scholarly journals The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data

2011 ◽  
Vol 1 (10) ◽  
pp. e50-e50 ◽  
Author(s):  
C M Middeldorp ◽  
M H M de Moor ◽  
L M McGrath ◽  
S D Gordon ◽  
D H Blackwood ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depression ◽  
Genetic Association ◽  
Genome Wide Association ◽  
Polygenic Score ◽  
Genome Wide ◽  
Score Analysis ◽  
Association Data

scholarly journals Informing disease modelling with brain-relevant functional genomic annotations

Brain ◽  
2019 ◽  
Vol 142 (12) ◽  
pp. 3694-3712 ◽  
Author(s):  
Regina H Reynolds ◽  
John Hardy ◽  
Mina Ryten ◽  
Sarah A Gagliano Taliun
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Therapeutic Targets ◽  
Genome Wide Association ◽  
Disease Modelling ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Genome Wide ◽  
Neuropsychiatric Diseases ◽  
Association Data

How can we best translate the success of genome-wide association studies for neurological and neuropsychiatric diseases into therapeutic targets? Reynolds et al. critically assess existing brain-relevant functional genomic annotations and the tools available for integrating such annotations with summary-level genetic association data.

scholarly journals The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls

2018 ◽  
Author(s):  
Jonathan R. I. Coleman ◽  
Héléna A. Gaspar ◽  
Julien Bryois ◽  
Gerome Breen ◽  
◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Major Depression ◽  
Depressive Disorder ◽  
Mood Disorders ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Major Depressive ◽  
Genome Wide ◽  
Genome Wide Significance

AbstractBackgroundMood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders.MethodsTo clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) 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; non-overlapping N = 609,424).ResultsSeventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than 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 – positive in bipolar disorder but negative in major depressive disorder.ConclusionsThe mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

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