Faculty Bibliography

BACKGROUND:Inorganic arsenic (As) is a carcinogen and >200 million people worldwide are exposed to As through drinking water. Long-term As exposure increases the risk of chronic diseases including cancer and cardiovascular disease. While prior work has identified several genomic regions where DNA methylation (DNAm) is associated with As exposure, our knowledge remains limited. METHODS:We first evaluated the association of As exposure (measured in urine and drinking water) with DNAm (measured genome-wide in blood cells at >720 000 cytosine-phosphate-guanine (CpG) sites) among 1186 Bangladeshi adults from the Health Effects of Arsenic Longitudinal Study-a population with a wide range of As exposure levels. We then utilized elastic net regression to build a DNAm-based biomarker of As exposure. RESULTS:We identified 1177 CpGs associated with urinary As (false discovery rate < 0.05) and further demonstrated that these associations are likely causal by using genetic determinants of As metabolism as instrumental variables. Arsenic-associated CpGs showed strong enrichment for genomic context and CpG sets related to disease states previously linked to As exposure. We developed a 255-CpG DNAm-based biomarker of As exposure that was highly predictive of urinary As levels (r2 = 0.46) and arsenical skin-lesion status (area under the receiver-operating characteristic curve = 0.69)-a common sign of As toxicity. This biomarker was also highly associated with measured urinary As levels in an independent Bangladeshi cohort (P = 1.3 × 10-19) and further validated in the Strong Heart Study (P = 6.7 × 10-6), in which the DNAm-predicted As was also associated with overall mortality (P = 4.6 × 10-4). CONCLUSION:We demonstrate the utility of a DNAm-based biomarker of As exposure that can predict the risk of toxicity and present guidelines for developing epigenetic biomarkers to track environmental chemical exposures.

BACKGROUND AND OBJECTIVE/UNASSIGNED:With rising incidence of pediatric retina disease, this study aimed to identify geographic and socioeconomic factors that predict residential access to pediatric retinal specialists. PATIENTS AND METHODS/UNASSIGNED:This cross-sectional, retrospective study identified pediatric retina specialists in the United States and de-identified census tract-level data from public datasets. An origin-destination cost matrix was used to calculate travel time to the closest pediatric vitreoretinal specialist. RESULTS/UNASSIGNED:< .001). CONCLUSIONS/UNASSIGNED:Counties with higher incidences of very low birth weight infants experience reduced travel durations to pediatric retina specialists. However, residents in rural, low-income, low-education census tracts, particularly in Southern regions, face greater travel burdens.

Water diffusion gives rise to micron-scale sensitivity of diffusion MRI (dMRI) to cellular-level tissue structure. Precision medicine and quantitative imaging depend on uncovering the information content of dMRI and establishing its parsimonious hardware-independent fingerprint. Based on the rotational SO(3) symmetry, we study the geometry of the dMRI signal and the topology of its acquisition, identify irreducible components and a full set of invariants for the cumulant tensors, and relate them to tissue properties. Including all kurtosis invariants improves multiple sclerosis classification in a cohort of 1189 subjects. We design the shortest acquisitions based on icosahedral vertices to determine the most used invariants in only 1-2 minutes for whole brain. Representing dMRI via scalar invariant maps with definite symmetries will underpin machine learning classifiers of pathology, development, and aging, while fast protocols will enable translation of advanced dMRI into clinic.

OBJECTIVE:Capturing a habitual event is often required to determine the etiology of events during video-EEG (vEEG) monitoring. vEEG studies that fail to capture a habitual event are typically considered non-diagnostic. In this study, we evaluated the clinical impact of non-diagnostic vEEG studies. METHODS:We identified non-diagnostic vEEG studies from a cohort of epilepsy monitoring unit (EMU) admissions. Patients were followed longitudinally in the outpatient clinic.Clinical impact was assessed by evaluating changes in diagnosis and antiseizure medication (ASM) management at EMU discharge and at the last clinic follow-up. RESULTS:Patients were categorized according to referral indication: (I) spell clarification in individuals with paroxysmal events (n = 10); (II) event differentiation in patients with epilepsy (n = 16); (III) reassessment of a prior epilepsy diagnosis (n = 20); and (IV) classification of seizure or epilepsy type (n = 18). Following EMU admission, one patient in Group I was diagnosed with seizures, while the prior epilepsy diagnosis was withdrawn in eight patients in Group III. At EMU discharge, ASM reduction was most frequent in Group III (11/20), whereas ASM escalation was most common in Group II (7/16). By the last clinic follow-up, two additional patients had been diagnosed with seizures. Further ASM escalation occurred in 14 patients: two in Group I, three in Group II, three in Group III, and six in Group IV. SIGNIFICANCE/CONCLUSIONS:Non-diagnostic vEEG studies can still provide meaningful diagnostic insight. Subsequent management strategies varied substantially depending on the indications for EMU admission and the clinical context.