- Email: [email protected]
Sleep and Inflammation: Implications for Domain Approach and Treatment Opportunities
Commentary
Biological Psychiatry
Sleep and Inflammation: Implications for Domain Approach and Treatment Opportunities Roger S. McIntyre Sleep disruption and/or alterations in sleep cycle or quality are identified within the Research Domain Criteria (RDoC) matrix as a transdiagnostic phenomenology (1,2). In addition, sleep disturbances are highly associated with adverse psychiatric and physical health outcomes. Results from epidemiologic and clinical samples, as well as experimental sleep manipulation studies, provide convergent evidence that alterations in sleep are associated with reproducible abnormalities across multiple effector systems relevant to the pathophysiology of psychiatric and medical disorders (3,4). Observations of biological perturbation associated with sleep may inform a broader conceptual framework (i.e., RDoC) as it regards disease modeling in psychiatric and medical disorders. For example, sleep disturbance, and its associated neurobiological alterations, may be relevant to the vulnerability, direct causality, illness propagation, comorbidity, and treatment of psychiatric disorders (Figure 1). Irwin et al. (1) provide an impressive systematic and metaanalytic review of extant studies to investigate the effects of sleep disturbance, duration, and/or experimental deprivation on peripheral proinflammatory markers. Their analysis, inclusive of 72 studies involving more than 50,000 subjects, evaluated the association between sleep disturbance and C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Sleep disturbance was categorically operationalized by symptom reporting, questionnaire, or diagnosis. Sleep duration was assessed as a continuous (i.e., subjectively or objectively) or categorical (i.e., short or long sleep) measure. Commensurate with the National Sleep Foundation’s recommended sleep duration of 7–8 hours for adults, less than 7 hours and greater than 8 hours of sleep were defined as short and long sleep, respectively. Sleep duration was assessed subjectively or objectively. The authors supplemented the review with studies that experimentally manipulated sleep. Sleep disturbance, as assessed by questionnaire, was associated with higher levels of CRP and IL-6. No statistically significant associations between sleep disturbance and TNF-α were observed. In addition, short sleep duration was associated with higher levels of CRP. Long sleep duration was associated with higher levels of IL-6 and CRP but not TNF-α. Partial or total experimental sleep manipulation was not associated with alterations in CRP, IL-6, or TNF-α. Similarly, sleep restriction over several days was not associated with alterations in CRP, IL-6, or TNF-α. The meta-analysis provides unequivocal empirical evidence supporting the association between sleep alteration and immunoinflammatory system activation. Strengths of the analysis are its large number of studies and subjects and the
comprehensive determination and measurement of sleep disruption. The authors note that there may have been some indication for publication bias; notwithstanding, evaluation of data excluding outliers eliminated evidence of publication bias (Egger’s test: p . .20). Translational application of the foregoing analysis to the broader concepts of chronobiology and immunoinflammatory systems is apparent. What is not known, however, is whether individuals participating in the component studies fulfilled diagnostic criteria for psychiatric disorders (e.g., mood, anxiety, or sleep disorders) or medical disorders (e.g., obesity, cardiovascular disease) that are known to be highly associated with sleep disturbance and immunoinflammatory system activation. A robust and compelling body of evidence indicates that innate immunoinflammatory system alterations are etiopathogenically related to the onset of psychiatric and medical
Figure 1. Disturbances in sleep are a critical component of the shared pathogenetic nexus between psychiatric and cardiometabolic disorders.
SEE CORRESPONDING ARTICLE ON PAGE 40
http://dx.doi.org/10.1016/j.biopsych.2016.04.018 ISSN: 0006-3223
9 & 2016 Society of Biological Psychiatry. Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
Biological Psychiatry
Commentary
disorders. For example, preclinical paradigms have well established that experimental provocation of immune systems (e.g., lipopolysaccharide) is associated with behavioral alterations suggestive of anhedonia, social disengagement, cognitive impairment, and sleep disturbance (5). Studies in human subjects also indicate that disturbances in peripheral and/or central proinflammatory markers, as well as alterations in inflammasome or inflammatory genetic architecture, increase risk for psychiatric disorders. In keeping with the RDoC domain-based approach, it is of interest that alterations in immunoinflammatory systems are highly associated with disturbances in general emotionally valenced cognition and in social cognition. Since the introduction of amine-based agents in the mid20th century, a genuinely novel pharmacologic treatment modality has not been discovered and/or developed. The lack of therapeutic progress in brain-based disorders is a consequence of the absence of a consensually agreed on, and empirically supported, disease pathogenic model. There is no evidence that current psychotropic agents are disease modifying. Instead, treatments are more accurately referred to as palliative rather than target-engaging and/or curative. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) field trials reported varying estimates of interobserver agreement across common and/or severe psychiatric disorders. The modest interobserver agreement, along with varying definitions of treatment response, is a critical determinant of suboptimal biomarker/biosignature predictions of response to psychotropic agents. It is axiomatic that if suboptimal agreement exists regarding the diagnostic construct and/or response phenotype, identification of pretreatment biological parameters capable of predicting therapeutic outcomes would be significantly compromised. The foregoing provides the clarion call for supplanting DSM-5–based diagnoses with domain-based categories as a tactic to improve biomarker/biosignature prediction. The RDoC framework provides a heuristic that aims to mitigate the foregoing deficiency by proposing a convergent phenotype with well-established neurobiological substrates. In keeping with this view, sleep disturbance is a replicable phenotype with high interobserver agreement with objective measurement capability. Moreover, the underlying neurobiological substrates subserving and regulating circadian rhythms are well established. Mechanistically, however, the directions of causality linking inflammation and sleep disturbance cannot be sufficiently addressed in the analysis by Irwin et al. For example, are disruptions in sleep cycle or quality a consequence or cause of abnormalities in peripheral proinflammatory cytokines? The association between sleep alteration and inflammation is particularly interesting in light of the robust link between sleep and peripheral inflammatory markers with cardiovascular disease, hypertension, insulin resistance, diabetes mellitus, obesity, and dyslipidemia (3). Individuals with psychiatric disorders are often differentially affected by multiple components of the metabolic syndrome (6). In addition to morbidity, co-occurrence of metabolic syndrome components with mental disorders may affect treatment response and is highly associated with more complicated and severe illness presentation (e.g., suicidality), course, and outcome. Moreover,
10
Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
metabolic syndrome components as well as other emerging risk factors for cardiovascular disease are the principal determinants of increased mortality rates in individuals with mental disorders (6). Co-occurrence of psychiatric and medical disorders (e.g., metabolic syndrome) is due to a clustering of factors across both illness categories and, possibly, a shared pathogenetic nexus. In susceptible individuals, it could be hypothesized that sleep disturbance, and its associated neurobiology, is the linchpin linking these disorders. A testable and viable hypothesis is that among individuals with declared mental disorders and reports of sleep disturbance, preemptive targeting of chronobiological disturbances may decrease risk for concurrent metabolic abnormalities. A separate hypothesis involves the gut microbiota/microbiome and its relevance to psychiatric and metabolic/inflammatory disorders. Available evidence indicates that gut microbes exhibit a discrete circadian clock pattern that may be altered by dietary composition (7). The foregoing observation provides reason to speculate that in susceptible individuals, an innate or acquired disturbance (e.g., by consumption of high-fat diet) in gut microbiota/microbiome may result in alterations in proinflammatory markers and other related systems that are relevant to circadian rhythms and sleep cycles. It is of interest that individuals with chronic fatigue syndrome, a phenotype highly associated with sleep alteration, psychiatric disorders, and metabolic abnormalities, are noted to have high colonization of gram-positive fecal Streptococcus (8). Moreover, the administration of an antimicrobial (i.e., erythromycin) is accompanied by alterations in Streptococcus populations and improvements on sleep. Early-childhood adversity and other social determinants of health are established as distal risk factors for psychiatric and cardiometabolic disorders (e.g., overweight/obesity, cardiovascular disease). Results from epidemiologic and cohort studies indicate that early-childhood adversity is highly associated with abnormal sleep duration and quality in adulthood (9). Interestingly, abnormalities in attachment, which are linked to risk for mental disorders, are also highly associated with activation of the immunoinflammatory system and sleep disturbance (10). The foregoing observations suggest that sleep disturbance may have a heterotypic continuity pattern with later declaration of psychiatric and medical disorders. Taken together, the biology of sleep may be a critical component within the shared pathogenetic nexus linking psychiatric and medical illness. Moreover, sleep disturbance may be an early indicator (and/or cause) of susceptibility to diagnosable psychiatric and medical conditions. Toward the aim of developing preventative and preemptive interventions, a future research vista would be to evaluate whether targeting sleep disturbance mitigates risk in individuals who have yet to declare medical morbidity. For individuals with declared psychiatric and medical disorders, mitigation of sleep abnormalities and the underlying neurobiology may not only be desired for obvious clinical reasons but may also provide opportunity for disease modification. Future vistas targeting sleep alterations and its associated neurobiology may not only involve pharmacologic (e.g., psychotropic agents), psychotherapeutic (e.g., cognitive behavioral therapy), and behavioral (e.g., exercise) interventions but
Biological Psychiatry
Commentary
may also involve dietary manipulation and/or interventions capable of altering gut microbiota/microbiome (e.g., prebiotic, probiotic, antibiotic). Moreover, available agents and/or novel treatments that target the inflammatory system may not only have salutary effects on medical disorders but may improve psychiatric outcomes in part via alterations in sleep chronobiology. It can be reasonably expected that an RDoC approach with particular emphasis further refining the chronobiology of sleep will provide important insights into the pathogenic model of psychiatric and medical comorbidity and provide genuinely novel disease-modifying and possibly curative interventions.
Acknowledgments and Disclosures Within the past 2 years (2014–2016), RSM has received research grant support from Lundbeck, JanssenOrtho, Shire, Purdue, AstraZeneca, Pfizer, Otsuka, Allergan, and Stanley Medical Research Institute (SMRI) and speaker/consultation fees from Lundbeck, Pfizer, AstraZeneca, Eli Lilly, JanssenOrtho, Purdue, Johnson & Johnson, Moksha8, Sunovion, Mitsubishi, Takeda, Forest, Otsuka, Bristol-Myers Squibb, and Shire. The author reports no biomedical financial interests or potential conflicts of interest.
References 1.
2.
3.
4.
5.
6.
7.
8.
Article Information From the Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, Department of Pharmacology, and Institute of Medical Science, University of Toronto, Toronto, Canada. Address correspondence to Roger S. McIntyre, M.D., F.R.C.P.C., University Health Network, 399 Bathurst Street, Toronto, ON, Canada, M5T 2S8; E-mail: [email protected]. Received Apr 25, 2016; revised and accepted Apr 26, 2016.
9.
10.
Irwin MR, Olmstead R, Carroll JE (2016): Sleep disturbance, sleep duration, and inflammation: A systematic review and meta-analysis of cohort studies and experimental sleep deprivation. Biol Psychiatry 80: 40–52. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, et al. (2010): Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. Am J Psychiatry 167: 748–751. Mullington JM, Haack M, Toth M, Serrador JM, Meier-Ewert HK (2009): Cardiovascular, inflammatory, and metabolic consequences of sleep deprivation. Prog Cardiovasc Dis 51:294–302. Czeisler CA, Buxton OM, Khalsa SBS (2005): The human circadian timing system and sleep-wake regulation A2. In: Dement MH, Kryger T, Roth WC, editors. Principles and Practice of Sleep Medicine, 4th ed. Philadelphia: W.B. Saunders, 375–394. Swardfager W, Walter S, Rosenblat JD, Meriem B, McIntyre RS (2016): Mapping inflammation onto mood: Inflammatory mediators of anhedonia. Neurosci Biobehav Rev 64:148–166. Mansur RB, Brietzke E, McIntyre RS (2015): Is there a “metabolicmood syndrome”? A review of the relationship between obesity and mood disorders. Neurosci Biobehav Rev 52:89–104. Kohsaka A, Akira K, Laposky AD, Ramsey KM, Carmela E, Corinne J, et al. (2007): High-fat diet disrupts behavioral and molecular circadian rhythms in mice. Cell Metab 6:414–421. Jackson ML, Butt H, Ball M, Lewis DP, Bruck D (2015): Sleep quality and the treatment of intestinal microbiota imbalance in chronic fatigue syndrome: A pilot study. Sleep Sci 8:124–133. Kajeepeta S, Gelaye B, Jackson CL, Williams MA (2015): Adverse childhood experiences are associated with adult sleep disorders: a systematic review. Sleep Med 16:320–330. Pennestri M-H, Marie-Hélène P, Ellen M, Katherine O, Vanessa L, Andrée-Anne B-T, et al. (2014): Establishment and consolidation of the sleep-wake cycle as a function of attachment pattern. Attach Hum Dev 17:23–42.
Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
11
Biological Psychiatry
Sleep and Inflammation: Implications for Domain Approach and Treatment Opportunities Roger S. McIntyre Sleep disruption and/or alterations in sleep cycle or quality are identified within the Research Domain Criteria (RDoC) matrix as a transdiagnostic phenomenology (1,2). In addition, sleep disturbances are highly associated with adverse psychiatric and physical health outcomes. Results from epidemiologic and clinical samples, as well as experimental sleep manipulation studies, provide convergent evidence that alterations in sleep are associated with reproducible abnormalities across multiple effector systems relevant to the pathophysiology of psychiatric and medical disorders (3,4). Observations of biological perturbation associated with sleep may inform a broader conceptual framework (i.e., RDoC) as it regards disease modeling in psychiatric and medical disorders. For example, sleep disturbance, and its associated neurobiological alterations, may be relevant to the vulnerability, direct causality, illness propagation, comorbidity, and treatment of psychiatric disorders (Figure 1). Irwin et al. (1) provide an impressive systematic and metaanalytic review of extant studies to investigate the effects of sleep disturbance, duration, and/or experimental deprivation on peripheral proinflammatory markers. Their analysis, inclusive of 72 studies involving more than 50,000 subjects, evaluated the association between sleep disturbance and C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Sleep disturbance was categorically operationalized by symptom reporting, questionnaire, or diagnosis. Sleep duration was assessed as a continuous (i.e., subjectively or objectively) or categorical (i.e., short or long sleep) measure. Commensurate with the National Sleep Foundation’s recommended sleep duration of 7–8 hours for adults, less than 7 hours and greater than 8 hours of sleep were defined as short and long sleep, respectively. Sleep duration was assessed subjectively or objectively. The authors supplemented the review with studies that experimentally manipulated sleep. Sleep disturbance, as assessed by questionnaire, was associated with higher levels of CRP and IL-6. No statistically significant associations between sleep disturbance and TNF-α were observed. In addition, short sleep duration was associated with higher levels of CRP. Long sleep duration was associated with higher levels of IL-6 and CRP but not TNF-α. Partial or total experimental sleep manipulation was not associated with alterations in CRP, IL-6, or TNF-α. Similarly, sleep restriction over several days was not associated with alterations in CRP, IL-6, or TNF-α. The meta-analysis provides unequivocal empirical evidence supporting the association between sleep alteration and immunoinflammatory system activation. Strengths of the analysis are its large number of studies and subjects and the
comprehensive determination and measurement of sleep disruption. The authors note that there may have been some indication for publication bias; notwithstanding, evaluation of data excluding outliers eliminated evidence of publication bias (Egger’s test: p . .20). Translational application of the foregoing analysis to the broader concepts of chronobiology and immunoinflammatory systems is apparent. What is not known, however, is whether individuals participating in the component studies fulfilled diagnostic criteria for psychiatric disorders (e.g., mood, anxiety, or sleep disorders) or medical disorders (e.g., obesity, cardiovascular disease) that are known to be highly associated with sleep disturbance and immunoinflammatory system activation. A robust and compelling body of evidence indicates that innate immunoinflammatory system alterations are etiopathogenically related to the onset of psychiatric and medical
Figure 1. Disturbances in sleep are a critical component of the shared pathogenetic nexus between psychiatric and cardiometabolic disorders.
SEE CORRESPONDING ARTICLE ON PAGE 40
http://dx.doi.org/10.1016/j.biopsych.2016.04.018 ISSN: 0006-3223
9 & 2016 Society of Biological Psychiatry. Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
Biological Psychiatry
Commentary
disorders. For example, preclinical paradigms have well established that experimental provocation of immune systems (e.g., lipopolysaccharide) is associated with behavioral alterations suggestive of anhedonia, social disengagement, cognitive impairment, and sleep disturbance (5). Studies in human subjects also indicate that disturbances in peripheral and/or central proinflammatory markers, as well as alterations in inflammasome or inflammatory genetic architecture, increase risk for psychiatric disorders. In keeping with the RDoC domain-based approach, it is of interest that alterations in immunoinflammatory systems are highly associated with disturbances in general emotionally valenced cognition and in social cognition. Since the introduction of amine-based agents in the mid20th century, a genuinely novel pharmacologic treatment modality has not been discovered and/or developed. The lack of therapeutic progress in brain-based disorders is a consequence of the absence of a consensually agreed on, and empirically supported, disease pathogenic model. There is no evidence that current psychotropic agents are disease modifying. Instead, treatments are more accurately referred to as palliative rather than target-engaging and/or curative. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) field trials reported varying estimates of interobserver agreement across common and/or severe psychiatric disorders. The modest interobserver agreement, along with varying definitions of treatment response, is a critical determinant of suboptimal biomarker/biosignature predictions of response to psychotropic agents. It is axiomatic that if suboptimal agreement exists regarding the diagnostic construct and/or response phenotype, identification of pretreatment biological parameters capable of predicting therapeutic outcomes would be significantly compromised. The foregoing provides the clarion call for supplanting DSM-5–based diagnoses with domain-based categories as a tactic to improve biomarker/biosignature prediction. The RDoC framework provides a heuristic that aims to mitigate the foregoing deficiency by proposing a convergent phenotype with well-established neurobiological substrates. In keeping with this view, sleep disturbance is a replicable phenotype with high interobserver agreement with objective measurement capability. Moreover, the underlying neurobiological substrates subserving and regulating circadian rhythms are well established. Mechanistically, however, the directions of causality linking inflammation and sleep disturbance cannot be sufficiently addressed in the analysis by Irwin et al. For example, are disruptions in sleep cycle or quality a consequence or cause of abnormalities in peripheral proinflammatory cytokines? The association between sleep alteration and inflammation is particularly interesting in light of the robust link between sleep and peripheral inflammatory markers with cardiovascular disease, hypertension, insulin resistance, diabetes mellitus, obesity, and dyslipidemia (3). Individuals with psychiatric disorders are often differentially affected by multiple components of the metabolic syndrome (6). In addition to morbidity, co-occurrence of metabolic syndrome components with mental disorders may affect treatment response and is highly associated with more complicated and severe illness presentation (e.g., suicidality), course, and outcome. Moreover,
10
Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
metabolic syndrome components as well as other emerging risk factors for cardiovascular disease are the principal determinants of increased mortality rates in individuals with mental disorders (6). Co-occurrence of psychiatric and medical disorders (e.g., metabolic syndrome) is due to a clustering of factors across both illness categories and, possibly, a shared pathogenetic nexus. In susceptible individuals, it could be hypothesized that sleep disturbance, and its associated neurobiology, is the linchpin linking these disorders. A testable and viable hypothesis is that among individuals with declared mental disorders and reports of sleep disturbance, preemptive targeting of chronobiological disturbances may decrease risk for concurrent metabolic abnormalities. A separate hypothesis involves the gut microbiota/microbiome and its relevance to psychiatric and metabolic/inflammatory disorders. Available evidence indicates that gut microbes exhibit a discrete circadian clock pattern that may be altered by dietary composition (7). The foregoing observation provides reason to speculate that in susceptible individuals, an innate or acquired disturbance (e.g., by consumption of high-fat diet) in gut microbiota/microbiome may result in alterations in proinflammatory markers and other related systems that are relevant to circadian rhythms and sleep cycles. It is of interest that individuals with chronic fatigue syndrome, a phenotype highly associated with sleep alteration, psychiatric disorders, and metabolic abnormalities, are noted to have high colonization of gram-positive fecal Streptococcus (8). Moreover, the administration of an antimicrobial (i.e., erythromycin) is accompanied by alterations in Streptococcus populations and improvements on sleep. Early-childhood adversity and other social determinants of health are established as distal risk factors for psychiatric and cardiometabolic disorders (e.g., overweight/obesity, cardiovascular disease). Results from epidemiologic and cohort studies indicate that early-childhood adversity is highly associated with abnormal sleep duration and quality in adulthood (9). Interestingly, abnormalities in attachment, which are linked to risk for mental disorders, are also highly associated with activation of the immunoinflammatory system and sleep disturbance (10). The foregoing observations suggest that sleep disturbance may have a heterotypic continuity pattern with later declaration of psychiatric and medical disorders. Taken together, the biology of sleep may be a critical component within the shared pathogenetic nexus linking psychiatric and medical illness. Moreover, sleep disturbance may be an early indicator (and/or cause) of susceptibility to diagnosable psychiatric and medical conditions. Toward the aim of developing preventative and preemptive interventions, a future research vista would be to evaluate whether targeting sleep disturbance mitigates risk in individuals who have yet to declare medical morbidity. For individuals with declared psychiatric and medical disorders, mitigation of sleep abnormalities and the underlying neurobiology may not only be desired for obvious clinical reasons but may also provide opportunity for disease modification. Future vistas targeting sleep alterations and its associated neurobiology may not only involve pharmacologic (e.g., psychotropic agents), psychotherapeutic (e.g., cognitive behavioral therapy), and behavioral (e.g., exercise) interventions but
Biological Psychiatry
Commentary
may also involve dietary manipulation and/or interventions capable of altering gut microbiota/microbiome (e.g., prebiotic, probiotic, antibiotic). Moreover, available agents and/or novel treatments that target the inflammatory system may not only have salutary effects on medical disorders but may improve psychiatric outcomes in part via alterations in sleep chronobiology. It can be reasonably expected that an RDoC approach with particular emphasis further refining the chronobiology of sleep will provide important insights into the pathogenic model of psychiatric and medical comorbidity and provide genuinely novel disease-modifying and possibly curative interventions.
Acknowledgments and Disclosures Within the past 2 years (2014–2016), RSM has received research grant support from Lundbeck, JanssenOrtho, Shire, Purdue, AstraZeneca, Pfizer, Otsuka, Allergan, and Stanley Medical Research Institute (SMRI) and speaker/consultation fees from Lundbeck, Pfizer, AstraZeneca, Eli Lilly, JanssenOrtho, Purdue, Johnson & Johnson, Moksha8, Sunovion, Mitsubishi, Takeda, Forest, Otsuka, Bristol-Myers Squibb, and Shire. The author reports no biomedical financial interests or potential conflicts of interest.
References 1.
2.
3.
4.
5.
6.
7.
8.
Article Information From the Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, Department of Pharmacology, and Institute of Medical Science, University of Toronto, Toronto, Canada. Address correspondence to Roger S. McIntyre, M.D., F.R.C.P.C., University Health Network, 399 Bathurst Street, Toronto, ON, Canada, M5T 2S8; E-mail: [email protected]. Received Apr 25, 2016; revised and accepted Apr 26, 2016.
9.
10.
Irwin MR, Olmstead R, Carroll JE (2016): Sleep disturbance, sleep duration, and inflammation: A systematic review and meta-analysis of cohort studies and experimental sleep deprivation. Biol Psychiatry 80: 40–52. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K, et al. (2010): Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. Am J Psychiatry 167: 748–751. Mullington JM, Haack M, Toth M, Serrador JM, Meier-Ewert HK (2009): Cardiovascular, inflammatory, and metabolic consequences of sleep deprivation. Prog Cardiovasc Dis 51:294–302. Czeisler CA, Buxton OM, Khalsa SBS (2005): The human circadian timing system and sleep-wake regulation A2. In: Dement MH, Kryger T, Roth WC, editors. Principles and Practice of Sleep Medicine, 4th ed. Philadelphia: W.B. Saunders, 375–394. Swardfager W, Walter S, Rosenblat JD, Meriem B, McIntyre RS (2016): Mapping inflammation onto mood: Inflammatory mediators of anhedonia. Neurosci Biobehav Rev 64:148–166. Mansur RB, Brietzke E, McIntyre RS (2015): Is there a “metabolicmood syndrome”? A review of the relationship between obesity and mood disorders. Neurosci Biobehav Rev 52:89–104. Kohsaka A, Akira K, Laposky AD, Ramsey KM, Carmela E, Corinne J, et al. (2007): High-fat diet disrupts behavioral and molecular circadian rhythms in mice. Cell Metab 6:414–421. Jackson ML, Butt H, Ball M, Lewis DP, Bruck D (2015): Sleep quality and the treatment of intestinal microbiota imbalance in chronic fatigue syndrome: A pilot study. Sleep Sci 8:124–133. Kajeepeta S, Gelaye B, Jackson CL, Williams MA (2015): Adverse childhood experiences are associated with adult sleep disorders: a systematic review. Sleep Med 16:320–330. Pennestri M-H, Marie-Hélène P, Ellen M, Katherine O, Vanessa L, Andrée-Anne B-T, et al. (2014): Establishment and consolidation of the sleep-wake cycle as a function of attachment pattern. Attach Hum Dev 17:23–42.
Biological Psychiatry July 1, 2016; 80:9–11 www.sobp.org/journal
11