Brain–heart–eye axis revealed by multi-organ imaging genetics and proteomics
Why this work is in the frame
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Bibliographic record
Abstract
Multi-organ research investigates interconnections among multiple human organ systems, enhancing our understanding of human aging and disease mechanisms. Here we use multi-organ imaging, individual- and summary-level genetics, and proteomics data consolidated via the MULTI Consortium to delineate a brain-heart-eye axis using brain patterns of structural covariance (PSCs), heart imaging-derived phenotypes (IDPs) and eye IDPs. We find that proteome-wide associations of the PSCs and IDPs show within-organ specificity and cross-organ interconnections. Pleiotropic effects of common single-nucleotide polymorphisms are observed across multiple organs, and key genetic parameters are estimated for single-nucleotide polymorphism-based heritability, polygenicity and selection signatures across the three organs. A gene-drug-disease network shows the potential of drug repurposing for cross-organ diseases. Co-localization and causal analyses reveal cross-organ causal relationships between PSC/IDP and chronic diseases, such as Alzheimer's disease, heart failure and glaucoma. Finally, integrating multi-organ/omics features improves prediction for systemic disease categories and cognition compared with single-organ/omics features, providing future avenues for modelling human aging and disease.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it