Standardized protocol for quantification of nerve bundle density as a biomarker for endometriosis - Zoet, Gerbrand; Tucker, Dwayne R.; Orr, Natasha L.; Alotaibi, Fahad T.; Liu, Yang Doris; Noga, Heather; Köbel, Martin; Yong, Paul J. (Frontiers in Reproductive Health, 2023)
Introduction We propose a standardized protocol for measurement of nerve bundle density in endometriosis as a potential biomarker, including in deep endometriosis (DE), ovarian endometriomas (OMA) and superficial peritoneal endometriosis (SUP). Methods This was a prospective cohort of surgically excised endometriosis samples from Dec 1st 2013 and Dec 31st 2017 at a tertiary referral center for endometriosis in Vancouver, BC, Canada. Surgical data were available from linked patient registry. Protein gene product 9.5 (PGP9.5) was used to identify nerve bundles on immunohistochemistry. PGP9.5 nerve bundles were counted visually. To calculate nerve bundle density, PGP9.5 nerve bundle count was divided by the tissue surface area (total on the slide). All samples were assessed using NHS Elements software for semi-automated measurement of the tissue surface area. For a subset of samples, high power fields (HPFs) were also counted as manual measurement of the tissue surface area. Intraclass correlation was used to assess intra observer and inter observer reliability. Generalized linear mixed model (GLMM) with random intercepts only was conducted to assess differences in PGP9.5 nerve bundle density by endometriosis type (DE, OMA, SUP). Results In total, 236 tissue samples out of 121 participants were available for analysis in the current study. Semi-automated surface area measurement could be performed in 94.5% of the samples and showed good correlation with manually counted HPFs (Spearman's rho = 0.781, p < 0.001). To assess intra observer reliability, 11 samples were assessed twice by the same observer; to assess inter observer reliability, 11 random samples were blindly assessed by two observers. Intra observer reliability and inter observer reliability for nerve bundle density were excellent: 0.979 and 0.985, respectively. PGP9.5 nerve bundle density varied among samples and no nerve bundles could be found in 24.6% of the samples. GLMM showed a significant difference in PGP9.5 nerve bundle density between the different endometriosis types (X2 = 87.6, P < 0.001 after adjusting for hormonal therapy, with higher density in DE and SUP in comparison to OMA). Conclusion A standardized protocol is presented to measure PGP9.5 nerve bundle density in endometriosis, which may serve as a biomarker reflecting local neurogenesis in the endometriosis microenvironment.