Exploring transfer effects on memory and its neural mechanisms through a computerized cognitive training in mild cognitive impairment: randomized controlled trial.

BACKGROUND: Computerized cognitive training (CCT) has been proposed as a potential therapy for cognitive decline. One of the benefits of CCT is a transfer effect, but its mechanism on the memory domain is unclear. This study aimed to investigate the transfer effect of non-memory multidomain CCT on the memory domain and its neural basis in patients with mild cognitive impairment (MCI) through a randomized controlled trial. METHODS: Patients with MCI recruited from memory clinics were randomly assigned to either the CCT or the control group. The CCT group received multidomain CCT training excluding memory training, while the control group read educational books with learning-based quizzes twice a week for 8 weeks. Participants underwent memory tests yielding a composite score, other cognitive domain tests, non-cognitive scales, and resting-state functional magnetic resonance imaging (rsfMRI), at baseline and after intervention. Within- and between-group comparisons, group × time interactions, and seed-to-voxel analyses in memory-involving brain networks were performed. RESULTS: The CCT group showed improvement over the control group in memory domain (Group × time, F = 5.87, P = 0.03, η2 = 0.31), which was related with the increased connectivity in the hippocampal-frontal and fusiform-occipital network. No other cognitive and non-cognitive symptoms differed between groups after adjusting for covariates. CONCLUSION: Eight weeks of multidomain CCT without memory training improved memory function and restored functional network in the hippocampal and medial temporal region in MCI patients. These results can provide evidence for the transferring ability of CCT on memory functioning with its neural basis.

The Application of a Machine Learning-Based Brain Magnetic Resonance Imaging Approach in Major Depression.

Major depressive disorder (MDD) shows a high prevalence and is associated with increased disability. While traditional studies aimed to investigate global characteristic neurobiological substrates of MDD, machine learning-based approaches focus on individual people rather than a group. Therefore, machine learning has been increasingly conducted and applied to clinical practice. Several previous neuroimaging studies used machine learning for stratifying MDD patients from healthy controls as well as in differentially diagnosing MDD apart from other psychiatric disorders. Also, machine learning has been used to predict treatment response using magnetic resonance imaging (MRI) results. Despite the recent accomplishments of machine learning-based MRI studies, small sample sizes and the heterogeneity of the depression group limit the generalizability of a machine learning-based predictive model. Future neuroimaging studies should integrate various materials such as genetic, peripheral, and clinical phenotypes for more accurate predictability of diagnosis and treatment response.

Associations between Melatonin, Neuroinflammation, and Brain Alterations in Depression.

Pro-inflammatory systemic conditions that can cause neuroinflammation and subsequent alterations in brain regions involved in emotional regulation have been suggested as an underlying mechanism for the pathophysiology of major depressive disorder (MDD). A prominent feature of MDD is disruption of circadian rhythms, of which melatonin is considered a key moderator, and alterations in the melatonin system have been implicated in MDD. Melatonin is involved in immune system regulation and has been shown to possess anti-inflammatory properties in inflammatory conditions, through both immunological and non-immunological actions. Melatonin has been suggested as a highly cytoprotective and neuroprotective substance and shown to stimulate all stages of neuroplasticity in animal models. The ability of melatonin to suppress inflammatory responses through immunological and non-immunological actions, thus influencing neuroinflammation and neurotoxicity, along with subsequent alterations in brain regions that are implicated in depression, can be demonstrated by the antidepressant-like effects of melatonin. Further studies that investigate the associations between melatonin, immune markers, and alterations in the brain structure and function in patients with depression could identify potential MDD biomarkers.

Cognitive reserve and the effects of virtual reality-based cognitive training on elderly individuals with mild cognitive impairment and normal cognition.

BACKGROUND: Cognitive reserve (CR) is a concept proposed to account for discrepancies between the extent of brain pathology and clinical manifestations of that pathology. This study aimed to explore the associations between CR and the effects of cognitive training using fully immersive virtual reality (VR). METHODS: A total of 44 older adults (22 cognitively normal, 22 with mild cognitive impairment) underwent eight cognitive training sessions using VR for a period of 4 weeks. CR was assessed using the Cognitive Reserve Index questionnaire (CRIq). To evaluate baseline cognitive function and the effects of VR training, the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery was administered to all participants before and after the training. RESULTS: Greater improvement in the total CERAD score was seen for cognitively normal participants with higher versus lower scores on the Education subdomain of the CRIq. Among patients with mild cognitive impairment, none of the CRIq subdomain scores (Education, Working Activity, Leisure Time) were related to a change in CERAD total scores. The CRIq total score did not predict the improvement of global cognition in either group. CONCLUSIONS: This study revealed different impacts of CR on cognitive training according to the participants' cognitive status. It also suggests that employing three proxies of CR rather than using a composite score would provide a more accurate understanding of one's CR.

Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks.

Major depressive disorder (MDD) is a leading cause of disability; its symptoms interfere with social, occupational, interpersonal, and academic functioning. However, the diagnosis of MDD is still made by phenomenological approach. The advent of neuroimaging techniques allowed numerous studies to use resting-state functional magnetic resonance imaging (rs-fMRI) and estimate functional connectivity for brain-disease identification. Recently, attempts have been made to investigate effective connectivity (EC) that represents causal relations among regions of interest. In the meantime, to identify meaningful phenotypes for clinical diagnosis, graph-based approaches such as graph convolutional networks (GCNs) have been leveraged recently to explore complex pairwise similarities in imaging/nonimaging features among subjects. In this study, we validate the use of EC for MDD identification by estimating its measures via a group sparse representation along with a structured equation modeling approach in a whole-brain data-driven manner from rs-fMRI. To distinguish drug-naïve MDD patients from healthy controls, we utilize spectral GCNs based on a population graph to successfully integrate EC and nonimaging phenotypic information. Furthermore, we devise a novel sensitivity analysis method to investigate the discriminant connections for MDD identification in our trained GCNs. Our experimental results validated the effectiveness of our method in various scenarios, and we identified altered connectivities associated with the diagnosis of MDD.

Machine learning-based prediction of persistent oppositional defiant behavior for 5 years.

BACKGROUND: Early detection of oppositional defiant behavior is warranted for timely intervention in children at risk. This study aimed to build a predictive model of persistent oppositional defiant behavior based on a machine learning algorithm. METHODS: With nationwide cohort data collected from 2012 to 2017, a tree-based ensemble model, random forest, was exploited to build a predictive model for persistent oppositional defiant behavior. The persistent oppositional defiant behavior was defined by the presence of oppositional defiant behavior for all the five years. The area under the receiver operating characteristic curve (AUC), overall accuracy, sensitivity, specificity, and Matthew's correlation coefficients (MCC) were measured. RESULTS: Data of 1,323 children were used for building the machine learning-based predictive model. The baseline mean ± standard deviation month-age of the participants was 51.0 ± 1.2 months. The proportion of persistent oppositional defiant behavior was 0.98% (13/1323). In the hold-out test set, the overall accuracy, AUC, sensitivity, specificity, and MCC were 0.955, 0.982, 1.000, 0.954, and 0.417, respectively. CONCLUSION: Our study demonstrated that the machine learning-based approach is useful for predicting persistent oppositional defiant behavior in preschool-aged children.

Prevalence and incidence of Parkinson's disease and drug-induced parkinsonism in Korea.

BACKGROUND: Parkinson's disease (PD) and drug-induced parkinsonism (DIP) are the major diseases of parkinsonism. To better understand parkinsonism, we aimed to assess the prevalence and incidence of PD and DIP in Korea from 2012 to 2015. METHODS: We used the Health Insurance Review and Assessment Service database, which covers the entire population in Korea. We used claims during 2011-2015 to assess epidemiology of PD and DIP during 2012-2015. Retrospective cross-sectional study design was employed to assess prevalence, whereas retrospective cohort study design was used to determine incidence. Patients with at least one claim with ICD-10 G20 and who received antiparkinsonian drugs for at least 60 days were classified as having PD. We excluded patients with antiparkinsonian drugs that can be used for indications other than PD. Patients with at least one claim with ICD-10 G211 or G251 during the prescription period of drugs that are frequently related with DIP were classified as having DIP. Incident cases had a disease-free period of 1 year before diagnosis. To evaluate the significance of changes in the prevalence or incidence over time, Poisson regression was used to determine p for trend. RESULTS: The prevalence of PD increased from 156.9 per 100,000 persons in 2012 to 181.3 per 100,000 persons in 2015 (p for trend< 0.0001). The incidence of PD decreased steadily from 35.4 per 100,000 person-years in 2012 to 33.3 per 100,000 person-years in 2015 (p for trend< 0.0001). The prevalence of DIP increased from 7.3 per 100,000 persons in 2012 to 15.4 per 100,000 persons in 2015 (p for trend< 0.0001) and the incidence of DIP increased from 7.1 per 100,000 person-years in 2012 to 13.9 per 100,000 person-years in 2015 (p for trend< 0.0001). CONCLUSIONS: Our study suggests that the incidence of PD has gradually decreased whereas, the incidence of DIP increased from 2012 to 2015. Further studies are warranted to examine possible causes of increased DIP incidence in order to develop management strategy for parkinsonism.

Big Data and Discovery Sciences in Psychiatry.

The modern society is a so-called era of big data. Whereas nearly everybody recognizes the "era of big data", no one can exactly define how big the data is a "big data". The reason for the ambiguity of the term big data mainly arises from the widespread of using that term. Along the widespread application of the digital technology in the everyday life, a large amount of data is generated every second in relation with every human behavior (i.e., measuring body movements through sensors, texts sent and received via social networking services). In addition, nonhuman data such as weather and Global Positioning System signals has been cumulated and analyzed in perspectives of big data (Kan et al. in Int J Environ Res Public Health 15(4), 2018 [1]). The big data has also influenced the medical science, which includes the field of psychiatry (Monteith et al. in Int J Bipolar Disord 3(1):21, 2015 [2]). In this chapter, we first introduce the definition of the term "big data". Then, we discuss researches which apply big data to solve problems in the clinical practice of psychiatry.

Suicide Methods According to Age and Sex: An Analysis of Data of 239,565 Suicide Victims in the Republic of Korea From 1991 to 2015.

Because suicide is irreversible, prevention is paramount. For the optimal strategy to reduce lethal means, we sought to investigate age- and sex-associated variations in suicide methods. Data on annual causes of death from 1991 to 2015 in the Republic of Korea were used. Major sociodemographic correlates of the five suicide methods were analyzed by multiple multinominal logistic regression analysis. Among a total of 239,565 suicides from 1991 to 2015, hanging was most common. Gas poisoning sharply increased from 2007 to 2015. The gap between hanging and the second most common method of suicide has increased from 659 in 2004 to 4,433 in 2015. Charcoal burning was most commonly used by males younger than 45 years of age, whereas pesticide was commonly used by both sexes ages 55 years and older. Our results suggest that age- and sex-specific suicide prevention strategies are needed, particularly for gas and pesticide poisoning.

Decreased serum magnesium levels in depression: a systematic review and meta-analysis.

BACKGROUND: Magnesium (Mg2+), an endogenous N-methyl-D-aspartate receptor antagonist, has received increased attention recently because of its role in the pathophysiology of and treatment response in depression. However, whether Mg2+ level is decreased in depression is not firmly established. We aimed to conduct a systematic review and meta-analysis to help making consensus for the association between Mg2+ levels and depression. METHODS: A systematic search was conducted in the electronic database resources PubMed and Embase. After a careful selection of relevant studies, a meta-analysis using the random effects model was conducted in each measuring source, such as serum, plasma, and cerebrospinal fluid (CSF). RESULTS: A total of 18 studies were included in this study. Among 11 studies that measured Mg2+ in the serum, Mg2+ level was lower in patients with depression than in controls (weighted mean difference = -.088, 95% confidence interval = -.164 to -.012). In the sensitivity analysis by removing studies one by one, 2 out of the 11 studies obliterated such significant differences. There were no significant differences in the Mg2+ levels in the studies for plasma and CSF. CONCLUSIONS: Despite some evidence supporting an association between decreased Mg2+ levels and depression from studies with serum, the results of our meta-analysis urge to use caution when associating Mg2+ levels and depression. Future studies are needed to establish a consensus for the role of low Mg2+ levels in depression.

Decreased regional gray matter volume in suicide attempters compared to suicide non-attempters with major depressive disorders.

OBJECTIVE: This study investigated regional gray matter (GM) volume differences between suicide attempters and suicide non-attempters with major depressive disorder (MDD) and their relationship with psychological risk factors for suicidality. METHODS: MDD patients with and without a suicide attempt history (n=19 in each group) participated. The Hamilton Depression Rating Scale, Clinical Global Impression (severity subscale), Scale for Suicide Ideation (SSI), Risk-Rescue Rating (RRR), Beck Hopelessness Scale (BHS), Barrett Impulsivity Scale, Eysenck Personality Questionnaire, and Ways of Coping Checklist (WCCL) were administered. T1-weighted structural magnetic resonance imaging scans were acquired to evaluate changes in GM volume. Voxel-based morphometry was performed using the SPM 8 software package. Two-sample t-tests were used during second-level group comparison analysis; partial correlation analysis controlling for gender and age identified associations between regional GM volume and psychological measures. RESULTS: Suicide attempters exhibited significantly decreased GM volume in the left angular gyrus (p<0.001, uncorrected) and right cerebellum (p<0.001, uncorrected). GM volume in the left angular gyrus was inversely correlated with BHS scores (r=-0.55, p<0.01) and positively correlated with the Seeking Social Support subscale of the WCCL (r=0.43, p<0.01). CONCLUSION: These findings provide evidence of a neural basis of suicidal behaviors in MDD. In particular, reduced GM volume in the left angular gyrus may be a neurobiological marker of suicidality in depressed patients.

Plasma glial cell line-derived neurotrophic factor in patients with major depressive disorder: a preliminary study.

BACKGROUND: Some clinical studies have reported reduced peripheral glial cell line-derived neurotrophic factor (GDNF) level in elderly patients with major depressive disorder (MDD). We verified whether a reduction in plasma GDNF level was associated with MDD. METHOD: Plasma GDNF level was measured in 23 healthy control subjects and 23 MDD patients before and after 6 weeks of treatment. RESULTS: Plasma GDNF level in MDD patients at baseline did not differ from that in healthy controls. Plasma GDNF in MDD patients did not differ significantly from baseline to the end of treatment. GDNF level was significantly lower in recurrent-episode MDD patients than in first-episode patients before and after treatment. CONCLUSIONS: Our findings revealed significantly lower plasma GDNF level in recurrent-episode MDD patients, although plasma GDNF levels in MDD patients and healthy controls did not differ significantly. The discrepancy between our study and previous studies might arise from differences in the recurrence of depression or the ages of the MDD patients.

DRD2 genotypic and haplotype variation is associated with improvements in negative symptoms after 6 weeks' amisulpride treatment.

The aim of this study was to identify the association between the rs1079597 and rs1800497 genetic polymorphisms of the gene encoding the dopamine D2 receptor (DRD2) protein and the treatment response to the selective dopamine receptor antagonist amisulpride. After 6 weeks of treatment with amisulpride, 125 schizophrenia patients were interviewed based on the Positive and Negative Syndrome Scale and the Clinical Global Impression-Severity Scale. Genotyping for rs1079597 and rs1800497 was performed using the TaqMan single nucleotide polymorphism genotyping assay. There were significant differences in the genotype frequency of the recessive model (χ = 5.73, P = 0.017) and allele frequency (χ = 5.16, P = 0.023) of rs1079597 between the responders and nonresponders based on the Positive and Negative Syndrome Scale negative symptoms scores. There was no significant finding in this regard for the rs1800497 polymorphism. The T-C and C-C haplotype of rs1079597-rs1800497 were associated with the negative symptom treatment response to amisulpride after permutation test. To the best of our knowledge, this is the first report of the positive finding in the association study between rs1079597 polymorphism and the treatment response to amisulpride in schizophrenic patients. A larger scale study involving more single nucleotide polymorphisms of DRD2 will progress the research into the pharmacogenetics of the treatment response to amisulpride.

Knowledge and Attitude of 851 Nursing Personnel toward Depression in General Hospitals of Korea.

Our study aimed to examine the knowledge and attitude of nursing personnel toward depression in general hospitals of Korea. A total of 851 nursing personnel enrolled at four university-affiliated general hospitals completed self-report questionnaires. Chi-square tests were used to compare the knowledge and attitude of registered or assistant nurses toward depression. In addition, binary logistic regression analysis was used to adjust for the following confounders: age-group and workplace. Registered and assistant nurses differed in their knowledge and attitude toward depression. The proportion of rational and/or correct responses were higher in registered nurses than assistant nurses for the following: constellation of depressive symptoms defined by DSM-IV (adjusted odds ratio [aOR], 3.876; P<0.001); suicide risk in depression recovery (aOR, 3.223; P=0.001) and psychological stress as a cause of depression (aOR, 4.370; P<0.001); the relationship between chronic physical disease and depression (aOR, 8.984; P<0.001); and other items. Our results suggest that in terms of the biological model of depression, the understanding of registered nurses is greater than that of assistant nurses. Moreover, specific psychiatric education programs for nursing personnel need to be developed in Korea. Our findings can contribute to the development of a general hospital-based model for early detection of depression in patients with chronic medical diseases.

Evidence-based, non-pharmacological treatment guideline for depression in Korea.

Although pharmacological treatment constitutes the main therapeutic approach for depression, non-pharmacological treatments (self-care or psychotherapeutic approach) are usually regarded as more essential therapeutic approaches in clinical practice. However, there have been few clinical practice guidelines concerning self-care or psychotherapy in the management of depression. This study introduces the 'Evidence-Based, Non-Pharmacological Treatment Guideline for Depression in Korea.' For the first time, a guideline was developed for non-pharmacological treatments for Korean adults with mild-to-moderate depression. The guideline development process consisted of establishing several key questions related to non-pharmacologic treatments of depression, searching the literature for studies which answer these questions, assessing the evidence level of each selected study, drawing up draft recommendation, and peer review. The Scottish Intercollegiate Guidelines Network grading system was used to evaluate the quality of evidence. As a result of this process, the guideline recommends exercise therapy, bibliotherapy, cognitive behavior therapy, short-term psychodynamic supportive psychotherapy, and interpersonal psychotherapy as the non-pharmacological treatments for adult patients with mild-to-moderate depression in Korea. Hence, it is necessary to develop specific methodologies for several non-pharmacological treatment for Korean adults with depression.

There is no association between the serotonin receptor gene and bipolar I disorder in the Korean population.

OBJECTIVE: Despite the close relationship between the functional polymorphism C(-1019)G (rs6295) of the serotonergic 1A receptor (5-HT1A) and mood, few studies have investigated the relationship between rs6295 and bipolar disorder. AIMS: In this study, we aimed to investigate whether rs6295 is associated with clinical prognosis and treatment response in patients with bipolar I disorder acute manic episodes. METHODS: One hundred twenty-eight patients with bipolar I disorder and one hundred sixty-eight healthy controls were recruited. Associations between patients with bipolar I disorder and healthy controls were compared. In addition, age at onset, number of admissions, and treatment response, including response rate, mean changes in manic symptoms, number of anti-manic agents and the total dosage of mood stabilizers for acute manic symptoms were compared between the rs6295 GG and CG+ CC groups in patients with bipolar I disorder. We conducted a separate subgroup analysis according to gender. RESULTS: There were no differences in frequency between patients and controls. In patients with bipolar disorder, clinical prognosis and treatment response were no different between GG and CG+ CC groups. However, in a subgroup analysis according to gender, male, but not female, patients in the GG group had a longer duration of illness and a greater number of both previous episodes and psychiatric ward admissions than did the GC+ CC group. CONCLUSIONS: Further studies should investigate the relationship between 5-HT1A polymorphisms and bipolar disorder in terms of mood episode and gender.

Effectiveness of paliperidone extended-release for patients with schizophrenia: focus on subjective improvement.

OBJECTIVE: This study assessed whether the subjective experience of patients with schizophrenia improved after switching from an oral antipsychotic to flexibly-dosed paliperidone extended-release. METHODS: We conducted a 24-week, multicenter, non-comparative, open-label trial. A total of 387 patients with schizophrenia participated the study. The primary study outcome was the change in subjective symptoms measured by the Symptom Checklist-90-Revised version (SCL-90-R) from baseline. Visual analogue scales were used for sleep and daytime somnolence as secondary subjective assessments. The clinical global impression-schizophrenia-severity scale was used to assess overall symptom severity. Social functioning was evaluated by the personal and social performance scale. Adverse events were also evaluated. RESULTS: All subjective symptoms measured by the SCL-90-R improved significantly. The early responders, who achieved >20% reduction in the SCL-90-R within 1 week, maintained significantly lower severity through the 24 weeks. The clinical global impression-schizophrenia-severity scale and personal and social performance scores also improved significantly. The visual analogue scales revealed that daytime somnolence improved significantly, whereas nocturnal sleep quality was unaltered. CONCLUSION: Our results suggest that switching to paliperidone extended-release was associated with improvements in various subjective symptoms, decreased overall symptom severity, and increased social functioning. The results also suggest that early detection and reduction of subjective symptoms are important for treatment outcome.

Prevalence and Correlates of Comorbid Posttraumatic Stress Disorder in Schizophrenia-Spectrum Disorder: A Systematic Review and Meta-Analysis.

OBJECTIVE: Schizophrenia-spectrum disorders and posttraumatic stress disorder (PTSD) share common clinical manifestations, genetic vulnerability, and environmental risk factors. We aimed to conduct a systematic review and meta-analysis of the comorbid prevalence of PTSD among schizophrenia-spectrum disorders. METHODS: We performed a meta-analysis to identify possible contributing factors to the heterogeneity among these studies. We systematically searched electronic databases with no restrictions on language of articles. RESULTS: We extracted 24 samples (18 for current prevalence and 6 for lifetime prevalence) from 22 studies and used a random effects model to estimate the pooled prevalence of PTSD among schizophrenia-spectrum disorders. The current and life prevalence of comorbid PTSD was 10.6% (95% confidence interval [CI]=6.3%-17.3%) and 13.0% (95% CI=5.3%-28.6%), respectively. Studies assessing psychotic experiences/involuntary admission reported the highest prevalence of comorbid PTSD (57.1%, 95% CI=43.6%-59.7%), whereas those assessing various anxiety disorders reported the lowest prevalence (1.1%, 95% CI=1.0%-5.5%). Heterogeneities of the subgroup analysis by similar objectives were largely homogeneous (I2=7.1-34.1). In the qualitative assessment, only two studies (9.1%) were evaluated as having a low risk of bias. CONCLUSION: Our results showed that a careful approach with particular attention to assessing PTSD is essential to reliably estimate the prevalence of PTSD comorbid with schizophrenia-spectrum disorders. The reason for the wide discrepancy in the prevalence of comorbid PTSD among the four groups of studies should be addressed in future research.

Temperament and character of young male conscripts with adjustment disorder: a case-control study.

Personality is an important clinical factor for successful adjustment in stressful situations. The aim of this study was to examine possible differences in temperament and character dimensions between patients with adjustment disorder with depressed mood and healthy controls. Among the young male conscripts, 86 subjects with adjustment disorder with depressed mood and 86 healthy controls were included. The mean scores in the 7 dimensions and 25 subscales of the Temperament and Character Inventory were compared between the patients with adjustment disorder with depressed mood and the control group by an independent t-test. The patients with adjustment disorder with depressed mood had significantly higher scores on harm-avoidance and lower scores on self-directedness, cooperativeness, and self-transcendence than did the controls. There were no differences in novelty seeking, reward dependence, and persistence in temperament between the two groups. The results of this study suggest that the personality traits of the subjects with adjustment disorder with depressed mood would make them vulnerable to stressful situations and less skilled in coping with conscription.