Repurpose terbutaline sulfate for amyotrophic lateral sclerosis using electronic medical records

Abstract

Prediction of new disease indications for approved drugs by computational methods has been based largely on the genomics signatures of drugs and diseases. We propose a method for drug repositioning that uses the clinical signatures extracted from over 13 years of electronic medical records from a tertiary hospital, including >9.4 M laboratory tests from >530,000 patients, in addition to diverse genomics signatures. Cross-validation using over 17,000 known drug-disease associations shows this approach outperforms various predictive models based on genomics signatures and a well-known "guilt-by-association" method. Interestingly, the prediction suggests that terbutaline sulfate, which is widely used for asthma, is a promising candidate for amyotrophic lateral sclerosis for which there are few therapeutic options. In vivo tests using zebrafish models found that terbutaline sulfate prevents defects in axons and neuromuscular junction degeneration in a dose-dependent manner. A therapeutic potential of terbutaline sulfate was also observed when axonal and neuromuscular junction degeneration have already occurred in zebrafish model. Cotreatment with a β2-adrenergic receptor antagonist, butoxamine, suggests that the effect of terbutaline is mediated by activation of β2-adrenergic receptors.

Figure 1. Overview of ClinDR.

(A) Construction of a drug–disease network. Known associations between drugs (circle nodes) and target diseases (square nodes) are represented as a bipartite network (black lines). We utilized existing drug prescription records in our EMRs and public drug indication resources to generated standard known drug-disease associations. (B) Calculation of drug–drug and disease–disease similarities using clinical signatures, such as distribution or pattern of laboratory test results under drugs or diseases related conditions. For disease pair similarity ClinDR uses the absolute values of individual types of laboratory test performed before any drug treatment. For drug pair similarity, ClinDR uses the changing pattern of laboratory test results during the corresponding drug medication. Then, ClinDR finds the maximum similarity scores across diverse types of laboratory test (C). (D–E) Calculation of drug–drug and disease–disease similarities using genomic signatures. (F) Prediction of final score (f(e) > θ, true) between the query indication (i.e. between drug α and disease a) using the combined clinic and genomic similarity matrixes from (C) and (E). The similarities between drug pairs or disease pairs are represented as edge widths. P_c(e) and P_g(e): the maximum score of a query indication (e) using clinical (P_c(e)) and genomic (P_c(e)) data, respectively. β_i: a similar drug to α. b_i: a similar disease to a.

Figure 2. Clustering of drug- or disease-pair similarities of clinical data and performance evaluations.

(A) Hierarchical clustering of Wilcoxon rank sum test for disease-disease and drug-drug pairs by distinct laboratory test results. (B) Bar chart for the 10-fold cross-validation of ClinDR with/without clinical physiome signatures and the GBA method. The GBA method presents deterministic results, without AUC. (C) The enrichment test of novel ClinDR repositionings with clinical trials in ClinicalTrials.gov.

Figure 3. Schematic view for the repurpose prediction of terbutaline sulfate for ALS.

ClinDR predict terbutaline sulfate (TS) as a promising candidate for ALS by drug-drug and disease-disease similarity analysis. Presented scores in between TS and Ursodeoxycholic acid (UDCA), and ALS and Kawasaki syndrome were analyzed similarity values using clinical signatures from EMRs (0.995 for the similarity between TS-UDCA pair and 0.99 for the disease pair similarity between ALS and Kawasaki syndrome). By integration of clinical (P_c) and genomic signature based predictions (P_g), TS was determined as a repositioning candidate for ALS therapy.

Figure 4. Experimental validation of terbutaline sulfate repurposing for ALS.

(A, C, F) All panels show lateral views of Tg(olig2:dsred2) spinal cords of zebrafishes, with anterior to the left and dorsal to the top. (A) Terbutaline sulfate (TS) prevent motor axon and neuromuscular junction degeneration of ALS model (d–f). In normal conditions, treatment with TS (c) had nonlethal effects compared with the untreated condition (a). Mt TDP indicates mutant TDP-43 mRNA-injected model and WT means wild type (i.e. normal). (B) Statistical analysis of panel A. Axonal defects indicate fragmentation and reduced lengths of axons. Data were obtained from 4 myotome segments from each of 10 control and 10 TS-treated models. (C) TS rescues the ALS phenotype. Mt TDPs had abnormal motor axon phenotypes at 36 h postfertilization (hpf) (b) and 48 hpf (f) compared with WTs (a, c). These models had clear motor axon and neuromuscular junction (NMJ) defects at 72 hpf (e, g). Mt TDP with 1 mM TS at 36 hpf (c) and 48 hpf (g), respectively, rescued motor axon and NMJ defects at 72 hpf (d, h). (D) Statistical analysis of panel C. (E) Inhibition of therapeutic effect of TS by beta2-adrenergic receptor antagonist, Butoxamine (BTX). In normal conditions, treatment with BTX had no effects compared with the untreated condition (a, c). Co-treatment with TS and BTX inhibits therapeutic effect of TS on ALS phenotype of Mt TDP model (b, d–f). (F) Statistical analysis of panel E. Data was obtained from 8 control and 8 terbutaline sulfate and/or BTX-treated models.