Cholesterol: A Renal Risk Factor in Diabetic Nephropathy

Cholesterol: A Renal Risk Factor in Diabetic Nephropathy? Henrik Mulee, MD, Svend Aage Johnsen, MD, aile Wiklund, MD, and Staff an BjOrek, MD • In a prospective follow-up of 30 patients with type 1 diabetes and nephropathy, serum cholesterol, triglycerides, apolipoprotein AI and B, and lipoprotein(a) were determined to study their relationship to the rate of decline in glomerular filtration rate. The patients had proteinuria and advanced nephropathy with a mean ± SO glomerular filtration rate of 39 mL/min/1.73 m 2 • The decline in glomerular filtration rate was determined during 2.5 ± 0.5 years. High serum cholesterol, triglycerides, and apolipoprotein B were correlated to a more rapid deterioration in kidney function. The rate of decline in glomerular filtration rate was 1.0 ± 2.5 mL/min/yr in the 10 patients with the lowest cholesterol level, compared with 4.5 ± 3.2 mL/min/yr in the patients with the highest serum cholesterol (P = 0.015). The combined effect of the measured lipids, blood pressure, type of antihypertensive treatment, protein intake, proteinuria, and hemoglobin A,c on the rate of decline in glomerular filtration rate was assessed by multiple regression analysis. The measured factors together had a high explanatory power for the rate of decline in glomerular filtration rate. In this model, 73% of the variation in decline in glomerular filtration rate was explained by the measured variables (multiple r2 = 0.73). Low cholesterol and treatment with an angiotensin-converting enzyme inhibitor were the strongest predictors of a favorable renal prognosis. This suggests that hypercholesterolemia is an important risk factor for diabetic nephropathy. © 1993 by the National Kidney Foundation, Inc. INDEX WORDS: Diuabetes; diabetic nephropathy; lipids; cholesterol; apolipoproteins; angiotensin-converting enzyme inhibition.

M

ORTALITY in diabetic patients with nephropathy has decreased dramatically during the last few years I and the decline in kidney function that previously was regarded as inevitable can be arrested in many patients.2 However, some patients will still lose kidney function rapidly despite satisfactory control of the known risk factors. Other mechanisms that lead to destruction of kidney function, therefore, have to be sought. Experimental results indicate that hyperlipidemia can accelerate the loss of renal function in renal diseases. 3-5 Similarities may exist between the process that leads to destruction of glomerular structures and atherosclerosis. 6 .7 Furthermore, a synergistic harmful renal effect in renal diseases of hypertension and high cholesterol has been suggested. 8 - 11 As the relevance of these animal data in humans is unknown, we studied the relationship between hyperlipidemia and the deFrom the Department of Nephrology and the Wallenberg Laboratory for Cardiovascular Research. Sahlgrenska Hospital. University of Goteborg. Sweden; and the Departments of Nephrology. Northern Alvsborgs and Bords Hospitals. Sweden. Received November 4. 1992; accepted in revised form January 4. 1993. Supported by grants from the Swedish Medical Research Council (projects 4531 and 05230). the Swedish Heart and Lung Foundation. andthe Ericsson Medical Research Fund. Address reprint requests to Staffan Bjorck. MD. Department of Nephrology. Sahlgrenska Hospital. S-413 45 Goteborg. Sweden. © 1993 by the National Kidney Foundation. Inc. 0272-6386/93/2201-0028$3.00/0 196

cline in glomerular filtration rate in a population of patients with type 1 diabetes and nephropathy. PATIENTS AND METHODS

Patients The glomerular filtration rate was prospectively studied in 30 patients with type I diabetes and nephropathy during 2.5 years (range, 1.5 to 3.0 years). They had type I diabetes, diabetic nephropathy, reduced renal function, and other diabetic complications such as retinopathy. The patients had a mean age of 44 years (range, 23 to 59 years) and mean age of onset of diabetes of 17 years (3 to 38 years). The mean duration of diabetes was 28 years (range, 16 to 46 years). All patients had retinopathy and three patients were blind. The onset and development of the kidney disease were typical of diabetic nephropathy in all patients. All patients were on antihypertensive treatment and at the start of the prospective monitoring of renal function they were randomized to angiotensin-converting enzyme inhibitor or beta-blocker treatment. Seventeen patients were given enalapril and 13 were given metoprolol. The effect of the antihypertensive treatment on kidney function has been previously reported. 2 The study was performed after obtaining the patients' informed consent and approval by the local ethical committee.

Methods We measured blood pressure, urinary albumin excretion, serum electrolytes, hemoglobin, and hemoglobinAlc at baseline and at 2-month intervals, and urinary nitrogen and glomerular filtration rate at 6-month intervals. The glomerular filtration rate was measured as the rate of disappearance of chromium-51 edetic acid in plasma after a single injection. Albumin excretion was measured in 24-hour urine samples by immunochemical turbidimetric assay, electrophoresis, or immunoprecipitation assay, depending on the routine of hospitals. Dietary protein intake was calculated from urinary nitrogen excretion. 12

American Journal of Kidney Diseases, Vol 22, No 1 (July), 1993: pp 196-201

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CHOLESTEROL IN DIABETIC NEPHROPATHY

Lipid Determinations At baseline and at 6-month intervals, nonfasting serum samples were analyzed for cholesterol and triglycerides using fully enzymatic methods. These values are listed in the Results section. For further analysis of the lipid profile, fasting samples were obtained on one occasion in all patients for analysis of apolipoprotein AI (ApoAI), apolipoprotein B (ApoB), and lipoprotein(a) (Lp(a)). Apolipoproteins AI and B were determined with immunoturbidometric methods (UniKit LaRoche, catalog nos. 07 2995 7 and 07 2994 9, Hoffmann LaRoche, Basel, Switzerland) in a Cobas Fara Autoanalyser (Hoffmann LaRoche); between assay variations were 4.4% and 3.4% respectively. For the determination ofLp(a) a radioimmunoassay was used (catalog no. 10-6497-01, Pharmacia Diagnostics AB, Uppsala, Sweden). Reference values for serum cholesterol, triglycerides, apo AI, and apo B were obtained from the Goteborg sample of the MONICA study.13 A value of Lp(a) above 200 mgjL was considered elevated (population data not available).

Statistics Results are presented as means ± SD. Due to their skewed distribution, urinary albumin excretion, cholesterol, triglycerides, and Lp(a) are given as geometric means (anti-log 95% confidence interval of the logarithms). In Tables I to 4, the results obtained during the observation period are summarized by one mean value for each patient; these values are used to calculate the means and geometric means. However, ApoAI, ApoB, and Lp(a) were only measured once in each patient. Serum cholesterol determined at this occasion showed a strong correlation (r = 0.8) to the average cholesterol level. The rate of deterioration of renal function was analyzed by regression lines for chromium-51 edetic acid clearance over time, determined for each patient over the whole period for that patient. One- and two-factor analysis of variance was used for comparisons between groups and P < 0.05 was considered significant. Data were analyzed after logarithmic transformation of urinary albumin excretion, serum cholesterol, triglycerides, ApoAI, ApoB, and Lp(a). Forward stepwise linear regression analysis was carried out to assess the influence of possible explanatory variables on the rate of decline in glomerular filtration rate. Statistical software was Statview SE-Graphics (Abacus Concepts Inc, Berkeley CA).

RESULTS

The clinical data and results of the serum analyses for the patients are given in Table 1. Fourteen patients had serum cholesterol and 12 patients had serum triglycerides above the 90th percentile of the population for their age group. Eighteen patients had elevated Lp(a). It was recently shown that angiotensin-converting enzyme inhibitor treatment can reduce proteinuria and the rate of the deterioration of glomerular filtration rate in diabetic nephropathy.2 The differ-

Table 1. Clinical Data and Laboratory Results During the Observation Period for 30 Patients with Diabetic Nephropathy

Female/male Age (yr) Duration of diabetes (yr) GFR (mL/min) Hemoglobin Ale (%) Cholesterol (mmol/L) Triglycerides (mmol/L) ApoAI (g/L) ApoB (g/L) Lp(a) (mg/L) Change in GFR (mL/min/yr) Albuminuria (g/24 hr) Serum albumin (g/L) Protein intake (g/24 hr) Blood pressure (mm Hg)

18/12 45.3 ± 9.1 SO 29 ± 8.0 SO 39 ± 14 SO 8.8 ± 1.7 SO 6.8 (6.3-7.4) 2.0 (1.7-2.5) 1.9 ± 0.3 SO 1.8 ± 0.5 SO 180 (109-295) -2.8 ± 3.0 SO 0.8 (0.5-1.2) 38.6 ± 4 SO 1.0 ± 0.3 SO 138/84 ± 11/5 SO

Note. Each patient is summarized by one mean value. These values are used to calculate the means and geometric means. Abbreviation: GFR, glomerular filtration rate.

ences in the results presented in Table 1 between angiotensin-converting enzyme inhibitor- and non-angiotensin-converting enzyme inhibitortreated patients were rate of decline in glomerular filtration rate -1.6 ± 1.9 mL/min/yr versus -4.3 ± 3.5 mL/min/yr (P = 0.01), serum triglycerides 1.6 mmoljL (1.2 to 2.2) versus 3.4 mmoljL (2.4 to 4.9) (P = 0.001), and albuminuria 0.5 g/24 hr (0.3 to 0.9) versus 1.4 g/24 hr (0.9 to 2.1) (P = 0.007), respectively. The differences in albuminuria and triglyceride levels are not due to differences before allocation to the two treatments since there were no differences before randomization. The serum triglyceride level was 1.8 mmoljL (1.3 to 2.4) in the angiotensin-converting enzyme inhibitor-treated patients and 2.0 mmolj L (1.5 to 2.5) in the beta-blocker-treated patients; urinary albumin excretion was 1.5 g/24 hr (0.9 to 2.5) and 1.4 g/24 hr (0.8 to 2.4), respectively. The rate of decline in glomerular filtration rate was negatively correlated to serum cholesterol, triglycerides, and ApoB and positively correlated to ApoAI. Coefficients are given in Table 2. Mean arterial blood pressure, hemoglobin Ale, and protein intake were not correlated to the decline in glomerular filtration rate. The relative importance of the different variables listed in Table 1 for the decline in glomerular filtration rate, assessed by stepwise regression

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Table 2. Correlations Between Explanatory Variables and the Rate of Change in Glomerular Filtration Rate in 30 Patients With Diabetic Nephropathy

Variable

Cholesterol Triglycerides (0.81) Albuminuria (0.23) ApoS (0.78) Lp(a) (0.1) HemogiobinA1 (0.24) Mean arterial pressure (0.51) Protein intake (- 0.3) ApoAI (-0.34)

(n

~

30)

-0.61' -0.48' -0.12 -0.39t - 0.11 -0.26 - 0.29 0.28 0.43t

Note. The correlations between cholesterol and the other variables are given in parentheses. 'P < 0.01 . t P < 0.05.

analysis, is shown in Table 3. When all variables are entered into the equation, the multiple correlation coefficicent is 0.86. With this model, the variation in the rate of decline in glomerular filtration rate is 73% determined by the variables used (multiple? = 0.73). The highest significances are found for angiotensin-converting and non-angiotensin-converting enzyme inhibitor treatment and serum cholesterol level (P :=:;; 0.002). Since the rate of decline in glomerular filtration rate is best predicted by the cholesterol level, the patients have been divided into three equal groups according to cholesterol level (Table 4). Diastolic blood pressure differed between these groups. The rate of decline in glomerular filtration rate differed significantly between the three groups and increased in proportion to serum cholesterol. The strongest explanatory factors for the decline in glomerular filtration rate were serum cholesterol and type of treatment (angiotensinconverting enzyme inhibitors v beta-blockade). The relationship between these two variables is shown in Fig I. The patients in the enalapril and the metoprolol group are divided into three groups, as equal in size as possible, depending on cholesterol. These two factors (type of treatment and cholesterol) are both independently correlated to the decline in glomerular filtration rate (P < 0.03 and P < 0.009, respectively; two-factor analysis of variance).

DISCUSSION

Hypertension is the most important factor known that accelerates the progressive decline in kidney function in diabetic nephropathy. 1 Careful attention to, and good control of, the blood pressure in most of our patients gives an opportunity to assess the importance of other risk factors by minimizing the influence of blood pressure. The progression of diabetic nephropathy is a multifactorial process. The interrelationship between many risk factors confounds any attempt to assess the importance of individual risk factors, but the strong association between cholesterol level and the decrease in glomerular filtration rate in our patients supports the hypothesis of a nephrotoxic effect of hypercholesterolemia in renal disease in humans. Lipid abnormalities secondary to proteinuria, reduced renal function, or dietary intake have been pointed out as one of the possible mediators in the progression of initial glomerular injury to glomerulosclerosis. 3 Glomerulosclerosis and atherosclerosis share several features, as recently reviewed. 14 Similarity to atherosclerosis is also suggested by the association between ApoAI and rate of progression. The specific lipid fraction responsible for progressive nephron destruction has not been identified. Kasiske et al 8 suggest that alterations in serum cholesterol may be more closely associated with glomerular injury than alterations in serum triglycerides, which is in agreement with our findings. The serum triglyceride level was clearly elevated in patients treated with metoprolol, whereas Table 3. Result of Forward Stepwise Multiple Regression Analysis of Different Variables on the Rate of Decline in Glomerular Filtration Rate in 30 Patients With Diabetic Nephropathy

Variable

F Value to Enter

p

Cholesterol Enalapril/metoprolol treatment

14.4 6.1

<0.001 <0.01

Note. The stepwise procedure selects the best subset of predictor variables and stops adding variables when the contribution to the result is small. Two variables were selected. The variables not in the equation and their F values are ApoA, 2.5; albuminuria, 1.8; hemogiabinA1, 1.7; triglycerides, 1.6; ApoS, 0.9; mean arterial blood pressure, 0.05; Lp(a), 0.3; and protein intake, 0.03.

199

CHOLESTEROL IN DIABETIC NEPHROPATHY Table 4. Clinical and Laboratory Characteristics in 30 Patients With Diabetic Nephropathy Divided Into Three Groups According to Their Serum Cholesterol Value Cholesterol Level (mmoIfL)

No. of patients ACE inhibitor treatment Male/Female HemogiobinA 1 (%) Blood pressure GFR (mL/min) ~GFR (mL/min/yr) Protein intake (g/kg/d) Albuminuria (g/24 hr)

<6.0

6.0-7.7

>7.7

p'

10 6 4/6 8.1 ± 1.3 134/80 ± 9/6 44.8 ± 10.3 -0.9 ± 1.9 1.2 ± 0.3 0.6 ± 0.3-1.1

10 7 5/5 9.4±1.8 138/86 ± 11/4 33 ± 12.8 -2.9 ± 3.0 1.0 ± 0.3 0.8 ± 0.3-1.8

10 4 9/1 9.0 ± 2.0 143/85 ± 11/5 40.9 ± 16.8 -4.5 ± 3.2 1.0 ± 0.4 1.1 ± 0.5-2.3

0.41 0.05 0.27 0.20/0.023 0.16 0.027 0.21 0.45

Abbreviations: ACE, angiotensin-converting enzyme; GFR, glomerular filtration rate; ~GFR, change in GFR. * Probability value for between-group differences were analyzed with one factor analysis of variance. The significances are underscored.

it was only moderately increased in those treated with enalapril. This is not explained by such factors as degree of renal failure, metabolic control, and proteinuria. A higher serum triglyceride level during treatment with beta-blockers has been shown in several studies. 15 Our patients had high cholesterol, triglyceride, and ApoB levels. This can be partly explained by poor metabolic control of the diabetes. Hemoglobin A IC was 9.1 % ± 2.7%, which is similar to what is usually described in this type of patient. I

r-

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ell

7'

~

III

~


~

:;/

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ell

~

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()

rJ

7 6

5 4

3

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Fig 1. Relationship between the rate of decline in glomerular filtration rate, enalapril/metoprolol treatment, and cholesterol level. Metoprolol- and enalapril-treated patients are both divided into three categories depending on cholesterol level.

Most of our patients were treated with four daily injections of insulin, adjusted after self-measurement of blood glucose. However, the impact of metabolic control on lipids is relatively small. In a recent study, a 1% decrease in hemoglobin A lc was associated with a decrease in total cholesterol of only 0.17 mmol/L and a decrease in triglycerides of 0.13 mmol/L. 16 Proteinuria appears to be more important. Even with proteinuria within the microalbuminuric range, an atherogenic lipid profile is present, 17-19 and it is further exaggerated in the presence of increasing proteinuria and decreasing renal function. 20 Lipoprotein(a), considered to be an independent risk factor for ischemic heart disease,21 was elevated in 18 of the 30 patients, in agreement with findings in microalbuminuric patients. 22 There was no correlation between Lp(a) and rate of decline in glomerular filtration rate. The interrelationship between risk factors is shown in Table 4. When the patients are grouped according to cholesterol level, the rate of decline in glomerular filtration rate increases linearly between the groups. However, there is a significant difference in blood pressure between the groups. When further analyzed by multiple regression analysis, serum cholesterol and type of antihypertensive treatment are found to be the most important explanatory variables for the variation in the rate of decline in glomerular filtration rate. In our analysis of the present data we found a clear-cut difference between the effect of the two main factors (angiotensin-converting enzyme in-

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200

hibitor treatment and cholesterol level) and the remaining variables (Table 3) on the rate of decline in glomerular filtration rate. It could be speculated that lipid nephrotoxicity is enhanced by an increased passage of macromolecules, including lipids, into the mesangial area and that reduction of this traffic by angiotensin-converting enzyme inhibitor treatment could be one explanation for the beneficial renal effect of angiotensin-converting enzyme inhibition. A reduction in cholesterol secondary to a reduction in proteinuria could therefore further enhance this effect. 2,23 This view is supported by the biphasic anti protein uric response to angiotensin-converting enzyme inhibitors. There is a decrease in proteinuria within weeks and a continued progressive decline in proteinuria over up to 3 years.2 Experimental studies have shown that hyperlipidemia may interact with hypertension and pre-existing renal damage to increase the glomerular damage dramatically. 3-5,8-11 Dietary protein intake was the same in the three groups and does not correlate with the decline in glomerular filtration rate. Interestingly, in a recent study showing a beneficial renal effect of dietary protein restriction, low-density lipoprotein cholesterol was reduced by 21%.24 In glomerular diseases, progression to renal failure is rare in the absence of proteinuria and interventions designed to reduce proteinuria seem to have a beneficial effect on progression of chronic renal disease,z5 Therefore, reactive mechanisms triggered by an increased protein traffic across the glomerular capillary have been suggested to be a key factor in the development of glomerulosclerosis. 26 However, our data indicate that hypercholesterolemia, which is linked to proteinuria, is the important factor contributing to glomerular injury. Thus, serum cholesterol might be one of the major risk factors in the multifactorial process of progression of renal failure in patients with diabetic nephropathy. If the importance of cholesterol is established by prospective studies aiming at normalization of cholesterol, this introduces the possibility of arresting the progression in many patients, considering the greatly improved prognosis that has already been achieved in this group of patients. 1,2

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2. Bjiirck S, Mulec H, Johnsen SA, Norden G, Aurell M: Renal protective effect of enalapril in diabetic nephropathy. Br Med J 304:339-343, 1992 3. Moorhead JF, Chang MK, El-Nahas M, Varghese Z: Lipid nephrotoxicity in chronic progressive glomerular and tubulointerstitial disease. Lancet 1:1309-1311, 1982 4. Moorhead JF: Lipids and progressive kidney disease. Kidney Int 39:35-40, 1991 (suppl 31) 5. Keane WF, Mulcahy S, Kasiske BL, Youngki K, O'Donnell MP: Hyperlipidemia and progressive renal disease. Kidney Int 39:41-48,1991 (suppl 31) 6. EI Nahas AM: Glomerulosclerosis: A form of atherosclerosis. Proceedings of the Xth International Congress of Nephrology 2: 1206-1220, 1987 7. Diamond JR, Karnovsky MJ: Focal and segmental glomerulosclerosis: Analogies to atherosclerosis. Kidney Int 33: 917-924,1988 8. Kasiske BL, 0 Donnell MP, Cowardin W, Keane WF: Lipids and the kidney. Hypertension 15:443-450, 1990 9. Kasiske BL, O'Donell MP, Garvis WJ, Keane WF: Pharmacologic treatment of hyperlipidemia reduces glomerular injury in rat 5/6 nephrectomy model of chronic renal failure. Circulation Res 62:367-374, 1988 10. Kasiske BL, 0 Donell MP, Schmitz PG, Kim Y, Keane WF: Renal injury of diet-induced hypercholesterolemia in rats. Kidney Int 37:880-891, 1990 11. Kasiske BL, O'Donell MP, Clearly MP, Keane WF: Effects of reduced renal mass on the tissue lipids and renal injury in hyperlipidemic rats. Kidney Int 35:40-47, 1989 12. Nyberg G, Norden G, Attman PO, Aurell M, Uddebom G, Arvidsson R, Isaksson B: Diabetic nephropathy: Is dietary protein harmful? J Diabet Complications 1:37-40, 1987 13. Keil U, Kuulasma K: WHO MONICA Project: Risk factors. Int J Epidemiol 18:S46-S65, 1989 (suppl 1) 14. Diamond JR: Analogous pathobiologic mechanism in glomerulosclerosis and atherosclerosis. Kidney Int 39:S-29-S34,1991 (suppI31) 15. Weinberger MH: Antihypertensive therapy and lipids. Paradoxical influence on cardiovascular disease risk. Am J Med 80:64-70, 1986 (suppl 2A) 16. Semenkovich CF, Ostlund RE, Schechtman KB: Plasma lipids in patients with type I diabetes mellitus: Influence of race, gender and plasma glucose control in black women. Arch Intern Med 149:51-56, 1989 17. Jensen T, Stender S, Deckert T: Abnormalities in plasma concentration of lipoproteins and fibrinogen in type 1 (insulin-dependent) diabetic patients with increased urinary albumin excretion. Diabetologia 31:142-145, 1988 18. Vannini P, Ciavarella A, Flammini M, Bargossi AM, Forlani G, Borgnino LC, Orsoni G: Lipid abnormalities in insulin-dependent diabetic patients with albuminuria. Diabetes Care 7:151-154, 1984 19. Jones SL, Close CF, Mattock MB, Jarrett RJ, Keen H, Viberti GC: Plasma lipid and coagulation factor concentrations in insulin dependent diabetics with microalbuminuria. Br Med J 298:487-490, 1989 20. Attman P-O, Nyberg G, William-Olsson T, KnightGibson C, Alaupovic P: Lipid and apolipoprotein profile in diabetic chronic renal failure. Abstracts of the 17th Congress of the EDTA, Wienna, Austria, 1990, p 71 (abstr)

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21. Scanu AM: Update on lipoprotein(a). Curr Opin Lipidol 2:253-258, 1991 22. Kapelrud H, Bangstad H-J, Dahl-Jorgensen K, Berg K, Hansen KF: Serum Lp(a) lipoprotein concentrations in insulin dependent diabetic patients with microalbuminuria. Br Med J 303:675-678, 1991 23. Keilani T, Schlueter W, Levin M, Battle DC: Reduction of serum total cholesterol and proteinuria with fosinopril, a new converting enzyme inhibitor. J Am Soc Nephrol 2:231, 1991 (abstr)

201 24. Walker JD, Bending J), Dodds RA, Mattock MB, Murrells TJ, Keen H, Viberti GC: Restriction of dietary protein and progression of renal failure in diabetic nephropathy. Lancet 86771:1411-1415,1989 25. Bjorck S, Mulec H, Johnsen SA, Nyberg G, Aurell M: Contrasting effects of enalapri1 and metoprolol on proteinuria in diabetic nephropathy. Br Med J 300:904-907, 1990 26. Remuzzi G, Bertani T: Editorial review: Is glomerulosclerosis a consequence of altered glomerular permeability to macromolecules? Kidney Int 38:384-394, 1989