Amyotrophic lateral sclerosis (i.e. ALS or Lou Gehrig's disease) is the most common adult-onset motor neuron disorder, with progressive weakness being the clinical hallmark. The average survival rate is 2-5 years post- diagnosis, but 10% of individuals survive ?10 years, due to highly variable rates of progression. There is no cure for ALS, but there are treatments and interventions that can limit symptoms and unnecessary complications, and improve quality of life. Unfortunately, there is no single definitive diagnostic for ALS or validated biomarker for disease progression. It takes nearly a year from the first occurrence of symptoms to confirm ALS in most patients using current approaches (e.g. MRI, nerve function analyses, multiple blood and urine tests to rule out mimic disorders). Also, the only validated markers of disease progression are time to death and the Revised ALS Functional Rating Scale (ALSFRS-R), which is a subjective measure of disability and breathing. Although ALS is a rare disease (affecting approximately 20,000 people in the US), many more prevalent diseases can mimic ALS including but not limited to peripheral neuropathies, multiple sclerosis, neuromuscular transmission disorders, and hyperthyroidism. Significantly, up to 61% of ALS patients are misdiagnosed with a mimic disorder initially, which can negatively impact patient outcomes. There is an urgent unmet need to diagnose ALS at earlier timepoints via rapid and non-invasive methods, and to objectively predict ALS progression, particularly in the clinical trial setting. ALS-associated antibodies offer a new avenue for ALS diagnostics and disease monitoring. While previous studies measuring total levels of humoral antibody types (IgG, IgA, and IgM) have been inconsistent, recent studies have identified specific IgG autoantibodies, independent of absolute IgG level, as potential new markers of sporadic ALS onset and progression. Based on these recent findings, we propose to identify a sensitive and selective immunosignature, which we will develop into a reliable, non-invasive, in vitro array for the early detection of ALS. This array may also have potential for monitoring and predicting disease progression. In this Phase 1 application, we will use phage display biopanning and next generation sequencing to identify peptides that bind antibodies specifically enriched in patients with sporadic ALS and develop a peptide array capable of reproducibly detecting this immunosignature from serum. In Phase 2, we will refine the immunosignature for the early detection of ALS at baseline and additional timepoints, assess utility of the array to determine progression of the disease, and scale up array production. This simple peptide-based test will provide clear and actionable results for primary care physicians and neurologists, allowing the definitive and rapid diagnosis of ALS, thereby increasing the rate of early detection, diagnosis, and proper management. This test also has potential to enable the serum-based prediction of disease progression.

Public Health Relevance

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disorder, yet there is no single diagnostic or validated biomarker of progression for this devastating disease. Progression rates are highly variable and it takes nearly a year with current approaches to confirm ALS after symptoms first appear in most patients, with survival after diagnosis averaging 2-5 years. Affinergy plans to develop a novel array to objectively identify patients with ALS that would be available to primary care providers and neurologists to improve rates of diagnosis, early detection, patient management, and potentially enable serum-based prediction of disease progression.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43NS115201-01
Application #
9906532
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Trzcinski, Natalie Katherine
Project Start
2020-01-15
Project End
2020-12-31
Budget Start
2020-01-15
Budget End
2020-12-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Affinergy, LLC
Department
Type
DUNS #
078296854
City
Durham
State
NC
Country
United States
Zip Code
27709