Molecular NeurodegenerationNeurosciencePeer-reviewed journal article
Spectrum of gamma-Secretase dysfunction as a unifying predictor of ADAD age at onset across PSEN1, PSEN2 and APP causal genes
Sara Gutiérrez FernándeziD, Cristina Gan Oria, Dieter PetitiD, Wim G. AnnaertiD, John Matthew RingmaniD, Nick C. FoxiD, Natalie Sarah RyaniD, Lucía Chávez‐GutiérreziD
Abstract
Autosomal Dominant Alzheimers Disease (ADAD), caused by mutations in Presenilins (PSEN1/2) and Amyloid Precursor Protein (APP) genes, typically manifests before age 65. Age at symptom onset (AAO) is relatively consistent among carriers of the same PSEN1 mutation, but more variable for PSEN2 and APP variants, with these mutations associated with later AAOs than PSEN1. Understanding this clinical variability is crucial for developing predictive models and tailored interventions in ADAD. Biochemical in vitro assessment of {gamma}-secretase function is valuable in evaluating PSEN1 variant pathogenicity, disease onset and progression. Here, we examined A{beta} profiles relationships to AAO across causal genes. Our analysis showed linear correlations between mutation-induced shifts in A{beta} profiles and AAO for PSEN2 and APP mutations. Integration with PSEN1 data revealed parallel but shifted correlations, indicating a common pathogenic mechanism with gene-specific onset timing shifts. Our data support a unified model of ADAD pathogenesis wherein {gamma}-secretase dysfunction and shifts in A{beta} profiles define disease onset. This biochemical analysis of ADAD causality and established quantitative relationships deepen our understanding of ADAD pathogenesis, offering potential for predictive AAO modelling with implications for clinical practice, genetic research and development of therapeutic strategies modulating {gamma}-secretase across ADAD forms and potentially more broadly in AD. SummaryWe examined the relationships between (full) A{beta} peptide profiles and age at symptom onset (AAO) across all Alzheimers disease causal genes. Our findings establish a quantitative framework for mutations pathogenicity assessment and AAO prediction; with implications for clinical practice, genetic counselling, fundamental and translational research.
- organism: human
- assay: proteomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- Citations
- 11
- FWCI
- 7.02
- Field percentile
- top 2%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Functional variations in gamma-secretase activity are critical determinants of the clinical, biomarker, and cognitive progression of autosomal dominant Alzheimer's disease
Stephanie A. Schultz, Lei Liu, … Dominantly Inherited Alzheimer Network Investigators·bioRxiv·Jul 4, 2023
- Correlations of 276 missense variants of PSEN1, PSEN2, and APP on the production of Aβ peptides against variant effect predictors and biophysical structures
J. J. Song, Serina Yan, … Chengbiao Wu·bioRxiv·Feb 11, 2026
- Plasma amyloid beta ratios in autosomal dominant Alzheimers disease: the influence of genotype
Antoinette O’Connor, Josef Pannee, … Nick C. Fox·BrainPeer-reviewed·Apr 22, 2021
- The pathogenicity of PSEN2 variants is tied to Aβ production and homology to PSEN1
Lei Liu, Stephanie A. Schultz, … Jasmeer P. Chhatwal·Alzheimer s & DementiaPeer-reviewed·Nov 19, 2024
- Alzheimer-mutant γ-secretase complexes stall amyloid β-peptide production
Parnian Arafi, Sujan Devkota, … Michael S. Wolfe·bioRxiv·Aug 30, 2024
- Alzheimer mutations stabilize synaptotoxic γ-secretase-substrate complexes
Sujan Devkota, Rui Zhou, … Michael S. Wolfe·bioRxiv·Sep 8, 2023