Semiparametric analysis of a generalized linear model with multiple covariates subject to detection limits.

Studies on the health effects of environmental mixtures face the challenge of limit of detection (LOD) in multiple correlated exposure measurements. Conventional approaches to deal with covariates subject to LOD, including complete-case analysis, substitution methods, and parametric modeling of covariate distribution, are feasible but may result in efficiency loss or bias. With a single covariate subject to LOD, a flexible semiparametric accelerated failure time (AFT) model to accommodate censored measurements has been proposed. We generalize this approach by considering a multivariate AFT model for the multiple correlated covariates subject to LOD and a generalized linear model for the outcome. A two-stage procedure based on semiparametric pseudo-likelihood is proposed for estimating the effects of these covariates on health outcome. Consistency and asymptotic normality of the estimators are derived for an arbitrary fixed dimension of covariates. Simulations studies demonstrate good large sample performance of the proposed methods vs conventional methods in realistic scenarios. We illustrate the practical utility of the proposed method with the LIFECODES birth cohort data, where we compare our approach to existing approaches in an analysis of multiple urinary trace metals in association with oxidative stress in pregnant women.

Nonparametric cluster significance testing with reference to a unimodal null distribution.

Cluster analysis is an unsupervised learning strategy that is exceptionally useful for identifying homogeneous subgroups of observations in data sets of unknown structure. However, it is challenging to determine if the identified clusters represent truly distinct subgroups rather than noise. Existing approaches for addressing this problem tend to define clusters based on distributional assumptions, ignore the inherent correlation structure in the data, or are not suited for high-dimension low-sample size (HDLSS) settings. In this paper, we propose a novel method to evaluate the significance of identified clusters by comparing the explained variation due to the clustering from the original data to that produced by clustering a unimodal reference distribution that preserves the covariance structure in the data. The reference distribution is generated using kernel density estimation, and thus, does not require that the data follow a particular distribution. By utilizing sparse covariance estimation, the method is adapted for the HDLSS setting. The approach can be used to test the null hypothesis that the data cannot be partitioned into clusters and to determine the optimal number of clusters. Simulation examples, theoretical evaluations, and applications to temporomandibular disorder research and cancer microarray data illustrate the utility of the proposed method.

Biclustering via sparse clustering.

In identifying subgroups of a heterogeneous disease or condition, it is often desirable to identify both the observations and the features which differ between subgroups. For instance, it may be that there is a subgroup of individuals with a certain disease who differ from the rest of the population based on the expression profile for only a subset of genes. Identifying the subgroup of patients and subset of genes could lead to better-targeted therapy. We can represent the subgroup of individuals and genes as a bicluster, a submatrix, U , of a larger data matrix, X , such that the features and observations in U differ from those not contained in U . We present a novel two-step method, SC-Biclust, for identifying U . In the first step, the observations in the bicluster are identified to maximize the sum of the weighted between-cluster feature differences. In the second step, features in the bicluster are identified based on their contribution to the clustering of the observations. This versatile method can be used to identify biclusters that differ on the basis of feature means, feature variances, or more general differences. The bicluster identification accuracy of SC-Biclust is illustrated through several simulated studies. Application of SC-Biclust to pain research illustrates its ability to identify biologically meaningful subgroups.

Identification of relevant subtypes via preweighted sparse clustering.

Cluster analysis methods are used to identify homogeneous subgroups in a data set. In biomedical applications, one frequently applies cluster analysis in order to identify biologically interesting subgroups. In particular, one may wish to identify subgroups that are associated with a particular outcome of interest. Conventional clustering methods generally do not identify such subgroups, particularly when there are a large number of high-variance features in the data set. Conventional methods may identify clusters associated with these high-variance features when one wishes to obtain secondary clusters that are more interesting biologically or more strongly associated with a particular outcome of interest. A modification of sparse clustering can be used to identify such secondary clusters or clusters associated with an outcome of interest. This method correctly identifies such clusters of interest in several simulation scenarios. The method is also applied to a large prospective cohort study of temporomandibular disorders and a leukemia microarray data set.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study.

Ex vivo chemical cytometric analysis of protein tyrosine phosphatase activity in single human airway epithelial cells.

We describe a novel method for the measurement of protein tyrosine phosphatase (PTP) activity in single human airway epithelial cells (hAECs) using capillary electrophoresis. This technique involved the microinjection of a fluorescent phosphopeptide that is hydrolyzed specifically by PTPs. Analyses in BEAS-2B immortalized bronchial epithelial cells showed rapid PTP-mediated dephosphorylation of the substrate (2.2 pmol min(-1) mg(-1)) that was blocked by pretreatment of the cells with the PTP inhibitors pervanadate, Zn(2+), and 1,2-naphthoquinone (76%, 69%, and 100% inhibition relative to PTP activity in untreated controls, respectively). These studies were then extended to a more physiologically relevant model system: primary hAECs cultured from bronchial brushings of living human subjects. In primary hAECs, dephosphorylation of the substrate occurred at a rate of 2.2 pmol min(-1) mg(-1) and was also effectively inhibited by preincubation of the cells with the inhibitors pervanadate, Zn(2+), and 1,2-naphthoquinone (91%, 88%, and 87% median PTP inhibition, respectively). Reporter proteolysis in single BEAS-2B cells occurred at a median rate of 43 fmol min(-1) mg(-1) resulting in a mean half-life of 20 min. The reporter displayed a similar median half-life of 28 min in these single primary cells. Finally, single viable epithelial cells (which were assayed for PTP activity immediately after collection by bronchial brushing of a human volunteer) showed dephosphorylation rates ranging from 0.34 to 36 pmol min(-1) mg(-1) (n = 6). These results demonstrate the utility and applicability of this technique for the ex vivo quantification of PTP activity in small, heterogeneous, human cells and tissues.

Incidence and predictors of acute psychological distress and dissociation after motor vehicle collision: a cross-sectional study.

OBJECTIVE: We examined the incidence and predictors of peritraumatic distress and dissociation after one of the most common forms of civilian trauma exposure: motor vehicle collision (MVC). METHOD: In this study, patients presenting to the emergency department after MVCs who were without serious injury and discharged to home after evaluation (n = 935) completed an emergency department interview evaluating sociodemographic, collision-related, and psychological characteristics. RESULTS: The incidence and predictors of distress (Peritraumatic Distress Inventory score ≥23) and dissociation (Michigan Critical Events Perception Scale score >3) were assessed. Distress was present in 355 of 935 patients (38%), and dissociation was present in 260 of 942 patients (28%). These outcomes showed only moderate correlation (r = .45) and had both shared and distinct predictors. Female gender, anxiety symptoms prior to the MVC, and vehicle damage severity predicted both distress and dissociation. Higher socioeconomic status (higher education, higher income, full-time employment) had a protective effect against distress but not dissociative symptoms. Better physical health and worse overall mental health were associated with increased risk of dissociation but not distress. Distress but not dissociation was associated with lower patient confidence in recovery and a longer expected duration of recovery. CONCLUSION: There are unique predictors of peritraumatic distress and dissociation. Further work is needed to better understand the neurobiology of peritraumatic distress and dissociation and the influence of these peritraumatic outcomes on persistent psychological sequelae.

Measurement of protein tyrosine phosphatase activity in single cells by capillary electrophoresis.

A fluorescent peptide substrate was used to measure dephosphorylation by protein tyrosine phosphatases (PTP) in cell lysates and single cells and to investigate the effect of environmental toxins on PTP activity in these systems. Dephosphorylation of the substrate by PTPN1 and PTPN2 obeyed Michaelis-Menten kinetics, with KM values of 770 ± 250 and 290 ± 54 nM, respectively. Dose-response curves and IC50 values were determined for the inhibition of these two enzymes by the environmental toxins Zn(2+) and 1,2-naphthoquinone, as well as pervanadate. In A431 cell lysates, the reporter was a poor substrate for peptidases (degradation rate of 100 ± 8.2 fmol min(-1) mg(-1)) but an excellent substrate for phosphatases (dephosphorylation rate of 1.4 ± 0.3 nmol min(-1) mg(-1)). Zn(2+), 1,2-naphthoquinone, and pervanadate inhibited dephosphorylation of the reporter in cell lysates with IC50 values of 470 nM, 35 µM, and 100 nM, respectively. Dephosphorylation of the reporter, following loading into living single cells, occurred at rates of at least 2 pmol min(-1) mg(-1). When single cells were exposed to 1,2-naphthoquinone (50 µM), Zn(2+) (100 µM), and pervandate (1 mM), dephosphorylation was inhibited with median values and first and third quartile values of 41 (Q1 = 0%, Q3 = 96%), 50 (Q1 = 46%, Q3 = 74%), and 53% (Q1 = 36%, Q3 = 77%), respectively, demonstrating both the impact of these toxic exposures on cell signaling and the heterogeneity of response between cells. This approach will provide a valuable tool for the study of PTP dynamics, particularly in small, heterogeneous populations such as human biopsy specimens.

Cross-validation for nonlinear mixed effects models.

Cross-validation is frequently used for model selection in a variety of applications. However, it is difficult to apply cross-validation to mixed effects models (including nonlinear mixed effects models or NLME models) due to the fact that cross-validation requires "out-of-sample" predictions of the outcome variable, which cannot be easily calculated when random effects are present. We describe two novel variants of cross-validation that can be applied to NLME models. One variant, where out-of-sample predictions are based on post hoc estimates of the random effects, can be used to select the overall structural model. Another variant, where cross-validation seeks to minimize the estimated random effects rather than the estimated residuals, can be used to select covariates to include in the model. We show that these methods produce accurate results in a variety of simulated data sets and apply them to two publicly available population pharmacokinetic data sets.

The relationship between resting arterial blood pressure and acute postoperative pain in endodontic patients.

AIMS: To evaluate the relationship between preoperative resting arterial blood pressure and postoperative pain in patients undergoing nonsurgical root canal therapy. METHODS: Written informed consent was obtained from normotensive patients seeking treatment for teeth with a preoperative diagnosis of pulpal necrosis and periradicular periodontitis. Preoperative resting blood pressure was recorded, and nonsurgical root canal therapy was initiated using a standardized protocol. Patients recorded their pre- and postoperative pain intensity on a 100-mm visual analog scale (VAS) for 7 days after the procedure. A linear regression model to predict postoperative VAS intensity used preoperative pain and blood pressure values as covariates. Pearson correlations were calculated to assess the relationship between the measures of preoperative blood pressure and both pre- and postoperative pain. RESULTS: After controlling for preoperative pain, significant correlations were observed between preoperative systolic blood pressure and postoperative pain (P < .05), as well as between preoperative pulse pressure and postoperative pain (P < .005) on day 1. CONCLUSION: This study has provided further evidence of a functional interaction between the cardiovascular and trigeminal pain regulatory systems. Understanding this complex relationship may lead to enhanced pain management strategies.

Association of Hormonal Contraceptive Use with Headache and Temporomandibular Pain: The OPPERA Study.

AIMS: To determine the relationship between hormonal contraceptive (HC) use and painful symptoms, particularly those associated with headache and painful temporomandibular disorders (TMD). METHODS: Data from the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) prospective cohort study were used. During the 2.5-year median follow-up period, quarterly health update (QHU) questionnaires were completed by 1,475 women aged 18 to 44 years who did not have TMD, menopause, hysterectomy, or hormone replacement therapy use at baseline. QHU questionnaires evaluated HC use, symptoms of headache and TMD, and pain of ≥ 1 day duration in 12 body regions. Participants who developed TMD symptoms were examined to classify clinical TMD. Headache symptoms were classified based on the International Classification of Headache Disorders 3 (ICHD-3). Associations between HC use and pain symptoms were analyzed using generalized estimating equations and Cox models. RESULTS: HC use, endorsed in 33.7% of QHU questionnaires, was significantly associated with concurrent symptoms of TMD (odds ratio [OR]: 1.20, 95% CI: 1.06 to 1.35) and headache (OR: 1.26, 95% CI: 1.11 to 1.43). HC use was also significantly associated with concurrent pain of ≥ 1 day duration in the head (OR: 1.38, 95% CI: 1.16 to 1.63), face (OR: 1.44, 95% CI: 1.13 to 1.83), and legs (OR: 1.22, 95% CI: 1.01 to 1.47), but not elsewhere. Initiation of HC use was associated with increased odds of subsequent TMD symptoms (OR: 1.37, 95% CI: 1.13 to 1.66) and pain of ≥ 1 day in the head (OR: 1.37, 95% CI: 1.01 to 1.85). Discontinuing HC use was associated with lower odds of subsequent headache (OR: 0.82, 95% CI: 0.67 to 0.99). HC use was not significantly associated with subsequent onset of examiner-classified TMD. CONCLUSION: These findings imply that HC influences craniofacial pain, and that this pain diminishes after cessation of HC use.

Phenotypic profile clustering pragmatically identifies diagnostically and mechanistically informative subgroups of chronic pain patients.

ABSTRACT: Traditional classification and prognostic approaches for chronic pain conditions focus primarily on anatomically based clinical characteristics not based on underlying biopsychosocial factors contributing to perception of clinical pain and future pain trajectories. Using a supervised clustering approach in a cohort of temporomandibular disorder cases and controls from the Orofacial Pain: Prospective Evaluation and Risk Assessment study, we recently developed and validated a rapid algorithm (ROPA) to pragmatically classify chronic pain patients into 3 groups that differed in clinical pain report, biopsychosocial profiles, functional limitations, and comorbid conditions. The present aim was to examine the generalizability of this clustering procedure in 2 additional cohorts: a cohort of patients with chronic overlapping pain conditions (Complex Persistent Pain Conditions study) and a real-world clinical population of patients seeking treatment at duke innovative pain therapies. In each cohort, we applied a ROPA for cluster prediction, which requires only 4 input variables: pressure pain threshold and anxiety, depression, and somatization scales. In both complex persistent pain condition and duke innovative pain therapies, we distinguished 3 clusters, including one with more severe clinical characteristics and psychological distress. We observed strong concordance with observed cluster solutions, indicating the ROPA method allows for reliable subtyping of clinical populations with minimal patient burden. The ROPA clustering algorithm represents a rapid and valid stratification tool independent of anatomic diagnosis. ROPA holds promise in classifying patients based on pathophysiological mechanisms rather than structural or anatomical diagnoses. As such, this method of classifying patients will facilitate personalized pain medicine for patients with chronic pain.

Nonlinear Dose-Response Modeling of High-Throughput Screening Data Using an Evolutionary Algorithm.

Nonlinear dose-response relationships exist extensively in the cellular, biochemical, and physiologic processes that are affected by varying levels of biological, chemical, or radiation stress. Modeling such responses is a crucial component of toxicity testing and chemical screening. Traditional model fitting methods such as nonlinear least squares (NLS) are very sensitive to initial parameter values and often had convergence failure. The use of evolutionary algorithms (EAs) has been proposed to address many of the limitations of traditional approaches, but previous methods have been limited in the types of models they can fit. Therefore, we propose the use of an EA for dose-response modeling for a range of potential response model functional forms. This new method can not only fit the most commonly used nonlinear dose-response models (eg, exponential models and 3-, 4-, and 5-parameter logistic models) but also select the best model if no model assumption is made, which is especially useful in the case of high-throughput curve fitting. Compared with NLS, the new method provides stable and robust solutions without sensitivity to initial values.

Premorbid and concurrent predictors of TMD onset and persistence.

BACKGROUND: Multiple risk factors predict temporomandibular disorders (TMD) onset, but temporal changes in risk factors and their contribution to risk of TMD have not been evaluated. The study aims were to (a) describe changes occurring in premorbid TMD risk factors when re-measured at TMD onset and 6 months later, and (b) determine if measures of change improve accuracy in predicting TMD incidence compared to premorbid measures alone. METHODS: In this observational prospective cohort study at four university research clinics, 3,258 community-based, 18- to 44-year-olds without TMD were enrolled. During the 3-year median follow-up, 260 incident cases of first-onset TMD were identified, and 196 TMD-free subjects were selected as matched controls. Six-months later, 147 of 260 incident cases (56.6%) were re-examined revealing 72 (49%) with 'persistent TMD' and 75 (51%) whose condition had resolved ('transient TMD'). Virtually all (126) of the 127 re-examined controls remained without TMD. Questionnaires and clinical measurements evaluated risk factors from clinical, health, psychological and behavioural and neurosensory domains. RESULTS: Most risk factors across all four domains increased with TMD onset, remained elevated in the persistent group and declined in the transient group (i.e., significant ANOVA interactions, p < .05). Accuracy in predicting first-onset TMD, quantified as area under the receiver operating characteristic curve was 0.71 (95% CL 0.68, 0.73) using only premorbid measures of risk factors, which increased to 0.91 (95% CL 0.89, 0.94) after addition of change measures. CONCLUSIONS: TMD pain onset and persistence appear to be determined by enduring characteristics of the person as well as mutually interactive with temporally evolving variables. SIGNIFICANCE: TMD is known to be a complex disorder, in which onset and persistence are associated with disease-related variables in multiple domains, including environmental exposure, clinical, psychological, health status, and pain processing variables. Using a more dynamic approach in order to capture change across time, many aspects of those domains were found to worsen prior to the reporting of pain, with bidirectional influences between domains and pain emergence likely. TMD onset appears to represent the cumulative effect of multiple system dysregulation.

Incident injury is strongly associated with subsequent incident temporomandibular disorder: results from the OPPERA study.

Cross-sectional studies confirm, as expected, a positive association between jaw injury and painful temporomandibular disorders (TMDs), but prospective evaluations are lacking. We prospectively assessed incident jaw injury, injury type, and development of TMD in adults aged 18 to 44 years. Data were collected from 3258 individuals from communities surrounding 4 US academic institutes between 2006 and 2008. At enrollment, participants reported no TMD history and no facial injuries in the previous 6 months. Quarterly, follow-up questionnaires assessed incident jaw injury, which was classified as intrinsic (attributed to yawning or prolonged mouth opening) or extrinsic (attributed to other causes). Examiners classified incident TMD during a median follow-up period of 2.8 years (range 0.2-5.2 years). Cox regression models used jaw injury as a time-dependent covariate to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association with incident TMD. Among 1729 participants with complete data, 175 developed TMD. Eighty percent of injuries were intrinsic. Temporomandibular disorder annual incidence was nearly twice as high in those experiencing jaw injury (5.37%) compared with those who did not (3.44%). In the Cox model that accounted for timing of injury, the corresponding HR was 3.94 (95% CI = 2.82-5.50) after adjusting for study site, age, race, and sex. Hazard ratios did not differ (P = 0.91) for extrinsic injuries (HR = 4.03, 95% CI = 2.00-8.12) and intrinsic injuries (HR = 3.85, 95% CI = 2.70-5.49). Jaw injury was strongly associated with incident TMD. If surveillance and intervention after jaw injury is to be effective in preventing TMD, they should focus on both intrinsic and extrinsic injuries.

Anatomical selectivity in overlap of chronic facial and bodily pain.

BACKGROUND: Chronic facial pain often overlaps with pain experienced elsewhere in the body, although previous studies have focused on a few, selected pain conditions when assessing the degree of overlap. AIM: To quantify the degree of overlap between facial pain and pain reported at multiple locations throughout the body. METHODS: Data were from a case-control study of US adults participating in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) project. They were interviewed to determine the presence of chronic facial pain (n = 424 cases) or its absence (n = 912 controls). A mailed questionnaire with a body drawing asked about pain at other locations. Odds ratios (ORs) and 95% confidence limits (95% CLs) quantified the degree of overlap between facial pain and pain at other locations. For replication, cross-sectional data were analyzed from the UK Biobank study (n = 459,604 participants) and the US National Health Interview Survey (n = 27,731 participants). RESULTS: In univariate analysis, facial pain had greatest overlap with headache (OR = 14.2, 95% CL = 9.7-20.8) followed by neck pain (OR = 8.5, 95% CL = 6.5-11.0), whereas overlap decreased substantially (ORs of 4.4 or less) for pain at successively remote locations below the neck. The same anatomically based ranking of ORs persisted in multivariable analysis that adjusted for demographics and risk factors for facial pain. Findings were replicated in the UK Biobank study and the US National Health Interview Survey. The observed anatomical selectivity in the degree of overlap could be a consequence of neurosensory and/or affective processes that differentially amplify pain according to its location.

Clinical predictors of persistent temporomandibular disorder in people with first-onset temporomandibular disorder: A prospective case-control study.

BACKGROUND: When patients first develop a painful temporomandibular disorder (TMD) and seek care, 1 priority for clinicians is to assess prognosis. The authors aimed to develop a predictive model by using biopsychosocial measures from the Diagnostic Criteria for Temporomandibular Disorders (DC-TMD) to predict risk of developing TMD symptom persistence. METHODS: At baseline, trained examiners identified 260 participants with first-onset TMD classified by using DC-TMD-compliant protocols. After follow-up at least 6 months later, 72 (49%) had examiner-classified TMD (persistent cases), and 75 (51%) no longer had examiner-classified TMD (transient cases). For multivariable logistic regression analysis, the authors used blocks of variables selected using minimum redundancy maximum relevance to construct a model to predict the odds of TMD persistence. RESULTS: At onset, persistent cases had multiple worse TMD clinical measures and, among Axis II measures, only greater baseline pain intensity (odds ratio [OR], 1.5; 95% confidence interval [CI], 1.04 to 2.2; P = .030) and more physical symptoms (OR, 1.8; 95% CI, 1.2 to 2.9; P = .004) than did transient cases. A multivariable model using TMD clinical measures showed greater discriminative capacity (area under the receiver operating characteristic curve, 0.74; 95% CI, 0.73 to 0.75) than did a model involving psychosocial measures (area under the receiver operating characteristic curve, 0.63; 95% CI, 0.62 to 0.64). CONCLUSIONS: Clinical measures that clinicians can assess readily when TMD first develops are useful in predicting the risk of developing persistent TMD. Psychosocial measures are important predictors of onset but do not add meaningfully to the predictive capacity of clinical measures. PRACTICAL IMPLICATIONS: When TMD first develops, clinicians usefully can identify patients at higher risk of developing persistence by using clinical measures that they logically also could use in treatment planning and for monitoring outcomes of intervention.

Genome-wide association reveals contribution of MRAS to painful temporomandibular disorder in males.

Painful temporomandibular disorders (TMDs) are the leading cause of chronic orofacial pain, but its underlying molecular mechanisms remain obscure. Although many environmental factors have been associated with higher risk of developing painful TMD, family and twin studies support a heritable genetic component as well. We performed a genome-wide association study assuming an additive genetic model of TMD in a discovery cohort of 999 cases and 2031 TMD-free controls from the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study. Using logistic models adjusted for sex, age, enrollment site, and race, we identified 3 distinct loci that were significant in combined or sex-segregated analyses. A single-nucleotide polymorphism on chromosome 3 (rs13078961) was significantly associated with TMD in males only (odds ratio = 2.9, 95% confidence interval: 2.02-4.27, P = 2.2 × 10). This association was nominally replicated in a meta-analysis of 7 independent orofacial pain cohorts including 160,194 participants (odds ratio = 1.16, 95% confidence interval: 1.0-1.35, P = 2.3 × 10). Functional analysis in human dorsal root ganglia and blood indicated this variant is an expression quantitative trait locus, with the minor allele associated with decreased expression of the nearby muscle RAS oncogene homolog (MRAS) gene (beta = -0.51, P = 2.43 × 10). Male mice, but not female mice, with a null mutation of Mras displayed persistent mechanical allodynia in a model of inflammatory pain. Genetic and behavioral evidence support a novel mechanism by which genetically determined MRAS expression moderates the resiliency to chronic pain. This effect is male-specific and may contribute to the lower rates of painful TMD in men.

hCAP-D3 expression marks a prostate cancer subtype with favorable clinical behavior and androgen signaling signature.

Growing evidence suggests that only a fraction of prostate cancers detected clinically are potentially lethal. An important clinical issue is identifying men with indolent cancer who might be spared aggressive therapies with associated morbidities. Previously, using microarray analysis we defined 3 molecular subtypes of prostate cancer with different gene-expression patterns. One, subtype-1, displayed features consistent with more indolent behavior, where an immunohistochemical marker (AZGP1) for subtype-1 predicted favorable outcome after radical prostatectomy. Here we characterize a second candidate tissue biomarker, hCAP-D3, expressed in subtype-1 prostate tumors. hCAP-D3 expression, assayed by RNA in situ hybridization on a tissue microarray comprising 225 cases, was associated with decreased tumor recurrence after radical prostatectomy (P=0.004), independent of pathologic tumor stage, Gleason grade, and preoperative prostate-specific antigen levels. Simultaneous assessment of hCAP-D3 and AZGP1 expression in this tumor set improved outcome prediction. We have previously demonstrated that hCAP-D3 is induced by androgen in prostate cells. Extending this finding, Gene Set Enrichment Analysis revealed enrichment of androgen-responsive genes in subtype-1 tumors (P=0.019). Our findings identify hCAP-D3 as a new biomarker for subtype-1 tumors that improves prognostication, and reveal androgen signaling as an important biologic feature of this potentially clinically favorable molecular subtype.

Long-term changes in biopsychosocial characteristics related to temporomandibular disorder: findings from the OPPERA study.

Painful temporomandibular disorders (TMDs) are both consequence and cause of change in multiple clinical, psychosocial, and biological factors. Although longitudinal studies have identified antecedent biopsychosocial factors that increase risk of the TMD onset and persistence, little is known about long-term change in those factors after TMD develops or remits. During a 7.6-year median follow-up period, we measured change in psychosocial characteristics, pain sensitivity, cardiovascular indicators of autonomic function, and clinical jaw function among 189 participants whose baseline chronic TMD status either persisted or remitted and 505 initially TMD-free participants, 83 of whom developed TMD. Among initially TMD-free participants who developed TMD, symptoms and pain sensitivity increased, whereas psychological function worsened. By contrast, participants with chronic TMD at baseline tended to show improved TMD symptoms, improved jaw function, reduced somatic symptoms, and increased positive affect. In general, clinical and psychosocial variables more frequently changed in parallel with TMD status compared with pain sensitivity and autonomic measures. These findings demonstrate a complex pattern of considerable changes in biopsychosocial function associated with changes in TMD status. In particular, several biopsychosocial parameters improved among participants with chronic TMD despite pain persisting for years, suggesting considerable potential for ongoing coping and adaptation in response to persistent pain.