Abstract
Background:
Non-invasive biomarkers that predict surgical treatment response would inform personalized treatments and provide insight into potential biological pathways underlying endometriosis-associated pain and symptom progression. Thus, we evaluated plasma proteins in relation to persistence of pelvic pain following laparoscopic surgery in predominantly adolescents and young adults with endometriosis using a multiplex aptamer-based proteomics biomarker discovery platform.
Methods:
We conducted a prospective analysis including 142 participants with laparoscopically-confirmed endometriosis from the Women’s Health Study: From Adolescence to Adulthood (A2A) observational longitudinal cohort with study enrollment from 2012–2018. Biologic samples and patient data were collected with modified World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (EPHect) tools. In blood collected before laparoscopic ablation or excision of endometriosis, we simultaneously measured 1,305 plasma protein levels including markers for immunity, angiogenesis and inflammation using SomaScan. Worsening or persistent post-surgical pelvic pain was defined as having newly developed, persistent (i.e., stable), or worsening severity, frequency, or persistent life-interference of dysmenorrhea or acyclic pelvic pain at one-year post-surgery compared to pre-surgery. We calculated odds ratios (OR) and 95% confidence intervals (CI) using logistic regression adjusted for age, body mass index, and fasting status and hormone use at blood draw. We applied Ingenuity Pathway Analysis and STRING analysis to identify pathophysiologic pathways and protein interactions.
Results:
Median age at blood draw was 17 years (interquartile range 15–19), and most participants were white race (90%). All had superficial peritoneal lesions only and were treated by excision or ablation. One-year post-surgery, pelvic pain worsened or persisted for 76 (54%) of these participants with endometriosis, while pelvic pain improved for 66 (46%). We identified 83 proteins associated with worsening or persistent pelvic pain one-year post-surgery (nominal p<0.05). Compared to those with improved pelvic pain one year post-surgery, those with worsening or persistent pelvic pain had higher plasma levels of CD63 antigen (OR=2.98, 95% CI:1.44–6.19) and CD47 (OR=2.68, 95%CI=1.28–5.61), but lower levels of Sonic Hedgehog protein (SHH; OR=0.55, 95%CI=0.36–0.84) in pre-surgical blood. Pathways related to cell migration were upregulated and pathways related to angiogenesis were downregulated in those with worsening/persistent post-surgical pelvic pain compared to those with improved pain. When we examined change in proteins levels from pre- to post-surgery and its subsequent risk of worsening/persistent post-surgical pain at one-year follow-up, we observed increasing levels of SHH from pre- to post-surgery was associated with four-fold increase in risk of post-surgical pain (OR quartile 4 vs. 1=3.86, 1.04–14.33).
Conclusion:
Using an aptamer-based proteomics platform, we identified plasma proteins and pathways associated with worsening or persistent pelvic pain post-surgical treatment of endometriosis among adolescents and young adults that may aid in risk stratification of individuals with endometriosis.
Keywords: pelvic pain, proteomics, endometriosis, adolescents, sonic hedgehog protein, surgery, EPHect, pain persistence
Tweetable statement:
Among adolescents and young adults with endometriosis, we identified plasma proteins and biological pathways dysregulated in pre-surgical blood associated with increased risk of worsening/persistent pelvic pain at one-year follow-up.
INTRODUCTION
Endometriosis is a chronic inflammatory condition with growth of endometrial-like tissue outside the uterus that often presents with severe pelvic pain, affecting about 10% of reproductive-aged women.1 While current conventional treatment for endometriosis is hormone therapy and surgical resection of endometriotic lesions,2 we and others have reported that about 30% of endometriosis patients suffer from chronic pelvic pain after standard of care treatment.3–6 Emerging evidence suggests central sensitization7 may play a role in chronic or persistent endometriosis-associated pain. For these women excision of the endometriotic lesions in the pelvis does not improve their pain. Currently there are no methods to predict response to surgical treatment prior to surgical intervention and the biological mechanisms driving surgical treatment resistance are not known.
For approximately two-thirds of women diagnosed with endometriosis in adulthood, their pelvic pain symptoms started during adolescence.8–10 Considering the chronic pain experience at a younger age increases risk of mental health disorders11 and opioid use disorder,12 predicting who will and will not respond to conventional treatments could provide new opportunities for improved personalized treatment and faster symptom improvement. Furthermore, defining the pathophysiology driving worsening/persistent pelvic pain after endometriosis-related surgery would provide new targets for treatment development. Thus, we sought to discover plasma proteomic profiles in pre-surgical blood samples associated with risk of worsening/persistent pelvic pain after surgery among adolescents and young adults with endometriosis.
MATERIALS AND METHODS
Study population
The Women’s Health Study: From Adolescence to Adulthood (A2A) is an ongoing observational longitudinal cohort that enrolled participants from 2012–2018, as described previously.6, 13–15 In brief, those with laparoscopically-confirmed endometriosis were identified from two tertiary academic hospitals. Of the 1,839 eligible participants approached, 1,569 (85%) enrolled. At baseline and Year 1 follow-up, an expanded version of the World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (WERF EPHect) standard clinical questionnaire16 was used to collect information including demographic characteristics, details on pelvic pain, treatment regimen, and medication use. Detailed clinical information was collected using an EPHect compliant surgical format time of endometriosis-related surgeries, including revised American Society for Reproductive Medicine (rASRM) score and medication use.17 All endometriosis patients had visualization and removal of endometriotic lesions by either excision or ablations techniques at surgery.18
Blood samples were collected at baseline and post-surgical follow-up [i.e. 5 weeks to 6 months after surgery, with the median for timing of post-surgical blood work being 16.3 weeks (IQR 12.3–19.7 weeks)] were collected, processed, and stored at ≤−80°C following the standard protocols of WERF EPHect fluid biospecimen collection19 with one exception - bloods were centrifuged at 1790 × g for 10 minutes. Detailed participant information at time of blood collection, such as fasting status and recent medication use, was collected using a biospecimen questionnaire.
Institutional Review Board (IRB) approval was provided by the Boston Children’s Hospital (BCH) and Brigham and Women’s Hospital IRBs. All participants provided written consent, with additional parental consent for participants <18 years old.
Defining pelvic pain worsening/persistence from pre-surgery to one-year post-surgery
Changes in pelvic pain symptoms from baseline to one-year post-surgery were calculated based on five acyclic pelvic pain variables and six dysmenorrhea variables assessing pain severity, frequency, and life interference assessed at the two timepoints (Supplemental Table 1).15 Among the 11 pain variables, change was dichotomized as pain symptoms worsened or persisted if any of the 11 pain variables worsened or if all symptoms persisted from baseline to Year 1 (i.e., >2 points in NRS score for severity and ≥ 1 category worsening for frequency and life interference). The changes were classified as pain symptoms improved if at least one of the pain symptoms improved and none of the other pain symptoms worsened from baseline to Year 1.
Covariates
Demographic and behavioral characteristics were collected at baseline, including age (years), self-reported race/ethnicity (white non-Hispanic, other race/ethnicity), analgesic use (never or regular use; regular use >1 dose per week for three months or longer), hormone use (no, yes), fasting status (no, yes), and rASRM stage (I/II, III/IV). Body mass index (BMI) was calculated from baseline height and weight and categorized as underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5–24.9 kg/m2), overweight (BMI 25–29.9 kg/m2), or obese (BMI ≥30 kg/m2) according to World Health Organization criteria for those ≥ 20 years old.20 For participants <20 years old, age specific BMI Z-score was calculated and categorized as underweight (Z-score ≤ −2), normal weight (>−2 to <1), overweight (1–2), or obese (>2).21 Hormone use and fasting status were obtained from the biospecimen questionnaire and reflect the status at time of blood draw. rASRM stage was assessed at laparoscopic surgery.
SomaScan Proteomics Assay
The 1.3k SomaScan Assay Kit was used to quantify relative protein levels in plasma (50μl)following the manufacturer’s standard protocol (SomaLogic; Boulder, CO), as described previously.22–24 Simultaneous measurement of 1,305 proteins was achieved using highly selective single-stranded Slow Off-rate Modified DNA Aptamers (SOMAmer), which was demonstrated to have high reproducibility and within-person stability over time.25 Most proteins included on this panel were circulating proteins involved in inflammatory/immune response, angiogenesis, and extracellular matrix. In parallel with the study participants’ plasma samples, we ran five pooled human plasma controls and one no-protein buffer control. Several hybridization spike-in controls were used to adjust for between sample variability. We conducted quality control, calibration, and normalization of the data as previously described.26 The 30 quality control (QC) samples which were blinded to the laboratory and were randomly distributed among the participants’ samples showed that 98% of proteins had intra-batch coefficient of variation (CVs) <25%, 99% had inter-batch CV <25%; there were no missing protein values.
Inclusion and exclusion
We enrolled 785 participants with surgically-confirmed endometriosis.6 Of the 785 participants with surgically-confirmed endometriosis, we excluded those who did not complete the baseline questionnaire (N=156), did not have a surgery at baseline (N=172), those who had an endometrioma(s) or deep lesion(s) (N=9), did not provide blood at baseline (N=180) or blood not collected within 90 days prior to the surgery (N=13), those whose blood was drawn more than 6 months from questionnaire completion (N=19) and those missing data on dysmenorrhea or acyclic pelvic pain (N=29). We further excluded those who did not complete the Year 1 questionnaire (N=54). Among the remaining 153 cases, we included those with post-surgical blood samples (N=89, collected 5 weeks to 6 months post-surgery) and randomly selected 53 additional cases, for a total of 142 participants with endometriosis (Supplemental Figure 1). There were only 20 (2.5%) participants with either endometrioma or deep endometriosis in the A2A study. The vast majority had superficial peritoneal lesions only, which is consistent with clinical presentation of endometriosis diagnosed in adolescents and young adults.6, 27, 28 We excluded patients with deep endometriosis a priori, because with such a small number of patients with anything other than superficial peritoneal only presentation, it was not possible in this population to compare and contrast the influence of different endometriosis macro phenotypes on the proteins predictive of persistent pelvic pain. At the sample size for this analysis, our power analysis estimate for type-I error at 0.05 the power estimate was 0.85 to detect an odd ratio of at least 1.7. When type-I error was set at 0.000038, the power estimate was only 0.13. We note that from our main results, most of the estimated odds ratio estimates were about 1.6 or above.
Statistical analysis
Multivariable logistic regression models adjusting for age at blood draw (years), BMI (underweight or normal, overweight or obese), hormone use at blood draw (no, yes), and fasting at blood draw (no, yes) were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) per one standard deviation (SD) increase in protein levels. False discovery rate (FDR)29 was used due to the large number of hypotheses being tested, each of which was based on the 1,305 SomaScan proteins. FDR-adjusted p-values were calculated to account for multiple testing. Among endometriosis patients with blood collected at two timepoints (pre-surgery and 5 weeks to 6 months post-surgery), we created quartiles based on relative percent change [i.e., 100*(post-surgery − pre-surgery) / pre-surgery] in protein levels at two timepoints for each protein and evaluated the association between the relative percent change in protein levels at two timepoints and the odds (risk) of worsening/persistent post-surgical pelvic pain at one-year follow-up.
Ingenuity Pathway Analysis (IPA) and functional category analysis of all dysregulated proteins with a p-value<0.05 from the logistic regression analysis (QIAGEN, Redwood City, CA) was used to identify biological pathways, as previously described. 22, 23, 30 The STRING database version 11.5 was used to identify protein-protein functional and physical interactions. These results were displayed as an interactive network31, with interactions considered with a STRING confidence score of ≥0.7 (out of 1.0) garnered from the “experimental” and “databases” categories. We removed proteins without associations to other proteins in the network. A k-means clustering algorithm was performed to select connected proteins (k-means/number of clusters=6). We conducted a manually curated evaluation of enriched KEGG pathway, Gene Ontology (GO), Reactome, STRING local network clusters terms, and PubMed literature search to assign functional description of the identified clusters.
All statistical analyses were performed using SAS/STAT version 9.4 (SAS Institute Inc., Cary, NC); systems biology analyses were performed using the Ingenuity Pathways Knowledge Base (Qiagen, Redwood City, CA).
RESULTS
Of the 142 participants with endometriosis, 76 (54%) reported their pelvic pain worsened or persisted (51 worsened and 25 persisted) and 66 (46%) reported their pelvic pain improved from pre-surgery (baseline) to one year follow-up (Year 1) (Table 1). Median age at blood draw was 17 years in both groups and most (>88%) were white race and on hormonal medications at time of blood draw. As expected, the majority (97%) were diagnosed with rASRM stage I or II. Of the 142 patients, 105 (74%) used hormones at one year follow-up and reported having no periods.
Table 1.
Baseline characteristics of 142 endometriosis patients in the A2A study.
Characteristics | Pain worsened or persisted (N=76) | Pain improved (N=66) |
---|---|---|
Age at blood draw, years, median (IQR) | 17 (15, 19) | 17 (15, 19) |
White race, n(%) | 67 (88) | 61 (92) |
Body mass index1, n(%) | ||
Normal | 48 (63) | 44 (67) |
Overweight | 22 (29) | 15 (23) |
Obese | 6 (8) | 7 (11) |
Taking hormonal medications at blood draw | 67 (88) | 60 (91) |
Fasting status | ||
Fasting | 21 (28) | 21 (32) |
Non-fasting/unknown | 55 (72) | 45 (68) |
Regular analgesic use2 | 44 (59) | 32 (51) |
rASRM stage | ||
Stage I/II | 74 (97) | 64 (97) |
Stage III/IV | 2 (3) | 2 (3) |
Abbreviations: A2A: The Women’s Health Study: From Adolescence to Adulthood
For women aged ≥20 years: underweight (BMI < 18.5 kg/m2), normal weight (BMI 18.5–24.9 kg/m2), overweight (BMI 25–29.9 kg/m2), or obese (BMI ≥ 30 kg/m2) according to World Health Organization criteria; For those <20 years, the age- and gender-specific BMI Z-score was calculated, and participants were categorized as underweight (Z-score ≤ −2), normal weight (Z-score >−2 to <1), overweight (Z-score 1–2), or obese (Z-score > 2).
Regular use of analgesic medications defined as use at least once a week for a period of three months or longer. Analgesic medications include aspirin, acetaminophen, nonsteroidal anti-inflammatory drugs, and narcotics.
Examining individual proteins, we identified 83 proteins significantly associated with worsening/persistent pelvic pain one-year post-surgery (unadjusted p<0.05; Table 2, Supplemental Table 2). In pre-surgical bloods, those with higher plasma levels of proteins suggesting activation of immune response [i.e., elevated CD63 (OR=2.98, 95% CI=1.44–6.19), CD47 (OR=2.68, 95%CI=1.28–5.61), and macrophage migration inhibitory factor (MIF) (OR=3.99, 95%CI=1.33–12.03)] had higher likelihood of experiencing worsening/persistent pelvic pain. Conversely, those with higher levels of parathyroid hormone (PTH) (OR=0.55, 95% CI: 0.37–0.80) and proteins that promote angiogenesis [e.g., SHH (OR=0.55, 95%CI=0.36–0.84), stromal cell-derived factor 1 (CXCL12) (OC=0.62, 95%CI=0.43–0.89)], and vascular endothelial growth factor A (VEGFA) (OR=0.61, 95%CI=0.43–0.89) were associated with lower likelihood of worsening/persistent pelvic pain one-year after surgery. When we examined the protein-protein interactions, several clusters of proteins were identified including proteins involved in angiogenesis, cell migration, activation of leukocytes, and neuropeptides (Figure 1). Consistent with these findings, pathway analysis revealed that those with worsening/persistent post-surgical pelvic pain had upregulation of pathways related to cell migration and downregulation of pathways related to angiogenesis compared to those with improved pain (Figure 2, Supplemental Table 3).
Table 2.
Individual proteins at baseline associated with worsening or persistent pelvic pain one-year after surgery
Top 15 proteins positively associated with worsening/persistent pain | |||
---|---|---|---|
Protein | Entrez Gene Symbol | Odds Ratio (95%CI)1 | p-value |
CD63 antigen | CD63 | 2.98 (1.44–6.19) | 0.003 |
Leukocyte surface antigen CD47 | CD47 | 2.68 (1.28–5.61) | 0.009 |
N-acetyl-D-glucosamine kinase | NAGK | 2.00 (1.19–3.37) | 0.009 |
Seizure 6-like protein 2 | SEZ6L2 | 1.94 (1.17–3.20) | 0.01 |
15-hydroxyprostaglandin dehydrogenase [NAD(+)] | HPGD | 1.63 (1.11–2.38) | 0.012 |
Angiopoietin-4 | ANGPT4 | 1.67 (1.11–2.50) | 0.013 |
Dickkopf-like protein 1 | DKKL1 | 2.46 (1.21–5.01) | 0.013 |
Macrophage migration inhibitory factor | MIF | 3.99 (1.33–12.03) | 0.014 |
Proteasome activator complex subunit 1 | PSME1 | 1.83 (1.10–3.04) | 0.019 |
Elongation factor 1-beta | EEF1B2 | 1.88 (1.11–3.20) | 0.02 |
14-3-3 protein theta | YWHAQ | 1.95 (1.11–3.43) | 0.02 |
Signal transducer and activator of transcription 6 | STAT6 | 1.54 (1.07–2.21) | 0.02 |
Cytokine receptor-like factor 2 | CRLF2 | 4.44 (1.25–15.77) | 0.02 |
cGMP-dependent 3’,5’-cyclic phosphodiesterase | PDE2A | 1.90 (1.09–3.28) | 0.02 |
Fibronectin Fragment 3 | FN1 | 1.63 (1.07–2.48) | 0.02 |
Top 15 proteins negatively associated with worsening/persistent pain | |||
Protein | Entrez Gene Symbol | Odds Ratio (95%CI)a | Unadjusted p-value |
Parathyroid hormone | PTH | 0.55 (0.37–0.80) | 0.002 |
WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2 | WFIKKN2 | 0.57 (0.39–0.84) | 0.004 |
Ciliary neurotrophic factor receptor subunit alpha | CNTFR | 0.59 (0.41–0.85) | 0.005 |
Sonic hedgehog protein | SHH | 0.55 (0.36–0.84) | 0.006 |
Ectodysplasin-A, secreted form | EDA | 0.24 (0.09–0.66) | 0.006 |
Lactadherin | MFGE8 | 0.61 (0.42–0.88) | 0.007 |
Mediator of RNA polymerase II transcription subunit 1 | MED1 | 0.61 (0.43–0.88) | 0.008 |
Netrin receptor UNC5D | UNC5D | 0.57 (0.38–0.87) | 0.009 |
Stromal cell-derived factor 1 | CXCL12 | 0.62 (0.43–0.89) | 0.009 |
Agouti-related protein | AGRP | 0.62 (0.43–0.89) | 0.01 |
Vascular endothelial growth factor A | VEGFA | 0.61 (0.43–0.89) | 0.01 |
Wnt inhibitory factor 1 | WIF1 | 0.60 (0.41–0.88) | 0.01 |
Plasma serine protease inhibitor | SERPINA5 | 0.49 (0.28–0.85) | 0.011 |
Ephrin-A4 | EFNA4 | 0.65 (0.46–0.92) | 0.016 |
Follistatin-related protein 3 | FSTL3 | 0.64 (0.44–0.92) | 0.017 |
FDR-adjusted p-values were non-statistically significant (>0.05) for all proteins.
Adjusted for age, BMI, fasting status, hormone use at blood draw.
Figure 1. Protein-protein interaction clusters and relevant pathways associated with worsening/persistent pelvic pain at Year 1 using STRING analysis (k-means = 6 clusters indicated by node color).
Protein-protein interaction network was created based on the 83 proteins that were significantly associated with worsening/persistent pelvic pain at Year 1 with unadjusted p-value <0.05. Related functional categories are labeled based on proteins with their reported functional involvement in the pathways of angiogenesis (red node), activation of leukocytes (green node), cell migration (light-green node), and neuropeptides (blue node). Solid line represents within-cluster, dashed gray line represents between-cluster interactions. Line thickness indicates strength of data support.
Figure 2. Biological pathways associated with risk of worsening/persistent pelvic pain one-year after surgery (p-value <1.3×10−12).
Biological pathways associated with risk of worsening/persistent pelvic pain are grouped by the direction of association (i.e., activation z-score) and presented within group ordered by p-value. Upregulated pathways are denoted by red bubbles and downregulated pathways are denoted by blue bubbles. Of the top 20 statistically significant pathways, three pathways (morphology of cardiovascular system, morphology of vasculature, and morphology of body cavity pathways) were removed due to activation z-score of 0.0.
Next, we examined the association between change in protein levels in blood samples collected before and after surgery and risk of worsening/persistent pelvic pain one-year after surgery in 89 with endometriosis. When comparing the lowest to highest quartile of the relative percent change in protein levels from pre- to post-surgery (or when comparing those whose protein levels decreased from pre- to post-surgery to those whose protein levels increased from pre- to post-surgery), there were 12 nominally significantly proteins associated with risk of worsening/persistent pelvic pain one-year after surgery, with 9 being associated with increased risk and 3 associated with decreased risk comparing extreme quartiles (Table 3). Of these, 9 proteins had significant linear trend (p-trend across 4 quartiles <0.05). Interestingly, only SHH was significantly associated with risk of worsening/persistent post-surgical pain (one year after surgery) in both pre-surgical blood and change from pre- to post-surgical blood. Compared to those who had ≤ −35.4% decreasing change in blood levels of SHH from pre- to post-surgery, those who had an increasing change of >21.6% had about four times greater risk of having post-surgical worsening/persistent pain at Year 1 (OR=3.86, 1.04–14.33; p-trend 0.03) (Figure 3). When comparing to those who had minimal change in SHH levels from pre- to post-surgery (percent change ranging from −10.8% to 21.6% from pre- to post-surgery), those who had an increasing change of >21.6% had about three times greater risk of having post-surgical worsening/persistent pain at Year 1 (OR=3.22, 95%CI=0.87–11.93).
Table 3.
Risk of worsening/persistent pelvic pain one-year after surgery with increasing protein levels in quartiles
Odds ratio (95%CI) of having worsening/persistent pelvic pain one-year after surgery by increasing change in proteins levels from pre- to post-surgery1 | ||||||
---|---|---|---|---|---|---|
Protein | Entrez Gene Symbol | Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | p-trend |
Interleukin-17 receptor B | IL17RB | ref | 2.73 (0.80–9.31) | 1.88 (0.54–6.58) | 4.74 (1.32–04.04) | 0.03 |
Inter-alpha-trypsin inhibitor heavy chain H4 | ITIH4 | ref | 1.46 (0.40–5.33) | 1.04 (0.29–3.71) | 4.86 (1.31–17.98) | 0.03 |
Cathepsin F | CTSF | ref | 0.58 (0.17–2.00) | 1.22 (0.34–4.43) | 0.21 (0.06–0.80) | 0.08 |
S-formylglutathione hydrolase | ESD | ref | 0.66 (0.19–2.30) | 0.56 (0.16–1.90) | 0.23 (0.06–0.81) | 0.01 |
Protein Wnt-7a | WNT7A | ref | 1.27 (0.38–4.23) | 2.35 (0.69–7.97) | 4.09 (1.12–14.95) | 0.02 |
Trypsin-3 | PRSS3 | ref | 1.49 (0.43–5.11) | 1.36 (0.40–4.60) | 3.86 (1.08–13.76) | 0.04 |
Sonic hedgehog protein | SHH | ref | 0.98 (0.30–3.23) | 1.20 (0.36–3.95) | 3.86 (1.04–14.33) | 0.03 |
Persulfide dioxygenase ETHE1, mitochondrial | ETHE1 | ref | 0.90 (0.27–3.03) | 1.90 (0.57–6.32) | 3.73 (1.04–13.43) | 0.03 |
Macrophage-capping protein | CAPG | ref | 0.43 (0.12–1.49) | 0.81 (0.23–2.89) | 0.28 (0.08–0.97) | 0.08 |
Leucine-rich repeat transmembrane neuronal protein 1 | LRRTM1 | ref | 1.19 (0.34–4.12) | 4.13 (1.16–14.70) | 3.57 (1.03–12.32) | 0.01 |
Glial fibrillary acidic protein | GFAP | ref | 2.52 (0.73–8.70) | 3.01 (0.88–10.38) | 3.60 (1.01–12.86) | 0.04 |
Thioredoxin domain-containing protein 12 | TXNDC12 | ref | 2.28 (0.66–7.91) | 1.68 (0.50–5.63) | 3.56 (1.00–12.63) | 0.09 |
25%tile, 50%tile, 75%tile cutoffs for increase in protein levels from pre-to post-surgery: IL17RB (−16.7%, −1.0%, 19.2%), ITIH4 (−6.2%, −0.1%, 7.4%), CTSF (−19.8%, −7.9%, 11.0%), ESD (−35.9%, −17.8%, 11.7%), WNT7A (−11.2%, 1.1%, 14.9%), PRSS3 (−6.1%, 0.8%, 12.0%), SHH (−35.4%, −1.08%, 21.6%), ETHE1 (−13.1%, −5.7%, 14.3%), CAPG (−11.6%, −1.7%, 13.0%), LRRTM1 (−8.9%, 0.8%, 14.8%), GFAP (−7.1%, 0.2%, 7.2%), TXNDC12 (−5.2%, 0.7%, 7.2%)
Figure 3. Relative percent change in Sonic hedgehog (SHH) protein levels across pre- and post-surgical blood collections and its association with subsequent risk of having persistent/worsening pain at 1-year post-surgery.
The table is showing the odds ratios (95% CIs) of having worsening/persistent pelvic pain one-year after surgery by increasing change in SHH levels in quartiles from pre- to post-surgery. The figure below is the plotting the change in SHH levels from pre- and post-surgery in each quartiles.
COMMENT
Principal Findings
Among adolescents and young adults with endometriosis, we discovered dysregulation of plasma proteins and biological pathways related to immune response, cell migration, and angiogenesis in pre-surgical bloods being associated with risk of worsening/persistent pelvic pain at one-year follow-up, providing evidence that there are differences in the systemic milieu prior to surgery indicative of response to surgical therapy of endometriosis. Furthermore, we examined the association between change in blood proteins levels from pre- to post-surgery with subsequent risk of having worsening/persistent pelvic pain at one-year follow-up and identified SHH as being significant in both analyses.
Results in the Context of What is Known
Emerging evidence supports that some women with endometriosis have pain central sensitization, therefore, conventional treatment that targets the endometriotic lesion fails to alleviate pain.32 To our knowledge, this is the first analysis that have comprehensively investigated pre-surgical plasma to discover risk biomarkers that are predictive of postoperative pain among endometriosis patients. Our results identified potential candidate biomarkers founding the basis for further investigation to develop blood-based biomarker signatures that will inform treatment response and provide biological support that inflammatory/immune signaling contributes to persistent pain after surgical treatment for endometriosis.
Elevation of several immune activation proteins in pre-surgery bloods were associated with increased risk of worsening/persistent post-surgical pain. CD63 is critical in leukocyte recruitment and an initiating inflammatory response.33, 34 CD47 is involved in transendothelial migration of neutrophils, monocytes, and dendritic cells, which are also important processes for inflammatory response.35 MIF is a pro-inflammatory cytokine involved in regulation of inflammatory responses through various functions including leukocyte recruitment and immune response with a previously described association with both endometriosis and pain.36, 37, 38 Moreover, MIF is a neuroendocrine modulator of inflammation and neuropathic pain and has been demonstrated to be essential for the development of neuropathic and inflammatory pain.39, 40 For instance, MIF levels are chronically and acutely elevated in patients with spinal cord injury, resulting in hyperactivation of nociceptors and neuropathic pain.41 These results together with the pathway analysis results showing upregulation of cell migration pathways and leukopoiesis suggest systemic immune dysfunction and promotion of neuropathic pain may play a role in the emergence and persistence of chronic pain.42, 43
In contrast, PTH, which was the top protein negatively associated with risk of worsening/persistent post-surgical pain, increases calcium levels in blood.44 Calcium is involved in neuronal plasticity,45 and plasmalemmal calcium signaling is involved in pain pathophysiology.46 Calcium signaling is also known to increase production of reactive oxygen species and ATP by mitochondria, and therefore may serve as regulator between these molecules and development of nociceptor sensitization.47 Nociceptors are sensory neurons that respond to potentially tissue-damaging stimuli. Nociceptor sensitization causes primary hyperalgesia, or increased pain produced by stimulation at the site of tissue insult. This is important because nociceptor sensitization is the trigger for initiation of an increase in excitability of central neurons in the nociceptive pathway or central sensitization.
Surprisingly, several proteins and pathways related to angiogenesis were downregulated in pre-surgical bloods of endometriosis patients with worsening/persistent post-surgical pain. Although studies suggest angiogenesis in the central nervous system is critical for developing central sensitization,48–50 diabetic neuropathy results due to destruction of vasculature supplying the peripheral nerves.51 A similar mechanism may play a role in endometriosis. Alternatively, those with angiogenic response may be those with more locally active endometriosis, as angiogenesis is required for persistence of endometriotic lesions.52 If pain is mostly due to the local endometriotic lesions, these patients may more benefit from surgical intervention, leading to less likelihood of suffering from worsening/persistent post-surgical pain.
Interestingly, the increase in SHH levels from pre- to post-surgery was associated with greater risk of post-surgical worsening/persistent pain at Year 1 and is consistent with studies reporting that the SHH signaling pathway is dysregulated in various chronic pain conditions, including cancer pain and neuropathic pain.53 The SHH signaling pathway activation has been reported to play a role in developing nociceptor sensitization.54 Another study has reported that SHH signaling activation contributed to chronic post-thoracotomy pain development via activating BDNF pathways in vivo.55 These results suggest that women with endometriosis who have increased SHH levels post-surgery may be developing nociceptor sensitization, leading to central sensitization and worsening/persistent pain one-year after their endometriosis surgery.
Clinical and research Implications
Pain is an unpleasant sensory and emotional sensation related with or similar to actual or potential tissue injury.56 Current treatment strategies focus on the endometriosis lesions and include surgical therapies aimed at excising the lesions or medical therapies that hormonally suppress them.7 However, at least 25% of afflicted women remain symptomatic and suffer persistent pain despite using these treatments,1, 57 leading to decreased quality of life and altered life course trajectories.58 Furthermore, women with endometriosis are at four times greater risk of chronic opioid use, dependence, and overdose compared to women without endometriosis.59 In fact, adolescents and young adult endometriosis patients (age<25 years) have a higher risk of becoming chronic opioid users compared to adult endometriosis patients.59 Therefore, optimal pain management in endometriosis patients, especially in adolescence, is critical and will have significant positive impact on clinical outcomes of endometriosis.
Our prospective study, comprehensively investigating the plasma proteome in relation to worsening/persistent post-surgical pain, is a critical step forward in developing a non-invasive tool that will inform surgical treatment response in these young endometriosis patients and could personalize treatment for endometriosis-associated pain. After replicating our findings in independent datasets, the ideal clinical assay should be based on multi-plex ELISA including <20 biomarkers, which would be more cost effective to predict post-surgical pelvic pain outcome. Furthermore, our findings together with mechanistic studies provide insight into the underlying biological pathways that may be involved in transitioning from acute to chronic pain and identify new therapeutic targets for persistent pain management. Future research is needed to validate our findings in independent datasets and mechanistic studies to elucidate the function of the identified proteins in development of post-surgical worsening/persistent pain in adolescents and young adults with endometriosis.
Strengths and Limitations
There are several strengths to this study. First, we applied a state-of-the art proteomics technology with high reproducibility, and comprehensively evaluated the plasma proteome to identify proteins associated with increased risk of worsening/persistent post-surgical pain in adolescents and young adults with endometriosis. Second, we focused on our unique study population of adolescents and young adults with deep phenotyping including detailed assessment of pain symptoms and prospective longitudinal study design. Third, we investigated changes in blood protein levels from pre- to post-surgery using bloods collected at two timepoints. However, our study population consisted mainly of white race and therefore generalizability may be limited. While this study is the most comprehensive proteomics analysis assessing proteins related to worsening/persistent post-surgical pain in endometriosis to our knowledge, there may be additional proteins that we were not able to evaluate on the SomaScan 1.3k platform and therefore were unable to detect their association with risk of persistent post-surgical pain. Validation of these results in an independent dataset is needed, although we believe this is a first critical step towards biomarker discovery for tailoring personalized treatment for endometriosis. Given that none of the individual proteins were statistically significantly associated with persistent post-surgical pain after multiple testing correction (all FDR>0.05), caution is warranted in interpretation of these results. However, we believe that this study provides initial evidence that there are likely differences in the blood proteome at pre-surgery that are predictive of post-surgical pain outcome among women with endometriosis. While the timing of the first post-surgical blood collection reflects the real-world and typical range of timing of first clinic return visit following surgical discharge, it is wide. This may drive toward the null the prediction of persistent pain for markers that are more dynamic during this window. A step toward establishment of clinically translational protein markers predictive of persistent pain should include studies that quantify change in these markers from week to week post-surgery and better define the optimal window for blood sample collection. Our results are valid and applicable to those patients with superficial peritoneal lesions only – the most common endometriosis subphenotype at all ages.60, 61 However, these results are not generalizable to patients with endometriomas or deep endometriosis; replication studies in populations oversampled for those endometriosis presentations are warranted to confirm similar or differing proteomic predictive pathways. Future studies are needed in populations deliberately designed to compare and contrast the proteome-defined pathways associated with persistent pain in those with superficial peritoneal endometriosis only and in those with deep endometriosis. While the surgical technique did not differ among these participants, post-surgical treatment was not standardized. However, this would not alter the pre-surgical proteome prediction of post-surgical persistence in pain, given that the clinician could not have considered the protein expression status in their treatment recommendations. From an epidemiologic methodological perspective, rather post-surgical treatment could act as a mediator (not a confounder) of the pre-surgical protein milieu and prediction of pain persistence one year after surgery.62 This does not alter or invalidate the interpretation of the present results but rather could be explored in studies intentionally designed to quantify mediating factors.
Conclusions
Our findings suggest that there are differences in the plasma proteome that could inform response to surgical treatment in endometriosis and provide novel biological evidence that inflammatory/immune signaling is playing a role in endometriosis patients developing worsening/persistent post-surgical pain. We observed that immune dysregulation prior to surgery and increase in blood SHH levels from pre- to post-surgery may be associated with increased risk of post-surgical worsening/persistent pain in adolescents and young adults with endometriosis. Further research is needed to validate in independent cohorts whether these proteomic markers are predictive of surgical treatment response in endometriosis patients.
Supplementary Material
Supplemental Figure 1. Overview of study design.
AJOG at a Glance:
A. Why was this study conducted?
To identify plasma proteins indicating pathophysiological mechanisms associated with persistent pelvic pain following laparoscopic surgery in adolescents and young adults with endometriosis using a multiplex aptamer-based proteomics biomarker discovery platform.
B. What are the key findings?
Among adolescents and young adults with endometriosis, we discovered plasma proteins and biological pathways dysregulated in pre-surgical blood samples that were associated with an increased risk of worsening or persistent pelvic pain at one-year follow-up.
C. What does this study add to what is already known?
These results provide evidence that there may be differences in the systemic milieu that could predict response to surgical treatment of endometriosis.
Acknowledgement:
The authors would like to thank the participants of the Women’s Health Study: From Adolescence to Adulthood for their valuable contributions and the staff of the Boston Center for Endometriosis.
Funding:
This study was supported by the Department of Defense W81XWH1910318 and the 2017 Boston Center for Endometriosis Trainee Award. Financial support for establishment of and data collection within the A2A cohort were provided by the J. Willard and Alice S. Marriott Foundation. N.S., A.F.V, S.A.M, K.L.T. have received funding from Marriott Family Foundation. N.S. and K.L.T. are supported by NICHD R21HD107266. S.A.M and K.L.T. are supported by NICHD R01HD094842.
Financial support:
This study was supported by the Department of Defense W81XWH1910318 and the 2017 Boston Center for Endometriosis Trainee Award. Financial support for establishment of and data collection within the A2A cohort were provided by the J. Willard and Alice S. Marriott Foundation. N.S., A.F.V, S.A.M, K.L.T. have received funding from Marriott Family Foundation. S.A.M and K.L.T. are supported by NICHD R01 HD94842.
Footnotes
Disclosure: N.S. and K.L.T. receive grant funding from Aspira Women’s Health unrelated to this project. S.A. has received consulting fees from Myovant (Sumitomo), Organon, and Bayer, unrelated to this project. S.A.M. receives grant funding from AbbVie, LLC, unrelated to this project.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Zondervan KT, Becker CM, Missmer SA. Endometriosis. N Engl J Med 2020;382:1244–1256. [DOI] [PubMed] [Google Scholar]
- 2.Becker CM, Bokor A, Heikinheimo O, et al. ESHRE guideline: endometriosis. Hum Reprod Open 2022;2022:hoac009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Abbott J, Hawe J, Hunter D, Holmes M, Finn P, Garry R. Laparoscopic excision of endometriosis: a randomized, placebo-controlled trial. Fertil Steril 2004;82:878–884. [DOI] [PubMed] [Google Scholar]
- 4.Abbott JA, Hawe J, Clayton RD, Garry R. The effects and effectiveness of laparoscopic excision of endometriosis: a prospective study with 2–5 year follow-up. Hum Reprod 2003;18:1922–1927. [DOI] [PubMed] [Google Scholar]
- 5.Coccia ME, Rizzello F, Palagiano A, Scarselli G. Long-term follow-up after laparoscopic treatment for endometriosis: multivariate analysis of predictive factors for recurrence of endometriotic lesions and pain. Eur J Obstet Gynecol Reprod Biol 2011;157:78–83. [DOI] [PubMed] [Google Scholar]
- 6.Sasamoto N, Shafrir AL, Wallace BM, et al. Trends in pelvic pain symptoms over 2 years of follow-up among adolescents and young adults with and without endometriosis. Pain 2023;164:613–624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.As-Sanie S, Black R, Giudice LC, et al. Assessing research gaps and unmet needs in endometriosis. Am J Obstet Gynecol 2019;221:86–94. [DOI] [PubMed] [Google Scholar]
- 8.Greene R, Stratton P, Cleary SD, Ballweg ML, Sinaii N. Diagnostic experience among 4,334 women reporting surgically diagnosed endometriosis. Fertil Steril 2009;91:32–39. [DOI] [PubMed] [Google Scholar]
- 9.Nnoaham KE, Hummelshoj L, Webster P, et al. Impact of endometriosis on quality of life and work productivity: a multicenter study across ten countries. Fertil Steril 2011;96:366–373.e368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Divasta AD, Vitonis AF, Laufer MR, Missmer SA. Spectrum of symptoms in women diagnosed with endometriosis during adolescence vs adulthood. Am J Obstet Gynecol 2018;218:324 e321–324 e311. [DOI] [PubMed] [Google Scholar]
- 11.Wrona SK, Melnyk BM, Hoying J. Chronic Pain and Mental Health Co-Morbidity in Adolescents: An Urgent Call for Assessment and Evidence-Based Intervention. Pain Manag Nurs 2021;22:252–259. [DOI] [PubMed] [Google Scholar]
- 12.Dash GF, Feldstein Ewing SW, Murphy C, Hudson KA, Wilson AC. Contextual risk among adolescents receiving opioid prescriptions for acute pain in pediatric ambulatory care settings. Addict Behav 2020;104:106314. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Sasamoto N, Depari M, Vitonis AF, et al. Evaluation of CA125 in relation to pain symptoms among adolescents and young adult women with and without surgically-confirmed endometriosis. PLoS One 2020;15:e0238043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Sasamoto N, Farland LV, Vitonis AF, et al. In utero and early life exposures in relation to endometriosis in adolescents and young adults. Eur J Obstet Gynecol Reprod Biol 2020;252:393–398. [DOI] [PubMed] [Google Scholar]
- 15.Shafrir AL, Vitonis AF, Wallace B, et al. Cohort profile: The Endometriosis pain QUality aftEr Surgical Treatment (EndoQUEST) Study. PLoS One 2022;17:e0269858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Vitonis AF, Vincent K, Rahmioglu N, et al. World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project: II. Clinical and covariate phenotype data collection in endometriosis research. Fertil Steril 2014;102:1223–1232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Becker CM, Laufer MR, Stratton P, et al. World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project: I. Surgical phenotype data collection in endometriosis research. Fertil Steril 2014;102:1213–1222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Taylor HS, Adamson GD, Diamond MP, et al. An evidence-based approach to assessing surgical versus clinical diagnosis of symptomatic endometriosis. Int J Gynaecol Obstet 2018;142:131–142. [DOI] [PubMed] [Google Scholar]
- 19.Rahmioglu N, Fassbender A, Vitonis AF, et al. World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project: III. Fluid biospecimen collection, processing, and storage in endometriosis research. Fertil Steril 2014;102:1233–1243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Eveleth PB. Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. American Journal of Human Biology 1996;8:786–787. [Google Scholar]
- 21.Barlow SE. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 2007;120 Suppl 4:S164–192. [DOI] [PubMed] [Google Scholar]
- 22.Sasamoto N, Ngo L, Vitonis AF, et al. Circulating proteomic profiles associated with endometriosis in adolescents and young adults. Hum Reprod 2022;37:2042–2053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sasamoto N, Ngo L, Vitonis AF, et al. Plasma proteomic profiles of pain subtypes in adolescents and young adults with endometriosis. Hum Reprod 2023;38:1509–1519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Shubin AV, Kollar B, Dillon ST, Pomahac B, Libermann TA, Riella LV. Blood proteome profiling using aptamer-based technology for rejection biomarker discovery in transplantation. Sci Data 2019;6:314. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Kim CH, Tworoger SS, Stampfer MJ, et al. Stability and reproducibility of proteomic profiles measured with an aptamer-based platform. Sci Rep 2018;8:8382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hathout Y, Brody E, Clemens PR, et al. Large-scale serum protein biomarker discovery in Duchenne muscular dystrophy. Proc Natl Acad Sci U S A 2015;112:7153–7158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Shim JY, Laufer MR. Adolescent Endometriosis: An Update. J Pediatr Adolesc Gynecol 2020;33:112–119. [DOI] [PubMed] [Google Scholar]
- 28.ACOG Committee Opinion No. 760: Dysmenorrhea and Endometriosis in the Adolescent. Obstet Gynecol 2018;132:e249–e258. [DOI] [PubMed] [Google Scholar]
- 29.Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological) 2018;57:289–300. [Google Scholar]
- 30.Krämer A, Green J, Pollard J Jr, Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 2013;30:523–530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019;47:D607–d613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Orr NL, Huang AJ, Liu YD, et al. Association of Central Sensitization Inventory Scores With Pain Outcomes After Endometriosis Surgery. JAMA Netw Open 2023;6:e230780. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Doyle EL, Ridger V, Ferraro F, Turmaine M, Saftig P, Cutler DF. CD63 is an essential cofactor to leukocyte recruitment by endothelial P-selectin. Blood 2011;118:4265–4273. [DOI] [PubMed] [Google Scholar]
- 34.Poeter M, Brandherm I, Rossaint J, et al. Annexin A8 controls leukocyte recruitment to activated endothelial cells via cell surface delivery of CD63. Nat Commun 2014;5:3738. [DOI] [PubMed] [Google Scholar]
- 35.Hayat SMG, Bianconi V, Pirro M, Jaafari MR, Hatamipour M, Sahebkar A. CD47: role in the immune system and application to cancer therapy. Cell Oncol (Dordr) 2020;43:19–30. [DOI] [PubMed] [Google Scholar]
- 36.Sumaiya K, Langford D, Natarajaseenivasan K, Shanmughapriya S. Macrophage migration inhibitory factor (MIF): A multifaceted cytokine regulated by genetic and physiological strategies. Pharmacol Ther 2022;233:108024. [DOI] [PubMed] [Google Scholar]
- 37.Elbaradie SMY, Bakry MS, Bosilah AH. Serum macrophage migration inhibition factor for diagnosing endometriosis and its severity: case-control study. BMC Womens Health 2020;20:189. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Morin M, Bellehumeur C, Therriault MJ, Metz C, Maheux R, Akoum A. Elevated levels of macrophage migration inhibitory factor in the peripheral blood of women with endometriosis. Fertil Steril 2005;83:865–872. [DOI] [PubMed] [Google Scholar]
- 39.Baugh JA, Donnelly SC. Macrophage migration inhibitory factor: a neuroendocrine modulator of chronic inflammation. J Endocrinol 2003;179:15–23. [DOI] [PubMed] [Google Scholar]
- 40.Alexander JK, Cox GM, Tian JB, et al. Macrophage migration inhibitory factor (MIF) is essential for inflammatory and neuropathic pain and enhances pain in response to stress. Exp Neurol 2012;236:351–362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Bavencoffe AG, Spence EA, Zhu MY, et al. Macrophage Migration Inhibitory Factor (MIF) Makes Complex Contributions to Pain-Related Hyperactivity of Nociceptors after Spinal Cord Injury. J Neurosci 2022;42:5463–5480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Chambel SS, Tavares I, Cruz CD. Chronic Pain After Spinal Cord Injury: Is There a Role for Neuron-Immune Dysregulation? Front Physiol 2020;11:748. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Generaal E, Vogelzangs N, Macfarlane GJ, et al. Basal inflammation and innate immune response in chronic multisite musculoskeletal pain. Pain 2014;155:1605–1612. [DOI] [PubMed] [Google Scholar]
- 44.Matikainen N, Pekkarinen T, Ryhanen EM, Schalin-Jantti C. Physiology of Calcium Homeostasis: An Overview. Endocrinol Metab Clin North Am 2021;50:575–590. [DOI] [PubMed] [Google Scholar]
- 45.Bravo-Sagua R, Parra V, Lopez-Crisosto C, Diaz P, Quest AF, Lavandero S. Calcium Transport and Signaling in Mitochondria. Compr Physiol 2017;7:623–634. [DOI] [PubMed] [Google Scholar]
- 46.Bourinet E, Altier C, Hildebrand ME, Trang T, Salter MW, Zamponi GW. Calcium-permeable ion channels in pain signaling. Physiol Rev 2014;94:81–140. [DOI] [PubMed] [Google Scholar]
- 47.Yousuf MS, Maguire AD, Simmen T, Kerr BJ. Endoplasmic reticulum-mitochondria interplay in chronic pain: The calcium connection. Mol Pain 2020;16:1744806920946889. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Wen ZH, Huang SY, Kuo HM, et al. Fumagillin Attenuates Spinal Angiogenesis, Neuroinflammation, and Pain in Neuropathic Rats after Chronic Constriction Injury. Biomedicines 2021;9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Hu XM, Yang W, Du LX, et al. Vascular Endothelial Growth Factor A Signaling Promotes Spinal Central Sensitization and Pain-related Behaviors in Female Rats with Bone Cancer. Anesthesiology 2019;131:1125–1147. [DOI] [PubMed] [Google Scholar]
- 50.Lin J, Li G, Den X, et al. VEGF and its receptor-2 involved in neuropathic pain transmission mediated by P2X₂(/)₃ receptor of primary sensory neurons. Brain Res Bull 2010;83:284–291. [DOI] [PubMed] [Google Scholar]
- 51.Sharma A, Behl T, Sharma L, et al. Exploring the molecular pathways and therapeutic implications of angiogenesis in neuropathic pain. Biomed Pharmacother 2023;162:114693. [DOI] [PubMed] [Google Scholar]
- 52.Groothuis PG, Nap AW, Winterhager E, Grummer R. Vascular development in endometriosis. Angiogenesis 2005;8:147–156. [DOI] [PubMed] [Google Scholar]
- 53.Zheng G, Ren J, Shang L, Bao Y. Sonic Hedgehog Signaling Pathway: A Role in Pain Processing. Neurochem Res 2023;48:1611–1630. [DOI] [PubMed] [Google Scholar]
- 54.Babcock DT, Shi S, Jo J, Shaw M, Gutstein HB, Galko MJ. Hedgehog signaling regulates nociceptive sensitization. Curr Biol 2011;21:1525–1533. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Yang Y, Wang X, Zhang X, et al. Sonic Hedgehog Signaling Contributes to Chronic Post-Thoracotomy Pain via Activating BDNF/TrkB Pathway in Rats. J Pain Res 2020;13:1737–1746. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Raja SN, Carr DB, Cohen M, et al. The revised International Association for the Study of Pain definition of pain: concepts, challenges, and compromises. Pain 2020;161:1976–1982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Becker CM, Gattrell WT, Gude K, Singh SS. Reevaluating response and failure of medical treatment of endometriosis: a systematic review. Fertil Steril 2017;108:125–136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Culley L, Law C, Hudson N, et al. The social and psychological impact of endometriosis on women’s lives: a critical narrative review. Hum Reprod Update 2013;19:625–639. [DOI] [PubMed] [Google Scholar]
- 59.Chiuve SE, Kilpatrick RD, Hornstein MD, et al. Chronic opioid use and complication risks in women with endometriosis: A cohort study in US administrative claims. Pharmacoepidemiol Drug Saf 2021;30:787–796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Bean E, Naftalin J, Horne A, Saridogan E, Cutner A, Jurkovic D. Prevalence of deep and ovarian endometriosis in early pregnancy: ultrasound diagnostic study. Ultrasound Obstet Gynecol 2022;59:107–113. [DOI] [PubMed] [Google Scholar]
- 61.Orlov S, Jokubkiene L. Prevalence of endometriosis and adenomyosis at transvaginal ultrasound examination in symptomatic women. Acta Obstet Gynecol Scand 2022;101:524–531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Farland LV, Correia KFB, Dodge LE, et al. The importance of mediation in reproductive health studies. Hum Reprod 2020;35:1262–1266. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental Figure 1. Overview of study design.