Review articleNeuroimaging insights into the link between depression and Insomnia: A systematic review
Introduction
Major Depressive Disorder (MDD) is an important cause of disability in the human population (American Psychiatric Association, 2013), also considered as one of the most common severe psychiatric disorders (Kessler et al., 2007, Waraich et al., 2004). According to the World Health Organization (WHO), 25% of the general population present symptoms consistent with a depressive episode at some time in their lives (Lepine and Briley, 2011). Based on Diagnostic and Statistical Manual of Mental Disorders-fifth edition (DSM-5), MDD is characterized by depressed mood, decreased or loss of pleasure, reduced or increased craving for food, loss of energy, psychomotor agitation or retardation, and changes in sleep profile (American Psychiatric Association, 2013). Several studies indicated that sleep problems are present in patients with MDD (Khazaie et al., 2013, Park et al., 2013, Soehner et al., 2014, Tsuno et al., 2005). Interestingly, 40% of MDD patients report insomnia symptoms before appearance of a depressive episode, and 22% report to have simultaneous occurrence of depressive symptoms with insomnia (Ohayon and Roth, 2003).
Insomnia is defined by complaints of initiating or maintaining sleep, which is associated with subjective distress and functional impairment during daytime (Morin et al., 2015). Importantly, insomnia is not only a frequent symptom of various psychiatric disorders (Emamian et al., 2019, Hung et al., 2018, Khazaie et al., 2013, Morin et al., 2015, Okun, 2016, Tahmasian et al., 2017), but also an important risk factor for the development of depression (Baglioni et al., 2011, Emamian et al., 2019). Individuals suffering from insomnia compared to individuals without insomnia are nearly twice as likely to develop depression in future (Baglioni et al., 2011, Franzen and Buysse, 2008, Perlis et al., 2006). Indeed, different symptoms of insomnia such as daytime fatigue, sleep maintenance problems, light sleep, and also early morning awakenings are typical sleep disturbances in MDD (Franzen and Buysse, 2008). Although to date, a causal relationship between insomnia and depression has not been confirmed, insomnia has been underscored as a significant contributor of disability due to MDD (Baglioni et al., 2011, Thase, 2006). It has also been suggested that abnormal emotional reactivity modulates the relationship between insomnia and depression (Baglioni et al., 2010).
There is also a strong genetic correlation between insomnia and depressive symptoms (Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, 2013, Stein et al., 2018). Recent Genome-wide association studies observed a strong link between insomnia and major depression (Hammerschlag et al., 2017, Jansen et al., 2018, Lane et al., 2018, Stein et al., 2018). In particular, the GWAS studies in insomnia suggested possible involvement of a few cortical and subcortical areas including the caudate nucleus and Brodmann areas 9 and 24, striatum, claustrum, and hypothalamus, where gene expression profiles show above-chance resemblance to the genetic risk profile of insomnia disorder (Jansen et al., 2018). Additionally, volume of hippocampus and MDD share similar genetic variants (Wigmore et al., 2017). Structural and functional changes in hippocampus and amygdala have been demonstrated in both insomnia and MDD (Baglioni et al., 2014, Joo et al., 2014, Riemann et al., 2007, Tahmasian et al., 2013). However, two separate neuroimaging meta-analyses on MDD and insomnia disorder suggested inconsistency of structural atrophy and functional impairments across previous studies (Muller et al., 2017, Tahmasian et al., 2018).
Recently, neuroimaging technology has opened a unique opportunity to evaluate different functional, molecular and neurochemical processes in the brain and to study their interaction in vivo, particularly in depression and insomnia, which has had a great impact on understanding their pathophysiology (Desseilles et al., 2008, Desseilles et al., 2011, Kambeitz et al., 2017, Khazaie et al., 2017, Muller et al., 2017, Spiegelhalder et al., 2015). However, few neuroimaging studies have directly investigated the link between MDD and insomnia. The present review provides an overview of existing studies pertaining to the neuroimaging link between insomnia and depression. Through the lenses of various neuroimaging techniques, we particularly provide a general view to extend our understanding of the neurocognitive association between depression and insomnia with a synthesis of the blueprint findings of their shared pathophysiology. Thus, we have divided relevant studies by using specific neuroimaging tools, including single-photon emission computed tomography (SPECT), positron emission tomography (PET), structural magnetic resonance imaging (sMRI), functional MRI (fMRI), magnetic resonance spectroscopy (MRS), and near-infrared spectroscopy (NIRS). For each section, we first provide a brief introduction of the special neuroimaging modality used in each study, and subsequently discuss the contribution of previous observations in the context of a shared network model, which could explain the mechanism underlying the link between MDD and insomnia. These studies included seven cross-sectional and one longitudinal study.
Section snippets
Search strategy
Our search strategy was based on the preferred reporting items for systematic reviews and meta-analyses statement “PRISMA” (Moher et al., 2009). The search was conducted using PubMed, EMBASE and Scopus in June 2018, and reference tracking of identified papers and reviews. The keywords were insomnia AND (depress* OR "major depressive disorder" OR MDD) AND (sMRI OR “structural MRI’ OR “structural magnetic resonance imaging” OR fMRI OR "functional MRI" OR "functional magnetic resonance imaging" OR
MRI studies
MRI is a non-invasive imaging method with high spatial resolution without using ionizing radiation (Hirsch et al., 2015). The brain's tissues can be visualized based on high-quality three-dimensional MRI images (Bunge and Kahn, 2009). In particular, sMRI is well suited technique to visualize and analyze the anatomical properties and abnormalities in the brain (Hirsch et al., 2015). VBM is a measurement based on T1-weighted MRI images, which has been broadly used to quantify volume of cortical
PET and SPECT studies
During the past decades, PET and SPECT provided clues to the etiology of neuropsychiatric disorders like MDD (Hamilton et al., 2012) and insomnia (Spiegelhalder et al., 2015). PET is a nuclear imaging technique, which relies on radiotracers to provide 3D images of tissue function (Rahmim and Zaidi, 2008), with few advantages compared to fMRI. For example, PET is 1) immune to the loss of signal at air-tissue interfaces, 2) has scanning environment that is less acoustically disturbing than the
MRS studies
In-vivo MRS is another non-invasive technique that is used to track metabolic activity in the brain. To date, MRS has played a significant role in diagnosing and monitoring patients with metabolic disorders (Ross and Bluml, 2001) by using hydrogen proton (1H) signals to measure biochemical changes in the brain (Jansen et al., 2006). Previous 1H-MRS studies on patients with MDD revealed a reduction of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the PFC and ACC (Bhagwagar
NIRS study
NIRS, yet another noninvasive functional neuroimaging technique uses non-ionizing light to assess spatiotemporal features of brain activity (Boas et al., 2004, Strangman et al., 2002). NIRS allows monitoring of blood flow in the brain by measuring near-infrared light changes. This technique measures regional cerebral blood volume by assessing oxyhemoglobin (oxy-Hb) and deoxyhemoglobin (deoxy-Hb) with a high temporal resolution. Oxy-Hb and deoxy-Hb reflect regional cerebral blood volume changes
Neuroimaging findings in various MDD subtypes
Different subtypes and modifiers of depression are specifically defined by a set of clinical features with response to distinctive treatment strategies. Beside clinical features, theories on biological markers such as monoamine systems and brain connectivity networks may help to improve identification of such subtypes. For instance, evidence shows that slow wave activity in the first cycle of sleep is more commonly decreased in atypical depression than melancholic depression (Peterson and
The monoamine system impairment in depression and insomnia
Considering dysfunction of the monoamine systems in MDD, the serotoninergic system also takes part in regulating sleep and wakefulness cycle. For example, one PET imaging study of MDD patients investigated the serotonin 1A receptor (5-HT1A) binding potential (Hirvonen et al., 2008). Interestingly, although the binding potential was not associated with overall depression severity, patients with lower binding potential were more likely to experience insomnia. This inverse association was stronger
Dysfunction of intrinsic brain networks in depression and insomnia
A recent study using 1017 participants from the Human Connectome Project demonstrated that both subjective insomnia symptoms and depressive problems scores are linked with higher functional connectivity between several brain regions including lateral orbitofrontal cortex, dorsolateral prefrontal cortex, anterior and posterior cingulate cortices, insula, parahippocampal gyrus, hippocampus, amygdala, temporal cortex, and precuneus (Cheng et al., 2018). This suggests that intrinsic functional
Limitations
Scant number of studies was available to be included in this review. The review was limited to English-Language articles. The applied methods for assessing structural and functional neural mechanisms of insomnia and depression were divergent, which in turn hinders meta-analytic procedures. Additionally, quality control of the included studies has not been done. More rigorous quality control of the studies could be obtained through bias assessments in future studies with more included
Conclusion
The present review provided an overview of neuroimaging studies addressing neural correlates of insomnia and MDD. In summary, neuroimaging helps understanding of the underlying neural mechanisms and the association between MDD and insomnia. The approach of exploring the association between these two conditions in form of neural networks, genetic, and the brain monoamine theories might affect research and treatment planning and outcomes. Based on the available limited evidence, abnormalities in
Authors’ statement
All authors are fully responsible for the study. Shadi Bagherzadeh-Azbari, Habibolah Khazaie, Masoud Tahmasian designed the study and collected data. Shadi Bagherzadeh-Azbari, Habibolah Khazaie, Amir A. Sepehry, Masoud Tahmasian wrote the manuscript. Mojtaba Zarei, Kai Spiegelhalder, Martin Walter, Jeanne Leerssen, Eus J. W. Van Someren, Amir A. Sepehry, Masoud Tahmasian revised the manuscript.
Funding
The authors received no support by any funding agency for this work.
Declaration of competing interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
This work was supported by the Kermanshah University of Medical Sciences and Shahid Beheshti University. JL and EVS supported by European Research Council grant no. ERC-ADG-2014-671084 INSOMNIA.
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S.B and H.K. contributed equally to this work.