OBJECTIVE: The objective was to evaluate the potential benefit of an integrated, five-gene pharmacogenomic test and interpretive report (GeneSight) for the management of psychotropic medications used to treat major depression in an outpatient psychiatric practice. METHODS: The open-label study was divided into two groups. In the first (unguided) group (n = 113), pharmacogenomic information was not shared until all participants completed the study. In the second (guided) group (n = 114), the pharmacogenomic report was provided to physicians for clinical use. Three depression ratings, the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Quick Inventory of Depressive Symptomatology - Clinician Rated (QIDS-C16), and the Patient Health Questionnaire (PHQ-9), were collected at baseline, and at 2, 4, and 8 weeks. RESULTS: The guided group experienced greater percent improvement in depression scores from baseline on all three depression instruments (HAMD-17, P < 0.0001; QIDS-C16, P < 0.0001; PHQ-9, P < 0.0001) compared with the unguided group. Eight-week response rates were higher in the guided group than in the unguided group on all three measurements (HAMD-17, P = 0.03; QIDS-C16, P = 0.005; PHQ-9, P = 0.01). Eight-week QIDS-C16 remission rates were higher in the guided group (P = 0.03). Participants in the unguided group who at baseline were prescribed a medication that was most discordant with their genotype experienced the least improvement compared with other unguided participants (HAMD-17, P = 0.007). Participants in the guided group and on a baseline medication most discordant with their genotype showed the greatest improvement compared with the unguided cohort participants (HAMD-17, P = 0.01). CONCLUSION: These findings replicate previous studies and demonstrate significantly improved depression outcomes with use of GeneSight, an integrated, multigenetic pharmacogenomic testing platform.
OBJECTIVE: The objective was to evaluate the potential benefit of an integrated, five-gene pharmacogenomic test and interpretive report (GeneSight) for the management of psychotropic medications used to treat major depression in an outpatientpsychiatric practice. METHODS: The open-label study was divided into two groups. In the first (unguided) group (n = 113), pharmacogenomic information was not shared until all participants completed the study. In the second (guided) group (n = 114), the pharmacogenomic report was provided to physicians for clinical use. Three depression ratings, the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Quick Inventory of Depressive Symptomatology - Clinician Rated (QIDS-C16), and the Patient Health Questionnaire (PHQ-9), were collected at baseline, and at 2, 4, and 8 weeks. RESULTS: The guided group experienced greater percent improvement in depression scores from baseline on all three depression instruments (HAMD-17, P < 0.0001; QIDS-C16, P < 0.0001; PHQ-9, P < 0.0001) compared with the unguided group. Eight-week response rates were higher in the guided group than in the unguided group on all three measurements (HAMD-17, P = 0.03; QIDS-C16, P = 0.005; PHQ-9, P = 0.01). Eight-week QIDS-C16 remission rates were higher in the guided group (P = 0.03). Participants in the unguided group who at baseline were prescribed a medication that was most discordant with their genotype experienced the least improvement compared with other unguided participants (HAMD-17, P = 0.007). Participants in the guided group and on a baseline medication most discordant with their genotype showed the greatest improvement compared with the unguided cohort participants (HAMD-17, P = 0.01). CONCLUSION: These findings replicate previous studies and demonstrate significantly improved depression outcomes with use of GeneSight, an integrated, multigenetic pharmacogenomic testing platform.
Authors: Katarina Arandjelovic; Harris A Eyre; Eric Lenze; Ajeet B Singh; Michael Berk; Chad Bousman Journal: J Neural Transm (Vienna) Date: 2017-10-29 Impact factor: 3.575
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Authors: C A Altar; J M Carhart; J D Allen; D K Hall-Flavin; B M Dechairo; J G Winner Journal: Pharmacogenomics J Date: 2015-02-17 Impact factor: 3.550
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