ArticleScientific reports2023
Investigation of genetic variants and causal biomarkers associated with brain aging.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The trial behind it
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Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Metabolomic signatures of brain aging: A multimodal and genetic study.Molecular psychiatry · 2026Article
- Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics.Communications medicine · 2025Article
- Integration of Genetic Information to Improve Brain Age Gap Estimation Models in the UK Biobank.Human brain mapping · 2025Article
- Association Between Plasma Metabolomic Profile and Machine Learning-Based Brain Age.Aging cell · 2025Article
- Genome-wide analysis of brain age identifies 59 associated loci and unveils relationships with mental and physical health.Nature aging · 2025Article
- Measurement characteristics and genome-wide correlates of lifetime brain atrophy estimated from a single MRI.Nature communications · 2025Article
- A review of artificial intelligence-based brain age estimation and its applications for related diseases.Briefings in functional genomics · 2025Review
- Decoding brain aging trajectory: predictive discrepancies, genetic susceptibilities, and emerging therapeutic strategies.Frontiers in aging neuroscience · 2025Review
- qMAP enabled microanatomical mapping of human skin aging.bioRxiv : the preprint server for biology · 2024Article
- Cellular senescence in brain aging and cognitive decline.Frontiers in aging neuroscience · 2023Review
- Deep learning interpretability in neuroimaging: A comprehensive survey and methodological recommendations.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 2 countries.
Funding
Abstract
Delta age is a biomarker of brain aging that captures differences between the chronological age and the predicted biological brain age. Using multimodal data of brain MRI, genomics, and blood-based biomarkers and metabolomics in UK Biobank, this study investigates an explainable and causal basis of high delta age. A visual saliency map of brain regions showed that lower volumes in the fornix and the lower part of the thalamus are key predictors of high delta age. Genome-wide association analysis of the delta age using the SNP array data identified associated variants in gene regions such as KLF3-AS1 and STX1. GWAS was also performed on the volumes in the fornix and the lower part of the thalamus, showing a high genetic correlation with delta age, indicating that they share a genetic basis. Mendelian randomization (MR) for all metabolomic biomarkers and blood-related phenotypes showed that immune-related phenotypes have a causal impact on increasing delta age. Our analysis revealed regions in the brain that are susceptible to the aging process and provided evidence of the causal and genetic connections between immune responses and brain aging.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.