Exit off canvas

Personal Information

Prefix/Title

Dr.

First Name

Andrew

Last Name

Lim

Email Address

andrew.lim@utoronto.ca

Bio

 
Dr. Lim is a scientist in the Hurvitz Brain Sciences Research Program at Sunnybrook Research Institute, an assistant professor of neurology at the University of Toronto and a neurologist at Sunnybrook Health Sciences Centre in Toronto. The focus of his clinical practice  and research programme is on disorders of sleep and circadian biology, especially as they relate to brain health. He completed an MD and residency in neurology at U of T, a clinical sleep fellowship at the Beth Israel Deaconess Medical Center in Boston and a master’s degree in clinical investigation at Harvard Medical School.

Academic Appointment Information

Academic Rank

Assistant Professor

Research Site

Sunnybrook Health Science Centre

Primary Graduate Appointment

IMS

Membership Type

Associate Member

Currently Recruiting Students

I am currently recruiting students

Project Description

Dr. Lim’s research is focused on answering three broad questions:

1) What is the impact of sleep and circadian rhythm disruption on human brain health, from neurobiological mechanisms to health outcomes?;
2) What are the genetic mechanisms contributing to human sleep and circadian function, and how can we modify their impact on brain health?; and
3) What are the molecular substrates of circadian and seasonal rhythms of human brain biology in health and disease?

To answer these questions, and in collaboration with laboratories in Toronto and elsewhere, he uses a number of complementary techniques. These include the following:

– ambulatory at-home measurement of sleep and circadian biology using wearable devices;
– genome-wide association analyses and other population genetic approaches;
– time-series analysis of genome-scale RNA sequencing, DNA methylation, and ChIP-seq (chromatin immunoprecipitation sequencing) data;
– MR brain imaging;
– computer-assisted psychometric testing;
– human brain histopathology; and
– linkage to administrative health databases.

 

He is applying these techniques in several large studies including:

 

1) The Ontario Sleep Health Study, which has prospectively obtained objective sleep and circadian measurements and blood samples from more than 2,000 Ontarians, of whom more than 300 have had brain MR imaging and psychometric testing. The team also has consent for linkage to administrative health databases at the Institute for Clinical Evaluative Sciences.
2) The Sunnybrook Brain Changes in Sleep Apnea study, in collaboration with Dr. Sandra Black and Dr. Brad Macintosh. The researchers will obtain detailed ambulatory measures of sleep physiology and cardiovascular physiology, detailed brain MR imaging, and psychometric testing on patients with severe sleep apnea before and after treatment with a continuous positive airway pressure device.
3) The Memory and Aging project, in collaboration with Dr. David Bennett and Dr. Aron Buchman. This study will use ambulatory measurements of sleep and rest patterns from more than 1,500 older adults. The researchers will also obtain sleep and cardiovascular measurements from more than1,000 study participants while linking these sleep and circadian data to cognitive outcomes, MR imaging, genotype, genome-scale transcriptome and epigenome data, and postmortem histopathology.

 

Work in the laboratory is funded by grants from the Canadian Institutes of Health Research, the National Institute on Aging, and the Ontario Ministry of Research, Innovation and Science.

The laboratory is looking to take on one or more graduate students at the master’s level through the Institute of Medical Science at U of T, as well as residents or medical students interested in undertaking sleep and circadian rhythm-related research projects, starting in the 2017–2018 academic year. In particular, Dr. Lim is looking for candidates with programming (especially R and MATLAB) and statistics experience, coupled with undergraduate-level knowledge of mathematics, genetics and neurobiology. If interested in applying, then please contact Dr. Lim at andrew.lim@utoronto.ca.

Academic Department

Medicine

Current Project

Current Project

The laboratory is currently recruiting students for 5 specific projects:

1. Genetic Determinants of Human Sleep and Circadian Traits.  Sleep and circadian rhythms affect many aspects of human physiology and performance and impact several chronic diseases.  Strokes, for instance, show a marked circadian variation in onset risk, with a nearly 7-fold increase in the risk of stroke at peak clock times. However despite substantial progress in understanding the genetic regulation of sleep and circadian rhythms in animal systems, our knowledge of the genetic networks regulating human sleep and circadian rhythms is incomplete. There is considerable inter-individual variability in sleep and circadian phenotypes and twin and family-based studies suggest that some sleep and circadian phenotypes are trait-like and partly heritable.  However, genetic association studies using subjective self-report phenotypes have identified relatively few robustly associated gene variants and technical factors have limited the ability to collect quantitative sleep/circadian measures in large cohorts with concomitant genotyping. The overall goal of this study is to identify genetic variants associated with clinically important sleep and circadian phenotypes, to explore potential mechanisms linking these variants with their associated phenotypes, and to apply these findings to the prediction of sleep and circadian phenomena in community-based and clinical populations.  Objective measures of sleep and circadian behavior in the community setting will be derived from the continuous measurement of individuals’ rest-activity patterns for up to 10 days using a wristwatch-like actigraph.  We are leveraging available genomic and transcriptomic data from several complementary existing cohorts – the Rush Memory and Aging Project (MAP), the PhenoGenetic Project (PGP), and the Ontario Health Study (OHS).  We are using a genome-wide association approach to identify gene variants associated with actigraphic sleep and circadian behavior in the MAP and PGP cohorts with validation in the OHS cohort.  We are then test the hypotheses that these associations may be mediated at the molecular level through modulation of gene expression, particularly cis-effects on nearby genes or trans-effects on canonical clock genes.  Identifying novel genetic variants associated with sleep/circadian traits and delineating the mechanisms by which they act will deepen our understanding of the generation and regulation of human sleep and circadian rhythms.  This in turn has the potential to lead to new mechanistically informed treatments and management strategies for shift-work, jet lag, and sleep disruption that have social and medical consequences for millions of Canadians.  Moreover, by facilitating prediction of individual-level sleep and circadian rhythms, this study may facilitate genetic personalization of school, work, travel, medical and other schedules to optimize human performance and clinical outcomes.


2. Sleep, Circadian Rhythms, and Mechanisms of Cognitive Decline in the Human Brain.  
Sleep and circadian disruption, including sleep apnea, sleep fragmentation, and circadian rhythm irregularity, affect millions of Americans, and are associated with impaired cognition and Alzheimer’s disease (AD). Challenges in applying standard techniques (e.g. polysomnography) in ambulatory settings to quantify sleep and circadian disruption in large numbers of community-dwelling older adults, and in obtaining detailed cognitive assessments and brain tissue from the same individuals, have left knowledge gaps. Thus, although sleep and circadian rhythm disruption affect millions of older Americans, there are few data concerning the contribution of their different forms to the growing number of older adults with cognitive impairment and dementia, and associated brain mechanisms. This study is filling fill these gaps. The overall goal of this study is to quantify the contributions of, and identify brain mechanisms linking, sleep and circadian rhythm disruption to cognitive decline and incident AD in older adults. In compelling preliminary work, we developed and applied a new method of measuring sleep fragmentation in the community setting using actigraphy, the non-invasive continuous measurement of movement using a watch-like device. In older adults, we found that higher sleep fragmentation is associated with 1) a greater risk of incident AD, 2) more brain arteriolosclerosis and subcortical strokes at autopsy, and 3) a higher burden of AD pathology in APOE e4 carriers. However, sleep fragmentation is only one type of sleep disruption, and its impact cannot be understood without simultaneously examining the impact of common sleep disorders such as sleep apnea, which may affect up to half of older adults. To extend these findings, we are using a portable battery of 2 wearable devices measuring continuous peripheral arterial tonometry, oximetry, and actigraphy to simultaneously quantify 5 key forms of sleep and circadian disruption in 780 older adults in the Rush Memory and Aging Project (R01AG17911). These will include 1) sleep apnea, 2) sleep duration, 3) sleep architecture, 4) sleep fragmentation, and 5) circadian irregularity. These measurements are being combined with donated cognitive and other clinical data, as well as post-mortem histopathology and brain MRI indices from decedents, to elucidate the brain correlates of sleep and circadian disruption in community-dwelling adults, and their impact on cognitive impairment and incident AD dementia. By overcoming key translational barriers, this study is filling important gaps in our knowledge concerning the burden and brain correlates of 5 key forms of sleep and circadian disruption in old age. This offers the potential to leverage sleep and circadian interventions to decrease the growing burden of cognitive impairment and AD, and for targeted therapies to improve brain health for the millions of Americans who experience sleep or circadian rhythm dysfunction.


3. The Brain Changes in Sleep Apnea Study.  Cerebral small vessel disease (SVD) is a key pathological correlate of dementia and other forms of neurological disability in older adults.  However, an incomplete understanding of the physiological changes leading to SVD in human populations, and in particular a paucity of identifiable treatable risk factors, has impeded the development of clinical programs to prevent SVD and its neurological sequelae.  Recent work in model organisms has suggested that dysfunction of the perivascular space (PVS) may play an important role in the development of SVD and in connecting it to neurological sequelae such as dementia.  In these model organisms, key modulators/regulators of PVS function include slow-wave sleep, sympathetic nervous system activity, and hypoxemia.  Sleep apnea, a disorder characterized by repeated obstruction of the upper airway in sleep leading to hypoxemia, high tonic and phasic sympathetic tone, and loss of slow wave sleep, may be an important modulator of PVS function, and hence risk factor for SVD and its neurological sequelae.  Indeed, sleep apnea is associated with an increased burden of white matter hyperintensities – a marker of SVD cerebrovascular pathology – in community-dwelling adults, and we have shown that sleep fragmentation – a key consequence of sleep apnea – is associated with cerebral arteriolosclerosis at autopsy, and enlarged perivascular spaces on MRI.  Moreover, sleep apnea is common, affecting up to 25% of middle-aged adults and 40% of older adults, and effectively treatable with continuous positive airway pressure (CPAP) leading to resolution of hypoxia, normalization of sleep architecture, and normalization of sympathetic nervous system activity.
The overall purpose of this study is to test the hypothesis that in patients with severe sleep apnea, treatment with 6 months of CPAP will result in improved small vessel, and especially perivascular, function and that these changes will mirror improvements in sleep architecture, nocturnal hypoxemia, nocturnal blood pressure, and phasic sympathetic activity.  Specifically, we hypothesize that 6 months of CPAP will result in decreased perivascular space volume, improved arterial pulsatility, improved endothelial dysfunction as measured by serum biomarkers, improved cerebrovascular reactivity, and improved white matter structure.  We are studying 80 adults attending the sleep clinics at Sunnybrook Health Sciences Centre and the University of Edinburgh.  Participants are undergoing home-based assessment with Health Canada approved wearable devices (24 hours of ambulatory blood pressure monitoring with a portable monitor, 7 days of actigraphy to assess sleep duration and fragmentation, and 1 night of finger-probe peripheral arterial tonometry and oximetry to assess cardiorespiratory physiology including sleep apnea), completion of a sleep and health questionnaire, banking of blood for endothelial biomarkers, cognitive evaluation, and an MRI of the brain, at 2 time points: 1) after initial polysomnographic diagnosis of sleep apnea but before the initiation of CPAP 2) after 6 months of CPAP.  We anticipate that after treatment with CPAP, participants with sleep apnea will show improvements in multiple measures of cerebrovascular biology, that these differences will parallel differences in blood pressure, sympathetic nervous system activity, sleep architecture, and hypoxemia, and that they will be predictive of improvements in cognition. 


4. The Ontario Sleep and Brain Health Study – An Extension of the Ontario Sleep Health Study to Examine the Links Between Sleep and Brain Health in Working-Age Ontarians.  Quantifying the contribution of sleep and circadian disruption to cognitive impairment and dementia in Ontario, and identifying their brain correlates, is a public health priority with important therapeutic implications.  Sleep and circadian disruption, including sleep apnea, sleep deprivation, sleep fragmentation, and circadian disruption from shift work, affect millions of Ontarians and may be contributing to the growing burden of Alzheimer’s disease (AD) and other dementias.  Studies in model organisms and studies in humans suggest that sleep and circadian disruption impair cognition and may predispose to dementia-associated brain damage including accumulation of toxic proteins, brain vessel damage, brain atrophy, and brain white matter injury.  In large studies of older adults, circadian irregularity, sleep fragmentation, and sleep apnea are associated with impaired cognition and AD, suggesting that targeting 1) common treatable causes of sleep or circadian disruption (e.g. sleep apnea), or 2) their brain consequences, may delay or prevent impaired cognition and AD.  However, most studies have focused on older adults, which is problematic since AD-related brain damage appears many years before AD onset.  Moreover, logistical and technological limitations have made it difficult to obtain sleep and circadian measures in large numbers of working-age adults with detailed brain imaging and long-term follow-up.  These factors have left gaps in our knowledge regarding which specific forms of sleep/circadian disruption most affect dementia risk, when in the lifespan they act, and via what mechanisms, impeding strategies to prevent cognitive decline and dementia by targeting sleep and circadian disruption or their brain consequences.  This study is quantifying the contributions of 4 key forms of mid-life sleep and circadian rhythm disruption to cognitive impairment, dementia-associated structural brain changes, and the risk of late-life dementia.  In compelling preliminary work, we have shown that higher late-life sleep fragmentation, measured with a novel metric we developed, is linked to 1) a higher risk of future AD, 2) more brain arteriolosclerosis, 3) a greater impact of genetic factors on AD risk and AD-related brain damage, and 4) smaller frontal lobes on MRI. However, fragmentation is only one type of sleep disruption, and its impact cannot be understood without simultaneously examining common sleep disorders such as sleep apnea.  Moreover, few studies have examined the impact of mid-life sleep or circadian disruption on cognition and dementia-associated brain structural changes.  Leveraging resources from two ongoing Ontario-based cohort studies, we are cost-effectively addressing these gaps by measuring 4 key forms of sleep and circadian disruption in 2400 adults aged 35-69 with wearable devices, and linking these data to cognitive impairment, dementia-associated brain changes, and late life dementia risk.  Our specific aims are:  Aim 1: Determine the burden and severity of a) sleep apnea, b) sleep deprivation, c) sleep fragmentation, and d) circadian irregularity in working-age Ontarians using wearable devices, and examine their impact on cognition and function.  Aim 2: Evaluate the associations of these 4 forms of sleep and circadian disruption with dementia-related brain damage including regional atrophy, white matter hyperintensities, lacunes, cerebral microbleeds, and enlarged perivascular spaces visualized using brain MRI.


5. A framework for hybrid machine and human computation for the accurate and scalable analysis of human clinical EEG recordings.  Electroencephalography (EEG) is a key tool in the diagnosis of epilepsy and sleep disorders. In current practice, EEG recordings are visually analyzed by specialist technicians and physicians. However, this is a slow process and dependent on the availability of these expert annotators. This limits EEG as a diagnostic medical tool in smaller communities. Even in larger centers, the time consuming nature of human EEG analysis can lead to backlogs and significant delays in diagnosis and treatment. Thus, there is a need for rapid, scalable, cost-efficient, accurate EEG interpretation that is not heavily dependent on the time of highly trained specialists. These limitations have motivated efforts to develop fully automated algorithms for the interpretation of human EEG signals. Unfortunately, to date, these approaches have had limited success, in part because many aspects of EEG interpretation are fundamentally image classification problems that while straightforward for trained humans, are difficult to fully automate. The field of human computation developed to address such problems where humans may have some advantages over pure automation. In this paradigm, problems are decomposed into a massive number of very simple, carefully designed, human micro-tasks to be carried out by an array of “human processors,” whose answers can be combined with automated algorithms to solve the original problem. This maximizes the advantages of both humans and computers in one algorithm, overcoming the limitations of either.  The overall goal of this project is to design a framework for hybrid machine and human computation to achieve accurate and scalable analysis of human clinical EEG recordings.  We have established a multi-site collaboration between the University of Waterloo, McGill University, the Clinical Neurophysiology Laboratory at Sunnybrook Health Sciences Centre, and the Epilepsy Program at the University Health Network to achieve the following aims:  Aim 1. Develop a general set of algorithms to decompose EEG analysis into micro-tasks, and integrate the responses of non-expert and expert human processors with automated algorithms to solve EEG-related clinical problems.   Aim 2. Develop a general framework to compare these algorithms against fully automated approaches and specialist analyses, and an iterative approach to improve these algorithms.   Aim 3. Apply the algorithms to the interpretation of clinical EEGs from Canadian hospitals.

 

Research Interests

Theme

Neuroscience / Brain Health

Platforms

Clinical Research, Genetics / Genomics / Proteomics

Keywords

Circadian Rhythms, Sleep, Brain, Cognitive Decline, Dementia, Population Genetics, Parkinson Disease, Stroke, Epigenetics, Seasonal Rhythms