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- Mullins, N., et al.
(författare)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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- Cearns, M., et al.
(författare)
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- 2022
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Ingår i: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 220:4, s. 219-228
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Tidskriftsartikel (refereegranskat)abstract
- Background Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. Aims To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. Method This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi(+)Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. Results The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Conclusions Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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- Kumar, P, et al.
(författare)
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Mitochondrial DNA copy number is associated with psychosis severity and anti-psychotic treatment
- 2018
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1, s. 12743-
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Tidskriftsartikel (refereegranskat)abstract
- Mitochondrial pathology has been implicated in the pathogenesis of psychotic disorders. A few studies have proposed reduced leukocyte mitochondrial DNA (mtDNA) copy number in schizophrenia and bipolar disorder type I, compared to healthy controls. However, it is unknown if mtDNA copy number alteration is driven by psychosis, comorbidity or treatment. Whole blood mtDNA copy number was determined in 594 psychosis patients and corrected for platelet to leukocyte count ratio (mtDNAcnres). The dependence of mtDNAcnres on clinical profile, metabolic comorbidity and antipsychotic drug exposure was assessed. mtDNAcnres was reduced with age (β = −0.210, p < 0.001), use of clozapine (β = −0.110,p = 0.012) and risperidone (β = −0.109,p = 0.014), dependent on prescribed dosage (p = 0.006 and p = 0.026, respectively), and the proportion of life on treatment (p = 0.006). Clozapine (p = 0.0005) and risperidone (p = 0.0126) had a reducing effect on the mtDNA copy number also in stem cell-derived human neurons in vitro at therapeutic plasma levels. For patients not on these drugs, psychosis severity had an effect (β = −0.129, p = 0.017), similar to age (β = −0.159, p = 0.003) and LDL (β = −0.119, p = 0.029) on whole blood mtDNAcnres. Further research is required to determine if mtDNAcnres reflects any psychosis-intrinsic mitochondrial changes.
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| 9. |
- Kumar, P, et al.
(författare)
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Plasma GDF15 level is elevated in psychosis and inversely correlated with severity
- 2017
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7:1, s. 7906-
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Tidskriftsartikel (refereegranskat)abstract
- Accumulating evidence suggests that GDF15 is a biomarker for ageing and morbidity of many somatic disorders such as cancer and inflammatory disorders. Recently, elevated serum GDF15 level was proposed as a marker for mood disorder. However, psychosis severity was not investigated in relation to plasma GDF15 levels. In the present study we measured GDF15 levels in plasma of 120 psychosis patients compared to 120 age and gender matched healthy controls. Within the patient cohort GDF15 levels were evaluated for association with age, gender, lifestyle factors, C-reactive protein levels, psychosis severity and metabolic disorder. Psychosis patients had elevated GDF15 levels compared to controls (medianPsychosis = 744 ng/mL, mediancontrols = 516 ng/mL, p < 0.001). Within the psychosis cohort, GDF15 levels, when corrected for age, metabolic health and lifestyle factors, were negatively correlated with psychosis severity (β = −0.218, p = 0.012). While GDF15 levels were elevated in patients versus healthy controls, the negative correlation between psychosis severity and GDF15 suggests a loss of anti-inflammatory GDF15 mediated functionality in severe psychosis. Study replication in larger cohorts will be necessary to assess the potential of GDF15 as a prognostic biomarker in psychosis.
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