Developing Biomarker Arrays Predicting Sleep and Circadian-Coupled Risks to Health

Discussion

Biomarkers to assess sleep health and circadian function are needed for research, point-of-care diagnosis of sleep disorders, and to evaluate the risk of associated heart, lung, blood, and aging diseases and disorders.  The availability of objective platforms capable of quantifying sleep and circadian function will ultimately determine whether advances in understanding sleep and circadian biology can be applied to improve medicine and reduce risks to health and public safety.  Without diagnostic tools for point of care measurement of sleep and circadian function, medical care and physician practices addressing sleep problems vary widely and contribute to socioeconomic disparities in health.

The keynote presentation by Mark Rosekind, PhD, Administrator, National Highway traffic safety administration, entitled, "Why do we need sleep and circadian biomarkers?" underscored the scope and human cost of not developing sleep biomarker capabilities.  The administrator identified platforms to objectively assess sleep and circadian function as critical to managing operator errors and risks to public safety in transportation systems world-wide.   

Dr. Peipei Ping, University of California, described an iterative dynamic process of discovery involving bio-physical investigation, identification and quantification, assay design, testing, and validation. This process cycles back between discovery and validation to develop and improve a biomarker until it is reliable and ready for industrial application.  Dr. Al Hero of the University of Michigan described how a small number of samples associated with a large array of characteristics can be used to select candidates for adaptive experimental designs and predictive modeling.  There is efficiency over empirical experimentation since only optimized computational models proceed to validation.  Dr. Christopher O'Donnell, National Heart Lung and Blood Institute, described opportunities to leverage existing cohorts and big data capabilities to validate biomarkers discovered in the experimental setting and their association with heart, blood, lung and sleep across disease states.  Exploiting functional genomics and precision medicine will facilitated translation and clinical application.

Dr. David F. Dinges of the University of Pennsylvania linked acute and chronic sleep loss to impaired behavioral function.  Insufficient and mis-timed sleep influences circadian rhythmicity through an array of physiological pathways.  Dr. Derk-Jan Dijk, University of Surrey, associated sleep timing with abnormalities in metabolic indicators, endocrine markers, and expression of the human blood transcriptome.

The plenary portion of the workshop closed with a summary by Dr. John Hogenesch, University of Pennsylvania on the State of the Science underlying development of sleep and circadian biomarkers.  He underscored that new collaborative teams will be needed to juxtapose emerging analytic approaches and biomarker technologies with a constellation of advances in sleep and circadian biology to overcome barriers to timely translation, application and implementation.

Breakout sessions paired sleep and circadian researchers with biomarker experts to discuss four “use case” examples of biomarker application.  The groups were charged with identifying existing opportunities for rapid development, accelerate development, critical gaps in knowledge, and key challenges to the development of biomarker panels from a pre-clinical phase to point-of-contact application.

Use Cases

1. Acute Sleep Loss

   Predict impaired behavioral function and performance relevant to fitness for duty. A biomarker might be used for roadside screening to assess sleep loss as a risk to performance and safe operation of a vehicle.

   The group noted that biomarker detection of a single night of sleep loss would need to be developed with consideration of potential sex and age specific differences.  Individual baseline data may be required to establish a reliable comparison for subsequent detection of acute sleep loss. Characterizing the extremes on the response dimensions to sleep deprivation was identified as a useful strategy for identifying metabolic signatures to acute sleep loss. Individuals may also vary in vulnerability to sleep loss and research may be needed to elucidate benchmarks of normality.  Existing cohorts could be leveraged by adding sleep phenotypes to accelerate the elucidation of normal benchmarks and biomarker development. 

2. Chronic Sleep Loss
   Predict risks to health reflecting long term deficiency in duration, timing, or quality of sleep.  The setting for the use of such a biomarker might be the annual physical examination at the PCP office, for instance.

   The group identified the need to develop clinical definitions and phenotypic measures relevant to predicting sleep health-related outcomes.  Adding sleep phenotypes to existing disease-risk based cohorts would accelerate the elucidation of biomarker development.  Combining “wearable” sleep/circadian monitoring technology, biochemical markers, and -omics characterization with computational modeling approaches would open new directions for management of sleep related risks to health.

3. Circadian Phase and Mistimed Sleep 

   Predict the adequacy of sleep and circadian rhythm alignment associated with optimal restorative, physiological, and homeostatic benefits of sleep.  These biomarkers could be used by primary care to differentiate insomnia, circadian phase disorders, shiftwork disorder, and extreme chronotypes.  Rhythm biomarkers could also enable the personalization of medical therapy with time-of-day dosing for oncologic and other pharmacotherapies. Surgical outcomes with potential links to circadian physiology such as cardioprotection from remote limb ischemic preconditioning, transplant tissue matching, vaccination, and metabolic disease management would also benefit from such biomarkers.

   The group identified the need for circadian characterized biosamples as a major barrier to biomarker development.  Since existing cohorts are not phenotyped with regard to circadian phase, the elucidation of circadian biomarkers will depend on prospective tissue collection (urine, saliva, blood, epithelial cells) combined with wearable sleep/circadian devices and –omic analyses. Research will be needed to elucidate the interaction of central and peripheral circadian rhythms, their interrelationships, and influence on approaches to individualized medicine.  Biomarker development will be accelerated by new capabilities to monitor the environment for factors modifying circadian rhythm.  These technologies open the door to opportunities leveraging big data approaches and international collaboration.  Adding time stamps to index samples collected in ongoing cohort studies could potentially increase the tissue resource suitable for sleep/circadian biomarker research.

4. Sleep Disordered Breathing
   Diagnostic aids to facilitate triage of probable sleep apnea identification, and personalize /optimize therapeutic strategy, identify comorbid health risks, and prognostic outcome stratification.

   The application of currently available -omic technologies to time-of-day indexed blood, urine, saliva and breath volatiles/condensate  samples was identified as essential to enabling the application computational approaches to biomarker development. These analyses will improve the interpretation of biomarker profiles for sleep apnea, aging, and comorbid heart, lung, and blood disorders, open new avenues to improve algorithms for risk stratification, and ultimately inform the selection of targeted/personalized treatments.  Elucidating domains of potential overlap is essential to developing a sensitive and specific marker for sleep apnea. Comparing extreme cases and determining the influence of individual differences, such as age and sex, will be helpful in linking phenotypes with useful biomarker.  Considering the impact of sleep apnea on multiple organ systems, disease vulnerability, aging-related outcomes, and public safety, inter-agency coordination was identified as an important overall strategy. 

Recommendations

There is compelling evidence that prevalent sleep deficiency and untreated sleep disorders contribute significantly to precipitating mechanisms and pathogenesis of heart, lung, blood, and aging disorders.  Decrements in sleep and circadian function reduce the likelihood of individuals achieving their optimal health outcome.  Race and ethnic differences in sleep-dependent biobehavioral factors contribute to health disparities, and conversely limit the ability of individuals to achieve their best possible socioeconomic status through its impact on performance in work and school, interpersonal/family relationships, medical/mental health, aging, and safety.  Biomarker development is critical to enabling social, medical, safety and health support delivery systems to detect individual risks to sleep/circadian health and measure responses to therapeutic interventions. 

Research Objective 1: Increase the scientific impact of prospective tissue collection for clinical research NIH-wide by encouraging specimen time-stamping for characterization of sleep/circadian health to enhance the precision medicine initiative.  In addition, promoting the integration of sleep/circadian parameters will facilitate the ability to leverage data repositories essential for computational biomarker development and predictive modeling approaches.  Secondary analyses of well-characterized datasets enhanced with sleep/circadian phenotypes would open the door to a new array of hypothesis testing, risk stratification and ultimately new opportunities for personalized medicine including the precision medicine initiative.  Access to cohorts with specimens time-stamped for sleep and circadian information should be enhanced through a public index.

Research Objective 2: Foster collaborative research partnerships between sleep/circadian discovery researchers at national and international levels, the research pipeline required to develop biomarkers predicting risks to health and safety, and implementation scientists developing point-of-contact applications.  Assembling the scientific teams needed to advance biomarker development in sleep and circadian domains will be a prerequisite to establishing research momentum.  Leveraging existing biomarker development activities by adding sleep/circadian expertise and data collection would efficiently accomplish this goal.

Research Objective 3: Remove barriers to planning, conducting, and reporting of sleep/circadian phenotypes in clinical research.  Foster the development and validation of “wearable” devices, m-Health applications, and instruments suitable for population-based and big data approaches used in developing predictive models and biomarker platforms assessing sleep and circadian health.  Encourage studies of physiological extreme sleep/circadian types that can be used reference ranges facilitating the modeling and interpretation of molecular analyses.

Research Objective 4: Encourage integrative research approaches in training programs in order to capitalize on the opportunities to advance science and improve public health through sleep/circadian biomarker development.  Sleep and circadian biology is a fundamental characteristic of all organs, physiological systems, and health-related behaviors that is generally under-represented in research training.  Incorporating this science and cross-training will accelerate biomarker development and ultimately stimulate new scientific discoveries in existing domains of research and medicine.

Support: This workshop was jointly supported by the NHLBI, NIA, and Sleep Research Society

Workshop Co-Chairs

• Geoffrey Ginsburg, M.D., PhD, -Duke University
• Allan Pack, MBChB, PhD, FRCP, -University of Pennsylvania. President, Sleep Research Society
• Janet Mullington, PhD, -Harvard Medical School
• Michael Twery, PhD, -National Heart, Lung, and Blood Institute
• Miroslaw Mackiewicz, PhD, -National Institute on Aging

Workshop Participants

• David F. Dinges, Ph.D.-University of Pennsylvania
• Ronald G. Crystal, M.D.-Weill Cornell Medical College
• Karyn A. Esser, Ph.D.-University of Kentucky
• David Gozal, M.D.-The University of Chicago Medicine
• John Harer, Ph.D.-Duke University
• Alfred Hero, Ph.D.-The University of Michigan
• John B. Hogenesch, Ph.D.-University of Pennsylvania
• M. Mahmood Hussain, Ph.D., Lic. Med.-SUNY Downstate Medical Center
• Rima Kaddurah-Daouk, Ph.D.-Duke University School of Medicine
• Satchidananda Panda, Ph.D.-The Salk Institute
• Peipei Ping, Ph.D.-UCLA School of Medicine
• Virend Somers, M.D., Ph.D.-Mayo Clinic at Rochester