Genetic and Causal Insights Into White Matter Hyperintensities Across the Brain‐Body Axis
Bibliographic record
Abstract
BACKGROUND: White matter hyperintensities (WMHs), visible as bright regions on T2-weighted FLAIR MRI, are frequent with age and elevated in Alzheimer's disease (AD). Representing axonal damage, demyelination, and edema, WMHs are driven by vascular mechanisms, including endothelial dysfunction and impaired cerebrovascular autoregulation. WMHs also exhibit strong heritability (55-73%), with overlapping genetic pathways shared with AD. Emerging evidence suggests systemic factors across the brain-body axis influence WMHs, yet these contributions and their genetic overlap with AD remain underexplored. Our study investigated genetic underpinnings specific to WMHs and those shared with AD by assessing partitioned heritability of WMHs and AD across the brain-body axis with SNP level tissue- and cell-specific annotations; identifying genes associated with WMHs and AD through integration of gene expression data, establishing causal links between SNP-level findings and imaging-derived phenotypes (IDPs), particularly structural variations in regional brain volumes. METHOD: Partitioned heritability was assessed using stratified-linkage disequilibrium score regression (sLDSC) on GWAS summary statistics (N = 3 WMH studies; N = 6 AD studies) using human A1) tissue level annotations (N = 10) and A2) continuous cell-specific annotations (N = 64). MAGMA and FUSION analyses highlighted genes associated with WMH and AD for further bioinformatics analysis (using human protein atlas (HPA) and STRING database). MACAW (Vigneshwaran et al, 2024) modeled causal relationships between WMH-associated SNPs (from FUMA analysis) and IDPs (N = 172), leveraging directed acyclic graphs to evaluate genetic effects while controlling for confounders (Figure 2). RESULT: Tissue-specific analysis revealed significant enrichment of WMH-associated SNPs in the CNS, liver, cardiovascular system, and kidneys, while AD-associated SNPs were enriched in the CNS, connective bone, liver, and immune tissues. (Figure 1). Cell-specific analysis identified vascular endothelial cells as enriched across WMH-enriched tissues. MAGMA analysis, combined with HPA analysis, corroborated sLDSC tissue-level findings. MAGMA and FUSION analyses highlighted genes associated with WMHs (N = 39 and 69) and AD (N = 291 and 193). MACAW linked WMH-associated SNP to 172 IDPs, consistently impacting WM hypointensities and regional brain volumes (e.g., left inferior temporal volume). CONCLUSION: Our findings highlight systemic multi-tissue contributions (CNS, liver, cardiovascular system, and kidneys) to WMHs, driven by vascular endothelial dysfunction and shared AD genetics, with SNPs across the body also affecting brain imaging derived phenotypes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".