Association of low frequency variants with regional cortical grey matter volumes in genetic frontotemporal dementia: Results from GENFI
Bibliographic record
Abstract
Abstract Background Frontotemporal dementia (FTD) is a neurodegenerative condition characterized by heterogeneous clinical, pathological, and genetic features. Mutations in three genes account for the majority of autosomal dominant FTD: GRN, MAPT, and C9orf72. We tested whether gene‐based aggregate burden of genome‐wide low‐frequency variants contribute to variation in regional cortical and subcortical grey matter volumes in the GENetic Frontotemporal dementia Initiative (GENFI), after controlling for effects of autosomal dominant mutations. Method GENFI recruits symptomatic and presymptomatic participants from families segregating genetic FTD. We included 517 participants with genotype (Neurochip; imputed against TOPMed), and T1w‐MRI brain volumetric data. Gene‐based burden tests that aggregate the number of uncommon/rare variants by gene were used to examine the association of low‐frequency variants (minor allele frequency: 0.000001 to <0.05) with regional cortical and subcortical grey matter volumes, controlling for age, sex, total intracranial volume, mutation status, population stratification, and family membership (kinship matrix). In two separate analyses, we used the following set of annotations to account for (i) loss of function mutations (LOF): start gain, stop loss, start loss, essential splice site, stop gain, normal splice site, and non‐synonymous, (ii) insertions, deletions, and frameshift mutations (indel‐fs). Result Of the 517 participants (300 women), 307 were mutation carriers (symptomatic = 82). For LOF mutations (731 genes tested; significance threshold: p = 0.05/731 = 6.8×10−5), aggregate burden of variants in BSND were associated with lower volumes in: temporal (p = 6.6×10−6), left insula (p = 5.0×10−5), and ventromedial prefrontal cortical (p = 2.8×10−5) regions. For indel‐fs mutations (826 genes tested; significance threshold: p = 0.05/826 = 6.05×10−5), aggregate burden of variants in: (i) E2F2 was associated with lower volumes in occipital (p = 8.7×10−6) regions; (ii) TMEM61 was associated with lower volumes in left temporal (p = 7.8×10−7), and left cingulate regions (p = 5.5×10−5); (iii) KDM4A‐AS1 was associated with lower volumes in the right temporal (p = 3.2×10‐7) region. All genes are variably expressed in the brain. Conclusion Identification of deleterious or protective low‐frequency variants contributing to FTD imaging phenotypes may help identify genetic modifiers of familial FTD. Replication of results followed by functional studies are needed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".