Overlap between common genetic polymorphisms underpinning kidney traits and cardiovascular disease phenotypes: The CKDGen consortium

Matthias Olden, Alexander Teumer, Murielle Bochud, Cristian Pattaro, Anna Köttgen, Stephen T Turner, Rainer Rettig, Ming Huei Chen, Abbas Dehghan, Francois Bastardot, Reinhold Schmidt, Peter Vollenweider, Heribert Schunkert, Muredach P. Reilly, Myriam Fornage, Lenore J. Launer, Germaine C. Verwoert, Gary F. Mitchell, Joshua C. Bis, Christopher J. O'DonnellChing Yu Cheng, Xueling Sim, David S. Siscovick, Josef Coresh, W. H Linda Kao, Caroline S. Fox, Conall M. O'Seaghdha

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Background: Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits. Study Design: We conducted 2 targeted analyses. First, we examined whether known single-nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5×10-4 (0.05/325 tests). Setting & Participants: Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395), and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium. Predictor: We used 19 kidney SNPs and 64 vascular SNPs. Outcomes & Measurements: Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber, and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria. Results: In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were nonsignificant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (P = 9.3 ×10-10) and diastolic (P = 1.6 ×10-14) blood pressure and coronary artery disease (P = 2.2 ×10-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were nonsignificant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (P = 1.06 ×10 -07 and P = 7.05 ×10-08). Limitations: The combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations. Conclusions: Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.

Original languageEnglish (US)
Pages (from-to)889-898
Number of pages10
JournalAmerican Journal of Kidney Diseases
Volume61
Issue number6
DOIs
StatePublished - Jun 2013

Fingerprint

Kidney Diseases
Genetic Polymorphisms
Blood Vessels
Cardiovascular Diseases
Single Nucleotide Polymorphism
Phenotype
Kidney
Coronary Artery Disease
Blood Pressure
Carotid Intima-Media Thickness
Pulse Wave Analysis
Albuminuria
Glomerular Filtration Rate
Chronic Renal Insufficiency
Brain
Population

Keywords

  • Cardiovascular disease
  • chronic kidney disease
  • genomics
  • single-nucleotide polymorphism (SNP)

ASJC Scopus subject areas

  • Nephrology

Cite this

Overlap between common genetic polymorphisms underpinning kidney traits and cardiovascular disease phenotypes : The CKDGen consortium. / Olden, Matthias; Teumer, Alexander; Bochud, Murielle; Pattaro, Cristian; Köttgen, Anna; Turner, Stephen T; Rettig, Rainer; Chen, Ming Huei; Dehghan, Abbas; Bastardot, Francois; Schmidt, Reinhold; Vollenweider, Peter; Schunkert, Heribert; Reilly, Muredach P.; Fornage, Myriam; Launer, Lenore J.; Verwoert, Germaine C.; Mitchell, Gary F.; Bis, Joshua C.; O'Donnell, Christopher J.; Cheng, Ching Yu; Sim, Xueling; Siscovick, David S.; Coresh, Josef; Kao, W. H Linda; Fox, Caroline S.; O'Seaghdha, Conall M.

In: American Journal of Kidney Diseases, Vol. 61, No. 6, 06.2013, p. 889-898.

Research output: Contribution to journalArticle

Olden, M, Teumer, A, Bochud, M, Pattaro, C, Köttgen, A, Turner, ST, Rettig, R, Chen, MH, Dehghan, A, Bastardot, F, Schmidt, R, Vollenweider, P, Schunkert, H, Reilly, MP, Fornage, M, Launer, LJ, Verwoert, GC, Mitchell, GF, Bis, JC, O'Donnell, CJ, Cheng, CY, Sim, X, Siscovick, DS, Coresh, J, Kao, WHL, Fox, CS & O'Seaghdha, CM 2013, 'Overlap between common genetic polymorphisms underpinning kidney traits and cardiovascular disease phenotypes: The CKDGen consortium', American Journal of Kidney Diseases, vol. 61, no. 6, pp. 889-898. https://doi.org/10.1053/j.ajkd.2012.12.024
Olden, Matthias ; Teumer, Alexander ; Bochud, Murielle ; Pattaro, Cristian ; Köttgen, Anna ; Turner, Stephen T ; Rettig, Rainer ; Chen, Ming Huei ; Dehghan, Abbas ; Bastardot, Francois ; Schmidt, Reinhold ; Vollenweider, Peter ; Schunkert, Heribert ; Reilly, Muredach P. ; Fornage, Myriam ; Launer, Lenore J. ; Verwoert, Germaine C. ; Mitchell, Gary F. ; Bis, Joshua C. ; O'Donnell, Christopher J. ; Cheng, Ching Yu ; Sim, Xueling ; Siscovick, David S. ; Coresh, Josef ; Kao, W. H Linda ; Fox, Caroline S. ; O'Seaghdha, Conall M. / Overlap between common genetic polymorphisms underpinning kidney traits and cardiovascular disease phenotypes : The CKDGen consortium. In: American Journal of Kidney Diseases. 2013 ; Vol. 61, No. 6. pp. 889-898.
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TY - JOUR

T1 - Overlap between common genetic polymorphisms underpinning kidney traits and cardiovascular disease phenotypes

T2 - The CKDGen consortium

AU - Olden, Matthias

AU - Teumer, Alexander

AU - Bochud, Murielle

AU - Pattaro, Cristian

AU - Köttgen, Anna

AU - Turner, Stephen T

AU - Rettig, Rainer

AU - Chen, Ming Huei

AU - Dehghan, Abbas

AU - Bastardot, Francois

AU - Schmidt, Reinhold

AU - Vollenweider, Peter

AU - Schunkert, Heribert

AU - Reilly, Muredach P.

AU - Fornage, Myriam

AU - Launer, Lenore J.

AU - Verwoert, Germaine C.

AU - Mitchell, Gary F.

AU - Bis, Joshua C.

AU - O'Donnell, Christopher J.

AU - Cheng, Ching Yu

AU - Sim, Xueling

AU - Siscovick, David S.

AU - Coresh, Josef

AU - Kao, W. H Linda

AU - Fox, Caroline S.

AU - O'Seaghdha, Conall M.

PY - 2013/6

Y1 - 2013/6

N2 - Background: Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits. Study Design: We conducted 2 targeted analyses. First, we examined whether known single-nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5×10-4 (0.05/325 tests). Setting & Participants: Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395), and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium. Predictor: We used 19 kidney SNPs and 64 vascular SNPs. Outcomes & Measurements: Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber, and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria. Results: In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were nonsignificant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (P = 9.3 ×10-10) and diastolic (P = 1.6 ×10-14) blood pressure and coronary artery disease (P = 2.2 ×10-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were nonsignificant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (P = 1.06 ×10 -07 and P = 7.05 ×10-08). Limitations: The combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations. Conclusions: Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.

AB - Background: Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits. Study Design: We conducted 2 targeted analyses. First, we examined whether known single-nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5×10-4 (0.05/325 tests). Setting & Participants: Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395), and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium. Predictor: We used 19 kidney SNPs and 64 vascular SNPs. Outcomes & Measurements: Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber, and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria. Results: In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were nonsignificant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (P = 9.3 ×10-10) and diastolic (P = 1.6 ×10-14) blood pressure and coronary artery disease (P = 2.2 ×10-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were nonsignificant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (P = 1.06 ×10 -07 and P = 7.05 ×10-08). Limitations: The combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations. Conclusions: Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.

KW - Cardiovascular disease

KW - chronic kidney disease

KW - genomics

KW - single-nucleotide polymorphism (SNP)

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