<i>PTCH1</i>
 gene haplotype association with basal cell carcinoma after transplantation

Begnini, Angela; Tessari, Gianpaolo; Turco, Alberto; Malerba, Giovanni; Naldi, Luigi; Gotti, Eliana; Boschiero, Luigino; Forni, Alberto; Rugiu, Carlo; Piaserico, Stefano; Fortina, Anna Belloni; Brunello, Anna; Cascone, Carmela; Girolomoni, Giampiero; Gomez-Lira, Macarena

doi:10.1111/j.1365-2133.2010.09776.x

Cited by 18 publications

(15 citation statements)

References 32 publications

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“…Numerous studies have reported cases when haplotype-based analysis resulted in detection of an association, while SNP-based analysis either did not yield any significant results or yielded much higher p-values [16-19]. A haplotype-based test may be more powerful than a genotype-based test if haplotypes tag a true causal variant better (although the imputation of untyped SNPs using publicly available reference panels may also be a powerful strategy), or if a SNP-SNP interaction is present within a region.…”

Section: Introductionmentioning

confidence: 99%

Combined genotype and haplotype tests for region-based association studies

et al. 2013

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BackgroundAlthough single-SNP analysis has proven to be useful in identifying many disease-associated loci, region-based analysis has several advantages. Empirically, it has been shown that region-based genotype and haplotype approaches may possess much higher power than single-SNP statistical tests. Both high quality haplotypes and genotypes may be available for analysis given the development of next generation sequencing technologies and haplotype assembly algorithms.ResultsAs generally it is unknown whether genotypes or haplotypes are more relevant for identifying an association, we propose to use both of them with the purpose of preserving high power under both genotype and haplotype disease scenarios. We suggest two approaches for a combined association test and investigate the performance of these two approaches based on a theoretical model, population genetics simulations and analysis of a real data set.ConclusionsBased on a theoretical model, population genetics simulations and analysis of a central corneal thickness (CCT) Genome Wide Association Study (GWAS) data set we have shown that combined genotype and haplotype approach has a high potential utility for applications in association studies.

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Section: Introductionmentioning

confidence: 99%

Combined genotype and haplotype tests for region-based association studies

et al. 2013

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“…Begnini et al, analysed the prevalence of several PTCH polymorphisms, including CGG repeats in the 5′UTR, in immunosuppressed Italian patients who had developed BCC following organ transplantation. They observed the CGG 8 allele in 46% of patients and the CGG 7 allele in 41%; however, this higher frequency was not statistically significant (12). It remains to be determined whether the prevalence of these polymorphisms is more strongly correlated with BCC susceptibility in non-mediterranean, more fair-skinned populations and outside the context of immunosuppression.…”

Section: Resultsmentioning

confidence: 94%

A non‐coding mutation in the 5′ untranslated region of patched homologue 1 predisposes to basal cell carcinoma

Tietze

Pfob

Eggert

et al. 2013

Experimental Dermatology

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Mutations in the human homolog of the Drosophila patched gene, patched homologue 1 (PTCH-1), are responsible for most hereditary and sporadic basal cell carcinomas. Here, we present a father and daughter with a high propensity for the development of basal cell carcinoma who were heterozygous for a non-coding germline mutation in the 5′ untranslated region (UTR) of PTCH-1 (insertion of a surplus CGG triplet at the site of a seven times CGG repeat). We analysed the impact of this mutation on PTCH translation using a luciferase-based reporter vector. Insertion of an eighth CGG in the 5′ UTR repressed protein translation dramatically when compared to the wild-type sequence. Our results suggest that this non-coding variant in the 5′ UTR represents a mutation predisposing to basal cell carcinoma.

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“…rs357564 is a missense variant within PTCH1 and rs1529889 is an intronic variant within ADAMST17 . rs357564 is predicted to be ‘functional’ by the prediction tool FATHMM (Shihab et al , 2015) and was reported to be associated with oral clefts, basal cell carcinoma and ameloblastoma (Begnini et al , 2010; Carter et al , 2010; Farias et al , 2012).…”

Section: Discussionmentioning

confidence: 99%

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics

et al. 2016

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MotivationFine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients (r2) of the variants. However, haplotypes rather than pairwise r2, are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel.ResultsSimulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N<2000) while other methods become suboptimal. Moreover, HAPRAP’s performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization).Availability and ImplementationThe HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/

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PTCH1 gene haplotype association with basal cell carcinoma after transplantation

Cited by 18 publications

References 32 publications

Combined genotype and haplotype tests for region-based association studies

Combined genotype and haplotype tests for region-based association studies

A non‐coding mutation in the 5′ untranslated region of patched homologue 1 predisposes to basal cell carcinoma

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics

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