Perinatal depression is associated with a higher polygenic risk for major depressive disorder than non‐perinatal depression

2022 ◽  
Author(s):  
Jacqueline Kiewa ◽  
Samantha Meltzer‐Brody ◽  
Jeanette Milgrom ◽  
Jerry Guintivano ◽  
Ian B. Hickie ◽  
...  
2015 ◽  
Vol 46 (4) ◽  
pp. 759-770 ◽  
Author(s):  
N. Mullins ◽  
R. A. Power ◽  
H. L. Fisher ◽  
K. B. Hanscombe ◽  
J. Euesden ◽  
...  

BackgroundMajor depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.MethodThe RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.ResultsPRS significantly predicted depression, explaining 1.1% of variance in phenotype (p= 1.9 × 10−6). SLEs and CT were also associated with MDD status (p= 2.19 × 10−4andp= 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p= 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.ConclusionsCT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.


2020 ◽  
Vol 98 (12) ◽  
pp. 2529-2540
Author(s):  
Henriette Acosta ◽  
Katri Kantojärvi ◽  
Jetro J. Tuulari ◽  
John D. Lewis ◽  
Niloofar Hashempour ◽  
...  

2019 ◽  
Vol 50 (10) ◽  
pp. 1653-1662 ◽  
Author(s):  
Mathew A. Harris ◽  
Xueyi Shen ◽  
Simon R. Cox ◽  
Jude Gibson ◽  
Mark J. Adams ◽  
...  

AbstractBackgroundSubstantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.MethodsThe present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants.ResultsThere was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = −0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.ConclusionsOur significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.


2016 ◽  
Vol 6 (11) ◽  
pp. e938-e938 ◽  
Author(s):  
H C Whalley ◽  
M J Adams ◽  
L S Hall ◽  
T-K Clarke ◽  
A M Fernandez-Pujals ◽  
...  

2019 ◽  
Vol 29 ◽  
pp. S1291
Author(s):  
Mathew Harris ◽  
Xueyi Shen ◽  
Simon Cox ◽  
Jude Gibson ◽  
Mark Adams ◽  
...  

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