| 51. |
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| 53. |
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| 54. |
- Hou, Liping, et al.
(author)
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Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.
- 2016
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In: Human molecular genetics. - : Oxford University Press (OUP). - 1460-2083 .- 0964-6906. ; 25:15, s. 3383-94
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Journal article (peer-reviewed)abstract
- Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p=5.87×10(-9); odds ratio=1.12) and markers within ERBB2 (rs2517959, p=4.53×10(-9); odds ratio=1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
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| 55. |
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| 56. |
- Amare, Azmeraw T, et al.
(author)
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Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.
- 2023
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In: Molecular psychiatry. - 1476-5578. ; 28, s. 5251-5261
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Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P=9.8×10-12, R2=1.9%) and continuous (P=6.4×10-9, R2=2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P=3.9×10-4, R2=0.9%), but not for the continuous outcome (P=0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
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| 57. |
- Andlauer, TFM, et al.
(author)
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Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders
- 2021
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In: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 26:4, s. 1286-1298
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Journal article (peer-reviewed)abstract
- Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.
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| 58. |
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| 59. |
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| 60. |
- Melin, Beatrice S., et al.
(author)
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Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors
- 2017
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:5, s. 789-794
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 x 10(-9), odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 x 10(-10), OR = 1.24), 16p13.3 (rs2562152; P = 1.93 x 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 x 10(-11), OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 x 10(-10), OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 x 10(-9), OR = 1.19), 1q44 (rs12076373; P = 2.63 x 10(-10), OR = 1.23), 2q33.3 (rs7572263; P = 2.18 x 10(-10), OR = 1.20), 3p14.1 (rs11706832; P = 7.66 x 10(-9), OR = 1.15), 10q24.33 (rs11598018; P = 3.39 x 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 x 10(-10), OR = 1.16), 14q12 (rs10131032; P = 5.07 x 10(-11), OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 x 10(-9), OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.
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