Post on 24-Jun-2020
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UNCNephropathology
Heterogeneity and Risk Prediction of Diabetic Kidne y Disease
Amy Mottl MD, J. Charles Jennette, MD
UNCNephropathology
• Pathology
• Pathogenesis
• Epidemiology
• Pathologic features for clinical correlation
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Diabetic Glomerulosclerosis
K-W nodule
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Capillary aneurysm caused by mesangiolysis
K-W nodule
Capsular drop
Hyaline cap
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IgG Staining in Diabetic Glomerulosclerosis
Linear staining of GBMs and TBMs.
Variable staining of mesangial matrix.
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normal diabetes
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Diabetic Kidney Disease
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UNCNephropathology
O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
Temporal and Demographic Trends in Glomerular Disease Epidemiology in the Southeastern United States, 1986–2015
Among 21,374 patients (mean age =48.3±18.3 years ol d; 50.8% men;
56.8% white; 38.3% black; 2.8% Latino; 1.4% Asian; 0.8% other),the
frequency of diabetic glomerulosclerosis in renal b iopsy specimens
increased dramatically over three decades (5.5%, 11 .4%, and 19.1% of
diagnoses, respectively; P for trend <0.001).
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Temporal trends in the relative renal biopsy freque ncies of the most common glomerular disease subtypes, 1986–2015.
DKD Frequencies excluding DKD
O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
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UNCNephropathology
O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
Relative renal biopsy diagnosis frequencies of the most common glomerular disease subtypes according to patient ag e category and typical
mode of clinical presentation.
DKD
Nephrotic Presentation Nephritic Presentation
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Absolute renal biopsy diagnosis frequencies of the most common glomerular disease subtypes according to patient ag e category
O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
DKD
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Renal biopsy diagnosis frequencies of the most comm on glomerular disease subtypes according to patient age category stratified by sex
UNCNephropathology
O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
DKD DKD
FSGSSLE
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O’Shaughnessy, Hogan, Poulton, Falk, Singh, Nickeleit, Jennette. CJASN 2017;12:614-623
Renal biopsy diagnosis frequencies of the most comm on glomerular disease subtypes according to patient age category stratified by race
DKDDKDFSGS
FSGS
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USA/Canada
Europe
Asia
Latin America
DKD
Glomerular Disease Frequencies by Race, Sex, and Region: Results from the International Kidney Biopsy Survey (IKBS). O'Shaughnessy, Hogan, Thompson, Coppo, Fogo, Jennette. Nephrol Dial Transplant 2017, in press.
Glomerular Disease Subtype Kidney Biopsy Frequencies, by Geographic Region
The higher risk for DKD in USA/Canada versus Europe, Latin America, or Asia may be driven by associations between unhealthy lifestyle, metabolic syndrome, and disease development.
>60K diagnoses, >40K glomerular disease diagnoses
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DKD DKD DKD
Glomerular Disease Subtype Kidney Biopsy Frequencie s, by Race, Comparing Regions of Ancestral Origin to USA/Canada
Glomerular Disease Frequencies by Race, Sex, and Region: Results from the International Kidney Biopsy Survey (IKBS). O'Shaughnessy, Hogan, Thompson, Coppo, Fogo, Jennette. Nephrol Dial Transplant 2017, in press.
Based on 42,603 renal biopsy diagnoses
DKD is a more frequent glomerular disease among whi tes in North America vs Europe (18% vs 6%, p<0.001); and more frequent among Latinos in USA/Ca mada vs Latin America (17% vs 4%, p<0.001)
>60K diagnoses, >40K glomerular disease diagnoses
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UNCNephropathology
Glomerular Segmental Sclerosis and Extracapillary H ypercellularityPredict Poor Outcome in Diabetic Kidney Disease
Amy K. Mottl, Adil Gasim, Fernanda P. Schober, Yichun Hu,Askia Dunnon, Susan L. Hogan, J. Charles Jennette
Submitted to JASN, 2017
• Study Design and Population: Longitudinal, retrospective study of clinical, 109native kidney biopsies at the University of North Carolina (UNC) between 1995–2011with a pathologic diagnosis of diabetic glomerulosclerosis, and adequate clinical data.
• Pathology Review of Kidney Biopsy Specimens: Renal biopsy review carried outwithout knowledge of clinical outcomes.
• Statistical Analyses: Baseline demographic and clinical parameters and pathologiccharacteristics quantified using percentages for categorical variables and median andinterquartile ranges (IQR) for continuous variables. Univariate and multivariable riskmodels of ESRD with death as a competing risk were constructed to assess theassociation between clinical and pathologic variables and ESRD.
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Class IV DGSSegmental sclerosis
& adhesionSegmental sclerosis
with collapseExtracapillary
hypercellularity
Extracapillary hypercellularity
Extracapillary hypercellularity and arteriolar occlusion
EXHC and SS
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Changing clinical landscape of DKD
1988-1994 1999-2004 2005-2008 2009-2014P value
for trend
Any DKD 28 (24-33) 27 (23-31) 27 (23-31) 26 (23-30) 0.39
AlbuminuriaACR≥30ug/mg
21 (16-25) 19 (15-22) 18 (14-23) 16 (13-19) § <0.001
Macroalbuminuria 5.6 (2.8-8.4) 5.4 (3.1-7.7) 4.9 (2.8-7.1) 5.0 (3.6-6.6) 0.22
eGFR < 60 ml/min/1.73m2 9.2 (6.2-12.2) 11.6 (8.5-14.6)§ 11.8 (8.4-15.1) § 14.1 (11.3-17.0) § <0.001
eGFR < 30ml/min/1.73m2 1.0 (0.5-2.0) 1.7 (1.1-2.6) 1.8 (1.2-2.7) 2.7 (2.0-3.7) § 0.004
*All characteristics account for persistence except eGFR < 30ml/min/1.73m2
§Significantly different from prevalence in reference years 1988-1994
Afkarian, et al. JAMA 2016; 316(6): 602-610
Changing prevalence, % (95% CI) clinical characteristics* of DKD over past 20 years from NHANES.
Changing clinical landscape of DKD
Afkarian, et al. JAMA 2016; 316(6): 602-610
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Krolewski et al. Diabetes Care 2014; 37:226-234
eGFR decline as an EARLY prognostic tool
Characteristics
Normoalbuminuria Microalbuminuria
GFR change during follow-up GFR change during follow-up
Nondecliner Decliner P-value Nondecliner Decliner P-value
Renal FunctionBaseline eGFRFollow up eGFReGFR slope (%/yr)
113 (103-124)103 (93-115)
-1.3 (-2.1 to -0.7)
104 (91-117)61 (54-76)
-5.0 (-7.3 to -3.8)
<0.005116 (105-124)103 (89-116)
-1.5 (-2.1 to -0.7)
99 (80-111)59 (48-76)
-5.1 (-7.4 to -4.0)
<0.001
AER abnormalityBaseline AER (µg/min)Progression to MicroProgression to Macro
16 (12-22)17%
--
16 (12-22)54%
--
NS<0.001
57 (42-92)--
4%
94 (51-166)--
27%
<0.001
<0.001
Factors associated with rapid eGFR decline
Krolewski et al. Diabetes Care 2014; 37:226-234
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Pathogenetic factors in DKD
Atherosclerosis
Hypertension Hyperglycemia
DKD
Obesity
Genetics
Insulin Resistance
ATNATN
Acute kidney injury in DKD
Thakar CV et al. CJASN 2011; 6: 2567-72
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Correlations of pathology with clinical markers
eGFR ≥ 60ml/min/1.73m 2 eGFR < 60ml/min/1.73m 2
Urine Albumin:Creatinine Ratio
<30ug/mg 30-299ug/mg ≥300ug/mg <30ug/mg 30-299ug/mg ≥300ug/mg
??
Clinical DKD phenotype using currently available markers of renal disease.
Fioretto et al. Diabetologia 1996; 39: 1569-1576; Ekinci et al; Diabetes Care 2013 Nov;36(11):3620-6; Mottl et al; unpublished
Pathologic Classification of DKDTervaert et al. J Am Soc Nephrol. 2010 Apr;21(4):556-63
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Renal survival, free of ESRD, among diabetic patients with (A) renal biopsy and (B) pure DN according to pathologic glomerular classification.
Renal survival according to histology
Oh, et al. Diab Res Clin Prac 2012; 97: 418-424
Characteristic Mean (95% CI)
Age, years 52 (46, 62)
Male sex, n (%) 62(56.9%)
Black race, n (%) 53(48.6%)
Type 2 diabetes, n (%) 79(86.8%)
Diabetes duration, years 14.1 (9.7, 17.4)
Hemoglobin A1c, % 6.8 (6.2, 9.0)
Systolic blood pressure, mmHg 151 (134, 165)
Follow-up time, months 18.2 (5.5, 42.3)
eGFR, ml/min/1.73m2 22 (15, 37)
Urine protein*, gm/gm 4.5 (2.0, 8.1)
eGFR slope, ml/min/1.73m2/yr -3.3 (-14.2, 0.00)
ESRD during f/u, n (%) 59 (55.7%)
Time to ESRD, months 9.1 (3.0, 29.9)
Death during follow up, n (%) 28 (26.4%)
Time to death, months 22.9 (11.5, 43.6)
Risk Stratification by Pathologic Characteristics
in Clinical Biopsies (N=109)
Mottl, Gasim, Jennette, et al; in review, JASN
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Mottl, Gasim, Jennette, et al; in review, JASN
Pathologic predictors in clinical biopsies
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Stereologic analyses in early DKD
Histologic Predictors of GFR Decline
25 –
20 –
15 –
10 –
5 –
0 –
-50 -25 -20 -15 -10 -5 0 +5 +10 +15 +20 +25
# of patients
//25 –
20 –
15 –
10 –
5 –
0 –
-50 -25 -20 -15 -10 -5 0 +5 +10 +15 +20 +25//
MicroalbuminuricsMedian: -0.40 % GFR/yr
% GFR change from base line per year
ProteinuricsMedian: -1.80 % GFR/yr
Nosadini R et al. Diabetes 2000; 49:476-484
Median
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Nosadini et al. Diabetes 2000; 49: 476-484
Stereology as a prognosticator
Stereology as a prognosticator
Morphometric Variable
Hazard Ratios (95% CI) for ≥40% renal function loss
Unadjusted Adjusted*
Global glomerular sclerosis, %
1.08 (0.83, 1.41) 1.63 (1.21, 2.21)
Mean glomerular volume, x106 u3 1.32 (1.02, 1.70) 1.42 (1.02, 1.96)
GBM width, nm 1.53 (1.16, 2.0) 1.48 (1.05, 2.08)
Mesangial Fractional Volume per glom, %
1.84 (1.39, 2.42) 2.27 (1.58, 3.26)
Glomerular Filtration Surface Density, µ2/µ3 0.67 (0.48, 0.92) 0.62 (0.41, 0.94)
Nonpodocyte no. per glomerulus
1.46 (1.15, 1.87) 1.50 (1.10, 2.05)
Endothelial Fenestration, % 0.68 (0.50, 0.91) 0.68 (0.48, 0.95)
*Adjusted for baseline age, sex, diabetes duration, HbA1c, GFR
Fufaa et al. CJASN 2016; 11: 254-261
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Circulating TNF Receptors
Niewczas et al. JASN 2012; 23: 507-515