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Complications

Modular Activation of Nuclear Factor-κB Transcriptional Programs in Human Diabetic Nephropathy

  1. Holger Schmid1,
  2. Anissa Boucherot1,
  3. Yoshinari Yasuda1,
  4. Anna Henger1,
  5. Bodo Brunner2,
  6. Felix Eichinger1,
  7. Almut Nitsche2,
  8. Eva Kiss3,
  9. Markus Bleich4,
  10. Hermann-Josef Gröne3,
  11. Peter J. Nelson1,
  12. Detlef Schlöndorff1,
  13. Clemens D. Cohen1,
  14. Matthias Kretzler1 and
  15. for the European Renal cDNA Bank (ERCB) Consortium*
  1. 1Medizinische Poliklinik, University of Munich, Munich, Germany
  2. 2Sanofi-Aventis Deutschland, Frankfurt, Germany
  3. 3German Cancer Research Center, Heidelberg, Germany
  4. 4Physiology Institute, University of Kiel, Kiel, Germany
  1. Address correspondence and reprint requests to Clemens D. Cohen, MD, Division of Nephrology, Medizinische Poliklinik, University of Munich, Pettenkoferstr. 8a, 80336 Munich, Germany. E-mail: clemens.cohen{at}med.uni-muenchen.de
  2. Matthias Kretzler, MD, Division of Nephrology, University of Michigan, 1570 MSRB II, 1150 W. Medical Ctr. Dr., Ann Arbor, MI 48109-0676. E-mail: kretzler{at}umich.edu
Diabetes 2006 Nov; 55(11): 2993-3003. https://doi.org/10.2337/db06-0477
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  • FIG. 1.
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    FIG. 1.

    Flow diagram of the experimental strategy to define the transcriptional regulation in progressive DN via an integrated systems biology approach.

  • FIG. 2.
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    FIG. 2.

    Hierarchical cluster analysis of gene expression profiles from renal biopsies with early or progressive DN and different controls. Tubulointerstitial compartments of renal biopsies from patients with DN (n = 13) and MCD (n = 4), as well as pretransplant biopsies from related LD (n = 3) and CD (n = 4) kidneys, were analyzed. For clinical and histological patient characteristics, see Table 1. Gene expression profiles were analyzed using Affymetrix oligonucleotide arrays HGU133A. Of the 22,283 probe sets, 10,183 probe sets (45.7%) were expressed above background signal. Each row represents a gene; each column represents a biopsy. Transcript abundance is displayed on a red-green color scale, with red expression above and green below the median. Using the SAM algorithm, a multiple comparison analysis of LDs, CDs, MCD, and early and progressive DN with an FDR of 1% detected differential regulation of 1,349 from the 10,183 expressed probe sets. The cluster dendrogram sorts the patients with the most similar gene expression profiles together with the shortest branches. Hierarchical clustering showed three principal branches of DN, CD, and MCD/LD, with the earliest DN (DN1) as the only outlier in the MCD/LD cluster. Differentially regulated mRNAs are provided in the online appendix.

  • FIG. 3.
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    FIG. 3.

    The canonical NF-κB signaling pathway shows a prominent induction in progressive DN. To identify underlying control mechanisms of stress response genes in progressive DN, differentially regulated molecules were categorized into canonical pathways. Starting from 2,738 probe sets regulated between progressive DN and the combined controls (MCD/LD), 1,725 genes could be annotated to biological pathways using the Ingenuity Pathways Knowledge Base. Evaluating the master switch of stress responses, the canonical NF-κB signaling pathway, a differential regulation of 23 of 85 members (27%) in progressive DN compared with none in early DN could be detected. Upregulated genes are marked in red, downregulated genes in green, and green/red symbols correspond to differential regulation of gene isoforms.

  • FIG. 4.
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    FIG. 4.

    NF-κB–dependant target molecules are significantly regulated in progressive DN. Of 232 NF-κB–dependant target genes, 138 (59.5%) showed mRNA expression above background in the kidney expression arrays. An unbiased cluster dendrogram using these 138 genes segregated progressive DN from the combined controls (MCD/LD) and early DN. Of the 138 expressed NF-κB–dependant mRNAs, 54 genes (39%) were significantly induced compared with the combined controls (LD/MCD). In contrast, only one of the 138 genes was upregulated in the early DN, underlining the role of NF-κB in the progression of DN.

  • FIG. 5.
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    FIG. 5.

    Confirmation of predicted gene regulation by the NFKB_IRFF_01 promoter module. A: Microarray and real-time RT-PCR confirm the induction of B2M, HLA-A, HLA-B, VCAM1, and CXCL10/IP10 in progressive DN. B2M, HLA-A, HLA-B, VCAM1, and CXCL10/IP10 expression levels in progressive DN extracted from the array studies are given as ratios to the combined control group (LD/MCD) in the left panel. For confirmation and validation of the hybridization experiments, mRNA expression for CXCL10/IP10 was studied in a cohort of progressive DN patients (n = 22) and different control subjects (LD, n = 9; CD, n = 1; and MCD, n = 7) using real-time RT-PCR (right panel). mRNA expression ratios were normalized to Cyclophilin A. Comparable with the array data (left panel) CXCL10/IP10 mRNA was induced in the tubulointerstitium of patients with advanced DN (DN vs. control, P = 0.013*). Con, control. B: mRNA expression for CCL5/RANTES, EDN1, and IFNB1 is significantly induced in patients with progressive DN. mRNA expression for CCL5/RANTES, EDN1, and IFNB1 was studied in a cohort of progressive DN patients (n = 22) and different control subjects (n = 17) by real-time RT-PCR. mRNA expression ratios normalized to Cyclophilin A revealed a significant induction in the tubulointerstitium of patients with advanced DN (CCL5/RANTES: DN vs. control, *P < 0.001; EDN1: DN vs. control, *P = 0.012; IFNB1: DN vs. control, *P = 0.010*). Con, control.

Tables

  • Figures
  • TABLE 1

    Clinical and histological characteristics of reference biopsies analyzed by oligonucleotide array–based gene expression profiling and real-time RT-PCR

    Sample nameSexAge (years)Histology major diagnosisHistology scoreCreatinine (mg/dl)Urine proteinuria (g/day)
    Living donor
        Array
            LD1F66LDxNA<1.1<0.2
            LD2M26LDx w/o prev. damageNA0.9<0.2
            LD3M49LDx w/o prev. damageNA<1.1<0.2
        Mean ± SEM47 ± 9.6<0.2
        RT-PCR
            LD4F35LDxNA<1.1<0.2
            LD5M39LDxNA<1.1<0.2
            LD6F55LDxNA<1.1<0.2
            LD7M41LDxNA<1.1<0.2
            LD8M61LDxNA<1.1<0.2
            LD9F58LDxNA<1.1<0.2
            LD10M27LDxNA<1.1<0.2
            LD11F54LDxNA<1.1<0.2
            LD12F61LDxNA<1.1<0.2
        Mean ± SEM48 ± 14<1.1<0.2
    Cadaveric donor
        Array
            CD1M50CDx, minor int. fibrosisNA0.9<0.2
            CD2M54CDx w/o prev. damageNA0.9<0.2
            CD3M61CDx w/o prev. damageNA1.2<0.2
            CD4F51CDx, minor int. fibrosisNA0.7<0.2
        Mean ± SEM54 ± 2.10.9 ± 0.1<0.2
        RT-PCR
            CD5NANACDxNA<1.1<0.2
    MCD/ no histological changes
        Array
            MCD1M32Minimal-change GN11.311.0
            MCD2F32Minimal-change GN10.73.0
            MCD3M16Minimal-change GN01.25.4
            MCD4M20Minimal-change GN in remission00.90.2
        Mean ± SEM25 ± 3.61.0 ± 0.24.9 ± 2.3
        RT-PCR
            MCD5F57Minimal-change GN01.110
            MCD6M33Minimal-change GN11.49.1
            MCD7M24No histological changes00.60.4
        Mean ± SEM38 ± 81.0 ± 0.26.5 ± 2.5
  • TABLE 2

    Clinical and histological characteristics of disease biopsies analyzed by oligonucleotide array–based gene expression profiling and real-time RT-PCR

    Sample nameSexAge (years)Histology major diagnosisHistology scoreCreatinine (mg/dl)Proteinuria (g/day)Diabetes typeDiabetes duration (years)HbA1c (%)Retinopathy
    DN
        Array
            DN1M45DN00.90.720.37.1No
            DN2F34DN11.40.3131NAYes
            DN3M57DN31.69.71208.7Yes
            DN4M61DN21.13.7235.7Yes
            DN5F46DN22.40.42257.5Yes
            DN6F67DN44.82.425NAYes
            DN7M73DN21.12.4217.3No
            DN8M62DN21.22.5255.6No
            DN9M67DN24.03.02NANANA
            DN10M62DN32.35.0247.8No
            DN11M68DN33.52.4247.2No
            DN14F70DN44.05.0———No
            DN15M46DN30.96.0———No
        Mean ± SEM58.3 ± 3.42.2 ± 0.43.3 ± 0.710.9 ± 3.47.1 ± 0.3
        RT-PCR
            DN3M57DN31.69.71208.7Yes
            DN5F46DN22.40.42257.5Yes
            DN6F67DN44.82.425NANA
            DN10M62DN32.35.0247.8Yes
            DN11M68DN33.52.4247.2No
            DN16M58DN21.70.726.57.4No
            DN17M78DN43.63.1232NANo
            DN18F59DN43.221.4212NANA
            DN19M58DN42.414.22319.8Yes
            DN20F63DN43.37.02187.9No
            DN21M63DN42.18.62107.1No
            DN22F47DN47.0NA2813.8Yes
            DN23M74DN32.50.3284.6No
            DN24F63DN32.96.5276.4No
            DN25M55DN42.87.5267.8Yes
            DN26M57DN31.61.42208.8NA
            DN27M63DN23.00.6266.2NA
            DN28M66DN29.81.72106.0No
            DN29M60DN42.22.0286.9No
            DN30M75DN21.76.2267.3No
            DN31MNADNNA1.210.02<1NANA
            DN32F63DN42.05.52236.4NA
        Mean ± SEM62 ± 1.73.0 ± 0.45.5 ± 1.111.3 ± 1.77.6 ± 0.4
    • Clinical data are presented for all patients involved in the study, either analyzed by microarrays, real-time RT-PCR, or both. Follow-up of the clinical data revealed in 2 (in boldface type) of the 30 patients with nodular glomerulosclerosis, no evidence for clinically overt diabetes but a light chain deposit disease in DN14 and unclassified nodular glomerulosclerosis with mesangial matrix expansion in DN15.

  • TABLE 3

    ModelInspector analysis demonstrates a clear overrepresentation of the NF-κB module NFKB_IRFF_01 in 54 upregulated NF-κB–dependant target genes

    ModulesInduced NF-κ B genes
    Non-ind. NF-κ B genes
    All human promoters
    Number of matchesProbability (per 10,000 bp)Number of matchesProbability (per 10,000 bp)Number of matchesProbability (per 10,000 bp)
    AP1F_NFKB_0120.2910.11530.02
    AP1F_NFKB_0240.5810.11410.01
    AP1F_NFKB_0300.0010.111450.04
    AP1F_NFKB_0410.1510.11190.01
    AP1F_NFKB_EBOX_0100.0010.1120.00
    CEBP_NFKB_0100.0010.11340.01
    CEBP_NFKB_0220.2910.111210.03
    CEBP_NFKB_0410.1510.111110.03
    CEBP_NFKB_0510.1500.001390.04
    CEBP_NFKB_0650.7330.34>1,0000.43
    CEBP_NFKB_NFAT_0200.0010.112040.06
    CEBP_NFKB_STAT_0100.0010.1110.00
    CREB_NFKB_0110.1510.111380.04
    CREB_NFKB_0310.1500.001270.04
    GATA_GATA_NFKB_NFKB_0110.1500.0010.00
    IRFF_NFKB_0110.1500.001060.03
    IRFF_NFKB_0300.0020.23700.02
    NFKB_AP1F_0140.5860.68>1,0000.58
    NFKB_AP1F_SP1F_0100.0020.23140.00
    NFKB_CEBP_0110.1540.465960.17
    NFKB_CREB_0160.8840.46>1,0000.58
    NFKB_ETSF_0100.0010.11540.02
    NFKB_IRFF_0150.7300.00620.02
    NFKB_NFKB_0200.0010.1150.00
    NFKB_NFKB_0330.4410.11400.01
    NFKB_RBPF_0130.4460.683440.10
    NFKB_SORY_01142.04111.257720.22
    NFKB_SORY_02101.4650.573480.10
    NFKB_STAT_0100.0020.23260.01
    NFKB_STAT_0271.0291.02>1,0000.76
    NFKB_STAT_NFKB_0120.2930.342650.08
    SP1F_NFKB_0100.0010.11320.01
    STAT_NFKB_0210.1500.00270.01
    YY1F_NFKB_0110.1510.11500.01
    • Numbers of matches by ModelInspector (Genomatix) analyses of individual experimentally verified NF-κB containing promoter modules in proximal promoter sequences of 54 DN upregulated NF-κB target genes, 84 DN noninduced NF-κB target genes, and the whole human promoter library, including 50.145 proximal promoter sequences are depicted. Total length of analyzed proximal promoter sequences were 68.468 bp in upregulated NF-κB target genes, 87.856 bp in noninduced NF-κB target genes, and 35.125.826 bp in the whole human promoter library. Probabilities of matches with individual modules were shown as frequency of matches observed in 10.000 bp of analyzed proximal promoter sequences. Only the module NFKB_IRFF_01 (in boldface type) was significantly overrepresented in the proximal promoter sequences of induced NF-κB target genes compared with noninduced target genes (P < 0.05).

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Modular Activation of Nuclear Factor-κB Transcriptional Programs in Human Diabetic Nephropathy
Holger Schmid, Anissa Boucherot, Yoshinari Yasuda, Anna Henger, Bodo Brunner, Felix Eichinger, Almut Nitsche, Eva Kiss, Markus Bleich, Hermann-Josef Gröne, Peter J. Nelson, Detlef Schlöndorff, Clemens D. Cohen, Matthias Kretzler
Diabetes Nov 2006, 55 (11) 2993-3003; DOI: 10.2337/db06-0477

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Modular Activation of Nuclear Factor-κB Transcriptional Programs in Human Diabetic Nephropathy
Holger Schmid, Anissa Boucherot, Yoshinari Yasuda, Anna Henger, Bodo Brunner, Felix Eichinger, Almut Nitsche, Eva Kiss, Markus Bleich, Hermann-Josef Gröne, Peter J. Nelson, Detlef Schlöndorff, Clemens D. Cohen, Matthias Kretzler
Diabetes Nov 2006, 55 (11) 2993-3003; DOI: 10.2337/db06-0477
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