Strangulating small intestinal disease (SSID) carries a poor prognosis for survival in comparison to other types of colic, particularly if resection is required. Identification of markers which aid early diagnosis may prevent the need for resection, assist with more accurate prognostication and/or support the decision on whether surgical intervention is likely to be successful, would be of significant welfare benefit.
To apply an unbiased methodology to investigate the plasma and peritoneal fluid proteomes in horses diagnosed with SSID requiring resection, to identify novel biomarkers which may be of diagnostic or prognostic value.
Prospective clinical study.
Plasma and peritoneal fluid from horses presented with acute abdominal signs consistent with SSID was collected at initial clinical examination. Samples from eight horses diagnosed with SSID at surgery in which resection of affected bowel was performed and four control horses subjected to euthanasia for orthopaedic conditions were submitted for liquid chromatography tandem mass spectrometry. Protein expression profiles were determined using label-free quantification. Data were analysed using analysis of variance to identify differentially expressed proteins between control and all SSID horses and SSID horses which survived to hospital discharge and those which did not. Significance was assumed at P¿0.05.
A greater number of proteins were identified in peritoneal fluid than plasma of both SSID cases and controls, with 123 peritoneal fluid and 13 plasma proteins significantly differentially expressed (DE) between cases and controls (P<0.05, ¿2 fold change). Twelve peritoneal fluid proteins (P<0.036) and four plasma proteins (P<0.05) were significantly DE between SSID horses which survived and those which did not.
A low number of samples were analysed, there was variation in duration and severity of SSID and only short-term outcome was considered.
Changes in peritoneal fluid proteome may provide a sensitive indicator of small intestinal strangulation and provide biomarkers relevant to prognosis.