CD3ζ ITAMs enable ligand discrimination and antagonism by inhibiting TCR signaling in response to low-affinity peptides.

The T cell antigen receptor (TCR) contains ten immunoreceptor tyrosine-based activation motif (ITAM) signaling sequences distributed within six CD3 subunits; however, the reason for such structural complexity and multiplicity is unclear. Here we evaluated the effect of inactivating the three CD3ζ chain ITAMs on TCR signaling and T cell effector responses using a conditional 'switch' mouse model. Unexpectedly, we found that T cells expressing TCRs containing inactivated (non-signaling) CD3ζ ITAMs (6F-CD3ζ) exhibited reduced ability to discriminate between low- and high-affinity ligands, resulting in enhanced signaling and cytokine responses to low-affinity ligands because of a previously undetected inhibitory function of CD3ζ ITAMs. Also, 6F-CD3ζ TCRs were refractory to antagonism, as predicted by a new in silico adaptive kinetic proofreading model that revises the role of ITAM multiplicity in TCR signaling. Finally, T cells expressing 6F-CD3ζ displayed enhanced cytolytic activity against solid tumors expressing low-affinity ligands, identifying a new counterintuitive approach to TCR-mediated cancer immunotherapy.

Defining features of hereditary lobular breast cancer due to CDH1 with magnetic resonance imaging and tumor characteristics.

Women with germline pathogenic variants in CDH1, which encodes E-cadherin protein, are at increased lifetime risk of invasive lobular carcinoma (ILC). The associated tumor characteristics of hereditary lobular breast carcinoma (HLBC) in this high-risk population are not well-known. A single-center prospective cohort study was conducted to determine the imaging and pathologic features of HLBC compared to population-based ILC using Surveillance, Epidemiology, and End Results (SEER) data. One hundred fifty-eight women with CDH1 variants were evaluated, of whom 48 (30%) also had an ILC diagnosis. The median age at CDH1 diagnosis was 45 years [interquartile range, IQR 34-57 years] whereas the median age at diagnosis of CDH1 with concomitant ILC (HLBC) was 53 [IQR 45-62] years. Among women with HLBC, 83% (40/48) were identified with CDH1 mutation after diagnosis of ILC. Among 76 women (48%, 76/158) undergoing surveillance for ILC with breast magnetic resonance imaging (MRI), 29% (22/76) had an abnormal MRI result with available biopsy data for comparison. MRI detected ILC in 7 out of 8 biopsy-confirmed cases, corresponding with high sensitivity (88%), specificity (75%), and negative predictive value (98%); however, false-positive and false-discovery rates were elevated also (25% and 68%, respectively). HLBC was most frequently diagnosed at age 40-49 years (44%, 21/48), significantly younger than the common age of diagnosis of ILC in SEER general population data (most frequent age range 60-69 years, 28%; p < 0.001). HLBC tumors were smaller than SEER-documented ILC tumors (median 1.40 vs. 2.00 cm; p = 0.002) and had a higher incidence of background lobular carcinoma in situ (88% vs. 1%; p < 0.001) as well as progesterone receptor positivity (95% vs. 81%, p = 0.032). These findings suggest that HLBC is often detected via conventional screening methods as an early-stage hormone receptor-positive tumor, thus the clinical benefit of intensive screening with MRI may be limited to a subset of women with germline CDH1 variants.

Serum neutralization activity declines but memory B cells persist after cure of chronic hepatitis C.

The increasing incidence of hepatitis C virus (HCV) infections underscores the need for an effective vaccine. Successful vaccines to other viruses generally depend on a long-lasting humoral response. However, data on the half-life of HCV-specific responses are lacking. Here we study archived sera and mononuclear cells that were prospectively collected up to 18 years after cure of chronic HCV infection to determine the role of HCV antigen in maintaining neutralizing antibody and B cell responses. We show that HCV-neutralizing activity decreases rapidly in potency and breadth after curative treatment. In contrast, HCV-specific memory B cells persist, and display a restored resting phenotype, normalized chemokine receptor expression and preserved ability to differentiate into antibody-secreting cells. The short half-life of HCV-neutralizing activity is consistent with a lack of long-lived plasma cells. The persistence of HCV-specific memory B cells and the reduced inflammation after cure provide an opportunity for vaccination to induce protective immunity against re-infection.

Use of gonadotropin-releasing hormone agonists for ovarian preservation in patients receiving cyclophosphamide for systemic lupus erythematosus: A meta-analysis.

BACKGROUND: Cyclophosphamide (CYC) has known cytotoxic effects on ovarian reserve and has been linked to premature ovarian failure (POF) in systemic lupus erythematosus (SLE). The concurrent use of gonadotropin-releasing hormone agonists (GnRHas) is postulated to preserve ovarian function by reducing the number of follicles exposed to CYC, but there is paucity of data to establish its efficacy. We conducted a meta-analysis to summarize the effect of concurrent GnRHa use in persevering ovarian function and pregnancy. METHODS: English language databases of PubMed, Embase, and Cochrane were searched to include studies published between 2000 and 2021. Studies in females with rheumatic diseases receiving concurrent GnRHa and CYC therapy to evaluate ovarian preservation as defined by amenorrhea, follicle stimulating hormone (FSH), anti-mullerian hormone (AMH), or estradiol levels or successful pregnancy were included. We used a fixed effect, exact, Mantel-Haenszel approach to estimate the overall odds ratio (OR) and associated 95% confidence intervals (95% CIs). RESULTS: Seven studies with 218 female patients were included. The ovarian function was preserved in 125/132 (94.6%) of women who received GnRHa concurrently with CYC compared to 50/86 (58%) of women who did not receive GnRHa (OR = 10.3, CI = 4.83-36.29). The OR for pregnancy with GnRHa use = 2.94 (CI = 1.04-9.89). CONCLUSION: Our results based on limited published studies suggest that concurrent GnRHa use preserves ovarian function and increase odds of pregnancy. It can be considered for premenopausal SLE females receiving CYC. Long-term follow-up studies are needed to establish the efficacy and safety of GnRHa use for ovarian preservation.

Daily diary study of loneliness, alcohol, and drug use during the COVID-19 Pandemic.

BACKGROUND: Research conducted during the COVID-19 Pandemic has identified two co-occurring public health concerns: loneliness and substance use. Findings from research conducted prior to the pandemic are inconclusive as to the links between loneliness and substance use. This study aimed to measure associations of loneliness with three different types of substance use during COVID-19: daily number of alcoholic drinks, cannabis use, and non-cannabis drug use. METHOD: Data were obtained between October 2020 and May 2021 from 2,648 US adults (Mage  = 38.76, 65.4% women) diverse with respect to race and ethnicity using online recruitment. Participants completed baseline surveys and daily assessments for 30 days. A daily loneliness measure was recoded into separate within- and between-person predictor variables. Daily outcome measures included the number of alcoholic drinks consumed and dichotomous cannabis and non-cannabis drug use variables. Generalized linear multilevel models (GLMLM) were used to examine within- and between-person associations between loneliness and substance use. RESULTS: The unconditional means model indicated that 59.0% of the variance in the daily number of alcoholic drinks was due to within-person variability. GLMLM analyses revealed that, overall, people drank more on days when they felt a particularly high or particularly low degree of loneliness (positive quadratic effect). There was a negative and significant within-person association between daily loneliness and the likelihood of cannabis use. There was also a positive and significant within-person association between daily loneliness and the likelihood of non-cannabis drug use. CONCLUSIONS: Associations between loneliness and substance use vary with substance type and whether within- or between-person differences are assessed. These findings are relevant to the persistence of substance use disorders and thus of potential clinical importance. Individuals who do not experience severe loneliness at intake but who show daily increases in loneliness above baseline levels are at heightened risk of alcohol and non-cannabis drug use. Future research could profitably examine just-in-time adaptive interventions that assess fluctuations in loneliness to prevent the development or exacerbation of substance use disorders.

Disparities in sleep duration among American children: effects of race and ethnicity, income, age, and sex.

Children in the United States sleep less than the recommended amount and sleep deficiencies may be worse among disadvantaged children. Prior studies that compared sleep time in children of different race/ethnic groups mostly relied on questionnaires or were limited to small sample sizes. Our study takes advantage of the Adolescent Brain Cognitive Development study to compare total sleep time using a week of actigraphy data among American children (n = 4,207, 9 to 13 y old) of different racial/ethnic and income groups. We also assessed the effects of neighborhood deprivation, experience of discrimination, parent's age at child's birth, body mass index (BMI), and time the child fell asleep on sleep times. Daily total sleep time for the sample was 7.45 h and race/ethnicity, income, sex, age, BMI, were all significant predictors of total sleep time. Black children slept less than White children (∼34 min; Cohen's d = 0.95), children from lower income families slept less than those from higher incomes (∼16 min; Cohen's d = 0.44), boys slept less than girls (∼7 min; Cohen's d = 0.18), and older children slept less than younger ones (∼32 min; Cohen's d = 0.91); mostly due to later sleep times. Children with higher BMI also had shorter sleep times. Neither area deprivation index, experience of discrimination, or parent's age at child's birth significantly contributed to sleep time. Our findings indicate that children in the United States sleep significantly less than the recommended amount for healthy development and identifies significant racial and income disparities. Interventions to improve sleep hygiene in children will help improve health and ameliorate racial disparities in health outcomes.

Predicting cancer immunotherapy response from gut microbiomes using machine learning models.

Cancer immunotherapy has significantly improved patient survival. Yet, half of patients do not respond to immunotherapy. Gut microbiomes have been linked to clinical responsiveness of melanoma patients on immunotherapies; however, different taxa have been associated with response status with implicated taxa inconsistent between studies. We used a tumor-agnostic approach to find common gut microbiome features of response among immunotherapy patients with different advanced stage cancers. A combined meta-analysis of 16S rRNA gene sequencing data from our mixed tumor cohort and three published immunotherapy gut microbiome datasets from different melanoma patient cohorts found certain gut bacterial taxa correlated with immunotherapy response status regardless of tumor type. Using multivariate selbal analysis, we identified two separate groups of bacterial genera associated with responders versus non-responders. Statistical models of gut microbiome community features showed robust prediction accuracy of immunotherapy response in amplicon sequencing datasets and in cross-sequencing platform validation with shotgun metagenomic datasets. Results suggest baseline gut microbiome features may be predictive of clinical outcomes in oncology patients on immunotherapies, and some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms. Findings demonstrate how machine learning models can reveal microbiome-immunotherapy interactions that may ultimately improve cancer patient outcomes.

The Association of Fractal Dimension with Vascularity and Clinical Outcomes in Glioblastoma.

BACKGROUND: Growing evidence indicates fractal analysis (FA) has potential as a computational tool to assess tumor microvasculature in glioblastoma (GBM). As fractal parameters of microvasculature have shown to be reliable quantitative biomarkers in brain tumors, there has been similar success in measuring the architecture of tumor tissue using FA in other tumor types. However, evaluating fractal parameters of tissue structure in relation to the microvasculature has not yet been implemented in GBM. We aimed to assess the utility of this methodology in quantifying structural characteristics of GBM cytoarchitecture and vascularity by correlating fractal parameters with gene expression. METHODS: Formalin-fixed paraffin-embedded specimens were retrospectively collected from 43 patients following resection of a newly diagnosed GBM; 4 normal brain specimens were obtained from epilepsy surgeries as controls. Tumor samples were processed using FA employing a software-based box-counting method algorithm and custom messenger RNA expression assays. Fractal parameters were then correlated with clinical features, outcomes, and a panel of 92 genes associated with vascularity and angiogenesis. RESULTS: Statistical analysis demonstrated that fractal-based indices were not adequate parameters for distinction of GBM cytoarchitecture compared with normal brain specimens. Correlation analysis of our gene expression findings suggested that hematoxylin and eosin-based FA may have adequate sensitivity to detect associations with vascular gene expression. CONCLUSIONS: The combination of neuropathological assessment and histology does not provide optimized data for FA in GBM. However, an association between FA and gene expression in GBM of genes pertaining to cytoarchitecture and angiogenesis warrants further investigation.

Loneliness and Daily Alcohol Consumption During the COVID-19 Pandemic.

AIMS: This pilot study aimed to identify associations of loneliness and daily alcohol consumption among US adults during the Coronavirus Disease-2019 pandemic. METHOD: Participants completed daily assessments for 30 days. RESULTS: Results suggest people who feel lonelier on average drink more alcohol, however, people who feel lonelier than usual drink less. CONCLUSION: Findings highlight the need to disaggregate within- and between-person components of alcohol use.

Frailty and Determinants of Health Among Older Adults in the United States 2011-2016.

OBJECTIVE: To characterize frailty phenotype in a representative cohort of older Americans and examine determinants of health factors. METHODS: Retrospective analysis of data from 5,553 adults ≥60 years old in the 2011-2016 cross-sectional National Health and Nutrition Examination Survey (NHANES). World Health Organization "Determinants of Health" conceptual model was used to prioritize variables for multinomial logistic regression for the outcome of modified Fried frailty phenotype. RESULTS: 482 participants (9%) were frail and 2432 (44%) prefrail. Four factors were highly associated with frailty: difficulty with ≥1 activity of daily living (77%; OR 24.81 p < 0.01), ≥2 hospitalizations in the previous year (17%, OR 3.94 p < 0.01), having >2 comorbidities (27%; OR 3.33 p < 0.01), and polypharmacy (66%; OR 2.38 p < 0.01). DISCUSSION: A modified Fried frailty assessment incorporating five self-reported criteria may be useful as a rapid nursing screen in low-resource settings. These assessments can streamline nursing care coordination and case management activities, thereby facilitating targeted frailty interventions to support healthy aging in vulnerable populations.

Automatic quadriceps and patellae segmentation of MRI with cascaded U2 -Net and SASSNet deep learning model.

PURPOSE: Automatic muscle segmentation is critical for advancing our understanding of human physiology, biomechanics, and musculoskeletal pathologies, as it allows for timely exploration of large multi-dimensional image sets. Segmentation models are rarely developed/validated for the pediatric model. As such, autosegmentation is not available to explore how muscle architectural changes during development and how disease/pathology affects the developing musculoskeletal system. Thus, we aimed to develop and validate an end-to-end, fully automated, deep learning model for accurate segmentation of the rectus femoris and vastus lateral, medialis, and intermedialis using a pediatric database. METHODS: We developed a two-stage cascaded deep learning model in a coarse-to-fine manner. In the first stage, the U2 -Net roughly detects the muscle subcompartment region. Then, in the second stage, the shape-aware 3D semantic segmentation method SASSNet refines the cropped target regions to generate the more finer and accurate segmentation masks. We utilized multifeature image maps in both stages to stabilize performance and validated their use with an ablation study. The second-stage SASSNet was independently run and evaluated with three different cropped region resolutions: the original image resolution, and images downsampled 2× and 4× (high, mid, and low). The relationship between image resolution and segmentation accuracy was explored. In addition, the patella was included as a comparator to past work. We evaluated segmentation accuracy using leave-one-out testing on a database of 3D MR images (0.43 × 0.43 × 2 mm) from 40 pediatric participants (age 15.3 ± 1.9 years, 55.8 ± 11.8 kg, 164.2 ± 7.9 cm, 38F/2 M). RESULTS: The mid-resolution second stage produced the best results for the vastus medialis, rectus femoris, and patella (Dice similarity coefficient = 95.0%, 95.1%, 93.7%), whereas the low-resolution second stage produced the best results for the vastus lateralis and vastus intermedialis (DSC = 94.5% and 93.7%). In comparing the low- to mid-resolution cases, the vasti intermedialis, vastus medialis, rectus femoris, and patella produced significant differences (p = 0.0015, p = 0.0101, p < 0.0001, p = 0.0003) and the vasti lateralis did not (p = 0.2177). The high-resolution stage 2 had significantly lower accuracy (1.0 to 4.4 dice percentage points) compared to both the mid- and low-resolution routines (p value ranged from < 0.001 to 0.04). The one exception was the rectus femoris, where there was no difference between the low- and high-resolution cases. The ablation study demonstrated that the multifeature is more reliable than the single feature. CONCLUSIONS: Our successful implementation of this two-stage segmentation pipeline provides a critical tool for expanding pediatric muscle physiology and clinical research. With a relatively small and variable dataset, our fully automatic segmentation technique produces accuracies that matched or exceeded the current state of the art. The two-stage segmentation avoids memory issues and excessive run times by using a first stage focused on cropping out unnecessary data. The excellent Dice similarity coefficients improve upon previous template-based automatic and semiautomatic methodologies targeting the leg musculature. More importantly, with a naturally variable dataset (size, shape, etc.), the proposed model demonstrates slightly improved accuracies, compared to previous neural networks methods.

Inflammation plays a causal role in fatigue-like behavior induced by pelvic irradiation in mice.

Fatigue is a persistent and debilitating symptom following radiation therapy for prostate cancer. However, it is not well-understood how radiation targeted to a small region of the body can lead to broad changes in behavior. In this study, we used targeted pelvic irradiation of healthy male mice to test whether inflammatory signaling mediates changes in voluntary physical activity levels. First, we tested the relationship between radiation dose, blood cell counts, and fatigue-like behavior measured as voluntary wheel-running activity. Next, we used oral minocycline treatments to reduce inflammation and found that minocycline reduces, but does not eliminate, the fatigue-like behavioral changes induced by radiation. We also used a strain of mice lacking the MyD88 adaptor protein and found that these mice also showed less fatigue-like behavior than the wild-type controls. Finally, using serum and brain tissue samples, we determined changes in inflammatory signaling induced by irradiation in wild-type, minocycline treated, and MyD88 knockout mice. We found that irradiation increased serum levels of IL-6, a change that was partially reversed in mice treated with minocycline or lacking MyD88. Overall, our results suggest that inflammation plays a causal role in radiation-induced fatigue and that IL-6 may be an important mediator.

Severity modeling of propionic acidemia using clinical and laboratory biomarkers.

PURPOSE: To conduct a proof-of-principle study to identify subtypes of propionic acidemia (PA) and associated biomarkers. METHODS: Data from a clinically diverse PA patient population ( https://clinicaltrials.gov/ct2/show/NCT02890342 ) were used to train and test machine learning models, identify PA-relevant biomarkers, and perform validation analysis using data from liver-transplanted participants. k-Means clustering was used to test for the existence of PA subtypes. Expert knowledge was used to define PA subtypes (mild and severe). Given expert classification, supervised machine learning (support vector machine with a polynomial kernel, svmPoly) performed dimensional reduction to define relevant features of each PA subtype. RESULTS: Forty participants enrolled in the study; five underwent liver transplant. Analysis with k-means clustering indicated that several PA subtypes may exist on the biochemical continuum. The conventional PA biomarkers, plasma total 2-methylctirate and propionylcarnitine, were not statistically significantly different between nontransplanted and transplanted participants motivating us to search for other biomarkers. Unbiased dimensional reduction using svmPoly revealed that plasma transthyretin, alanine:serine ratio, GDF15, FGF21, and in vivo 1-13C-propionate oxidation, play roles in defining PA subtypes. CONCLUSION: Support vector machine prioritized biomarkers that helped classify propionic acidemia patients according to severity subtypes, with important ramifications for future clinical trials and management of PA.

Brain-derived neurotrophic factor polymorphism Val66Met protects against cancer-related fatigue.

Cancer-related fatigue is an extremely common and debilitating psychiatric symptom that affects up to 80% of cancer patients. Despite its negative impact on the patient's quality of life, there is no well-established biomarker or mechanisms associated with this debilitating condition. The functional brain-derived neurotrophic factor (BDNF) Val66Met single nucleotide polymorphism (SNP) has been associated with a variety of psychiatric illnesses. We hypothesized that Val66Met may influence the risk for developing cancer-related fatigue. BDNF Val66Met was analyzed by polymerase chain reaction in 180 patients with confirmed cancer diagnoses. Fatigue was measured using the Functional Assessment of Cancer Therapy-Fatigue (FACIT-Fatigue) questionnaire. Depression was measured using the Hamilton Depression Scale (HAM-D). Data were transformed when necessary and regression models were constructed to access the association between genotype and symptom severity. Participants carrying the Met allele reported significantly less fatigue compared to the Val/Val genotype group. The presence of the Met allele did not influence depression levels. The results suggest that the BDNF Val66Met polymorphism confers protective advantage against cancer-related fatigue; whereas having the Val/Val genotype may be a genetic risk factor. Findings from this study not only provide clues to the neural basis of cancer-related fatigue, but also allow for symptom severity prediction and patient education with the goal to improve symptom management.

Analysis of National Library of Medicine (NLM) DOCLINE® Interlibrary Loan System Request Patterns during Selected Public Health Events.

DOCLINE®, the U.S. National Library of Medicine's (NLM) interlibrary loan (ILL) request system, sought to better understand its role in providing information access during public health events (PHEs). Such data can guide service improvement, especially when connecting the public health community to the latest research during such incidents. Four U.S. public health outbreaks were used to measure DOCLINE's capacity to support information seeking behaviors: requests during the Summer 2019 measles outbreak; the Fall 2019 e-cigarette lung injury event; the 2018-2019 influenza season; and early stages of the 2020 COVID-19 outbreak. NLM Medical Subject Headings were used to identify related requests. A team of NLM librarians analyzed these for trends in request volume, geographic and institution type, and content. While the number of PHE-related requests did not make up a large percentage of the total placed, there were identifiable increases during the selected periods. These originated from a variety of geographic locations, with some noticeable intersection with outbreak areas. Hospitals initiated the most requests. This investigation provides evidence that DOCLINE data can be used to drive system development and that a targeted ILL system with rapid turnaround times is an especially valuable library resource during PHEs.

A comparison of treatment patterns, healthcare resource utilization, and costs among young adult Medicaid beneficiaries with schizophrenia treated with paliperidone palmitate or oral atypical antipsychotics in the US.

BACKGROUND: Much of the burden associated with schizophrenia is attributed to its early onset and chronic nature. Treatment with once monthly paliperidone palmitate (PP1M) is associated with lower healthcare utilization and better adherence as compared to oral atypical antipsychotics (OAAs). This study aimed to evaluate real-world effectiveness of PP1M and OAA therapies among US-based adult Medicaid patients with schizophrenia, overall and among young adults aged 18-35 years. METHODS: Adult patients with a diagnosis of schizophrenia and at least two claims for PP1M or OAA between January 1, 2010 and December 31, 2014 were selected from the IBM Watson Health MarketScan Medicaid Database. Treatment patterns and healthcare resource utilization and costs were compared between PP1M and OAA treatment groups following inverse probability of treatment (IPT) weighting to adjust for potential differences. Utilization and cost outcomes were estimated using OLS and weighted Poisson regression models. RESULTS: After IPT weighting, the young adult PP1M and OAA cohorts were comprised of 3,095 and 3,155 patients, respectively. PP1M patients had a higher duration of continuous treatment exposure (168.2 vs 132.5 days, p = .004) and better adherence on the index medication (proportion of days covered ≥80%: 19.0% vs 17.1%, p < .049). Young adults treated with PP1M were 37% less likely to have an all-cause inpatient admission (odds ratio [OR] = 0.63, 95% confidence interval [CI] = 0.53-0.74) and 33% less likely to have an ER visit (OR = 0.67, 95% CI = 0.55-0.81) compared to OAA young adult patients, but 27% more likely to have an all-cause outpatient office visit (OR = 1.27, 95% CI = 1.02-1.56). PP1M patients incurred significantly lower medical costs as compared to OAA patients. CONCLUSIONS: Medicaid patients with schizophrenia treated with PP1M have higher medication adherence and have fewer hospitalizations as compared to patients treated with OAAs. PP1M may lead to reduced healthcare utilization and improved clinical outcomes.

The Direct and Indirect Costs Associated With Overactive Bladder Within a Commercially-Insured Population in the United States.

OBJECTIVE: To quantify the burden associated with overactive bladder (OAB) within a commercially-insured United States (US) population. METHODS: Adults with OAB identified from the MarketScan databases (2008 to 2013) were propensity score matched 1:1 to non-OAB controls. Per-patient-per-month (PPPM) direct healthcare costs, and indirect costs attributable to workplace absence and short-term disability (STD), were estimated. RESULTS: Adjusted PPPM healthcare costs were higher for OAB patients than matched controls for both direct costs ($3003 vs $1123; P < 0.0001) and indirect costs due to STD ($114 vs $98; P < 0.05). There was no difference in the indirect costs due to absence between the OAB cases and controls. CONCLUSIONS: The direct healthcare costs of OAB patients are substantial. Additional research is needed to quantify the impact of OAB on workplace productivity. Improved management of OAB symptoms may reduce costs and enhance patient quality of life.

The economic burden of overactive bladder (OAB) and its effects on the costs associated with other chronic, age-related comorbidities in the United States.

AIMS: The prevalence of OAB increases with age and is associated with several chronic comorbidities. However, the impact of OAB on the healthcare costs of patients with such comorbidities is not well-understood. This study aimed to quantify the impact of OAB on healthcare costs and assess the potential moderating effects of OAB on the costs of patients with chronic comorbidities. METHODS: Adults with evidence of OAB/OAB-related therapy between 1/1/2008-12/31/2013 were identified from two large, administrative claims databases. Per-patient-per-month (PPPM) expenditures for OAB cases were estimated and compared to those of propensity score-matched subjects without OAB. Costs were modeled using ordinary least squares regression including main effects and interactions of chronic depression, dementia, diabetes, hypertension, and osteoporosis with OAB. Values for the comparisons were calculated on the original dollar scale using smearing estimators. RESULTS: A total of 110 059 pairs of OAB cases and matched non-OAB controls were identified. The mean, multivariable-adjusted, PPPM all-cause costs of OAB cases from the model without interactions were $3003, compared to $1123 for matched controls (P < 0.0001). In the model assessing the interactions of chronic comorbidities with OAB, those OAB patients with comorbid depression, dementia, diabetes, hypertension, and osteoporosis incurred significantly higher costs than controls with these comorbidities. The synergistic effect of these interactions was estimated to be $95-$574 PPPM. CONCLUSIONS: Within this US-based population, the healthcare costs of OAB patients were more than 2.5 times those of similar patients without OAB. Additionally, patients with OAB and chronic, age-related comorbidities incurred higher healthcare costs than non-OAB controls with the same comorbidities.