Faculty Bibliography

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m² in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

BACKGROUND:In utero exposure to bisphenols, widely used in consumer products, may alter lung development and increase the risk of respiratory morbidity in the offspring. However, evidence is scarce and mostly focused on bisphenol A (BPA) only. OBJECTIVE:To examine the associations of in utero exposure to BPA, bisphenol F (BPF), and bisphenol S (BPS) with asthma, wheeze, and lung function in school-age children, and whether these associations differ by sex. METHODS:We included 3,007 mother-child pairs from eight European birth cohorts. Bisphenol concentrations were determined in maternal urine samples collected during pregnancy (1999-2010). Between 7 and 11 years of age, current asthma and wheeze were assessed from questionnaires and lung function by spirometry. Wheezing patterns were constructed from questionnaires from early to mid-childhood. We performed adjusted random-effects meta-analysis on individual participant data. RESULTS:Exposure to BPA was prevalent with 90% of maternal samples containing concentrations above detection limits. BPF and BPS were found in 27% and 49% of samples. In utero exposure to BPA was associated with higher odds of current asthma (OR = 1.13, 95% CI = 1.01, 1.27) and wheeze (OR = 1.14, 95% CI = 1.01, 1.30) (p-interaction sex = 0.01) among girls, but not with wheezing patterns nor lung function neither in overall nor among boys. We observed inconsistent associations of BPF and BPS with the respiratory outcomes assessed in overall and sex-stratified analyses. CONCLUSION:This study suggests that in utero BPA exposure may be associated with higher odds of asthma and wheeze among school-age girls.

Survival modeling with time-varying coefficients has proven useful in analyzing time-to-event data with one or more distinct failure types. When studying the cause-specific etiology of breast and prostate cancers using the large-scale data from the Surveillance, Epidemiology, and End Results (SEER) Program, we encountered two major challenges that existing methods for estimating time-varying coefficients cannot tackle. First, these methods, dependent on expanding the original data in a repeated measurement format, result in formidable time and memory consumption as the sample size escalates to over one million. In this case, even a well-configured workstation cannot accommodate their implementations. Second, when the large-scale data under analysis include binary predictors with near-zero variance (e.g., only 0.6% of patients in our SEER prostate cancer data had tumors regional to the lymph nodes), existing methods suffer from numerical instability due to ill-conditioned second-order information. The estimation accuracy deteriorates further with multiple competing risks. To address these issues, we propose a proximal Newton algorithm with a shared-memory parallelization scheme and tests of significance and nonproportionality for the time-varying effects. A simulation study shows that our scalable approach reduces the time and memory costs by orders of magnitude and enjoys improved estimation accuracy compared with alternative approaches. Applications to the SEER cancer data demonstrate the real-world performance of the proximal Newton algorithm.

OBJECTIVE:To determine if there is an association between patient race and physician time spent with the patient during outpatient urology consultations. METHODS:We identified all adult urology new outpatient visits in the National Ambulatory Medical Care Survey dataset for 2012-2016. Patient race was dichotomized as White or non-White. Our primary outcome was time spent during the visit between the patient and urologist. Using population-level weighting, we compared differences in mean time spent during visits with White and non-White patients. Mixed-effects linear regression was used to adjust for confounding factors and to account for clustering among individual physicians. Secondary outcomes included number of services provided and if ancillary providers were seen. RESULTS:Over the 5 year period, 1668 raw visits met criteria and were used to estimate 21million new outpatient urology visits nationwide. 80% of all visits were with White patients. Mean physician time spent among visits with white patients was 23.9 minutes and 24.4 minutes for non-White patients. There was no difference in number of services provided but visits with non-white patients were less likely to include an ancillary provider. After adjustment, there was no significant difference in mean time spent with the urologist among visits with White and non-White patients (difference 0.9 minutes, 95% CI: -0.6-2.4). There were also no differences in adjusted mean time spent among return visits or new visits for hematuria, urologic cancers, or BPH. CONCLUSION/CONCLUSIONS:We found no statistically significant difference in time spent with a urologist during outpatient office consultations between White and non-White patients.

BACKGROUND:Studies report higher diagnostic accuracy using the collective intelligence (CI) of multiple clinicians compared with individual clinicians. However, the diagnostic process is iterative, and unexplored is the value of CI in improving clinical recommendations leading to a final diagnosis. METHODS:To compare the appropriateness of diagnostic recommendations advised by individual physicians versus the CI of physicians, we entered actual consultation requests sent by primary care physicians to specialists onto a web-based CI platform capable of collecting diagnostic recommendations (next steps for care) from multiple physicians. We solicited responses to 35 cases (12 endocrinology, 13 gynecology, 10 neurology) from ≥3 physicians of any specialty through the CI platform, which aggregated responses into a CI output. The primary outcome was the appropriateness of individual physician recommendations versus the CI output recommendations, using recommendations agreed upon by 2 specialists in the same specialty as a gold standard. The secondary outcome was the recommendations' potential for harm. RESULTS:= 0.11). LIMITATIONS:Cases were from a single institution. CI was solicited using a single algorithm/platform. CONCLUSIONS:When seeking specialist guidance, diagnostic recommendations from the CI of multiple physicians are more appropriate than recommendations from most individual physicians, measured against specialist recommendations. Although CI provides useful recommendations, some have potential for harm. Future research should explore how to use CI to improve diagnosis while limiting harm from inappropriate tests/therapies.

To identify biomarkers of exposure present in Heated Tobacco Products (HTPs) users' urine which are associated with bladder cancer and to compare quantitative biomarker levels to those seen in combustible cigarette users. A systematic literature review was conducted in December 2020 with no date limits. Relevant studies that reported quantitative urinary biomarker of exposure in HTP users were included. Biomarkers and their parent compounds were classified by carcinogenicity according to the International Agency for Research on Cancer Monographs and were cross-referenced with the Collaborative on Health and the Environment Toxicant and Disease Database to determine associations with bladder cancer. Our literature search identified 561 articles and 30 clinical trial reports. 11 studies met inclusion criteria. These studies identified 29 biomarkers of exposure present in HTP users' urine, which reflect exposure to 21 unique parent compounds. Of these parent compounds, 14 are carcinogens and 10 have a known link to bladder cancer. HTP users' biomarkers of exposure were present at lower levels than combustible cigarette users but higher than never-smokers. Biomarkers of exposure to bladder carcinogens are present in the urine of HTP users. While levels of these biomarkers appear to be lower than combustible cigarette users, chronic urothelial exposure to bladder carcinogens is concerning and degree of bladder cancer risk remains unknown. Further long-term study is needed to elucidate the bladder cancer risk of HTP use.

BACKGROUND:Prenatal phthalate exposure has been associated with lower birth weight but also higher weight in childhood. Few studies have examined weight or adiposity from birth to childhood and thus cannot assess growth trajectories associated with exposure. OBJECTIVE:We assessed associations between maternal phthalate exposures in pregnancy and child weight and adiposity measured prenatally through childhood (3-6 years of age). METHODS: RESULTS: DISCUSSION:We observed associations between prenatal exposure to phthalates and lower weight at birth but not at childhood follow-up visits. However, for adiposity, we observed an interesting pattern of association with low adiposity at delivery as well as high adiposity at 3-4 years of age. Although it is not clear from our results whether these associations occur within the same children, such a pattern of adiposity in early life has been linked to cardiometabolic disease in adulthood and deserves special attention as an outcome in the study of prenatal exposures in the developmental origins of health and disease. https://doi.org/10.1289/EHP10077.

OBJECTIVE:To develop a screening tool to identify emergency department (ED) patients at risk of entering a homeless shelter, which could inform targeting of interventions to prevent future homelessness episodes. DATA SOURCES/METHODS:Linked data from (1) ED patient baseline questionnaires and (2) citywide administrative homeless shelter database. STUDY DESIGN/METHODS:Stakeholder-informed predictive modeling utilizing ED patient questionnaires linked with prospective shelter administrative data. The outcome was shelter entry documented in administrative data within 6 months following the baseline ED visit. Exposures were responses to questions on homelessness risk factors from baseline questionnaires. DATA COLLECTION/EXTRACTION METHODS/METHODS:Research assistants completed questionnaires with randomly sampled ED patients who were medically stable, not in police/prison custody, and spoke English or Spanish. Questionnaires were linked to administrative data using deterministic and probabilistic matching. PRINCIPAL FINDINGS/RESULTS:Of 1993 ED patients who were not homeless at baseline, 5.6% entered a shelter in the next 6 months. A screening tool consisting of two measures of past shelter use and one of past criminal justice involvement had 83.0% sensitivity and 20.4% positive predictive value for future shelter entry. CONCLUSIONS:Our study demonstrates the potential of using cross-sector data to improve hospital initiatives to address patients' social needs.