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Proteogenomic signature of Alzheimer’s disease and related dementia risk in individuals with major depressive disorder

Nature Mental Health volume 3, pages 879–888 (2025)Cite this article

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Abstract

The mechanisms linking a history of major depressive disorder (MDD) to an increased risk of Alzheimer’s disease and related dementia (ADRD) are not fully understood. Using the UK Biobank, we evaluated the biological mechanisms linking the conditions. In participants without history of MDD, 493 proteins were significantly associated with the risk of ADRD. By contrast, in participants with a history of MDD at baseline, a smaller set of six proteins were significantly associated with ADRD risk (NfL, GFAP, PSG1, VGF, GET3 and HPGDS), with GET3 being specifically associated with ADRD risk in the latter group. Two-sample Mendelian randomization analysis showed that the apolipoprotein E and IL-10 receptor subunit B genes were causally linked to incident ADRD. Finally, we developed a proteomic risk score (PrRSMDD-ADRD), which showed strong discriminative power (C statistic = 0.84) to identify participants with MDD who developed ADRD on follow-up. Here we show that plasma proteins associated with inflammation and amyloid-β metabolism are causally linked to a higher ADRD risk in individuals with MDD. Moreover, the PrRSMDD-ADRD can be useful to identify individuals with the highest risk of developing ADRD in a highly vulnerable population.

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Fig. 1: Proteins significantly associated with incident ADRD in participants with a history of MDD at baseline (n = 3,615).
Fig. 2: MR-Egger plots to show causal estimates from IVW versus other MR methods for the effects of APOE and IL10RB (IVW FDR-adjusted P < 0.05) on incident ADRD in participants of European descent with a history of MDD at baseline (n = 30,903).
Fig. 3: Spearman correlations between PrRSMDD-ADRD, age and cognitive performance measures from baseline (reaction time, numeric memory, fluid intelligence score) or first imaging visit (symbol digit substitution, trail making, matrix pattern completion).
Fig. 4: Spearman correlations of PrRSMDD-ADRD with T1 structural and T2-weighted brain MRI IDPs, adjusting for head size.

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Data availability

The analyses were done using the restricted and sensitive data from the UK Biobank dataset. These data are available on request following the UK Biobank policies.

Code availability

The code for the calculation of the PrRSMDD-ADRD is available at https://github.com/kuo-lab-uchc.

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Acknowledgements

This research was supported by NIH grant P30AG067988 and has been conducted using the UK Biobank Resource under Application Number 92647, ‘Research to Inform the Field of Precision Gerontology’ (principal investigator R. H. Fortinski). In particular, this work uses data provided by patients and collected by the NHS as part of their care and support.

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Authors and Affiliations

  1. UConn Center on Aging, University of Connecticut Health Center, Farmington, CT, USA

    Breno Satler Diniz, Zhiduo Chen, Richard H. Fortinsky, George A. Kuchel & Chia-Ling Kuo

  2. Department of Psychiatry, University of Connecticut Health Center, Farmington, CT, USA

    Breno Satler Diniz & David C. Steffens

  3. Epidemiology and Public Health Group, Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK

    Luke Pilling

  4. The Cato T. Laurencin Institute for Regenerative Engineering, University of Connecticut Health Center, Farmington, CT, USA

    Yuliya Nikolova

  5. Centre for Addiction and Mental Health, Toronto, Ontario, Canada

    Kevan Clifford & Chia-Ling Kuo

  6. Department of Public Health Sciences, University of Connecticut Health Center, Farmington, CT, USA

    Chia-Ling Kuo

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Contributions

B.S.D.: study conception and design, result interpretation, paper draft, and revision. Z.C.: data analysis, result interpretation, and paper review. D.C.S.: result interpretation and paper review. L.P.: consulted on data analysis, result interpretation, and paper review. Y.N., K.C.: figure preparation, result interpretation, and paper review. R.H.F. and G.A.K.: result interpretation and paper review. C.-L.K.: study conception and design, data analysis, result interpretation, paper draft, and revision.

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Correspondence to Breno Satler Diniz.

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Diniz, B.S., Chen, Z., Steffens, D.C. et al. Proteogenomic signature of Alzheimer’s disease and related dementia risk in individuals with major depressive disorder. Nat. Mental Health 3, 879–888 (2025). https://doi.org/10.1038/s44220-025-00460-0

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