Abstract
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P 5 5.6 3 10-9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 3 10-4-2.2× 10-7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
Original language | English (US) |
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Article number | dds369 |
Pages (from-to) | 5329-5343 |
Number of pages | 15 |
Journal | Human Molecular Genetics |
Volume | 21 |
Issue number | 24 |
DOIs | |
State | Published - Dec 2012 |
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ASJC Scopus subject areas
- Genetics
- Genetics(clinical)
- Molecular Biology
Cite this
Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function. / Chasman, Daniel I.; Fuchsberger, Christian; Pattaro, Cristian; Teumer, Alexander; Böger, Carsten A.; Endlich, Karlhans; Olden, Matthias; Chen, Ming Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; O'Seaghdha, Conall M.; Glazer, Nicole; Isaacs, Aaron; Liu, Ching Ti; Smith, Albert V.; O'Connell, Jeffrey R.; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Johnson, Andrew D.; Gierman, Hinco J.; Feitosa, Mary F.; Hwang, Shih Jen; Atkinson, Elizabeth J.; Lohman, Kurt; Cornelis, Marilyn C.; Johansson, Åsa; Tönjes, Anke; Dehghan, Abbas; Lambert, Jean Charles; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Coassin, Stefan; Pistis, Giorgio; Harris, Tamara B.; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Boerwinkle, Eric; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; Hu, Frank; Demirkan, Ayse; Oostra, Ben A.; De Andrade, Mariza; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Meisinger, Christa; Gieger, Christian; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G.; Rivadeneira, Fernando; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K.; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R.; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; Siscovick, David S.; van Duijn, Cornelia M.; Borecki, Ingrid B.; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C.; Rudan, Igor; Gyllensten, Ulf; Wilson, James F.; Franke, Andre; Pramstaller, Peter P.; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M.; Parsa, Afshin; Bochud, Murielle; Heid, Iris M.; Kao, W. H Linda; Fox, Caroline S.; Köttgen, Anna.
In: Human Molecular Genetics, Vol. 21, No. 24, dds369, 12.2012, p. 5329-5343.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function
AU - Chasman, Daniel I.
AU - Fuchsberger, Christian
AU - Pattaro, Cristian
AU - Teumer, Alexander
AU - Böger, Carsten A.
AU - Endlich, Karlhans
AU - Olden, Matthias
AU - Chen, Ming Huei
AU - Tin, Adrienne
AU - Taliun, Daniel
AU - Li, Man
AU - Gao, Xiaoyi
AU - Gorski, Mathias
AU - Yang, Qiong
AU - Hundertmark, Claudia
AU - Foster, Meredith C.
AU - O'Seaghdha, Conall M.
AU - Glazer, Nicole
AU - Isaacs, Aaron
AU - Liu, Ching Ti
AU - Smith, Albert V.
AU - O'Connell, Jeffrey R.
AU - Struchalin, Maksim
AU - Tanaka, Toshiko
AU - Li, Guo
AU - Johnson, Andrew D.
AU - Gierman, Hinco J.
AU - Feitosa, Mary F.
AU - Hwang, Shih Jen
AU - Atkinson, Elizabeth J.
AU - Lohman, Kurt
AU - Cornelis, Marilyn C.
AU - Johansson, Åsa
AU - Tönjes, Anke
AU - Dehghan, Abbas
AU - Lambert, Jean Charles
AU - Holliday, Elizabeth G.
AU - Sorice, Rossella
AU - Kutalik, Zoltan
AU - Lehtimäki, Terho
AU - Esko, Tõnu
AU - Deshmukh, Harshal
AU - Ulivi, Sheila
AU - Chu, Audrey Y.
AU - Murgia, Federico
AU - Trompet, Stella
AU - Imboden, Medea
AU - Coassin, Stefan
AU - Pistis, Giorgio
AU - Harris, Tamara B.
AU - Launer, Lenore J.
AU - Aspelund, Thor
AU - Eiriksdottir, Gudny
AU - Mitchell, Braxton D.
AU - Boerwinkle, Eric
AU - Schmidt, Helena
AU - Cavalieri, Margherita
AU - Rao, Madhumathi
AU - Hu, Frank
AU - Demirkan, Ayse
AU - Oostra, Ben A.
AU - De Andrade, Mariza
AU - Turner, Stephen T
AU - Ding, Jingzhong
AU - Andrews, Jeanette S.
AU - Freedman, Barry I.
AU - Giulianini, Franco
AU - Koenig, Wolfgang
AU - Illig, Thomas
AU - Meisinger, Christa
AU - Gieger, Christian
AU - Zgaga, Lina
AU - Zemunik, Tatijana
AU - Boban, Mladen
AU - Minelli, Cosetta
AU - Wheeler, Heather E.
AU - Igl, Wilmar
AU - Zaboli, Ghazal
AU - Wild, Sarah H.
AU - Wright, Alan F.
AU - Campbell, Harry
AU - Ellinghaus, David
AU - Nöthlings, Ute
AU - Jacobs, Gunnar
AU - Biffar, Reiner
AU - Ernst, Florian
AU - Homuth, Georg
AU - Kroemer, Heyo K.
AU - Nauck, Matthias
AU - Stracke, Sylvia
AU - Völker, Uwe
AU - Völzke, Henry
AU - Kovacs, Peter
AU - Stumvoll, Michael
AU - Mägi, Reedik
AU - Hofman, Albert
AU - Uitterlinden, Andre G.
AU - Rivadeneira, Fernando
AU - Aulchenko, Yurii S.
AU - Polasek, Ozren
AU - Hastie, Nick
AU - Vitart, Veronique
AU - Helmer, Catherine
AU - Wang, Jie Jin
AU - Stengel, Bénédicte
AU - Ruggiero, Daniela
AU - Bergmann, Sven
AU - Kähönen, Mika
AU - Viikari, Jorma
AU - Nikopensius, Tiit
AU - Province, Michael
AU - Ketkar, Shamika
AU - Colhoun, Helen
AU - Doney, Alex
AU - Robino, Antonietta
AU - Krämer, Bernhard K.
AU - Portas, Laura
AU - Ford, Ian
AU - Buckley, Brendan M.
AU - Adam, Martin
AU - Thun, Gian Andri
AU - Paulweber, Bernhard
AU - Haun, Margot
AU - Sala, Cinzia
AU - Mitchell, Paul
AU - Ciullo, Marina
AU - Kim, Stuart K.
AU - Vollenweider, Peter
AU - Raitakari, Olli
AU - Metspalu, Andres
AU - Palmer, Colin
AU - Gasparini, Paolo
AU - Pirastu, Mario
AU - Jukema, J. Wouter
AU - Probst-Hensch, Nicole M.
AU - Kronenberg, Florian
AU - Toniolo, Daniela
AU - Gudnason, Vilmundur
AU - Shuldiner, Alan R.
AU - Coresh, Josef
AU - Schmidt, Reinhold
AU - Ferrucci, Luigi
AU - Siscovick, David S.
AU - van Duijn, Cornelia M.
AU - Borecki, Ingrid B.
AU - Kardia, Sharon L R
AU - Liu, Yongmei
AU - Curhan, Gary C.
AU - Rudan, Igor
AU - Gyllensten, Ulf
AU - Wilson, James F.
AU - Franke, Andre
AU - Pramstaller, Peter P.
AU - Rettig, Rainer
AU - Prokopenko, Inga
AU - Witteman, Jacqueline
AU - Hayward, Caroline
AU - Ridker, Paul M.
AU - Parsa, Afshin
AU - Bochud, Murielle
AU - Heid, Iris M.
AU - Kao, W. H Linda
AU - Fox, Caroline S.
AU - Köttgen, Anna
PY - 2012/12
Y1 - 2012/12
N2 - In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P 5 5.6 3 10-9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 3 10-4-2.2× 10-7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
AB - In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P 5 5.6 3 10-9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 3 10-4-2.2× 10-7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
UR - http://www.scopus.com/inward/record.url?scp=84870691564&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870691564&partnerID=8YFLogxK
U2 - 10.1093/hmg/dds369
DO - 10.1093/hmg/dds369
M3 - Article
C2 - 22962313
AN - SCOPUS:84870691564
VL - 21
SP - 5329
EP - 5343
JO - Human Molecular Genetics
JF - Human Molecular Genetics
SN - 0964-6906
IS - 24
M1 - dds369
ER -