The role of body mass index at diagnosis of colorectal cancer on Black-White disparities in survival: a density regression mediation approach.

The study of racial/ethnic inequalities in health is important to reduce the uneven burden of disease. In the case of colorectal cancer (CRC), disparities in survival among non-Hispanic Whites and Blacks are well documented, and mechanisms leading to these disparities need to be studied formally. It has also been established that body mass index (BMI) is a risk factor for developing CRC, and recent literature shows BMI at diagnosis of CRC is associated with survival. Since BMI varies by racial/ethnic group, a question that arises is whether differences in BMI are partially responsible for observed racial/ethnic disparities in survival for CRC patients. This article presents new methodology to quantify the impact of the hypothetical intervention that matches the BMI distribution in the Black population to a potentially complex distributional form observed in the White population on racial/ethnic disparities in survival. Our density mediation approach can be utilized to estimate natural direct and indirect effects in the general causal mediation setting under stronger assumptions. We perform a simulation study that shows our proposed Bayesian density regression approach performs as well as or better than current methodology allowing for a shift in the mean of the distribution only, and that standard practice of categorizing BMI leads to large biases when BMI is a mediator variable. When applied to motivating data from the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium, our approach suggests the proposed intervention is potentially beneficial for elderly and low-income Black patients, yet harmful for young or high-income Black populations.

A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota.

Statistical analysis of microbial genomic data within epidemiological cohort studies holds the promise to assess the influence of environmental exposures on both the host and the host-associated microbiome. However, the observational character of prospective cohort data and the intricate characteristics of microbiome data make it challenging to discover causal associations between environment and microbiome. Here, we introduce a causal inference framework based on the Rubin Causal Model that can help scientists to investigate such environment-host microbiome relationships, to capitalize on existing, possibly powerful, test statistics, and test plausible sharp null hypotheses. Using data from the German KORA cohort study, we illustrate our framework by designing two hypothetical randomized experiments with interventions of (i) air pollution reduction and (ii) smoking prevention. We study the effects of these interventions on the human gut microbiome by testing shifts in microbial diversity, changes in individual microbial abundances, and microbial network wiring between groups of matched subjects via randomization-based inference. In the smoking prevention scenario, we identify a small interconnected group of taxa worth further scrutiny, including Christensenellaceae and Ruminococcaceae genera, that have been previously associated with blood metabolite changes. These findings demonstrate that our framework may uncover potentially causal links between environmental exposure and the gut microbiome from observational data. We anticipate the present statistical framework to be a good starting point for further discoveries on the role of the gut microbiome in environmental health.

Development of a Definition of Postacute Sequelae of SARS-CoV-2 Infection.

Importance: SARS-CoV-2 infection is associated with persistent, relapsing, or new symptoms or other health effects occurring after acute infection, termed postacute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. Characterizing PASC requires analysis of prospectively and uniformly collected data from diverse uninfected and infected individuals. Objective: To develop a definition of PASC using self-reported symptoms and describe PASC frequencies across cohorts, vaccination status, and number of infections. Design, Setting, and Participants: Prospective observational cohort study of adults with and without SARS-CoV-2 infection at 85 enrolling sites (hospitals, health centers, community organizations) located in 33 states plus Washington, DC, and Puerto Rico. Participants who were enrolled in the RECOVER adult cohort before April 10, 2023, completed a symptom survey 6 months or more after acute symptom onset or test date. Selection included population-based, volunteer, and convenience sampling. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: PASC and 44 participant-reported symptoms (with severity thresholds). Results: A total of 9764 participants (89% SARS-CoV-2 infected; 71% female; 16% Hispanic/Latino; 15% non-Hispanic Black; median age, 47 years [IQR, 35-60]) met selection criteria. Adjusted odds ratios were 1.5 or greater (infected vs uninfected participants) for 37 symptoms. Symptoms contributing to PASC score included postexertional malaise, fatigue, brain fog, dizziness, gastrointestinal symptoms, palpitations, changes in sexual desire or capacity, loss of or change in smell or taste, thirst, chronic cough, chest pain, and abnormal movements. Among 2231 participants first infected on or after December 1, 2021, and enrolled within 30 days of infection, 224 (10% [95% CI, 8.8%-11%]) were PASC positive at 6 months. Conclusions and Relevance: A definition of PASC was developed based on symptoms in a prospective cohort study. As a first step to providing a framework for other investigations, iterative refinement that further incorporates other clinical features is needed to support actionable definitions of PASC.

Assessing environmental epidemiology questions in practice with a causal inference pipeline: An investigation of the air pollution-multiple sclerosis relapses relationship.

When addressing environmental health-related questions, most often, only observational data are collected for ethical or practical reasons. However, the lack of randomized exposure often prevents the comparison of similar groups of exposed and unexposed units. This design barrier leads the environmental epidemiology field to mainly estimate associations between environmental exposures and health outcomes. A recently developed causal inference pipeline was developed to guide researchers interested in estimating the effects of plausible hypothetical interventions for policy recommendations. This article illustrates how this multistaged pipeline can help environmental epidemiologists reconstruct and analyze hypothetical randomized experiments by investigating whether an air pollution reduction intervention decreases the risk of multiple sclerosis relapses in Alsace region, France. The epidemiology literature reports conflicted findings on the relationship between air pollution and multiple sclerosis. Some studies found significant associations, whereas others did not. Two case-crossover studies reported significant associations between the risk of multiple sclerosis relapses and the exposure to air pollutants in the Alsace region. We use the same study population as these epidemiological studies to illustrate how appealing this causal inference approach is to estimate the effects of hypothetical, but plausible, environmental interventions.

Multiple sclerosis incidence rate in southern Iran: a Bayesian epidemiological study.

BACKGROUND: Multiple Sclerosis (MS) remains to be a public health challenge, due to its unknown biological mechanisms and clinical impacts on young people. The prevalence of this disease in Iran is reported to be 5.30 to 74.28 per 100,000-person. Because of high prevalence of this disease in Fars province, the purpose of this study was to assess the spatial pattern of MS incidence rate by modeling both the associations s of spatial dependence between neighboring regions and risk factors in a Bayesian Poisson model, which can lead to the improvement of health resource allocation decisions. METHOD: Data from 5468 patients diagnosed with MS were collected, according to the McDonald's criteria. New cases of MS were reported by the MS Society of Fars province from 1991 until 2016. The association between the percentage of people with low vitamin D intake, smoking, abnormal BMI and alcohol consumption in addition to spatial structure in a Bayesian spatio-temporal hierarchical model were used to determine the relative risk and trend of MS incidence rate in 29 counties of Fars province. RESULTS: County-level crude incidence rates ranged from 0.22 to 11.31 cases per 100,000-person population. The highest relative risk was estimated at 1.80 in the county of Shiraz, the capital of Fars province, while the lowest relative risk was estimated at 0.11 in Zarindasht county in southern of Fars. The percentages of vitamin D supplementation intake and smoking were significantly associated with the incidence rate of MS. The results showed that 1% increase in vitamin D supplementation intake is associated with 2% decrease in the risk of MS and 1% increase in smoking is associated with 16% increase in the risk of MS. CONCLUSION: Bayesian spatio-temporal analysis of MS incidence rate revealed that the trend in the south and south east of Fars province is less steep than the mean trend of this disease. The lower incidence rate was associated with a higher percentage of vitamin D supplementation intake and a lower percentage of smoking. Previous studies have also shown that smoking and low vitamin D, among all covariates or risk factors, might be associated with high incidence of MS.

The Role of Ambient Particle Radioactivity in Inflammation and Endothelial Function in an Elderly Cohort.

BACKGROUND: The mechanisms by which exposure to particulate matter might increase risk of cardiovascular morbidity and mortality are not fully known. However, few existing studies have investigated the potential role of particle radioactivity. Naturally occurring radionuclides attach to particulate matter and continue to release ionizing radiation after inhalation and deposition in the lungs. We hypothesize that exposure to particle radioactivity increases biomarkers of inflammation. METHODS: Our repeated-measures study included 752 men in the greater Boston area. We estimated regional particle radioactivity as a daily spatial average of gross beta concentrations from five monitors in the study area. We used linear mixed-effects regression models to estimate short- and medium-term associations between particle radioactivity and biomarkers of inflammation and endothelial dysfunction, with and without adjustment for additional particulate air pollutants. RESULTS: We observed associations between particle radioactivity on C-reactive protein (CRP), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1), but no associations with fibrinogen. An interquartile range width increase in mean 7-day particle radioactivity (1.2 × 10 Bq/m) was associated with a 4.9% increase in CRP (95% CI = 0.077, 9.9), a 2.8% increase in ICAM-1 (95% CI = 1.4, 4.2), and a 4.3% increase in VCAM-1 (95% CI = 2.5, 6.1). The main effects of particle radioactivity remained similar after adjustment in most cases. We also obtained similar effect estimates in a sensitivity analysis applying a robust causal model. CONCLUSION: Regional particle radioactivity is positively associated with inflammatory biomarkers, indicating a potential pathway for radiation-induced cardiovascular effects.

Larval zebrafish as an in vitro model for evaluating toxicological effects of mycotoxins.

The presence of mycotoxins in food has created concern. Mycotoxin prevalence in our environment has changed in the last few years maybe due to climatic and other environmental changes. Evidence has emerged from in vitro and in vivo models: some mycotoxins have been found to be potentially carcinogenic, embryogenically harmful, teratogenic, and to generate nephrotoxicity. The risk assessment of exposures to mycotoxins at early life stages became mandatory. In this regard, the effects of toxic compounds on zebrafish have been widely studied, and more recently, mycotoxins have been tested with respect to their effects on developmental and teratogenic effects in this model system, which offers several advantages as it is an inexpensive and an accessible vertebrate model to study developmental toxicity. External post-fertilization and quick maturation make it sensitive to environmental effects and facilitate the detection of endpoints such as morphological deformities, time of hatching, and behavioral responses. Therefore, there is a potential for larval zebrafish to provide new insights into the toxicological effects of mycotoxins. We provide an overview of recent mycotoxin toxicological research in zebrafish embryos and larvae, highlighting its usefulness to toxicology and discuss the strengths and limitations of this model system.

Educational Interventions on Human Papillomavirus for Oral Health Providers.

The aim of this study was to evaluate the effectiveness of an educational intervention on HPV infection, HPV-related cancers and prevention modalities to improve Oral Health Care Providers (OHPs) knowledge and awareness about these topics, considering the rise of HPV-related malignancies in the USA. Educational sessions on HPV were offered to OHPs between 2016 and 2018 in the New England area. Participants were asked to fill out a questionnaire both before and after each session. Responses from the pre-questionnaire were compared to those from the post-questionnaire to evaluate the effectiveness of the lectures in increasing HPV-related knowledge of the OHPs. Among 277 participants, 263 completed both the pre- and post-questionnaire. A significant improvement was observed for the following categories: epidemiology of HPV infections, HPV-related diseases, and HPV vaccination and prevention. After the educational intervention, OHPs also indicated an increased comfort level in regard to educating their patients about the importance of HPV vaccination. Educational lectures can be effective in increasing OHPs knowledge and awareness about HPV, HPV-related cancers, and vaccination. More educational sessions on HPV are needed to reach a larger number of OHPs. OHPs may be the first to identify signs and symptoms of HPV-related oropharyngeal cancers. In addition, they may encourage their patients to take advantage of the HPV vaccine.

Causal Modeling in Environmental Health.

The field of environmental health has been dominated by modeling associations, especially by regressing an observed outcome on a linear or nonlinear function of observed covariates. Readers interested in advances in policies for improving environmental health are, however, expecting to be informed about health effects resulting from, or more explicitly caused by, environmental exposures. The quantification of health impacts resulting from the removal of environmental exposures involves causal statements. Therefore, when possible, causal inference frameworks should be considered for analyzing the effects of environmental exposures on health outcomes.

Ozone, NO2 and PM10 are associated with the occurrence of multiple sclerosis relapses. Evidence from seasonal multi-pollutant analyses.

BACKGROUND: Triggers of multiple sclerosis (MS) relapses are essentially unknown. PM10 exposure has recently been associated with an increased risk of relapses. OBJECTIVES: We further explore the short-term associations between PM10, NO2, benzene (C6H6), O3, and CO exposures, and the odds of MS relapses' occurrence. METHODS: Using a case-crossover design, we studied 424 MS patients living in the Strasbourg area, France between 2000 and 2009 (1783 relapses in total). Control days were chosen to be ± 35 days relative to the case (relapse) day. Exposure was modeled through ADMS-Urban software at the census block scale. We consider single-pollutant and multi-pollutant conditional logistic regression models coupled with a distributed-lag linear structure, stratified by season ("hot" vs. "cold"), and adjusted for meteorological parameters, pollen count, influenza-like epidemics, and holidays. RESULTS: The single-pollutant analyses indicated: 1) significant associations between MS relapse incidence and exposures to NO2, PM10, and O3, and 2) seasonality in these associations. For instance, an interquartile range increase in NO2 (lags 0-3) and PM10 exposure were associated with MS relapse incidence (OR = 1.08; 95%CI: [1.03-1.14] and OR = 1.06; 95%CI: [1.01-1.11], respectively) during the "cold" season (i.e., October-March). We also observed an association with O3 and MS relapse incidence during "hot" season (OR = 1.16; 95%CI: [1.07-1.25]). C6H6 and CO were not significantly related to MS relapse incidence. However, using multi-pollutant models, only O3 remained significantly associated with the odds of relapse triggering during "hot" season. CONCLUSION: We observed significant single-pollution associations between the occurrence of MS relapses and exposures to NO2, O3 and PM10, only O3 remained significantly associated with occurrence of MS relapses in the multi-pollutant model.

Traffic-Related Air Pollution, Blood Pressure, and Adaptive Response of Mitochondrial Abundance.

BACKGROUND: Exposure to black carbon (BC), a tracer of vehicular-traffic pollution, is associated with increased blood pressure (BP). Identifying biological factors that attenuate BC effects on BP can inform prevention. We evaluated the role of mitochondrial abundance, an adaptive mechanism compensating for cellular-redox imbalance, in the BC-BP relationship. METHODS AND RESULTS: At ≥ 1 visits among 675 older men from the Normative Aging Study (observations=1252), we assessed daily BP and ambient BC levels from a stationary monitor. To determine blood mitochondrial abundance, we used whole blood to analyze mitochondrial-to-nuclear DNA ratio (mtDNA/nDNA) using quantitative polymerase chain reaction. Every standard deviation increase in the 28-day BC moving average was associated with 1.97 mm Hg (95% confidence interval [CI], 1.23-2.72; P<0.0001) and 3.46 mm Hg (95% CI, 2.06-4.87; P<0.0001) higher diastolic and systolic BP, respectively. Positive BC-BP associations existed throughout all time windows. BC moving averages (5-day to 28-day) were associated with increased mtDNA/nDNA; every standard deviation increase in 28-day BC moving average was associated with 0.12 standard deviation (95% CI, 0.03-0.20; P=0.007) higher mtDNA/nDNA. High mtDNA/nDNA significantly attenuated the BC-systolic BP association throughout all time windows. The estimated effect of 28-day BC moving average on systolic BP was 1.95-fold larger for individuals at the lowest mtDNA/nDNA quartile midpoint (4.68 mm Hg; 95% CI, 3.03-6.33; P<0.0001), in comparison with the top quartile midpoint (2.40 mm Hg; 95% CI, 0.81-3.99; P=0.003). CONCLUSIONS: In older adults, short-term to moderate-term ambient BC levels were associated with increased BP and blood mitochondrial abundance. Our findings indicate that increased blood mitochondrial abundance is a compensatory response and attenuates the cardiac effects of BC.

Distributional changes in gene-specific methylation associated with temperature.

Temperature has been related to mean differences in DNA methylation. However, heterogeneity in these associations may exist across the distribution of methylation outcomes. This study examined whether the association between three-week averaged of temperature and methylation differs across quantiles of the methylation distributions in nine candidate genes. We measured gene-specific blood methylation repeatedly in 777 elderly men participating in the Normative Aging Study (1999-2010). We fit quantile regressions for longitudinal data to investigate whether the associations of temperature on methylation (expressed as %5mC) varied across the distribution of the methylation outcomes. We observed heterogeneity in the associations of temperature across percentiles of methylation in F3, TLR-2, CRAT, iNOS, and ICAM-1 genes. For instance, an increase in three-week temperature exposure was associated with a longer left-tail of the F3 methylation distribution. A 5°C increase in temperature was associated with a 0.15%5mC (95% confidence interval (CI): -0.27,-0.04) decrease on the 20th quantile of F3 methylation, but was not significantly related to the 80th quantile of this distribution (Estimate:0.06%5mC, 95%CI: -0.22, 0.35). Individuals with low values of F3, TLR-2, CRAT, and iNOS methylation, as well as a high value of ICAM-1 methylation, may be more susceptible to temperature effects on systemic inflammation.

Estimating Causal Associations of Fine Particles With Daily Deaths in Boston.

Many studies have reported associations between daily particles less than 2.5 µm in aerodynamic diameter (PM2.5) and deaths, but they have been associational studies that did not use formal causal modeling approaches. On the basis of a potential outcome approach, we used 2 causal modeling methods with different assumptions and strengths to address whether there was a causal association between daily PM2.5 and deaths in Boston, Massachusetts (2004-2009). We used an instrumental variable approach, including back trajectories as instruments for variations in PM2.5 uncorrelated with other predictors of death. We also used propensity score as an alternative causal modeling analysis. The former protects against confounding by measured and unmeasured confounders and is based on the assumption of a valid instrument. The latter protects against confounding by all measured covariates, provides valid estimates in the case of effect modification, and is based on the assumption of no unmeasured confounders. We found a causal association of PM2.5 with mortality, with a 0.53% (95% confidence interval: 0.09, 0.97) and a 0.50% (95% confidence interval: 0.20, 0.80) increase in daily deaths using the instrumental variable and the propensity score, respectively. We failed to reject the null association with exposure after the deaths (P =0.93). Given these results, prior studies, and extensive toxicological support, the association between PM2.5 and deaths is almost certainly causal.

Effects of temperature and relative humidity on DNA methylation.

BACKGROUND: Previous studies have found relationships between DNA methylation and various environmental contaminant exposures. Associations with weather have not been examined. Because temperature and humidity are related to mortality even on non-extreme days, we hypothesized that temperature and relative humidity may affect methylation. METHODS: We repeatedly measured methylation on long interspersed nuclear elements (LINE-1), Alu, and 9 candidate genes in blood samples from 777 elderly men participating in the Normative Aging Study (1999-2009). We assessed whether ambient temperature and relative humidity are related to methylation on LINE-1 and Alu, as well as on genes controlling coagulation, inflammation, cortisol, DNA repair, and metabolic pathway. We examined intermediate-term associations of temperature, relative humidity, and their interaction with methylation, using distributed lag models. RESULTS: Temperature or relative humidity levels were associated with methylation on tissue factor (F3), intercellular adhesion molecule 1 (ICAM-1), toll-like receptor 2 (TRL-2), carnitine O-acetyltransferase (CRAT), interferon gamma (IFN-γ), inducible nitric oxide synthase (iNOS), and glucocorticoid receptor, LINE-1, and Alu. For instance, a 5°C increase in 3-week average temperature in ICAM-1 methylation was associated with a 9% increase (95% confidence interval: 3% to 15%), whereas a 10% increase in 3-week average relative humidity was associated with a 5% decrease (-8% to -1%). The relative humidity association with ICAM-1 methylation was stronger on hot days than mild days. CONCLUSIONS: DNA methylation in blood cells may reflect biological effects of temperature and relative humidity. Temperature and relative humidity may also interact to produce stronger effects.

Accelerated aging and altered subclinical response to ozone exposure in young, healthy adults.

Ozone exposure induces a myriad of adverse cardiopulmonary outcomes in humans. Although advanced age and chronic disease are factors that may exacerbate a person's negative response to ozone exposure, there are no molecular biomarkers of susceptibility. Here, we examine whether epigenetic age acceleration (EAA) is associated with responsiveness to short-term ozone exposure. Using data from a crossover-controlled exposure study (n = 17), we examined whether EAA, as measured in lung epithelial cells collected 24 h after clean air exposure, modifies the observed effect of ozone on autonomic function, cardiac electrophysiology, hemostasis, pulmonary function, and inflammation. EAA was assessed in lung epithelial cells extracted from bronchoalveolar lavage fluids, using the pan-tissue aging clock. We used two analytic approaches: (i) median regression to estimate the association between EAA and the estimated risk difference for subclinical responses to ozone and (ii) a block randomization approach to estimate EAA's effect modification of subclinical responses. For both approaches, we calculated Fisher-exact P-values, allowing us to bypass large sample size assumptions. In median regression analyses, accelerated epigenetic age modified associations between ozone and heart rate-corrected QT interval (QTc) ([Formula: see text]= 0.12, P-value = 0.007) and between ozone and C-reactive protein ([Formula: see text] = -0.18, P = 0.069). During block randomization, the directions of association remained consistent for QTc and C-reactive protein; however, the P-values weakened. Block randomization also revealed that responsiveness of plasminogen activator inhibitor-1 (PAI-1) to ozone exposure was modified by accelerated epigenetic aging (PAI-1 difference between accelerated aging-defined block groups = -0.54, P-value = 0.039). In conclusion, EAA is a potential biomarker for individuals with increased susceptibility to ozone exposure even among young, healthy adults.

Researching COVID to enhance recovery (RECOVER) tissue pathology study protocol: Rationale, objectives, and design.

IMPORTANCE: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or organ dysfunction after the acute phase of infection, termed Post-Acute Sequelae of SARS-CoV-2 (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are poorly understood. The objectives of the Researching COVID to Enhance Recovery (RECOVER) tissue pathology study (RECOVER-Pathology) are to: (1) characterize prevalence and types of organ injury/disease and pathology occurring with PASC; (2) characterize the association of pathologic findings with clinical and other characteristics; (3) define the pathophysiology and mechanisms of PASC, and possible mediation via viral persistence; and (4) establish a post-mortem tissue biobank and post-mortem brain imaging biorepository. METHODS: RECOVER-Pathology is a cross-sectional study of decedents dying at least 15 days following initial SARS-CoV-2 infection. Eligible decedents must meet WHO criteria for suspected, probable, or confirmed infection and must be aged 18 years or more at the time of death. Enrollment occurs at 7 sites in four U.S. states and Washington, DC. Comprehensive autopsies are conducted according to a standardized protocol within 24 hours of death; tissue samples are sent to the PASC Biorepository for later analyses. Data on clinical history are collected from the medical records and/or next of kin. The primary study outcomes include an array of pathologic features organized by organ system. Causal inference methods will be employed to investigate associations between risk factors and pathologic outcomes. DISCUSSION: RECOVER-Pathology is the largest autopsy study addressing PASC among US adults. Results of this study are intended to elucidate mechanisms of organ injury and disease and enhance our understanding of the pathophysiology of PASC.

Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design.

IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or "Long COVID") in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults. OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIH's REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of four cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study (n = 10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n = 6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n = 6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n = 600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science. CONCLUSIONS AND RELEVANCE: RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions. CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.

High-dimensional randomization-based inference capitalizing on classical design and modern computing.

A common complication that can arise with analyses of high-dimensional data is the repeated use of hypothesis tests. A second complication, especially with small samples, is the reliance on asymptotic p-values. Our proposed approach for addressing both complications uses a scientifically motivated scalar summary statistic, and although not entirely novel, seems rarely used. The method is illustrated using a crossover study of seventeen participants examining the effect of exposure to ozone versus clean air on the DNA methylome, where the multivariate outcome involved 484,531 genomic locations. Our proposed test yields a single null randomization distribution, and thus a single Fisher-exact p-value that is statistically valid whatever the structure of the data. However, the relevance and power of the resultant test requires the careful a priori selection of a single test statistic. The common practice using asymptotic p-values or meaningless thresholds for "significance" is inapposite in general.

The role of combat exposure on drinking behavior and subjective well-being: A Rubin Causal Model approach.

OBJECTIVE: Investigating the role of combat exposure on behavioral outcomes has been limited due to ethical and logistical constraints. METHOD: Using a large data set from UK BioBank of U.K. citizens (n = 157,161), we created hypothetical randomized experiments, with treatment conditions for combat exposure or no combat exposure matched for relevant covariates and compared differences in combat exposure groups on a broad range of alcohol-related and subjective well-being outcomes. Additionally, using a randomization-based approach, we calculated 95% Fisherian intervals for constant treatment effects consistent with the matched data and the hypothetical combat exposure intervention. RESULTS: Results suggest that combat exposure plays a role in several negative outcomes related to alcohol behavior and subjective well-being, such as increased typical daily alcohol consumption (estimated average causal effect [ACE] = 0.0545, Fisher p-value = .0119) and less general health happiness (estimated ACE = -0.1077, Fisher p-value < 1/100,000). CONCLUSIONS: This study expands our current understanding of the role of combat exposure on many alcohol and subjective well-being-related measures. We also show that the Rubin Causal Model provides a rigorous and valid approach to better understand myriad other issues in psychological science. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A permutation-based approach using a rank-based statistic to identify sex differences in epigenetics.

Epigenetic sex differences and their resulting implications for human health have been studied for about a decade. The objective of this paper is to use permutation-based inference and a new ranked-based test statistic to identify sex-based epigenetic differences in the human DNA methylome. In particular, we examine whether we could identify separations between the female and male distributions of DNA methylation across hundred of thousands CpG sites in two independent cohorts, the Swedish Adoption Twin study and the Lamarck study. Based on Fisherian p-values, we set a threshold for methylation differences "worth further scrutiny". At this threshold, we were able to confirm previously-found CpG sites that stratify with respect to sex. These CpG sites with sex differences in DNA methylation should be further investigated for their possible contribution to various physiological and pathological functions in the human body. We followed-up our statistical analyses with a literature review in order to inform the proposed disease implications for the loci we uncovered.