Research published within the past three years highlights a unique role for proteomics to aid critical areas of unmet need in rare disease populations, defined in the United States as conditions affecting fewer than 200,000 people at any time, and in the European Union as fewer than one in 2,000.
Many of these rare diseases are marked by highly burdened diagnostic journeys and limited development of treatment options. Often, these diseases are difficult to study due to factors such as small populations, poorly defined diagnoses, unexplained disease heterogeneity, and complex disease pathways — even in instances of genetically defined disease.
Proteomic insights complement genomic information by identifying and quantifying multiple proteins in a single patient sample, enabling the discovery of new and relevant biomarkers and pathways to better understand specific rare diseases and potential therapeutic targets.
One unique affinity-based platform is the SomaScan Assay, which uses modified aptamers — SOMAmer reagents — to identify and quantify up to 7,000 proteins from a single patient sample.
Enabling Proteomics Research on Rare Diseases
A 2019 study explored protein markers in cystic fibrosis (CF), an inherited condition that dehydrates mucus, leading to severe damage to the lungs and other organs. While the lung environment can be directly assessed through bronchoalveolar lavage (BAL) samples, BAL samples contain low concentrations of important proteins that are difficult to assess through traditional methods.
Emily DeBoer and colleagues used the SomaScan Assay to assess 1,129 different proteins among BAL samples collected during exacerbations for 50 pediatric patients with CF and nine disease controls. The analysis was conducted with the goal of identifying proteins and pathways to aid understanding of disease progression, track therapeutic response, and enrich enrollment of clinical trials.
Proteomic analysis confirmed known proteins involved in immune responses and extracellular matrix remodeling pathways, while sensitively quantifying several new protein leads to study further as part of potential clinical panels or even therapeutics targets. The detected pathways implicate protein folding and aggregation, host defense, metabolic and glucose regulation, and more.
Protein quantification also identified two separate endotypes in the CF samples, distinguishable by their distinct proteomic profiles. The characteristics of each endotype extended into clinical differences in levels of inflammation and infection when measuring white blood cells, neutrophils, and the presence of CF pathogen. This suggests a need to better understand the mechanisms driving exacerbations.
Discerning Diagnoses and Endotype Categories
Another 2019 study focused on children’s interstitial diffuse lung disease (chILD), a heterogeneous umbrella condition whose mechanistic diagnoses are poorly understood and, therefore, present a challenge for diagnosis, prognosis, and therapeutic development.
The primary challenge within chILD diagnoses is how to improve differentiation between the two main categories of mechanistic diagnoses. The first relates to genetic abnormalities and dysfunction of specific surfactant proteins, and the second involves neuroendocrine cell hyperplasia of infancy (NEHI).
Robin Deterding and colleagues analyzed 1,129 proteins using the SomaScan Assay in BAL samples across 47 patients: 22 with NEHI, eight with surfactant dysfunction mutations, eight with other chILD diseases, and nine disease control subjects with nonspecified cough.
This analysis uncovered 20 unique proteins across two distinct proteomic profiles that may differentiate surfactant dysfunction from NEHI etiologies of chILD. With further study, these proteins could become leads for diagnostic markers and even new targeted therapeutic interventions.
Additionally, the study uncovered two surprising endotypes within the NEHI category that did not align with existing classifications or specific clinical features. This finding, which deserves further study, suggests differences in underlying disease mechanisms and a justification for NEHI diagnoses in future research.
Predicting Disease Progression
Proteomics has also been used in recent studies as a way to identify markers of disease progression in conditions such as CF, which faces unique challenges that require prognostic clarity.
A 2021 study by Julie Renwick and colleagues examined BAL samples using the SomaScan Assay for early baseline biomarkers that may inform progression risk within early-life CF, compelled by the rapid patterns of progression and lung damage evidenced in patients as young as age six.
The study assessed 1,305 proteins in BAL samples from 14 clinically stable patients with CF ranging from ages one to five years. They identified 18 proteins significantly correlated with radiologic progression scores, including seven markers associated with known inflammation and neutrophilic pathways. Biomarker levels for three of these proteins correlated with significantly greater lung damage later in childhood (high levels of azurocidin or myeloperoxidase; low levels of interleukin-22).
By tracing their proteomic analysis through known disease mechanisms and clinical outcomes, the study was able to report biomarker leads for identifying the most vulnerable populations, and even potential targets to investigate within the inflammatory processes of CF.
As the breadth of proteomics develops further into thousands of protein targets, it continues to enable explorations into diseases with small heterogeneous populations and a broad range of mechanistic pathways. In rare diseases, this could make the difference in detecting new pathophysiologic mechanisms and potential drug targets, as well as developing new diagnostics and prognostics.
Discover more about powerful protein profiling at Technology—SomaLogic.