| Title: | Large-scale neuroimaging and genetic analyses of the human thalamus in loneliness |
| Journal: | Biological Psychiatry Global Open Science |
| Published: | 1 Jul 2026 |
| DOI: | https://doi.org/10.1016/j.bpsgos.2026.100798 |
| URL: | https://www.sciencedirect.com/science/article/pii/S2667174326001114/pdf |
Publication 21383
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Abstract
Background While loneliness is prevalent and significantly impacts society globally, its neural and genetic bases remain poorly understood. The thalamus, which receives sensory information from the environment, may have a more significant role in social interactions than previously recognized. Here, we integrate neuroimaging and genetic approaches to characterize structural differences within the thalamus associated with loneliness. Methods We obtained thalamic nuclei volumes on brain scans from 45,834 individuals (age range: 45-82) in the UK Biobank and grouped them into six anatomical groups. We investigated effects of loneliness and social isolation using self-reported data. We then performed GWAS analyses on the genetic overlap between thalamic volumes and loneliness. Results The volumes of the whole thalamus and its medial, lateral, and posterior nuclei are significantly reduced in individuals with loneliness compared to those who do not feel lonely. Frequent loneliness without social isolation is associated with smaller volumes, whereas social isolation without loneliness shows no such reduction. Leveraging data from genome-wide association studies on thalamic volumes (n = 30,114) and loneliness (n = 370,342) in UK Biobank, we identify loci shared between thalamus structure and loneliness. Conclusions Our findings support the emerging view that the thalamus plays important roles in social interactions and in the experience of loneliness.</p>
8 Authors
- Verónica Mäki-Marttunen
- Uta Sailer
- Jakub Kopal
- Espen Hagen
- Alexey Shadrin
- Ole A. Andreassen
- Linn Nilsen Rødevand
- Torbjørn Elvsåshagen
1 Application
| Application ID | Title |
|---|---|
| 27412 | Boosting the power of GWAS using novel statistical tools |
Enabling scientific discoveries that improve human health