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Pregled bibliografske jedinice broj: 1139339

Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables


Iniesta, Raquel; Hodgson, Karen; Stahl, Daniel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana et al.
Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables // Scientific reports, 8 (2018), 5530, 9 doi:10.1038/s41598-018-23584-z (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1139339 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables

Autori
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

Izvornik
Scientific reports (2045-2322) 8 (2018); 5530, 9

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
antidepressants ; depression, treatment outcomes ; genetic variables ; clinical variables

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Temeljne medicinske znanosti, Kliničke medicinske znanosti



POVEZANOST RADA


Ustanove:
Medicinski fakultet, Zagreb

Profili:

Avatar Url Neven Henigsberg (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi www.nature.com

Citiraj ovu publikaciju:

Iniesta, Raquel; Hodgson, Karen; Stahl, Daniel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana et al.
Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables // Scientific reports, 8 (2018), 5530, 9 doi:10.1038/s41598-018-23584-z (međunarodna recenzija, članak, znanstveni)
Iniesta, R., Hodgson, K., Stahl, D., Malki, K., Maier, W., Rietschel, M., Mors, O., Hauser, J., Henigsberg, N. & Dernovsek, M. (2018) Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables. Scientific reports, 8, 5530, 9 doi:10.1038/s41598-018-23584-z.
@article{article, author = {Iniesta, Raquel and Hodgson, Karen and Stahl, Daniel and Malki, Karim and Maier, Wolfgang and Rietschel, Marcella and Mors, Ole and Hauser, Joanna and Henigsberg, Neven and Dernovsek, Mojca Zvezdana and Souery, Daniel and Dobson, Richard and Aitchison, Katherine J. and Farmer, Anne and McGuffin, Peter and Lewis, Cathryn M. and Uher, Rudolf}, year = {2018}, pages = {9}, DOI = {10.1038/s41598-018-23584-z}, chapter = {5530}, keywords = {antidepressants, depression, treatment outcomes, genetic variables, clinical variables}, journal = {Scientific reports}, doi = {10.1038/s41598-018-23584-z}, volume = {8}, issn = {2045-2322}, title = {Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables}, keyword = {antidepressants, depression, treatment outcomes, genetic variables, clinical variables}, chapternumber = {5530} }
@article{article, author = {Iniesta, Raquel and Hodgson, Karen and Stahl, Daniel and Malki, Karim and Maier, Wolfgang and Rietschel, Marcella and Mors, Ole and Hauser, Joanna and Henigsberg, Neven and Dernovsek, Mojca Zvezdana and Souery, Daniel and Dobson, Richard and Aitchison, Katherine J. and Farmer, Anne and McGuffin, Peter and Lewis, Cathryn M. and Uher, Rudolf}, year = {2018}, pages = {9}, DOI = {10.1038/s41598-018-23584-z}, chapter = {5530}, keywords = {antidepressants, depression, treatment outcomes, genetic variables, clinical variables}, journal = {Scientific reports}, doi = {10.1038/s41598-018-23584-z}, volume = {8}, issn = {2045-2322}, title = {Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables}, keyword = {antidepressants, depression, treatment outcomes, genetic variables, clinical variables}, chapternumber = {5530} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • Social Science Citation Index (SSCI)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





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