Table 3 Kidney functional and morphological changes in castrated male Göttingen Minipigs fed with standard diet (SD) or fat, fructose and cholesterol rich diet (FFC) with or without additional salt (S) and with or without streptozotocin-induced diabetes (DIA).

From: Functional and morphological renal changes in a Göttingen Minipig model of obesity-related and diabetic nephropathy

Functional kidney parameters

GFR (ml/min/pig)

T1

13.5 (12.8–14.9)

24.1 (19.6–26.2)15

17.9 (16.5–21.1)10

20.2 (14.7–23.5)7

Group*time (P < 0.0029):

T1: FFC > SD, FFC-DIA

T2:FFC, FFC-DIA, FFC-DIA + S > SD

T2 > T1: FFC, FFC-DIA, FFC-DIA + S

T2

17.1 (14.6–18.0)8

29.5 (26.3–33.1)13

36.4 (32.4–41.3)7

27.1 (25.8–35.6)6

Resitive index

T1

0.42

(0.38–0.42)

0.44

(0.41–0.48)

0.46

(0.38–0.48)12

0.47

(0.43–0.55)9

Group (P = 0.0002):

FFC, FFC-DIA, FFC-DIA + S > SD

Time (P = 0.047): T2 > T1

T2

0.37

(0.36–0.42)7

0.47

(0.44–0.50)14

0.49

(0.44–0.51)8

0.52

(0.43–0.57)8

Kidney morphology

Kidney weight (KW) (g)

T2

72

(57–76)7

116

(100–126)14

139

(128–151)8

109

(96–143)8

Group (P < 0.0001):

FFC, FFC-DIA, FFC-DIA + S > SD

Kidney fibrosis

T2

0.0679 (0.0661–0.0104)7

0.0854 (0.0470–0.1259)14

0.0555 (0.0422–0.0722)8

0.0653 (0.0406–0.1152)8

NS

Average percentage glomeruli with ME score 0/1/2/3

T2

100/0/0/0

51/22/16/1014

30/31/15/248

26/33/20/21

####NS for comparison between the FFC groups

SD not included in the analysis since all had score 0

Glomerulus area (µm2)

T2

11,383

(9202–11,602)7

14,907

(13,174–21,771)14

21,839

(18,518–30,269)8

18,262

(16,066–25,095)8

##Group (P < 0.0001):

FFC, FFC-DIA, FFC-DIA + S > SD

  1. GFR: glomerular filtration rate, FFBM: fat-free body mass, KW: kidney weight. T1: Approx. 7 months of diet-feeding, T2: Approx. 13 months of diet feeding. Median and interquartile range (Q1-Q3). Superscript: Actual numbers included in the statistical analysis due to missing data. P-values from post hoc tests were adjusted using Bonferroni correction. ##Non parametric test, ###Two-sided analysis of variance, ####Proc genmod.