Next generation modeling of omics, exposures and social determinants in health inequities

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1 Next generation modeling of omics, exposures and social determinants in health inequities Terry Hyslop, PhD Professor, Duke University Department of Biostatistics & Bioinformatics Director of Biostatistics Duke Cancer Institute

2 Conflict of interest Funding sources: NIH, NCI, Breast Cancer Research Foundation, Komen Foundation Consultant to AbbVie 1

3 The importance of measurement But in the past year I have been struck again and again by how important measurement is to improving the human condition. You can achieve amazing progress if you set a clear goal and find a measure that will drive progress toward that goal Bill Gates 2013 Annual Letter 2

4 Human Genome timeline The Human Genome Project Timeline contains major milestones in genomics from 1865 to More: Darryl Leja, NHGRI. 3

5 Human genome evidence? Cystic fibrosis CFTR (G551D) Pharmacogenomic for ivacaftor Tier 1 HIV HLA-B*5701 Pharmacogenomic for abacavir Tier 1 Lipid disorders, cholesterol, dyslipidemia Familial hypercholesterolemia (FH) Unresectable or metastatic melanoma Unresectable or metastatic melanoma Unresectable or metastatic melanoma Family history of cardiovascular disease before age 50 years in male relatives and age 60 years in female relatives DNA testing and LDL-C concentration measurement Risk factor (for coronary heart disease) to inform cholesterol screening Tier 1 Cascade testing of relatives of people Tier 1 diagnosed with FH BRAF V600E Pharmacogenomic for vemurafenib Tier 1 BRAF V600E Pharmacogenomic for dabrafenib Tier 1 BRAF V600E/K Pharmacogenomic for trametinib Tier 1 Non-small cell lung cancer ALK gene rearrangement Pharmacogenomic for crizotinib Tier 1 Locally advanced or metastatic nonsmall-cell lung cancer Metastatic non-small-cell lung cancer Transfusion-dependent anemia due to low-or intermediate-1-risk myelodysplastic syndromes associated with a deletion 5q Leukemia, lymphoma, solid tumor malignancies EGFR (exon 19 deletions and exon 21 (L858R) substitution mutations) EGFR (exon 19 deletions and exon 21 (L858R) substitution mutations) Pharmacogenomic for erlotinib Tier 1 Pharmacogenomic for afatinib Tier 1 Chromosome 5q deletion Pharmacogenomic for lenalidomide Tier 1 G6PD Pharmacogenomic for rasburicase Tier genetic tests with Level 1 evidence, most for therapeutic selection CDC, Office of Public Health Genomics

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7 Open cohort of all Medicare beneficiaries (60,925,443 persons) 460,310,521 person-years of follow-up from 2000 to 2012 PM2.5 and ozone measured at zip code of participant Significant evidence of adverse mortality effects related to exposure to PM2.5 and ozone at concentrations below current national standards Most pronounced among self-identified racial minorities and people with low income 6

8 Variation of average PM2.5 over regions, years, and months within year 7

9 Lancet, participants aged years enrolled in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) in six metropolitan areas in the USA. Residence-specific spatio-temporal pollution concentration models, incorporating community specific measurements, agency monitoring data, and geographical predictors, estimated concentrations of PM2.5 and nitrogen oxides (NOX) In analysis adjusted for potential confounders, a 5 μg/m. higher PM2.5 concentration was associated with 4.1 units per year (95% CI ) increased rate of coronary artery calcium progression. 8

10 20 17 En vi ro nm en ta lh ea l th Sc ho l ar s Fa ll Fo ru m PM2.5 and NOx in cohort locations, points are study participants 9

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13 Racial (or other) discrimination stress SES Low physical activity nutrition smoking Lack of open space PM2.5 Access to nutritional foods trust 12 Insurance and coverage Other financial access burdens Drug responsiveness biomarkers Inherited or acquired risk

14 Health Behaviors Environmental Exposures Social Determinants Built Environment Race 13 Socioeconomic Status Biology

15 Health Behaviors Environmental Exposures Social Determinants Built Environment Race 14 Socioeconomic Status Biology

16 How do we measure socioeconomic status? No consistency/standards in implementation racial differences in models often disappear after adjusting for SES in standard modeling approaches REAL problems: Lack of SES-based information in many studies Lack of characterization/measurement of SES Differential healthcare resources, may not be measured well Current standard modeling approaches introduce collinearity due to association of measures, utilize simplistic assumptions 15

17 Index domains Poverty % Poverty % Female-headed % Income <$30k % Public Assistance % No Vehicle % No Telephone Employment % Unemployed % Males not in Workforce Education % No HS Education Residential Stability % In Same Residence Since 1995 Occupation Messer LC, Laraia RA, Kaufman JS, et al. The Development of a Standardized Neighborhood Deprivation Index. Journal of Urban Health. 2006; 83(6): % Management (M) % Management (F) %Professional Occup. (M) % Professional Occup. (F) Housing % Crowded Housing % Rented Housing % Vacant Housing % Median Household Value % Renter/Owner Costs in Excess of 50% of Income Residential Composition % Non-Hispanic Black % Older than 65 Years % Single/Unmarried % Single with Dependents

18 A Latent Class Model of SES High Advantage Low Disadvantage High Advantage High Disadvantage Low Advantage Low Disadvantage Low Advantage High Disadvantage Palumbo A, Michael Y, Hyslop T. Latent class model characterization of neighborhood socioeconomic status. Cancer Causes & Control. 2016;27(3):

19 20 17 En vi ro nm en ta lh ea l th Sc ho l ar s Fa ll Fo ru m Socio-economic burden differences and complexity of correlation 18

20 lh ea l ro nm en ta En vi th ar s Sc ho l Fa ll Fo ru m

21 Strong correlation of race and biology 20

22 Strong correlation of race and SES measures 21

23 Outcomes of biology stratified by SES 22

24 Fa ll Fo ru m Extending modeling to food availability, environmental burden, and insulin resistance ro nm en ta lh ea l th Sc ho l ar s Bayesian Hierarchical Distributed Lag models En vi Within the rings, include food access, environmental burdens, SES And at individual level measure behaviors, biomarkers, other factors R01CA , Epigenetic damage in women living in LA food-desert zip codes, Seewaldt, Anh, Shones, Hyslop, co-pis 23

25 17 20 lh ea l ro nm en ta En vi th ar s Sc ho l Fa ll Fo ru m Environmental exposures 24

26 Food vulnerability and health Low-income census tracts where a significant number or share of residents is more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket. 25

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28 17 20 Environmental exposure and health 27 lh ea l ro nm en ta En vi th ar s Sc ho l Fa ll Fo ru m

29 Zwickl, K., Ash, M. & Boyce, J.K., Regional Variation in Environmental Inequality: Industrial Air Toxics expsure in U.S. cities. Ecological Economics, (107), pp

30 Project in development Hot spots of breast cancer incidence in NC 29

31 20 17 En vi ro nm en ta lh ea l th Sc ho l ar s Fa ll Fo ru m Environmental Exposure in NC Diesel exposure from EJSCREEN 30

32 Characteristics of models Area level heterogeneity Relative distances in area-specific way Measures association pertinent to areas, and determines whether there is uniformity of association or lack thereof For example if BMI is associated with presence of convenience stores; is that always the case, or not? Our role: to extend the models to incorporate area level exposures i.e. environmental exposures, as well as individual level exposures such as biomarkers, epigenetic markers, behaviors, and SES 31

33 Summary There is an underlying complexity to the drivers of disease initiation, progression, and prognosis Many drivers differ in sub-populations, such that personalized interventions may be required. Modeling approaches should incorporate the complexity The ultimate goal is to identify modifiable factors and sub-populations most at risk! 32

34 Acknowledgements Ladies of Port Richmond A grass-roots organization of working-class women in Philadelphia who raise funds for breast cancer research, and provided my first funding in breast cancer disparities Komen Foundation Provided funding that established much of this work and solidified my thinking on disparities NCI Funding our new grant to study food deserts, epigenetics 33

35 Thank you! With four parameters I can fit an elephant and with five I can make him wiggle his trunk. John von Neumann. 34