OBJECTIVE—Patients with diabetes who manifest proteinuria are at increased risk for cardiovascular events. Some studies suggest that proteinuria exerts its cardiovascular effects at least partly through a positive association with total plasma homocysteine (tHcy). Modestly sized but better designed contrary studies find no such link through a limited range of serum creatinine and proteinuria. We tested the hypothesis that proteinuria independently predicts tHcy levels in a larger cohort of type 2 diabetic patients with nephropathy throughout a much broader range of kidney disease and proteinuria.
RESEARCH DESIGN AND METHODS—Baseline data for the cross-sectional study were obtained from 717 patients enrolled in the multicenter Irbesartan Diabetic Nephropathy Trial. All subjects had type 2 diabetes, hypertension, and proteinuria and were between 29 and 78 years of age. Data included age, sex, BMI, serum creatinine and albumin, LDL and HDL cholesterol, triglyceride, proteinuria and albuminuria, plasma folate, B12, and pyridoxal 5′-phosphate (PLP) (the active form of B6), HbA1c, and tHcy levels. Unadjusted and multivariable models were used in the analysis.
RESULTS—Crude analyses revealed significant associations between tHcy and age (r = 0.074; P = 0.008), creatinine (r = 0.414; P < 0.001), PLP (r = −0.105; P = 0.021), B12 (r = −0.216; P < 0.001), folate (r = −0.241; P < 0.001), and HbA1c (r = −0.119; P = 0.003), with serum albumin approaching significance (r = 0.055; P = 0.072). Only serum creatinine, plasma folate, B12, serum albumin, sex, HbA1c, and age were independent predictors of tHcy after controlling for all other variables.
CONCLUSIONS—By finding no independent correlation between proteinuria (or albuminuria) and tHcy levels, this study improves the external validity of previous negative findings. Therefore, it is unlikely that the observed positive association between proteinuria and cardiovascular disease is directly related to hyperhomocysteinemia.
Patients with type 2 diabetes are at increased risk for cardiovascular morbidity and death compared with nondiabetic subjects (1,2). This risk rises even further in individuals who manifest proteinuria, irrespective of quantity (3–6). In fact, regardless of etiology, proteinuria itself is being increasingly recognized as an independent risk factor for cardiovascular disease (CVD) (7,8), although not all data are in agreement (9–11). Recent studies in diabetic and nondiabetic populations (12–16) have also suggested that proteinuria is positively associated with levels of total plasma homocysteine (tHcy), a sulfur amino acid that is itself an independent risk factor for arteriosclerosis and atherothrombosis (17,18). These results support the hypothesis that proteinuria’s influence on CVD risk (8) may be directly linked, at least in part, to its biological association with hyperhomocysteinemia. In contrast, better designed analyses that controlled for renal function and all other associated risk factors (19–22) not accounted for in the positive studies found no association between proteinuria and tHcy. However, the external validity of these studies is hindered by their modest size (19–22) and restricted and/or nonquantified ranges of proteinuria (19–21) and renal function (21). To help definitively resolve this controversy, we tested the hypothesis that proteinuria independently predicts tHcy levels by analyzing a much larger patient cohort that encompassed broad unrestricted ranges of proteinuria and kidney function. This baseline cross-sectional analysis was performed on a well-established representative cohort of type 2 diabetic patients with nephropathy from the Irbesartan Diabetic Nephropathy Trial (IDNT) (23).
RESEARCH DESIGN AND METHODS
Study patients
A detailed description of the IDNT cohort is found elsewhere (23). In brief, between March 1996 and February 1999, 1,715 individuals aged 29–78 years with documented type 2 diabetes, hypertension, and proteinuria were recruited from over 200 clinical centers in North and South America, Europe, and Asia. All subjects gave written informed consent. The average subject had type 2 diabetes for 15 years. The IDNT cohort was representative of the population with type 2 diabetic nephropathy. Resource limitations restricted this analysis to a convenience sample of 42% (717 subjects) of the original cohort, in whom complete baseline data as well as tHcy levels were available.
Laboratory tests
Baseline samples were drawn between 21 March 1996 and 25 February 1999 and stored at −70°C. tHcy and B vitamins were measured in the Vitamin Metabolism and Aging Laboratory (United States Department of Agriculture Human Nutrition Research Center, Boston, MA). Previous data have shown that plasma tHcy levels remain very stable under these storage conditions (24). Other laboratory examinations were performed in one of four IDNT regional laboratories. tHcy levels were determined by high-performance liquid chromatography with fluorescence detection (25). Plasma pyridoxal 5′-phosphate (PLP) (the active form of B6) levels were measured by radioenzymatic (tyrosine decarboxylase) assay (26), and plasma folate and B12 levels were ascertained by radioassay (Bio-Rad Quantaphase II; Bio-Rad, Hercules, CA). Serum albumin, creatinine, HbA1c, lipid levels, and 24-h urinary protein levels were measured using standard automated clinical chemistry techniques.
Statistical analysis
The skewed outcome variable, tHcy, was logarithmically transformed, as were the independent variables proteinuria (and albuminuria), folate, PLP, and B12, to improve normality. Unadjusted correlations between potential predictor variables were performed using the Pearson correlation matrix. Forward and backward stepwise linear modeling with ANCOVA was then performed to determine the independent association between potential predictor variables (age, sex, BMI, serum creatinine, LDL and HDL cholesterol, triglycerides, urinary protein or albumin excretion, plasma folate, B12, PLP, serum albumin, and HbA1c) and tHcy levels. Two serum creatinine levels were censored before statistical analysis (88 and 483 mg/dl, respectively). Statistical analyses were performed using SYSTAT (Version 9) software.
RESULTS
To ensure that the cohort studied was representative of the larger IDNT cohort, the two groups were compared in Table 1. There were no clinically significant differences between the cohorts with regard to demographic and physical attributes (age, sex, and BMI), major markers of nephropathy (serum creatinine and 24-h proteinuria), and metabolic derangements (total cholesterol and HbA1c).
Descriptive data of the 717 subjects included are presented in Table 2. Subjects were between the ages of 29 and 78 years. The ranges of serum creatinine (0.7–5.5 mg/dl), proteinuria (4 mg to 39 g), and albuminuria (1 mg to 25 g) in this cohort were very wide. B vitamin indexes indicate that a segment of the population was deficient in vitamins B6, B12, and folate. A substantial portion of the cohort had tHcy levels that were elevated above the normal upper limit (i.e., <12 μmol/l). This upper limit applies to populations exposed to folate supplementation of foodstuffs, such as in the U.S. and Canada.
As seen in Table 3, significant unadjusted correlations were found between tHcy and age (r = 0.074; P = 0.008), creatinine (r = 0.414; P < 0.001), PLP (r = −0.105; P = 0.021), B12 (r = −0.216; P < 0.001), folate (r = −0.241; P < 0.001), and HbA1c (r = −0.119; P = 0.003), with serum albumin approaching significance (r = 0.055; P = 0.072). There was no significant univariate correlation between proteinuria or albuminuria and tHcy levels.
Stepwise multiple regression modeling in the 610 subjects with available data that included all the independent variables in Table 2 found that only serum creatinine, plasma folate and B12, serum albumin, sex, HbA1c, and age were independent predictors of tHcy after controlling for other factors (Table 4). Proteinuria (or albuminuria) never became significant with either forward or backward elimination modeling.
CONCLUSIONS
An analysis of a large patient cohort found no association between proteinuria (or albuminuria) and tHcy levels after controlling for all relevant confounding variables. In fact, proteinuria was not significantly associated with tHcy in either the unadjusted or multivariable analyses when using serum creatinine as a marker of renal function. Similar analyses using 24-h creatinine clearance did not change the results (data not shown). The cohort itself comprised a representative sample of type 2 diabetic patients with nephropathy, a population that encompassed a wide range of kidney disease and proteinuria. The results did confirm previously well-documented associations between tHcy and renal function (as measured by serum creatinine), serum albumin, plasma folate and B12, sex, age, and HbA1c.
Previous reports found that albuminuria in patients with type 1 or type 2 diabetes (12–16), and even in individuals without diabetes (13), could predict tHcy levels. However, these studies were limited by numerous significant shortcomings. Ranges of serum creatinine and proteinuria were narrowly and arbitrarily restricted (12–14), sample sizes were often modest (15,16), and of particular importance, statistical analyses failed to control for all known major predictors of tHcy (e.g., renal function, B vitamins, albumin, age, and sex) (13–16). Finally, renal function was assessed by serum creatinine measurements (12–16). Persistently albuminuric patients have, by definition, suffered microvascular damage at the glomerular level (27). Because even early subtle declines in the glomerular filtration rate (GFR) (19,20) can raise tHcy levels, it is important to obtain accurate measurements of renal function when identifying factors that predict tHcy. Although serum creatinine is a simple and inexpensive marker of renal function, it is unfortunately not very good at detecting declines in GFR in early renal failure (28).
In contrast to these findings, other analyses performed in diabetic (20,21) and nondiabetic subjects (19,22) found no association between proteinuria and tHcy levels after controlling for all major confounding factors. Furthermore, most of these studies determined GFR by highly accurate clearance methods (19,20,22). However, external validity was compromised by their modest sample sizes and limited ranges of proteinuria (19–21) and renal function (21) measured. Of note, our analysis studied a much larger patient cohort that includes far broader ranges of serum creatinine and proteinuria. Furthermore, the study subjects were all enrolled in the well-designed multicenter IDNT cohort and were representative of the high-cardiovascular risk population of type 2 diabetic patients with nephropathy. These facts extend and improve the external validity of the previous negative studies (19–22). Therefore, it is unlikely that the positive association between proteinuria and cardiovascular events (3–6) is related to hyperhomocysteinemia.
The associations with tHcy found in this analysis have, in general, been well documented in the literature. Serum creatinine has traditionally been one of the major, if not primary, determinants of tHcy levels in populations with and without renal failure (29,30). This is related to its role as a renal function marker as well as its link to homocysteine production through creatine-creatinine synthesis via one-carbon metabolism (31). tHcy levels have been conclusively shown to be inversely proportional to GFR (19,20,22). Whether tHcy levels rise because the kidney itself is progressively unable to clear and metabolize homocysteine or whether accumulating uremic factors interfere with normal extrarenal homocysteine metabolism is not presently known (31).
By facilitating the normal metabolism of homocysteine, folate and vitamin B12 have been shown as two of the more important predictors of tHcy levels (32,33). The relatively low folate levels seen in some subjects is consistent with the fact that baseline measurements were performed in many individuals not exposed to folate supplementation of foodstuffs, as is currently done in the U.S. and Canada.
As a major plasma binder of tHcy, serum albumin is also a known determinant of tHcy (32). Advancing age is associated with increasing tHcy levels (32), possibly because of such factors as declining renal function, lower B vitamin status, or a higher prevalence of hypothyroidism (34).
For unclear reasons, women had slightly higher mean tHcy levels than men after controlling for other variables (men 13.7 μmol/l, women 14.4 μmol/l; P = 0.03). Differences in tHcy levels between men and women have previously been noted. One study of healthy subjects found that men had higher tHcy levels than women, presumably because homocysteine is linked to creatine/creatinine synthesis, which is typically greater in men (32). Another study in subjects with type 2 diabetes found tHcy levels to be higher in women who were postmenopausal and/or after a methionine load (21).
This study found that HbA1c is inversely predictive of tHcy levels, although previous investigations have reached conflicting results with regard to glycemic markers in patients with diabetes. Some investigations have found that these markers are positively correlated with tHcy levels (35,36), others have found a negative correlation (37), and still others have found no significant relationship (15,38). The cause of the inverse relationship found here is not obvious. It is conceivable that as the complications of diabetes, such as nephropathy, manifest themselves to the patient and health care practitioner, greater attempts at glycemic control are made.
Finally, proteinuria has been found to be independently predictive of cardiovascular outcomes in a number of retrospective and prospective studies (4,7,8). Preliminary studies suggest that measuring the true GFR using highly accurate filtration markers may help to further stratify CVD risk among individuals with albuminuria (9–11).
Characteristics . | Study cohort . | Complete IDNT cohort* . |
---|---|---|
Age (years) | 58.0 ± 8.0 | 58.9 ± 8.0 |
Male sex (%) | 65.5 | 66.8 |
BMI (kg/m2) | 31.9 ± 6.6 | 31.0 ± 7.0 |
Creatinine (mg/dl) | 1.7 ± 0.6 | 1.7 ± 0.6 |
24-h proteinuria (g) | 4.35 ± 3.8 | 4.02 ± 3.5 |
Total cholesterol (mg/dl) | 229 ± 81 | 229 ± 58 |
HbA1c (%) | 7.7 ± 1.7 | 8.1 ± 1.7 |
Characteristics . | Study cohort . | Complete IDNT cohort* . |
---|---|---|
Age (years) | 58.0 ± 8.0 | 58.9 ± 8.0 |
Male sex (%) | 65.5 | 66.8 |
BMI (kg/m2) | 31.9 ± 6.6 | 31.0 ± 7.0 |
Creatinine (mg/dl) | 1.7 ± 0.6 | 1.7 ± 0.6 |
24-h proteinuria (g) | 4.35 ± 3.8 | 4.02 ± 3.5 |
Total cholesterol (mg/dl) | 229 ± 81 | 229 ± 58 |
HbA1c (%) | 7.7 ± 1.7 | 8.1 ± 1.7 |
Data are % or means ± SD.
From Rodby et al.: The Irbesartan Type II Diabetic Nephropathy Trial: Study design and baseline patient characteristics. Nephrol Dialysis Transplant 15:487–497, 2000.
Variable . | . |
---|---|
Age (years) | 58.0 ± 8.0 (29–78) |
Male sex (%) | 468 ± 65.5 |
BMI (kg/m2) | 31.9 ± 6.6 (16–62) |
Creatinine (mg/dl) | 1.7 ± 0.6 (0.7–5.5) |
LDL cholesterol (mg/dl) | 138 ± 49 |
HDL cholesterol (mg/dl) | 46.6 ± 108 |
Triglycerides (mg/dl) | 227 ± 196 |
Urinary protein excretion (g/24 h) | 3.12 (1.74–5.72) |
Range | 0.004–39.0 |
Urinary albumin excretion (g/24 h) | 1.87 (1.09–4.15) |
Range | 0.001–24.75 |
PLP (nmol/ml) | 24.9 (14.1–42.0) |
B12 (pg/ml) | 478 (359–619) |
Folate (ng/ml) | 5.7 (3.91–7.99) |
Albumin (mg/dl) | 3.7 ± 0.5 |
HbA1c (%) | 7.7 ± 1.7 |
tHcy (μmol/l) | 14.0 (11.1–17.4) |
Variable . | . |
---|---|
Age (years) | 58.0 ± 8.0 (29–78) |
Male sex (%) | 468 ± 65.5 |
BMI (kg/m2) | 31.9 ± 6.6 (16–62) |
Creatinine (mg/dl) | 1.7 ± 0.6 (0.7–5.5) |
LDL cholesterol (mg/dl) | 138 ± 49 |
HDL cholesterol (mg/dl) | 46.6 ± 108 |
Triglycerides (mg/dl) | 227 ± 196 |
Urinary protein excretion (g/24 h) | 3.12 (1.74–5.72) |
Range | 0.004–39.0 |
Urinary albumin excretion (g/24 h) | 1.87 (1.09–4.15) |
Range | 0.001–24.75 |
PLP (nmol/ml) | 24.9 (14.1–42.0) |
B12 (pg/ml) | 478 (359–619) |
Folate (ng/ml) | 5.7 (3.91–7.99) |
Albumin (mg/dl) | 3.7 ± 0.5 |
HbA1c (%) | 7.7 ± 1.7 |
tHcy (μmol/l) | 14.0 (11.1–17.4) |
Data are means ± SD, means ± SD (range), or geometric means (25th to 75th percentile), unless otherwise stated.
Variable . | P . | r . |
---|---|---|
Age | 0.008 | 0.074 |
Sex | 0.506 | 0.007 |
BMI | −0.118 | 0.017 |
Creatinine | <0.001 | 0.414 |
LDL cholesterol | 0.176 | −0.057 |
HDL cholesterol | 0.085 | −0.028 |
Triglycerides | 0.927 | −0.018 |
Urinary albumin excretion* | 0.989 | −0.000 |
Urinary protein excretion* | 0.581 | −0.013 |
PLP* | 0.021 | −0.105 |
B12* | <0.001 | −0.216 |
Folate* | <0.001 | −0.241 |
Albumin | 0.072 | 0.055 |
HbA1c | 0.003 | −0.119 |
Variable . | P . | r . |
---|---|---|
Age | 0.008 | 0.074 |
Sex | 0.506 | 0.007 |
BMI | −0.118 | 0.017 |
Creatinine | <0.001 | 0.414 |
LDL cholesterol | 0.176 | −0.057 |
HDL cholesterol | 0.085 | −0.028 |
Triglycerides | 0.927 | −0.018 |
Urinary albumin excretion* | 0.989 | −0.000 |
Urinary protein excretion* | 0.581 | −0.013 |
PLP* | 0.021 | −0.105 |
B12* | <0.001 | −0.216 |
Folate* | <0.001 | −0.241 |
Albumin | 0.072 | 0.055 |
HbA1c | 0.003 | −0.119 |
tHcy was logarithmically transformed.
Variable* . | β Coefficient . | P (95% CI) . |
---|---|---|
Creatinine | 0.279 | <0.001 (0.24 to 0.317) |
Folate | −0.141 | <0.001 (−0.180 to −0.102) |
B12 | −0.139 | <0.001 (−0.189 to −0.090) |
Albumin | 0.121 | <0.001 (0.073 to 0.168) |
Sex | 0.050 | 0.037 (0.003 to 0.097) |
HbA1c | −0.018 | 0.006 (−0.031 to −0.005) |
Age | 0.004 | 0.013 (0.001 to 0.006) |
Variable* . | β Coefficient . | P (95% CI) . |
---|---|---|
Creatinine | 0.279 | <0.001 (0.24 to 0.317) |
Folate | −0.141 | <0.001 (−0.180 to −0.102) |
B12 | −0.139 | <0.001 (−0.189 to −0.090) |
Albumin | 0.121 | <0.001 (0.073 to 0.168) |
Sex | 0.050 | 0.037 (0.003 to 0.097) |
HbA1c | −0.018 | 0.006 (−0.031 to −0.005) |
Age | 0.004 | 0.013 (0.001 to 0.006) |
Adjusted R2 = 0.313.
B12, folate, and tHcy were logarithmically transformed
Article Information
The main funding for this research effort was provided by RO1 HL 67695-02, awarded to A.G.B. Support was also provided by the U.S. Department of Agriculture, under agreement 581950-9-001. The IDNT was supported by grants from Bristol-Myers Squibb and Sanofi-Synthelabo.
The authors wish to thank Marie Nadeau for her invaluable laboratory assistance.
References
Address correspondence and reprint requests to Allon N. Friedman, MD, Vitamin Metabolism and Aging, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington St., Rm. 829, Boston, MA 02111. E-mail: [email protected].
Received for publication 10 April 2002 and accepted in revised form 31 July 2002.
Any opinions, findings, conclusions, or recommendations expressed in this article are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.