Wang M, Chen WT, Wang HT, Liu BS, Ju YM, Dong QL, Lu XW, Sun JR, Zhang L, Guo H, Zhao FT, Li WH, Zhang L, Li ZX, Liao M, Zhang Y, Liu J, Li LJ. Sleep disturbances and psychomotor retardation in the prediction of cognitive impairments in patients with major depressive disorder. World J Psychiatry 2024; 14(10): 1474-1483 [PMID: 39474372 DOI: 10.5498/wjp.v14.i10.1474]
Corresponding Author of This Article
Mei Liao, Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, No. 139 Renmin Middle Road, Changsha 410011, Hunan Province, China. liaomei123@csu.edu.cn
Research Domain of This Article
Psychiatry
Article-Type of This Article
Observational Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Mi Wang, Department of Mental Health Center, Xiangya Hospital, Central South University, Changsha 410008, Hunan Province, China
Mi Wang, National Clinical Research Center of Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, Hunan Province, China
Mi Wang, Wen-Tao Chen, Hao-Ting Wang, Bang-Shan Liu, Yu-Meng Ju, Qiang-Li Dong, Xiao-Wen Lu, Jin-Rong Sun, Liang Zhang, Wei-Hui Li, Li Zhang, Ze-Xuan Li, Mei Liao, Yan Zhang, Jin Liu, Ling-Jiang Li, Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan Province, China
Hua Guo, Fu-Tao Zhao, Department of Psychiatry, Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan Province, China
Co-corresponding authors: Ling-Jiang Li and Mei Liao.
Author contributions: Li LJ and Liu J codesigned the study; Liu BS, Ju YM, Dong QL, Lu XW, Sun JR, Zhang L, Guo H, Zhao FT, Li WH, Zhang L, Li ZX, Liao M and Zhang Y were responsible for participant recruitment and data collection; Chen WT and Wang M performed the statistical analyses; Chen WT wrote the initial draft of the manuscript. Wang M and Wang HT made substantial revisions to the manuscript. All the authors have approved the final version of this manuscript. In this study, both corresponding authors provided critical guidance and supervision at different stages. Li LJ played a central role in the early stages of study design and project initiation, being responsible for the construction of the study concept and the overall supervision of manuscript writing. Liao M, on the other hand, provided crucial support in the later stages of the study, particularly during the revision process, where she was responsible for data analysis and made significant contributions to the revision and refinement of the manuscript. The contributions of both corresponding authors are complementary and indispensable, and their joint designation as corresponding authors is a fair reflection of their sustained contributions.
Supported byNational Key Research and Development Program of China, No. 2019YFA0706200; National Natural Science Foundation of China, No. 82301738; and Natural Science Foundation of Hunan Province, No. 2022JJ40701 and No. 2022JJ40697.
Institutional review board statement: This study was approved by the Medical Ethics Committees of the Second Xiangya Hospital of Central South University and the Zhumadian Psychiatric Hospital.
Informed consent statement: All the participants signed the written informed consent form before study initiation.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Mei Liao, Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, No. 139 Renmin Middle Road, Changsha 410011, Hunan Province, China. liaomei123@csu.edu.cn
Received: July 3, 2024 Revised: August 26, 2024 Accepted: September 25, 2024 Published online: October 19, 2024 Processing time: 105 Days and 18.5 Hours
Abstract
BACKGROUND
Symptoms of depression and comorbid anxiety are known risk factors for cognitive impairment in major depressive disorder (MDD). Understanding their relationships is crucial for developing targeted interventions to mitigate cognitive impairments in MDD patients. We expect that the severity of sleep disturbances and other depressive symptoms will be positively correlated with the degree of cognitive impairments. We also hypothesize that anxiety symptoms, especially psychic anxiety, is a key factor in predicting cognitive performance in MDD patients and may indirectly contribute to cognitive impairment by affecting sleep disturbances and other potential factors.
AIM
To determine which dimension of the depressive and anxiety symptoms predicts cognitive impairment during a depressive episode.
METHODS
A comprehensive neurocognitive test battery assessed executive function, attention, processing speed, and memory in 162 medication-free MDD patients and 142 matched healthy controls. The 24-item Hamilton Depression Rating Scale was used to assess depressive symptoms, and the 14-item Hamilton Anxiety Scale was used to assess anxiety symptoms. Linear regression analyses and mediation analyses were conducted to evaluate the impact of depressive and anxiety symptoms, as well as their interactions, on cognitive impairments.
RESULTS
Among the depressive symptoms, sleep disturbances were associated with poorer executive function (P = 0.004), lower processing speed (P = 0.047), and memory impairments (P < 0.001), and psychomotor retardation (PR) was associated with lower processing speed in patients with MDD (P = 0.019). Notably, PR was found to mediate the impact of sleep disturbances on the processing speed. Regarding anxiety symptoms, psychic anxiety, rather than somatic anxiety, was associated with cognitive impairments in all aspects. Sleep disturbances mediated the effect of psychic anxiety on executive function [β = -0.013, BC CI (-0.027, -0.001)] and memory [β = -0.149, BC CI (-0.237, -0.063)], while PR mediated its effect on processing speed (β = -0.023, BC CI (-0.045, -0.004)].
CONCLUSION
Sleep disturbances may be a key predictor of poorer executive function, lower processing speed, and memory loss, while PR is crucial for lower processing speed during a depressive episode. Psychic anxiety contributes to all aspects of cognitive impairments, mediated by sleep disturbances and PR.
Core Tip: In this study, four major cognitive domains were assessed in 162 patients with major depressive disorder and 142 healthy controls via a comprehensive cognitive battery. Linear regression analyses and mediation analyses revealed that sleep disturbances independently contributed to executive function, processing speed, and memory, whereas psychomotor retardation (PR) symptoms independently contributed to processing speed. PR symptoms completely mediated the effect of sleep disturbances on processing speed. Psychic anxiety symptoms contributed to impairment in all four cognitive domains. Sleep disturbances mediated the effect of psychic anxiety symptoms on executive function, and PR symptoms mediated the effect of psychic anxiety symptoms on processing speed.
Citation: Wang M, Chen WT, Wang HT, Liu BS, Ju YM, Dong QL, Lu XW, Sun JR, Zhang L, Guo H, Zhao FT, Li WH, Zhang L, Li ZX, Liao M, Zhang Y, Liu J, Li LJ. Sleep disturbances and psychomotor retardation in the prediction of cognitive impairments in patients with major depressive disorder. World J Psychiatry 2024; 14(10): 1474-1483
Cognitive impairment is a well-established feature of major depressive disorder (MDD). Numerous studies have shown that cognitive impairments, mainly poor executive function, attention deficit, low processing speed, and memory loss, are overrepresented in patients with acute depression[1-4], and such symptoms have been reported to be associated with the outcomes[5-7], recurrence[8] and psychosocial functioning[9-11] of these patients. However, in previous years, the primary focus was on addressing mood and somatic symptoms in patients with depression rather than on cognitive symptoms, although improvements in cognitive symptoms have been observed as positive side effects of antidepressant treatment[12]. Nonetheless, an increasing number of studies have reported long-term cognitive impairments following depressive episodes[13]. The lack of effective treatment for cognitive impairments during depressive episodes might be a leading cause of residual cognitive symptoms. Notably, identifying the association between depressive symptoms and cognitive impairments not only helps provide insight into the cause of cognitive impairments but also facilitates efforts to identify targets of antidepressant treatment regarding cognitive function.
Some studies have addressed the association between the severity of depression and cognitive performance. Previous epidemiological studies demonstrated that high levels of depressive symptoms are associated with cognitive decline in older adults[14-16]. A meta-analysis by McDermott and Ebmeier[17] revealed that the severity of current depressive symptoms was significantly associated with executive function, processing speed, and episodic memory in patients with MDD. A later meta-analysis investigating the impairment of executive function in patients with MDD suggested a significant correlation between the severity of depression and executive dysfunction[18]. Additionally, more severe current depressive symptoms, rather than the duration of illness, contributed to impaired processing speed in unmedicated adult patients with MDD[2]. The above findings suggest that the severity of depression is a core risk factor for poor cognitive function during acute depressive episodes. However, the limited research focusing on individual depressive symptoms, rather than overall severity, has hindered the understanding of the relationship between depressive symptoms and cognitive performance in patients with MDD.
Anxiety symptoms are another critical factor to consider, as they are a common comorbidity in patients with MDD. A study revealed that up to 78.0% of patients with MDD met the criteria for “anxious distress specifiers”[19]. In addition, comorbid anxiety symptoms have been reported as a predictor of a poor prognosis of MDD, including poorer outcomes[20,21], higher rates of insomnia[22] and sleep problems[23], increased suicidal ideation[24] and attempts[25], and poorer psychosocial functioning[19]. Furthermore, previous findings also indicated a negative effect of comorbid anxiety on cognitive function[26-28]. Comorbid anxiety, especially psychic anxiety, is associated with poor executive function, attention deficit, lower processing speed, and memory loss in patients with MDD with “anxious distress”[29]. However, it is still unclear whether the impact of anxiety symptoms on cognitive function is direct or just mediated by specific factors. For example, comorbid anxiety was found to be predictive of both sleep disturbances and cognitive impairments, whereas some previous studies also reported that patients with insomnia performed poorer on various cognitive tests[30,31]. Thus, the effect of sleep disturbances on the association of comorbid anxiety with cognitive impairments remains to be explored.
To investigate these unresolved issues, we explored the influence of different depressive and anxiety symptoms on cognitive impairments in medication-free patients with MDD during depressive episodes via a comprehensive battery of neurocognitive tests. We expected that the severity of sleep disturbances and other depressive symptoms would be positively correlated with the degree of cognitive impairment. We also hypothesized that anxiety symptoms, especially psychic anxiety symptoms, may be key factors in predicting cognitive performance in patients with MDD and may indirectly contribute to cognitive impairment by affecting sleep disturbances and other potential factors.
MATERIALS AND METHODS
Participants
A total of 162 patients with MDD were recruited from the inpatient and outpatient departments of Zhumadian Psychiatric Hospital (Henan, China), and 142 healthy controls were recruited from nearby communities from 2013 to 2018. All participants were aged between 18 and 55 years, were right-handed, and had at least 6 years of education. Additional inclusion criteria for patients with MDD were as follows: (1) Diagnosed with MDD by well-trained attending psychiatrists via the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition; (2) Currently experiencing a major depressive episode, with a total score ≥ 20 on the 24-item Hamilton Depression Rating Scale (HAM-D24); and (3) Not using psychotropic medications for at least 2 weeks (6 weeks for fluoxetine) before enrollment. Individuals with any other psychiatric comorbidities (except generalized anxiety disorder) or major physical illnesses, alcohol or drug abuse or dependence, a history of head injury or neurological illnesses, or color-blindness, pregnant and breastfeeding women, and individuals who had undergone similar neurocognitive assessments within the past 12 months were excluded.
This study was approved by the Medical Ethics Committees of the Second Xiangya Hospital of Central South University and the Zhumadian Psychiatric Hospital. All the participants signed written informed consent forms before study initiation.
Assessments
A self-designed demographic information form was used to collect demographic information, and a structured clinical interview was conducted to collect relevant information about the patients’ medical conditions.
Depressive symptoms were evaluated via the HAM-D24, which includes 7 dimensions: Psychomotor retardation (PR) (including 4 items: Depressed mood, work and activities, retardation symptoms, and genital symptoms), cognitive disturbances (including 6 items: Feelings of guilt, suicide, psychomotor agitation, depersonalization and derealization, paranoid symptoms, and obsessional symptoms), sleep disturbances (including 3 items: Early insomnia, middle insomnia, and late insomnia), anxiety/somatization (including 6 items: Psychic anxiety, somatic anxiety, gastrointestinal symptoms, general somatic symptoms, hypochondriasis, and insight), weight loss (including 1 item: Loss of weight), diurnal variation (including 1 item: Diurnal variation), and hopelessness (including 3 items: Helplessness, hopelessness, and worthlessness). Anxiety symptoms were evaluated via the 14-item Hamilton Anxiety Rating Scale (HAM-A), which includes the dimensions of psychic anxiety symptoms (including 7 items: Anxious mood, tension, fears, insomnia, intellectual symptoms, depressed mood, and behavior during the interview) and somatic anxiety symptoms (including 7 items: Somatic-muscular, somatic-sensory, cardiovascular, respiratory, gastrointestinal, genitourinary, and autonomic symptoms).
Executive functions, attention, processing speed, and memory were assessed via a comprehensive battery of neuropsychological tests[2,29]. Executive function was assessed via the digit span backward test from the Wechsler Adult Intelligence Scale-Revised (WAIS-R), the color-word interference condition of the Stroop test, the categories completed and preservative errors on the Wisconsin Card Sorting Test, Part B of the Trail-Making Task (TMT)-B, and the Semantic Verbal Fluency (animals) test; attention was assessed via the digit span forward test from the WAIS-R and the word condition of the Stroop test; processing speed was assessed via part A of the TMT-A and the color condition of the Stroop test; and memory was assessed via the Visual Memory Test, Intelligent Memory Test, and Associative Memory Test from the Wechsler Memory Scale-Revised.
Statistical analysis
To group different subsets into different cognitive domains, raw scores were converted to standardized z scores, and the average composite z score was calculated as a measure for each domain. The z scores were calculated via the equation Xindividual-Xcontrols/σcontrols, where Xindividual represents the raw score of each individual, Xcontrols represents the mean score of the controls, and σcontrols represents the standard deviation of the controls. This conversion was based on our previous research[29]. To standardize z scores across all subtests, we reversed scores for the subtests where lower raw values (TMT-A and perseverative errors on the WCST) indicated better performance. The internal consistency of different tests in each cognitive domain was assessed via Cronbach’s alpha. All variables were tested for normality via the Kolmogorov-Smirnov test or Shapiro-Wilk test, and log or square root transformation was performed for variables that were not normally distributed.
Linear regression analysis was used to assess the impact of depressive and anxiety symptoms on cognitive function. Mediation analysis was also conducted to assess the associations between depressive and anxiety symptoms and each cognitive domain. The CI of the indirect effect was a bias-corrected bootstrapped CI based on 5000 bootstrap samples (BC CI). In this test, a significant indirect effect and a significant direct effect (with the CI excluding zero, P < 0.05) indicated partial mediation, and a significant indirect effect alongside a nonsignificant direct effect (with CI including zero, P ≥ 0.05) indicated complete mediation. Mediators were defined as factors with a significant indirect effect (i.e., with the CI excluding zero).
The level of statistical significance was set at P < 0.05 (two-tailed). All the statistical analyses were conducted via SPSS 24.0 software, and the mediation analyses were performed via Process Tool version 3.3.
RESULTS
Demographic and clinical characteristics
The demographic and clinical characteristics of the patients with MDD are presented in Table 1. The mean HAM-D score was 31.56 points, and the mean HAM-A score was 18.33 points, indicating that the patients experienced moderate-to-severe depression with obvious comorbid anxiety symptoms.
Table 1 Demographic and clinical characteristics of patients with major depressive disorder, mean (SD).
Characteristics
MDD (n = 162)
Age (years)
35.1 (9.55)
Male/female
72/90
Education (years)
10.45 (3.41)
Age of onset (years)
31.94 (9.71)
Number of episodes (n)
2.15 (1.51)
Total illness duration (months)
40.36 (50.64)
HAM-D score
31.56 (7.28)
Retardation
8.08 (2.94)
Cognitive disturbances
4.73 (2.32)
Sleep disturbances
4.13 (1.98)
Anxiety/somatization
6.44 (2.31)
Weight loss
0.86 (0.79)
Diurnal variation
1.07 (0.82)
Hopelessness
6.25 (2.26)
HAM-A score
18.33 (6.31)
Psychic anxiety symptoms
12.47 (3.52)
Somatic anxiety symptoms
5.76 (3.49)
Impact of depressive symptoms on cognitive performance in the MDD group
The Cronbach’s alpha values for executive function, attention, processing speed, and memory were 0.732, 0.655, 0.778, and 0.763, respectively, indicating high internal consistency of the tests for the four cognitive domains. Using regression models with the scores for the seven subdomains of the HAM-D as independent variables, sleep disturbance was found to be an independent factor for impaired executive function (P = 0.004), lower processing speed (P = 0.047), and memory loss (P < 0.001), whereas PR was an independent factor for lower processing speed only (P = 0.019) (Table 2).
Table 2 Results of multiple linear regression analyses for the impact of depressive symptoms on different cognitive domains.
β
t
P value
R2
F
P value
Executive function
Retardation
-0.023
-0.850
0.396
0.096
20.31
0.029
Cognitive disturbances
0.049
0.605
0.546
Sleep disturbances
-0.235
-20.94
0.004
Anxiety/somatization
0.076
0.901
0.369
Weight loss
-0.017
-0.215
0.830
Diurnal variation
-0.087
-10.10
0.273
Hopelessness
-0.086
-0.959
0.339
Attention
Retardation
-0.01
-0.110
0.912
0.080
10.89
0.075
Cognitive disturbances
0.113
10.37
0.172
Sleep disturbances
-0.256
-30.17
0.002
Anxiety/somatization
-0.028
-0.324
0.746
Weight loss
-0.008
-0.102
0.919
Diurnal variation
0.091
10.14
0.256
Hopelessness
-0.053
-0.585
0.560
Processing speed
Retardation
-0.218
-20.37
0.019
0.095
20.30
0.029
Cognitive disturbances
-0.006
-0.076
0.940
Sleep disturbances
-0.160
-20.00
0.047
Anxiety/somatization
-0.036
-0.428
0.670
Weight loss
-0.001
-0.015
0.988
Diurnal variation
0.083
10.05
0.297
Hopelessness
0.001
0.007
0.995
Memory
Retardation
-0.113
-10.27
0.207
0.165
30.77
< 0.001
Cognitive disturbances
0.067
0.843
0.401
Sleep disturbances
-0.352
-40.52
< 0.001
Anxiety/somatization
-0.045
-0.546
0.586
Weight loss
0.052
0.670
0.504
Diurnal variation
-0.062
-0.334
0.739
Hopelessness
0.047
0.542
0.589
The mediating effect of PR on the association between sleep disturbances and cognitive performance in the MDD group
Mediation analysis was conducted to investigate whether PR mediated the relationship between sleep disturbances and processing speed. In the mediation model, sleep disturbances, PR, and processing speed served as the predictor, mediator, and outcome variables, respectively, and PR partially mediated the effect of sleep disturbances on processing speed, as there was a significant indirect effect [β = -0.021, BC CI (-0.051, -0.002)] and a nonsignificant direct effect [β = -0.075, BC CI (-0.150, 0.0001)] (Table 3).
Table 3 Simple mediation analysis for the relationship between sleep disturbances and processing speed.
Impact of anxiety symptoms on cognitive performance in the MDD group
In regression models with psychic anxiety symptoms and somatic anxiety symptoms as independent variables, higher HAM-A scores for psychic anxiety symptoms were associated with poor executive function (β = -0.343, P < 0.001), attention deficit (β = -0.278, P = 0.004), lower processing speed (β = -0.215, P = 0.025), and memory loss (β = -0.238, P = 0.012); however, the HAM-A score for somatic anxiety symptoms was not associated with any cognitive impairment (all P > 0.05) (Table 4).
Table 4 Results of multiple linear regression analysis for the effect of anxiety symptoms on different cognitive domains.
β
t
P value
R2
F
P value
Executive function
HAMA-psychic symptoms
-0.343
-30.67
< 0.001
0.081
60.84
< 0.001
HAMA-somatic symptoms
0.158
10.69
0.094
Attention
HAMA-psychic symptoms
-0.278
-20.96
0.004
0.053
40.41
0.014
HAMA-somatic symptoms
0.140
10.48
0.140
Processing speed
HAMA-psychic symptoms
-0.215
-20.27
0.025
0.040
30.32
0.039
HAMA-somatic symptoms
-0.027
0.282
0.778
Memory
HAMA-psychic symptoms
-0.238
-20.54
0.012
0.060
50.03
0.008
HAMA-somatic symptoms
-0.011
-0.116
0.908
The mediating effect of depression severity on the association between anxiety symptoms and cognitive performance in the MDD group
To further investigate whether sleep disturbances mediate the effect of psychic anxiety symptoms on different cognitive domains, mediation analyses were conducted with psychic anxiety symptoms, sleep disturbances, and cognitive domains as the predictor, mediator, and outcome variables, respectively (Table 5). The results showed that sleep disturbances mediated the effect of psychic anxiety symptoms on executive function [β = -0.013, BC CI (-0.027, -0.001)] and memory [β = -0.149, BC CI (-0.237, -0.063)] but did not mediate the effect of psychic anxiety symptoms on processing speed [β = -0.018, BC CI (-0.042, 0.007)]. In the mediation model with psychic anxiety symptoms, PR, and processing speed as the predictor, mediator, and outcome variables, respectively, PR completely mediated the effect of psychic anxiety symptoms on processing speed (β = -0.023, BC CI (-0.045, -0.004)].
Table 5 Simple mediation analysis for the relationship between psychic anxiety symptoms and cognitive performance.
This study investigated the impact of depressive and anxiety symptoms on cognitive functions during a depressive episode in patients with MDD via a comprehensive battery of cognitive assessments. Generally, the severity of depression has been regarded as the main risk factor for cognitive impairments. It has been reported that more severe current symptoms of depression are predictive of poor cognitive function[17,18]. The findings of the present study support this notion and further demonstrate that comorbid anxiety symptoms are also a risk factor for poor cognitive performance. Specifically, we found that not all depressive symptoms were linked to cognitive impairments, with only sleep disturbances being related to poor executive function, lower processing speed and memory loss. Additionally, PR was associated with lower processing speed and mediated the effects of sleep disturbances on processing speed. Comorbid anxiety is also regarded as a risk factor for cognitive impairment in patients with MDD[26-29]. Our study revealed that among all types of anxiety symptoms, psychic anxiety symptoms were associated with impairment in all four cognitive domains, whereas somatic anxiety symptoms showed no such associations. Sleep disturbances were found to mediate the effects of psychic anxiety symptoms on executive function and memory, whereas PR was found to mediate the effect of psychic anxiety symptoms on processing speed, indicating that the impact of comorbid anxiety symptoms on cognitive functions was mediated mainly by sleep disturbances and PR in patients with MDD. To our knowledge, this is the first study to explore the impact of depressive symptoms and comorbid anxiety symptoms on cognitive functions in patients with MDD, revealing that sleep disturbances might be a core predictor of poor cognitive performance and that PR might be a major influencing factor of lower processing speed during a depressive episode.
Sleep disturbances are among the most common symptoms of MDD; they usually appear before the onset of depression and persist during remission[32]. A three-year prospective study revealed that sleep problems were reported by approximately 85% of patients with MDD during major depressive episodes and 39% of patients with MDD during remission[33]. McClintock et al[34] reported that up to 94.6% of patients with MDD who failed to achieve clinical remission after 12 weeks of antidepressant treatment experienced residual sleep problems. Previous studies identified insomnia as a risk factor for MDD[35,36]. A meta-analysis suggested that individuals with insomnia are twice as likely to develop depression as those without sleep difficulties[37]. Moreover, a STAR*D report showed that insomnia was predictive of increased depressive symptom severity[36]. Insomnia also greatly impacts patients’ cognitive functions. A recent meta-analysis on the impact of insomnia on cognitive function that included 48 studies revealed that both subjective and objective cognitive functions were significantly impaired in patients with insomnia[31]. By investigating the cognitive function of older adults with depression and sleep symptoms, Biddle et al[38] reported that poor sleep efficiency was associated with impaired executive function and decreased response speed but not with the severity of depression. On the basis of previous studies, the present study is the first to demonstrate that sleep disturbances predict poor cognitive performance and mediate the effect of comorbid anxiety on cognitive functions in patients with MDD. This may be due to the overlapping neural mechanism of sleep disturbances and cognitive impairments. It has been demonstrated that sleep disturbances are linked with 5-HT and glutamate abnormalities, as well as hypothalamic-pituitary-adrenal (HPA) axis dysfunction[39,40], and these abnormalities are also involved in changes in cognitive functions[41,42].
Another important finding of the present study is that PR may be a major influencing factor of lower processing speed. Specifically, PR not only is an independent influencing factor of lower processing speed but also mediates the effect of psychic anxiety symptoms on processing speed. PR encompasses a series of symptoms related to low energy, especially psychomotor slowing. Although few studies have explored the relationship between PR and processing speed, it has been proposed that lower processing speed in patients with MDD might be related to psychomotor slowing[43-45]. Previous neuroimaging studies have shown that decreased processing speed may be attributed to prefrontal white matter hyperintensities and fronto-striatal disconnection[46,47], whereas white matter hyperintensity was found to be the structural basis of psychomotor slowing in individuals with late-life depression[48]. Functional magnetic resonance imaging studies have also reported that psychomotor slowing in individuals with depression is related to a decrease in BOLD signals in the dorsolateral prefrontal cortex, left prefrontal cortex, angular gyrus, and anterior cingulate cortex[49,50]. The above evidence is in line with the neuroimaging findings on processing speed, which provides a basis for the association between psychomotor slowing and lower processing speed in patients with depression.
Unexpectedly, we did not find any significant independent influence of cognitive disturbances, anxiety/somatization, weight loss, diurnal variation, or hopelessness on the four cognitive domains. The subdomain of cognitive disturbances in the HAM-D24 is related mainly to “hot cognition” rather than neurocognitive function; however, the relationship between these two aspects of cognition is still unclear. The anxiety/somatization subdomain included 6 items: Psychic anxiety, somatic anxiety, gastrointestinal symptoms, general somatic symptoms, hypochondriasis, and insight. In the present study, anxiety symptoms (assessed via the HAM-A), especially psychic anxiety symptoms, were associated with broad cognitive impairments, but no such association was found regarding anxiety/somatization. We speculate that this may be related to the more detailed anxiety symptom information provided by the HAM-A, as this level of detail may aid in a more precise analysis of the specific links between anxiety symptoms and cognitive functions. Weight loss is also a common symptom for patients with depressive episodes. Hidese et al[51] reported that patients with MDD and obesity performed worse on working memory, processing speed, and executive function tests than did those without obesity. Nonetheless, there is still a lack of evidence to support that weight loss directly affects cognitive function in patients with MDD. Similarly, although previous studies have revealed an association between diurnal variation changes (related to the HPA axis) and global cognitive impairments in individuals of advanced age[52], as well as a relationship between suicidal ideation and cognitive dysfunction[53-55], there is still a lack of direct evidence in patients with MDD. Therefore, prospective studies and more specific assessment tools are needed to explore the factors affecting cognitive function. Despite the strength of our comprehensive assessment of the relationships among depressive symptoms, anxiety symptoms, and cognitive impairments in a relatively large sample of medication-free patients with MDD, two main limitations should be noted. First, the cross-sectional design of the present study makes it difficult to make accurate causal inferences; thus, prospective and longitudinal studies with larger sample sizes are needed. Second, the dimensions of depressive and anxiety symptoms included in the HAM-D24 provide only limited information, indicating the need for assessment tools for more specific symptoms (e.g., the Insomnia Severity Index).
CONCLUSION
In summary, the present study investigated the impact of different depressive and anxiety symptoms on the cognitive functions of patients with MDD. These findings indicate that sleep disturbances and PR are responsible for cognitive impairments in patients with MDD during a depressive episode, which provides evidence for factors affecting cognitive performance in patients with MDD as well as potential targets for the treatment of residual cognitive symptoms. Our results suggest that sleep disturbances should receive more attention from patients with executive dysfunction and memory loss, whereas early intervention for PR symptoms is likely to benefit patients with lower processing speed.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Psychiatry
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade C
Novelty: Grade C
Creativity or Innovation: Grade C
Scientific Significance: Grade C
P-Reviewer: Jing Z S-Editor: Qu XL L-Editor: A P-Editor: Yuan YY
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