Abstract LB-23: Meta-analysis of genome-wide association studies identifies multiple loci associated with chronic lymphocytic leukemia.

Author(s):  
Sonja I. Berndt ◽  
Christine F. Skibola ◽  
Vijai Joseph ◽  
Nicola J. Camp ◽  
Alexandra Nieters ◽  
...  
Blood ◽  
2012 ◽  
Vol 120 (4) ◽  
pp. 843-846 ◽  
Author(s):  
Susan L. Slager ◽  
Christine F. Skibola ◽  
Maria Chiara Di Bernardo ◽  
Lucia Conde ◽  
Peter Broderick ◽  
...  

Abstract We performed a meta-analysis of 3 genome-wide association studies to identify additional common variants influencing chronic lymphocytic leukemia (CLL) risk. The discovery phase was composed of genome-wide association study data from 1121 cases and 3745 controls. Replication analysis was performed in 861 cases and 2033 controls. We identified a novel CLL risk locus at 6p21.33 (rs210142; intronic to the BAK1 gene, BCL2 antagonist killer 1; P = 9.47 × 10−16). A strong relationship between risk genotype and reduced BAK1 expression was shown in lymphoblastoid cell lines. This finding provides additional support for polygenic inheritance to CLL and provides further insight into the biologic basis of disease development.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2875-2875
Author(s):  
Bethany Tesar ◽  
Lillian Werner ◽  
Megan Hanna ◽  
Ma Reina Improgo ◽  
Nathalie Pochet ◽  
...  

Abstract Abstract 2875 Genome wide association studies (GWAS) in chronic lymphocytic leukemia (CLL) have identified thirteen single nucleotide polymorphisms (SNPs) that are associated with the risk of developing CLL but do not affect the coding regions of genes. The functional targets of these SNPs remain largely unknown although they are thought to potentially serve as regulatory elements for nearby genes. We have previously published the results of a high resolution integrated genomic analysis of 161 CLLs with matched normal DNAs using Affymetrix 6.0 SNP arrays and Affymetrix U133 Plus 2.0 arrays run on the CLL lymphocytes. In this analysis, we sought to exploit this dataset to investigate whether SNP genotype at loci implicated in CLL risk by GWAS was associated with altered expression of genes in the CLL lymphocyte expression arrays. We therefore investigated 19 SNPs previously described in GWAS studies, either the SNP itself if present on the Affymetrix 6.0 SNP array, or one or more proxy SNPs for those not present on the array, chosen based on their high linkage disequilibrium (r2 > 0.7, usually > 0.9) with the GWAS SNP. Regions studied included 2q13 (1 SNP), 2q37.1 (1 SNP), 2q37.3 (1 SNP), 6p21.3 (1 SNP), 6p25.3 (2 SNPs), 8q24.2 (6 proxy SNPs), 11q24.1 (1 SNP), 15q21.3 (1 SNP), 15q23 (1 proxy SNP), 15q25.2 (1 SNP), 18q21.1 (1 proxy SNP), and 19q13.32 (2 proxy SNPs). We hypothesized that the genes most likely to be regulated by these loci would be located nearby, and therefore explored associations between SNP genotypes and the expression of genes located within 2 Mb of the relevant SNP using the Kruskal-Wallis test. The number of genes evaluated ranged from 11–22 depending on the locus. The analysis was performed independently for SNP genotypes derived from the tumor / lymphocyte samples (n=143) and from the normal / saliva samples (n=70–80). Discordant genotypes between tumor and normal samples were manually reviewed for reconciliation or excluded in the case of poor quality, indeterminate genotype or altered genomic copy number at the locus. Using the SNP genotypes from the tumor samples, we identified 13 genes with expression significantly associated with a risk SNP (using p value < 0.05). Using the SNP genotypes from the normal samples, we identified 15 genes using the same criteria. In both the tumor and normal analyses, eight SNPs were associated with a total of seven genes. The most significant associations were found between the risk allele of rs674313 on 6p21 and higher expression of HLA-DQA1 (p<0.0001), and between the risk allele of rs4802322 on 19q13 and higher expression of FKRP (p<0.0001), although the latter did not show a wide range of gene expression. IRF4 expression on 6p25 was also significantly associated with rs872071 (p=0.01), as we and others have previously shown. MYC expression was associated with two of the proxy SNPs at 8q24, rs17762878 (p=0.03) and rs7823764 (p<0.04). Additional significant associations were seen for rs4777184 on chromosome 15 with TLE3 expression (p<0.02), for rs783540 on chromosome 15 with CPEB1 expression (p<0.01), and for rs305088 on chromosome 16 with COX4NB expression (p<0.04). The regulation of IRF4 and MYC by GWAS SNP alleles is unsurprising; current work is focused on validating the associations with the other genes in an extension cohort and exploring their possible functions in CLL. Disclosures: No relevant conflicts of interest to declare.


Circulation ◽  
2011 ◽  
Vol 123 (7) ◽  
pp. 731-738 ◽  
Author(s):  
Abbas Dehghan ◽  
Josée Dupuis ◽  
Maja Barbalic ◽  
Joshua C. Bis ◽  
Gudny Eiriksdottir ◽  
...  

2021 ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Masatoshi Matsunami ◽  
Momoko Horikoshi ◽  
Minoru Iwata ◽  
...  

Abstract Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases, and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (p &lt; 1.0 × 10−4) in an independent case–control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stage-1 and -2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, p = 1.62 × 10−9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11–1.23, and rs140508424 within PALM2 on chromosome 9, p = 4.19 × 10−8, OR = 1.61, 95% CI 1.36–1.91. However, the association of these two loci were not replicated in Korean, European, or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (p = 2.17 × 10−6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.


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