Excavating FAIR Data: the Case of the Multicenter Animal Spinal Cord Injury Study (MASCIS), Blood Pressure, and Neuro-Recovery

Abstract

Meta-analyses suggest that the published literature represents only a small minority of the total data collected in biomedical research, with most becoming 'dark data' unreported in the literature. Dark data is due to publication bias toward novel results that confirm investigator hypotheses and omission of data that do not. Publication bias contributes to scientific irreproducibility and failures in bench-to-bedside translation. Sharing dark data by making it Findable, Accessible, Interoperable, and Reusable (FAIR) may reduce the burden of irreproducible science by increasing transparency and support data-driven discoveries beyond the lifecycle of the original study. We illustrate feasibility of dark data sharing by recovering original raw data from the Multicenter Animal Spinal Cord Injury Study (MASCIS), an NIH-funded multi-site preclinical drug trial conducted in the 1990s that tested efficacy of several therapies after a spinal cord injury (SCI). The original drug treatments did not produce clear positive results and MASCIS data were stored in boxes for more than two decades. The goal of the present study was to independently confirm published machine learning findings that perioperative blood pressure is a major predictor of SCI neuromotor outcome (Nielson et al., 2015). We recovered, digitized, and curated the data from 1125 rats from MASCIS. Analyses indicated that high perioperative blood pressure at the time of SCI is associated with poorer health and worse neuromotor outcomes in more severe SCI, whereas low perioperative blood pressure is associated with poorer health and worse neuromotor outcome in moderate SCI. These findings confirm and expand prior results that a narrow window of blood-pressure control optimizes outcome, and demonstrate the value of recovering dark data for assessing reproducibility of findings with implications for precision therapeutic approaches.

Keywords: Autonomic; Data science; Hemodynamics; Metascience; Motor recovery; Neurotrauma; Reproducibility; Spinal contusion.

Fig. 1

This flow chart describes the number of rats used in each of the three MASCIS studies, the number of rats for which data was recovered from each MASCIS study represented by solid or dashed lines, and where that data can be retrieved. An unknown number of rats were used in YM95. Data from Center 1 (OSU) were used in Beattie et al., , Young ; Ferguson et al., , and Nielson et al., . The current paper describes data recovered from Centers 2–8, collectively titled MASCIS 2020. Note that Center 2 did not contribute data in MY96, and Center 8 only contributed data in MY96. The compiled dataset can be retrieved in odc-sci.org and is titled “ODC-SCI MASCIS”. Upon request or with permission, some centers can be unmasked

Fig. 2

This heatmap demonstrates data recovered from the surgery record sheets of MP94 and MY96. Each row represents a unique rat (n = 1125), and each column represents a unique variable from the surgery records (n = 64), and each individual square a data point

Fig. 3

Change in BBB score (a) and weight gain (c) over time are shown with SEM bars for each time point. The linear relations between pre-injury blood pressure and ∆BBB (b) and ∆%weight (d) depicted, and the shaded areas represents the 95% confidence interval