Abstract
Abstract
Background
Inflammation is associated with depression, but causality remains unclear. We investigated potential causality and direction of effect between inflammation and depression.
Methods
Using data from the ALSPAC birth cohort (n = 4021; 42.18 % male), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression and depression symptoms, assessed at ages 18y and 24y.
We used two-sample Mendelian randomization (MR) to investigate potential causality and directionality. Genetic variants for GlycA were obtained from UK Biobank (UKB) (N = 115,078); for depression from the Psychiatric Genomics Consortium and UKB (N = 500,199); and for depressive symptoms (N = 161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted method, we used sensitivity analyses to strengthen causal inference. We conducted multivariable MR adjusting for body mass index (BMI) due to known genetic correlation between inflammation, depression and BMI.
Results
In the cohort analysis, after adjusting for potential confounders we found no evidence of associations between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression (OR = 1∙18, 95 % CI: 1∙03–1∙36).
MR suggested no causal effect of GlycA on depression, but there was a causal effect of depression on GlycA (mean difference in GlycA = 0∙09; 95 % CI: 0∙03–0∙16), which was maintained in some, but not all, sensitivity analyses.
Limitations
The GWAS sample overlap could incur bias.
Conclusion
We found no consistent evidence for an effect of GlycA on depression. There was evidence that depression increases GlycA in the MR analysis, but this may be confounded/mediated by BMI.
Background
Inflammation is associated with depression, but causality remains unclear. We investigated potential causality and direction of effect between inflammation and depression.
Methods
Using data from the ALSPAC birth cohort (n = 4021; 42.18 % male), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression and depression symptoms, assessed at ages 18y and 24y.
We used two-sample Mendelian randomization (MR) to investigate potential causality and directionality. Genetic variants for GlycA were obtained from UK Biobank (UKB) (N = 115,078); for depression from the Psychiatric Genomics Consortium and UKB (N = 500,199); and for depressive symptoms (N = 161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted method, we used sensitivity analyses to strengthen causal inference. We conducted multivariable MR adjusting for body mass index (BMI) due to known genetic correlation between inflammation, depression and BMI.
Results
In the cohort analysis, after adjusting for potential confounders we found no evidence of associations between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression (OR = 1∙18, 95 % CI: 1∙03–1∙36).
MR suggested no causal effect of GlycA on depression, but there was a causal effect of depression on GlycA (mean difference in GlycA = 0∙09; 95 % CI: 0∙03–0∙16), which was maintained in some, but not all, sensitivity analyses.
Limitations
The GWAS sample overlap could incur bias.
Conclusion
We found no consistent evidence for an effect of GlycA on depression. There was evidence that depression increases GlycA in the MR analysis, but this may be confounded/mediated by BMI.
| Original language | English |
|---|---|
| Pages (from-to) | 431-439 |
| Number of pages | 9 |
| Journal | Journal of Affective Disorders |
| Volume | 335 |
| Early online date | 15 May 2023 |
| DOIs | |
| Publication status | Published - 15 Aug 2023 |
Bibliographical note
Funding Information:GMK acknowledges funding support from the Wellcome Trust (grant code: 201486/Z/16/Z ), the MQ: Transforming Mental Health (grant code: MQDS17/40 ), the Medical Research Council UK (grant code: MC_PC_17213 and MR/S037675/1 ) and the BMA Foundation (J Moulton grant 2019 ).
Funding Information:
ARC and MCB work in the MRC Integrative Epidemiology Unit (MC_UU_00011/6) and are supported by the University of Bristol British Heart Foundation Accelerator Award ( AA/18/7/34219 ).
Funding Information:
This work was supported in part by the GW4 BIOMED DTP (D.C., MR/N0137941/ ), awarded to the Universities of Bath, Bristol, Cardiff and Exeter from the Medical Research Council (MRC)/UKRI.
Funding Information:
This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol - http://www.bristol.ac.uk/acrc/. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council and Wellcome (Grant ref.: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and DC will serve as guarantor for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf); This research was specifically funded by Wellcome Trust and MRC (core) (Grant ref.: 76467/Z/05/Z), MRC (Grant ref.: MR/L022206/1) and Wellcome Trust (Grant ref.: 8426812/Z/07/Z). This work was supported in part by the GW4 BIOMED DTP (D.C. MR/N0137941/), awarded to the Universities of Bath, Bristol, Cardiff and Exeter from the Medical Research Council (MRC)/UKRI. GMK acknowledges funding support from the Wellcome Trust (grant code: 201486/Z/16/Z), the MQ: Transforming Mental Health (grant code: MQDS17/40), the Medical Research Council UK (grant code: MC_PC_17213 and MR/S037675/1) and the BMA Foundation (J Moulton grant 2019). AF, GK and others works in the MRC Integrative Epidemiology Unit (MC_UU_00011). ARC and MCB work in the MRC Integrative Epidemiology Unit (MC_UU_00011/6) and are supported by the University of Bristol British Heart Foundation Accelerator Award (AA/18/7/34219). The research by MCB was supported by a UK Medical Research Council (MRC) Skills Development Fellowship (MR/P014054/1) and a Vice-Chancellor's Fellowship from the University of Bristol. NG was supported by the John Templeton Foundation (Grant ref.: 61917).
Funding Information:
NG was supported by the John Templeton Foundation (Grant ref.: 61917 ).
Funding Information:
The UK Medical Research Council and Wellcome (Grant ref.: 217065/Z/19/Z ) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and DC will serve as guarantor for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ); This research was specifically funded by Wellcome Trust and MRC (core) (Grant ref.: 76467/Z/05/Z ), MRC (Grant ref.: MR/L022206/1 ) and Wellcome Trust (Grant ref.: 8426812/Z/07/Z ).
Funding Information:
The research by MCB was supported by a UK Medical Research Council (MRC) Skills Development Fellowship ( MR/P014054/1 ) and a Vice-Chancellor's Fellowship from the University of Bristol .
Publisher Copyright:
© 2023 The Authors
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Epidemiological investigations into chronic inflammation using the novel biomarker Glycoprotein Acetyls
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