Predictors of the effectiveness of an early medication change strategy in patients with major depressive disorder

Common polygenic variation in the early medication change (EMC) cohort affects disorder risk, but not the antidepressant treatment response

BACKGROUND

Given the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort.

METHODS

In this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined.

RESULTS

PGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10-12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR.

LIMITATIONS

The study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS).

CONCLUSIONS

The present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes.

Concordance of the treatment patterns for major depressive disorders between the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm and real-world practice in China

Background: Antidepressant (AD) algorithm is an important tool to support treatment decision-making and improve management of major depressive disorder (MDD). However, little is known about its concordance with real-world practice. This study aimed to assess the concordance between the longitudinal treatment patterns and AD algorithm recommended by a clinical practice guideline in China. Methods: Data were obtained from the electronic medical records of Shanghai Mental Health Center (SMHC), one of the largest mental health institutions in China. We examined the concordance between clinical practice and the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm among a cohort composed of 19,955 MDD patients. The longitudinal characteristics of treatment regimen and duration were described to identify the specific inconsistencies. Demographics and health utilizations of the algorithm-concordant and -discordant subgroups with optimized treatment were measured separately. Results: The overall proportion of algorithm-concordant treatment significantly increased from 84.45% to 86.03% during the year of 2015-2017. Among the patients who received recommended first-line drugs with subsequent optimized treatment (n = 2977), the concordance proportion was 27.24%. Mirtazapine and trazodone were the most used drugs for adjunctive strategy. Inadequate or extended duration before optimized treatment are common inconsistency. The median length of follow-up for algorithm-concordant (n = 811) and algorithm-discordant patients (n = 2166) were 153 days (Q1-Q3 = 79-328) and 368 days (Q1-Q3 = 181-577) respectively, and the average number of clinical visits per person-year was 13.07 and 13.08 respectively. Conclusion: Gap existed between clinical practice and AD algorithm. Improved access to evidence-based treatment is required, especially for optimized strategies during outpatient follow-up.

Sex-Specific Retinal Anomalies Induced by Chronic Social Defeat Stress in Mice

Major depressive disorder (MDD) is one of the most common consequences of chronic stress. Still, there is currently no reliable biomarker to detect individuals at risk to develop the disease. Recently, the retina emerged as an effective way to investigate psychiatric disorders using the electroretinogram (ERG). In this study, cone and rod ERGs were performed in male and female C57BL/6 mice before and after chronic social defeat stress (CSDS). Mice were then divided as susceptible or resilient to stress. Our results suggest that CSDS reduces the amplitude of both oscillatory potentials and a-waves in the rods of resilient but not susceptible males. Similar effects were revealed following the analysis of the cone b-waves, which were faster after CSDS in resilient mice specifically. In females, rod ERGs revealed age-related changes with no change in cone ERGs. Finally, our analysis suggests that baseline ERG can predict with an efficacy up to 71% the expression of susceptibility and resilience before stress exposition in males and females. Overall, our findings suggest that retinal activity is a valid biomarker of stress response that could potentially serve as a tool to predict whether males and females will become susceptible or resilient when facing CSDS.

Predictors of poor 6-week outcome in a cohort of major depressive disorder patients treated with antidepressant medication: the role of entrapment

BACKGROUND

Only a small number of consistent processes predict which depressed patients will achieve remission with antidepressant medication. One set of processes is that of social ranking strategies/variables that are related to life events and severe difficulties. Particularly, defeat and entrapment predict poorer response to antidepressants. However, results are inconsistent.

AIM

The current study aimed to evaluate evolutionary strategies, childhood maltreatment, neglect and life events and difficulties (LEDs) as predictors of remission in depressed patients undergoing pharmacological treatment in a psychiatric outpatient sample.

METHODS

A cohort of 139 depressed outpatients undergoing pharmacological treatment was followed prospectively in a naturalistic study for 6 weeks. Two major evaluations were considered at baseline and 6 weeks. We allocated patients to a pharmacological treatment algorithm for depression - the Texas Medication Algorithm Project. Variables evaluated at baseline and tested as predictors of remission included demographic and clinical data, severity of depression, social ranking, evolution informed variables, LEDs and childhood maltreatment.

RESULTS

Of the 139 patients, only 24.5% were remitted at week 6. In univariate analyses, non-remitted patients scored significantly higher in all psychopathology and vulnerability scales except for submissive behaviour and internal entrapment. For the logistic regression, a higher load of LEDs of the entrapment and humiliation dimension in the year before the index episode (OR = 6.62), and higher levels external entrapment in the Entrapment Scale (OR = 1.10) predicted non-remission. These variables accounted for 28.7% of the variance.

CONCLUSIONS

Multivariate analysis revealed that external entrapment was the only predictor of non-remission.