Faculty Bibliography

BACKGROUND/UNASSIGNED:Maternal sustained smoking during pregnancy is associated with thousands of differentially methylated CpGs in newborns, but impacts of other prenatal tobacco smoking exposures remain unclear. OBJECTIVE/UNASSIGNED:To identify differential DNA methylation in newborns from maternal sustained smoking and less studied prenatal smoking exposures (i.e., maternal exposure to secondhand smoke [SHS] exposure during pregnancy, maternal quitting before pregnancy, paternal smoking around conception, paternal quitting before pregnancy). METHODS/UNASSIGNED:We conducted a large meta-analysis of prenatal tobacco smoking exposures and epigenome-wide newborn blood DNA methylation through the Pregnancy And Childhood Epigenetics Consortium (PACE). Across 19 cohorts, 11,175 parent-newborn pairs contributed information on at least one prenatal smoking exposure, mostly from questionnaires. Maternal blood or urine cotinine measurements, available in a few studies, provided objective data on maternal SHS and smoking during pregnancy. Primary analyses used Illumina450K methylation data; secondary analyses in 5 cohorts examined CpGs unique to the EPIC array. RESULTS/UNASSIGNED:) was associated with paternal former smoking. Forty-one novel genes were identified using maternal cotinine measurements compared to questionnaire. In EPIC unique analyses (n=3,415), differential methylation was observed with maternal sustained smoking (211 CpGs), maternal SHS (5 CpGs), and paternal former smoking (4 CpGs). Smoking-associated CpGs in blood were strongly enriched for functional elements across multiple tissues. CONCLUSIONS/UNASSIGNED:Maternal sustained smoking has the largest impact on newborn DNA methylation, suggesting a strong influence of the intrauterine environment. We observed minimal impacts for less studied exposures including SHS, maternal former smoking and paternal smoking. https://doi.org/10.1289/EHP16303.

Policy Points We can leverage data science and artificial intelligence to inform state and local resource allocation for overdose prevention. Data science and artificial intelligence can help us answer four questions: (1) What is the impact of laws on access to interventions and overdose risk? (2) Where should interventions be targeted? (3) Which types of demographic subgroups benefit the most and the least from interventions? and (4) Which types of interventions should they invest in for each setting and population? Advances in data science and artificial intelligence can accelerate the pace at which we can answer these critical questions and help inform an effective overdose prevention response.

Response to immune checkpoint inhibitors (ICIs) in metastatic melanoma (MM) varies among patients, and current baseline biomarkers predicting treatment outcomes are limited. As mitochondrial (MT) metabolism has emerged as an important regulator of host immune function, we explored the association of host MT genetics (MT haplogroups) with ICI efficacy in 1,225 ICI-treated patients with MM from the clinical trial CheckMate-067 and the International Germline Immuno-Oncology Melanoma Consortium. We discovered and validated significant associations of MT haplogroup T (HG-T) with resistance to anti-programmed cell death protein-1-based ICI (both single-agent and combination) and have shown that HG-T is independent from established tumor predictors. We also found that patients belonging to HG-T exhibit a unique nivolumab-resistant baseline peripheral CD8⁺ T cell repertoire compared to other MT haplogroups, providing, to our knowledge, the first link between MT inheritance, host immunity and ICI resistance. The study proposes a host blood-based biomarker with stand-alone clinical value predicting ICI efficacy and points to an ICI-resistance mechanism associated with MT metabolism, with clinical relevance in immuno-oncology.

BACKGROUND:Our understanding of traditional atherosclerotic risk factors is based predominantly on one-time measurements and associations with adverse cardiovascular outcomes. OBJECTIVES/OBJECTIVE:The aim of this study was to evaluate the contribution of mid- to late-life cumulative risk factor exposure to healthy arterial aging, represented by a persistent coronary artery calcium (CAC) score of zero. METHODS:Among 2,044 community-dwelling, participants free of coronary heart disease from the ARIC (Atherosclerosis Risk in Communities) study, the associations of ∼30-year time-weighted average mid- to late-life (starting at a median age of 49 years in 1987-1989) traditional atherosclerotic risk factors (cholesterol, systolic blood pressure, fasting glucose, and smoking) with late-life (median age 80 years in 2018-2019) CAC 0 were evaluated. RESULTS:A total of 204 participants (10.0%) had CAC 0, and they tended to have more favorable mid- to late-life average risk factor profiles than those with CAC: lower total cholesterol, especially <160 mg/dL; lower systolic blood pressure, especially <125 mm Hg; and higher high-density lipoprotein cholesterol, especially >45 mg/dL. The association was less evident for fasting glucose, with no increased probability of CAC 0 at <95 mg/dL. Never smoking was associated with a 5.7 (95% CI: 2.3-16.7) times greater odds of CAC 0 vs smoking throughout mid- to late-life. Within sex-race groups, average modifiable risk factors predicted substantial differences in CAC 0 probability (eg, for a Black woman, 53% vs 0.4% for a low vs high risk factor profile, respectively). CONCLUSIONS:Favorable average risk factor profiles at mid- to late-life were associated with a greater probability of CAC 0 at older age. These results highlight the importance of maintaining a healthy risk factor profile from mid- to late-life, with implications for public health promotion and policy.

BACKGROUND:A majority of the 8.9 million Americans with opioid misuse have mild or no symptoms of opioid use disorder (OUD), but they may be at elevated risk of developing more severe OUD, overdose, or other health consequences of opioid use. The "Subthreshold Opioid Use Disorder Prevention"(STOP) Trial is evaluating a collaborative care intervention for risky opioid use in primary care. Here, we describe baseline characteristics of participants to understand their needs and assess the generalizability of the sample. METHODS:Recruitment at five primary care sites spanned March 2021-May 2023. Adult patients who screened positive for subthreshold OUD (current illicit or non-medical opioid use without meeting DSM-5 criteria for moderate-severe OUD) were eligible. Baseline assessments measured self-reported demographic characteristics, other substance use, pain, and physical and mental health symptoms. Descriptive statistics summarize characteristics of the enrolled sample across sites. RESULTS:Among the 202 participants, the majority identified as female (63.4%), white (70.8%), and non-Hispanic (96.5%), with mean age 55.7 (SD: 12.7) years. Nearly half (49.0%) had problem or high-risk use of prescription opioids, and most received a prescription for opioid medication in the past six months (74.8%). Many participants reported current problem use or high-risk use of alcohol (47.0%) or cannabis (31.2%). Approximately one-third endorsed mental health symptoms, including moderate-severe anxiety (35.6%), depression (31.2%), or sleep disturbance (29.7%), and 20.3% reported a past suicide attempt. In the prior six months, 14.7% had experienced a nonfatal overdose. Moderate-severe pain was reported by 63.4%, and 60.4% rated their general health as fair or poor. CONCLUSIONS:Patients with subthreshold OUD had high rates of polysubstance use and comorbidities that may present challenges to reducing risky opioid use. The STOP trial presents an opportunity to detect and address subthreshold OUD in a cohort with considerable medical and social needs, within primary care settings. CLINICAL TRIALS REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04218201.

IMPORTANCE/UNASSIGNED:Midlife vascular risk factors are associated with an elevated risk of dementia. However, the total contribution of vascular risk factors in midlife and late life with incident dementia is uncertain. OBJECTIVE/UNASSIGNED:To quantify the proportion of incident dementia attributable to modifiable vascular risk factors measured in midlife and late life and to examine differences by apolipoprotein ε4 genotype, self-reported race, and sex. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This was a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study using 33 years of follow-up (1987-2020). The setting included ARIC field centers (Jackson, Mississippi; Forsyth County, North Carolina; Minneapolis suburbs, Minnesota; Washington County, Maryland). Study baseline in Black and White participants with complete exposure and covariate data was set by age at risk factor measurement (45-54 years, 55-64 years, and 65-74 years). Data were analyzed from August 2023 to December 2024. EXPOSURES/UNASSIGNED:Hypertension (systolic blood pressure [BP] ≥130 mm Hg, diastolic BP ≥80 mm Hg, or use of medication for BP), diabetes (fasting glucose ≥126 mg/dL, nonfasting glucose ≥200 mg/dL, self-reported physician's diagnosis, or use of any diabetes medication), and current smoking (self-reported). MAIN OUTCOMES AND MEASURES/UNASSIGNED:Incident dementia. Population attributable fractions were estimated by age 80 years, and separately after 80 years, from having at least 1 vascular risk factor by age at risk factor measurement. RESULTS/UNASSIGNED:A total of 7731 participants were included in analysis of risk factors measured at age 45 to years (4494 female [58%]; 2207 Black [29%]; 5524 White [71%]), 12 274 contributed to analysis of risk factors measured at age 55 to 64 years (6698 female [55%]; 2886 Black [24%]; 9388 White [76%]), and 6787 contributed to analysis of risk factors measured at age 65 to 74 years (3764 female [56%], 1375 Black [20%]; 5412 White [80%]). There were 801, 995, and 422 dementia cases by 80 years, respectively. The fraction of dementia by 80 years attributable to at least 1 vascular factor at age 45 to 54 years was 21.8% (95% CI, 14.3%-29.3%), at 55 to 64 years was 26.4% (95% CI, 19.1%-33.6%), and at 65 to 74 years was 44.0% (95% CI, 30.9%-57.2%). Attributable fractions for these factors were higher in apolipoprotein ε4 noncarriers at age 55 years and older (range, 33.3%-61.4%), Black individuals at age 45 years and older (range, 25.5%-52.9%), and female individuals at age 55 years and older (range, 29.2%-51.3%). Only 2% to 8% of dementia cases after 80 years were attributable to these factors. CONCLUSIONS AND RELEVANCE/UNASSIGNED:Results of this cohort study suggest that between 22% and 44% of incident dementia cases by 80 years in the ARIC study were attributed to midlife and late-life vascular risk factors. Assuming causal relationships, maintaining optimal vascular health across the life course could mitigate a sizeable proportion of dementia risk by 80 years.

Alzheimer's disease rates are expected to triple by 2050. Early detection and specific mitigation efforts are warranted to blunt the alarming increase. Physical function index (PFI) declines with age; additionally, higher PFI is associated with better cognitive functioning in middle-to-older age individuals. However, most studies utilize one domain of PFI to examine associations with cognition. Therefore, using clustering methods, the purpose of this investigation was to determine if high-risk individuals with higher PFI have better cognitive outcomes compared to individuals with lower PFI. Participants (n = 215; 73.1% female; 45-75 years) completed a body mass scan, venous blood draw, 7 PFI tasks, and 7 cognitive tests. A k-means cluster analysis was utilized to identify PFI cluster for participants, one-way ANCOVAs were used to assess differences in cognition among clusters. Cluster 1 (C1; n = 29) was characterized as the highest strength/power, faster dual-task walking time, and higher aerobic capacity, Cluster 3 (C3; n = 113) had the lowest values between PFI groups, Cluster 2 (C3; n = 74) was in-between C1 and C3. Individuals in C1 had significantly higher global cognitive, visuospatial scores, digital executive functioning and associative learning compared to individuals in C3 (p < 0.05). Individuals in C1 and C2 had significantly higher values on orientation task and figure recall than individuals in C3 (p < 0.05). The results from this current study demonstrate that individuals with higher combined PFI output have higher global cognitive scores than individuals with lower combined PFI output. Examining PFI variables together may be a valuable tool when assessing cognition among cognitively at-risk individuals.

Algorithmic bias occurs when predictive model performance varies meaningfully across sociodemographic classes, exacerbating systemic healthcare disparities. NYC Health + Hospitals, an urban safety net system, assessed bias in two binary classification models in our electronic medical record: one predicting acute visits for asthma and one predicting unplanned readmissions. We evaluated differences in subgroup performance across race/ethnicity, sex, language, and insurance using equal opportunity difference (EOD), a metric comparing false negative rates. The most biased classes (race/ethnicity for asthma, insurance for readmission) were targeted for mitigation using threshold adjustment, which adjusts subgroup thresholds to minimize EOD, and reject option classification, which re-classifies scores near the threshold by subgroup. Successful mitigation was defined as 1) absolute subgroup EODs <5 percentage points, 2) accuracy reduction <10%, and 3) alert rate change <20%. Threshold adjustment met these criteria; reject option classification did not. We introduce a Supplementary Playbook outlining our approach for low-resource bias mitigation.

AIMS/OBJECTIVE:To characterize changes in continuous glucose monitoring (CGM)-derived time in tight range (TIR) measures in individuals with prediabetes or non-insulin-treated type 2 diabetes undergoing dietary weight loss intervention and to quantify the association between weight loss and TIR improvement. METHODS:) were analysed. The association between weight change and TIR change adjusted for demographic and clinical covariates was computed using linear regression. RESULTS:. There were no associations between weight loss and change in any overnight TIR measure. CONCLUSION/CONCLUSIONS:in individuals with prediabetes and non-insulin-treated type 2 diabetes undergoing dietary intervention. The daytime time in tight range measures can complement traditional markers like HbA1c, offering a more comprehensive view of glycaemic variations during dietary weight loss programmes for individuals with prediabetes and type 2 diabetes not on insulin.

BACKGROUND:Fetal growth is shaped by a complex interplay of parental traits, environmental exposures, nutritional intake, and genetic predispositions. In epidemiological research, birth weight is widely used as a proxy of impaired or favorable fetal growth; but it fails to provide a comprehensive measure, particularly if used alone. METHODS:In a cohort of 538 mother-fetal pairs from the New York University Children's Health and Environment Study (NYU CHES), we utilized multiple linear regression and structural equation modeling (SEM) to assess the influence of various determinants-maternal characteristics, chemical exposures, and dietary factors-on fetal growth. To comprehensively evaluate fetal growth, we employed the concept of latent variable Favorable Fetal Growth Conditions (FFGC), together with three observed outcomes: birth weight, birth length, and gestational age. RESULTS:Maternal characteristics such as height, BMI, race/ethnicity, and maternal alcohol intake were significantly associated with birth weight, birth length, and gestational age in both the linear regression and with FFGC in the SEM. However, SEM additionally revealed significant relationships that were not detected by linear regression. Specifically, di(2-ethylhexyl) phthalate (DEHP) latent factor showed a negative association with the FFGC (β=-0.16, 95% confidence interval (CI)=-0.27, -0.04). The diet latent variable positively impacted FFGC (β=0.15, 95% CI=0.04, 0.25), whereas total calorie intake exhibited a negative effect (β=-0.13, 95% CI=-0.22, -0.05). CONCLUSION/CONCLUSIONS:The SEM provided a thorough understanding of the multifaceted pathways through which multiple factors of chemical mixtures, diet intakes, and maternal characteristics affected fetal development, uncovering nuanced associations that were not apparent in direct effects models. Our findings highlight the intricate interplay of maternal characteristics, chemical exposures, and dietary factors in shaping fetal growth.