IC‐P‐158: GENETIC AND ENVIRONMENTAL FACTORS ARE DIFFERENTIALLY RELATED TO Aβ BURDEN IN THE PRESYMPTOMATIC PHASE OF AUTOSOMAL DOMINANT AND SPORADIC ALZHEIMER'S DISEASE
Bibliographic record
Abstract
Autosomal dominant Alzheimer's disease (ADAD) is considered as a model of preclinical sporadic Alzheimer's disease (sAD), since estimated years from symptom onset (EYO) can be derived in presymptomatic mutation carriers, taking parental age at symptom onset as a reference (Bateman et al., 2012). However, whether the preclinical phase of the disease is comparable between the two variants remains unclear. Our objective is to evaluate if factors known to affect Aβ trajectories in presymptomatic ADAD mutation carriers also affect asymptomatic individuals with a parental history (PH) of sAD, and vice-versa. Aβ-PET scans were collected using 11C-PIB in 114 presymptomatic ADAD mutation carriers (DIAN study; age=35.62±9.30) and 18F-NAV4694 in 82 asymptomatic individuals with a PH of sAD (PREVENT-AD cohort; age=66.51±4.63). General linear models were used to test in each cohort the effect of i) EYO (parent's age at symptom onset – participant's age at assessment) and ii) apolipoproteinE4 [APOE4], education (i.e. years of schooling) and their interaction on Aβ burden (mean neocortical SUVR). Analyses were controlled for age, gender and, for ADAD, mutation type (APP/presenilin1/presenilin2). EYO was related to increased Aβ burden in both cohorts (Figure 1). In asymptomatic individuals with a PH of sAD, we found an effect of APOE4 status, education, and an APOE4*education interaction, such that the protective effect of education was stronger in APOE4 carriers (Figure 2). In presymptomatic ADAD, APOE4 had no effect on Aβ accumulation, but completing higher levels of education were associated with lower Aβ burden. Complementary analysis in ADAD highlighted an education*mutation type interaction, indicating a stronger effect of education in presenilin carriers (Figure 2). Aβ accumulation as a function of the estimated years to symptoms onset (EYO) in presymptomatic autosomal dominant AD (ADAD) mutation carriers (left panel) and asymptomatic individuals with a parental history of sporadic(s) AD (right panel). EYO is associated with Aβ accumulation in the two cohorts. Solid lines represent estimated regression lines, while dotted lines represent 95% confidence intervals. Statistical values were obtained using partial correlations, controlling for age, gender and, in ADAD, mutation type. Gene * Education interaction on Aβ burden in presymptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals with a parental history of sporadic (s) AD. Education, but not apolipoprotein E (APOE)4, was related to Aβ burden in presymptomatic ADAD. Complementary analyses showed an Education * Mutation type interaction, such that the effect of education was present only in presenilin carriers (left panel). The APOE4 * Education interaction was significant in individuals at risk of sAD, such that the effect of education was present only in APOE4 carriers (right panel). Solid lines represent estimated regression lines, while dotted lines represent 95% confidence intervals. Statistical values were obtained from general linear models, controlling for age, gender and Mini Mental State. APOE4 homozygous carriers (n=1 in each cohort) were removed from these analyses. Our results suggest that a sporadic parental EYO might help to predict Aβ accumulation in preclinical sAD. While APOE4 is highly associated with Aβ burden in people at risk of sAD, APOE4 has no impact in ADAD. By contrast, environmental factors, approximated here using education, could affect biomarker progression in both variants of the disease, suggesting the existence of reserve mechanism both in individuals at risk of sAD and ADAD mutation carriers.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".