Faculty Bibliography

Background Somatic genetic alterations have been associated with differential disposition of the intratumoral immune milieu. In contrast, the role of germline genetics remains largely unknown. The Cancer Genome Atlas (TCGA) Pan-Cancer Immune Response Working Group recently analyzed associations between immunological features of tumor microenvironment, prognosis, and tumor-intrinsic properties (including somatic mutations and copy number aberrations). The study generated a comprehensive set of per-sample immune response signatures, and identified distinct tumor immunological subtypes shared across multiple cancer types [1]. Here, we examined the germline genetic contribution to >100 such immune response signatures, considered as potential traits, in >9,000 study participants across 30 different cancer types in the TCGA. Methods We used SNP data from Affymetrix 6.0 arrays typed on normal tissue and blood. After stringent quality control, we imputed missing SNPs using the Haplotype Reference Consortium dataset and included SNPs with minor allele frequency >0.005 and imputation quality R2>0.5. We inferred genetic ancestry using principal components analysis. We estimated genome-wide heritability of the immune signatures using the genomic-relatedness-based restricted maximumlikelihood (GREML) approach implemented in genome-wide complex trait analysis (GCTA). We performed genome-wide association studies (GWAS) using linear regression models. All analyses were adjusted for cancer type, age at diagnosis, gender, and genetic ancestry using principal components 1-7. Linear regression was also applied to germline exome sequence data [2] to evaluate rare variant associations. Results Across different tumor types, we found significant heritability (FDR< 0.05) for estimates of innate and adaptive immune cell enrichment including natural killer cells, activated dendritic cells, eosinophils and neutrophils, and T-cell subsets (CD8 Cytotoxic, T-helper, T-follicular helper, T-effector memory, T-central memory, Th1 and Th17 cells) respectively, as well as for antigen-presenting machinery and interferon-related signatures. Furthermore, we found significant interactions between germline modifiers and distinct immune subtypes (FDR<0.05). Through GWAS analysis, we identified several polymorphisms associated with both immune cells and immunomodulatory signaling passing the genome-wide significance threshold (p<5E-8). Two SNPs previously associated with the risk of several auto-immune diseases [3], rs2111485 and rs1990760 mapping to Interferon Induced Helicase C Domain 1 (IFIH1) locus, were significantly correlated with interferon signaling in tumors (Figure 1). Moreover, suggestive associations between rare variants and immune response traits were found. Conclusions We demonstrated that intratumoral immune disposition is partially under germline control through systematic pan-cancer analysis. Germline variants associated with differential immune response might be used to stratify patients based on likelihood of treatment response and to prioritize targets for development of novel therapies. (Figure Preseted)

INTRODUCTION/BACKGROUND:Understanding context and how this can be systematically assessed and incorporated is crucial to successful implementation. We describe how context has been assessed (including exploration or evaluation) in Global Alliance for Chronic Diseases (GACD) implementation research projects focused on improving health in people with or at risk of chronic disease and how contextual lessons were incorporated into the intervention or the implementation process. METHODS:Using a web-based semi-structured questionnaire, we conducted a cross-sectional survey to collect quantitative and qualitative data across GACD projects (n = 20) focusing on hypertension, diabetes and lung diseases. The use of context-specific data from project planning to evaluation was analyzed using mixed methods and a multi-layered context framework across five levels; 1) individual and family, 2) community, 3) healthcare setting, 4) local or district level, and 5) state or national level. RESULTS:Project teams used both qualitative and mixed methods to assess multiple levels of context (avg. = 4). Methodological approaches to assess context were identified as formal and informal assessments, engagement of stakeholders, use of locally adapted resources and materials, and use of diverse data sources. Contextual lessons were incorporated directly into the intervention by informing or adapting the intervention, improving intervention participation or improving communication with participants/stakeholders. Provision of services, equipment or information, continuous engagement with stakeholders, feedback for personnel to address gaps, and promoting institutionalization were themes identified to describe how contextual lessons are incorporated into the implementation process. CONCLUSIONS:Context is regarded as critical and influenced the design and implementation of the GACD funded chronic disease interventions. There are different approaches to assess and incorporate context as demonstrated by this study and further research is required to systematically evaluate contextual approaches in terms of how they contribute to effectiveness or implementation outcomes.

Background: Patients with advanced kidney disease have an elevated symptom burden, increased mortality, and poor quality of life. While palliative care can address these issues, nephrology patients infrequently receive such care. To address this, we implemented an ambulatory kidney palliative care program. We describe our initial outcomes.
Method(s): Utilizing chart abstractions, we characterized the clinic population and symptom burden for patients seen from May 6, 2016-July 6, 2018.
Result(s): Ninety-four patients were referred; 74 (78.7%) patients seen. Forty (54.1%) had follow-up appointments (range 2-13). Mean patient age was 72.7 +/-16 years with 32 (43.2%) on dialysis. The mean symptom burden (n=65) was 12 (+/- 4.9) symptoms (out of 17) with mean severity of 2 (range 0-4), representing moderate severity. The most common physical symptoms were nausea (78%), dyspnea (72%), pain (68%) and itch (66%). Eighty-seven percent reported anxiety and 73% reported depression. There was no difference in symptom burden between patients on dialysis and those on conservative management (n=22). Patients on conservative management were significantly older and had more comorbidities. By visit two, there was a significant reduction in global symptom score (21.9 vs 19.0, p=0.01) in addition to a reduction in anxiety (2.1 vs 1.7, p=0.03), vomiting (0.8 vs 0.2, p=0.04), and restless legs syndrome (1.3 vs 0.8, p = 0.02).
Conclusion(s): Patients with serious kidney disease treated in a kidney palliative care clinic have a high symptom burden regardless of treatment choice. The decision to pursue conservative management is more prevalent in older patients with more comorbidities. Follow up visits to the clinic demonstrated a decrease in symptom burden, suggesting that a dedicated kidney-palliative care clinic may be successful in managing symptoms and addressing unmet need

Demographic and income disparities may impact food accessibility. Research has not yet well documented the precise location of healthy and unhealthy food resources around children's homes and schools. The objective of this study was to examine the food environment around homes and schools for all public school children, stratified by race/ethnicity and poverty status. This cross-sectional study linked data on the exact home and school addresses of a population-based sample of public school children in New York City from 2013 to all corner stores, supermarkets, fast-food restaurants, and wait-service restaurants. Two measures were created around these addresses for all children: 1) distance to the nearest outlet, and 2) count of outlets within 0.25 miles. The total analytic sample included 789,520 K-12 graders. The average age was 11.78 years (SD ± 4.0 years). Black, Hispanic, and Asian students live and attend schools closer to nearly all food outlet types than White students, regardless of poverty status. Among not low-income students, Black, Hispanic, and Asian students were closer from home and school to corner stores and supermarkets, and had more supermarkets around school than White students. The context in which children live matters, and more nuanced data is important for development of appropriate solutions for childhood obesity. Future research should examine disparities in the food environment in other geographies and by other demographic characteristics, and then link these differences to health outcomes like body mass index. These findings can be used to better understand disparities in food access and to help design policies intended to promote healthy eating among children.

BACKGROUND:Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. The ability to predict obesity before age five could be a useful tool, allowing prevention strategies to focus on high risk children. The few existing prediction models for obesity in childhood have primarily employed data from longitudinal cohort studies, relying on difficult to collect data that are not readily available to all practitioners. Instead, we utilized real-world unaugmented electronic health record (EHR) data from the first two years of life to predict obesity status at age five, an approach not yet taken in pediatric obesity research. METHODS AND FINDINGS/RESULTS:We trained a variety of machine learning algorithms to perform both binary classification and regression. Following previous studies demonstrating different obesity determinants for boys and girls, we similarly developed separate models for both groups. In each of the separate models for boys and girls we found that weight for length z-score, BMI between 19 and 24 months, and the last BMI measure recorded before age two were the most important features for prediction. The best performing models were able to predict obesity with an Area Under the Receiver Operator Characteristic Curve (AUC) of 81.7% for girls and 76.1% for boys. CONCLUSIONS:We were able to predict obesity at age five using EHR data with an AUC comparable to cohort-based studies, reducing the need for investment in additional data collection. Our results suggest that machine learning approaches for predicting future childhood obesity using EHR data could improve the ability of clinicians and researchers to drive future policy, intervention design, and the decision-making process in a clinical setting.