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A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND)
OBJECTIVE: Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866106/ https://www.ncbi.nlm.nih.gov/pubmed/24358131 http://dx.doi.org/10.1371/journal.pone.0081888 |
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author | Thameem, Farook Igo, Robert P. Freedman, Barry I. Langefeld, Carl Hanson, Robert L. Schelling, Jeffrey R. Elston, Robert C. Duggirala, Ravindranath Nicholas, Susanne B. Goddard, Katrina A. B. Divers, Jasmin Guo, Xiuqing Ipp, Eli Kimmel, Paul L. Meoni, Lucy A. Shah, Vallabh O. Smith, Michael W. Winkler, Cheryl A. Zager, Philip G. Knowler, William C. Nelson, Robert G. Pahl, Madeline V. Parekh, Rulan S. Kao, W. H. Linda Rasooly, Rebekah S. Adler, Sharon G. Abboud, Hanna E. Iyengar, Sudha K. Sedor, John R. |
author_facet | Thameem, Farook Igo, Robert P. Freedman, Barry I. Langefeld, Carl Hanson, Robert L. Schelling, Jeffrey R. Elston, Robert C. Duggirala, Ravindranath Nicholas, Susanne B. Goddard, Katrina A. B. Divers, Jasmin Guo, Xiuqing Ipp, Eli Kimmel, Paul L. Meoni, Lucy A. Shah, Vallabh O. Smith, Michael W. Winkler, Cheryl A. Zager, Philip G. Knowler, William C. Nelson, Robert G. Pahl, Madeline V. Parekh, Rulan S. Kao, W. H. Linda Rasooly, Rebekah S. Adler, Sharon G. Abboud, Hanna E. Iyengar, Sudha K. Sedor, John R. |
author_sort | Thameem, Farook |
collection | PubMed |
description | OBJECTIVE: Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR. METHODS: Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula. RESULTS: The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10(−5)) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10(−4)) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10(−4)) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome. CONCLUSION: The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN. |
format | Online Article Text |
id | pubmed-3866106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38661062013-12-19 A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) Thameem, Farook Igo, Robert P. Freedman, Barry I. Langefeld, Carl Hanson, Robert L. Schelling, Jeffrey R. Elston, Robert C. Duggirala, Ravindranath Nicholas, Susanne B. Goddard, Katrina A. B. Divers, Jasmin Guo, Xiuqing Ipp, Eli Kimmel, Paul L. Meoni, Lucy A. Shah, Vallabh O. Smith, Michael W. Winkler, Cheryl A. Zager, Philip G. Knowler, William C. Nelson, Robert G. Pahl, Madeline V. Parekh, Rulan S. Kao, W. H. Linda Rasooly, Rebekah S. Adler, Sharon G. Abboud, Hanna E. Iyengar, Sudha K. Sedor, John R. PLoS One Research Article OBJECTIVE: Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR. METHODS: Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula. RESULTS: The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10(−5)) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10(−4)) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10(−4)) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome. CONCLUSION: The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN. Public Library of Science 2013-12-17 /pmc/articles/PMC3866106/ /pubmed/24358131 http://dx.doi.org/10.1371/journal.pone.0081888 Text en © 2013 Thameem et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Thameem, Farook Igo, Robert P. Freedman, Barry I. Langefeld, Carl Hanson, Robert L. Schelling, Jeffrey R. Elston, Robert C. Duggirala, Ravindranath Nicholas, Susanne B. Goddard, Katrina A. B. Divers, Jasmin Guo, Xiuqing Ipp, Eli Kimmel, Paul L. Meoni, Lucy A. Shah, Vallabh O. Smith, Michael W. Winkler, Cheryl A. Zager, Philip G. Knowler, William C. Nelson, Robert G. Pahl, Madeline V. Parekh, Rulan S. Kao, W. H. Linda Rasooly, Rebekah S. Adler, Sharon G. Abboud, Hanna E. Iyengar, Sudha K. Sedor, John R. A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title | A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title_full | A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title_fullStr | A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title_full_unstemmed | A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title_short | A Genome-Wide Search for Linkage of Estimated Glomerular Filtration Rate (eGFR) in the Family Investigation of Nephropathy and Diabetes (FIND) |
title_sort | genome-wide search for linkage of estimated glomerular filtration rate (egfr) in the family investigation of nephropathy and diabetes (find) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866106/ https://www.ncbi.nlm.nih.gov/pubmed/24358131 http://dx.doi.org/10.1371/journal.pone.0081888 |
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