Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease
Bibliographic record
Abstract
Abstract Background Limbic white matter (WM) abnormalities are strongly elevated along the Alzheimer's Disease (AD) diagnostic continuum, but the underlying biological mechanisms remain unclear. This study aims to conduct a large‐scale genetic analysis of WM microstructure in older adults. Method WM was assessed in seven limbic tracts, including the cingulum, fornix, inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and transcallosal tracts of the inferior, middle, and superior temporal gyri (ITG, MTG, STG) using advanced diffusion MRI metrics corrected for free‐water (FW) (fractional anisotropy [FA FWcorr ], axial diffusivity [AxD FWcorr ], mean diffusivity [MD FWcorr ], radial diffusivity [RD FWcorr ]). Genetic associations with WM microstructure were investigated using harmonized data from seven aging cohorts, comprising 2,614 non‐Hispanic white older adults (mean age = 73.66 ± 9.76; 42.65% male), through SNP‐heritability estimation, genome‐wide association studies (GWAS), and post‐GWAS analyses (genetic correlation, gene‐level, and pathway analysis). Bulk RNA‐seq brain data were used to evaluate the relationship between expression of genes identified in the GWAS with cognition and AD pathologies. Result WM microstructure is heritable, with 16 of 35 metrics exhibiting estimates between 0.26 and 0.60 (p FDR <0.05). Genome‐wide associations ( p <5×10 −8 ) were observed for fornix AxD FWcorr (chr3, rs78407651), ILF FA FWcorr (chr15, rs8026709) and AxD FWcorr (chr15, rs8026709), STG RD FWcorr (chr10, rs11542181), and cingulum RD FWcorr (chr6, rs56017587). A locus with 38 genome‐wide significant SNPs (chr18, rs12959877) was associated with FA FWcorr and RD FWcorr (Figure 1). These SNPs are eQTLs for CDH19 , a gene highly expressed in oligodendrocytes with a role in cell adhesion. Among the genes identified in the GWAS, RORA , FAM107 and KC6 expression in brain tissues was linked to cognitive decline and AD pathologies (p FDR <.05). Gene‐level analysis highlighted SERPINA12 (z=4.60, p FDR =.03), a gene implicated in type 2 diabetes and atherosclerosis. Pathway analysis revealed associations with insulin, immune response, and neurotrophic signaling. Genetic correlations were identified with lipid profiles, cardiovascular traits, and neuropsychiatric conditions (p FDR <.05). Conclusion This study identified genetic factors related to cognition, vascular health, and inflammation as contributors to WM microstructure changes in aging and AD. These findings open avenues for future research on AD's molecular mechanisms and therapeutic targets for improving vascular and metabolic health in aging populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".