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Polygenic score analyses on antidepressant response in late-life depression, results from the IRL-GRey study

The Pharmacogenomics Journal volume 24, Article number: 38 (2024) Cite this article

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Abstract

Late-life depression (LLD) is often accompanied by medical comorbidities such as psychiatric disorders and cardiovascular diseases, posing challenges to antidepressant treatment. Recent studies highlighted significant associations between treatment-resistant depression (TRD) and polygenic risk score (PRS) for attention deficit hyperactivity disorder (ADHD) in adults as well as a negative association between antidepressant symptom improvement with both schizophrenia and bipolar. Here, we sought to validate these findings with symptom remission in LLD. We analyzed the Incomplete Response in Late Life Depression: Getting to Remission (IRL-GRey) sample consisting of adults aged 60+ with major depression (N = 342) treated with venlafaxine for 12 weeks. We constructed PRSs for ADHD, depression, schizophrenia, bipolar disorder, neuroticism, general intelligence, antidepressant symptom remission and antidepressant percentage symptom improvement using summary statistics from the Psychiatric Genomics Consortium and the GWAS Catalog. Logistic regression was used to test the association of PRSs with venlafaxine symptom remission and percentage symptom improvement, co-varying for the genomic principal components, age, sex and depressive symptoms severity at baseline. We found a nominal (i.e., p value ≤ 0.05) association between symptom remission and both PRS for ADHD and (OR = 1.36 [1.07, 1.73], p = 0.011) and PRS for bipolar disorder (OR = 0.75 [0.58, 0.97], p = 0.031), as well as between percentage symptom improvement and PRS for general intelligence (beta = 6.81 (SE = 3.122), p = 0.03). However, the ADHD association was in the opposite direction as expected, and both associations did not survive multiple testing corrections. Altogether, these findings suggest that previous findings regarding ADHD PRS and antidepressant response (measured with various outcomes) do not replicate in older adults.

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Fig. 1: Distribution of top PRS findings accross remission status and symptom percentage improvement.

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Data availability

The GWAS summary statistics for the psychiatric disorders used in this analysis are publicly available from: the Psychiatric Genomics Consortium; https://www.med.unc.edu/pgc/download-results/, and the GWAS Catalogue; https://www.ebi.ac.uk/gwas.

Code availability

To obtain the results presented here, we mostly followed the tutorials and general usage available from PLINK 2.0 alpha; https://www.cog-genomics.org/plink/2.0/, PRSice-2; https://choishingwan.github.io/PRS-Tutorial/.

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Acknowledgements

This work was supported by funding from (1) CIHR #; (2) funding from CANSSI Ontario: Trainee SSME is a fellow of STAGE (Strategic Training for Advanced Genetic Epidemiology); (3) the CAMH Discovery Fund Postdoctoral Fellowship supporting SSME; (4) Temerty-Tanz-TDRA Research Fellowships supporting SSME. Computations were performed on the CAMH Specialized Computing Cluster (SCC). The SCC is funded by: The Canada Foundation for Innovation, Research Hospital Fund.

Author information

Authors and Affiliations

  1. Campbell Family Mental Health Research Institute, Center for Addiction and Mental Health, Toronto, ON, Canada

    Samar S. M. Elsheikh, Xiaoyu Men, Farhana Islam, Vanessa F. Gonçalves, Daniel Felsky, James L. Kennedy, Benoit H. Mulsant & Daniel J. Müller

  2. Columbia University Irving Medical Center, New York, NY, USA

    Victoria S. Marshe

  3. Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada

    Xiaoyu Men, Farhana Islam, Vanessa F. Gonçalves & Daniel J. Müller

  4. Department of Psychiatry, University of Toronto, Toronto, ON, Canada

    Vanessa F. Gonçalves, Daniel Felsky, James L. Kennedy, Benoit H. Mulsant & Daniel J. Müller

  5. Institute of Medical Science, University of Toronto, Toronto, ON, Canada

    Vanessa F. Gonçalves, Daniel Felsky, James L. Kennedy, Benoit H. Mulsant & Daniel J. Müller

  6. Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, Canada

    Guillaume Paré

  7. Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, 237 Barton Street East, Hamilton, ON, Canada

    Guillaume Paré

  8. Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, 1280 Main Street West, Hamilton, ON, Canada

    Guillaume Paré

  9. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada

    Guillaume Paré

  10. Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

    Daniel Felsky

  11. Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA

    Charles F. Reynolds 3rd

  12. Healthy Mind Lab, Department of Psychiatry, Washington University, St. Louis, MO, USA

    Eric J. Lenze

  13. Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany

    Daniel J. Müller

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  1. Samar S. M. Elsheikh
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Contributions

The study was conceptualized by Samar S. M. Elsheikh (SSME) and Daniel J. Müller (DM). The methodology was designed by SSME, DM and Victoria S. Marshe (VM). Formal analysis of the data was performed by SSME. The manuscript was drafted by SSME. Comprehensive reviewing and editing of the manuscript were carried out by all authors.

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Correspondence to Daniel J. Müller.

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Elsheikh, S.S.M., Marshe, V.S., Men, X. et al. Polygenic score analyses on antidepressant response in late-life depression, results from the IRL-GRey study. Pharmacogenomics J 24, 38 (2024). https://doi.org/10.1038/s41397-024-00351-0

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