prikaz prve stranice dokumenta Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables
  Download
PDF 1.04 MB
Scientific paper - Original scientific paper
Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables
Scientific Reports, 8 (2018), 1; 5530. https://doi.org/10.1038/s41598-018-23584-z
Iniesta, Raquel; Hodgson, Karen; Stahl, Daniel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Dobson, Richard; Aitchison, Katherine J.; Farmer, Anne; McGuffin, Peter; Lewis, Cathryn M.; Uher, Rudolf More authors...

Institutional repository: Dr Med - University of Zagreb School of Medicine Digital Repository

Cite this document

Iniesta, R., Hodgson, K., Stahl, D., Malki, K., Maier, W., Rietschel, M. ... Uher, R. (2018). Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables. Scientific Reports, 8. (1), 5530. doi: 10.1038/s41598-018-23584-z

Iniesta, Raquel, et al. "Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables." Scientific Reports, vol. 8, no. 1, 2018, p. 5530. https://doi.org/10.1038/s41598-018-23584-z

Iniesta, Raquel, Karen Hodgson, Daniel Stahl, Karim Malki, Wolfgang Maier, Marcella Rietschel, Ole Mors, et al. "Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables." Scientific Reports 8, no. 1 (2018): 5530. https://doi.org/10.1038/s41598-018-23584-z

Iniesta, R., et al. (2018) 'Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables', Scientific Reports, 8(1), p. 5530. doi: 10.1038/s41598-018-23584-z

Iniesta R, Hodgson K, Stahl D, Malki K, Maier W, Rietschel M, and sur.. Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables. Scientific Reports [Internet]. 2018 April 03 [cited 2024 November 23];8(1):5530. doi: 10.1038/s41598-018-23584-z

R. Iniesta, et al., "Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables", Scientific Reports, vol. 8, no. 1, p. 5530, April 2018. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:105:119521. [Accessed: 23 November 2024]

Metadata
Title (english)Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables
AuthorRaquel Iniesta
AuthorKaren Hodgson
AuthorDaniel Stahl
AuthorKarim Malki
AuthorWolfgang Maier
AuthorMarcella Rietschel
AuthorOle Mors
AuthorJoanna Hauser
AuthorNeven Henigsberg
AuthorMojca Zvezdana Dernovsek
AuthorDaniel Souery
AuthorRichard Dobson
AuthorKatherine J. Aitchison
AuthorAnne Farmer
AuthorPeter McGuffin
AuthorCathryn M. Lewis
AuthorRudolf Uher
Author's institutionUniversity of Zagreb
School of Medicine
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Basic Medical Sciences
Abstract (english)
Individuals with depression differ substantially in their response to treatment with antidepressants. Specific predictors explain only a small proportion of these differences. To meaningfully predict who will respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables. Using statistical learning on common genetic variants and clinical information in a training sample of 280 individuals randomly allocated to 12-week treatment with antidepressants escitalopram or nortriptyline, we derived models to predict remission with each antidepressant drug. We tested the reproducibility of each prediction in a validation set of 150 participants not used in model derivation. An elastic net logistic model based on eleven genetic and six clinical variables predicted remission with escitalopram in the validation dataset with area under the curve 0.77 (95%CI; 0.66-0.88; p = 0.004), explaining approximately 30% of variance in who achieves remission. A model derived from 20 genetic variables predicted remission with nortriptyline in the validation dataset with an area under the curve 0.77 (95%CI; 0.65-0.90; p < 0.001), explaining approximately 36% of variance in who achieves remission. The predictive models were antidepressant drug-specific. Validated drug-specific predictions suggest that a relatively small number of genetic and clinical variables can help select treatment between escitalopram and nortriptyline.
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titleScientific Reports
Numberingvol. 8, no. 1, p. 5530
p-ISSN2045-2322
DOIhttps://doi.org/10.1038/s41598-018-23584-z
URN:NBNurn:nbn:hr:105:119521
Publication2018-04-03
Document URLhttps://doi.org/10.1038/s41598-018-23584-z
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-03-28 10:03:50