| Title: | Vitamin D and the risk of treatment-resistant and atypical depression: A Mendelian randomization study |
| Journal: | Translational Psychiatry |
| Published: | 4 Nov 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34737282/ |
| DOI: | https://doi.org/10.1038/s41398-021-01674-3 |
| URL: | https://www.nature.com/articles/s41398-021-01674-3.pdf |
Publication 5993
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Abstract
Observational evidence has implicated vitamin D levels as a risk factor in major depressive disorder (MDD). Confounding or reverse causation may be driving these observed associations, with studies using genetics indicating little evidence of an effect. However, genetic studies have relied on broad definitions of depression. The genetic architecture of different depression subtypes may vary since MDD is a highly heterogenous condition, implying potentially diverging requirements in therapeutic approaches. We explored the associations between vitamin D and two subtypes of MDD, for which evidence of a causal link could have the greatest clinical benefits: treatment-resistant depression (TRD) and atypical depression (AD). We used a dual approach, combining observational data with genetic evidence from polygenic risk scores (PRS) and two-sample Mendelian randomization (MR), in the UK Biobank. There was some evidence of a weak association between vitamin D and both incident TRD (Ncases = 830) and AD (Ncases = 2366) in observational analyses, which largely attenuated when adjusting for confounders. Genetic evidence from PRS and two-sample MR, did not support a causal link between vitamin D and either TRD (Ncases = 1891, OR = 1.01 [95%CI 0.78, 1.31]) or AD (Ncases = 2101, OR = 1.04 [95%CI 0.80, 1.36]). Our comprehensive investigations indicated some evidence of an association between vitamin D and TRD/AD observationally, but little evidence of association when using PRS and MR, mirroring findings of genetic studies of vitamin D on broad depression phenotypes. Results do not support further clinical trials of vitamin D in these MDD subtypes but do not rule out that small effects may exist that require larger samples to detect.9 Authors
- Ryan Arathimos
- Amy Ronaldson
- Laurence J. Howe
- Chiara Fabbri
- Saskia Hagenaars
- Matthew Hotopf
- Fiona Gaughran
- Cathryn M. Lewis
- Alexandru Dregan
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