Skip to main content

Advertisement

SpringerLink
Log in

Genome-wide association study of urinary albumin excretion rate in patients with type 1 diabetes

  • Article
  • Published:
Diabetologia Aims and scope Submit manuscript

Abstract

Aims/hypothesis

An abnormal urinary albumin excretion rate (AER) is often the first clinically detectable manifestation of diabetic nephropathy. Our aim was to estimate the heritability and to detect genetic variation associated with elevated AER in patients with type 1 diabetes.

Methods

The discovery phase genome-wide association study (GWAS) included 1,925 patients with type 1 diabetes and with data on 24 h AER. AER was analysed as a continuous trait and the analysis was stratified by the use of antihypertensive medication. Signals with a p value <10−4 were followed up in 3,750 additional patients with type 1 diabetes from seven studies.

Results

The narrow-sense heritability, captured with our genotyping platform, was estimated to explain 27.3% of the total AER variability, and 37.6% after adjustment for covariates. In the discovery stage, five single nucleotide polymorphisms in the GLRA3 gene were strongly associated with albuminuria (p < 5 × 10−8). In the replication group, a nominally significant association (p = 0.035) was observed between albuminuria and rs1564939 in GLRA3, but this was in the opposite direction. Sequencing of the surrounding genetic region in 48 Finnish and 48 UK individuals supported the possibility that population-specific rare variants contribute to the synthetic association observed at the common variants in GLRA3. The strongest replication (p = 0.026) was obtained for rs2410601 between the PSD3 and SH2D4A genes. Pathway analysis highlighted natural killer cell mediated immunity processes.

Conclusions/interpretation

This study suggests novel pathways and molecular mechanisms for the pathogenesis of albuminuria in type 1 diabetes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

AER:

Albumin excretion rate

ACR:

Albumin-to-creatinine ratio

AHT:

Antihypertensive

CEU:

Centre d’Etude du Polymorphisme (Utah residents with northern and western European ancestry)

ESRD:

End-stage renal disease

FinnDiane:

Finnish Diabetic Nephropathy study

GLRA3 :

Glycine receptor subunit α-3

GWAS:

Genome-wide association study

LD:

Linkage disequilibrium

MAF:

Minor allele frequency

NFS-ORPS:

UK Nephropathy Family Study and Oxford Regional Prospective Study

nU-AER:

Overnight urine AER

QQ-plot:

Quantile–quantile plot

SDR:

Scania Diabetes Registry

SNP:

Single nucleotide polymorphism

SUMMIT:

SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools

UK-ROI:

All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK and Republic of Ireland

References

  1. Nathan DM, Zinman B, Cleary PA et al (2009) Modern-day clinical course of type 1 diabetes mellitus after 30 years’ duration: the diabetes control and complications trial/epidemiology of diabetes interventions and complications and Pittsburgh epidemiology of diabetes complications experience (1983–2005). Arch Intern Med 169:1307

    Article  PubMed Central  PubMed  Google Scholar 

  2. Caramori ML, Fioretto P, Mauer M (2006) Enhancing the predictive value of urinary albumin for diabetic nephropathy. J Am Soc Nephrol 17:339–352

    Article  CAS  PubMed  Google Scholar 

  3. Remuzzi G, Benigni A, Remuzzi A (2006) Mechanisms of progression and regression of renal lesions of chronic nephropathies and diabetes. J Clin Invest 116:288–296

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Groop PH, Thomas MC, Moran JL et al (2009) The presence and severity of chronic kidney disease predicts all-cause mortality in type 1 diabetes. Diabetes 58:1651

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Tarnow L, Groop PH, Hadjadj S et al (2008) European rational approach for the genetics of diabetic complications–EURAGEDIC: patient populations and strategy. Nephrol Dial Transplant 23:161–168

    Article  CAS  PubMed  Google Scholar 

  6. Parving HH, Smidt UM (1986) Hypotensive therapy reduces microvascular albumin leakage in insulin-dependent diabetic patients with nephropathy. Diabet Med 3:312–315

    Article  CAS  PubMed  Google Scholar 

  7. Ritz E, Viberti GC, Ruilope LM et al (2010) Determinants of urinary albumin excretion within the normal range in patients with type 2 diabetes: the Randomised Olmesartan and Diabetes Microalbuminuria Prevention (ROADMAP) study. Diabetologia 53:49–57

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Forsblom CM, Kanninen T, Lehtovirta M, Saloranta C, Groop LC (1999) Heritability of albumin excretion rate in families of patients with type II diabetes. Diabetologia 42:1359–1366

    Article  CAS  PubMed  Google Scholar 

  9. Krolewski AS, Poznik GD, Placha G et al (2006) A genome-wide linkage scan for genes controlling variation in urinary albumin excretion in type II diabetes. Kidney Int 69:129–136

    Article  CAS  PubMed  Google Scholar 

  10. Quinn M, Angelico MC, Warram JH, Krolewski AS (1996) Familial factors determine the development of diabetic nephropathy in patients with IDDM. Diabetologia 39:940–945

    Article  CAS  PubMed  Google Scholar 

  11. Harjutsalo V, Katoh S, Sarti C, Tajima N, Tuomilehto J (2004) Population-based assessment of familial clustering of diabetic nephropathy in type 1 diabetes. Diabetes 53:2449–2454

    Article  CAS  PubMed  Google Scholar 

  12. Boger CA, Chen MH, Tin A et al (2011) CUBN is a gene locus for albuminuria. J Am Soc Nephrol 22:555–570

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Fioretto P, Mauer M (2010) Diabetic nephropathy: diabetic nephropathy-challenges in pathologic classification. Nat Rev Nephrol 6:508–510

    Article  PubMed  Google Scholar 

  14. Sandholm N, Salem RM, McKnight AJ et al (2012) New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet 8:e1002921

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Pezzolesi MG, Poznik GD, Mychaleckyj JC et al (2009) Genome-wide association scan for diabetic nephropathy susceptibility genes in type 1 diabetes. Diabetes 58:1403–1410

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Thorn LM, Forsblom C, Fagerudd J et al (2005) Metabolic syndrome in type 1 diabetes: association with diabetic nephropathy and glycemic control (the FinnDiane study). Diabetes Care 28:2019–2024

    Article  PubMed  Google Scholar 

  17. Del Bo R, Scarlato M, Ghezzi S et al (2006) VEGF gene variability and type 1 diabetes: evidence for a protective role. Immunogenetics 58:107–112

    Article  CAS  PubMed  Google Scholar 

  18. Lindholm E, Agardh E, Tuomi T, Groop L, Agardh CD (2001) Classifying diabetes according to the new WHO clinical stages. Eur J Epidemiol 17:983–989

    Article  CAS  PubMed  Google Scholar 

  19. Mollsten A, Kockum I, Svensson M et al (2008) The effect of polymorphisms in the renin–angiotensin–aldosterone system on diabetic nephropathy risk. J Diabet Complicat 22:377–383

    Article  Google Scholar 

  20. Amin R, Widmer B, Prevost AT et al (2008) Risk of microalbuminuria and progression to macroalbuminuria in a cohort with childhood onset type 1 diabetes: prospective observational study. BMJ 336:697–701

    Article  PubMed Central  PubMed  Google Scholar 

  21. Marcovecchio ML, Dalton RN, Schwarze CP et al (2009) Ambulatory blood pressure measurements are related to albumin excretion and are predictive for risk of microalbuminuria in young people with type 1 diabetes. Diabetologia 52:1173–1181

    Article  CAS  PubMed  Google Scholar 

  22. McKnight AJ, Patterson CC, Pettigrew KA et al (2010) A GREM1 gene variant associates with diabetic nephropathy. J Am Soc Nephrol 21:773–781

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Li Y, Willer C, Sanna S, Abecasis G (2009) Genotype imputation. Annu Rev Genomics Hum Genet 10:387–406

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR (2010) MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 34:816–834

    Article  PubMed Central  PubMed  Google Scholar 

  25. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904–909

    Article  CAS  PubMed  Google Scholar 

  26. Purcell S, Neale B, Todd-Brown K et al (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  27. Willer CJ, Li Y, Abecasis GR (2010) METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26:2190–2191

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Yang J, Lee SH, Goddard ME, Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 88:76–82

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Untergasser A, Cutcutache I, Koressaar T et al (2012) Primer3—new capabilities and interfaces. Nucleic Acids Res 40:e115

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Barrett JC (2009) Haploview: visualization and analysis of SNP genotype data. Cold Spring Harb Protoc 2009:pdb.ip71

  31. NCBI Resource Coordinators (2013) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 41:D8–D20

    Article  PubMed Central  Google Scholar 

  32. Segre AV, DIAGRAM Consortium, MAGIC investigators et al (2010) Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet 6:e1001058

    Article  PubMed Central  PubMed  Google Scholar 

  33. Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB (2010) Rare variants create synthetic genome-wide associations. PLoS Biol 8:e1000294

    Article  PubMed Central  PubMed  Google Scholar 

  34. Anderson CA, Soranzo N, Zeggini E, Barrett JC (2011) Synthetic associations are unlikely to account for many common disease genome-wide association signals. PLoS Biol 9:e1000580

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. Norio R (2003) Finnish Disease Heritage I: characteristics, causes, background. Hum Genet 112:441–456

    PubMed  Google Scholar 

  36. Norio R (2003) Finnish Disease Heritage II: population prehistory and genetic roots of Finns. Hum Genet 112:457–469

    PubMed  Google Scholar 

  37. Kingsmore SF, Suh D, Seldin MF (1994) Genetic mapping of the glycine receptor alpha 3 subunit on mouse chromosome 8. Mamm Genome 5:831–832

    Article  CAS  PubMed  Google Scholar 

  38. Li C, Liu C, Nissim I et al (2013) Regulation of glucagon secretion in normal and diabetic human islets by gamma-hydroxybutyrate and glycine. J Biol Chem 288:3938–3951

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. den Eynden JV, Ali SS, Horwood N et al (2009) Glycine and glycine receptor signalling in non-neuronal cells. Front Mol Neurosci 2:9

    Google Scholar 

  40. Yin M, Zhong Z, Connor HD et al (2002) Protective effect of glycine on renal injury induced by ischemia-reperfusion in vivo. Am J Physiol Renal Physiol 282:F417–F423

    Article  CAS  PubMed  Google Scholar 

  41. Woroniecka KI, Park AS, Mohtat D, Thomas DB, Pullman JM, Susztak K (2011) Transcriptome analysis of human diabetic kidney disease. Diabetes 60:2354–2369

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Schmid H, Boucherot A, Yasuda Y et al (2006) Modular activation of nuclear factor-kappaB transcriptional programs in human diabetic nephropathy. Diabetes 55:2993–3003

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge M. Parkkonen, A. Sandelin, A.-R. Salonen, T. Soppela and J. Tuomikangas (Folkhälsan Research Center, Helsinki, Finland and Division of Nephrology, Helsinki University Central Hospital, Helsinki, Finland) for their skilful laboratory assistance. We also thank all the patients who participated in the study and gratefully acknowledge all the physicians and nurses at each centre involved in the recruitment of participants (ESM [Table 8]).

Funding

The FinnDiane study was supported by grants from the Folkhälsan Research Foundation, the Wilhelm and Else Stockmann Foundation, Liv och Hälsa Foundation, Helsinki University Central Hospital Research Funds (EVO), the Sigrid Juselius Foundation, the Finnish Cultural Foundation, the Signe and Ane Gyllenberg Foundation, Finska Läkaresällskapet, Academy of Finland (no. 134379), Novo Nordisk Foundation and Tekes. The research was supported by the European Union Seventh Framework Program (FP7/2007–2013) for the Innovative Medicine Initiative under grant agreement no. IMI/115006 (the SUMMIT consortium), the Northern Ireland Research and Development Office and the Northern Ireland Kidney Research Fund.

Duality of interest

P-HG has received lecture honorariums from AbbVie, Boehringer Ingelheim, Cebix, Eli Lilly, Genzyme, Novartis, Novo Nordisk, MSD and Medscape, and research grants from Eli Lilly and Roche. P-HG is also an advisory board member of Boehringer Ingelheim, Eli Lilly and Novartis. The other authors declare that they have no duality of interest associated with this manuscript.

Contribution statement

NS and AJM contributed to the conception and design of the study, analysed and interpreted the data and drafted the article. CF and V-PM contributed to the conception and design of the study and interpretation of the results and critically revised the article. CF also contributed to the acquisition of data. A-MÖ, BH, EA and JC contributed to the analysis and acquisition of the data and critically revised the article. VH, RL, DG, MP, MS, LMT, NT, JW, JT, ML, AM, MLM, DD, ADP, GZ, LG and LT contributed to the acquisition of the phenotype and/or genotype data and reviewed the manuscript critically. APM and KT contributed to the conception and study design and to the data acquisition and revised the article critically.

P-HG designed and supervised the study and reviewed the article critically, and is responsible for the integrity of the work as a whole. All authors approved the final version of the article to be published.

Author information

Authors and Affiliations

  1. Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland

    Niina Sandholm, Carol Forsblom, Ville-Petteri Mäkinen, Valma Harjutsalo, Raija Lithovius, Daniel Gordin, Maija Parkkonen, Markku Saraheimo, Lena M. Thorn, Nina Tolonen, Johan Wadén & Per-Henrik Groop

  2. Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Biomedicum Helsinki, Haartmaninkatu 8, P.O. Box 63, 00014, University of Helsinki, Helsinki, Finland

    Niina Sandholm, Carol Forsblom, Ville-Petteri Mäkinen, Valma Harjutsalo, Raija Lithovius, Daniel Gordin, Maija Parkkonen, Markku Saraheimo, Lena M. Thorn, Nina Tolonen, Johan Wadén & Per-Henrik Groop

  3. Department of Biomedical Engineering and Computational Science, Aalto University School of Science, Helsinki, Finland

    Niina Sandholm

  4. Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA

    Ville-Petteri Mäkinen

  5. Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, UK

    Amy Jayne McKnight & Alexander P. Maxwell

  6. Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden

    Anne-May Österholm, Bing He & Karl Tryggvason

  7. Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland

    Valma Harjutsalo & Jaakko Tuomilehto

  8. Centre for Vascular Prevention, Danube-University Krems, Krems, Austria

    Jaakko Tuomilehto

  9. Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia

    Jaakko Tuomilehto

  10. Clinical Research Department, Steno Diabetes Center, Gentofte, Denmark

    Maria Lajer & Lise Tarnow

  11. Department of Clinical Sciences, Diabetes and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden

    Emma Ahlqvist & Leif Groop

  12. Department of Clinical Sciences, Paediatrics, Umeå University, Umeå, Sweden

    Anna Möllsten

  13. Department of Paediatrics, Institute of Metabolic Science, University of Cambridge, Cambridge, UK

    M. Loredana Marcovecchio & David Dunger

  14. Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK

    Jason Cooper

  15. Genetics and Genome Biology Program, Hospital for Sick Children Research Institute, Toronto, ON, Canada

    Andrew D. Paterson

  16. Complications of Diabetes Unit, Division of Metabolic and Cardiovascular Sciences, San Raffaele Scientific Institute, Milan, Italy

    Gianpaolo Zerbini

  17. Health, Aarhus University, Aarhus, Denmark

    Lise Tarnow

  18. Research Unit, Nordsjaellands Hospital, Hilleroed, Denmark

    Lise Tarnow

  19. Regional Nephrology Unit, Belfast City Hospital, Belfast, UK

    Alexander P. Maxwell

  20. Baker IDI Heart & Diabetes Institute, Melbourne, VIC, Australia

    Per-Henrik Groop

Authors
  1. Niina Sandholm
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carol Forsblom
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ville-Petteri Mäkinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amy Jayne McKnight
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Anne-May Österholm
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bing He
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Valma Harjutsalo
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Raija Lithovius
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Daniel Gordin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Maija Parkkonen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Markku Saraheimo
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Lena M. Thorn
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Nina Tolonen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Johan Wadén
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Jaakko Tuomilehto
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Maria Lajer
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Emma Ahlqvist
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Anna Möllsten
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. M. Loredana Marcovecchio
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Jason Cooper
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. David Dunger
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Andrew D. Paterson
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Gianpaolo Zerbini
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Leif Groop
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Lise Tarnow
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Alexander P. Maxwell
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Karl Tryggvason
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Per-Henrik Groop
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

on behalf of The SUMMIT Consortium

on behalf of the FinnDiane Study Group

Corresponding author

Correspondence to Per-Henrik Groop.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM

(PDF 1332 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sandholm, N., Forsblom, C., Mäkinen, VP. et al. Genome-wide association study of urinary albumin excretion rate in patients with type 1 diabetes. Diabetologia 57, 1143–1153 (2014). https://doi.org/10.1007/s00125-014-3202-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00125-014-3202-3

Keywords

Search

Navigation