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Cited by 114Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and AnimalsDiabetes and associated disorders

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Statistical independence of the colocalized association signals for type 1 diabetes and RPS26 gene expression on chromosome 12q13

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Plagnol, Vincent, Smyth, Deborah J., Todd, John A., Clayton, David G.·2009·Biostatistics
DOI 10.1093/biostatistics/kxn039PMC PMC2648905
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Abstract

Following the recent success of genome-wide association studies in uncovering disease-associated genetic variants, the next challenge is to understand how these variants affect downstream pathways. The most proximal trait to a disease-associated variant, most commonly a single nucleotide polymorphism (SNP), is differential gene expression due to the cis effect of SNP alleles on transcription, translation, and/or splicing gene expression quantitative trait loci (eQTL). Several genome-wide SNP-gene expression association studies have already provided convincing evidence of widespread association of eQTLs. As a consequence, some eQTL associations are found in the same genomic region as a disease variant, either as a coincidence or a causal relationship. Cis-regulation of RPS26 gene expression and a type 1 diabetes (T1D) susceptibility locus have been colocalized to the 12q13 genomic region. A recent study has also suggested RPS26 as the most likely susceptibility gene for T1D in this genomic region. However, it is still not clear whether this colocalization is the result of chance alone or if RPS26 expression is directly correlated with T1D susceptibility, and therefore, potentially causal. Here, we derive and apply a statistical test of this hypothesis. We conclude that RPS26 expression is unlikely to be the molecular trait responsible for T1D susceptibility at this locus, at least not in a direct, linear connection.

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Fig. 1. Correlation between RPS26 expression and rs1131017 genotypes. RPS26 expression was measured using the Affymetrix HG-U133 Plus 2.0 gene expression chip.
Fig. 1. Correlation between RPS26 expression and rs1131017 genotypes. RPS26 expression was measured using the Affymetrix HG-U133 Plus 2.0 gene expression chip.CC BY-NC · PubMed Central
Fig. 2. Comparison of estimated regression coefficients in the T1D case–control and the eQTL RPS26 expression studies, analyzing 1 SNP at a time. Assuming a sole causal variant for both traits, the estimated regression coefficients should be proportional between both studies.
Fig. 2. Comparison of estimated regression coefficients in the T1D case–control and the eQTL RPS26 expression studies, analyzing 1 SNP at a time. Assuming a sole causal variant for both traits, the estimated regression coefficients should be proportional between both studies.CC BY-NC · PubMed Central
Fig. 3. (A) Jointly estimated regression coefficients and confidence intervals for rs1131017 and rs705704 under the null hypothesis 0 of a sole common variant and under the alternative 1. Under the null hypothesis 0, estimated regression coefficients have to be located on a line passing through the origin. (B) Rescaled version of (A) highlighting the fact that when compared on the same unit scale (i.e. regression estimates located on the unit circle), the variance of the estimated coefficients is higher for the T1D study. Therefore, regression estimates under the null are driven by the RPS26 expression data.
Fig. 3. (A) Jointly estimated regression coefficients and confidence intervals for rs1131017 and rs705704 under the null hypothesis 0 of a sole common variant and under the alternative 1. Under the null hypothesis 0, estimated regression coefficients have to be located on a line passing through the origin. (B) Rescaled version of (A) highlighting the fact that when compared on the same unit scale (i.e. regression estimates located on the unit circle), the variance of the estimated coefficients is higher for the T1D study. Therefore, regression estimates under the null are driven by the RPS26 expression data.CC BY-NC · PubMed Central

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Metadata

Authors
Plagnol, V., Smyth, D. J., Todd, J. A., & Clayton, D. G.
Affiliations
University of Cambridge (GB)
Corresponding author
Plagnol, Vincent
ORCID
Venue
Biostatistics
Publisher
Oxford University Press (OUP)
Published
2008-11-27
Volume
10
Issue
2
Pages
327-334
ISSN
  • 1465-4644 (ISSN-L)
  • 1468-4357
DOI
10.1093/biostatistics/kxn039
PMC
PMC2648905
OpenAlex
W2160717726
Cited by
113
References
14
Citations by year
2026: 6 · 2025: 10 · 2024: 9 · 2023: 8 · 2022: 10 · 2021: 19 · 2020: 8 · 2019: 5 · 2018: 3 · 2016: 1 · 2015: 5 · 2014: 4 · 2013: 6 · 2012: 5
FWCI
2.66
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Biostatistics (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
  • Wellcome Trust (061858, 079895)
  • National Institute for Health and Care Research (NF-SI-0508-10275)
  • Cambridge Institute for Medical Research, University of Cambridge (079895)
  • NIHR Cambridge Biomedical Research Centre
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
Keywords
type 1 diabetes, RPS26, expression quantitative trait loci, colocalization, cis-regulation, chromosome 12q13, single nucleotide polymorphisms, causal inference
MeSH terms
Chromosome Mapping, Chromosomes, Human, Pair 12, Diabetes Mellitus, Type 1, Humans, Models, Genetic, Ribosomal Proteins, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study

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