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- Coleman, Jonathan R I, et al.
(författare)
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The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls.
- 2020
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Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 88:2, s. 169-184
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Tidskriftsartikel (refereegranskat)abstract
- Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.
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| 2. |
- Hannon, Eilis, et al.
(författare)
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DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia
- 2021
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Ingår i: eLIFE. - : eLife Sciences Publications. - 2050-084X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.
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| 3. |
- Iacoangeli, Alfredo, et al.
(författare)
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SCFD1 expression quantitative trait loci in amyotrophic lateral sclerosis are differentially expressed
- 2021
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Ingår i: Brain Communications. - : Oxford University Press. - 2632-1297. ; 3:4
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Tidskriftsartikel (refereegranskat)abstract
- Evidence indicates that common variants found in genome-wide association studies increase risk of disease through gene regulation via expression Quantitative Trait Loci. Using multiple genome-wide methods, we examined if Single Nucleotide Polymorphisms increase risk of Amyotrophic Lateral Sclerosis through expression Quantitative Trait Loci, and whether expression Quantitative Trait Loci expression is consistent across people who had Amyotrophic Lateral Sclerosis and those who did not. In combining public expression Quantitative Trait Loci data with Amyotrophic Lateral Sclerosis genome-wide association studies, we used Summary-data-based Mendelian Randomization to confirm that SCFD1 was the only gene that was genome-wide significant in mediating Amyotrophic Lateral Sderosis risk via expression Quantitative Trait Loci (Summary-data-based Mendelian Randomization beta = 0.20, standard error = 0.04, P-value = 4.29 x 10(-6)). Using post-mortem motor cortex, we tested whether expression Quantitative Trait Loci showed significant differences in expression between Amyotrophic Lateral Sclerosis (n= 76) and controls (n= 25), genome-wide. Of 20 757 genes analysed, the two most sign ificant expression Quantitative Trait Loci to show differential in expression between Amyotrophic Lateral Sclerosis and controls involve two known Amyotrophic Lateral Sclerosis genes (SCFD1 and VCP). Cis-acting SCFD1 expression Quantitative Trait Loci downstream of the gene showed significant differences in expression between Amyotrophic Lateral Sclerosis and controls (top expression Quantitative Trait Lod beta = 0.34, standard error = 0.063, P-value = 4.54 x 10(-7)). These SCFD1 expression Quantitative Trait Loci also significantly modified Amyotrophic Lateral Sclerosis survival (number of samples = 4265, hazard ratio = 1.11, 95% confidence interval = 1.05-1.17, P-value = 2.06 x 10(-4)) and act as an Amyotrophic Lateral Sclerosis trans-expression Quantitative Trait Loci hotspot for a wider network of genes enriched for SCFD1 function and Amyotrophic Lateral Sderosis pathways. Using gene-set analyses, we found the genes that correlate with this trans-expression Quantitative Trait Loci hotspot significantly increase risk of Amyotrophic La teral Sderosis (beta = 0.247, standard deviation = 0.017, P= 0.001) and schizophrenia (beta = 0.263, standard deviation = 0.008, P-value 1.18 x 10(-5)), a disease that genetically correlates with Amyotrophic Lateral Sclerosis. In summary, SCFD1 expression Quantitative Trait Lod are a major factor in Amyotrophic Lateral Sderosis, not only influencing disease risk but are differentially expressed in post-mortem Amyotrophic Lateral Sclerosis. SCFD1 expression Quantitative Trait Loci show distinct expression profiles in Amyotrophic Lateral Sclerosis that correlate with a wider network of genes that also confer risk of the disease and modify the disease's duration.
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