Repurpose drugs for new indications

Png G, Barysenka A, Repetto L, et al. Mapping the serum proteome to neurological diseases using whole genome sequencing. (2021) Nature Communications, DOI: 10.1038/s41467-021-27387-1

This protein quantitative trait locus (pQTL) analysis analyzed 184 neurologically-relevant proteins using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In total, 214 independently-associated variants were detected for 107 proteins, the majority of which (76%) were cis-acting, including 114 previously unknown variants. Two-sample Mendelian randomisation identified causal associations between serum CD33 and Alzheimer’s disease, GPNMB and Parkinson’s disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting repurposing opportunities for existing drugs targeting these proteins.

Al-Nesf MAY, Abdesselem HB, Bensmail I, et al. Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications. (2022) Nature Communications, DOI: 10.1038/s41467-022-28639-4

This study used plasma proteomics to identify 375 proteins that are differentially expressed in patients with severe COVID-19 compared to those with mild or moderate disease. This was used to derive a 12-protein “COVID-19 molecular severity score” with extremely high predictive value for the severe form of the disease (100% specificity and 98% sensitivity, AUC= 0.999). Additionally, they used the protein data to train another high-performance risk score based on clinical measurements and both were then validated in an independent data set. The authors also identified a list of FDA-approved drugs that target proteins identified in their severity score, which they suggested could be further investigated in the context of repurposing for severe COVID-19 therapy.

Simats A, Ramiro L, Valls R, et al.  Ceruletide and Alpha-1 Antitrypsin as a Novel Combination Therapy for Ischemic Stroke. (2022) Neurotherapeutics, DOI: 10.1007/s13311-022-01203-0

This study took a novel approach to repurpose existing drugs for improved treatment of ischemic stroke. While tPA is used successfully as a thrombolytic therapy for stroke, attempts to develop neuroprotective drugs to limit the impact of the stoke have all failed so far. The study authors used an in silico, systems biology strategy based on artificial intelligence and pattern recognition tools to integrate available biological, pharmacological, and medical knowledge into mathematical models to simulate in silico complexity of the stroke. Combinational treatments were acquired by screening these models with more than 5 million two-by-two combinations of drugs on the DRUGBANK database. This identified a combination of ceruletide alpha-1 antitrypsin (referred to as CA) as having a high probability to confer neuroprotection in stroke cases.

Experimental verification of CA treatment in a mouse model of stroke indicated a significant neuroprotective effect, reducing brain tissue death by >30%, but only when the two drugs were used in combination. Proteomic analysis of affected and unaffected brain hemisphere tissue from CA-treated mice suffering stroke provided important information regarding the MOA of the drug combination. Enrichment analysis of proteins differentially expressed in CA vs placebo animals were involved in pro-inflammatory cytokine signaling, necrotic and apoptotic processes, as well as promotion of endothelial cell proliferation and angiogenesis, suggesting important mechanistic aspects of the drug combination treatment.