Sex difference in the risk for exercise-induced albuminuria correlates with hemoglobin A1C and abnormal exercise ECG test findings

Diabetic nephropathy (DN) is the leading cause of renal disease in adults [1] and is characterized by two distinct biomarkers; estimated glomerular filtration rate (eGFR) and urinary albumin excretion (often assessed as albumin to creatinine ratio (UACR) ≥30 mg/g in a urine spot test). These two biomarkers provide the basis for the kidney disease: improving global outcomes (KDIGO) chronic kidney disease (CKD) classification [2]. DN, is associated with a significant increase in mortality, and has been identified as a leading cause of excess risk of death in patients with diabetes [3]. Nevertheless and despite clear screening recommendations the number of patients with under diagnosed DN remains substantially high [4].

Several studies have shown that exercise unmasks albuminuria in normo-albuminuric diabetic individuals (exercise induced albuminuria—EiA, measured as spot UACR before and after exercise), suggesting this as the earliest sign of DN [5, 6]. Exercise leads to albuminuria by both modulating glomerular passage and tubular reuptake of albumin [7, 8]. We have recently published a study showing that EiA is independently correlated with a higher prevalence of metabolic syndrome in non-diabetic individuals, however the association among diabetic and pre-diabetic patients in a sex related perspective has never been studied [9].

Clear sex related differences have been identified in cardiovascular disease (CVD) [10, 11]. The clinical presentation of ischemic heart disease in women is very different from the classical presentation described in men and is therefore under diagnosed [12, 13]. This may result from pathophysiologic differences with a greater contribution of microvascular myocardial damage to disease progression in women [14, 15]. Recent studies have demonstrated sex differences in renal damage among healthy and diabetic individuals [16]. In non-diabetic individuals with chronic kidney disease, male sex has been identified as a risk factor for rapid decline in renal function as opposed to pre-menopausal women [17]. In diabetic individuals conflicting reports exist in different populations; a recent study among Japanese subjects with type 2 diabetes identified a higher risk in women [18], whereas a report regarding European individuals indicated an increased risk for renal decline in men [19]. Thus, the influence of sex on the development of DN has yet to be established conclusively [16, 20–23].

We, therefore, sought to investigate the association between EiA, sex, metabolic and physiologic parameters in a large cohort of individuals (both healthy, pre-diabetic and diabetic) who participated in the Tel-Aviv Medical Center Inflammation Survey.

3029 participants were included in the analysis. Participant characteristics are shown in Table 1. For the entire cohort, urinary albumin concentrations were elevated after exercise; the median urinary albumin concentration before and after exercise were 3 mg/l (IQR; 0.8–7.8) and 5 (IQR; 1.5–15.5) mg/l respectively (p < 0.001). The change in urinary albumin concentrations was 1.3 (−0.7 to 8.6) mg/l for median (IQR). UACR values before and after exercise were 3.3 (1.4–7.8) and 7.5 (2.6–22.3) mg/g for median (IQR) respectively (p < 0.001). The exercise induced change in UACR (ΔEiA) was 2.8 (0–13.6) mg/g for median (IQR). To rule out the possibility of an increase in EiA due to dehydration, urine specific gravity was analyzed before and after exercise. No significant difference was demonstrated between before and after exercise values (1.0076 and 1.004 respectively, p value = 0.184). Furthermore, no significant correlation with albumin concentrations or exercise induced change in albumin was noted (r = 0.024 and 0.022, p value >0.2 for both).

A very weak positive correlation between A1C and baseline UACR was found for the entire cohort (r = 0.083, p < 0.001). This correlation increased slightly when albumin concentration was measured following exercise (r = 0.107, p value <0.001).

A one-way ANOVA test demonstrated significant difference in ΔEiA with accumulating parameters of the metabolic syndrome; mean ΔEiA = 9.5 ± 1.4, 13.5 ± 1.7, 17.3 ± 2.9, 37.6 ± 7.7, 55.1 ± 14 (mg/g) (±SE) for patients with 0, 1, 2, 3, 4 or more metabolic syndrome components respectively, p < 0.001. This analysis was repeated, excluding patients with one of the four different metabolic syndrome components at a time. A similar pattern was demonstrated repeatedly with no significant differences in ΔEiA between the groups of exclusion. In the waist circumference criteria excluded group (651 patients excluded), a similar pattern was observed but lower values were shown; mean ΔEiA = 22.3 ± 6.2 (mg/g) for patients with the metabolic syndrome (three components or more) vs. 42.5 ± 6.8 (mg/g) for metabolic syndrome patients in the entire cohort (Fig. 1).

Sex effect

Men were older, had higher BMI, METs score during the exercise test, blood pressure measurements, LDL, A1C and fasting glucose levels alongside lower levels of HDL (Table 1). At rest, men presented with lower UACR values compared to women; 2.9 (1.3–6.8) vs. 4.8 (1.9–11.2) mg/g for median (IOR), p < 0.001. Following exercise UACR values were similar; 7.1 (2.5–22.3) vs. 7.9 (2.9–22.3) mg/g for median (IQR), p = 0.306. The change in UACR values (ΔEiA) was significantly higher in men compared to women; 3.1 (0.1–14.7) vs. 1.7 (−0.8 to −10.7) mg/g for median (IQR).

General linear univariate model to predict baseline UACR, showed significant effect of eGFR, but no significant effect of sex, age, A1C levels, BMI or METs components (Table 2).

Dependent variable	Rest UACR			ΔEiA
Predictors	B	CI (95%)	p value	B	CI (95%)	p value
Sex	32.95	−9.95 to 75.85	0.132	−89.98	−0.13 to −44.42	<0.001
Age	−0.1	−0.39 to 0.18	0.488	−0.1	−0.41 to 0.2	0.522
BMI	0.31	−0.3 to 0.92	0.319	2	1.34 to 2.66	<0.001
eGFR	−0.38	−0.57 to −0.19	<0.001	0.01	−0.2 to 0.21	0.956
A1C categorized	−15.69	−55.28 to 23.91	0.437	−109.82	−151.86 to −67.78	<0.001
METs	−0.48	−1.01 to 0.13	0.122	0.68	0.0–1.33	0.04
Baseline U albumin				−0.05	−0.09 to −0.01	0.016
Sex*A1c categorized	32.24	−75.74 to 10.92	0.143	95.37	49.34–141.39	<0.001

The model estimates predictors for rest urinary albumin to creatinine ratio (Rest UACR) and ΔEiA (UACR following exercise minus UACR at rest). Presented are results of a general linear regression model with Rest UACR (left side) or ΔEiA (right side) as the dependent variable and sex, age, BMI, eGFR, A1C, METs, rest UACR and the interaction between sex and categories of A1C as independent variables. Sex and the interaction between sex and A1C were significant predictors at the exercise induced model but not at rest

When searching for predictors of ΔEiA, we found a significant effect of sex, A1C and the interaction between them along with BMI, METs and baseline UACR (Table 2). Specifically, our data show that women with an A1C > 6.5% are at increased risk for higher ΔEiA even after controlling for age, BMI, eGFR, baseline UACR and METs; B = 95.37, 95% CI 49.34–141.39, p < 0.001 (Table 2; Fig. 2b).

A ΔEiA > 13 mg/g was defined as a cutoff level based on it being the lower bound of the top quartile of the cohort [75% of the cohort demonstrated ΔEiA < 13.6 (mg/g)]. ΔEiA > 13 mg/g was a significant predictor of positive (i.e. abnormal) exercise ECG findings in men and women, with women demonstrating much higher rates (OR = 2.691, p = 0.001 vs. OR = 1.511 p = 0.036, respectively). Among men, fasting glucose levels, Blood pressure and age were also observed as significant predictors (Fig. 3).

The positive predictive value (PPV) of ΔEiA > 13 mg/g in predicting positive ECG findings was higher in women compared to men (38 and 27% respectively). The negative predictive value (NPV) was high among the entire cohort NPV = 81% (82% in men and 77% in women).

CVD is the leading cause of morbidity and mortality among individuals with type 2 diabetes mellitus [33]. Among these patients, symptoms of coronary artery disease (CAD) are often absent even with advanced disease [34]. A wide variety of clinical strategies including exercise stress testing and various stress cardiac imaging techniques have been proposed for identifying diabetic patients with CAD before clinical manifestation is present [34–37]. In line with these, we suggest here ΔEiA as a sensitive and early biomarker for cardiovascular risk stratification in healthy, pre-diabetic and diabetic individuals.

Our data link ΔEiA to metabolic risk and clearly demonstrate a sex difference with regards to ΔEiA and the risk for an abnormal stress test. Women with diabetes are at a greater risk for higher ΔEiA which correlates with abnormal ECG findings during an exercise stress test. These differences were not detected by traditional biomarkers such as resting UACR and thus suggest a potential for ΔEiA as a biomarker for assessing CVD risk in women. Recent studies have shown similar patterns regarding exercise induced albuminuria and its correlation to the metabolic syndrome and diabetes in particular [5, 6, 9]. Our current study marks another step towards achieving a comprehensive understanding of dysmetabolic complications, their onset and progression throughout the disease. ΔEiA increased with accumulating metabolic syndrome criteria even after eliminating the effect of each criterion separately (with the largest effect observed after eliminating waist circumference criterion). Consequently, an increase in ΔEiA seems to be a characteristic disorder during progression of the metabolic syndrome.

Recent studies have shown that elevated low grade albuminuria (<30 mg/g) in the currently defined “normal” range is a predictor of worse CV outcomes [38–40]. These findings coupled with the currently reported findings linking high ΔEiA to increased CVD risk even in subjects with apparently normal albuminuria, call for a reassessment of our current definitions of “normal” range urinary albumin excretion.

The sex specific association between ΔEiA and an abnormal stress test ECG aligns with our current understanding of the role of microvascular heart disease in women with CVD. The observed link between these seemingly distinct processes is not surprising; measuring the effect of exercise on albuminuria is a sensitive method of directly assessing the renal microvasculature’s ability to withstand a “hemodynamic stress test”. It is reasonable to hypothesize that the metabolic process causing microvascular dysfunction would not be limited to the renal vasculature but affect other sensitive vascular beds including the heart. This concept has been recently demonstrated in other organs with microvascular disease such as retina and skin [41].

The major limitation of our study is the relative low event rate of major cardiovascular outcomes and evident renal damage in our cohort, limiting our assessment of the importance of ΔEiA in CV and renal disease risk stratification. Moreover, the current study was not designed to investigate whether ΔEiA predicts future CVD events or renal damage. Future longer studies with sufficient follow up periods, looking at major cardiovascular events (CV death, myocardial infarction and stroke) alongside incident albuminuria or reduced GFR, are needed to fully appreciate the potential of ΔEiA as a method for stratifying current and future CVD and CKD risk, and its clinical usefulness over widely used biomarkers such as resting UACR in women. However, the current findings in a relatively young and apparently healthy cohort were not detected by standard UACR and emphasize the ability to use ΔEiA as an early screening tool.

An additional limitation of our study is the relative wide definition of positive exercise ECG test findings; including ischemia related findings (ST segment depressions and T wave abnormalities) alongside VPCs. Future studies regarding EiA and CVD should address the debatable inclusion of VPCs under the definition of a positive cardiac stress test [42].

Another limitation of our study is the fact that a majority of women with A1C > 6.5% were post-menopausal. It is possible that sex hormones contribute to the progression of diabetic complications, specifically microvascular related ones [43]. There are numerous studies supporting this concept suggesting an influence of sex hormones on the renin-angiotensin system, endothelial function, and NO production (in relation to oxidative stress level) [44, 45]. A more focused investigation is needed to fully assess the contribution of sex hormones to ΔEiA and CVD.

A reduction in albuminuria is related to favorable cardiovascular outcomes [39, 46]. Early treatment of diabetic or hypertensive patients with angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, β-blockers, Ca²⁺ channel blockers, DPP-4 inhibitors, GLP-1 agonists and more recently SGLT-2 inhibitors was effective in lowering rest albuminuria [47–51]. Our data suggests that stress test-induced albuminuria may serve as a powerful screening tool to detect a high-risk subpopulation of women who require careful follow-up and possible refinement of preventive treatment. On the contrary, the relatively high negative predictive value demonstrated in our findings suggest that evaluating ΔEiA could also serve as an important screening tool through which unnecessary and costly ECG exercise tests could be avoided in women.

Our findings demonstrate excessive urinary albumin excretion following exercise among dysmetabolic patients. In women, ΔEiA is correlated with A1C levels. ΔEiA could possibly serve as a new screening tool for identifying female population at risk for abnormal exercise ECG test findings. The usefulness of ΔEiA as a biomarker for cardiovascular risk stratification among healthy and diabetic individuals will need to be validated in future studies.