Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.

Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma.

Posterior cingulate and medial prefrontal excitation-inhibition balance in euthymic bipolar disorder.

BACKGROUND: Persistent cognitive deficits and functional impairments are associated with bipolar disorder (BD), even during the euthymic phase. The dysfunction of default mode network (DMN) is critical for self-referential and emotional mental processes and is implicated in BD. The current study aims to explore the balance of excitatory and inhibitory neurotransmitters, i.e. glutamate and γ-aminobutyric acid (GABA), in hubs of the DMN during the euthymic patients with BD (euBD). METHOD: Thirty-four euBD and 55 healthy controls (HC) were recruited to the study. Using proton magnetic resonance spectroscopy (1H-MRS), glutamate (with PRESS sequence) and GABA levels (with MEGAPRESS sequence) were measured in the medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC) and the posterior cingulate gyrus (PCC). Measured concentrations of excitatory glutamate/glutamine (Glx) and inhibitory GABA were used to calculate the excitatory/inhibitory (E/I) ratio. Executive and attentional functions were respectively assessed using the Wisconsin card-sorting test and continuous performance test. RESULTS: euBD performed worse on attentional function than controls (p = 0.001). Compared to controls, euBD had higher E/I ratios in the PCC (p = 0.023), mainly driven by a higher Glx level in the PCC of euBD (p = 0.002). Only in the BD group, a marginally significant negative association between the mPFC E/I ratio (Glx/GABA) and executive function was observed (p = 0.068). CONCLUSIONS: Disturbed E/I balance, particularly elevated Glx/GABA ratio in PCC is observed in euBD. The E/I balance in hubs of DMN may serve as potential biomarkers for euBD, which may also contribute to their poorer executive function.

A Novel Adductomics Workflow Incorporating FeatureHunter Software: Rapid Detection of Nucleic Acid Modifications for Studying the Exposome.

Exposure to the physicochemical agents that interact with nucleic acids (NA) may lead to modification of DNA and RNA (i.e., NA modifications), which have been associated with various diseases, including cancer. The emerging field of NA adductomics aims to identify both known and unknown NA modifications, some of which may also be associated with proteins. One of the main challenges for adductomics is the processing of massive and complex data generated by high-resolution tandem mass spectrometry (HR-MS/MS). To address this, we have developed a software called "FeatureHunter", which provides the automated extraction, annotation, and classification of different types of key NA modifications based on the MS and MS/MS spectra acquired by HR-MS/MS, using a user-defined feature list. The capability and effectiveness of FeatureHunter was demonstrated by analyzing various NA modifications induced by formaldehyde or chlorambucil in mixtures of calf thymus DNA, yeast RNA and proteins, and by analyzing the NA modifications present in the pooled urines of smokers and nonsmokers. The incorporation of FeatureHunter into the NA adductomics workflow offers a powerful tool for the identification and classification of various types of NA modifications induced by reactive chemicals in complex biological samples, providing a valuable resource for studying the exposome.

Peripheral insulin sensitivity predicting cognitive function in euthymic bipolar disorder patients.

OBJECTIVE: High prevalence of insulin resistance (IR) has been reported in bipolar disorder (BD) patients. Importantly, impaired insulin sensitivity could modulate the course and treatment outcome in BD. Here, we hypothesized that insulin sensitivity could be potentially associated with the neurocognitive trajectory in euthymic BD. We aimed to examine differences in insulin sensitivity and executive function between BD patients and controls. METHODS: Sixty-two patients with BD receiving mood stabilizer treatment and 62 controls, matching age, sex, and body mass index, were recruited in this study. Insulin sensitivity was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR). The Wisconsin card-sorting test (WCST) was applied to test participants' ability to shift cognitive set. Group differences were measured and multivariate regression analysis was performed to examine relationships among factors. RESULTS: The results indicated that the HOMA-IR (P = .048) value in the patients with BD were significantly higher than those in controls. With regards to executive function, the BD patients performed significantly poorer than the control subjects (P < .05). Moreover, the interaction effect between BD diagnosis and HOMA-IR value on the WCST-preservation errors was significant (P = .01), and post-hoc analyses showed that the cognitive abilities were worse in the BD patients with a higher IR than in the others groups. CONCLUSION: Insulin sensitivity is associated with the neurocognitive performance in euthymic BD patients. Although the underlying mechanisms remain unclear, interventions to improve insulin sensitivity could potentially improve the functional outcome of BD.

Add-on repetitive transcranial magnetic stimulation in patients with opioid use disorder undergoing methadone maintenance therapy.

Background: Repetitive transcranial magnetic stimulation (rTMS) shows potential therapeutic effects for individuals with addiction, but few studies have examined individuals with opioid use disorder (OUD).Objectives: We conducted an add-on double-blinded, sham-controlled rTMS feasibility pilot trial to examine OUD participants undergoing methadone maintenance therapy (MMT). The current report focused on the effects of rTMS on (1) craving and heroin use behavior and (2) depression, impulsivity, and attention.Methods: Active or sham rTMS treatment was applied to the left dorsolateral prefrontal cortex (DLPFC) over a total of 11 sessions in 4 weeks (15-Hz frequency, 4 seconds per train, intertrain interval of 26 seconds, 40 trains per session) in OUD participants (ClinicalTrials.gov registration number: NCT03229642). Craving, heroin use severity, urine morphine tests, the Hamilton Depression Rating Scale (HDRS), the Barratt Impulsiveness Scale-11 (BIS-11), and the Continuous Performance Tests (CPTs) were measured.Results: Twenty-two OUD participants were enrolled, of which eleven (8 males) were undergoing active rTMS and nine (8 males) were in the sham rTMS group. After 12 weeks of follow-up, the active rTMS group did not show significantly greater improvements than the sham group with respect to craving, heroin use, or urine morphine test results. However, HDRS scores, BIS-11 attentional subscales, and CPTs commission T-scores (C-TS) were significantly lower in the active rTMS group (P = .003, 0.04, and 0.02, respectively) than in the sham group.Conclusion: Add-on rTMS did not appear to improve heroin use behavior but may have benefitted depressive symptoms, impulse control and attention in OUD participants undergoing MMT.

Quantitative Proteomics Reveals the Dynamic Regulation of the Tomato Proteome in Response to Phytophthora infestans.

Late blight (LB) disease is a major threat to potato and tomato production. It is caused by the hemibiotrophic pathogen, Phytophthora infestans. P. infestans can destroy all of the major organs in plants of susceptible crops and result in a total loss of productivity. At the early pathogenesis stage, this hemibiotrophic oomycete pathogen causes an asymptomatic biotrophic infection in hosts, which then progresses to a necrotrophic phase at the later infection stage. In this study, to examine how the tomato proteome is regulated by P. infestans at different stages of pathogenesis, a data-independent acquisition (DIA) proteomics approach was used to trace the dynamics of the protein regulation. A comprehensive picture of the regulation of tomato proteins functioning in the immunity, signaling, defense, and metabolism pathways at different stages of P. infestans infection is revealed. Among the regulated proteins, several involved in mediating plant defense responses were found to be differentially regulated at the transcriptional or translational levels across different pathogenesis phases. This study increases understanding of the pathogenesis of P. infestans in tomato and also identifies key transcriptional and translational events possibly targeted by the pathogen during different phases of its life cycle, thus providing novel insights for developing a new strategy towards better control of LB disease in tomato.

Risks of post-traumatic stress disorder among emergency medical technicians who responded to the 2016 Taiwan earthquake.

BACKGROUND: Few studies have explored the field experiences and risk factors related to post-traumatic stress disorder (PTSD) among disaster rescue workers. METHODS: A 6.4-magnitude earthquake struck southern Taiwan on February 6, 2016. A standardized, paper-based, self-administered survey questionnaire including demographic information, field experiences and the Post-Traumatic Stress Disorder Checklist (PCL) was conducted among emergency medical technicians (EMTs) one month after the earthquake. A multivariate regression model was used to analyze the associations between risk factors and the PCL. A two-sided p value less than 0.05 was considered statistically significant. RESULTS: The survey response rate was 86.1% (447/519). The respondents who exceeded the cut-off points for the re-experience, avoidance, or hyperarousal domains were 11.8%, 2.7%, or 4.7%, respectively. A proportion of 12.7% of respondents met partial PTSD. The personality characteristics of anxiety (p < 0.001), perfectionism (p = 0.023) and introvert tendency (p = 0.002) were significantly correlated with partial PTSD. Emergency medical services (EMS) were significantly associated with partial PTSD than other main tasks (p < 0.001). The prevalence of partial PTSD was higher but was not significantly different in the groups of lower educational level, longer EMT careers, earlier arrival date, fewer field working hours, or managing dead people. Both univariate and multivariate logistic regression analyses showed that an anxious personality and EMS as the main task during the missions were significantly associated with PTSD risk. CONCLUSION: Not only personality characteristics but also the task components could alter the PTSD risks in disasters. A broad realization of these risks may improve the mental outcomes of disaster rescuers.

An improved scoring method for the identification of endogenous peptides based on the Mascot MS/MS ion search.

To identify endogenous peptides using MS/MS analysis and searching against a polypeptide sequence database, a non-enzyme specific (NES) search considering all of the possible proteolytic cleavages is required. However, the use of a NES search generates more false positive hits than an enzyme specific search, and therefore shows lower identification performance. In this study, the use of the sub-ranked matches for improving the identification performance of the Mascot NES search was investigated and a new scoring method was developed that considered the contribution of all sub-ranked random match probabilities, named the contribution score (CS). The CS showed the highest identification sensitivity using the Mascot NES search with a full protein database when compared to the use of the Mascot first ranked score and the delta score (DS). The confident peptides identified by DS and CS were shown to be complementary. When applied to plant endogenous peptide identification, the identification numbers of tomato endogenous peptides using DS and CS were 176.3% and 184.2%, respectively, higher than the use of the first ranked score of Mascot. The combination of DS and CS identified 200.0% and 8.6% more tomato endogenous peptides compared to the use of Mascot and DS, respectively. This method by combining the CS and DS can significantly improve the identification performance of endogenous peptides without complex computational steps and is also able to improve the identification performance of the enzyme specific search. In addition to the application in the plant peptidomics analysis, this method may be applied to the improvement of peptidomics studies in different species. A web interface for calculating the DS and CS based on Mascot search results was developed herein.

Application of Data-Independent Acquisition Approach to Study the Proteome Change from Early to Later Phases of Tomato Pathogenesis Responses.

Plants and pathogens are entangled in a continual arms race. Plants have evolved dynamic defence and immune mechanisms to resist infection and enhance immunity for second wave attacks from the same or different types of pathogenic species. In addition to evolutionarily and physiological changes, plant-pathogen interaction is also highly dynamic at the molecular level. Recently, an emerging quantitative mass spectrometry-based proteomics approach named data-independent acquisition (DIA), has been developed for the analysis of the proteome in a high-throughput fashion. In this study, the DIA approach was applied to quantitatively trace the change in the plant proteome from the early to the later stage of pathogenesis progression. This study revealed that at the early stage of the pathogenesis response, proteins directly related to the chaperon were regulated for the defence proteins. At the later stage, not only the defence proteins but also a set of the pathogen-associated molecular pattern-triggered immunity (PTI) and effector triggered immunity (ETI)-related proteins were highly induced. Our findings show the dynamics of the plant regulation of pathogenesis at the protein level and demonstrate the potential of using the DIA approach for tracing the dynamics of the plant proteome during pathogenesis responses.

Respiratory symptoms among search and rescue workers who responded to the 2016 Taiwan earthquake.

OBJECTIVES: High respiratory hazards among search and rescue workers (SRWs) emerged after the World Trade Center attacks on 11 September 2001. There have been limited studies on respiratory symptoms among earthquake SRWs. We investigated the respiratory symptoms and the use of respiratory protective equipment among the SRWs who responded to the 2016 Taiwan earthquake. METHODS: On 6 February 2016, a 6.4-magnitude earthquake struck southern Taiwan and caused 513 injuries and 117 deaths. During the 9-day field operation, 519 firefighters affiliated with the Tainan City Government Fire Bureau participated in the search and rescue response. A standardised, self-completed questionnaire was used to collect data on demographics, dust exposures, personal protective measures and health outcomes 3 weeks after the earthquake. Descriptive and multivariate analyses adjusting for demographics and exposure variables were performed for new or worsened outcomes. RESULTS: Of the 519 SRWs, 414 (80%) responded to the questionnaire. Of these SRWs, 153 (37%) reported new or worsened respiratory symptoms, with cough (23%) as the leading symptom, followed by rhinorrhoea or nasal congestion (22%) and chest tightness (6%). More than 90% of the symptoms persisted to the third week after the earthquake. The prevalence of new or worsened respiratory symptoms was significantly higher among SRWs with a higher level of exposure to dust. Prior training in response to respiratory pollutants was only 5%. CONCLUSIONS: There were significant respiratory hazards among earthquake SRWs. The persistent symptoms and low coverage of training warrant further regular examination and occupational health programmes.

Quantitative peptidomics study reveals that a wound-induced peptide from PR-1 regulates immune signaling in tomato.

Many important cell-to-cell communication events in multicellular organisms are mediated by peptides, but only a few peptides have been identified in plants. In an attempt to address the difficulties in identifying plant signaling peptides, we developed a novel peptidomics approach and used this approach to discover defense signaling peptides in plants. In addition to the canonical peptide systemin, several novel peptides were confidently identified in tomato (Solanum lycopersicum) and quantified to be induced by both wounding and methyl jasmonate (MeJA). A wounding or wounding plus MeJA-induced peptide derived from the pathogenesis-related protein 1 (PR-1) family was found to induce significant antipathogen and minor antiherbivore responses in tomato. This study highlights a role for PR-1 in immune signaling and suggests the potential application of plant endogenous peptides in efforts to defeat biological threats in crop production. As PR-1 is highly conserved across many organisms and the putative peptide from At-PR1 was also found to be bioactive in Arabidopsis thaliana, our results suggest that this peptide may be useful for enhancing resistance to stress in other plant species.

Unaltered Dopamine Transporter Availability in Drug-Naive Patients With Schizophrenia After 6 Months of Antipsychotics Treatment: A Naturalistic Study.

BACKGROUND: Dopaminergic dysfunction, namely, dopamine transporter (DAT) availability variations in patients with drug-naive schizophrenia after long-term treatment, is still not well understood. The aims of the study were to explore (i) whether the DAT availability in patients with drug-naive schizophrenia differed after antipsychotic treatment and (ii) whether treatment with different generations of antipsychotics influenced the DAT availability after follow-up for 6 months. METHODS: Twenty-four first-episode, drug-naive patients with schizophrenia were divided into first- and second-generation antipsychotic groups naturalistically. After 6 months of follow-up, 7 patients who received first-generation antipsychotic treatment and 17 patients who received second-generation antipsychotic treatment completed the study. The patients underwent premedication and 6-month follow-up measurements using single-photon emission computed tomography with technetium Tc 99m (Tc) TRODAT-1. Psychopathological evaluations and adverse effects were recorded using appropriate scales. RESULTS: Both of the treatment groups significantly improved according to Positive and Negative Symptoms Scale evaluation. However, no significant difference was noticed between the premedication and 6-month follow-up DAT scans. Nonsignificant differences existed even in the groups of different generations of antipsychotics. CONCLUSIONS: Improvements in psychotic symptoms in patients with schizophrenia may not be influenced by DAT availability, even under treatment with different antipsychotics for a sufficient treatment period.

Coexisting geriatric anxiety and depressive disorders may increase the risk of ischemic heart disease mortality-a nationwide longitudinal cohort study.

OBJECTIVES: In the elderly, the risk of mortality because of physical illnesses related to anxiety disorders varies with potential confounding influences, including comorbidity with depressive disorders. Our study aimed to explore (i) whether anxiety disorders increase the risk of mortality in the elderly, and (ii) whether the risk of mortality mediated by anxiety and depressive disorders differs between physical illnesses. METHODS: Our longitudinal cohort study included subjects aged over 60 years from the National Health Insurance Research Database. One thousand and eighty-six subjects with anxiety disorders and 50 554 control subjects without anxiety disorders were included. Propensity score-matched cohorts were analyzed. Rate ratios (RRs) were calculated for the risk of mortality associated with different physical illnesses with comorbidities of either anxiety disorders only or both anxiety and depressive disorders. RESULTS: The risk of mortality in patients with anxiety disorders was significantly higher than controls, and was even higher when subjects had both anxiety and depressive disorder comorbidities. Furthermore, the co-occurrence of anxiety and depressive disorders increased the risk of mortality in elderly patients with ischemic heart diseases (RR = 1.60; 95% CI: 1.14-2.24). CONCLUSIONS: Coexisting anxiety and depressive disorders could increase the risk of mortality in elderly patients with ischemic heart diseases. Copyright © 2016 John Wiley & Sons, Ltd.

Coexisting anxiety disorders alter associations with physical disorders in the elderly: A Taiwan cross-sectional nationwide study.

AIM: We used population-based analyses to explore whether anxiety disorders are associated with certain physical illnesses, as previous studies have suggested, and whether a greater number of comorbid anxiety disorders would influence physical illnesses in the elderly. METHODS: Using the National Health Insurance Research Database, we included subjects aged over 60 years. The study included 954 subjects with anxiety disorders (as defined by the ICD-9-CM) and 4770 control subjects without anxiety disorders. Odds ratios (OR) were calculated for the risks of physical illnesses in both groups. RESULTS: Subjects with anxiety disorders had higher OR for cardiovascular disease (OR = 1.33-2.80), cerebrovascular disease (OR = 2.07), peptic ulcer (OR = 3.41), and hyperlipidemia (OR = 2.99). Furthermore, a greater number of comorbid anxiety disorders may further increase the OR of the aforementioned physical illnesses, except for peripheral vascular disorder, when compared to those without anxiety disorders. CONCLUSION: Elderly subjects with more anxiety disorders may be associated with vascular and metabolic problems. Clinicians should carefully assess the physical illnesses of elderly patients with anxiety disorders.

Peripheral inflammation is associated with impaired sadness recognition in euthymic bipolar patients.

BACKGROUND: Inflammation impairs cognitive function in healthy individuals and people with psychiatric disorders, such as bipolar disorder (BD). This effect may also impact emotion recognition, a fundamental element of social cognition. Our study aimed to investigate the relationships between pro-inflammatory cytokines and emotion recognition in euthymic BD patients and healthy controls (HCs). METHODS: We recruited forty-four euthymic BD patients and forty healthy controls (HCs) and measured their inflammatory markers, including high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and TNF-α. We applied validated cognitive tasks, the Wisconsin Card-Sorting Test (WCST) and Continuous Performance Test (CPT), and a social cognitive task for emotion recognition, Diagnostic Analyses of Nonverbal Accuracy, Taiwanese Version (DANVA-2-TW). We analyzed the relationships between cytokines and cognition and then explored possible predictive factors of sadness recognition accuracy. RESULTS: Regarding pro-inflammatory cytokines, TNF-α was elevated in euthymic BD patients relative to HCs. In euthymic BD patients only, higher TNF-α levels were associated with lower accuracy of sadness recognition. Regression analysis revealed that TNF-α was an independent predictive factor of sadness recognition in patients with euthymic BD when neurocognition was controlled for. CONCLUSIONS: We demonstrated that enhanced inflammation, indicated by increased TNF-α, was an independent predictive factor of impaired sadness recognition in BD patients but not in HCs. Our findings suggested a direct influence of TNF-α on sadness recognition and indicated vulnerability to depression in euthymic BD patients with chronic inflammation.

Machine learning for prediction of schizophrenia based on identifying the primary and interaction effects of minor physical anomalies.

In the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) are considered neurodevelopmental markers of schizophrenia. To date, there has been no research to evaluate the interaction between MPAs. Our study built and used a machine learning model to predict the risk of schizophrenia based on measurements of MPA items and to investigate the potential primary and interaction effects of MPAs. The study included 470 patients with schizophrenia and 354 healthy controls. The models used are classical statistical model, Logistic Regression (LR), and machine leaning models, Decision Tree (DT) and Random Forest (RF). We also plotted two-dimensional scatter diagrams and three-dimensional linear/quadratic discriminant analysis (LDA/QDA) graphs for comparison with the DT dendritic structure. We found that RF had the highest predictive power for schizophrenia (Full-training AUC = 0.97 and 5-fold cross-validation AUC = 0.75). We identified several primary MPAs, such as the mouth region, high palate, furrowed tongue, skull height and mouth width. Quantitative MPA analysis indicated that the higher skull height and the narrower mouth width, the higher the risk of schizophrenia. In the interaction, we further identified that skull height and mouth width, furrowed tongue and skull height, high palate and skull height, and high palate and furrowed tongue, showed significant two-item interactions with schizophrenia. A weak three-item interaction was found between high palate, skull height, and mouth width. In conclusion, we found that the two machine learning methods showed good predictive ability in assessing the risk of schizophrenia using the primary and interaction effects of MPAs.

Wolfberry genome database: integrated genomic datasets for studying molecular biology.

Wolfberry, also known as goji berry or Lycium barbarum, is a highly valued fruit with significant health benefits and nutritional value. For more efficient and comprehensive usage of published L. barbarum genomic data, we established the Wolfberry database. The utility of the Wolfberry Genome Database (WGDB) is highlighted through the Genome browser, which enables the user to explore the L. barbarum genome, browse specific chromosomes, and access gene sequences. Gene annotation features provide comprehensive information about gene functions, locations, expression profiles, pathway involvement, protein domains, and regulatory transcription factors. The transcriptome feature allows the user to explore gene expression patterns using transcripts per kilobase million (TPM) and fragments per kilobase per million mapped reads (FPKM) metrics. The Metabolism pathway page provides insights into metabolic pathways and the involvement of the selected genes. In addition to the database content, we also introduce six analysis tools developed for the WGDB. These tools offer functionalities for gene function prediction, nucleotide and amino acid BLAST analysis, protein domain analysis, GO annotation, and gene expression pattern analysis. The WGDB is freely accessible at https://cosbi7.ee.ncku.edu.tw/Wolfberry/. Overall, WGDB serves as a valuable resource for researchers interested in the genomics and transcriptomics of L. barbarum. Its user-friendly web interface and comprehensive data facilitate the exploration of gene functions, regulatory mechanisms, and metabolic pathways, ultimately contributing to a deeper understanding of wolfberry and its potential applications in agronomy and nutrition.

UniQua: a universal signal processor for MS-based qualitative and quantitative proteomics applications.

Recent developments in high resolution mass spectrometry (HR-MS) technology have ushered proteomics into a new era. However, the importance of using a common, open data platform for signal processing of HR-MS spectra has not been sufficiently addressed. In this study, a MS signal processor was developed to facilitate data integration from different instruments and different proteomics approaches into a unified platform without compromising protein identification and quantitation performance. This processor supports parallel processing capability which allows full utilization of computing resources to speed up signal processing performance to >1 gigabytes/min. The storage space occupied by the processed MS data can be reduced to ~10%, which helps the analysis and management of large quantities of data from comprehensive proteomics studies. For quantitation at the MS level, processing accuracy is improved and processing time for ASAPRatio is reduced to ~50%. For quantitation at the MS/MS level, accurate reporter ion ratios from different instruments can be directly determined by the processed MS/MS spectra and reported in the Mascot search result directly without using specialized iTRAQ software.

Taiwan consensus on biological treatment of bipolar disorder during the acute, maintenance, and mixed phases: The 2022 update.

BACKGROUND: Bipolar disorder is a mood dysregulation characterized by recurrent symptoms and episodes of mania, hypomania, depression, and mixed mood. The complexity of treating patients with bipolar disorder prompted the Taiwanese Society of Biological Psychiatry and Neuropsychopharmacology (TSBPN) to publish the first Taiwan consensus on pharmacological treatment of bipolar disorders in 2012. This paper presents the updated consensus, with changes in diagnostic criteria (i.e., mixed features) and emerging pharmacological evidence published up to April 2022. METHODS: Our working group systemically reviewed the clinical research evidence and international guidelines and determined the levels of evidence for each pharmacological treatment on the basis of the most recent World Federation of Societies of Biological Psychiatry grading system. Four clinical-specific issues were proposed. The current TSBPN Bipolar Taskforce then discussed research evidence and clinical experience related to each treatment option in terms of efficacy and acceptability and then appraised final recommendation grades through anonymous voting. RESULTS: In the updated consensus, we include the pharmacological recommendations for bipolar disorder with mixed features considering its high prevalence, the severe clinical prognosis, and the absence of approved medications. Cariprazine, lurasidone, repetitive transcranial magnetic stimulation, and ketamine are incorporated as treatment options. In the maintenance phase, the application of long-acting injectable antipsychotics is emphasized, and the hazards of using antidepressants and conventional antipsychotics are proposed. CONCLUSIONS: This updated Taiwan consensus on pharmacological treatment for bipolar disorder provides concise evidence-based and empirical recommendations for clinical psychiatric practice. It may facilitate treatment outcome improvement in patients with bipolar disorder.

Which Severe Mental Illnesses Most Increase the Risk of Developing Dementia? Comparing the Risk of Dementia in Patients with Schizophrenia, Major Depressive Disorder and Bipolar Disorder.

Objective: Previous studies have shown that certain severe mental illnesses (SMIs) increase the risk of dementia, but those that increase the risk to a greater degree in comparison with other SMIs are unknown. Furthermore, physical illnesses may alter the risk of developing dementia, but these cannot be well-controlled. Methods: Using the Taiwan National Health Insurance Research Database, patients with schizophrenia, bipolar disorder and major depressive disorder (MDD) were recruited. We also recruited normal healthy subjects as the control group. All subjects were aged over 60 years, and the duration of follow-up was from 2008 to 2015. Multiple confounders were adjusted, including physical illnesses and other variables. Use of medications, especially benzodiazepines, was analyzed in a sensitivity analysis. Results: 36,029 subjects (MDD: 23,371, bipolar disorder: 4,883, schizophrenia: 7,775) and 108,084 control subjects were recruited after matching according to age and sex. The results showed that bipolar disorder had the highest hazard ratio (HR) (HR: 2.14, 95% confidence interval [CI]: 1.99-2.30), followed by schizophrenia (HR: 2.06, 95% CI: 1.93-2.19) and MDD (HR: 1.60, 95% CI: 1.51-1.69). The results remained robust after adjusting for covariates, and sensitivity analysis showed similar results. Anxiolytics use did not increase the risk of dementia in any of the three groups of SMI patients. Conclusion: SMIs increase the risk of dementia, and among them, bipolar disorder confers the greatest risk of developing dementia. Anxiolytics may not increase the risk of developing dementia in patients with an SMI, but still need to be used with caution in clinical practices.