Vincent Agboto

The Public Health Exposome: A Population-Based, Exposure Science Approach to Health Disparities Research

The lack of progress in reducing health disparities suggests that new approaches are needed if we are to achieve meaningful, equitable, and lasting reductions. Current scientific paradigms do not adequately capture the complexity of the relationships between environment, personal health and population level disparities. The public health exposome is presented as a universal exposure tracking framework for integrating complex relationships between exogenous and endogenous exposures across the lifespan from conception to death. It uses a social-ecological framework that builds on the exposome paradigm for conceptualizing how exogenous exposures “get under the skin”. The public health exposome approach has led our team to develop a taxonomy and bioinformatics infrastructure to integrate health outcomes data with thousands of sources of exogenous exposure, organized in four broad domains: natural, built, social, and policy environments. With the input of a transdisciplinary team, we have borrowed and applied the methods, tools and terms from various disciplines to measure the effects of environmental exposures on personal and population health outcomes and disparities, many of which may not manifest until many years later. As is customary with a paradigm shift, this approach has far reaching implications for research methods and design, analytics, community engagement strategies, and research training.

Increased Black–White Disparities in Mortality After the Introduction of Lifesaving Innovations: A Possible Consequence of US Federal Laws

OBJECTIVES We explored whether the introduction of 3 lifesaving innovations introduced between 1989 and 1996 increased, decreased, or had no effect on disparities in Black-White mortality in the United States through 2006. METHODS Centers for Disease Control and Prevention data were used to assess disease-, age-, gender-, and race-specific changes in mortality after the introduction of highly active anti-retroviral therapy (HAART) for treatment of HIV, surfactants for neonatal respiratory distress syndrome, and Medicare reimbursement of mammography screening for breast cancer. RESULTS Disparities in Black-White mortality from HIV significantly increased after the introduction of HAART, surfactant therapy, and reimbursement for screening mammography. Between 1989 and 2006, these circumstances may have accounted for an estimated 22,441 potentially avoidable deaths among Blacks. CONCLUSIONS These descriptive data contribute to the formulation of the hypothesis that federal laws promote increased disparities in Black-White mortality by inadvertently favoring Whites with respect to access to lifesaving innovations. Failure of legislation to address known social factors is a plausible explanation, at least in part, for the observed findings. Further research is necessary to test this hypothesis, including analytic epidemiological studies designed a priori to do so.

Reduced annexin A6 expression promotes the degradation of activated epidermal growth factor receptor and sensitizes invasive breast cancer cells to EGFR-targeted tyrosine kinase inhibitors

BackgroundThe expression of annexin A6 (AnxA6) in AnxA6-deficient non-invasive tumor cells has been shown to terminate epidermal growth factor receptor (EGFR) activation and downstream signaling. However, as a scaffolding protein, AnxA6 may stabilize activated cell-surface receptors to promote cellular processes such as tumor cell motility and invasiveness. In this study, we investigated the contribution of AnxA6 in the activity of EGFR in invasive breast cancer cells and examined whether the expression status of AnxA6 influences the response of these cells to EGFR-targeted tyrosine kinase inhibitors (TKIs) and/or patient survival.ResultsWe demonstrate that in invasive BT-549 breast cancer cells AnxA6 expression is required for sustained membrane localization of activated (phosho-Y1068) EGFR and consequently, persistent activation of MAP kinase ERK1/2 and phosphoinositide 3- kinase/Akt pathways. Depletion of AnxA6 in these cells was accompanied by rapid degradation of activated EGFR, attenuated downstream signaling and as expected enhanced anchorage-independent growth. Besides inhibition of cell motility and invasiveness, AnxA6-depleted cells were also more sensitive to the EGFR-targeted TKIs lapatinib and PD153035. We also provide evidence suggesting that reduced AnxA6 expression is associated with a better relapse-free survival but poorer distant metastasis-free and overall survival of basal-like breast cancer patients.ConclusionsTogether this demonstrates that the rapid degradation of activated EGFR in AnxA6-depleted invasive tumor cells underlies their sensitivity to EGFR-targeted TKIs and reduced motility. These data also suggest that AnxA6 expression status may be useful for the prediction of the survival and likelihood of basal-like breast cancer patients to respond to EGFR-targeted therapies.

Monitoring the covariance matrix with fewer observations than variables

Multivariate control charts are essential tools in multivariate statistical process control. In real applications, when a multivariate process shifts, it occurs in either location or scale. Several methods have been proposed recently to monitor the covariance matrix. Most of these methods deal with a full rank covariance matrix, i.e., in a situation where the number of rational subgroups is larger than the number of variables. When the number of features is nearly as large as, or larger than, the number of observations, existing Shewhart-type charts do not provide a satisfactory solution because the estimated covariance matrix is singular. A new Shewhart-type chart for monitoring changes in the covariance matrix of a multivariate process when the number of observations available is less than the number of variables is proposed. This chart can be used to monitor the covariance matrix with only one observation. The new control chart is based on using the graphical LASSO estimator of the covariance matrix instead of the traditional sample covariance matrix. The LASSO estimator is used here because of desirable properties such as being non-singular and positive definite even when the number of observations is less than the number of variables. The performance of this new chart is compared to that of several Shewhart control charts for monitoring the covariance matrix.

Scalable combinatorial tools for health disparities research

Despite staggering investments made in unraveling the human genome, current estimates suggest that as much as 90% of the variance in cancer and chronic diseases can be attributed to factors outside an individual’s genetic endowment, particularly to environmental exposures experienced across his or her life course. New analytical approaches are clearly required as investigators turn to complicated systems theory and ecological, place-based and life-history perspectives in order to understand more clearly the relationships between social determinants, environmental exposures and health disparities. While traditional data analysis techniques remain foundational to health disparities research, they are easily overwhelmed by the ever-increasing size and heterogeneity of available data needed to illuminate latent gene x environment interactions. This has prompted the adaptation and application of scalable combinatorial methods, many from genome science research, to the study of population health. Most of these powerful tools are algorithmically sophisticated, highly automated and mathematically abstract. Their utility motivates the main theme of this paper, which is to describe real applications of innovative transdisciplinary models and analyses in an effort to help move the research community closer toward identifying the causal mechanisms and associated environmental contexts underlying health disparities. The public health exposome is used as a contemporary focus for addressing the complex nature of this subject.

Preterm labor: CD55 in maternal blood leukocytes.

Problem  Intrauterine inflammation is a frequent and significant factor associated with the pathogenesis of preterm labor/birth (PTL/PTB). However, it remains unclear whether the intrauterine inflammatory responses activate the maternal peripheral circulation. We explored the association between PTL/PTB and the ‘activation’ of the peripheral circulatory system by determining whether CD55 mRNA expression within peripheral WBCs differed between PTL and control patients not in labor.

ORIGINAL ARTICLE: Preterm Labor: CD55 in Maternal Blood Leukocytes

Problem  Intrauterine inflammation is a frequent and significant factor associated with the pathogenesis of preterm labor/birth (PTL/PTB). However, it remains unclear whether the intrauterine inflammatory responses activate the maternal peripheral circulation. We explored the association between PTL/PTB and the ‘activation’ of the peripheral circulatory system by determining whether CD55 mRNA expression within peripheral WBCs differed between PTL and control patients not in labor.

A Comparison of Three Approaches for Constructing Robust Experimental Designs

While optimal designs are widely used in the design of experiments, a common concern is that they depend on the form of an a priori assumed regression model. If the assumed regression model is not the same as the true, unknown regression function, the “optimal” design might not be a good choice. Several useful criteria have been proposed to reduce the dependence of optimal designs on a single, assumed model, and efficient designs have been then constructed based on the criteria, often algorithmically. In the model robust design paradigm, a space of possible models is specified and designs are sought that are efficient for all models in the space. The Bayesian criterion given by DuMouchel and Jones (1994) posits a single model that contains both primary and potential terms. In this article we propose a new Bayesian model robustness criterion that combines aspects of both of these approaches. We then evaluate the efficacy of these three alternatives empirically.

Perinatal factors and breast cancer risk among Hispanics

Purpose: This study assessed whether perinatal factors were associated with breast cancer among Hispanics, a group with fairly low incidence rates of breast cancer. Methods: Data were used from a case–control study of breast cancer among Hispanics aged 30–79 conducted between 2003 and 2008 on the Texas–Mexico border. In-person interviews were completed with 188 incident breast cancer cases ascertained through surgeons and oncologists, and 974 controls (with respective response rates of 97% and 78%). Results: Relative to birth weight 2500–3999 g, there was no elevation in breast cancer risk for birth weight of ⩾4000 g (odds ratio [OR] 0.76, 95% confidence interval [CI] 0.47–1.21). Conclusions: The results tended to differ slightly from previous studies of this topic perhaps owing to the different hormonal milieu among Hispanics relative to Caucasians, African Americans and Asians in whom all previous studies of this topic have been conducted. Confirmation of these findings in larger studies may assist in determining how hormonal mechanisms responsible for breast cancer differ by ethnicity.

Abstract 698: Overexpression of the aryl hydrocarbon receptor correlates with high tumor grade in human breast invasive carcinomas

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL The aryl hydrocarbon receptor (AhR) is a ligand-activated basic helix-loop-helix transcription factor which binds environmental poly aromatic hydrocarbons (PAH) and mediates their carcinogenic effects. Recent reports, including data from our laboratory implicate AhR in breast cancer development and progression independent of the receptor occupancy by PAH. In this study we investigated the potential of AhR as a stage specific marker of breast cancer. We examined the expression of AhR by immunohistochemistry in tissue microarrays (TMA) containing 192 specimens of clinically defined three stages of invasive breast cancer: node-negative (NN), node-positive (NP) and metastatic (Met) carcinoma. The TMA were obtained from the National Cancer Institute Cooperative Breast Cancer Tissue Resource [NCI-CBCTR] and were stained for AhR using high affinity antibody. The AhR staining was then scored by three evaluators, including two pathologists who were blinded to the study. Statistical analysis showed a significant correlation between the AhR expression and the carcinoma case type (NN, NP or Met) (p-value of ANOVA is < 0.0003), and although there is a significant difference of AhR expression among carcinoma case type of white women (p< 0.0017) there is no significant difference for black women (p<0.0968). There is also a strong positive correlation between the receptor expression and the tumor grade (p <0.0001). While there is no correlation with the status of estrogen or progesterone receptors (p= 0.1643 and 0.1884, respectively), there is strong correlation of high AhR expression and invasive breast carcinoma in women over 50 years old (p<0.0043). In conclusion, our findings identify the AhR as a new predictive clinical marker for metastatic breast cancer and a unique target for the design of novel selective inhibitors for therapeutic intervention of metastatic breast cancer. More importantly, the AhR overexpression identifies a subset of patients who could benefit from therapy targeting this receptor. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 698. doi:1538-7445.AM2012-698