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Updated: Jun 12, 2026
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Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
Shared genetic architecture between Alzheimer's disease and brain morphology
Xiao Wu1, Alexey Shadrin2, Gabriëlla A M Blokland3
1Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands. xiao.wu@maastrichtuniversity.nl.
Alzheimer'S Research & Therapy
|June 11, 2026
Summary
Genetic overlap exists between Late-onset Alzheimer's disease (LOAD) and brain morphology, despite no global correlation. Shared genetic factors influence cell development, offering insights into neurodegeneration mechanisms.
Area of Science:
- Neurogenetics
- Brain Morphology
- Alzheimer's Disease Research
Background:
- Late-onset Alzheimer's disease (LOAD) is characterized by brain atrophy.
- Genetic drivers of neurodegeneration and their link to brain morphology are complex and not fully understood.
- Resolving the shared genetic architecture is crucial for understanding LOAD pathogenesis.
Purpose of the Study:
- To investigate the genetic architecture shared between LOAD and brain morphology.
- To identify specific genetic loci and biological pathways implicated in both conditions.
- To clarify the relationship between genetic factors influencing brain structure and LOAD risk.
Main Methods:
- Analysis of UK Biobank genotype data (n=272,513) and LOAD genome-wide association study summary statistics.
- Utilized linkage disequilibrium score regression (LDSC), polygenic score (PGS), and Local Analysis of [co]Variant Association (LAVA).
- Employed bivariate causal mixture modeling (MiXeR) and conjunctional FDR to identify shared loci and pathways.
Main Results:
- No significant global genetic correlations were found between LOAD and brain morphology using LDSC or PGS.
- LAVA identified significant local genetic correlations (positive and negative) across all LOAD-brain trait pairs.
- 183 shared loci mapping to 80 genes involved in cell differentiation, development, and organization were identified, explaining the lack of global correlation through mixed effect directions.
Conclusions:
- Extensive polygenic overlap exists between LOAD and brain morphology, driven by mixed local effect directions.
- Shared genetic architectures implicate pathways in cellular development and differentiation.
- Provides a molecular framework for understanding the link between brain morphology and LOAD.
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