Individual Differences in Executive (Dys)function in Relation to Sleep Duration and Psychopathology

This dissertation presents four studies that examined how executive functions (EFs) relate to problematic behaviors, such as psychopathology and atypical sleep, as well as how EFs are characterized in healthy individuals. The first study examined whether genetic risk for five different forms of psychopathology predicted EFs at the latent variable level in a population sample. The second study characterized the neural activation patterns in health individuals in response to 3 different types of EF tasks. This study (a) assessed the overlapping activation elicited across the different EF task types, and (b) used neural activation to predict high or low EF ability. The third study examined whether individual differences in sleep duration influenced either depression or EFs (a) within a single time of assessment, (b) across time, and (c) how sleep duration, depression, and EFs influence each other in the same model. Study 4 decomposed the relationships of sleep duration with depression and then EF into their genetic and environmental factors in order to better understand the underlying architecture for these relationships. In the first study, publically available datasets from the Psychiatric Genomics Consortia were used to generate polygenic risk scores for 5 different psychiatric disorders: Autism, Attention Deficit Hyperactivity Disorder (ADHD), Bipolar Disorder, Major Depressive Disorder (MDD), and Schizophrenia. I then used a deeply phenotyped (and genotyped) subset of 354 twins in the Colorado Longitudinal Twin Study (LTS) from the University of Colorado Boulder to test whether or not genetic risk in these individuals predicted EF abilities. I also examined whether the appropriate risk scores were associated with ADHD and MDD symptoms or lifetime diagnoses to the same relative extent as the EF scores. Results indicated polygenic risk for psychopathology did not significantly predict EFs after controlling for multiple testing. Results also suggested that effect sizes for EFs were comparable to those for ADHD and MDD symptoms and lifetime diagnoses. The second study was a pilot study that included 30 subjects from the Colorado Twin Study from the University of Colorado Boulder at approximately age 28. These subjects were chosen because they were either high or low in Common EF ability as measured in a previous wave of data collection 7 years prior, until we had 15 of each. Each subject completed 3 EF tasks in a functional magnetic resonance imaging scanner. Results indicated that common brain activation in response to these tasks both overlapped with a frontoparietal network typically associated with cognitive tasks, and extended beyond this network. The common areas associated with individual differences in EF ability fell outside of the frontoparietal network. The third and fourth studies utilized data from the same group of 857 twins from the LTS sample. These studies examined sleep, depression, and EF when available at approximately ages 12, 17, 21, and 23. Study three looked at the phenotypic relationships between these variables and found linear and nonlinear relationships between sleep duration and EFs and depression across age. When put together in the same model, depression seems to suppress the relationship between EF and sleep duration in adolescence. Study four results showed that sleep duration is moderately heritable, and that the phenotypic relationships between these variables is typically attributable to non-shared environmental influences

Overnight changes in waking auditory evoked potential amplitude reflect altered sleep homeostasis in major depression

Objective: Sleep homeostasis is altered in major depressive disorder (MDD). Pre- to postsleep decline in waking auditory evoked potential (AEP) amplitude has been correlated with sleep slow wave activity (SWA), suggesting that overnight changes in waking AEP amplitude are homeostatically regulated in healthy individuals. This study investigated whether the overnight change in waking AEP amplitude and its relation to SWA is altered in MDD. Method: Using 256-channel high-density electroencephalography, all-night sleep polysomnography and single-tone waking AEPs pre- and postsleep were collected in 15 healthy controls (HC) and 15 non-medicated individuals with MDD. Results: N1 and P2 amplitudes of the waking AEP declined after sleep in the HC group, but not in MDD. The reduction in N1 amplitude also correlated with fronto-central SWA in the HC group, but a comparable relationship was not found in MDD, despite equivalent SWA between groups. No pre- to postsleep differences were found for N1 or P2 latencies in either group. These findings were not confounded by varying levels of alertness or differences in sleep variables between groups. Conclusion: MDD involves altered sleep homeostasis as measured by the overnight change in waking AEP amplitude. Future research is required to determine the clinical implications of these findings

Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry

Introduction: Heritability estimates of nicotine dependence (ND) range from 40% to 70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction. Methods: We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, mu(age) = 40.08 [s.d. = 10.43]) and 3061 individuals from a nationally-representative sample with Fagerstrom Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day [CPD], the Alcohol Use Disorders Identification Test [AUDIT-Consumption and AUDIT-Problems], Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index [BMI], and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components. Results: The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (beta = -0.125; 95% CI: [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited. Conclusions: Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.Peer reviewe

Multi-omic and multi-species meta-analyses of nicotine consumption.

Cross-species translational approaches to human genomic analyses are lacking. The present study uses an integrative framework to investigate how genes associated with nicotine use in model organisms contribute to the genetic architecture of human tobacco consumption. First, we created a model organism geneset by collecting results from five animal models of nicotine exposure (RNA expression changes in brain) and then tested the relevance of these genes and flanking genetic variation using genetic data from human cigarettes per day (UK BioBank N = 123,844; all European Ancestry). We tested three hypotheses: (1) DNA variation in, or around, the \u27model organism geneset\u27 will contribute to the heritability to human tobacco consumption, (2) that the model organism genes will be enriched for genes associated with human tobacco consumption, and (3) that a polygenic score based off our model organism geneset will predict tobacco consumption in the AddHealth sample (N = 1667; all European Ancestry). Our results suggested that: (1) model organism genes accounted for ~5-36% of the observed SNP-heritability in human tobacco consumption (enrichment: 1.60-31.45), (2) model organism genes, but not negative control genes, were enriched for the gene-based associations (MAGMA, H-MAGMA, SMultiXcan) for human cigarettes per day, and (3) polygenic scores based on our model organism geneset predicted cigarettes per day in an independent sample. Altogether, these findings highlight the advantages of using multiple species evidence to isolate genetic factors to better understand the etiological complexity of tobacco and other nicotine consumption

The Relationship Between Resting State Network Connectivity and Individual Differences in Executive Functions

The brain is organized into a number of large networks based on shared function, for example, high-level cognitive functions (frontoparietal network), attentional capabilities (dorsal and ventral attention networks), and internal mentation (default network). The correlations of these networks during resting-state fMRI scans varies across individuals and is an indicator of individual differences in ability. Prior work shows higher cognitive functioning (as measured by working memory and attention tasks) is associated with stronger negative correlations between frontoparietal/attention and default networks, suggesting that increased ability may depend upon the diverging activation of networks with contrasting function. However, these prior studies lack specificity with regard to the higher-level cognitive functions involved, particularly with regards to separable components of executive function (EF). Here we decompose EF into three factors from the unity/diversity model of EFs: Common EF, Shifting-specific EF, and Updating-specific EF, measuring each via factor scores derived from a battery of behavioral tasks completed by 250 adult participants (age 28) at the time of a resting-state scan. We found the hypothesized segregated pattern only for Shifting-specific EF. Specifically, after accounting for one’s general EF ability (Common EF), individuals better able to fluidly switch between task sets have a stronger negative correlation between the ventral attention network and the default network. We also report non-predicted novel findings in that individuals with higher Shifting-specific abilities exhibited more positive connectivity between frontoparietal and visual networks, while those individuals with higher Common EF exhibited increased connectivity between sensory and default networks. Overall, these results reveal a new degree of specificity with regard to connectivity/EF relationships

Never Resting Brain: Simultaneous Representation of Two Alpha Related Processes in Humans

Brain activity is continuously modulated, even at “rest”. The alpha rhythm (8–12 Hz) has been known as the hallmark of the brain's idle-state. However, it is still debated if the alpha rhythm reflects synchronization in a distributed network or focal generator and whether it occurs spontaneously or is driven by a stimulus. This EEG/fMRI study aimed to explore the source of alpha modulations and their distribution in the resting brain. By serendipity, while computing the individually defined power modulations of the alpha-band, two simultaneously occurring components of these modulations were found. An ‘induced alpha’ that was correlated with the paradigm (eyes open/ eyes closed), and a ‘spontaneous alpha’ that was on-going and unrelated to the paradigm. These alpha components when used as regressors for BOLD activation revealed two segregated activation maps: the ‘induced map’ included left lateral temporal cortical regions and the hippocampus; the ‘spontaneous map’ included prefrontal cortical regions and the thalamus. Our combined fMRI/EEG approach allowed to computationally untangle two parallel patterns of alpha modulations and underpin their anatomical basis in the human brain. These findings suggest that the human alpha rhythm represents at least two simultaneously occurring processes which characterize the ‘resting brain’; one is related to expected change in sensory information, while the other is endogenous and independent of stimulus change

Sleep disturbances in an arctic population: The Tromsø Study

<p>Abstract</p> <p>Background</p> <p>Prevalence estimates for insomnia range from 10 to 50% in the adult general population. Sleep disturbances cause great impairment in quality of life, which might even rival or exceed the impairment in other chronic medical disorders. The economic implications and use of health-care services related to chronic insomnia represent a clinical concern as well as a pronounced public health problem. Hypnotics are frequently prescribed for insomnia, but alcohol and over-the-counter sleep aids seem to be more widely used by insomniacs than prescription medications. Despite the complex relationship between insomnia and physical and mental health factors, the condition appears to be underrecognized and undertreated by health care providers, probably due to the generally limited knowledge of the causes and natural development of insomnia.</p> <p>Methods/Design</p> <p>The Tromsø Study is an ongoing population-based cohort study with five previous health studies undertaken between 1974 and 2001. This protocol outlines a planned study within the sixth Tromsø Study (Tromsø VI), aiming at; 1) describing sleep patterns in a community-based sample representative of the general population of northern Norway, and 2) examining outcome variables of sleep disturbances against possible explanatory and confounding variables, both within a cross-sectional approach, as well as retrospectively in a longitudinal study – exploring sleep patterns in subjects who have attended two or more of the previous Tromsø studies between 1974 and 2009. First, we plan to perform a simple screening in order to identify those participants with probable sleep disturbances, and secondly to investigate these sleep disturbances further, using an extensive sleep-questionnaire. We will also collect biological explanatory variables, i.e. blood samples, weight, height and blood pressure. We plan to merge data on an individual level from the Tromsø VI Study with data from the Norwegian Prescription Database (NorPD), which is a national registry including data for all prescription drugs issued at Norwegian pharmacies. Participants with sleep disturbances will be compared with pair-matched controls without sleep disturbances.</p> <p>Discussion</p> <p>Despite ongoing research, many challenges remain in the characterization of sleep disturbances and its correlates. Future mapping of the biological dimensions, natural history, as well as the behavioral and drug-related aspects of sleep disturbances in a representative population samples is clearly needed.</p

Conditional corticotropin-releasing hormone overexpression in the mouse forebrain enhances rapid eye movement sleep

Impaired sleep and enhanced stress hormone secretion are the hallmarks of stress-related disorders, including major depression. The central neuropeptide, corticotropin-releasing hormone (CRH), is a key hormone that regulates humoral and behavioral adaptation to stress. Its prolonged hypersecretion is believed to play a key role in the development and course of depressive symptoms, and is associated with sleep impairment. To investigate the specific effects of central CRH overexpression on sleep, we used conditional mouse mutants that overexpress CRH in the entire central nervous system (CRH-COE-Nes) or only in the forebrain, including limbic structures (CRH-COE-Cam). Compared with wild-type or control mice during baseline, both homozygous CRH-COE-Nes and -Cam mice showed constantly increased rapid eye movement (REM) sleep, whereas slightly suppressed non-REM sleep was detected only in CRH-COE-Nes mice during the light period. In response to 6-h sleep deprivation, elevated levels of REM sleep also became evident in heterozygous CRH-COE-Nes and -Cam mice during recovery, which was reversed by treatment with a CRH receptor type 1 (CRHR1) antagonist in heterozygous and homozygous CRH-COE-Nes mice. The peripheral stress hormone levels were not elevated at baseline, and even after sleep deprivation they were indistinguishable across genotypes. As the stress axis was not altered, sleep changes, in particular enhanced REM sleep, occurring in these models are most likely induced by the forebrain CRH through the activation of CRHR1. CRH hypersecretion in the forebrain seems to drive REM sleep, supporting the notion that enhanced REM sleep may serve as biomarker for clinical conditions associated with enhanced CRH secretion

Insomnia and its correlates in a representative sample of the Greek population

<p>Abstract</p> <p>Background</p> <p>Insomnia is a major public health concern affecting about 10% of the general population in its chronic form. Furthermore, epidemiological surveys demonstrate that poor sleep and sleep dissatisfaction are even more frequent problems (10-48%) in the community. This is the first report on the prevalence of insomnia in Greece, a southeastern European country which differs in several socio-cultural and climatic aspects from the rest of European Community members. Data obtained from a national household survey (n = 1005) were used to assess the relationship between insomnia symptoms and a variety of sociodemographic variables, life habits, and health-related factors.</p> <p>Methods</p> <p>A self-administered questionnaire with questions pertaining to general health and related issues was given to the participants. The Short Form-36 (Mental Health subscale), the Athens Insomnia Scale (AIS) as a measure of insomnia-related symptoms, and the International Physical Activity Questionnaire (IPAQ) were also used for the assessment.</p> <p>Results</p> <p>The prevalence of insomnia in the total sample was 25.3% (n = 254); insomnia was more frequent in women than men (30.7% vs. 19.5%) and increased with age. Multiple regression analysis revealed a significant association of insomnia with low socio-economical status and educational level, physical inactivity, existence of a chronic physical or mental disease and increased number of hospitalizations in the previous year.</p> <p>Conclusions</p> <p>The present study confirms most findings reported from other developed countries around the world regarding the high prevalence of insomnia problems in the general population and their association with several sociodemographic and health-related predisposing factors. These results further indicate the need for more active interventions on the part of physicians who should suspect and specifically ask about such symptoms.</p

Uncovering the Genetic Landscape for Multiple Sleep-Wake Traits

Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL) analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28) QTL affected a particular sleep-wake trait (e.g., amount of wake) across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts), as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency). Construction of a Bayesian network for sleep-wake traits and loci led to the identification of sub-networks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits and emphasize the need for a systems biology approach for elucidating the full extent of the genetic regulatory mechanisms of this complex and universal behavior