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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Anesthesiology. Author manuscript; available in PMC 2012 April 1.
Published in final edited form as:
PMCID: PMC3063327
NIHMSID: NIHMS274782

Beta-2- Adrenergic Receptor Genotype and Other Variables that Contribute to Labor Pain and Progress

Elena Reitman, M.D., Clinical Fellow, Jessamyn Conell-Price, B.A., Research Coordinator, Jennifer Evansmilth, Undergraduate Student, Luke Olson, B.A., Research Coordinator, Sofia Drosinos, M.D., Assistant Clinical Professor, Nancy Jasper, M.D., Assistant Clinical Professor, Paula Randolph, M.D., Assistant Clinical Professor, Richard Smiley, PhD, M.D., Professor of Clinical Anesthesiology, Steven Shafer, M.D., Professor of Anesthesiology, and Pamela Flood, M.D., Associate Professor of Clinical Anesthesiology

Abstract

Background

Beta-2-adrenergic receptor (β2AR) activity influences labor and its genotype affects the incidence of preterm delivery. We determined the effect of β2AR genotype on term labor progress and pain.

Methods

We prospectively enrolled 150 nulliparous parturients in the third trimester and obtained sensory thresholds, demographic information and DNA. Cervical dilation, pain scores and labor management data were extracted with associated times. The association of genetic and demographic factors with labor was tested with mixed effects models.

Results

Parturients who express Gln at the 27 position of the β2AR had slower labor (P<0.03). They progressedfrom 1–10cm dilation in approximately 21 hours compared to 14 hours in otherpatients. Asian ethnicity, previously associated with slower labor, is highly associated with this polymorphism (P<0.0001). Heavier and Black patients had slower latent labor (P<0.01, 0.01) and neuraxial analgesia was associated with slower labor progress (P<0.0001). It could take up to 36 hours for the heaviest and the Black parturients to transition from 1cm cervical dilation to active labor; however once the active phase began, labor rate was the same as other patients’.

Conclusion

We detected a strong association between β2AR genotype and slower labor. Asian ethnicity may be a proxy for β2AR genotype. Black and heavy women have slower latent labor. These results confirm many of the associations found when this mathematical model was applied to a large retrospectivecohort, further validating this approach to description and analysis of labor progress.

Introduction

Term labor and delivery occurs tens of millions of times a year yet is remarkably poorly understood. Labor that begins prematurely or proceeds too slowly or too rapidly poses serious risks for the mother and profound risks to the fetus. Labor progress is highly variable among women. Studies that have looked at demographic influences on labor progress have only found a few significant differences that explain a small degree of the overall variability among women 14. Slow labor progress is a common cause of cesarean delivery, the incidence of which has been increasing dramatically in recent years 5.The high rate of cesarean section has caused a strain on health care resources and has likely resulted in increased incidence of abnormal placentation and postpartum hemorrhage 6. Our previous work with a biexponential mathematical model of labor demonstrated several factors associated with slower labor including greater maternal weight, Asian ethnicity and neuraxial analgesia 4.

Uterine contractility is modulated by several factors including endogenous catecholamines that activate beta-2 adrenergic receptors (β2ARs). The β2AR has 2 common polymorphisms in the coding region, at codons 16 (p.Arg16Gly) and 27 (p.Gln27Glu), that have been shown to influence receptor function in a clinically significant manner 7. We hypothesized that genotype of the β2AR may influence the course of human labor.

The experience of pain during labor is influenced by labor progress and also varies greatly among women. We have previously shown that a faster rate of cervical dilation predicts faster development of pain, and that Asian ethnicity predicts slower development of pain during labor 4. The μ-opioid receptor (OPRM1) is a target for both endogenous and exogenous opioid agonists. The gene has a common polymorphism at nucleotide 118 (codon 40, p.Asp40Asn) which is thought to impact on baseline pain sensitivity 8,9 and has been shown to affect the efficacy of fentanyl spinal analgesia in human labor10. We hypothesize that this polymorphism may impact on the experience of labor pain.

We prospectively enrolled a nulliparous cohort from a single private practice who underwent quantitative behavioral testing for baseline pain sensitivity, provided demographic information, and provided a DNA sample, in order to identify factors that affect labor progress and pain. This study was designed to use previously described mathematical models 4,11 to test the hypotheses that polymorphisms in the β2AR would be associated with different rates of labor progress and that the p.Asp40Asn polymorphism in the opioid receptor would be predictive of the development of labor pain. Furthermore, we hypothesized that we would be able to predict the magnitude of pain in the upcoming labor with quantitative behavioral pain testing during the third trimester of pregnancy.

Materials and Methods

This prospective cohort study was approved by the Institutional Review Board of Columbia University Medical Center(New York, NY). One hundred and fifty parturients were recruited from a single private obstetrical practice (S.D., N.J. and P.R.) during a third trimester office visit. Eligible for inclusion were healthy nulliparous parturients aged 18–45, gestational age 24–36 weeks who planned vaginal delivery. Patients with intrauterine growth restriction, fetal malformations, preeclampsia, and planned cesarean sections were excluded. All subjects provided written informed consent. At the enrollment visit, patients completed a demographic questionnaire, underwent quantitative pain sensitivity testing, and provided a blood sample for genotyping.

Quantitative Behavioral Testing

Pressure sensitivity was tested using an electronic Von Frey Analgesiometer (IITC Life Science, Woodland Hills, CA), a pressure transducer attached to a sterile, blunt 1 mm wide plastic tip. Graded pressure was applied via the plastic tip to the bony aspect of the subject’s non-dominant shin. The subject was instructed to indicate when the stimulus first became painful. The pressure at which pain was first reported was recorded as the “pressure threshold.”

Heat and cold sensitivity were tested using a Neurosensory Analyzer TSAII (Medoc, Durham, NC). A 30mm temperature probe was applied to the thenar eminence of the non-dominant hand. A computer-driven program increased or decreased temperature of the probe by 1 degree per second from 30 °C – 50 °C (heat threshold) and 30°C - 0 °C (cold threshold). The subject was instructed to click a mouse button with the other hand when the temperature became painful, which immediately terminated the stimulation. The temperature at which the test was terminated was recorded as the heat or cold threshold. Each test was completed in triplicate on each subject for all sensory modalities. The results of the replicate tests for each individual were averaged.

Genotyping

A 10 ml blood sample was obtained and stored for DNA extraction and analysis. Genomic DNA was extracted with a Wizard Genomic DNA Purification Kit, (Promega, Madison, WI) according to the manufacturer’s instructions. The genotype at two known polymorphic sites on the β2AR (rs1042713,rs1042714, corresponding to codons 16 and 27) and one site on the OPRM1 gene (rs1799971, codon 40) was determined at the University of Geneva, Switzerland as we have previously described 12,10

Labor Management

Demographic variables including maternal age, height, and self-reported ethnicity were recorded at enrollment. Self-reported ethnicity was queried according to categories derived from the 2000 census. Patients were asked to choose only one category from the choices that included: Asian, Black, Hispanic, White, and Other. Maternal weight, gestational age, and infant weight and treatment variables were recorded at delivery.

Labor was managed by three attending obstetricians from the practice group (S.D., N.J. and P.R.) with support from hospital OB/GYN residents. Generally, labor was managed with a standard clinical protocol with cervical examination every 4 hours during latent labor and every 2 hours during active labor unless otherwise clinically indicated. Timed cervical exams were recorded. Labor induction, oxytocin augmentation, and the time of membrane rupture were recorded. The time, type and amount of any pain treatments were recorded. The mode of delivery (normal spontaneous vaginal delivery, operative vaginal delivery with vacuum or forceps, or cesarean section during the first stage or after full dilation) was recorded. Patients who underwent cesarean section during the first stage of labor were not included in our analysis as full dilation is required in our model for temporal alignment of the labor progress data.

On enrollment, patients were instructed in the use of a numerical rating score for pain, ranging from 0 (no pain) to 10 (worst pain imaginable). They were told that they would be asked for a pain score relating to the pain at peak contraction. Pain scores were recorded by the patient’s nurse on arrival in the labor and delivery suite, at every change in condition, and prior to initiation of analgesia. Pain scores were not recorded or analyzed for the purposes of this study after the patient received analgesia.

Data Analysis and Statistics

Demographic and obstetrical characteristics were compared among self-identified ethnic groups because of our previous finding of differences in labor pain and progress based on ethnicity 4. Incidence datais reported as a percent and compared using a chi-square analysis (Stata 10.1, Statacorp, College Station, TX). The distribution of the three genotypes was assessed according to ethnic group because of previously reported ethnic differences in β2AR 13and OPRM1 genotype incidence14. To identify ethnic differences in genotypic distribution, each ethnic group's characteristics were compared to the total cohort’s characteristics using chi-square analysis. Continuous data are reported as median and Interquartile Range. Differences in continuous variables are compared with a Mann-Whitney test for two group comparisons or a Kruskal-Wallis test for three or more groups (GraphPadInStat 3.06, San Diego, CA). P < 0.05 was considered significant in all analyses.

Labor Progress Model

Labor progress was analyzed using the bi-exponential model for labor progress previously derived and validated by Debiec et al.4 using NONMEM (Nonlinear Mixed-Effects Modeling; Globomax, Ellicott City, MD) with PLT Tools (PLT Soft, San Francisco, CA). This structural model requires estimation of only 3 variables, a rate constant for latent labor, a rate constant for active labor and the cervical dilation at which transition between the latent and active phases occurs.

Each genetic, demographic and treatment variable was first tested independently to determine whether it was predictive of a significant difference in active labor rate constant, latent labor rate constant or cervical dilation at transition. The most parsimonious combination was determined for each effect. The factors tested for potential inclusion in the final model were β2AR genotype, ethnicity, maternal age, height and weight, gestational age, infant weight, mode of delivery and time of membrane rupture, oxytocin treatment and neuraxial analgesia. The factors that statistically improved the model individually were further considered for inclusion into the final model in rank order of statistical significance. Factors that significantly improved the model after correction for the next strongest affect were maintained in the final model.

Because genotype was significantly correlated with ethnicity (e.g., none of the self-reported Asians had genotype at β2AR27-GG), so two final models were constructed so that ethnicity and β2AR genotype could be considered separately after correction for other factors.

The bias in the model describes whether the model generally over- or under-predicts the actual measured values. Bias was calculated as the median prediction error (MPE), MPE = Median ((measured – predicted) / predicted). Inaccuracy was defined as the median absolute prediction error (MAPE), MAPE = Absolute value (Median ((measured – predicted) / predicted)). MAPE is a measure of how close the typical observation is to the predicted value.

Cumulative Probability Evaluation

Mixed effects models are extremely sensitive and have the potential to detect real effects that are statistically significant but that are too small to be clinically relevant. The effect size that is clinically relevant may differ among clinicians and clinical situations. In order to give clinicians a way to assess the absolute size of differences taking statistical confidence into account, we constructed “cumulative probability graphs”. The details of their construction are included in an Appendix 1. Briefly, the value of the variable being compared (for example, latent labor rate constant, active labor rate constant, transition point, or the effect of a continuous variable like maternal weight on the previous variables) is displayed on the x-axis and the cumulative probability of the true value being at least that value is on the denoted on the y-axis (from 0–1). The most likely value is located at 0.5, denoted by a solid horizontal line. Thus, the probability of any difference that the clinician thinks is potentially important can be determined visually.

Labor Pain Model

The effect of genetic, demographic and treatment variables on labor pain were assessed with a sigmoidal model with NONMEM using PLT Tools that we have previously described in detail. 4,15 The sigmoidal labor pain model requires 4 variables, Numerical Rating Scale (NRSMIN), representing pain in early labor, NRSMAX, representing pain in late labor, γ, a slope function which represents the rate of increase in pain during labor and the closely related but unintuitive CD50, which is the cervical dilation at which pain has increased to 50% of maximal pain.

Similar to the modeling process for labor progress, each genetic, demographic and treatment variable was first tested independently to determine whether it was predictive of a significant difference in NRSMIN, NRSMAX, γ and CD50 and the best model was determined for each factor. In addition to OPRM1 genotype, the same demographic and obstetric factors were tested in the pain model as in the progress model, except that neuraxial analgesia was not included because pain scores were not recorded after analgesia.

We considered the variability between patients (interindividual variability) on NRSMINand NRSMAX as additive factors (i.e. an individual’s NRSMINandNRSMAXcould be larger or smaller than the nominal (population) value by an amount added or subtracted), and we used an exponential model for the inter-individual variability in CD50. No inter-individual variability was modeled for slope function because it could not be estimated. The residual error that does not represent true differences between individuals but rather random measurement error) was additive. Confidence in each covariate included in the labor pain model was assessed with cumulative probability graphsas described for the labor progress model.

Sample Size Calculation

The study was powered to detect a difference induced by a genetic covariate of two NRS units with a variance of 2, similar to the magnitude of effect we found in our previous studies 15. The prevalence of the p.Arg16Arghomozygous genotypes is about 20%, and that of p.Glu27Glu about 10–12%. The minor allele (Glu) at codon 27 has an incidence of about 35%, and the minor allele at 16 (Arg) is about 45% 16. For OPRM1, allele frequency for Asn (the G nucleotide) is about 30% in Caucasians and 60% in Asians 17,18. As such, we recruited 150 patients to have ~100 vaginal deliveries with analyzable data; this provides 80% power to detect a difference of 2 NRS units with a variance of 2 at P<0.05.

Web Supplement

The full data setfor all the patients used in the study (supplemental digital content 1), NONMEM control files (supplemental digital content 2) for the final labor progress and labor pain models and diagnostic graphics of the model (supplemental digital content 3) are provided.

Results

Two hundred and fifteen women were screened for enrollment between 09/28/06 and 11/06/08. One hundred and fifty women were enrolled, and 103 women had labor that progressed to full dilation. The analyzed data set thus contains data from 103 women. The screening and enrollment patient flow sheet is shown in figure 1. Of 103 patients with analyzable data 14 were Asian, 11 were Black, 10 were Hispanic, 67 were White, and one reported being in the “Other” category. There was no difference in maternal age, weight, height, gestational age at delivery, or newborn weight according to ethnicity (table1). Patients received 4–7 (median 5) cervical exams during the first stage of labor. 26% of patients had induced labor, and 57% of patients had spontaneous rupture of membranes. Patients provided 1–3 (median 2) pain scores before analgesia. 96% of patients had neuraxial analgesia initiated at some point during the first stage of labor (table 2).

Fig 1
Screening and enrollment
Table 1
Demographic Characteristics of 103 Nulliparous Women That Became Fully Dilated
Table 2
Labor Characteristics for 103 Nulliparous Women

All women were genotyped for two polymorphisms in the β2AR gene, p.Arg16Gly and p.Gln27Glu. Sixty-five of the 103 patients who reached full dilation were also genotyped for the p.Asp40Asn polymorphism in the OPRM1. Genotyping of OPRM1 was added after the initiation of the study and thus consent was not requested from all participants, hence the incomplete genotyping for the OPRM1 gene. All resulting genotypes were within the expected Hardy-Weinberg equilibrium within the population as a whole and for each ethnic group. However, fewer than expected Asians expressed Glu at β2AR27 position (P<0.01) (table 3). Asian ethnicity thus functions as a proxy for expression of Gln at the 27 position of the β2AR. Because both Asian ethnicity and β2AR-27 genotype were individually predictive of the transition point between active and latent labor, separate alternative final models were created to allow consideration of the effect of both factors individually as they would likely be collinear and inject instability in any model containing both variables. As has been previously reported 10,19 Asians were also more likely than patients of other ethnicities to express the minor allele (G) at OPRM1 (P<0.001).

Table 3
Genetic Characteristics by Ethnicity

Labor Progress Model

The biexponential model for labor progress was unbiased (MPE = 0.0cm), with an inaccuracy (MAPE) of 0.94 cm (Figure 2A, table 4). Vertical bars represent measured data and solid squares the prediction by the model. When assessed independently, maternal weight, ethnicity, genotype at β2AR27 position, and the presence of neuraxial analgesia were significant covariates (table 4).

Fig 2
Labor Progress Population Models
Table 4
Labor Progress Model.

Since all of the Asian patients expressed at least one C at the p-β2AR-27 position, genotype and ethnicity could not be considered together in one model. As such, two final models were created: one optimized for ethnicity and the other was optimized for genotype. The results of the final model optimized for genetic information are shown in Figure 2B. The genetically optimized model showed that patients with β2AR27 genotype CC (p.Gln27Gln) transition to active labor at 3.92 (2.95–4.50) cm while patients with other genotypes at β2AR27 gene (CG and GG) transition to active labor earlier, at 2.73 (1.85–3.60) cm. The model also shows that heavier parturients had slower latent labor; their latent rate labor constants were lower by 0.01 hr−1(0.0017-0.02) per pound that they weighed more than median maternal weight. The active rate constant was very slightly increased by 0.007 hr−1 for each maternal pound (0.002–0.015). The epidural time scale factor is 0.29 (0.17–0.42), which means thatlabor progress is slower in the setting of earlier neuraxial analgesia. Specifically, the expected duration of labor in a parturient in whichneuraxial analgesia was not present is approximately 1/3rd of the time observed in the presence of neuraxial analgesia.

The final model remained unbiased (MPE = 0.00 cm) and was made more accurate (MAPE = 0.74 cm) by the consideration of β2AR genotype, maternal weight and neuraxial analgesia. At baseline our biexponential model of labor progress was off by 0.95cm. A residual error of 0.45cm can be attributed to random variability such as measurement error, rather than to true differences between individuals (individual post hoc Bayesian fit). As such, consideration of β2AR genotype, maternal weight, and neuraxial analgesia predicted 42% of the difference in labor progress between individuals, with 58% of the variability between individuals remaining to be explained by other, perhaps genetic or environmental factors.

The final model optimized for ethnicity is shown in Figure 2C. The ethnicity-optimized model showed that Black women have a very slow rate of latent labor 0.01 hr−1 (−0.13 to 0.07, table 4) compared to non-Black women who have a latent labor rate constant of 0.08 hr−1 (0.02–0.16). Asian patients transition to active labor later than other patients, at 5.2 (3.7–7.0) cm compared to 3.3 (2.52–4.20) cm. The model optimized for ethnicity also finds that neuraxial analgesia is associated with prolonged labor progress by 0.32 (0.23–0.47). The model is unbiased (MPE = 0.00 cm) and more accurate (MAPE = 0.72 cm) than the model without covariates.

Figure 3 shows the cumulative probability distributions for each parameter tested in the genetically optimized model. This method was used to determine the 95% confidence interval for each variable. The solid line at 50% probability marks the most likely value for each parameter and the dotted vertical lines denote the range of 95% probability. The irregularity seen in the curve represents the regression program, NONMEM, finding a local minimum rather than a global minimum. It is an artifact in the analysis, and does not have any clinical meaning. Figure 4 shows the probability distribution for a range of values for each variable tested in the ethnicity optimized model.

Fig 3
Cumulative Probability Curves - genetically optimized model
Fig 4
Cumulative Probability Curves - ethnicity optimized model

Labor Progress Simulations

Figure 5A shows simulations for labor progress in the genetically optimized model. The X-axis in figure 5A shows the progress of labor from 1 cm cervical dilation (time runs forward in a normal way). The nominal patient is a patient with β2AR CG or GG genotype of median weight without neuraxial analgesia. Labor progress for patients with β2AR genotype CC is shown in turquoise color. The predicted labor progress for the lightest patient (120 lbs) is shown in the magenta line. The predicted labor progress for the largest patient (326 lbs) is shown in the dark green line. The predicted labor progress for a patient who had neuraxial analgesia placed at 4 cm is shown in solid blue line and at 1 cm is shown in dotted blue line.

Fig 5
Simulations of labor progress with impact of significant covariates

Figure 5B shows simulations for labor progress for the ethnicity optimized model. The nominal patient is non-Asian, non-Black, and without neuraxial analgesia. The predicted labor progress for Asian patient is shown in red line. The labor progress for Black patient is shown in green. The labor progress for the patient who had neuraxial analgesia placed at 4 cm is shown in solid blue line and at 1 cm is shown in dotted blue line.

Labor Pain Model

The timed cervical dilations used in the pain model were derived from the labor progress model. Figure 6A shows the basic sigmoidal labor pain model without covariates. The model was unbiased (MPE = 0.00 NRS units), with a median inaccuracy (MAPE) of 1.57 NRS units. Figure 6B shows the fit of the final, covariate adjusted model relating labor pain to predicted cervical dilation. The final model was very slightly biased (MPE = 0.08 NRS units) and slightly more accurate (MAPE = 1.48) than the model without covariates. Individual parameter values for the pain model are found in Table 5.

Fig 6
Pain model
Table 5
Pain Model

In the final model, patients who eventually required instrumental vaginal delivery had significantly higher pain scores in early labor, 5.43 (2.20–9.80) compared to initial pain scores of 0.79 ((0.27–1.33), P<0.001) in women who had a normal spontaneous vaginal delivery. Cold sensitivity determined with quantitative behavior testing, was a significant predictor for labor pain. Patients who were more sensitive to cold reported more labor pain. For every degree (C) higher than the median cold threshold value, the predicted initial pain score (NRSMIN) was greater by 0.14 (0.05–0.24) NRS points. Thus, the patient with the highest cold threshold (23°C) would be predicted to have an initial pain score 3.22 NRS higher than the nominal patient. OPRM1 genotype was not a significant predictor in the final model. In the pain model, the error attributable to truly random factors (post hoc Bayesian estimate of error) is 0.83 NRS points. The median absolute error in the initial model was 1.57 leaving 0.74 NRS points to be explained by true differences between individuals. Cold sensitivity and mode of delivery were able to explain only 12% of the variability.

Figure 7 shows the probability of distribution of each variable contributing to the final pain model. The 50% probability is represented as a solid line; the range of values that contributed to 95% probability is separated by dashed vertical lines.

Fig 7
Cumulative Probability Curve: Pain model

Pain Model Simulation

Figure 8 is a simulation of pain throughout the first stage of labor. The nominal patient with median cold sensitivity who had a spontaneous vaginal delivery is represented by solid black line. Patients who eventually required an instrumental vaginal delivery have significantly more pain from the beginning of labor, shown with a magenta line. The patient with extreme cold sensitivity (23°C threshold for discomfort) is represented in red line. These patients, also, report significantly higher pain scores from the beginning of labor. The patient with the least cold sensitivity (0°C threshold) is shown in purple.

Fig 8
Pain model forward simulation

Discussion

We have evaluated labor pain and progress in a prospectively enrolled cohort. Patients who express the CC allele at the β2AR-27 position transition to active labor later than patients with other genotypes and thus have longer labors. Separately considered, Asian ethnicity also predicted significantly slower labor progress. The much greater likelihood of expressing the CC allele at β2AR-27 position found in Asians may provide a genetic explanation for our previous and current finding of slower labor in Asian parturients4. Greater maternal weight and neuraxial analgesia were also predictive of slower labor, and is also in accordance with our and others previous findings 4. Genetic data for a single polymorphism in the β2AR allowed us to explain a significantly greater proportion of the residual variability compared to that which we were able to explain with demographic and treatment variables alone 4. The labor pain model was minimally informed by cold sensitivity and mode of delivery both variables were predictive of pain in early labor (NRSMIN).

Because there was collinearity between ethnicity and genotype, we constructed 2 models to separately evaluate the two factors. It is well known that Gln is more commonly expressed in Blacks 20, and even more so in Asians than in the White population21,22. Indeed, in our simulations for labor progress, the affect of Asian ethnicity is very similar to the effect of expressing CC at the β2AR 27 position (figure 5a,b). In fact, 11 of 14 Asian parturients had genotype CC at the β2AR 27position in our sample (none were GG). It may be that the effect of Asian ethnicity is due to a difference in the β2AR, a hypothesis that cannot be adequately tested with such a high correlation of CC genotype and Asian ethnicity. On the other hand, β2AR could simply be a marker for Asian ethnicity and the causative difference in rate of labor progress result from some other mechanism. We think this is unlikely for two reasons. 1)Non-Asians carrying the CC genotype experience a time course of labor progress that is similar to the Asian ethnic group. 2) β2AR activation (by endogenous catecholamines or the synthetic terbutaline) is well known to reduce uterine contractility, so a possible physiological explanation is available. The β2AR 27 polymorphism is thought to relate to receptor desensitization so it is mechanistically appealing to reason that the common allele is less desensitized and thus active and available to slow labor. The slow latent phase in Black parturients may be related to β2AR genotype or maternal weight, but this issue is not clear and must be addressed in a larger, more diverse population. It should also be noted that the actual, in vivo effect of these β2AR genotypes and haplotypes is still somewhat controversial

Other genes besides β2AR might also contribute to the portion of variability among women’s labor progress that remains unexplained. For example, the receptor for oxytocin has many polymorphisms that are thought to be important in autism spectrum disorders. However, a role of oxytocin receptor polymorphisms in the normal progress of labor and pharmacological administration of oxytocin for augmentation of labor has not yet been identified. We hope that genetic differences in the β2AR and potentially other receptors that modulate uterine contractility will come together to describe a haplotype for labor progress. Using our models, we can and will evaluate the importance of other gene candidates in labor pain and progress in the future.

An analysis of the National Collaborative Perinatal Project database that was published in April 2010 23 examined labor patterns in a large parturient population that delivered between 1959–1964, using interval censored regression to estimate the distribution of times for progression of labor. Comparing a simulation of their findings for nulliparas (kindly provided by Dr. Jun Zhang) to ours, it is clear that the rates of latent labor are strikingly similar but patients in our cohort transition to active labor at a lesser cervical dilation than in the historical cohort (Figure 9). This difference could be a result of the many demographic and treatment differences that have occurred during the past 50 years. However, the difference is unlikely to be a result of the different modeling paradigms because their data can be easily assessed with our structural model and our data with their high order polynomial equations with similar findings (data not shown)

Fig 9
Comparisons of Zhang Polynomial Model to Bi-exponential Model

We were able to explain a disappointingly small amount (12%) of the variability in labor pain that exists among women with the covariates that we studied. Quantitative behavioral testing for sensitivity to pressure, heat, and cold was performed on the subjects in the third trimester of pregnancy. Cold sensitivity was a significant predictor of early labor pain in the labor pain model, however, sensitivity to heat and pressure were not found to be important. It is not known whether the Transient Receptor Potential (TRP) channel subtypes, TRPM8 and TRPA1, which have a role in cold sensation 24 are even expressed in the uterus or play a role in labor pain. However, TRPV1 receptors are upregulated in the human lower uterine segment and cervix at term 25and these receptors may form heterodimers with TRPA1 subunits in sensory neurons 26. Performing immunocytochemistry in order to detect these cold receptors in human pregnant uterus will be helpful to elucidate this issue.

Genetic association studies that focus on pain focus on the OPRM1 gene as one of the highest ranked candidate polymorphism for pain studies9. The μ opioid receptor single nucleotide polymorphism OPRM1 118A>G (dbSNP rsl1799971) has been shown to be associated with a 0.8 fold decrease pressure pain intensity 27. However, in this study we were likely underpowered to detect a difference by OPRM1 genotype. In this study OPRM1 genotyping was added after the commencement of the study and therefore was not requested in all the consent documents, leading to incomplete genotyping in our cohort. Only 65 subjects were genotyped for OPRM1 gene. If the phenotype is conferred by the minor allele or the homozygous minor allele genotype, a much larger dataset will be required to detect a significant effect.

Aside from OPRM1, there are other genes that are known to be important in baseline pain sensitivity and that have been suggested as candidate genes for pain trials8. These include transient receptor potential cation channel, subfamily V, member 1 (TRPV1), transient receptor potential cation channel, subfamily A, member 1, also known as TRPA1, Catechol-O-methyl transferase (COMT), fatty acid amide hydrolase, and delta opioid receptorOPRD1. Among these, polymorphisms in the TRP genes may be particularly interesting because they have been associated with differences in cold sensitivity in previous human trials and are highly expressed in the uterine cervix at term pregnancy.

It should be noted that there were significant limitations to our study. Our database was relatively small consisting of 103 patients who reached full dilation, and we only tested for few candidate genes. Our trial was limited to nulliparous women from one private practice. This design allowed us to limit variability in obstetrical practice but also limited demographic variability. Ideally, future studies will be conducted in larger cohorts or DNA-linked databases to allow more thorough evaluation of genetic effects on labor pain and progress. Also, as discussed extensively in Debiec et al.4, our pain model suffers from both left and right censoring as women often come to the labor room because of pain and are more likely to request neuraxial analgesia earlier if they have more pain. The use of this model in a population in which neuraxial anesthesia is less prevalent will help assess factors that affect pain in later labor. It is notable, however, that in two separate cohorts of laboring women, one retrospective and one prospectively enrolled, we have identified Asian ethnicity (now with a potential mechanistic explanation), maternal weight and neuraxial analgesia as being predictive of labor progress.

A benefit of our structural model is that in the future, it could be used with concurrent patient data to predict the time of full dilation. Prospective validation of this technique will potentially allow us to differentiate the criteria that are associated with successful vaginal delivery from those associated with cesarean section for dystocia. A better understanding of these criteria combined with a reasonable estimation of the time required to achieve full cervical dilation may help the practitioner and patient to have a more informed discussion about the delivery plan.

What we already know about this topic

  • β2-adrenoceptor genotype affects the incidence of preterm labor, but its effect on labor progress and pain are not known

What this article tells us that is new

  • In 150 nulliparous parturients there was a strong association between β2-adrenoceptor genotype and progress of labor, with Asian women (who are likely to express one of the genotypes) to have slower labor progress
  • Black and heavy women were also noted to have slower latent labor
Figure 10
Representative Likelihood Profile
Figure 11
Likelihood Profile with 95% Confidence Limits
Figure 12
Cumulative Probability Curve

Supplementary Material

Appendix

Acknowledgments

Funding: This project was partially funded by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Bethesda, MD to RMS (RO1HD48805) and in part by departmental funds (Columbia University, New York, NY)

Footnotes

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Contributor Information

Elena Reitman, Division of Obstetrical Anesthesiology, Columbia University.

Jessamyn Conell-Price, Department of Anesthesiology, Columbia University.

Jennifer Evansmilth, Columbia College, Columbia University.

Luke Olson, Department of Anesthesiology, Columbia University.

Sofia Drosinos, Department of Obstetrics and Gynecology, Columbia University.

Nancy Jasper, Department of Obstetrics and Gynecology, Columbia University.

Paula Randolph, Department of Obstetrics and Gynecology, Columbia University.

Richard Smiley, Division of Obstetrical Anesthesiology, Columbia University.

Steven Shafer, Columbia University.

Pamela Flood, Division of Obstetrical Anesthesiology, Columbia University.

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