Despite decades of research, the pathogenesis of human diabetic kidney disease remains largely unclear. Our goal is to use archived human kidney biopsy tissue from patients with and with diabetic nephropathy to identify new molecules that drive and/or protect against disease progression. We will use RNA sequencing to identify transcriptomic changes that associate with histologic and functional outcomes.

RESEARCH OBJECTIVES A. To identify differences in transcription profiles obtained from residual kidney tissue which was obtained for clinical purposes.

B. To identify differences in transcription profile between patients whose loss of kidney function progresses rapidly (eGFR decline ≥4ml/min/year) and in whom it progresses more slowly (eGFR decline <4ml/min/year).

C. To identify differences in transcription profile between predominantly glomerular and predominantly tubulointerstitial histopathological types .

D. To identify new pathogenetic pathways that may become targets for therapeutic intervention

METHODS The planned study centres on the use of archival biopsy material that is superfluous to what is or would be needed for clinical care (01/01/1995 to 31/05/2018 , n= approximately 400-500). Archived samples will be collected from St. Michael's Hospital and a number of collaborating centres, including but not limited to University of British Columbia, the University of Manitoba, and the University of Ottawa.

RNA will be extracted from the biopsy material using either the core that has been used for immunofluorescence microscopy and is stored at -80˚C, and/or the core that is formalin-fixed, embedded in paraffin wax and stored at room temperature. The RNA thereby extracted will be subjected to detailed interrogation by RNASeq to quantify the expression level of mRNAs (transcriptome) and compare differences, as indicated in the research objectives detailed above. The transcriptome will then be related to the clinical course (eGFR decline) and histopathological changes, in addition to examining potentially pathogenetically important and that are amenable to therapeutic intervention.

Histopathology will also be performed and classified according to established systems.

Clinical information that would be retrieved from patients' medical records are listed below.

Clinical data

1. Age

2. Gender

3. Ethnicity

4. Diabetes history

5. Diabetes type: 1, 2

6. Retinopathy history

7. Smoking history

8. Medications

9. Comorbidities

10. Past medical history

11. Primary nephrologist Laboratory data (prior to biopsy, at biopsy and post-biopsy)

12. Renal function measures and calculations. For example:

    i. Serum creatinine, eGFR ii. Change in creatinine and eGFR iii. Urinary albumin:creatinine values and ratio (ACR) iv. Urine protein:creatinine values and ratio (PCR) v. Urinary protein excretion rate (UPEx) vi. Changes in ACR, PCR, UPEx

13. Diabetes measures and calculations. Biopsy data

14. Biopsy related data

Each site will locally maintain a confidential Master Linking Log.

De-identified data will be entered into a secure REDCap database that is hosted by St. Michael's Hospital.

Inclusion Criteria (diabetic kidney disease cases):

• history of type 1 or type 2 diabetes
• at least 1 archived native kidney biopsy that demonstrates either pure diabetic kidney disease or features of non-specific vascular disease, including glomerulosclerosis, non-inflammatory vascular disease,
• sufficient remaining archived kidney biopsy tissue for RNA sequencing (100 um thick tissue section) and histologic analysis (PAS and Masson Trichrome staining)

Exclusion Criteria (diabetic kidney disease cases):

• less than 3 eGFR values post-biopsy
• latest recorded eGFR values less than 6 months post-biopsy

Inclusion Criteria (healthy controls):

- at least 1 native kidney disease biopsy with no diagnostic abnormality

1. Cases: A group of patients with diabetic kidney disease
2. Controls: A group of healthy control patients