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BMC Med Genomics. 2018 Sep 14;11(Suppl 3):76. doi: 10.1186/s12920-018-0390-6.

Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer's disease.

Author information

1
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, USA.
2
Present Address: Department of Genetics, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
3
Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, 84106, USA.
4
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
5
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA. knho@iupui.edu.
6
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, USA. dkim@geisinger.edu.
7
Huck Institute of the Life Sciences, Pennsylvania State University, University Park, PA, USA. dkim@geisinger.edu.

Abstract

BACKGROUND:

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases that causes problems related to brain function. To some extent it is understood on a molecular level how AD arises, however there are a lack of biomarkers that can be used for early diagnosis. Two popular methods to identify AD-related biomarkers use genetics and neuroimaging. Genes and neuroimaging phenotypes have provided some insights as to the potential for AD biomarkers. While the field of imaging-genomics has identified genetic features associated with structural and functional neuroimaging phenotypes, it remains unclear how variants that affect splicing could be important for understanding the genetic etiology of AD.

METHODS:

In this study, rare variants (minor allele frequency < 0.01) in splicing regulatory element (SRE) loci from whole genome sequencing (WGS) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, were used to identify genes that are associated with global brain cortical glucose metabolism in AD measured by FDG PET-scans. Gene-based associated analyses of rare variants were performed using the program BioBin and the optimal Sequence Kernel Association Test (SKAT-O).

RESULTS:

The gene, EXOC3L4, was identified as significantly associated with global cortical glucose metabolism (FDR (false discovery rate) corrected p < 0.05) using SRE coding variants only. Three loci that may affect splicing within EXOC3L4 contribute to the association.

CONCLUSION:

Based on sequence homology, EXOC3L4 is likely a part of the exocyst complex. Our results suggest the possibility that variants which affect proper splicing of EXOC3L4 via SREs may impact vesicle transport, giving rise to AD related phenotypes. Overall, by utilizing WGS and functional neuroimaging we have identified a gene significantly associated with an AD related endophenotype, potentially through a mechanism that involves splicing.

KEYWORDS:

Alternative splicing; Alzheimer’s disease; Imaging genomics; Rare variants; Whole genome sequencing

PMID:
30255815
PMCID:
PMC6156983
DOI:
10.1186/s12920-018-0390-6
[Indexed for MEDLINE]
Free PMC Article

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