Faculty Bibliography

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73-0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49-0.55]) compared to case incidence rate (0.65 [0.62-0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.

SIGNIFICANCE STATEMENT:We describe circulating proteins associated with albuminuria in a population of African American Study of Kidney Disease and Hypertension with CKD (AASK) using the largest proteomic platform to date: nearly 7000 circulating proteins, representing approximately 2000 new targets. Findings were replicated in a subset of a general population cohort with kidney disease (ARIC) and a population with CKD Chronic Renal Insufficiency Cohort (CRIC). In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in the Black group, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. LMAN2, TNFSFR1B, and members of the ephrin superfamily had the strongest associations. Pathway analysis also demonstrated enrichment of ephrin family proteins. BACKGROUND:Proteomic techniques have facilitated understanding of pathways that mediate decline in GFR. Albuminuria is a key component of CKD diagnosis, staging, and prognosis but has been less studied than GFR. We sought to investigate circulating proteins associated with higher albuminuria. METHODS:We evaluated the cross-sectional associations of the blood proteome with albuminuria and longitudinally with doubling of albuminuria in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; mean GFR 46; median urine protein-to-creatinine ratio 81 mg/g; n =703) and replicated in two external cohorts: a subset of the Atherosclerosis Risk in Communities (ARIC) study with CKD and the Chronic Renal Insufficiency Cohort (CRIC). RESULTS:In cross-sectional analysis, 104 proteins were significantly associated with albuminuria in AASK, of which 67 of 77 available proteins were replicated in ARIC and 68 of 71 available proteins in CRIC. Proteins with the strongest associations included LMAN2, TNFSFR1B, and members of the ephrin superfamily. Pathway analysis also demonstrated enrichment of ephrin family proteins. Five proteins were significantly associated with worsening albuminuria in AASK, including LMAN2 and EFNA4, which were replicated in ARIC and CRIC. CONCLUSIONS:Among individuals with CKD, large-scale proteomic analysis identified known and novel proteins associated with albuminuria and suggested a role for ephrin signaling in albuminuria progression.

Plastic pollution breaks a planetary boundary threatening wildlife and humans through its physical and chemical effects. Of the latter, the release of endocrine disrupting chemicals (EDCs) has consequences on the prevalence of human diseases related to the endocrine system. Bisphenols (BPs) and phthalates are two groups of EDCs commonly found in plastics that migrate into the environment and make low-dose human exposure ubiquitous. Here we review epidemiological, animal, and cellular studies linking exposure to BPs and phthalates to altered glucose regulation, with emphasis on the role of pancreatic β-cells. Epidemiological studies indicate that exposure to BPs and phthalates is associated with diabetes mellitus. Studies in animal models indicate that treatment with doses within the range of human exposure decreases insulin sensitivity and glucose tolerance, induces dyslipidemia, and modifies functional β-cell mass and serum levels of insulin, leptin, and adiponectin. These studies reveal that disruption of β-cell physiology by EDCs plays a key role in impairing glucose homeostasis by altering the mechanisms used by β-cells to adapt to metabolic stress such as chronic nutrient excess. Studies at the cellular level demonstrate that BPs and phthalates modify the same biochemical pathways involved in adaptation to chronic excess fuel. These include changes in insulin biosynthesis and secretion, electrical activity, expression of key genes, and mitochondrial function. The data summarized here indicate that BPs and phthalates are important risk factors for diabetes mellitus and support a global effort to decrease plastic pollution and human exposure to EDCs.

Substantial heterogeneity in effects of social policies on health across subgroups may be common, but has not been systematically characterized. Using a sample of 55 contemporary studies on health effects of social policies, we recorded how often heterogeneous treatment effects (HTEs) were assessed, for what subgroups (e.g., male, female), and the subgroup-specific effect estimates expressed as Standardized Mean Differences (SMDs). For each study, outcome, and dimension (e.g., gender), we fit a random-effects meta-analysis. We characterized the magnitude of heterogeneity in policy effects using the standard deviation of the subgroup-specific effect estimates (Ï„). Among the 44% of studies reporting subgroup-specific estimates, policy effects were generally small (<0.1 SMDs) with mixed impacts on health (67% beneficial) and disparities (50% implied narrowing of disparities). Across study-outcome-dimensions, 54% indicated any heterogeneity in effects, and 20% had Ï„ > 0.1 SMDs. For 26% of study-outcome-dimensions, the magnitude of Ï„ indicated that effects of opposite signs were plausible across subgroups. Heterogeneity was more common in policy effects not specified a priori. Our findings suggest social policies commonly have heterogeneous effects on health of different populations; these HTEs may substantially impact disparities. Studies of social policies and health should routinely evaluate HTEs.

STUDY QUESTION:How did the first two coronavirus disease 2019 (COVID-19) waves affect fertility rates in the USA? SUMMARY ANSWER:States differed widely in how their fertility rates changed following the COVID-19 outbreak and these changes were influenced more by state-level economic, racial, political, and social factors than by COVID-19 wave severity. WHAT IS KNOWN ALREADY:The outbreak of the COVID-19 pandemic contributed to already declining fertility rates in the USA, but not equally across states. Identifying drivers of differential changes in fertility rates can help explain variations in demographic shifts across states in the USA and motivate policies that support families in general, not only during crises. STUDY DESIGN, SIZE, DURATION:This is an ecological study using state-level data from 50 US states and the District of Columbia (n = 51). The study period extends from 2020 to 2021 with historical data from 2016 to 2019. We identified Wave 1 as the first apex for each state after February 2020 and Wave 2 as the second apex, during Fall/Winter 2020-2021. PARTICIPANTS/MATERIALS, SETTING, METHODS:State-level COVID-19 wave severity, defined as case acceleration during each 3-month COVID-19 wave (cases/100 000 population/month), was derived from 7-day weekly moving average COVID-19 case rates from the US Centers for Disease Control and Prevention (CDC). State-level fertility rate changes (change in average monthly fertility rate/100 000 women of reproductive age (WRA)/year) were derived from the CDC Bureau of Vital Statistics and from 2020 US Census and University of Virginia 2021 population estimates 9 months after each COVID-19 wave. We performed univariate analyses to describe national and state-level fertility rate changes following each wave, and simple and multivariable linear regression analyses to assess the relation of COVID-19 wave severity and other state-level characteristics with fertility rate changes. MAIN RESULTS AND THE ROLE OF CHANCE:Nationwide, fertility dropped by 17.5 births/month/100 000 WRA/year following Wave 1 and 9.2 births/month/100 000 WRA/year following Wave 2. The declines following Wave 1 were largest among majority-Democrat, more non-White states where people practiced greater social distancing. Greater COVID-19 wave severity was associated with steeper fertility rate decline post-Wave 1 in simple regression, but the association was attenuated when adjusted for other covariates. Adjusting for the economic impact of the pandemic (hypothesized mediator) also attenuated the effect. There was no relation between COVID-19 wave severity and fertility rate change following Wave 2. LIMITATIONS, REASONS FOR CAUTION:Our study harnesses state-level data so individual-level conclusions cannot be inferred. There may be residual confounding in our multivariable regression and we were underpowered to detect some effects. WIDER IMPLICATIONS OF THE FINDINGS:The COVID-19 pandemic initially impacted the national fertility rate but, overall, the fertility rate rebounded to the pre-pandemic level following Wave 2. Consistent with prior literature, COVID-19 wave severity did not appear to predict fertility rate change. Economic, racial, political, and social factors influenced state-specific fertility rates during the pandemic more than the severity of the outbreak alone. Future studies in other countries should also consider whether these factors account for internal heterogeneity when examining the impact of the COVID-19 pandemic and other crises on fertility. STUDY FUNDING/COMPETING INTEREST(S):L.G.K. received funding from the National Institute of Environmental Health Sciences (R00ES030403), M.C. from the National Science Foundation Graduate Research Fellowship Program (20-A0-00-1005789), and M.L. and E.S. from the National Institute of Environmental Health Sciences (R01ES032808). None of the authors have competing interests. TRIAL REGISTRATION NUMBER:N/A.

Communities of color are disproportionately impacted by gun violence. Unlocking potential community-led solutions could be the key to quelling the gun violence epidemic and its impact on these communities. In this qualitative study, we explored community perspectives on local assets that may prevent and mitigate gun violence. We conducted semi-structured, in-depth interviews (n = 45) among individuals not directly involved in gun violence (i.e., shooting victim or perpetrator) despite having a high probability of being involved in gun violence in New Haven, CT. Participants were asked to describe social structures that may deter local gun violence. Here, we report emergent themes to preventing gun violence across multiple levels, including role models (interpersonal), social cohesion and home ownership (neighborhood), and community-based organizations (organizational). Our findings suggest that investments in stable housing, efforts to build social cohesion, access to community-based mental health services, and youth activities are needed to curb the drivers of community gun violence.

BACKGROUND/UNASSIGNED:Research investigating adverse effects from drug use has focused extensively on poisonings and mortality. This study focuses on drug-related adverse effects not necessarily resulting in hospitalization or death among a population known for high prevalence of party drug use-electronic dance music (EDM) nightclub and festival attendees. METHODS/UNASSIGNED: = 1952). Those reporting past-month use of a drug were asked whether they had experienced a harmful or very unpleasant effect after use. We examined 20 drugs and drug classes with a particular focus on alcohol, cannabis, cocaine, and ecstasy. Prevalence and correlates of adverse effects were estimated. RESULTS/UNASSIGNED:Almost half (47.6%) of adverse effects involved alcohol and 19.0% involved cannabis. 27.6% of those using alcohol reported an adverse effect, while 19.5%, 15.0%, and 14.9% of participants reported an effect from use of cocaine, ecstasy, and cannabis, respectively. Use of less prevalent drugs, such as NBOMe, methamphetamine, fentanyls, and synthetic cathinones, tended to be associated with higher prevalence of adverse effects. The most consistent risk factor was younger age, while past-month use of a greater number of drugs was often a protective factor against adverse effects. For most drugs, taking too much was the most common perceived reason for the adverse effect, and visiting a hospital after use was most prevalent among those experiencing an adverse effect from cocaine (11.0%). CONCLUSIONS/UNASSIGNED:Adverse drug effects are common in this population and results can inform prevention and harm reduction in this population and the general population.

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.