Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma

Zhang, Mingfeng; Liang, Liming; Morar, Nilesh; Dixon, Anna; Lathrop, G.M.; Ding, Jun; Moffatt, Miriam F.; Cookson, William; Kraft, Peter; Qureshi, Abrar A.; Han, Jiali

doi:10.1007/s00439-011-1107-5

Cited by 30 publications

(23 citation statements)

References 53 publications

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“…This is more than six times larger than our previous eQTL database , which has been used to identify association with expression for SNPs associated with asthma ), Crohn's disease (Libioulle et al 2007), and type 1 diabetes (Plagnol et al 2009). Even before publication, our two newly developed eQTL databases have been used to interpret findings from large-scale GWAS, including human height (Lango Allen et al 2010), body mass index , waisthip ratio (Heid et al 2010), osteoporosis-related traits (Hsu et al 2010), Graves' disease (Chu et al 2011), pancreatic cancer (Wu et al 2012), and pathways associated with basal cell skin carcinoma (Zhang et al 2012). Our systematic investigation of the GWAS database presented in Supplemental Table 3 suggests that eQTL analyses may add to the understanding of many other loci mapped for complex genetic diseases.…”

Section: Discussionmentioning

confidence: 99%

A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines

et al. 2013

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Gene expression levels can be an important link DNA between variation and phenotypic manifestations. Our previous map of global gene expression, based on ∼400K single nucleotide polymorphisms (SNPs) and 50K transcripts in 400 sib pairs from the MRCA family panel, has been widely used to interpret the results of genome-wide association studies (GWASs). Here, we more than double the size of our initial data set with expression data on 550 additional individuals from the MRCE family panel using the Illumina whole-genome expression array. We have used new statistical methods for dimension reduction to account for nongenetic effects in estimates of expression levels, and we have also included SNPs imputed from the 1000 Genomes Project. Our methods reduced false-discovery rates and increased the number of expression quantitative trait loci (eQTLs) mapped either locally or at a distance (i.e., in cis or trans) from 1534 in the MRCA data set to 4452 (with <5% FDR). Imputation of 1000 Genomes SNPs further increased the number of eQTLs to 7302. Using the same methods and imputed SNPs in the newly acquired MRCE data set, we identified eQTLs for 9000 genes. The combined results identify strong local and distant effects for transcripts from 14,177 genes. Our eQTL database based on these results is freely available to help define the function of disease-associated variants.

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Section: Discussionmentioning

confidence: 99%

A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines

et al. 2013

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“…eQTL results can be used to provide functional interpretation for findings from GWAS (Moffatt et al, 2007; Heid et al, 2010; Hsu et al, 2010; Lango Allen et al, 2010; Speliotes et al, 2010; Chu et al, 2011; Wu et al, 2012) and prioritize genes in an association region for carrying out functional experiments using animal models (Teslovich et al, 2010). Focusing on eQTLs may also be useful to identify genetic pathways associated with the risk of complex diseases and traits, such as basal cell carcinoma in a skin cancer GWAS (Zhang et al, 2012) and type 2 diabetes (Zhong et al, 2010). Other results show that many cis eQTLs are shared across tissues (Ding et al, 2010) and that a comprehensive eQTL catalog in one tissue might be used to increase the power of capturing relevant transcripts for other diseases (including those that are only weakly or incidentally expressed in tissues where eQTL information was collected).…”

Section: Introductionmentioning

confidence: 99%

Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

Li¹,

Kabesch²,

Bouzigon³

et al. 2013

Front. Genet.

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Increasing evidence suggests that single nucleotide polymorphisms (SNPs) associated with complex traits are more likely to be expression quantitative trait loci (eQTLs). Incorporating eQTL information hence has potential to increase power of genome-wide association studies (GWAS). In this paper, we propose using eQTL weights as prior information in SNP based association tests to improve test power while maintaining control of the family-wise error rate (FWER) or the false discovery rate (FDR). We apply the proposed methods to the analysis of a GWAS for childhood asthma consisting of 1296 unrelated individuals with German ancestry. The results confirm that eQTLs are enriched for previously reported asthma SNPs. We also find that some SNPs are insignificant using procedures without eQTL weighting, but become significant using eQTL-weighted Bonferroni or Benjamini–Hochberg procedures, while controlling the same FWER or FDR level. Some of these SNPs have been reported by independent studies in recent literature. The results suggest that the eQTL-weighted procedures provide a promising approach for improving power of GWAS. We also report the results of our methods applied to the large-scale European GABRIEL consortium data.

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“…TFs from PAX family are associated with tissue specific gene expression and linked to development of specific tissues, including kidney and optic nerves (PAX-2; Lindoso et al, 2009); ear, eye, and facial development (PAX-3; Zhang et al, 2012); pancreatic islet beta cells (PAX-4; Collombat et al, 2009); b-cell differentiation, as well as neural and spermatogenesis development (PAX-5; Decker et al, 2009) and eyes and sensory organs, certain neural, and epidermal tissues development (PAX-6; Guo et al, 2010; Rowan et al, 2010). Forkhead box (FOX) family of TFs is implicated in processes of embryonic development, cell growth, proliferation, and cell differentiation (Hannenhalli and Kaestner, 2009).…”

Section: Discussionmentioning

confidence: 99%

Mutations and Binding Sites of Human Transcription Factors

Kamanu¹,

Medvedeva²,

Schaefer³

et al. 2012

Front. Gene.

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Mutations in any genome may lead to phenotype characteristics that determine ability of an individual to cope with adaptation to environmental challenges. In studies of human biology, among the most interesting ones are phenotype characteristics that determine responses to drug treatments, response to infections, or predisposition to specific inherited diseases. Most of the research in this field has been focused on the studies of mutation effects on the final gene products, peptides, and their alterations. Considerably less attention was given to the mutations that may affect regulatory mechanism(s) of gene expression, although these may also affect the phenotype characteristics. In this study we make a pilot analysis of mutations observed in the regulatory regions of 24,667 human RefSeq genes. Our study reveals that out of eight studied mutation types, “insertions” are the only one that in a statistically significant manner alters predicted transcription factor binding sites (TFBSs). We also find that 25 families of TFBSs have been altered by mutations in a statistically significant manner in the promoter regions we considered. Moreover, we find that the related transcription factors are, for example, prominent in processes related to intracellular signaling; cell fate; morphogenesis of organs and epithelium; development of urogenital system, epithelium, and tube; neuron fate commitment. Our study highlights the significance of studying mutations within the genes regulatory regions and opens way for further detailed investigations on this topic, particularly on the downstream affected pathways.

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Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma

Cited by 30 publications

References 53 publications

A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines

A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines

Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

Mutations and Binding Sites of Human Transcription Factors

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