Use of atypical antipsychotics and risks of cataract development in patients with schizophrenia: A population-based, nested case-control study

Search of inhibitors of aldose reductase for treatment of diabetic cataracts using machine learning

Purpose

Patients with diabetes mellitus have an elevated chance of developing cataracts, a degenerative vision-impairing condition often needing surgery. The process of the reduction of glucose to sorbitol in the lens of the human eye that causes cataracts is managed by the Aldose Reductase Enzyme (AR), and it is been found that AR inhibitors may mitigate the onset of diabetic cataracts. There exists a large pool of natural and synthetic AR inhibitors that can prevent diabetic complications, and the development of a machine-learning (ML) prediction model may bring new AR inhibitors with better characteristics into clinical use.

Methods

Using known AR inhibitors and their chemical-physical descriptors we created the ML model for prediction of new AR inhibitors. The predicted inhibitors were tested by computational docking to the binding site of AR.

Results

Using cross-validation in order to find the most accurate ML model, we ended with final cross-validation accuracy of 90%. Computational docking testing of the predicted inhibitors gave a high level of correlation between the ML prediction score and binding free energy.

Conclusions

Currently known AR inhibitors are not used yet for patients for several reasons. We think that new predicted AR inhibitors have the potential to possess more favorable characteristics to be successfully implemented after clinical testing. Exploring new inhibitors can improve patient well-being and lower surgical complications all while decreasing long-term medical expenses.

Deep Neural Network to Differentiate Brain Activity Between Patients With First-Episode Schizophrenia and Healthy Individuals: A Multi-Channel Near Infrared Spectroscopy Study

Backgrounds: Reduced brain cortical activity over the frontotemporal regions measured by near infrared spectroscopy (NIRS) has been reported in patients with first-episode schizophrenia (FES). This study aimed to differentiate between patients with FES and healthy controls (HCs) on basis of the frontotemporal activity measured by NIRS with a support vector machine (SVM) and deep neural network (DNN) classifier. In addition, we compared the accuracy of performance of SVM and DNN. Methods: In total, 33 FES patients and 34 HCs were recruited. Their brain cortical activities were measured using NIRS while performing letter and category versions of verbal fluency tests (VFTs). The integral and centroid values of brain cortical activity in the bilateral frontotemporal regions during the VFTs were selected as features in SVM and DNN classifier. Results: Compared to HCs, FES patients displayed reduced brain cortical activity over the bilateral frontotemporal regions during both types of VFTs. Regarding the classifier performance, SVM reached an accuracy of 68.6%, sensitivity of 70.1%, and specificity of 64.6%, while DNN reached an accuracy of 79.7%, sensitivity of 88.8%, and specificity of 74.9% in the classification of FES patients and HCs. Conclusions: Compared to findings of previous structural neuroimaging studies, we found that using DNN to measure the NIRS signals during the VFTs to differentiate between FES patients and HCs could achieve a higher accuracy, indicating that NIRS can be used as a potential marker to classify FES patients from HCs. Future additional independent datasets are needed to confirm the validity of our model.

Associations among antipsychotics, metabolism-related diseases, and cataracts in patients with schizophrenia: A retrospective cohort study

BACKGROUND

Long-term cataract risks associated with first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs), and their associations with metabolism-related diseases are not yet elucidated.

METHODS

Using Taiwan National Health Insurance data, we conducted a propensity score matched population-based cohort study consisting of 10,014 patients with newly diagnosed schizophrenia from 2005 to 2009 and followed them until the end of 2013. A Cox hazard model with metabolism-related diseases as time-dependent covariates was adapted to estimate the hazard ratio (HR) of cataracts between SGAs and FGAs groups.

RESULTS

During the 8-year follow-up, patients receiving SGAs were associated with a higher risk of cataract than those receiving FGAs with an adjusted HR of 1.59 (95% confidence interval [CI] = 1.06-2.36). Patients receiving high-metabolic-risk SGAs (clozapine and olanzapine) showed the highest risk of cataracts among SGAs when compared with those receiving FGAs (aHR = 2.57, 95% CI: 1.35-4.88). SGAs demonstrated a stronger contribution in the risk of cataract in patients without diabetes mellitus (DM) and hyperlipidemia than in those developed these diseases. Patients who developed DM or hyperlipidemia after receiving antipsychotics had an approximately 2.5-fold increased cataract risk over those who did not develop these diseases.

CONCLUSIONS

Regardless of the condition of metabolic-related diseases, SGAs were independently associated with an increased risk of cataract. DM and hyperlipidemia developed after antipsychotics contributed to the risk of cataract risk.

Associations between use of mood stabilizers and risk of cataract: A population-based nested case-control study

BACKGROUND

The aim of this study was to investigate whether use of mood stabilizers (MS) is associated with an increased risk of cataract development.

METHODS

We conducted a nested case-control study using National Health Insurance Research Database in Taiwan. A total of 14,288 patients with bipolar disorder (BD) and schizophrenia were included; 7651 in the cataract group and 6637 in the control group. Based on overall cumulative period of MS (lithium, carbamazepine, valproate, and lamotrigine) treatment, we categorized into following groups: no use, and duration < 1 year, 1 to 2 years, and > 2 years. Conditional logistic regression analysis was used to explore the association between use of MS and risk of cataract development.

RESULTS

The risks for cataract development were significantly higher in patients using lithium alone and lithium combined with other MS for more than 2 years (adjusted odd ratio [AOR] = 1.39; 95% CI = 1.01-1.92, p = 0.043 and AOR = 1.44; 95% CI = 1.13-1.85, p = 0.003, respectively) than in non-users. Furthermore, the risks of cataract development increased in those treated with valproic acid combined with other MS (AOR = 1.26; 95% CI = 1.02-1.57, p = 0.035). Finally, no increased risks of cataract development were found in carbamazepine and lamotrigine users.

CONCLUSIONS

We found increased risks of cataract development in long-term users of lithium, lithium combined with other MS and valproic acid combined with other MS for more than two years among patients with BD and schizophrenia.

Antidepressants and risk of cataract development: A population-based, nested case-control study

BACKGROUND

Previous studies demonstrated increased risk of cataract development among users of selective serotonin reuptake inhibitors (SSRIs). However, it remains unknown whether this risk also prevails with the use of other types of antidepressants. The aim of this study was to investigate whether use of antidepressants is associated with an increased risk of cataract development. Moreover, the relationship between binding affinities of serotonin transporter (SERT) of antidepressant and the risk of cataracts is examined.

METHODS

We conducted a nested case-control study using National Health Insurance Research Database in Taiwan. A total of 14,288 patients were included; 7651 in the cataract group and 6637 in the control group. Antidepressant exposure was categorized by type, duration of use, and binding affinities of SERT. The association between antidepressant exposure and cataract development was assessed using conditional logistic regression analysis.

RESULTS

The adjusted odds ratios (AORs) for developing cataracts among continuous users of SSRIs, serotonin norepinephrine reuptake inhibitors (SNRIs), and other antidepressants were 1.26 (95% confidence interval (CI): 1.12-1.41, p<0.001), 1.21 (95% CI: 1.02-1.43, p=0.027), and 1.18 (95% CI: 1.04-1.34, p=0.009) respectively. Specifically, continuous uses of fluoxetine (AOR: 1.21; 95% CI: 1.01-1.46, p=0.042), fluvoxamine (AOR: 1.47; 95% CI: 1.01-2.12, p=0.043), venlafaxine (AOR: 1.44; 95% CI: 1.19-1.74, p<0.001) significantly increased the risk of cataract development. Moreover, continuous users of antidepressants with intermediate SERT binding affinities (AOR: 1.68; 95% CI: 1.10-2.56, p=0.017) were significantly associated with increased risks of cataract development.

LIMITATIONS

Several confounding factors such as obesity, multiple drug users, family history of cataracts, substance use, and environmental factors (such as sunlight or radiation exposure) were acquired.

CONCLUSIONS

We found increased risk of cataract development in patients continuously using antidepressants. Regular ocular evaluations in these patients are warranted.

Association between antipsychotic drug use and cataracts in patients with bipolar disorder: A population-based, nested case-control study

BACKGROUND

No previous study has focused on the association between use of antipsychotic drugs and the development of cataracts in patients with bipolar disorder (BD); hence, we aimed to examine this association in the present study.

METHODS

We conducted a retrospective nested case-control study using data from the National Health Insurance Database of Taiwan between 2000 and 2011. A total of 3292 BD patients, 1684 with cataracts and 1608 controls matched for age, sex, and index date, were included. Antipsychotic drug exposure was categorized by type of drug and duration of use. A conditional logistic regression analysis was used to analyze the association.

RESULTS

Among BD patients, we found significantly reduced odds ratio (OR) of cataract development among past (adjusted OR (AOR), 0.74; 95% confidence interval (CI), 0.62-0.89; p=0.001) and continuous users (AOR, 0.71; 95% CI, 0.59-0.85; p<0.001) of atypical antipsychotics. No association was found between the odds of cataract development and typical antipsychotics. Besides, concomitant use of antidepressants (AOR, 1.23; 95% CI, 1.06-1.43; p=0.007) and mood stabilizers (AOR, 1.23; 95% CI, 1.06-1.42; p=0.007) were associated with increased odds of cataract development.

LIMITATIONS

Some important contributors to cataract development such as family history of cataract, smoking and alcohol exposure could not be measured from the claims data and this may confound the results.

CONCLUSIONS

Reduced odds of cataract were found in patients with BD taking atypical antipsychotics. However, given that BD patients often have risk factors for developing cataract, regular ocular evaluations are recommended for those treated with antipsychotics drugs.

Use of Selective Serotonin Reuptake Inhibitors and Risks of Stroke in Patients with Obsessive Compulsive Disorder: A Population-Based Study

Background

Previous research has suggested a link between antidepressants use and the development of cerebrovascular events, but there has never been any study investigating the risk of stroke in obsessive-compulsive disorder (OCD) patients treated with a selective serotonin reuptake inhibitor (SSRI).

Methods

A retrospective observational cohort study was conducted using data from the National Health Insurance Database of Taiwan between the year of 2001 and 2009. A total of 527 OCD patients with 412 subjects in the SSRI use group and 115 in the non SSRI use group were included. Multivariable Cox proportional-hazards models were used to explore the associations between SSRI use and the occurrence of stroke, controlling for age, gender, concomitant medications, and comorbid medical illnesses.

Results

A total of nineteen OCD patients were diagnosed with new onset of stroke during the follow-up period including six cases in the SSRI group and thirteen in the non SSRI use group. SSRI use was demonstrated to be associated with a decreased risk of stroke (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.10–0.86, P = 0.02). The increase in age-related risk of strokes was 2.55 per decade (HR = 2.55; 95% CI = 1.74–3.75, P<0.001). Alternatively, sex, concomitant use of aspirin and non-steroidal anti-inflammatory drugs, and comorbidities with angina pectoris, diabetes mellitus, hypertension, and hyperlipidemia were not found to be associated with an increased risk for stroke in OCD patients.

Conclusions

Our study showed that SSRI use was associated with decreased risk of stroke in OCD patients. Further investigation into the possible biological mechanisms underlying the relationship between stroke and SSRI use in OCD patients is warranted.