Comparing the performance of ChatGPT GPT-4, Bard, and Llama-2 in the Taiwan Psychiatric Licensing Examination and in differential diagnosis with multi-center psychiatrists.

AIM: Large language models (LLMs) have been suggested to play a role in medical education and medical practice. However, the potential of their application in the psychiatric domain has not been well-studied. METHOD: In the first step, we compared the performance of ChatGPT GPT-4, Bard, and Llama-2 in the 2022 Taiwan Psychiatric Licensing Examination conducted in traditional Mandarin. In the second step, we compared the scores of these three LLMs with those of 24 experienced psychiatrists in 10 advanced clinical scenario questions designed for psychiatric differential diagnosis. RESULT: Only GPT-4 passed the 2022 Taiwan Psychiatric Licensing Examination (scoring 69 and ≥ 60 being considered a passing grade), while Bard scored 36 and Llama-2 scored 25. GPT-4 outperformed Bard and Llama-2, especially in the areas of 'Pathophysiology & Epidemiology' (χ2 = 22.4, P < 0.001) and 'Psychopharmacology & Other therapies' (χ2 = 15.8, P < 0.001). In the differential diagnosis, the mean score of the 24 experienced psychiatrists (mean 6.1, standard deviation 1.9) was higher than that of GPT-4 (5), Bard (3), and Llama-2 (1). CONCLUSION: Compared to Bard and Llama-2, GPT-4 demonstrated superior abilities in identifying psychiatric symptoms and making clinical judgments. Besides, GPT-4's ability for differential diagnosis closely approached that of the experienced psychiatrists. GPT-4 revealed a promising potential as a valuable tool in psychiatric practice among the three LLMs.

The now and future of ChatGPT and GPT in psychiatry.

ChatGPT has sparked extensive discussions within the healthcare community since its November 2022 release. However, potential applications in the field of psychiatry have received limited attention. Deep learning has proven beneficial to psychiatry, and GPT is a powerful deep learning-based language model with immense potential for this field. Despite the convenience of ChatGPT, this advanced chatbot currently has limited practical applications in psychiatry. It may be used to support psychiatrists in routine tasks such as completing medical records, facilitating communications between clinicians and with patients, polishing academic writings and presentations, and programming and performing analyses for research. The current training and application of ChatGPT require using appropriate prompts to maximize appropriate outputs and minimize deleterious inaccuracies and phantom errors. Moreover, future GPT advances that incorporate empathy, emotion recognition, personality assessment, and detection of mental health warning signs are essential for its effective integration into psychiatric care. In the near future, developing a fully-automated psychotherapy system trained for expert communication (such as psychotherapy verbatim) is conceivable by building on foundational GPT technology. This dream system should integrate practical 'real world' inputs and friendly AI user and patient interfaces via clinically validated algorithms, voice comprehension/generation modules, and emotion discrimination algorithms based on facial expressions and physiological inputs from wearable devices. In addition to the technology challenges, we believe it is critical to establish generally accepted ethical standards for applying ChatGPT-related tools in all mental healthcare environments, including telemedicine and academic/training settings.

Kawasaki disease in childhood and psychiatric disorders: A population-based case-control prospective study in Taiwan.

BACKGROUND: Kawasaki disease (KD) is a common childhood acute inflammatory disease and potentially triggers a chronic inflammation. Although some researches have investigated neurodevelopmental consequences following KD, the findings have been inconsistent. This is the first population-based study targeted on KD and common psychiatric disorders. OBJECTIVES: We aimed to investigate the association between KD and psychiatric disorders and hypothesized that standard anti-inflammatory treatment by intravenous immunoglobulin (IVIG) may protect against development of psychiatric disorders. METHOD: We retrieved data from Taiwan's National Health Insurance Research database (NHIRD). Patients (n = 282,513) with psychiatric disorders (the case group) during 1997-2013 were included, and the control group was matched with age, sex, income and urbanization (1:1). We calculated the prevalence of KD in both groups and estimated odd ratios (ORs) and 95% confidence intervals (CIs) in the subgroup analyses for KD in conditions of age, severity, and common psychiatric comorbidity. RESULTS: Numbers of patients with KD were 460 in the cases and 380 in the controls (p = .006), and the crude OR of KD was 1.21 times greater (95% CI = 1.06-1.39, p = .006) in the case than the control groups. KD patients without IVIG treatment (n = 126) were higher in the cases than those in the controls (n = 54), with the OR of 2.33 (95% CI = 1.70-3.21, p < .0001). Subgroup analyses showed that KD survivors were at significant risk for autism spectrum disorders (ASD) (OR = 2.15, 95% CI = 1.27-3.65; p = .005) and attention deficit and hyperactivity disorders (ADHD) (OR = 1.19, 95% CI = 1.02-1.39; p = 0.03), and a trend of increased risk for anxiety disorders (OR = 1.36, 95%CI = 0.99-1.86; p = 0.05). CONCLUSIONS: Patients with KD were more likely to have comorbid psychiatric disorders, including ASD and ADHD. Moreover, anti-inflammatory treatment with IVIG may have potential prophylactic effects against the development of psychiatric disorders.

Genetic Variations of Ionotropic Glutamate Receptor Pathways on Interferon-α-induced Depression in Patients with Hepatitis C Viral Infection.

IMPORTANCE: The most supportive evidence of the inflammation theory of depression is that up to one-third of patients with Hepatitis C virus infection (HCV) develop clinical depressive episodes during interferon-α (IFN-α) therapy. As glutamate-mediated excitotoxicity has been found to be a consequence of excessive inflammation and a pathogenic mechanism of depression, it is plausible to investigate genes on ionotropic glutamate receptor pathways. OBJECTIVE: To identify the at-risk genetic variations on ionotropic glutamate receptor pathways for interferon-α-induced depression. METHOD: We assessed 291 patients with chronic HCV undergoing IFN-α therapy and analyzed the single nucleotide polymorphisms (SNPs) in genes related to ionotropic glutamate receptors in this prospective case-control study. Patients who developed IFN-α-induced depression anytime during the treatment were defined as the case group, while those who did not were defined as the control group. Genomic DNA was extracted from peripheral blood and analyzed by Affymetrix TWB array. Allelic and haplotype association tests were conducted using χ2 tests to assess the difference in allele and haplotype frequencies between cases and controls. Additionally, we performed 5000 permutations to control gene-wide family-wise error rates and create empirical p-values. Stratified analyses were then done to control for confounders and adjust odds ratios for our significant SNPs. We also did an additional stratified analysis to re-assess genes with near-significant SNPs (empirical p-value=0.05-0.10), employing Bonferroni correction with the effective number of independent tests to control gene-wide family-wise error rates. RESULTS: The minor and major allele frequencies of rs7542 (empirical p-value=0.0310) in MAPK3, rs3026685 (empirical p-value=0.0378) in PICK1, rs56005409 (empirical p-value=0.0332) in PRKCA, rs12914792 (empirical p-value=0.0096), rs17245773 (empirical p-value=0.0340) in RASGRF1, and rs78387863 (empirical p-value=0.0086), rs74365480 (empirical p-value=0.0200) in RASGRF2 were found significantly different between cases and controls. Haplotype association tests also revealed one significant haplotype in PRKCA (empirical p-value=0.0200) and one in RASGRF1 (empirical p-value=0.0048). Stratified analyses showed no signs of confounders for most of our significant SNPs, except for rs78387863 in RASGRF2. After a re-assessment of our near-significant genes by stratified analyses, two SNPs in GRIN2B turned significant. CONCLUSIONS: This study provided supportive evidence of the involvement of the RAS/RAF/mitogen-activated protein kinase (MAPK) signaling pathway and glutamate ionotropic receptor AMPA type subunit 2(GluR2) transportation in the pathogenesis of IFN-α-induced depression.

Identification of Genetic Variations in the NAD-Related Pathways for Patients with Major Depressive Disorder: A Case-Control Study in Taiwan.

Background and Objectives: Nicotinamide adenine dinucleotide (NAD) is an important coenzyme in various physiological processes, including sirtuins (SIRTs) and kynurenine pathway (KP). Previous studies have shown that lower NAD levels can be indicative of increased risks of cancer and psychiatric disorders. However, there has been no prior study exploring the link between NAD homeostasis and psychiatric disorders from a genetic perspective. Therefore, we aimed to investigate the association of genetic polymorphism in the pathways of NAD biosynthesis with major depressive disorder (MDD). Methods: A total of 317 patients were included in the case group and were compared with sex-matched control group of 1268 participants (1:4 ratio) from Taiwan Biobank (TWB). All subjects in the control group were over 65 years old, which is well past the average age of onset of MDD. Genomic DNA extracted from patients' blood buffy coat was analyzed using the Affymetrix TWB array. Full-model tests were conducted for the analysis of single nucleotide polymorphism (SNPs) in all candidate genes. We focused on genes within the NAD-related candidate pathways, including 15 in KP, 12 in nicotinate metabolism, 7 in SIRTs, and 19 in aldehyde dehydrogenases (ALDHs). A total of 508 SNPs were analyzed in this study. After significant SNPs were determined, 5000 genome-wide max(T) permutations were performed in Plink. Finally, we built a predictive model with logistic regression and assessed the interactions of SNPs with the haplotype association tests. Results: We found three SNPs that were significantly associated with MDD in our NAD-related candidate pathways, one within the KP (rs12622574 in ACMSD) and two within the nicotinate metabolism (rs28532698 in BST1 and rs3733593 in CD38). The observed association with MDD was significant in the dominant model of inheritance with marital status, education level, and body mass index (BMI) adjusted as covariates. Lastly, in haplotype analysis, the three associated SNPs consisted of one haploblock in ACMSD, four haploblocks in BST1, and two haploblocks in CD38. Conclusions: This study provides the first evidence that genetic variations involved in NAD homeostasis in the KP and nicotinate metabolism may be associated with the occurrence of MDD.

Predictive Genetic Variations in the Kynurenine Pathway for Interferon-α-Induced Depression in Patients with Hepatitis C Viral Infection.

Importance: The high incidence of major depressive episodes during interferon-α (IFN-α) therapy is considered the most powerful supportive evidence for the inflammation theory of depression. As the kynurenine pathway plays an important role connecting inflammation and depression, it is plausible to investigate this pathway for predictive genetic markers for IFN-α-induced depression. Methods: In this prospective case-control study, we assessed 291 patients with chronic hepatitis C viral infection taking IFN-α therapy and analyzed the single nucleotide polymorphisms (SNPs) in genes in the kynurenine pathway. Our case group contained patients who developed IFN-α-induced depression during the treatment, and others were defined as the control group. Genomic DNA was extracted from leukocytes in the peripheral blood and analyzed by Affymetrix TWB array. We first tested allelic, dominant, and recessive models on each of our SNPs using Fisher's exact test. We then conducted 5000 gene-wide max(T) permutations based on the best model of each SNP to provide strong gene-wide family-wise error rate control. Finally, we preformed logistic regression for the significant SNPs acquired in previous procedures, with sex and education level as covariates to build predictive models. Additional haplotype analyses were conducted with Haploview 4.2 to investigate the combining effect of multiple significant SNPs within a gene. Results: With sex and education level as covariates, rs8082252 (p = 0.0015, odds ratio = 2.716), rs8082142 (p = 0.0031, odds ratio = 2.499) in arylformamidase (AFMID), and rs12477181 (p = 0.0004, odds ratio = 0.3478) in kynureninase (KYNU) were significant in logistic regression models with dominant modes of inheritance. Haplotype analyses showed the two significant SNPs in AFMID to be in the same haploblock and highly correlated (r2 = 0.99). There were two significant haplotypes (by the sequence of rs8082252, rs8082142): AT (χ2 = 7.734, p = 0.0054) and GC (χ2 = 6.874, p = 0.0087). Conclusions: This study provided supportive evidence of the involvement of the kynurenine pathway in IFN-α-induced depression. SNPs in this pathway were also predictive of this disease.