Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker

Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder with few biomarkers even though it impacts a relatively large portion of the population and is predicted to affect significantly more individuals in the future. Neuroimaging has been used in concert with genetic information to improve our understanding in relation to how AD arises and how it can be potentially diagnosed. Additionally, evidence suggests synonymous variants can have a functional impact on gene regulatory mechanisms, including those related to AD. Some synonymous codons are preferred over others leading to a codon bias. The bias can arise with respect to codons that are more or less frequently used in the genome. A bias can also result from optimal and non-optimal codons, which have stronger and weaker codon anti-codon interactions, respectively. Although association tests have been utilized before to identify genes associated with AD, it remains unclear how codon bias plays a role and if it can improve rare variant analysis. In this work, rare variants from whole-genome sequencing from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort were binned into genes using BioBin. An association analysis of the genes with AD-related neuroimaging biomarker was performed using SKAT-O. While using all synonymous variants we did not identify any genome-wide significant associations, using only synonymous variants that affected codon frequency we identified several genes as significantly associated with the imaging phenotype. Additionally, significant associations were found using only rare variants that contains an optimal codon in among minor alleles and a non-optimal codon in the major allele. These results suggest that codon bias may play a role in AD and that it can be used to improve detection power in rare variant association analysis.

Original languageEnglish (US)
Title of host publicationPACIFIC SYMPOSIUM ON BIOCOMPUTING 2018
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages365-376
Number of pages12
Edition212669
ISBN (Print)9789813235533
DOIs
StatePublished - Jan 1 2018
Event23rd Pacific Symposium on Biocomputing, PSB 2018 - Kohala Coast, United States
Duration: Jan 3 2018Jan 7 2018

Other

Other23rd Pacific Symposium on Biocomputing, PSB 2018
CountryUnited States
CityKohala Coast
Period1/3/181/7/18

Fingerprint

Biomarkers
Genes
Imaging techniques
Neuroimaging
Association reactions

Keywords

  • Alzheimer’s disease
  • BioBin
  • Codon bias
  • Neuroimaging
  • Rare variant analysis
  • SKATO
  • Synonymous variant

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics

Cite this

Alzheimer’s Disease Neuroimaging Initiative (ADNI) (2018). Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker. In PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018 (212669 ed., pp. 365-376). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789813235533_0034

Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker. / Alzheimer’s Disease Neuroimaging Initiative (ADNI).

PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018. 212669. ed. World Scientific Publishing Co. Pte Ltd, 2018. p. 365-376.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2018, Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker. in PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018. 212669 edn, World Scientific Publishing Co. Pte Ltd, pp. 365-376, 23rd Pacific Symposium on Biocomputing, PSB 2018, Kohala Coast, United States, 1/3/18. https://doi.org/10.1142/9789813235533_0034
Alzheimer’s Disease Neuroimaging Initiative (ADNI). Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker. In PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018. 212669 ed. World Scientific Publishing Co. Pte Ltd. 2018. p. 365-376 https://doi.org/10.1142/9789813235533_0034
Alzheimer’s Disease Neuroimaging Initiative (ADNI). / Codon bias among synonymous rare variants is associated with alzheimer’s disease imaging biomarker. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018. 212669. ed. World Scientific Publishing Co. Pte Ltd, 2018. pp. 365-376
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abstract = "Alzheimer’s disease (AD) is a neurodegenerative disorder with few biomarkers even though it impacts a relatively large portion of the population and is predicted to affect significantly more individuals in the future. Neuroimaging has been used in concert with genetic information to improve our understanding in relation to how AD arises and how it can be potentially diagnosed. Additionally, evidence suggests synonymous variants can have a functional impact on gene regulatory mechanisms, including those related to AD. Some synonymous codons are preferred over others leading to a codon bias. The bias can arise with respect to codons that are more or less frequently used in the genome. A bias can also result from optimal and non-optimal codons, which have stronger and weaker codon anti-codon interactions, respectively. Although association tests have been utilized before to identify genes associated with AD, it remains unclear how codon bias plays a role and if it can improve rare variant analysis. In this work, rare variants from whole-genome sequencing from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort were binned into genes using BioBin. An association analysis of the genes with AD-related neuroimaging biomarker was performed using SKAT-O. While using all synonymous variants we did not identify any genome-wide significant associations, using only synonymous variants that affected codon frequency we identified several genes as significantly associated with the imaging phenotype. Additionally, significant associations were found using only rare variants that contains an optimal codon in among minor alleles and a non-optimal codon in the major allele. These results suggest that codon bias may play a role in AD and that it can be used to improve detection power in rare variant association analysis.",
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