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Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy.

ABSTRACT: Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina's HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All individuals genotyped in this study were Caucasians with (cases) and without (controls) diabetic nephropathy. About 449 individuals with type 2 diabetes (203 cases, 246 controls) were genotyped in the initial study. 1,467 individuals with type 1 diabetes (718 cases, 749 controls) were genotyped in the follow up study. 11,152 SNPs were successfully analysed and ranked for association with diabetic nephropathy based on significance (P) values. The top ranked 32 SNPs were subsequently genotyped using MassARRAY iPLEX(™) and TaqMan technologies to investigate association of these polymorphisms with nephropathy in individuals with type 1 diabetes. The top ranked nsSNP, rs1543547 (P = 10(-5)), is located in RAET1L, a major histocompatibility class I-related gene at 6q25.1. Of particular interest, multiple nsSNPs within the top ranked (0.2%) SNPs are within several plausible candidate genes for nephropathy on 3q21.3 and 6p21.3.

SUBMITTER: McKnight AJ

PROVIDER: S-EPMC2882642 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy.

McKnight Amy Jayne AJ Currie Diane D Patterson Chris C CC Maxwell Alexander P AP Fogarty Damian G DG

The HUGO journal 20091201 1-4

Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina's HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All i ...[more]

PMID: 21119753

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Project description:Aims/hypothesisDiabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.MethodsWe performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets.ResultsThe meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10-9; although not withstanding correction for multiple testing, p>9.3×10-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p<2.7×10-6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10-6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10-11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10-8] and negatively with tubulointerstitial fibrosis [p=2.0×10-9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10-16], and SNX30 expression correlated positively with eGFR [p=5.8×10-14] and negatively with fibrosis [p<2.0×10-16]).Conclusions/interpretationAltogether, the results point to novel genes contributing to the pathogenesis of DKD.Data availabilityThe GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).

Project description:We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater "load" of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

Project description:Osteoporosis is a serious public health issue, which is mostly characterized by low bone mineral density (BMD). To search for additional genetic susceptibility loci underlying BMD variation, an effective strategy is to focus on testing of specific variants with high potential of functional effects. Single nucleotide polymorphisms (SNPs) that introduce or disrupt CpG dinucleotides (CpG-SNPs) may alter DNA methylation levels and thus represent strong candidate functional variants. Here, we performed a targeted GWAS for 63,627 potential functional CpG-SNPs that may affect DNA methylation in bone-related cells, in five independent cohorts (n = 5905). By meta-analysis, 9 CpG-SNPs achieved a genome-wide significance level (p < 7.86 × 10-7) for association with lumbar spine BMD and additional 15 CpG-SNPs showed suggestive significant (p < 5.00 × 10-5) association, of which 2 novel SNPs rs7231498 (NFATC1) and rs7455028 (ESR1) also reached a genome-wide significance level in the joint analysis. Several identified CpG-SNPs were mapped to genes that have not been reported for association with BMD in previous GWAS, such as NEK3 and NFATC1 genes, highlighting the enhanced power of targeted association analysis for identification of novel associations that were missed by traditional GWAS. Interestingly, several genomic regions, such as NEK3 and LRP5 regions, contained multiple significant/suggestive CpG-SNPs for lumbar spine BMD, suggesting that multiple neighboring CpG-SNPs may synergistically mediate the DNA methylation level and gene expression pattern of target genes. Furthermore, functional annotation analyses suggested a strong regulatory potential of the identified BMD-associated CpG-SNPs and a significant enrichment in biological processes associated with protein localization and protein signal transduction. Our results provided novel insights into the genetic basis of BMD variation and highlighted the close connections between genetic and epigenetic mechanisms of complex disease.

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Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy.

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Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy.

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