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- Tabrizi, Fara, et al.
(författare)
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P117. Predicting Genetic Risk for Depression and Anxiety Disorders
- 2022
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Ingår i: Biological Psychiatry. - : Elsevier BV. - 0006-3223 .- 1873-2402. ; 91
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundPolygenic scores (PGSs) harness the potential to provide an overall measure of individuals’ genetic liability to develop a disease (Torkamani et al., 2018), though much research is still needed. The aim of the present study was to predict prescription of pharmacological treatment of anxiety or depression from PGSs.MethodsThe target sample comprised two cohorts of genotyped Swedish twins (n = 11037). Cases were defined as individuals prescribed pharmacological treatment of depression (n = 1129) or anxiety (n = 1446). We constructed 6 PGSs based on GWAS on MDD diagnosis, Anxiety, Schizophrenia, Neuroticism scores, the GAD-7 scale, and the PHQ-9. Data were analyzed by logistic regression models with change in pseudo-R2 (above the baseline model with sex, age, cohort, and 20 ancestral PCs) following the inclusion of PGSs to predict the risk of anxiety or depression medication. All results corrected for multiple comparisons.ResultsPredictive performance was estimated to ΔR2depression = 0.028; ΔR2anxiety = 0.025 when all PGSs were included in the same model, with PGS for MDD being the single best predictor for both anxiety and depression. Individuals in the top 10% of the PGS distribution had greater odds of drug prescription (ORdepression = 1.82; CI95% = 1.53—2.17; ORanxiety = 1.65; CI95% = 1.40—1.95), while the bottom 10% had decreased risk (ORanxiety = 0.56; CI95% = 0.45—0.70; ORdepression = 0.58; CI95% = 0.45—0.74) compared to the remaining 90% of the distribution.ConclusionsPGSs can predict drug prescription for anxiety and depression in an independent sample.
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| 2. |
- Tabrizi, Fara, et al.
(författare)
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Prediction of anxiety and depression from polygenic scores in Swedish twins
- 2021
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Ingår i: Abstracts of the WASAD Congress 2021. - : Springer. ; , s. 1802-1803
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Konferensbidrag (refereegranskat)abstract
- Recent genome-wide association studies (GWAS) have identified several common variants associated with depression (Howard et al. 2019; Levey et al. 2021) and anxiety disorders (Levey et al. 2020; Meier et al. 2019; Purves et al. 2020), and these findings have been harnessed to develop polygenic scores (PGS) in order to provide an overall measure of individuals’ genetic liability to develop a disease (Torkamani et al. 2018). Research on the utility of PGSs as predictors of risk for disease is gaining traction, with studies on somatic illness showing that disease risk increases sharply in the right tail of the PGS distribution (Khera et al. 2018). Thus, PGS stratification could be of clinical relevance if it provides an opportunity to target those in need of preventive interventions with increased precision. The current potential of PGS stratification for depression and anxiety disorders remains an open question. In the current study, we applied 36 predefined PGSs from the polygenic index repository (Becker et al. 2021) on a target sample of 11,210 genotyped twins. Cases were defined as those with prescribed medication, where the prescription explicitly stated that a drug was ordinated for indication of depression or anxiety, respectively. Drugs included antidepressants (SSRI and SNRI), Benzodiazepines, Antihistamines, Buspirone, and Betablockers.
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| 3. |
- Tabrizi, Fara, et al.
(författare)
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Psychometric evaluation of the Swedish Multidimensional Psychological Flexibility Inventory (MPFI)
- 2023
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Ingår i: Cognitive Behaviour Therapy. - : Routledge. - 1650-6073 .- 1651-2316. ; 52:4, s. 295-316
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Tidskriftsartikel (refereegranskat)abstract
- Psychiatric disorders are common, and reliable measures are crucial for research and clinical practice. A cross-diagnostic construct that can be used to index treatment outcomes as well as prevalence of psychological ill health is psychological flexibility. The aim of this study was to validate a Swedish version of the Multidimensional Psychological Flexibility Inventory (MPFI). The MPFI has 12 subscales, six of which measure flexibility, and six that measure inflexibility. Using confirmatory factor analysis in a community sample of 670 participants, we found that a model with two higher order factors had satisfactory fit (CFI = .933) and a 12-factor model had the best fit to the data (CFI = .955). All 12 subscales showed adequate reliability (CRs = .803-.933) and the factor structure was similar across age groups and gender. Findings suggest that the Swedish version of the MPFI is a reliable instrument that can be used to index psychological flexibility. Potential areas for improvement of the instrument are discussed.
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