Metal exposure estimates in established biomarkers, epigenetic biomarkers, and associations with cardiovascular outcomes in the Strong Heart Study

Cardiovascular disease remains the leading causing of death worldwide. American Indians experience an elevated prevelance of cardiovascular disease (CVD) and chronic metal exposures. Determining the impact of metal exposures on CVD can inform prevention and exposure reduction strategies. This dissertation will advance environmental monitoring and biological monitoring of lead, uranium, and selenium exposures using both established biomarkers and novel epigenetic biomarkers to determine the associations of metals with CVD, leveraging the Strong Heart Study (SHS), a prospective cohort of CVD and its risk factors among American Indian adults from tribes and communities in Arizona, Oklahoma, North Dakota, and South Dakota. In Chapter 1, we discuss lead, uranium, and selenium, sources of exposure, and relevance to cardiovascular disease. This includes an overview of metal toxicokinetics and how we can assess these contaminants in both established biomarkers, including blood and urine, as well as in epigenetic biomarkers. In Chapter 2, we estimated urinary uranium concentrations from data on uranium in water among Strong Heart Family Study participants. These estimates were derived from relationships between urinary uranium and water uranium assessed in Strong Heart Family Study (SHFS) participants (n=1,356). Predictions were made using generalized linear models and included demographic and clinical participant characteristics in addition to other metal contaminants measured in water and urine. The root mean square error (RMSE) of the prediction model was 1.01, and predicted urine uranium levels were comparable (median: 0.04 μg/g creatinine, 25th-75th: 0.02-0.08 μg/g creatinine) to urine uranium measured in the SHFS (0.04 μg/g creatinine, 0.02-0.07 μg/g creatinine). These findings emphasize the contribution of uranium in water to urine uranium (reflecting internal dose), and demonstrate the relevance of estimating metal contaminants in urine for the SHS to inform relationships with health effects. In Chapter 3, we evaluated whether urinary uranium concentrations were associated with measures of cardiac geometry and functioning among 1,332 American Indian youth and young adults from the SHFS. Transthoracic echocardiography and blood pressure was assessed at baseline (2001-2003) and a follow-up visit (2006-2009). We estimated mean differences in measures of cardiac geometry and functioning at baseline and follow-up using linear mixed effect models with random intercept and slope over time. In fully adjusted models, a log-doubling of urinary uranium was positively associated with left ventricular (LV) mass index (mean difference: 0.49 g/m2, 95% CI: 0.07-0.92 g/m2), left atrial systolic diameter (0.02 cm, 0.01-0.03 cm), and stroke volume (0.66 mL, 0.25-1.08 mL) at baseline. At follow-up, uranium was associated with increases in left atrial diameter (0.02 cm, 0.01-0.03 cm), pulse pressure (0.28 mmHg, 0.05-0.52 mmHg), and incident LV hypertrophy (OR: 1.25, 95% CI: 1.06, 1.48). These findings support the need to determine the potential long-term clinical and subclinical cardiovascular effects of chronic uranium exposure in the general population, and the need for future strategies to reduce exposure. In Chapter 4, we evaluated if blood lead was associated with CVD incidence and mortality in 1,818 adult American Indian participants. This study estimated the risk of incident CVD and CVD deaths in models adjusted for demographic, lifestyle, and cardiovascular risk factors. Blood lead levels in American Indian adults were associated with increased risk of CVD and coronary heart disease (CHD) incidence and mortality. The hazard ratio (HR) (95% CI) of mortality per change across the 80th-20th quantiles in blood lead was 1.15 (1.02-1.30) for CVD overall and 1.22 (1.08-1.37) for CHD. The corresponding HR was 1.11 (1.01-1.22) for incident CVD and 1.12 (1.00-1.25) for incident CHD. These findings contribute to the evidence of lead as a CVD risk factor at low levels and highlight the importance of further reducing lead exposure in communities across the United States, including American Indian communities. In Chapter 5, we leveraged novel epigenetic biomarkers of lead exposure to investigate their association with cardiovascular disease (CVD) incidence and mortality among 2,231 participants of the Strong Heart Study. Blood DNA methylation was measured using the Illumina MethylationEPIC BeadChip at baseline (1989-1991) and epigenetic biomarkers of lead levels in blood, patella, and tibia were estimated using previously developed biomarkers of DNA methylation at specific CpG sites. In adjusted models, the hazard ratio (HR) (95% CI) of CVD mortality per doubling increase in lead epigenetic biomarkers were 1.42 (1.07-1.87) for tibia lead, 1.22 (0.93-1.60) for patella lead, and 1.57 (1.16-2.11) for blood lead. The corresponding HRs for incident CVD were 0.99 (0.83-1.19), 1.07 (0.89-1.29), and 1.06 (0.87-1.30). The association between the tibia lead epigenetic biomarker and CVD mortality was modified by sex (interaction p-value: 0.014), with men at increased risk (HR: 1.42, 95% CI:1.17-1.72) compared to women (HR: 1.04, 95% CI:0.89-1.22). These findings support that epigenetic biomarkers of lead exposure may capture some of the disease risk associated with lead exposure. In Chapter 6, we investigated the association between urinary selenium levels and DNA methylation (DNAm) among 1,357 participants free of CVD and diabetes in the SHS. Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry. DNAm in whole blood was measured cross-sectionally using the Illumina Methylation EPIC BeadChip (850K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated CpG sites associated with urinary selenium levels. Across 788,368 CpG sites, five differentially methylated positions (DMP) (cg00163554, cg18212762, cg25194720, cg11270656, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top associated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Future analyses should explore these relationships prospectively and investigate the potential role of differentially methylated sites with disease endpoints. In Chapter 7, we evaluated if declines in blood lead were associated with changes in systolic and diastolic blood pressure in adult American Indian participants from the SHFS (n=285). Using generalized estimating equations, a significant non-linear association between declines in blood lead and declines in systolic blood pressure was detected, with significant linear associations where blood lead decline was 1 µg/L or higher. These findings suggest the need to further study the cardiovascular impacts of reducing lead exposures and the importance of lead exposure prevention. In conclusion, we find that established biomarkers of metal exposure reflecting internal dose such as blood and urine, as well as epigenetic biomarkers of metals exposures, were associated with subclinical CVD and CVD incidence and mortality. Findings concerning blood lead emphasize that low levels of lead remain relevant for CVD, and declines in blood lead even when small (1.0-10.0 µg/L), were associated with reductions in systolic blood pressure. Novelly, we present that urinary uranium levels were adversely associated with measures of cardiac geometry and left ventricular functioning among American Indian adults, and that future attention must be paid to investigating associations with subclinical disease. We also find utility in using epigenetic biomarkers to capture CVD risk, as tibia and blood epigenetic biomarkers of lead, were associated with increased risk of CVD mortality, and urinary selenium was associated with distinct changes in DNAm. Although further work must further validate these epigenetic biomarkers in different populations, future work must continue to investigate these epigenetic biomarkers given their potential to capture CVD risk

Analyzing disparities in COVID-19 testing trends according to risk for COVID-19 severity across New York City

Background!#!Given the interplay between race and comorbidities on COVID-19 morbidity and mortality, it is vital that testing be performed in areas of greatest need, where more severe cases are expected. The goal of this analysis is to evaluate COVID-19 testing data in NYC relative to risk factors for COVID-19 disease severity and demographic characteristics of NYC neighborhoods.!##!Methods!#!COVID-19 testing and the racial/ethnic composition of NYC Zip Code Tabulation Areas (ZCTA) were obtained from the NYC Coronavirus data repository and the American Community Survey, respectively. The prevalence of neighborhood-level risk factors for COVID-19 severity according to the Centers for Disease Control and Prevention criteria for risk of severe illness and complications from COVID-19 were used to create a ZCTA-level risk index. Poisson regressions were performed to study the ratio of total tests relative to the total ZCTA population and the proportion of positive tests relative to the total tests performed over time.!##!Results!#!From March 2nd-April 6th, the total tests/population (%) was positively associated with the proportion of white residents (IRR!##!Conclusions!#!Testing in NYC has suffered from the lack of availability in high-risk populations, and was initially limited as a diagnostic tool for those with severe symptoms, which were mostly concentrated in areas where vulnerable residents live. Subsequent time periods of testing were not targeted in areas according to COVID-19 disease risk, as these areas still experience more positive tests

Longitudinal Impact of Hurricane Sandy Exposure on Mental Health Symptoms

Hurricane Sandy hit the eastern coast of the United States in October 2012, causing billions of dollars in damage and acute physical and mental health problems. The long-term mental health consequences of the storm and their predictors have not been studied. New York City and Long Island residents completed questionnaires regarding their initial Hurricane Sandy exposure and mental health symptoms at baseline and 1 year later (N = 130). There were statistically significant decreases in anxiety scores (mean difference = −0.33, p < 0.01) and post-traumatic stress disorder (PTSD) scores (mean difference = −1.98, p = 0.001) between baseline and follow-up. Experiencing a combination of personal and property damage was positively associated with long-term PTSD symptoms (ORadj 1.2, 95% CI [1.1–1.4]) but not with anxiety or depression. Having anxiety, depression, or PTSD at baseline was a significant predictor of persistent anxiety (ORadj 2.8 95% CI [1.1–6.8], depression (ORadj 7.4 95% CI [2.3–24.1) and PTSD (ORadj 4.1 95% CI [1.1–14.6]) at follow-up. Exposure to Hurricane Sandy has an impact on PTSD symptoms that persists over time. Given the likelihood of more frequent and intense hurricanes due to climate change, future hurricane recovery efforts must consider the long-term effects of hurricane exposure on mental health, especially on PTSD, when providing appropriate assistance and treatment

Mild anemia as a single independent predictor of mortality in patients with COVID‐19

Abstract The coronavirus disease 2019 (COVID‐19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) has led to an unprecedented international health crisis. COVID‐19 clinical presentations cover a wide range from asymptomatic to severe illness and death. Given the limited therapeutic resources and unexpected clinical features of the disease, readily accessible predictive biomarkers are urgently needed to improve patient care and management. We asked the degree to which anemia may influence the outcome of patients with COVID‐19. To this end, we identified 3777 patients who were positively diagnosed with COVID‐19 between March 1 and April 1 2020 in New York City. We evaluated 2,562 patients with available red blood cell, hemoglobin, and related laboratory values. Multivariable cox proportional hazards regression showed that anemia was a significant independent predictor of mortality (hazard ratio (HR): 1.26, 95% Confidence Interval [CI]: 1.06‐1.51), independent of age, sex, and comorbidities. There was a direct correlation between the degree of anemia and the risk of mortality when hemoglobin was treated as a continuous variable (HRadj 1.05; [CI]: 1.01‐1.09). The hemoglobin level that was maximally predictive of mortality, was 11.5 g/dL in males and 11.8 g/dL in females. These findings identify a routinely measured biomarker that is predictive of disease outcomes and will aid in refining clinical care algorithms and optimize resource allocation. Mechanisms of impacts of anemia on COVID‐19 outcome are likely to be multiple in nature and require further investigation

Preliminary Assessment of Hurricane Harvey Exposures and Mental Health Impact

Hurricane Harvey made landfall in Houston, Texas on 25 August 2017, the psychological and physical effects of which are still unknown. We assessed hurricane exposure and the immediate mental health needs of the population to define public health priorities for a larger epidemiological study. Convenience sampling was used to recruit participants (n = 41) from the greater Houston area aged ≥18 years. Participants completed a questionnaire about demographics, hurricane exposures, and physical/mental health. Post-Traumatic Stress Disorder (PTSD) was measured with the Post-Traumatic Stress Disorder Checklist-S (PCL-S; a score ≥30 indicated probable PTSD symptoms). The Patient Health Questionnaire-4 (PHQ-4) was used to assess symptoms of depression and generalized anxiety disorder. The average PTSD score was 32.9 (SD = 17.1); a total of 46% of participants met the threshold for probable PTSD. Increased overall hurricane exposure (adjusted odds ratio (ORadj) 1.42; 95% confidence interval (CI): 1.06–2.05) and property-related exposure (ORadj 1.53; 95% CI: 1.07–2.18) were both statistically significantly associated with increased odds of probable PTSD symptoms. A perception of chemical/toxin exposure due to Hurricane Harvey was reported by 44% of participants. A higher number of personal or property exposures were associated with greater mental health symptoms three weeks post-hurricane. This work has implications for the ongoing response to Hurricane Harvey and for assessing the immediate needs of the population

Associations between flood exposure measurements [self-reported / FEMA-reported, dichotomous (flooding yes/no) / continuous (feet)] and mental health (anxiety, depression, PTSD).

<p>The model was adjusted for age, gender, race, education, existing mental health status, elapsed time since Hurricane Sandy, and living in an apartment.</p

Self-Reported and FEMA Flood Exposure Assessment after Hurricane Sandy: Association with Mental Health Outcomes

<div><p>Hurricane Sandy caused extensive physical and economic damage; the long-term mental health consequences are unknown. Flooding is a central component of hurricane exposure, influencing mental health through multiple pathways that unfold over months after flooding recedes. Here we assess the concordance in self-reported and Federal Emergency Management (FEMA) flood exposure after Hurricane Sandy and determine the associations between flooding and anxiety, depression, and post-traumatic stress disorder (PTSD). Self-reported flood data and mental health symptoms were obtained through validated questionnaires from New York City and Long Island residents (N = 1231) following Sandy. Self-reported flood data was compared to FEMA data obtained from the FEMA Modeling Task Force Hurricane Sandy Impact Analysis. Multivariable logistic regressions were performed to determine the relationship between flooding exposure and mental health outcomes. There were significant discrepancies between self-reported and FEMA flood exposure data. Self-reported dichotomous flooding was positively associated with anxiety (OR_adj: 1.5 [95% CI: 1.1–1.9]), depression (OR_adj: 1.7 [1.3–2.2]), and PTSD (OR_adj: 2.5 [1.8–3.4]), while self-reported continuous flooding was associated with depression (OR_adj: 1.1 [1.01–1.12]) and PTSD (OR_adj: 1.2 [1.1–1.2]). Models with FEMA dichotomous flooding (OR_adj: 2.1 [1.5–2.8]) or FEMA continuous flooding (OR_adj: 1.1 [1.1–1.2]) were only significantly associated with PTSD. Associations between mental health and flooding vary according to type of flood exposure measure utilized. Future hurricane preparedness and recovery efforts must integrate micro and macro-level flood exposures in order to accurately determine flood exposure risk during storms and realize the long-term importance of flooding on these three mental health symptoms.</p></div