Progress in Characterizing the Human Exposome: a Key Step for Precision Medicine

Examination of the exposome in an animal model: The impact of high fat diet and rat strain on local and systemic immune markers following occupational welding fume exposure

The goal of this study was to investigate the impact of multiple exposomal factors (genetics, lifestyle factors, environmental/occupational exposures) on pulmonary inflammation and corresponding alterations in local/systemic immune parameters. Accordingly, male Sprague-Dawley (SD) and Brown Norway (BN) rats were maintained on either regular (Reg) or high fat (HF) diets for 24wk. Welding fume (WF) exposure (inhalation) occurred between 7 and 12wk. Rats were euthanized at 7, 12, and 24wk to evaluate local and systemic immune markers corresponding to the baseline, exposure, and recovery phases of the study, respectively. At 7wk, HF-fed animals exhibited several immune alterations (blood leukocyte/neutrophil number, lymph node B-cell proportionality)-effects which were more pronounced in SD rats. Indices of lung injury/inflammation were elevated in all WF-exposed animals at 12wk; however, diet appeared to preferentially impact SD rats at this time point, as several inflammatory markers (lymph node cellularity, lung neutrophils) were further elevated in HF over Reg animals. Overall, SD rats exhibited the greatest capacity for recovery by 24wk. In BN rats, resolution of immune alterations was further compromised by HF diet, as many exposure-induced alterations in local/systemic immune markers were still evident in HF/WF animals at 24wk. Collectively, HF diet appeared to have a greater impact on global immune status and exposure-induced lung injury in SD rats, but a more pronounced effect on inflammation resolution in BN rats. These results illustrate the combined impact of genetic, lifestyle, and environmental factors in modulating immunological responsivity and emphasize the importance of the exposome in shaping biological responses.

Simulating patterns of life: More representative time-activity patterns that account for context

BACKGROUND

Complex contributions of environment to health are intimately connected to human behavior. Modeling of human behaviors and their influences helps inform important policy decisions related to critical environmental and public health challenges. A typical approach to human behavior modeling involves generating daily schedules based on time-activity patterns of individual humans, simulating 'agents' with these schedules, and interpreting patterns of life that emerge from the simulation to inform a research question. Current behavior modeling, however, rarely incorporates the context that surrounds individuals' truly broad scope of activities and influences on those activities.

OBJECTIVES

We describe in detail a range of elements involved in generating time-activity patterns and connect work in the social science field of behavior modeling with applications in exposure science and environmental health. We propose a framework for behavior modeling that takes a systems approach and considers the broad scope of activities and influences required to simulate more representative patterns of life and thus improve modeling that underlies understanding of environmental contributions to health and associated decisions to promote and protect public health.

METHODS

We describe an agent-based modeling approach reliant on generating a population's schedules, filtering the schedules, simulating behavior using the schedules, analyzing the emergent patterns, and interrogating results that leverages general empirical information in a systems context to inform fit-for-purpose action.

DISCUSSION

We propose a centralized and standardized program to codify behavior information and generate population schedules that researchers can select from to simulate human behavior and holistically characterize human-environment interactions for a variety of public health applications.

Achieving Precision Medicine in Allergic Disease: Progress and Challenges

Allergic diseases (atopic dermatitis, food allergy, eosinophilic esophagitis, asthma and allergic rhinitis), perhaps more than many other traditionally grouped disorders, share several overlapping inflammatory pathways and risk factors, though we are still beginning to understand how the relevant patient and environmental factors uniquely shape each disease. Precision medicine is the concept of applying multiple levels of patient-specific data to tailor diagnoses and available treatments to the individual; ideally, a patient receives the right intervention at the right time, in order to maximize effectiveness but minimize morbidity, mortality and cost. While precision medicine in allergy is in its infancy, the recent success of biologics, development of tools focused on large data set integration and improved sampling methods are encouraging and demonstrates the utility of refining our understanding of allergic endotypes to improve therapies. Some of the biggest challenges to achieving precision medicine in allergy are characterizing allergic endotypes, understanding allergic multimorbidity relationships, contextualizing the impact of environmental exposures (the “exposome”) and ancestry/genetic risks, achieving actionable multi-omics integration, and using this information to develop adequately powered patient cohorts and refined clinical trials. In this paper, we highlight several recently developed tools and methods showing promise to realize the aspirational potential of precision medicine in allergic disease. We also outline current challenges, including exposome sampling and building the “knowledge network” with multi-omics integration.

Digital Health for Supporting Precision Medicine in Pediatric Endocrine Disorders: Opportunities for Improved Patient Care

Digitalization of healthcare delivery is rapidly fostering development of precision medicine. Multiple digital technologies, known as telehealth or eHealth tools, are guiding individualized diagnosis and treatment for patients, and can contribute significantly to the objectives of precision medicine. From a basis of "one-size-fits-all" healthcare, precision medicine provides a paradigm shift to deliver a more nuanced and personalized approach. Genomic medicine utilizing new technologies can provide precision analysis of causative mutations, with personalized understanding of mechanisms and effective therapy. Education is fundamental to the telehealth process, with artificial intelligence (AI) enhancing learning for healthcare professionals and empowering patients to contribute to their care. The Gulf Cooperation Council (GCC) region is rapidly implementing telehealth strategies at all levels and a workshop was convened to discuss aspirations of precision medicine in the context of pediatric endocrinology, including diabetes and growth disorders, with this paper based on those discussions. GCC regional investment in AI, bioinformatics and genomic medicine, is rapidly providing healthcare benefits. However, embracing precision medicine is presenting some major new design, installation and skills challenges. Genomic medicine is enabling precision and personalization of diagnosis and therapy of endocrine conditions. Digital education and communication tools in the field of endocrinology include chatbots, interactive robots and augmented reality. Obesity and diabetes are a major challenge in the GCC region and eHealth tools are increasingly being used for management of care. With regard to growth failure, digital technologies for growth hormone (GH) administration are being shown to enhance adherence and response outcomes. While technical innovations become more affordable with increasing adoption, we should be aware of sustainability, design and implementation costs, training of HCPs and prediction of overall healthcare benefits, which are essential for precision medicine to develop and for its objectives to be achieved.

Personalized medicine for allergy treatment: Allergen immunotherapy still a unique and unmatched model

The introduction of personalized medicine (PM) has been a milestone in the history of medical therapy, because it has revolutionized the previous approach of treating the disease with that of treating the patient. It is known today that diseases can occur in different genetic variants, making specific treatments of proven efficacy necessary for a given endotype. Allergic diseases are particularly suitable for PM, because they meet the therapeutic success requirements, including a known molecular mechanism of the disease, a diagnostic tool for such disease, and a treatment blocking the mechanism. The stakes of PM in allergic patients are molecular diagnostics, to detect specific IgE to single-allergen molecules and to distinguish the causative molecules from those merely cross-reactive, pursuit of patient's treatable traits addressing genetic, phenotypic, and psychosocial features, and omics, such as proteomics, epi-genomics, metabolomics, and breathomics, to forecast patient's responsiveness to therapies, to detect biomarker and mediators, and to verify the disease control. This new approach has already improved the precision of allergy diagnosis and is likely to significantly increase, through the higher performance achieved with the personalized treatment, the effectiveness of allergen immunotherapy by enhancing its already known and unique characteristics of treatment that acts on the causes.