I am a neuroscientist with extensive training and research experience in mammalian sleep and circadian neurobiology and physiology and molecular genetics. My long-term career goal is to establish a laboratory in sleep genetics focusing on the inter-relationship of sleep behavior, circadian physiology, and cardio-metabolic function, particularly in vulnerable populations - minority populations (who commonly suffer a disproportionate burden of sleep loss, obesity, diabetes, and CVD) and pediatric populations. My immediate career goals are to acquire the formal didactic and mentored training in genetic statistical analysis and epidemiological and biostatistical modeling skills needed to address these research questions in large cohorts. In order to effectively achieve my career goals I have designed, together with my mentor Dr. Redline and co-mentor Dr. Saxena, a tailored and comprehensive multidisciplinary training plan that uses three targeted approaches: 1) Specific courses in the academic areas of advanced statistical analysis, epidemiology, and biostatistical analysis will provide formal training in essential methods. 2) Critical career development courses, seminars, and workshops offered through the BWH and Harvard-affiliated institutions include grant writing, developing effective presentation skills, communications seminar series, navigating academic promotions systems, managing mentor relationships, and the Brigham leadership program;these opportunities will provide the skills I need to develop and sustain a thriving and independent sleep genetics research program. 3) Intensive work with my mentors and their research groups is described in my training plan, below. Dr. Redline will play a primary role in providing mentored training in epidemiological approaches for the design and analysis of large data sets and their integration into sleep medicine and in cardiopulmonary physiology, and key guidance on developing the funding base for my research program. Dr. Saxena will provide training in genetic statistical methods, biostatistical analysis of multiethnic population data, an metabolic/diabetes function and risk. This focused, mentored research will provide the foundational data, research capacity, publications, and grant-writing expertise needed to successfully compete for funding for my sleep genetics program. Sleep deficiency, a term encompassing insufficient sleep duration and inadequate quality sleep, is a risk factor for obesity, metabolic dysfunction, coronary heart disease, and mortality in adults, independent of other risk factors. The costs of the obesity epidemic, including healthcare costs, and to individual burden of co- morbidities and early mortality, are increasing. Risk of developing obesity, diabetes, and metabolic disorders is influenced by genetic factors, which may influence individual responses to an increasingly obesogenic environment. Although mounting evidence has implicated variants in circadian-related genes in pathways that influence obesity and metabolic phenotypes, there is little research that has explicitly examined in humans the interactions among circadian genes and sleep phenotypes that may influence obesity and metabolic function. Furthermore, no study has examined the associations among circadian genes, objectively-measured sleep phenotypes and obesity and metabolic outcomes across the life course. The long-term goal of my research plan is to determine the role of circadian genes in influencing the inter- related phenotypes of obesity, metabolic outcomes and sleep and to identify age-dependent associations. I will analyze existing genetic data, objectively-assessed sleep (actigraphy) data, and obesity and metabolic outcomes from seven well-characterized cohorts spanning the life course. The overall objective of the proposed studies is to identify circadian gene variants that have significant associations with sleep phenotypes, obesity, and metabolic function. My central hypothesis is that circadian gene variants, independently of or interacting with other genes, influence sleep, obesity, and metabolic phenotypes across the lifespan - in childhood, middle-age, and older adulthood. The rationale for the proposed research is that identification of genes that influence these phenotypes will uncover potential targets for therapeutic and or behavioral intervention designs relevant to several major health disease/disorders. The training objective of the proposed studies is to learn and apply genetic epidemiological methods and advanced statistical analyses to large datasets. It is anticipated that completion of my proposed aims will yield significant associations between candidate SNPs and 1) obesity/metabolic outcomes;2) sleep phenotypes;and 3) other functionally-related genes to modify outcomes across all ages. These results are expected to have an important positive impact on our understanding of the interrelationships between obesity, cardio-metabolic function, and sleep. In addition, this work will provide a framework for examining the role of genetic influences across the age span and for modeling correlated traits as multivariate outcomes, which may have enhanced power. Furthermore, I expect to have obtained extensive training and experience in the design and execution of genetic analyses of sleep, obesity, and cardio-metabolic outcome measures in large and diverse populations.
The research objective of the proposed project is to identify circadian gene variants that have significant associations with sleep phenotypes, obesity, and cardio-metabolic function. The training objective of the proposed project is to learn and apply genetic epidemiological methods and advanced statistical analyses to large datasets of diverse populations.
|Lane, Jacqueline M; Chang, Anne-Marie; Bjonnes, Andrew C et al. (2016) Impact of Common Diabetes Risk Variant in MTNR1B on Sleep, Circadian, and Melatonin Physiology. Diabetes 65:1741-51|
|Chang, Anne-Marie; Aeschbach, Daniel; Duffy, Jeanne F et al. (2015) Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci U S A 112:1232-7|