Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Purves, Kirstin; Davis, Katrina; Rayner, Christopher; Choi, Shing Wan; Hübel, Christopher; Kan, Carol; Adams, Mark J.; Lyall, Donald M.; Choi, Karmel W.; Wray, Naomi R.; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M.; Abdellaoui, Abdel; Adams, Mark; Agerbo, Esben; Air, Tracy; Andlauer, Till F. M.; Bacanu, Silviu‐Alin; Bækvad‐Hansen, Marie; Beekman, Aartjan T.F.; Bigdeli, Tim B.; Binder, Elisabeth B.; Bryois, Julien; Buttenschøn, Henriette Nørmølle; Bybjerg‐Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni‐Kim; Coleman, Jonathan; Colodro‐Conde, Lucía; Couvy‐Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E.; Davies, Gail; Deary, Ian J.; Degenhardt, Franziska; Derks, Eske M.; Direk, Neşe; Dolan, Conor V.; Dunn, Erin C.; Eley, Thalia C.; Escott‐Price, Valentina; Kiadeh, Farnush Farhadi Hassan; Finucane, Hilary; Foo, Jerome C.; Forstner, Andreas J.; Frank, Josef; Gaspar, Héléna A.; Gill, Michael; Goes, Fernando S.; Gordon, Scott D.; Grove, Jakob; Hall, Lynsey S.; Hansen, Christine Søholm; Hansen, Thomas; Herms, Stefan; Hickie, Ian B.; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke‐Jan; Hougaard, David M.; Howard, David M.; Ising, Marcus; Jansen, Rick; Jones, Ian; Jones, Lisa; Jorgenson, Eric; Knowles, James A.; Kohane, Isaac S.; Kraft, Julia; Kretzschmar, Warren W.; Kutalik, Zoltán; Li, Yihan; Lind, Penelope A.; MacIntyre, Donald J.; MacKinnon, Dean F.; Maier, Robert; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick J.; McGuffin, Peter; Medland, Sarah E.; Mehta, Divya; Middeldorp, Christel M.; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mondimore, Francis M.; Montgomery, Grant W.; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G.; Nyholt, Dale R.; O’Reilly, Paul; Óskarsson, Högni; Owen, Michael John; Painter, Jodie N.; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E.; Pettersson, Erik; Peyrot, Wouter J.; Pistis, Giorgio; Posthuma, Daniëlle; Quiróz, Jorge A.; Qvist, Per; Rice, John P.; Riley, Brien P.; Rivera, Margarita; Mirza, Saira Saeed; Schoevers, Robert A.; Schulte, Eva C.; Shen, Lei; Shi, Jianxin; Shyn, Stanley I.; Sigurðsson, Engilbert; Sinnamon, Grant; Smit, Johannes H.; Smith, Daniel J.; Stefánsson, Hreinn; Steinberg, Stacy; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E.; Teismann, Henning; Teumer, Alexander; Thompson, Wesley K.; Thomson, Pippa A.; Thorgeirsson, Thorgeir E.; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, Andrés G.; Umbricht, Daniel; Auwera, Sandra Van der; Hemert, Albert M. van; Viktorin, Alexander; Visscher, Peter M.; Wang, Yunpeng; Webb, Bradley T.; Weinsheimer, Shantel; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H.; Wu, Yang; Xi, Hualin Simon; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T.; Berger, Klaus; Boomsma, Dorret I.; Cichon, Sven; Dannlowski, Udo; Geus, E.J.C. de; DePaulo, J. Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J.; Hamilton, Steven P.; Hayward, Caroline; Heath, Andrew C.; Kendler, Kenneth S.; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin; Lucae, Susanne; Madden, Pamela A. F.; Magnusson, Patrik K. E.; Martin, Nicholas; McIntosh, Andrew M.; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller‐Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M.; O’Donovan, Michael; Paciga, Sara A.; Pedersen, Nancy L.; Penninx, Brenda W. J. H.; Perlis, Roy H.; Porteous, David J.; Potash, James B.; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G.; Smoller, Jordan W.; Stefánsson, Kári; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M.; Werge, Thomas; Lewis, Cathryn M.; Levinson, Douglas F.; Børglum, Anders; Sullivan, Patrick F.; Dunn, Erin C.; Vassos, Evangelos; Danese, Andrea; Maughan, Barbara; Grabe, Hans‐Jörgen; Lewis, Cathryn M.; O’Reilly, Paul F.; McIntosh, Andrew M.; Smith, Daniel J.; Wray, Naomi R.; Hotopf, Matthew; Eley, Thalia C.; Breen, Gerome

doi:10.1038/s41380-019-0546-6

Cited by 140 publications

(153 citation statements)

References 96 publications

Supporting

Mentioning

145

Contrasting

Order By: Relevance

“…Compared with the ‘core MD factors’, an interaction between controls and recurrent MD with MD PRS was not detected for the factors relating to anxiety and subjective well-being at the level of nominal significance. This may suggest that although these symptom dimensions contain a highly pleiotropic genetic component (Purves et al, 2020), a diagnosis of MD contains a degree of specificity which reflects the structure suggested by the DSM and ICD. However, as no factors survived correction for multiple testing for the recurrent case interaction, this conclusion warrants further investigation.…”

Section: Discussionmentioning

confidence: 99%

“…MD PRS were constructed using PRSice v2 (Euesden, Lewis & O’Reilly, 2014) in unrelated individuals of European ancestry (N = 119,692) using genotype data and quality control procedures previously described (Supplementary Methods) (Bycroft et al, 2018; Coleman et al, 2020). Summary statistics from Wray et al (2018) with 23andMe and UK Biobank samples removed (N cases =45,591, N controls = 97,674) were used as the base dataset.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Using Major Depression Polygenic Risk Scores to Explore the Depressive Symptom Continuum

Jermy

Hagenaars

Glanville

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

BackgroundIt is not clear whether major depression (MD) is a categorical disorder or if depressive symptoms exist on a continuum based on severity. Observational studies comparing sub-threshold and clinical depression suggest MD is continuous, but many do not explore the full continuum and are yet to consider genetics as a risk factor. This study sought to understand if polygenic risk for MD could provide insight into the continuous nature of MD.MethodsFactor analysis on symptom-level data from the UK Biobank (N=148,957) was used to derive continuous depression phenotypes which were tested for association with polygenic risk scores for a categorical definition of MD (N=119,692).ResultsConfirmatory factor analysis showed a five-factor hierarchical model, incorporating 15 of the original 18 items, produced good fit to the observed covariance matrix (CFI = 0.992, TLI = 0.99, RMSEA = 0.038, SRMR = 0.031). MD PRS associated with each factor score (standardised ß range: 0.057 – 0.064) and the association remained when the sample was stratified into case- and control-only subsets. The case-only subset had an increased association compared to controls for all factors, shown via a significant interaction between lifetime MD diagnosis and MD PRS (p-value range: 2.28×10−3 - 4.56×10−7).ConclusionsAn association between MD PRS and a continuous phenotype of depressive symptoms in case- and control-only subsets provides support against a purely categorical phenotype; indicating further insights into MD can be obtained when this within-group variation is considered. The stronger association within cases suggests this variation may be of particular importance.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Using Major Depression Polygenic Risk Scores to Explore the Depressive Symptom Continuum

Jermy

Hagenaars

Glanville

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…This could relate to a difference in the extent and nature of the cognitive dysfunction, or the less heritable nature of depression and more penetrant influences of environmental stressors in its aetiology (77). The latter possibility is supported by a recent study in the UK Biobank which suggests that early life stress can amplify the penetrance of genetic risk signals in predisposing to major depressive disorder (78). In addition, it is supported by animal and in vitro studies which suggest that the downstream effects of stress, particularly increased cortisol levels and glucocorticoid receptor activation, might moderate depression risk by affecting the proliferation of hippocampal progenitors (41,49).…”

Section: <<< Figure 2 >>> (Ii) Old Hippocampal Progenitor Cells Exhibmentioning

confidence: 95%

The impact of telomere shortening on human hippocampal neurogenesis: Implications for cognitive function and psychiatric disorder risk

Palmos

Duarte

Smeeth

et al. 2020

Preprint

View full text Add to dashboard Cite

Telomere shortening is one hallmark of cell ageing that can limit the proliferative capacity of cell populations and increase risk for age-related disease. It has been hypothesized that short telomeres, and subsequently a limited proliferative capacity of hippocampal progenitor cells, could contribute to smaller hippocampal volumes and impaired cognition, amongst psychiatric disorder patients. The current study employed a systematic, multidisciplinary approach which aimed to model the effects of telomere shortening on human hippocampal neurogenesis, and to explore its relationship with cognition and psychiatric disorder risk. We modelled telomere shortening in human hippocampal progenitor cells in vitro using a serial passaging protocol that mimics the end-replication problem. Aged progenitors demonstrated shorter telomeres (p<0.05), and reduced rates of cell proliferation, as marked by bromodeoxyuridine staining (p<0.001), with no changes in the ability of cells to differentiate into neurons or glia. RNAsequencing and gene set enrichment analysis revealed an effect of cell ageing on gene networks related to neurogenesis, telomere maintenance, cell senescence and cytokine production. Downregulated transcripts showed a significant overlap with genes regulating cognitive function and risk for schizophrenia and bipolar disorder. Collectively, our results suggest that reductions in adult hippocampal neurogenesis, caused by telomere shortening, could represent a cellular mechanism contributing to age-related cognitive impairment and psychiatric disorder risk.

show abstract

“…Interactions on the additive scale assess whether the joint effect of smoking and the PRS is greater than the sum of their individual effects. Modelling multiplicative and additive GxE using linear and logistic regressions has been described elsewhere (29,30,39).…”

Section: Interaction Effect Analysesmentioning

confidence: 99%

“…However, no studies have tested whether PRSs for psychiatric disorders and smoking make independent contributions to psychotic experiences. Significant gene-environment interactions (GxE) have been reported for several psychiatric traits including schizophrenia and depression (28)(29)(30), but studies are yet to explore whether there is an interaction between smoking and PRSs for psychiatric disorders on psychotic experiences. That is, whether the effects of genetic risk are greater for individuals exposed to smoking.…”

Section: Introductionmentioning

confidence: 99%

The effects of polygenic risk for psychiatric disorders and smoking behaviour on psychotic experiences in UK Biobank

García‐González

Ramírez

Howard

et al. 2019

Preprint

View full text Add to dashboard Cite

While psychotic experiences are core symptoms of mental health disorders like schizophrenia, they are also reported by 5-10% of the population. Both smoking behaviour and genetic risk for psychiatric disorders have been associated with psychotic experiences, but the interplay between these factors remains poorly understood. We tested whether smoking status, maternal smoking around birth, and number of packs smoked/year were associated with lifetime occurrence of three psychotic experiences phenotypes: delusions (n=2067), hallucinations (n=6689), and any psychotic experience (delusions or hallucinations; n=7803) in 144818 UK Biobank participants. We next calculated polygenic risk scores for schizophrenia (PRSSCZ), major depression (PRSDEP) and attention deficit hyperactivity disorder (PRSADHD) in the UK Biobank participants to assess whether association between smoking and psychotic experiences was attenuated after adjustment of diagnosis of psychiatric disorders and the PRSs. Finally, we investigated whether smoking exacerbates the effects of genetic predisposition on the psychotic phenotypes in gene-environment interaction models. Smoking status, maternal smoking, and number of packs smoked/year were significantly associated with psychotic experiences (p<1.77x10-5). Except for packs smoked/year, effects were attenuated but remained significant after adjustment for diagnosis of psychiatric disorders and PRSs (p<1.99x10-3). Gene-environment interaction models showed the effects of PRSDEP and PRSADHD (but not PRSSCZ) on delusions (but not hallucinations) were significantly greater in current smokers compared to never smokers (p<0.0028). There were no significant gene-environment interactions for maternal smoking nor for number of packs smoked/year. Our results suggest that both genetic risk of psychiatric disorders and smoking status may have independent and synergistic effects on specific types of psychotic experiences.

show abstract

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Abstract: Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Cited by 140 publications

References 96 publications

Using Major Depression Polygenic Risk Scores to Explore the Depressive Symptom Continuum

Using Major Depression Polygenic Risk Scores to Explore the Depressive Symptom Continuum

The impact of telomere shortening on human hippocampal neurogenesis: Implications for cognitive function and psychiatric disorder risk

The effects of polygenic risk for psychiatric disorders and smoking behaviour on psychotic experiences in UK Biobank

Contact Info

Product

Resources

About