Genome-wide association studies in East Asian populations have identified the gene variant, rs12415800, of the Sirtuin 1 gene (SIRT1) as a major depressive disorder (MDD) risk locus with the A allele conferring increased risk. Accumulating evidence suggests that SIRT1-related genetic effects extend beyond MDD.

To investigate the association between rs12415800 and bipolar disorder, with additional analysis of MDD.

We analysed data from the Taiwan Biobank linked to the National Health Insurance Research Database, including 145 780 participants of Han Chinese ancestry. Clinically diagnosed bipolar disorder and MDD were identified using standardised ICD-9-CM and ICD-10-CM codes. Multivariable logistic regression models were applied with the GG genotype as the reference, adjusting for age and sex. Stratified analyses were conducted by age group and sex.

Both the rs12415800 AG and AA genotypes were associated with an increased risk of bipolar disorder. Compared with GG genotype carriers, AA genotype carriers had a significantly higher risk of bipolar disorder overall (adjusted odds ratio (aOR) = 1.20, 95% CI = 1.05–1.37), particularly among participants aged ≥50 years (aOR = 1.38, 95% CI = 1.14–1.68). The overall and age-stratified associations remained materially similar after excluding participants with schizophrenia or schizo-affective disorder, although sex-specific findings were inconsistent.

Our findings suggest that genetic variation near SIRT1, particularly the rs12415800 risk A allele, may be associated with bipolar disorder susceptibility, especially among older individuals. Given prior evidence linking this allele to reduced SIRT1 mRNA expression, further investigation of SIRT1-related pathways in the pathophysiology of bipolar disorder is warranted.

Betel quid chewing (BQC) is a common psychoactive habit in Taiwan and other Asian regions. Evidence regarding its association with specific psychiatric disorders remains limited. This study examined associations between BQC assessed at Taiwan Biobank enrolment and major psychiatric disorders recorded in linked health-insurance claims data.

We analysed 51,522 male participants from the Taiwan Biobank successfully linked to the National Health Insurance Research Database, including 7,973 ever-users (BQC) and 43,549 never-users of betel quid (non-BQC). Psychiatric disorders included schizophrenia, bipolar disorder, major depressive disorder (MDD), depressive disorders, obsessive-compulsive disorder (OCD), panic disorder, generalized anxiety disorder, attention-deficit/hyperactivity disorder (ADHD) and dementia. Multivariable logistic regression models were constructed with sequential adjustment for age, claims-record ascertainment period, education, urbanization, cigarette smoking and alcohol drinking. No correction for multiple testing was applied across the nine psychiatric outcomes.

Compared with non-users, BQC users were older, had lower educational attainment and had markedly higher prevalence of cigarette smoking and alcohol drinking. In crude analyses, BQC was associated with higher odds of schizophrenia, bipolar disorder, MDD, depressive disorders, and panic disorder but lower odds of OCD and ADHD. After full adjustment, BQC remained associated with depressive disorders (adjusted OR: 1.19, 95% CI: 1.09–1.31). An exploratory inverse estimate for OCD (adjusted OR: 0.62, 95% CI: 0.39–0.98) was based on only 24 exposed cases. All estimates were nominal because no correction for multiple testing was applied.

In these linked Taiwanese data, BQC was modestly associated with depressive disorders, whereas associations with most other psychiatric conditions were attenuated after adjustment for sociodemographic and lifestyle factors. As BQC was assessed at a single time point and psychiatric diagnoses could predate or follow that assessment, the findings represent associations and do not establish temporality or causality.

The association between geriatric depression and out-of-hospital cardiac arrest (OHCA) has not been fully clarified.

This study aimed to develop and validate a predictive model for OHCA in older patients through a longitudinal, population-based approach.

This study analysed data from the National Health Insurance Research Database for the period 2011–2020, focusing on older patients both diagnosed with depression and treated with antidepressant medications. A multivariate logistic regression model was used to identify potential predictors of OHCA. Considering the effect of COVID-19, data-sets from 2019 and 2020 were used as external validation. The model’s performance was evaluated using receiver operating characteristic (ROC) curves and confusion matrix metrics.

Out of 104 022 geriatric patients with depression, 2479 (2.4%) experienced OHCA. Significant predictors of OHCA included age, male gender, previous utilisation of medical resources, renal failure with haemodialysis, existing comorbidities, medication changes and recent psychotherapy. The ROC values for the predictive models ranged from 0.707 to 0.771 in the 2019 and 2020 external validations for 7-, 30- and 90-day OHCA. For 2019, the 7-day model demonstrated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of 0.600, 0.718, 2.130, 0.560 and 3.840, respectively. For 2020, these metrics for the 7-day model were 0.775, 0.655, 2.250, 0.340 and 6.550, respectively.

This study developed and validated a predictive model for OHCA in older patients with depression. The model identified crucial predictors, providing valuable insights for psychiatrists and emergency clinicians to identify high-risk patients and implement early preventive measures.