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Genetic susceptibility to diabetic kidney disease is linked to promoter variants of XOR

Nature Metabolism volume 5, pages 607–625 (2023)Cite this article

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Abstract

The lifetime risk of kidney disease in people with diabetes is 10–30%, implicating genetic predisposition in the cause of diabetic kidney disease (DKD). Here we identify an expression quantitative trait loci (QTLs) in the cis-acting regulatory region of the xanthine dehydrogenase, or xanthine oxidoreductase (Xor), a binding site for C/EBPβ, to be associated with diabetes-induced podocyte loss in DKD in male mice. We examine mouse inbred strains that are susceptible (DBA/2J) and resistant (C57BL/6J) to DKD, as well as a panel of recombinant inbred BXD mice, to map QTLs. We also uncover promoter XOR orthologue variants in humans associated with high risk of DKD. We introduced the risk variant into the 5′-regulatory region of XOR in DKD-resistant mice, which resulted in increased Xor activity associated with podocyte depletion, albuminuria, oxidative stress and damage restricted to the glomerular endothelium, which increase further with type 1 diabetes, high-fat diet and ageing. Therefore, differential regulation of Xor contributes to phenotypic consequences with diabetes and ageing.

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Fig. 1: QTL on chr 17 influences podocyte numbers in long-term diabetes and causative variant points to XOR regulation.
Fig. 2: C/EBPβ binding to risk variants in the Xor promoter upregulates Xor expression in diabetic D2 mice.
Fig. 3: Xor promoter risk variants upregulate Xor activity in diabetic B6-Xorem1 mice.
Fig. 4: Xor promoter risk variants promote podocyte depletion and glomerular injury with diabetes.
Fig. 5: Xor promoter risk variants in B6-XORem1 mice promote DKD following STZ treatment, in genetically induced type 1 diabetes and under a HFD.
Fig. 6: Xor promoter risk variants in B6-Xorem1 mice mediate DKD and promote ageing-related glomerulosclerosis.
Fig. 7: Diabetes increased oxidative stress and mitochondrial damage in GECs of diabetic B6-Xorem1 and D2-WT mice.

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The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files. Source data are provided with this paper.

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Acknowledgements

We thank the Genome Engineering and iPSC Center (GEiC) at Washington University Department of Genetics for providing support in the generation of small guide RNAs. We acknowledge Dr. K Kelly (The Institutional Mouse Genetics and Gene Targeting CoRE at Mount Sinai) for his valuable technical help in generation of B6-Xorem1(rs50771495-A>C/rs50017899-T>A)Isd knock-in mice. We thank A. Bajpai for his assistance with mice genetics. Parts of this research have been conducted using the UK Biobank Resource under application number 53074. This work was supported by grants from National Institutes of Health (NIH) grant R01DK097253 and Department of Defense CDMRP grant E01 W81XWH2010836 to I.D., and Leducq Foundation Award Number 21CVD01 to Y.I.

Author information

Authors and Affiliations

  1. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Qin Wang, Haiying Qi, Liping Yu, Rihab Bouchareb, Shuyu Li, Emelie Lassén, Gabriella Casalena, Zhengzi Yi, Shaolin Shi, Weijia Zhang, Erwin Böttinger & Ilse Daehn

  2. Department of Pharmacy, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China

    Qin Wang

  3. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Yiming Wu & Yuval Itan

  4. Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA

    Krisztian Stadler

  5. Department of Neuroscience and Physiology, Physiology, University of Gothenburg, Gothenburg, Sweden

    Kerstin Ebefors

  6. Pathology, Molecular and Cell based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Fadi Salem & Ronald Gordon

  7. Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA

    Lu Lu & Robert W. Williams

  8. Prime Medicine, Inc., Boston, MA, USA

    Jeremy Duffield

  9. Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Yuval Itan

  10. Hasso Plattner Institute for Digital Heath at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Erwin Böttinger

  11. Digital Health Center, Hasso Plattner Institut, University of Potsdam, Potsdam, Germany

    Erwin Böttinger

Authors
  1. Qin Wang
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  2. Haiying Qi
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  3. Yiming Wu
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  4. Liping Yu
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  5. Rihab Bouchareb
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  6. Shuyu Li
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  7. Emelie Lassén
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  8. Gabriella Casalena
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  9. Krisztian Stadler
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  10. Kerstin Ebefors
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  11. Zhengzi Yi
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  12. Shaolin Shi
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  13. Fadi Salem
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  14. Ronald Gordon
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  15. Lu Lu
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  16. Robert W. Williams
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  17. Jeremy Duffield
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  18. Weijia Zhang
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  19. Yuval Itan
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  20. Erwin Böttinger
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  21. Ilse Daehn
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Contributions

Q.W., H.Q., E.B. and I.D. conceived the idea, designed the research and wrote the first version of the manuscript. Q.W., H.Q., G.C., S.S., R.B., E.L., S.L., I.D. and L.Y. collected samples and performed the in vitro and in vivo experiments and performed the validation experiments. Z.Y. and W.Z. were responsible for the bioinformatic analyses of the microarray data. Y.W. and Y.I. performed human PheWAS. L.L. and R.W.W. performed the mouse QTL and eQTL analysis. J.D. performed in silico assessment of TFBS. K.S. performed and analysed electron paramagnetic resonance spectroscopy experiments. K.E., F.S. and R.G. performed TEM and provided pathology insights. Q.W., H.Q. and I.D. prepared the figures. I.D. developed the experimental strategy, supervised the project and wrote and edited the manuscript, which was then read by, commented on and approved by all authors.

Corresponding author

Correspondence to Ilse Daehn.

Ethics declarations

Competing interests

I.D. has a consultancy agreement with RUMI. J.D. is an executive at Prime Medicine. None of the other authors have competing interests.

Peer review

Peer review information

Nature Metabolism thanks Jochen Reiser, Farhad Danesh, Karin Jandeleit-Dahm and Jason Bubier for their contribution to the peer review of this work. Primary handling editor: Isabella Samuelson, in collaboration with the Nature Metabolism team.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Fasting blood glucose (FBG), body weight (BW), urine albumin:creatinine uACR and podocyte numbers per glomerulus in non-diabetic and diabetic D2 mice + /- XOi.

Bar graph shows the mean + /- SD of fasting blood glucose (FBG; mg/dl) in a) and BW (g) b) of D2-WT control ± allopurinol (XOi; n = 5/group) or STZ treated D2-WT mice ± XOi (n = 8/group) at 6 and 12 weeks of diabetes as indicated. c) uACR (ug/mg) of D2-WT ± XOi (n = 5/group) or STZ treated D2-WT only (n = 5) or + XOi (n = 10) at 6, 12 weeks of diabetes, and d) podocyte number (WT1 + cells) per glomerular section of control D2-WT ± XOi, or STZ treated D2-WT ± XOi at 6, 12 weeks of diabetes in >50 glomerular profiles/mouse (n = 5 mice/group). All data are presented as mean values ±SEM. Statistical significance in was calculated by one-way ANOVA with Tukey’s multiple comparisons test.

Extended Data Fig. 2 Transcription Factor Binding Sites (TFBS) in the promoter of XOR.

Mulan sequence conservation profile for the XOR promoter locus from human, cow and mouse genomes a). CEBP binding sites show high regulatory potential as indicated by a purple block depicted as colored tick marks above the conservation profile. Coding exons are in blue, UTRs in yellow, intergenic elements in red, and intronic in pink. b) multiTF visualization of XOR transcription factor binding site detected in the XOR locus constructed with mouse sequences (black rectangle). Identified TFBSs are depicted as colored blocks above the conservation profile.

Extended Data Fig. 3 Genotyping for XOR variants in mGECs and FACS gating strategy for ROS.

a) Representative agarose gel showing bands for B6-XorWT (top) and D2-WT (bottom) variants. Molecular weight markers in lane 1, lane 2: D2-WT, lane 3: B6-XorWT mice and in lane 4: mGECs. Image is representative of 4 independent tests. b) Genotyping strategy for detecting SNP variant through mismatch with AS primers F1 and F2 using a common R primer as described in Methods. c) FACS gating strategy showing a representative plot of negative unlabeled control mGECs % population of CM-H2-DCFDA, and d) % population of cells positive for CM-H2-DCFDA after 24 hr HG treatment.

Extended Data Fig. 4 Fasting blood glucose, body weights, serum suPAR and triglycerides in mice made diabetic by STZ, or genetic predisposition (Akita), or high fat diet (HFD).

a) Bar graph shows the fasting blood glucose in male B6-XorWT, B6-Xorem1 and D2-WT mice (n = 6/group) and female B6-XorWT (n = 4), B6-Xorem1 (n = 5) and D2-WT mice (n = 6) at 12 weeks of diabetes. b) Serum suPAR levels in diabetic B6-XorWT, B6-Xorem1 (n = 5/group) and D2-WT mice (n = 4). c) Fasting blood glucose and d) body weight (g) of Akita B6 (n = 4) and Akita B6-Xorem1 mice (n = 5) at 12 weeks of diabetes. e) Shows the fasting blood glucose, f) the body weight, g) triglycerides (mg/dL) and h) serum suPAR levels in B6-XorWT and B6-Xorem1 after 16 weeks of high fat diet (HFD, n = 5 mice/group). All data are presented as mean values ±SEM. In a) a two-way analysis of variance and Tukey’s multiple comparisons test was performed (*P < 0.05). In b-h) unpaired two-tailed Student’s t-tests was performed and showed no statistical significance between the groups.

Extended Data Fig. 5 C/EBPβ in high glucose or oxidized LDL treated primary GECs and podocytes.

a) Representative immunofluorescence staining for C/EBPβ (green) and CD31 (magenta) in primary glomerular endothelial cells from B6-XorWT and B6-Xorem1 mice (n = 3), treated with control normal glucose (NG), or high glucose (HG, 30 mM) for 24 hours showing nuclear translocation. Bar=20μm. b) C/EBPβ (green) and synaptopodin (red) in primary podocytes from B6-XorWT and B6-Xorem1 mice (n = 3), treated as in a). Bar=20μm. These are representative images from 3 independent experiments performed in primary cells grown from 3 separate B6-XorWT and 3 separate B6-Xorem1 mice.

Extended Data Table. 1 Candidate genes
Full size table
Extended Data Table. 2 XOR regulatory variants in participants in the UK Biobank
Full size table
Extended Data Table. 3 Gene level phenome wide association analyses
Full size table
Extended Data Table. 4 CRISPR/Cas9 off-target analysis in the B6-XORem1(rs50771495-A>C/rs50017899-T>A)Isd mouse line
Full size table

Supplementary information

Source data

Source Data Fig. 1

Unprocessed gel for Fig. 2b.

Source Data Fig. 2

Unprocessed western blot for Fig. 2g

Source Data Fig. 3

Unprocessed western blot for Fig. 3e

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Wang, Q., Qi, H., Wu, Y. et al. Genetic susceptibility to diabetic kidney disease is linked to promoter variants of XOR. Nat Metab 5, 607–625 (2023). https://doi.org/10.1038/s42255-023-00776-0

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