Locus and gene-based GWAS meta-analysis identifies new diabetic nephropathy genes
Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due...
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| Published in | Immunogenetics (New York) Vol. 70; no. 6; pp. 347 - 353 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2018
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0093-7711 1432-1211 1432-1211 |
| DOI | 10.1007/s00251-017-1044-0 |
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| Abstract | Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES.
CARS
and
FRMD3
were confirmed as DN genes, and five known diabetes-associated genes, viz.
NLRP3
,
INPPL1
,
PIK3C2G
,
NRXN3
, and
TBC1D4
, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz.
NTN1
,
EBF2
, and
DNAH11
. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes. |
|---|---|
| AbstractList | Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes. Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes.Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes. Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3 , INPPL1 , PIK3C2G , NRXN3 , and TBC1D4 , not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1 , EBF2 , and DNAH11 . Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes. |
| Author | Saeed, Mohammad |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29147756$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1111_jdi_13930 crossref_primary_10_3390_biom9030104 crossref_primary_10_2147_JIR_S482047 crossref_primary_10_2147_DMSO_S452227 crossref_primary_10_1007_s00251_018_1068_0 crossref_primary_10_1016_j_ejmg_2019_103828 crossref_primary_10_3389_fpain_2025_1501932 crossref_primary_10_1128_spectrum_00324_22 |
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| SubjectTerms | Allergology Biomedical and Life Sciences Biomedicine Cell Biology Clustering Datasets Diabetes Diabetes mellitus Diabetic nephropathy Gene Function Genes Genome-wide association studies Genomes Human Genetics Immunology Inositol polyphosphate 5-phosphatase Loci Meta-analysis Nephropathy Netrin-1 Original Article Single-nucleotide polymorphism |
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| Title | Locus and gene-based GWAS meta-analysis identifies new diabetic nephropathy genes |
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