Whole genome sequence‐based association of cognitive decline and retinal thickness in the Japanese population
Bibliographic record
Abstract
Abstract Background Dementia is age‐related with a significant genetic contribution, yet genome‐wide association studies have not fully accounted for heritability. This discrepancy may in part be due to reliance on SNPs and small indels. Whole‐genome sequencing (WGS) data in the Japanese population may reveal population‐specific susceptibility loci for dementia. Retinal imaging with optical coherence tomography (OCT) is noninvasive, reproducible, and can detect thinning associated with progressive neurodegeneration. Association of population‐specific genetic susceptibility loci with retinal thinning and cognitive decline may reveal novel aspects of dementia risk and pathophysiology. Method Among participants with WGS data from the Tohoku Medical Megabank Organization (ToMMo) Ophthalmology Study ("ToMMo Eye Study"), individuals with adequate quality data on retinal nerve fiber layer and ganglion cell layer thickness from spectral‐domain optical coherence tomography (SD‐OCT) scans were selected. Since retinal thinning also occurs in glaucoma, we performed a GWAS using age, sex, and 10 principal components as covariates using SAGE1.2 to obtain a set of genes responsible for glaucoma and confirm that the genotyping was successful. We then attempted to identify susceptibility loci for cognitive decline by using (1) the Mini‐Mental State Examination, Japanese version (MMSE‐J), (2) the Montreal Cognitive Assessment, Japanese version (MoCA‐J), and (3) the Mini‐COG© (a simple screening for early detection of dementia, Japanese version) scores as associated factors, respectively. Furthermore, these validation results were also compared with those obtained from GWAS using imputation data performed on custom arrays (Japonica ArrayTM, v2 or NEO) for Japanese. Result 84 significant (p < 5.0E‐8) genome‐wide susceptibility loci (hg38) of RNFL were detected on 14K WGS‐based study (the top hit locus: Chr14, SIX6 gene, P=4.50E‐46). There were many genetic loci that have already been reported to be associated with glaucoma susceptibility, including the above locus. Among the results of GWAS for cognitive decline combining the three cognitive scores after normalization to z‐scores, several loci have shown significant susceptibility in both of RNFL and cognitive rating scale. Some loci suggested more than a high or moderate effect of altering protein efficacy. Conclusion We present an initial WGS‐based genetic study of retinal thickness and cognitive decline in the Japanese population.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".