of Program Coordination, Planning, and Strategic Initiatives
Title of proposed idea: Synergizing Omic Science with Patient Reported Outcomes
Nominator: NIH Institutes/Centers
Major obstacle/challenge to overcome: Current breakthroughs in omic research have increased awareness that diseases are complex disorders arising in response to the interaction among multiple genes, cellular metabolites, and environmental factors. In addition, there is growing speculation that how a person experiences illness may be genetically predisposed. Hence, a new era suggests scientific progress towards innovations in health will require the integration of diverse information from biologic processes, physiologic pathways, and behavioral models in order to predict and treat disease, improve survival, manage symptoms and enhance quality of life. This symbiosis of disparate knowledge is necessary to ensure biomedical science improves health through its translation into practical clinical applications. Therefore, fostering synergy between omic science (genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics) and patient reported outcomes such as symptoms (‘‘sympt-omics ‘’) and health-related quality life (HRQL) may promote new pathways for reducing burdens associated with chronic illness and enhance personalized health
Emerging scientific opportunity ripe for Common Fund investment: Progress in this area promises to fill gaps in broadening the links between genetic and molecular variants and patient reported outcomes in chronic illness. This opportunity will: 1) support cross-cutting research with substantial potential to create new perspectives for reducing the illness burden of chronic health conditions; and 2) encourage collaborative teams of diverse, interdisciplinary investigators to tackle the complex health and research challenges posed by chronic illness and to turn their discoveries into practical solutions for patients.
Common Fund investment that could accelerate scientific progress in this field:
Potential impact of Common Fund investment: Synergy of omic profiling with practical application to patients will allow new pathways for improving treatment outcomes to emerge and ultimately reduce the chronic illness burden and enhance personalized health across the lifespan.
Tags: new methods, genetics/genomics, proteomics, metabolomics, epigenomics, symptoms, patients, biomarker, intervention
Title of proposed idea: Developmental Origins of Health and Disease: Disease Prevention Across Generations
Major obstacle/challenge to overcome: It is clear that many complex diseases and conditions result from a combination of genetics and environment. What is not clear is when and how this interaction of genetics and environment actually leads to disease. The concept of developmental origins of health and disease (DOHaD) is a fundamental principle underlying many chronic diseases and conditions in children and adults. Decades of DOHaD studies suggest that a wide variety of early exposures occurring during periods of time where tissues and organ systems are developing markedly increase risk for (or even cause) disease across the life course. These “environmental” exposures are varied and include drugs, nutrition, chemicals, stress, microbes or viral infections. Examples of these non-communicable diseases and disorders (NCDs) include obesity, type II diabetes, insulin resistance, asthma, cardiovascular diseases, dyslipidemia, cognitive and behavioral disorders, neurodegenerative diseases, a variety of cancers, and reproductive disorders. Disadvantaged populations may experience greater exposure to these hazards and exhibit higher rates of disease incidence, morbidity and mortality. Understanding and modulating this risk in humans during critical windows of development offers the promise of primary prevention for many of these NCDs and may result in reducing health disparities.
Although the range of diseases and conditions believed to result (at least in part) from early life exposures spans nearly all of the NIH Institutes and Centers (ICs), the concept of developmental origins has yet to be broadly adopted as a new research paradigm. A trans-NIH program funded by the Common Fund (CF) will support research to 1) characterize early life exposures and their health effects in a comprehensive way, 2) encourage cellular and molecular research on the mechanisms of these triggers (or stressors) on development, and 3) encourage the development of targeted interventional studies in human subjects. The initiative would result in a new awareness among researchers funded across the NIH to consider the role of developmental stressors in triggering the diseases and conditions they study. This would also jumpstart the field of transgenerational inheritance, i.e., the transmission of environmentally-induced phenotypes to subsequent generations without direct exposure. This phenomenon is well-described in non-mammalian systems, but despite the existence of several published examples, it remains highly controversial whether it truly occurs in humans or rodents, or how common it might be. Finally, the initiative would build the body of science needed to strengthen prevention research, an important element of health care reform.
Emerging scientific opportunity ripe for Common Fund investment: No single IC has the capability or the expertise to integrate all the approaches and technologies needed to assess how genetics and multiple environmental triggers (or stressors) combine to affect health across the lifespan and even across generations. Furthermore, early life exposures even to a single stressor can lead to adverse health outcomes affecting multiple tissues and organ systems that are not readily appreciated in traditional single institute research programs. For these reasons, adopting a coordinated, trans-NIH approach is a critical step in changing existing paradigms about the etiology of a variety of diseases and conditions, and transforming this information into knowledge that targets the most advantageous times, and possible interventions, to prevent their occurrence. This program would also leverage and integrate current CF and trans-NIH initiatives such as those on epigenetics, exposure biology, genetics/genomics, the microbiome, bioinformatics, developmental biology and programming, stem cell development and differentiation, and animal, epidemiologic and clinical assessment of disease.
Common Fund investment that could accelerate scientific progress in this field: We propose a CF program that will transform thinking about disease prevention: a comprehensive investigation of the developmental basis of a wide range of diseases and conditions. Such a program would enable the NIH to identify a host of environmental stressors that increase disease risk, and the mechanisms by which these exposures alter normal developmental programs, manifesting in disease or conditions, years and even generations later. Moreover, a comprehensive research program focused on the developmental origins of disease would enable scientists to pinpoint susceptibility windows – unique developmental time points at which humans are most susceptible to the combined effects of environmental exposures and genetic factors. Identifying these developmental windows and developing predictive biomarkers of exposure will dramatically increase our ability not only to understand disease etiology, but also to develop intervention strategies that will ultimately prevent disease, by reducing exposure. Possible investments include:
1. Develop centralized, well-characterized, novel models and clinical research designs and analytic techniques that would promote effective multigenerational analysis and would leverage existing CF investments and infrastructure, such as that in mouse phenotyping (KOMP2).
2. Identify stressors (nutritional, environmental, social) and investigate early gene-environment interactions that may perturb the normative development of various tissues and organ systems (such as the cardiovascular, neurological, immune, gastrointestinal, skeletal, endocrine, reproductive systems), increasing the risk of disease or conditions later in life and across generations. Particular focus would be placed on diseases, conditions or syndromes that have been steadily increasing in incidence and where health disparities are apparent in the United States. A focus on exposure characterization during early life would be imperative and would include vulnerable populations defined by race, ethnicity, and socioeconomic status.
3. Apply state-of-the-art sequencing technologies to investigate epigenetic and genetic mechanisms by which early life events lead to developmental reprogramming, impacting disease risk both in both children and adults (e.g., somatic or cognitive changes) long after the stressor is gone, and how increased risk is transmitted to subsequent generations through various mechanisms (i.e., germline, mitochondrial, or other changes).
4. Use birth cohorts in human subjects, to identify sex-specific developmental susceptibility windows that are specific to common diseases and conditions in early development.
5. Identify biomarkers of developmental stress for single exposures and combinations that predict susceptibility to specific diseases and conditions later in life that could also be used to target and develop preventive interventions.
6. Develop bioinformatics and statistical programs to allow the assessment and integration of developmental exposure to a variety of stresses and their importance in the development of disease outcomes.
Potential impact of Common Fund investment: This would be the first CF program specifically designed to focus on disease prevention, and it will do it in an integrated and transformative manner. Once it is clear how certain diseases or conditions originate in early development – including which stressors or combinations of stressors are responsible for the altered programming, and during which developmental stages humans are most sensitive to these effects – effective strategies can be developed both to reduce exposure to the stressors and or intervene to reduce disease incidence. Such strategies have the potential not only to reduce the overall societal burden of disease but to reduce or eliminate health disparities.
Tags: new tools, computational, prevention, intervention, developmental, genetics/genomics, biomarker, disease, environmental
Title of proposed idea Chronic Pain Conditions: A Transformative Classification for Stimulating Research, Improving Diagnosis, and Personalizing Treatment
Major obstacle/challenge to overcome: Chronic pain conditions afflict as many as one-third of the US population and incur $560-635 billion per year in incremental healthcare costs and lost productivity (IOM Report June 29, 2011). The long term clinical goal in alleviating chronic pain is to develop targeted therapies and identify patients responsive to these therapies, both of which are supported by etiological- and mechanism-based case definitions and diagnostic criteria of disease. A major challenge in the field is the lack of a mechanism-based case definition and diagnostic criteria for multiple chronic pain conditions. Common Fund investments could facilitate the development of a new objective, biopsychosocial classification system for chronic pain disorders to overcome this major obstacle. This new system will accelerate research by standardizing research diagnoses used across laboratories, enhance clinical diagnoses by developing more objective, mechanism-based measures of disease, and identify subjects responsive to new therapies by developing novel biomarkers of disease and clinical outcomes.
Emerging scientific opportunity ripe for Common Fund investment: We propose a research program to develop a new, comprehensive, mechanism-based, biopsychosocial classification of chronic pain conditions. Three opportunities are ready for Common fund investment. This proposal endorses the ideas and sharpens the focus of “Molecular Classification of Disease”, a topic that emerged from the Innovation Brainstorm meeting, and takes on sophisticated data management and analysis elements of the topics on “Beyond GWAS” and “Cross-Cutting Issues in Computation and Informatics”.
Common Fund investment that could accelerate scientific progress in this field: This program would create a centralized data bank/repository containing information from a large chronic pain cohort to include study subjects with Temporomandibular Joint Disorders, Fibromyalgia, Chronic Fatigue Syndrome, Vulvodynia, Endometriosis, Irritable Bowel Syndrome, Interstitial Cystitis, Headache, Low Back Pain, Arthritis, etc., recruited and identified using today’s best diagnostic criteria. Many of these subjects will have multiple, comorbid chronic pain conditions. This cohort would be genotyped as well as phenotyped extensively using molecular, imaging and psychosocial methodologies. All data would be agnostically analyzed via pathway analyses and new algorithms for lumping and splitting in order to subtype and re-classify these chronic pain patients. Results emerging from the Common Fund incubator space would lead to a breakdown in the current “walls” separating these disorders (and researchers) and a transformation of diagnostic criteria based on a completely new classification of chronic pain conditions. After an intense 5 year effort, the data bank/repository and analytical tool set would become self sustaining with support from Pharma, the genotyping industry, and the NIH Pain Consortium.
Potential impact of Common Fund investment: The outcome of this project will be a completely new way of discovery and management of chronic pain conditions: researchers currently housed in different laboratories collaborating in multidisciplinary teams to study pain, rapid discovery of therapeutic targets, development of novel analgesic therapies based on common mechanisms of disease, introduction of individualized medical treatments and identification of those likely to respond to therapy. Ultimately, results from this project will lead to an overall reduction in the burden of chronic pain, currently $560-$635 billion/year in the US in incremental healthcare costs and lost productivity.
Chronic pain should be thought of as a disease unto itself like other chronic conditions such as diabetes and heart disease, and not merely a symptom of disease. Research approaches to and management of chronic pain conditions must consider that, like other chronic conditions, disease progression and complexity, early identification and intervention, and effective therapies, all influence patient burden and economic costs of disease. A transformative classification of chronic pain conditions will ultimately reduce long-term morbidity and decrease the economic impact of these wide-spread conditions.
Tags: pain, diagnostics, therapeutics, clinical, classification system, biomarker, molecular mechanism
Title of proposed idea: Biomarkers for chronic pain using functional brain connectivity
Major obstacle/challenge to overcome: Chronic pain is a debilitating condition affecting at least 116 million American adults, resulting in significantly reduced quality of life and an estimated annual cost of $560 – 635 billion 1. Unfortunately, its assessment is based solely on subjective self-report, using limited scales or measures, which are unsuitable for elucidating the different types and causes of pain (i.e., pain endophenotypes) and for rigorously evaluating the impact of targeted interventions. Self-report measures also hamper progress in the monitoring required to precisely dose a medication and then evaluate its comparative effectiveness among different individuals. Also, importantly, the field of pain management has been long challenged by the twin fears of undertreating pain in those who are suffering vs. triggering or facilitating a drug problem. Because of all these obstacles, there is a pressing need for a standardized, brief and simple measurement that can translate, or at least reproducibly correlate, subjective pain experience into objective and quantitative readings for both clinical and research purposes.
Emerging scientific opportunity ripe for Common Fund investment: In functional neuroimaging, there has been a recent explosion of findings on functional connectivity (FC) between brain regions, especially in the resting-state (RSFC), which is defined as the signal coherence between discrete brain regions in the absence of a cognitive task. RSFC has uncovered discrete functional networks, where the strength or activity coherence can be quantified. Based on recent reports of differences in intrinsic brain network connectivity between patients with chronic pain and controls, it has been suggested that RSFC could be a suitable platform to develop objective biomarkers of pain. Moreover, recent expansion of neuroimage data-sharing, especially of RSFC data in the 1000 Functional Connectomes Project, has demonstrated that data from different sources can be pooled to define subtypes of populations stratified by age, gender, medical conditions, and other variables, to enhance statistical power for discovery. If this level of between-labs consistency turns out to also apply to pain related measurements, RSFC could revolutionize the field of pain research and management.
Common Fund investment that could accelerate scientific progress in this field: Chronic pain is a clinical condition characteristic of a wide range of physical syndromes that collectively span the programmatic purview of many different ICs. A request for applications (RFA) on this topic to fund five or six research project grants would enable multi-disciplinary teams (comprised of pain clinicians, functional neuroimagers, and computational/network neuroscientists) to 1) develop techniques for image time-series analysis to identify brain RSFC signatures of different types of chronic pain, and 2) test the value of said signatures in a clinical context. For example, R21/R33 phased-innovation awards would enable initial collaborations to assess basic cross-sectional differences between controls and patients with different syndromes of chronic pain, and to develop and optimize new analytical tools for better identification of sensitive and specific RSFC biomarkers of pain. The common fund program concept would also enable comparative effectiveness research, data harmonization across funded projects, foster a consortium on pain RSFC biomarkers, and inform prospective evidence-based, personalized care of pain.
Potential impact of Common Fund investment: Advances in image acquisition and data analytic approaches could yield a level of objectivity, sensitivity, and specificity that would be unprecedented for chronic pain. In theory, a single resting-state functional MRI scan could serve as a diagnostic procedure akin to a head MRI for brain cancer or other neurological diagnoses. Data derived from that scan may not only provide an objective and reliable marker, but also help identify optimum therapeutic approaches, lowering the costs and loss of productivity associated with ineffective pain treatments. Validation of pain biomarkers is critical in the development of pain medications and for the adequate use of prescription analgesics matched to the needs of individuals. When the proposed program achieves its objectives, the collaborative effort among funded projects will complete the characterization and validation phase of functional brain connectivity as biomarkers for chronic pain, helping to bring evidence-based, personalized management of pain closer to reality.
Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education
and Research. Committee on Advancing Pain Research, Care, and Education Board on Health Sciences Policy. Institute of medicine of the national Academies (2011).
Tags: neuroimaging, biomarker, pain, clinical