Neither cytochrome P450 family genes nor neuroendocrine factors could independently predict the SSRIs treatment in the Chinese Han population

Increased adrenocorticotropic hormone (ACTH) levels predict severity of depression after six months of follow-up in outpatients with major depressive disorder

Previous studies have reported dysfunction in the hypothalamic-pituitary-adrenal (HPA) axis in patients with major depressive disorder (MDD). Outpatients diagnosed with MDD (n = 199) underwent psychological evaluation, and were followed up with a phone interview after 6 months, using the Patient Health Questionnaire (PHQ-9). At 6-month follow-up, 59 out of 199 patients with MDD were still depressed (29.5%), as shown by scores ≥ 10 on the PHQ-9. The depressed group at follow-up showed significantly higher anxiety and suicidality levels at baseline than the non-depressed group at follow-up. Among the complete blood counts, lipid profiles, and hormone levels, adrenocorticotropic hormone (ACTH) was the only parameter that was significantly increased in the still depressed group. Levels higher than 40 pg/mL of ACTH at baseline were associated with higher depression scores at follow-up. Multiple linear regression analyses revealed that ACTH and cortisol predicted depression scores at follow-up, after controlling for baseline depression scores. Increased ACTH level at baseline may predict ongoing symptoms and severity of depression at follow-up, suggesting the role of dysfunctional HPA axis in MDD prognosis.

Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years

BACKGROUND

Antidepressant drugs are widely prescribed, but response rates after 3 months are only around one-third, explaining the importance of the search of objectively measurable markers predicting positive treatment response. These markers are being developed in different fields, with different techniques, sample sizes, costs, and efficiency. It is therefore difficult to know which ones are the most promising.

OBJECTIVE

Our purpose was to compute comparable (i.e., standardized) effect sizes, at study level but also at marker level, in order to conclude on the efficacy of each technique used and all analyzed markers.

METHODS

We conducted a systematic search on the PubMed database to gather all articles published since 2000 using objectively measurable markers to predict antidepressant response from five domains, namely cognition, electrophysiology, imaging, genetics, and transcriptomics/proteomics/epigenetics. A manual screening of the abstracts and the reference lists of these articles completed the search process.

RESULTS

Executive functioning, theta activity in the rostral Anterior Cingular Cortex (rACC), and polysomnographic sleep measures could be considered as belonging to the best objectively measured markers, with a combined d around 1 and at least four positive studies. For inter-category comparisons, the approaches that showed the highest effect sizes are, in descending order, imaging (combined d between 0.703 and 1.353), electrophysiology (0.294-1.138), cognition (0.929-1.022), proteins/nucleotides (0.520-1.18), and genetics (0.021-0.515).

CONCLUSION

Markers of antidepressant treatment outcome are numerous, but with a discrepant level of accuracy. Many biomarkers and cognitions have sufficient predictive value (d ≥ 1) to be potentially useful for clinicians to predict outcome and personalize antidepressant treatment.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Influence of CYP2D6 and β2-adrenergic receptor gene polymorphisms on the hemodynamic response to propranolol in Chinese Han patients with cirrhosis

BACKGROUND AND AIM

Propranolol is widely used to prevent gastroesophageal variceal bleeding; however, some patients could not benefit from propranolol. This study is to evaluate the relationship between CYP2D6 and β2-adrenergic receptor (β2-AR) gene polymorphisms and the hemodynamic response to propranolol in Chinese Han patients.

METHODS

The clinical data of patients with gastroesophageal varices undergoing hepatic venous pressure gradient (HVPG) measurement before and 7 days after oral propranolol administration in our department were collected. Four single nucleotide polymorphisms of CYP2D6 and β2-AR genes were detected. The relationship was identified by logistic regression model.

RESULTS

Thirty patients were involved in the analysis. Sixty milligram propranolol twice each day was well tolerated by all the patients. The initial and secondary average of HVPG was 17.4 ± 5.8 mmHg vs. 13.2 ± 4.8 mmHg, respectively (t = 5.726, P < 0.001). Twenty patients responded to propranolol. The mean reduction value of HVPG was 6.6 ± 3.6 mmHg (range from 3 to 19). Genotype analysis showed: 20 homozygotes for C/C188 and 10 for heterozygous C/T188, 8 homozygotes for G/G4268 and 22 heterozygotes for G/C4268, 14 homozygotes for Gly16 and 10 heterozygotes, and 6 homozygotes for Arg16, 27 homozygotes for Gln27 and 3 heterozygotes. The multivariate logistic regression analysis indicated that CYP2D6 (188C>T) genotype was an independent predicting factor for HVPG response to propranolol (P = 0.033).

CONCLUSIONS

CYP2D6 (188C>T) gene polymorphisms influence the hemodynamic response to propranolol in this population of Chinese Han patients with gastroesophageal varices. However, HVPG response cannot be completely predicted from CYP2D6 and β2-AR gene polymorphisms.