scholarly journals Pharmacogenetics of antidepressant response: a polygenic approach

2016 ◽  
Author(s):  
Judit García-González ◽  
Katherine E. Tansey ◽  
Joanna Hauser ◽  
Neven Henigsberg ◽  
Wolfgang Maier ◽  
...  

AbstractBackgroundMajor depressive disorder (MDD) has a high personal and socio-economic burden and more than 60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait.MethodsPolygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756).ResultsNo significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results.DiscussionWe identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.

2018 ◽  
Author(s):  
Joey Ward ◽  
Nicholas Graham ◽  
Rona Strawbridge ◽  
Amy Ferguson ◽  
Gregory Jenkins ◽  
...  

AbstractThere are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 783). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, β = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, β = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.


PLoS ONE ◽  
2018 ◽  
Vol 13 (9) ◽  
pp. e0203896 ◽  
Author(s):  
Joey Ward ◽  
Nicholas Graham ◽  
Rona J. Strawbridge ◽  
Amy Ferguson ◽  
Gregory Jenkins ◽  
...  

2022 ◽  
Author(s):  
Miruna C. Barbu ◽  
Carmen Amador ◽  
Alex Kwong ◽  
Xueyi Shen ◽  
Mark Adams ◽  
...  

2020 ◽  
Vol 21 (8) ◽  
pp. 559-569 ◽  
Author(s):  
Lisa Brown ◽  
Oliver Vranjkovic ◽  
James Li ◽  
Kunbo Yu ◽  
Talal Al Habbab ◽  
...  

Aim: To perform a meta-analysis of prospective, two-arm studies examining the clinical utility of using the combinatorial pharmacogenomic test, GeneSight Psychotropic, to inform treatment decisions for patients with major depressive disorder (MDD). Patients & methods: The pooled mean effect of symptom improvement and pooled relative risk ratio (RR) of response and remission were calculated using a random effect model. Results: Overall, 1556 patients were included from four studies, with outcomes evaluated at week 8 or week 10. Patient outcomes were significantly improved for patients with MDD whose care was guided by the combinatorial pharmacogenomic test results compared with unguided care (symptom improvement Δ = 10.08%, 95% CI: 1.67–18.50; p = 0.019; response RR = 1.40, 95% CI: 1.17–1.67; p < 0.001; remission RR = 1.49, 95% CI: 1.17–1.89; p = 0.001). Conclusion: GeneSight Psychotropic guided care improves outcomes among patients with MDD.


2020 ◽  
Vol 21 (13) ◽  
pp. 963-974
Author(s):  
Dan Du ◽  
Qiong Tang ◽  
Qiong Han ◽  
Jin Zhang ◽  
Xuemei Liang ◽  
...  

This network meta-analysis was conducted to compare the predictive value of eight SNPs on the efficacy of antidepressants in major depressive disorder (MDD), including 5-HTTLPR, 5HTR2A (rs6311, rs6314, rs7997012 and rs6313), 5HTR2A (rs6295), BDNF (rs6265) and 5HTTSTin2. Databases were searched for related studies published up to December 2019. A total of 16 studies were included in this study. The predictive value were evaluated by the use of the odd ratios (OR) and drawing surface under the cumulative ranking curves (SUCRA). The pairwise meta-analysis indicated that in terms of overall response ratio, the SNPs were not associated with the efficacy of antidepressants in MDD. The result of this network meta-analysis suggested that there was no significant difference in predictive value of eight SNPs on the efficacy of antidepressants in MDD. More research is needed to explore the relationship between SNPs and antidepressant response.


2021 ◽  
Vol 53 ◽  
pp. S646-S647
Author(s):  
G. Fanelli ◽  
C. Fabbri ◽  
K. Domschke ◽  
A. Minelli ◽  
M. Gennarelli ◽  
...  

2021 ◽  
Vol 51 ◽  
pp. e180
Author(s):  
Giuseppe Fanelli ◽  
Katharina Domschke ◽  
Alessandra Minelli ◽  
Massimo Gennarelli ◽  
Eduard Maron ◽  
...  

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