Methods for Multivariate Exposures with Application to Network Interference and Exposure Mixtures

Treatments in real-world settings are often multifaceted. Studies may explore the effect of peer social distancing on an individual's infectious disease status or the impact of exposure to multiple trace elements in the body simultaneously on chronic disease. Multiple components of the treatment varying simultaneously can be represented succinctly as a multivariate exposure (MVE). MVE can be studied jointly to build a holistic understanding of the complex relationship between exposures and health outcomes. This dissertation considers three topics related to MVE. The first topic considers causal inference with interference, specifically within networks of interacting individuals where interference may be present. Interference occurs when one person's treatment affects another person's outcome, which is a form of MVE that violates standard structural assumptions usually required for valid causal inference. Randomization-based inference (RI) methods provide a theoretical basis for causal inference in randomized studies, even in the presence of interference. The first project in this dissertation considers RI of the intervention effect in the eX-FLU trial, a randomized study designed to assess the effect of a social distancing intervention on influenza-like-illness transmission in a connected network of college students. The proposed methods are evaluated empirically with simulations and applied to data from the eX-FLU trial. The second topic introduces causal methods for MVE in observational studies. Observational studies often collect information on multiple correlated exposures simultaneously, resulting in an exposure mixture with components that may synergistically or antagonistically impact disease. Specifying a confounding set to satisfy causal identifiability assumptions with an exposure mixture can be challenging, due to the numerous possible relationships between the MVE, confounders, and outcome. The second project in this dissertation proposes a Bayesian approach to confounder adjustment that allows for non-linear and non-additive interaction effects among exposures. This method provides inference about causal effects that accounts for the uncertainty in model selection. The proposed approach is evaluated through simulations and applied to data from the Sister Study to study the causal relationship between a mixture of metal concentrations in the body and BMI in a cohort of women. The third topic explores methods for identifying risk-relevant components of an exposure mixture, characterized by a large or high-dimensional set of correlated exposures measured simultaneously. With correlated exposures, methods that impose linearity or restrictions on interactions in the outcome model may miss informative synergistic interactions among exposures. The third project proposes a genetic algorithm to identify sets of exposures within a large exposure mixture that are jointly informative for risk of an outcome. The proposed approach is compared with existing methods for variable selection and applied to data from the China Health and Nutrition Survey to identify subsets of a metabolite mixture that are predictive of hypertension.Doctor of Philosoph

Single-Cell Profiling Reveals Inflammatory Polarization of Human Carotid Versus Femoral Plaque Leukocytes

Femoral atherosclerotic plaques are less inflammatory than carotid plaques histologically, but limited cell-level data exist regarding comparative immune landscapes and polarization at these sites. We investigated intraplaque leukocyte phenotypes and transcriptional polarization in 49 patients undergoing femoral (n = 23) or carotid (n = 26) endarterectomy using single-cell RNA-Seq (scRNA-Seq; n = 13), flow cytometry (n = 24), and IHC (n = 12). Comparative scRNA-Seq of CD45+-selected leukocytes from femoral (n = 9; 35,265 cells) and carotid (n = 4; 30,655 cells) plaque revealed distinct transcriptional profiles. Inflammatory foam cell-like macrophages and monocytes comprised higher proportions of myeloid cells in carotid plaques, whereas noninflammatory foam cell-like macrophages and LYVE1-overexpressing macrophages comprised higher proportions of myeloid cells in femoral plaque (P \u3c 0.001 for all). A significant comparative excess of CCR2+ macrophages in carotid versus plaque was observed by flow cytometry in a separate validation cohort. B cells were more prevalent and exhibited a comparatively antiinflammatory profile in femoral plaque, whereas cytotoxic CD8+ T cells were more prevalent in carotid plaque. In conclusion, human femoral plaques exhibit distinct macrophage phenotypic and transcriptional profiles as well as diminished CD8+ T cell populations compared with human carotid plaques

Comparing postacute care healthcare charges after hospitalisation due to influenza or COVID-19 infection in an all-payer administrative dataset in the USA: a retrospective cohort study

Objective SARS-CoV-2 infection often causes a persistent syndrome of multiorgan dysfunction with symptoms that may be debilitating. Individuals seeking care for this syndrome are likely to generate significant healthcare utilisation and spending. It is unknown if healthcare costs after SARS-CoV-2 infection differ from those after influenza infection.Methods and analysis We used an all-payer administrative dataset comprised coding and billing data from 446 hospitals in the USA that use a financial analytics platform by Strata Decision Technology. The deidentified analytical sample included patients aged 18 years or older who were admitted to a hospital between July 2018 and May 2021 with an International Classification of Disease-10 code for COVID-19 or influenza. Analyses were stratified by age (18–44, 45–64 and 65+) and need for ventilation during acute hospitalisation. Linear regression models were used to evaluate the relationship between infection type (COVID-19 or influenza) and cumulative charges between 1 and 5 months after hospitalisation. Independent variables included medical comorbidities, health system classification and prehospitalisation charges, among others.Results Of 110 381 patients included in our analysis, 94 927 (86.0%) were hospitalised for COVID-19 and 15 454 (14.0%) were hospitalised for influenza. Patients hospitalised for COVID-19 generated a median of US$5248 (inter-quartile range (IQR) US$25693) in postacute healthcare charges, whereas patients hospitalised for influenza generated a median of US$8463 (IQR US$41063). Compared with influenza, linear model results demonstrated no significant differences in postacute charges among patients hospitalised with COVID-19.Conclusion Our findings suggest that individual healthcare expenditures after acute COVID-19 infection are not significantly different from those after influenza infection

Additional file 1 of Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth

Supplementary Material 1

Parasite DNA and Markers of Decreased Immune Activation Associate Prospectively with Cardiac Functional Decline over 10 Years among Trypanosoma cruzi Seropositive Individuals in Brazil

International audienceParasitemia and inflammatory markers are cross-sectionally associated with chronic Chagas cardiomyopathy (CCC) among patients with Trypanosoma cruzi. However, the prospective association of the parasite load and host immune response-related characteristics with CCC (that is, progressors) among T. cruzi seropositive individuals has only been partially defined. In a cohort of T. cruzi seropositive patients in Montes Claros and São Paulo, Brazil who were followed over 10 years, we identified the association of a baseline T. cruzi parasite load and systemic markers of inflammation with a decline in cardiac function and/or the presence of cardiac congestion 10 years later. The progressors (n = 21) were individuals with a significant decline in the left ventricular ejection fraction and/or elevated markers of cardiac congestion after 10 years. The controls (n = 31) had normal markers of cardiac function and congestion at the baseline and at the follow-up. They were matched with the progressors on age, sex, and genetic ancestry. The progressors had higher mean parasite loads at the baseline than the controls (18.3 vs. 0.605 DNA parasite equivalents/20 mL, p < 0.05). Of the 384 inflammation-related proteins analyzed, 47 differed significantly at a false discovery rate- (FDR-) corrected p < 0.05 between the groups. There were 44 of these 47 proteins that were significantly higher in the controls compared to in the progressors, including the immune activation markers CCL21, CXCL12, and HCLS1 and several of the tumor necrosis factor superfamily of proteins. Among the individuals who were seropositive for T. cruzi at the baseline and who were followed over 10 years, those with incident CCC at the 10-year marker had a comparatively higher baseline of T. cruzi parasitemia and lower baseline markers of immune activation and chemotaxis. These findings generate the hypothesis that the early impairment of pathogen-killing immune responses predisposes individuals to CCC, which merits further study

Study protocol for a longitudinal observational study of disparities in sleep and cognition in older adults: the DISCO study

Introduction Cognitive dysfunction, a leading cause of mortality and morbidity in the USA and globally, has been shown to disproportionately affect the socioeconomically disadvantaged and those who identify as black or Hispanic/Latinx. Poor sleep is strongly associated with the development of vascular and metabolic diseases, which correlate with cognitive dysfunction. Therefore, sleep may contribute to observed disparities in cognitive disorders. The Epidemiologic Study of Disparities in Sleep and Cognition in Older Adults (DISCO) is a longitudinal, observational cohort study that focuses on gathering data to better understand racial/ethnic sleep disparities and illuminate the relationship among sleep, race and ethnicity and changes in cognitive function. This investigation may help inform targeted interventions to minimise disparities in cognitive health among ageing adults.Methods and analysis The DISCO study will examine up to 495 individuals aged 55 and older at two time points over 24 months. An equal number of black, white and Hispanic/Latinx individuals will be recruited using methods aimed for adults traditionally under-represented in research. Study procedures at each time point will include cognitive tests, gait speed measurement, wrist actigraphy, a type 2 home polysomnography and a clinical examination. Participants will also complete self-identified assessments and questionnaires on cognitive ability, sleep, medication use, quality of life, sociodemographic characteristics, diet, substance use, and psychological and social health.Ethics and dissemination This study was approved by the Northwestern University Feinberg School of Medicine Institutional Review Board. Deidentified datasets will be shared via the BioLINCC repository following the completion of the project. Biospecimen samples from the study that are not being analysed can be made available to qualified investigators on review and approval by study investigators. Requests that do not lead to participant burden or that conflict with the primary aims of the study will be reviewed by the study investigators