Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans

Abstract

Despite many recent advances in imaging and epidemiological data analysis, musculoskeletal injuries continue to be a welfare issue in racehorses. Peptide biomarker studies have failed to consistently predict bone injury. Molecular profiling studies provide an opportunity to study equine musculoskeletal disease. A systematic review of the literature was performed using preferred reporting items for systematic reviews and meta-analyses protocols (PRISMA-P) guidelines to assess the use of miRNA profiling studies in equine and human musculoskeletal injuries. Data were extracted from 40 papers between 2008 and 2020. Three miRNA studies profiling equine musculoskeletal disease were identified, none of which related to equine stress fractures. Eleven papers studied miRNA profiles in osteoporotic human patients with fractures, but differentially expressed miRNAs were not consistent between studies. MicroRNA target prediction programmes also produced conflicting results between studies. Exercise affected miRNA profiles in both horse and human studies (e.g., miR-21 was upregulated by endurance exercise and miR-125b was downregulated by exercise). MicroRNA profiling studies in horses continue to emerge, but as yet, no miRNA profile can reliably predict the occurrence of fractures. It is very important that future studies are well designed to mitigate the effects of variation in sample size, exercise and normalisation methods.

Science‐in‐brief: Genomic and transcriptomic approaches to the investigation of equine diseases

“…Another class of RNAs, microRNAs (miRNAs), bind to target mRNAs and regulate gene expression and are routinely profiled in many human diseases 43 . To date, three miRNA studies have profiled equine musculoskeletal disease (tendon injury, laminitis and osteochondrosis) but none were related to equine stress fractures (reviewed in 44,45 ).…”

Study design synopsis: Omics studies of fractures in the horse — Which technology is best?

“…The study of DNA, RNA, protein and metabolites is referred to as genomics, transcriptomics, proteomics and metabolomics respectively. A recent scoping and systematic review of the literature 8 identified a genome association study with no transcriptomic, proteomic or metabolomic studies pertaining to fractures in racehorses confirming the gap in the scientific literature in this area. We anticipate that veterinary researchers will set out to fill this gap soon.…”

“…Pre-analytical factors that can influence microRNA expression were identified as fasting, exercise and diet, for example, microR-NA-21 has been reported to increase with exercise in three publications. 8 Analytical factors that vary between studies are the platform used to quantify microRNA such as RNA-seq, RT-qPCR or miRNA arrays. Post-analytical factors that can influence results include how reference genes are selected for individual studies and the statistical approaches used to determine the false discovery rate in RNAseq analyses.…”

“…Most commercial companies that provide RNA‐seq analyses routinely test for the degree of haemolysis in their standard quality control protocol. Several human studies have used the delta Ct between miRNA‐23a and miRNA‐451 to indicate haemolysis (>7 being indicative of haemolysis) 8 . Haemolysis above the threshold level for accurate quantification of miRNAs has been found to occur in the majority of plasma samples taken from fit thoroughbreds in active training in one study 16 emphasising the importance of stringent quality control measures in such studies.…”

“…Pre‐analytical factors that can influence microRNA expression were identified as fasting, exercise and diet, for example, microRNA‐21 has been reported to increase with exercise in three publications 8 . Analytical factors that vary between studies are the platform used to quantify microRNA such as RNA‐seq, RT‐qPCR or miRNA arrays.…”