Both clinically informed and brain region agnostic approaches identify neuroimaging derived phenotypes associated with genetically regulated gene expression of late‐onset Alzheimer’s disease genes

Background Genetically regulated gene expression (GReX) data leverages expression quantitative trait loci to investigate the genetic mechanism of Alzheimer’s disease (AD). This study utilized the GReX‐mediated neuro‐imaging derived phenotypes (NIDPs), summary features derived from brain imaging moda...

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Veröffentlicht in:Alzheimer's & dementia 2023-12, Vol.19 (S17), p.n/a
Hauptverfasser: Wang, Ting‐Chen, Bledsoe, Xavier, Shaw, Douglas, Chen, Hung‐Hsin, Naj, Adam C., Bush, William S., Gamazon, Eric J, Below, Jennifer E.
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Sprache:eng
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Zusammenfassung:Background Genetically regulated gene expression (GReX) data leverages expression quantitative trait loci to investigate the genetic mechanism of Alzheimer’s disease (AD). This study utilized the GReX‐mediated neuro‐imaging derived phenotypes (NIDPs), summary features derived from brain imaging modalities, as an endophenotype to identify brain regions associated with late‐onset AD (LOAD) via gene expression. Method This study contained brain region‐agnostic and region‐informed approaches. Both approaches utilized a set of 25 genes causally associated with LOAD in our previous cross‐tissue transcriptome‐wide association studies (TWAS) (Chen et al., 2021) to identify LOAD‐associated GReX‐mediated NIDPs. We leveraged the UK Biobank (UKBB) neuroimaging TWAS resource to provide GReX‐mediated NIDP information. Region‐agnostic: We assessed associations between GReX of LOAD genes and T1‐derived cortical and subcortical grey matter NIDPs from the UKBB neuroimaging TWAS. Region‐informed: We identified a set of AD‐associated cortical grey matter NIDPs from diagnosed AD patients (Westman et al., 2013). Next, we subset the UKBB neuroimaging TWAS data to those describing associations between GReX of LOAD genes and the selected AD NIDPs. A Benjamini‐Hochberg FDR p‐value threshold of 0.05 was used to establish statistical significance, and causal inference testing on associations between GReX of LOAD genes and NIDPs was conducted by implementing MR‐JTI in both approaches. Result Region‐agnostic: This approach found associations between GReX of 8 LOAD‐associated genes and 14 NIDPs (Figure 1). The most significant association is the GreX of ZNF296 and the right pars opercularis of the inferior frontal cortex, which replicated across 16 different tissues. Region‐informed: A single highly significant causal association between the GReX of PSMC3 and the ventral diencephalon was identified and replicated in gene expression models of 3 different bansal ganglia‐derived tissue models. Conclusion Our study shows the highly significant causal association between the GReX of ZNF296 and the right pars opercularis on LOAD through the region‐agnostic approach and the strong causal association between the GReX of PSMC3 and the ventral diencephalon on LOAD in AD‐associated region‐informed analyses. Our methodologies provide opportunities to explore brain regions associated with LOAD that are mediated by GReX of AD‐associated genes illuminating the impact of LOAD‐associated genes on gene e
ISSN:1552-5260
1552-5279
DOI:10.1002/alz.080191