Faculty Bibliography

The coronavirus disease 2019 (COVID-19) pandemic disrupted health care, creating challenges for people with diabetes and health care systems. Diabetes was recognized as a risk factor for severe disease early in the pandemic. Subsequently, risk factors specific for people with type 1 diabetes were identified, including age, hemoglobin A1c level, and lack of continuous glucose monitoring . Telemedicine, especially when accompanied by diabetes data, allowed effective remote care delivery. However, pre-existing racial disparities in access to diabetes technology persisted and were associated with worse outcomes. Events of the COVID-19 pandemic underscore the importance of continuing to develop flexible and more equitable health care delivery systems.

STUDY QUESTION/OBJECTIVE:Do children born to mothers with polycystic ovary syndrome (PCOS) have an adverse cardiometabolic profile including arterial stiffness at 9 years of age compared to other children? SUMMARY ANSWER/CONCLUSIONS:Children of mothers with PCOS did not have differing cardiometabolic outcomes than children without exposure. WHAT IS KNOWN ALREADY/BACKGROUND:While women with PCOS themselves have higher risk of cardiometabolic conditions such as obesity and diabetes, the evidence on intergenerational impact is unclear. Given in utero sequalae of PCOS (e.g. hyperandrogenism, insulin resistance), the increased risk could be to both boys and girls. STUDY DESIGN, SIZE, DURATION/METHODS:The Upstate KIDS cohort is a population-based birth cohort established in 2008-2010 to prospectively study the impact of infertility treatment on children's health. After ∼10 years of follow-up, 446 mothers and their 556 children attended clinical visits to measure blood pressure (BP), heart rate, arterial stiffness by pulse wave velocity (PWV), mean arterial pressure, lipids, high-sensitivity C-reactive protein (hsCRP), hemoglobin A1c (HbA1c), and anthropometrics. PARTICIPANTS/MATERIALS, SETTING, METHODS/METHODS:Women self-reported ever diagnoses of PCOS ∼4 months after delivery of their children in 2008-2010. Linear regression models applying generalized estimating equations to account for correlation within twins were used to examine associations with each childhood cardiometabolic outcome. MAIN RESULTS AND THE ROLE OF CHANCE/RESULTS:In this cohort with women oversampled on infertility treatment, ∼14% of women reported a PCOS diagnosis (n = 61). We observed similarities in BP, heart rate, PWV, lipids, hsCRP, HbA1c, and anthropometry (P-values >0.05) among children born to mothers with and without PCOS. Associations did not differ by child sex. LIMITATIONS, REASONS FOR CAUTION/CONCLUSIONS:The sample size of women with PCOS precluded further separation of subgroups (e.g. by hirsutism). The population-based approach relied on self-reported diagnosis of maternal PCOS even though self-report has been found to be valid. Participants were predominantly non-Hispanic White and a high proportion were using fertility treatment due to the original design. Differences in cardiometabolic health may be apparent later in age, such as after puberty. WIDER IMPLICATIONS OF THE FINDINGS/CONCLUSIONS:Our results provide some reassurance that cardiometabolic factors do not differ in children of women with and without self-reported PCOS during pregnancy. STUDY FUNDING/COMPETING INTEREST(S)/BACKGROUND:Supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, United States (contracts #HHSN275201200005C, #HHSN267200700019C, #HHSN275201400013C, #HHSN275201300026I/27500004, #HHSN275201300023I/27500017). The authors have no conflicts of interest. REGISTRATION NUMBER/BACKGROUND:NCT03106493.

BACKGROUND/UNASSIGNED:Systematic and comprehensive data acquisition from the electronic health record (EHR) is critical to the quality of data used to improve patient care. We described EHR tools, workflows, and data elements that contribute to core quality metrics in the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI). METHOD/UNASSIGNED:We conducted interviews with quality improvement (QI) representatives at 13 T1DX-QI centers about their EHR tools, clinic workflows, and data elements. RESULTS/UNASSIGNED:All centers had access to structured data tools, nine had access to patient questionnaires and two had integration with a device platform. There was significant variability in EHR tools, workflows, and data elements, thus the number of available metrics per center ranged from four to 17 at each site. Thirteen centers had information about glycemic outcomes and diabetes technology use. Seven centers had measurements of additional self-management behaviors. Centers captured patient-reported outcomes including social determinants of health (n = 9), depression (n = 11), transition to adult care (n = 7), and diabetes distress (n = 3). Various stakeholders captured data including health care professionals, educators, medical assistants, and QI coordinators. Centers that had a paired staffing model in clinic encounters distributed the burden of data capture across the health care team and was associated with a higher number of available data elements. CONCLUSIONS/UNASSIGNED:The lack of standardization in EHR tools, workflows, and data elements captured resulted in variability in available metrics across centers. Further work is needed to support measurement and subsequent improvement in quality of care for individuals with type 1 diabetes.

BACKGROUND:Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals and are commonly found in everyday items. PFAS have been linked to disrupting glucose homeostasis, however, whether they are associated with gestational diabetes mellitus (GDM) risk remains inconclusive. We examined prospective associations of PFAS concentrations measured twice in pregnancy with GDM risk. METHODS:In the PETALS pregnancy cohort, a nested case-control study which included 41 GDM cases and 87 controls was conducted. PFAS analytes were measured in blood serum collected in both early and mid-pregnancy (mean [SD]: 13.9 [2.2] and 20.2 [2.2] gestational weeks, respectively), with cumulative exposure calculated by the area-under-the-curve (AUC) to integrate both the PFAS concentration and the timing of the exposure. Individual adjusted weighted unconditional logistic regression models examined seven PFAS in association with GDM risk. P-values were corrected using the false-discovery-rate (FDR). Mixture models were analyzed with Bayesian kernel machine regression (BKMR). RESULTS:PFDA, PFNA and PFOA were individually associated with higher GDM risk per interquartile range (IQR) in early pregnancy (OR [95% CI]: 1.23 [1.09, 1.38]), 1.40 [1.24, 1.58]), and 1.15 [1.04, 1.27], respectively), mid-pregnancy (1.28 [1.15, 1.43], 1.16 [1.05, 1.28], and 1.20 [1.09, 1.33], respectively), and with cumulative exposure (1.23 [1.09, 1.38], 1.21 [1.07, 1.37], and 1.19 [1.09, 1.31], respectively). PFOS in mid-pregnancy and with cumulative exposure was associated with increased GDM risk (1.41 [1.17, 1.71] and 1.33 [1.06, 1.58], respectively). PFUnDA in early pregnancy was associated with lower GDM risk (0.79 [0.64, 0.98]), whereas mid-pregnancy levels were associated with higher risk (1.49 [1.18, 1.89]). PFHxS was associated with decreased GDM risk in early and mid-pregnancy (0.48 [0.38, 0.60] and 0.48 [0.37, 0.63], respectively) and with cumulative exposure (0.49 [0.38,0.63]). PFPeA was not associated with GDM. Similar conclusions were observed in BKMR models; however, overall associations in these models were not statistically significant. CONCLUSIONS:Higher risk of GDM was consistently observed in association with PFDA, PFNA, and PFOA exposure in both early and mid-pregnancy. Results should be corroborated in larger population-based cohorts and individuals of reproductive age should potentially avoid known sources of PFAS.

BACKGROUND:There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer (PC). Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for PC. METHODS:Data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium (PanScan; cases n=5090, controls n=8733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n=4,163, controls n=3,792) were analyzed. We used data on 68 genetic variants with four different MR methods (inverse variance weighting [IVW], MR-Egger, simple median, and penalized weighted median) separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and PC risk, using logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for PC risk factors, including obesity and diabetes. RESULTS:No association was found between genetically predicted NAFLD and PC risk in the PanScan or PanC4 samples (e.g., PanScan, IVW OR=1.04, 95% CI: 0.88-1.22, MR-Egger OR=0.89, 95% CI: 0.65-1.21; PanC4, IVW OR=1.07, 95% CI: 0.90-1.27, MR-Egger OR=0.93, 95% CI: 0.67-1.28). None of the four MR methods indicated an association between genetically predicted NAFLD and PC risk in either sample. CONCLUSIONS:Genetic predisposition to NAFLD is not associated with PC risk. IMPACT/CONCLUSIONS:Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and PC might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and PC.

OBJECTIVES:We sought to examine in individuals with SARS-CoV-2 infection whether risk for thrombotic and thromboembolic events (TTE) is modified by presence of a diabetes diagnosis. Furthermore, we analysed whether differential risk for TTEs exists in type 1 diabetes mellitus (T1DM) versus type 2 diabetes mellitus (T2DM). DESIGN:Retrospective case-control study. SETTING:COVID-19 database is a deidentified, nationwide database containing electronic medical record (EMR) data from 87 US-based health systems. PARTICIPANTS:We analysed EMR data for 322 482 patients >17 years old with suspected or confirmed SARS-CoV-2 infection who received care between December 2019 and mid-September 2020. Of these, 2750 had T1DM; 57 811 had T2DM; and 261 921 did not have diabetes. OUTCOME:TTE, defined as presence of a diagnosis code for myocardial infarction, thrombotic stroke, pulmonary embolism, deep vein thrombosis or other TTE. RESULTS:Odds of TTE were substantially higher in patients with T1DM (adjusted OR (AOR) 2.23 (1.93-2.59)) and T2DM (AOR 1.52 (1.46-1.58)) versus no diabetes. Among patients with diabetes, odds of TTE were lower in T2DM versus T1DM (AOR 0.84 (0.72-0.98)). CONCLUSIONS:Risk of TTE during COVID-19 illness is substantially higher in patients with diabetes. Further, risk for TTEs is higher in those with T1DM versus T2DM. Confirmation of increased diabetes-associated clotting risk in future studies may warrant incorporation of diabetes status into SARS-CoV-2 infection treatment algorithms.

Wolfram syndrome is a neurodegenerative disorder caused by pathogenic variants in the genes WFS1 or CISD2. Clinically, the classic phenotype is composed of optic atrophy, diabetes mellitus type 1, diabetes insipidus, and deafness. Wolfram syndrome, however, is phenotypically heterogenous with variable clinical manifestations and age of onset. We describe four cases of genetically confirmed Wolfram syndrome with variable presentations, including acute-on-chronic vision loss, dyschromatopsia, and tonic pupils. All patients had optic atrophy, only three had diabetes, and none exhibited the classic Wolfram phenotype. MRI revealed a varying degree of the classical features associated with the syndrome, including optic nerve, cerebellar, and brainstem atrophy. The cohort's genotype and presentation supported the reported phenotype-genotype correlations for Wolfram, where missense variants lead to milder, later-onset presentation of the Wolfram syndrome spectrum. When early onset optic atrophy and/or diabetes mellitus are present in a patient, a diagnosis of Wolfram syndrome should be considered, as early diagnosis is crucial for the appropriate referrals and management of the associated conditions. Nevertheless, the condition should also be considered in otherwise unexplained, later-onset optic atrophy, given the phenotypic spectrum.

BACKGROUND:Nontargeted analysis (NTA) methods identify novel exposures; however, few chemicals have been quantified and interrogated with pregnancy complications. OBJECTIVES:We characterized levels of nine exogenous and endogenous chemicals in maternal and cord blood identified, selected, and confirmed in prior NTA steps, including linear and branched isomers perfluorooctane sulfonate (PFOS), perfluorohexane sulfonate (PFHxS), monoethylhexyl phthalate, 4-nitrophenol, tetraethylene glycol, tridecanedioic acid, octadecanedioic acid, and deoxycholic acid. We evaluated relationships between maternal and cord levels and between gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy in a diverse pregnancy cohort in San Francisco. METHODS:We collected matched maternal and cord serum samples at delivery from 302 pregnant study participants from the Chemicals in Our Bodies cohort in San Francisco. Chemicals were identified via NTA and quantified using targeted approaches. We calculated distributions and Spearman correlation coefficients testing the relationship of chemicals within and between the maternal and cord blood matrices. We used adjusted logistic regression to calculate the odds of GDM and hypertensive disorders of pregnancy associated with an interquartile range increase in maternal chemical exposures. RESULTS: DISCUSSION:We identified both exogenous and endogenous chemicals seldom quantified in pregnant study participants that were also related to pregnancy complications and demonstrated the utility of NTA to identify chemical exposures of concern. https://doi.org/10.1289/EHP11546.

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.

OBJECTIVES/OBJECTIVE:Antenatal corticosteroids (ACS) administered to mothers at risk for preterm delivery before 34 weeks has been standard care to improve neonatal outcomes. After introducing a new obstetric policy based on updated recommendations advising the administration of ACS to pregnant women at risk for late preterm (LPT) delivery (34-36 6/7 weeks), we set out to determine the short-term clinical impact on those LPT neonates. METHODS:Retrospective chart review of LPT neonates delivered at NYU Langone Medical Center both one year before and after the policy went into place. We excluded subjects born to mothers with pre-gestational diabetes, multiple gestations, and those with congenital/genetic abnormalities. We also excluded subjects whose mothers already received ACS previously in pregnancy. Subjects were divided into pre-policy and post-policy groups. Neonatal and maternal data were compared for both groups. RESULTS:388 subjects; 180 in the pre-policy and 208 in the post-policy group. This policy change resulted in a significant increase in ACS administration to mothers who delivered LPT neonates (67.3 vs. 20.6%, p<0.001). In turn, there was a significant reduction in LPT neonatal intensive care unit (NICU) admissions (44.2 vs. 54.4%, p=0.04) and need for respiratory support (27.9 vs. 42.8%, p<0.01). However, we also found an increased incidence of hypoglycemia (49.5 vs. 28.3%, p<0.001). CONCLUSIONS:This LPT ACS policy appears effective in reducing the need for LPT NICU level care overall. However, clinicians must be attentive to monitor for adverse effects like hypoglycemia, and there remains a need for better understanding of potential long-term impacts.