COPD. Disease activity biomarkers differentiate between actively progressing COPD and stable COPD. During treatment, circulating biomarkers can distinguish between patients responding to treatment and those not responding. These are a highly responsive indicator compared to classical clinical metrics which change over the course of decades rather than months. Given the vast number of proteins in the human body, identifying these biomarkers requires a large-scale proteomic platform to assay thousands of proteins simultaneously. The SomaScan® Assay measures 7000 proteins from a single sample, making it an ideal approach for biomarker identification.
Notably, not everyone who smokes or is exposed to air pollution develops COPD. This makes it essential to identify those at high risk who may benefit from an intervention. Russell Bowler, M.D., Ph.D. studies the mechanisms behind COPD resulting from cigarette smoke. His lab has generated genetic, proteomic, and metabolic profiles on 10,000 subjects in the NIH sponsored COPDGene cohort and is now using this data to identify novel diagnostic and therapeutic targets. To better understand why not everyone exposed to COPD causal factors develops the disease, his team used the SomaScan Assay v4.0 (which measured 4,776 human proteins) to identify plasma biomarkers of disease status, as well as severity and progression in 6,017 subjects from the COPDGene cohort.
Dr. Bowler and his team at National Jewish Health Hospital identified hundreds of cross-sectional and longitudinal biomarkers associated with different COPD clinical metrics, including C-reactive protein3 which gave some insight to the observed phenotypes. They also used penalized regression (LASSO) to develop protein risk scores, which typically include 200-300 of the most influential proteins. These protein risk scores explained up to 50% variance of disease. Data from these studies could potentially lead to identifying drug targets that could slow disease progression and help identify those at risk of disease progression.
While the mortality rate of COPD is still high, these proteomic advances pave the way for personalized therapies in COPD. Combining proteomic discoveries with metabolomics3 for instance, has helped shed more light on pathways that are associated with distinct COPD clinical phenotypes. Similar to this COPD study, biomarker discovery and identification can provide insight into complex disease states. To learn more, watch this webinar recording where Dr. Bowler discusses in depth the findings of his research.
References
- WHO Global Health Estimates
- K. Han, C.H. Martinez, D.H. Au, et al. “Meeting the challenge of COPD care delivery in the USA: a multiprovider perspective” Lancet Respir Med, 4 (6) (2016), pp. 473-526
- L. Zemans, S. Jacobson, J. Keene, et al. “Multiple biomarkers predict disease severity, progression and mortality in COPD” Respir Res, 18 (1) (2017), p. 117
- Mastej, L. Gillenwater, Y. Zhuang, K.A. Pratte, R.P. Bowler, K. Kechris “Identifying protein-metabolite networks associated with COPD phenotypes” Metabolites, 10 (4) (2020), p. 124
More blogs
BlogUnlocking cancer insights: SomaLogic-EPIC study partnership reveals how lifestyle choices impact risk
Having provided more insights into the relationship between environmental factors and the incidence of cancer than any other cohort in existence, EPIC has been crucial to understanding how lifestyle influences risk of disease. This is important because current cancer research shows that factors such as tobacco, diet, infection, alcohol, drugs, and chemicals are more important than genetic (hereditary) factors in determining the development of most cancers. In fact, only 5-10% of all cancer cases can be attributed to genetic defects, whereas the remaining 90-95% have their roots in environment and lifestyle.
BlogBiomarkers are key to understanding dementia risk, disease pathology, and mechanism of action for new therapeutics
Our team was honored to see so many researchers in academic research groups and pharma companies worldwide present findings from clinical trials and research studies spanning various dementia types and utilizing multiple neurological and peripheral matrices using data derived from our SomaScan® Platform. Their discoveries inspire us and are proof that forward momentum is being made – as a consequence to high-throughput proteomics - to better understand this group of diseases and identify meaningful therapuetics .
BlogProteomic profiling for discovery of biomarkers and mechanistic insights into acute myeloid leukemia (AML)
Acute myeloid leukemia (AML) is a cancer of the blood and bone marrow that is characterized by the abnormal proliferation of immature myeloid cells. It is the most common type of leukemia among the adult population that accounts for about 80% of all cases1. AML is a complex, genetically heterogeneous disease, which presents challenges for treatment. Although most patients respond to standard intensive chemotherapy, approximately two-thirds of the patients relapse within 18 months to 5 years of the initial treatment2. The bone marrow microenvironment is thought to play a significant role in mediating the persistence of malignant leukemic stem cells. However, the exact nature of bone marrow–leukemic cell interactions is not well understood.