Iben M. Miller1, Nicholas Carlson2, Ulla B. Mogensen3, Christina Ellervik4 and Gregor B. E. Jemec1
1Department of Dermatology, Roskilde Hospital, Faculty of Health and Medical Sciences, University of Copenhagen, Roskilde, 2Department of Nephrology, Herlev Hospital, Herlev. 3Department of Biostatistics, University of Copenhagen, Copenhagen, and 4Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, and Department of Research, Nykøbing Falster Hospital, Nykøbing Falster, Denmark
The chronic inflammatory skin diseases hidradenitis suppurativa (HS) and psoriasis have been linked to cardiovascular risk factors and the latter has also been linked to possible renal dysfunction. Since basement membrane thinning in the skin of HS patients has been described, we speculated whether similar basement membrane defects might occur in renal tissue. Our objective was to investigate a possible association between HS and renal dysfunction. We performed a hospital and population-based cross-sectional study using estimated Glomerular-Filtration-Rate (eGFR) to assess renal function. Thirty-two hospital individuals with HS, 430 population individuals with HS, and 20,780 population individuals without HS (controls) were identified. The age-, sex-, smoking-, BMI-, hypertension- and diabetes-adjusted analysis revealed a statistically significant higher eGFR for the hospital group with HS and a mean difference in eGFR of 6.81 (1.27–12.35) ml/min/1.73 m2 between the hospital group with HS and the population group without HS. The observed higher eGFR in the hospital group with HS indicates a possible association of HS and renal dysfunction. Key words: co-morbidities; epidemiology; estimated glomerular filtration rate (eGFR); hidradenitis suppurativa (HS); hyperfiltration; inflammation.
Accepted Feb 16, 2015; Epub ahead of print Feb 24, 2015
Acta Derm Venereol
Iben Marie Miller, MD, Department of Dermatology, Roskilde Hospital, Køgevej 7–13, DK-4000 Roskilde, Denmark. E-mail: firstname.lastname@example.org.
During the last decade evidence that chronic inflammatory skin diseases may be linked to systemic disorders has accumulated. For example, psoriasis has been linked to metabolic syndrome and cardiovascular disease, and recently also to renal dysfunction (1–4).
Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder, which manifests itself as recurrent painful deep-seated boils and fistulae in apocrine gland-bearing skin, i.e. axillae and groin with subsequent scarring (5, 6). A population-based prevalence of 2.1% has been reported (7), and an association to metabolic syndrome has been described (8–10). Furthermore, basement membrane thinning in the skin of HS patients has been suggested (11). It may be speculated that a similar defect can occur in other tissues, e.g. renal tissue, where a disturbance of the glomerular basement membrane may promote hyperfiltration.
We therefore hypothesised that HS may be associated with renal dysfunction independent of traditional risk factors, i.e. overweight, hypertension and diabetes, and have therefore investigated a possible association between HS and renal dysfunction taking advantage of the Danish General Suburban Population Study (GESUS), a cross-sectional study of the adult Danish general suburban population in Naestved Municipality (70 km south of Copenhagen) (12), and a hospital HS group recruited from the outpatient clinic at the Department of Dermatology at Roskilde Hospital in Denmark (serving the region of Zealand which includes Naestved).
MATERIALS AND METHODS (Appendix S11)
The data used from GESUS were within the period January 1, 2010 to October 10, 2013. A total of 32 individuals in the hospital HS group, 430 individuals in the population HS group, and 20,780 individuals in the population non-HS group (controls) were identified. The background factors and characteristics of the HS group and the non-HS group showed that the HS groups were predominately younger, female and smokers (Table SI1).
Renal function assessed by estimated glomerular filtration rate
The unadjusted analysis revealed a statistically significant mean difference (MD) of 17.61 ml/min/1.73 m2 (95% CI 11.10–24.13) (p < 0.0001) for the hospital HS group vs. non-HS group, and a statistically significant MD of 6.42 ml/min/1.73 m2 (95% CI 4.63–8.22) (p < 0.0001) for the population HS group vs. the non-HS group (Tables SII and SIII1).
The age-, sex- and smoke-adjusted analysis revealed a mean eGFR of 94.63 ml/min/1.73 m2 (95% CI 89.99–99.27) for the hospital HS group, 88.00 ml/min/1.73 m2 (95% CI 86.72–89.29) for the population HS group, and 88.41 ml/min/1.73 m2 (95% CI 88.10–88.71) for the population non-HS group. Thus, yielding a statistically significant age-, sex- and smoke-adjusted MD of 6.22 ml/min/1.73 m2 (95% CI 0.92–11.53) (p > 0.0172) for the hospital HS group vs. the non-HS group, and a statistically non-significant age-, sex- and smoke-adjusted MD of –0.40 ml/min/1.73 m2 (95% CI –1.87–1.06) (p = 0.7866) for the population HS group vs. the non-HS group (Tables SII and SIII1).
The age-, sex-, smoke-, BMI-, hypertension- and diabetes-adjusted analysis revealed a mean eGFR of 95.53 ml/min/1.73 m2 (95% CI 90.66–100.40) for the hospital HS group, 90.25 ml/min/1.73 m2 (95% CI 88.55–91.96) for the population HS group, and 88.72 ml/min/1.73 m2 (95% CI 88.10–89.34) for the population non-HS group. Thus, yielding a statistically significant age-, sex-, smoke-, BMI-, hypertension- and diabetes-adjusted MD of 6.81 ml/min/1.73 m2 ((95% CI 1.27–12.35) (p = 0.0119) for the hospital HS group vs. the non-HS group, and a statistically non-significant age-, sex-, smoke-, BMI-, hypertension- and diabetes-adjusted MD of 1.53 ml/min/1.73 m2 (95% CI –0.35–3.41) (p = 0.1322) for the population HS group vs. non-HS group (Fig. 1, Tables SII and SIII1).
Fig. 1. Age-sex-smoking-BMI-hypertension-diabetes-adjusted eGFR mean values (95%CI) for the hospital HS- group, population HS- group, and population non-HS- group. The Mean Difference between the hospital HS group and non-HS group was 6.81 ml/min/1.73 m2 (p = 0.0119), and the Mean Difference for the population HS group vs. the non-HS group was 1.53 ml/min/1.73 m2 (p = 0.1322).
Stratifying eGFR levels according to chronic kidney disease (CKD) stages revealed a statistically higher frequency of eGFR> = 90 ml/min/1.73 m2 in HS groups compared to the non-HS group (Table SII1).
With regard to a possible association between HS severity degree and eGFR we found diverging results; a statistically significant association between the 3 HS severity degrees and eGFR; the more severe the HS was, the higher eGFR was (Table SIV1).
In contrast, the association between number of boils and eGFR was statistically non-significant (p = 0.1307). Similarly, the association between Sartorius score and eGFR was statistically non-significant (p = 0.1996).
Lastly, an age-, sex-, and smoking-adjusted subgroup analysis of severe population-based HS group (n = 93) only, revealed no difference in eGFR when compared to the non-HS group (p = 0.598)
The body of literature describing renal complications in chronic cutaneous inflammation is scarce, but renal dysfunction has been described in patients with psoriasis (4). To the best of our knowledge the association of HS and renal dysfunction is a hitherto unexplored topic.
We found that eGFR was higher for both the hospital and population-based HS groups when compared to the non-HS group (controls). When adjusting for background factors and possible confounders, the eGFR was only significantly higher in the hospital HS group vs. the non-HS group. Individuals recruited from a hospital outpatient clinic is more likely to represent severe skin disease than individuals recruited from the general population. This is supported by the distribution of severity observed in this study (Table SI1). According to Hills causal criteria in epidemiology a possible dose-response relationship favours causality. The fact that the hospital HS group (i.e. predominantly severe HS) has a higher eGFR when compared to the population HS group (ie. mild-severe HS) may thus suggest a causal relationship between HS and eGFR. Supportive of this we found a direct relationship between HS severity degree and eGFR. However, the results must be seen in light of a possible selection bias, i.e. the hospital and population HS groups may also represent certain subgroups or subtypes of HS and the inclusion criteria of the two HS groups varied.
The observed higher eGFR in the hospital HS group remains after adjusting for potential confounders including elements of the metabolic syndrome, suggesting that the HS comorbidities may not entirely explain the higher eGFR.
A histology study of skin samples from 20 HS patients suggested a structural defect of the basement membrane zone in the folliculopilosebaceous unit (11). We speculated that a similar defect could occur in other tissues, e.g. renal tissue, where a similar thinning of glomerular basement membrane may promote glomerular hyperfiltration, and subsequent augmented eGFR and proteinuria.
An association between the metabolic syndrome (MetS) and CKD as well as HS has been demonstrated (8–10, 15–18). MetS is a cluster of cardiovascular risk factors, i.e. insulin resistance/diabetes, dyslipidemia, hypertension, and obesity. Glomerular hypertension and hyperfiltration is a recognised early change in subjects with diabetes and hypertension (19, 20). Dyslipidemia seems to damage podocyte function leading to protein leakage (21) and accumulation of lipids in the glomerular capillary endothelial and mesangial cells may stimulate local inflammation leading to chronic nephropathy (22, 23). Obesity-related nephropathy appears to include an increased renal blood flow, augmentation of GFR, and proteinuria as well as vascular changes resulting from renal hyperfiltration and hyperperfusion (24–26).
The treatment regime of HS include systemic cyclosporine and rifampicin, both known to be associated with risk of kidney injury, although the latter very rarely (27–29).
Chronic inflammation may interlink atherosclerosis, MetS, CKD, and HS (26, 30–33). The inflammatory cytokine TNF-alpha, which has been linked to HS pathogenesis, induces mineralisation of vascular cells in vitro (34), appears to induce apoptosis of renal cells (35), and progression of diabetic nephropathy (36). Thus, chronic inflammation in HS may mediate renal vascular change and apoptosis of renal cells with subsequent alterations in renal function.
No commonly acknowledged definition of glomerular hyperfiltration exists (37). However, several studies set the threshold for hyperfiltration from 125 to 175 ml/min/1.73 m2 (37). Glomerular hyperfiltration has been observed as a physiological response as well as a pathological sign (37).
Although the traditional perception of renal dysfunction reduced renal flow and low eGFR, an increased GFR can be an expression of early manifestations of a renal dysfunction.
Both the association of eGFR with cardiovascular risk and mortality appear U-shaped (38, 39), i.e. both low and high eGFR may be predictive of increased mortality and cardiovascular risk. The finding may be biased by muscle waisting in chronic disease/malnutrition/cachexia with subsequent low muscle mass, low creatinine and high eGFR. However, a recent study adjusting for muscle mass found renal hyperfiltration to be a possible novel marker for all-cause mortality (40). Additionally, a Hazard ratio for all-cause mortality of 1.29 (1.19–1.41) for patients with high eGFR (90–119 ml/min) and an odds ratio of 1.49 (1.05–2.09) for carotide intima media thickness in high eGFR (101.2–138.6 ml/min) have been reported (38, 39). Animal models indicate that loss of nephrons induce an adaptive response with increased intraglomerular pressure, glomerular hypertrophy, and compensary glomerular hyperfiltration in the spared nephrons with subsequent secondary glomerulosclerosis (35).The higher eGFR demonstrated in the hospital HS group may thus reflect the earliest signs of renal dysfunction. Our study may have identified early as opposed to end-stage HS-related kidney damage, only because the HS individuals are relatively young with a mean age of 42 years.
In aggregate, possible association between HS and renal dysfunction could in theory occur via one or several of the following mechanisms: 1) HS-basement membrane nephropathy, 2) co-morbidities (i.e. MetS), 3) treatment-associated nephrotoxicity, or 4) chronic inflammatory-associated nephropathy.
The major strengths of our study are the large number of population HS individuals and the broad inclusion of both hospital- and population HS individuals reducing selection bias and adding a broader range of disease severity aiding the generalisation. The HS diagnosis has previously been validated yielding a sensitivity of 90% and a specificity of 97% providing information on misclassification bias (7). As the self-reported questions used to identify the population HS group refer to symptoms (i.e. boils) rather than the actual diagnosis (i.e. do you suffer from HS?), possible undiagnosed HS subjects were included. The diagnosis of the hospital HS group was physician-verified, and possible confounders were explored.
Potential limitations should be considered. First, it is crucial to recognise that as this study is cross-sectional, we cannot prove causality. Furthermore, the population is suburban, Caucasian and underrepresenting the age group 20–30, which may limit the generalisability. Additionally, background factors differered between the HS groups and non-HS group; however, statistical adjustments accordingly were made. The low participation rate of the hospital HS group reduced power, and may furthermore have resulted in selection bias, e.g. only the healthiest HS patients may have participated whereas the most mentally and physically burdened patients did not have the resources to participate in GESUS potentially excluding the HS patients with the most burdensome co-morbidities. We did not include information on HS medical treatment or known renal disease. Additionally, urine analysis for protein leakage was not performed. The method of estimating GFR should be questioned as the CKD-EPI equation (see Appendix S11) expresses the kidney function as a body surface area indexed value (ml/min/1.73 m2), which might underestimate eGFR in patients with extreme body sizes (12). As HS is associated with obesity, eGFR for HS subjects may be underestimated. However, we adjusted for BMI.We used CKD-EPI since it is the best validated method of estimating GFR. Furthermore, as the non-HS population (controls) has a relatively high mean age, this could indicate low muscle mass, low creatinine, overestimation of eGFR and subsequent underestimation of the difference in eGFR between the HS group and non-HS group. CKD-EPI is, however, validated up to 80 years. As with any questionnaire survey there is a risk of recall bias.
In conclusion, the observed higher eGFR amongst the hospital-based HS subjects indicates a possible association of HS and renal dysfunction. As this is the first study of its kind, it may be too speculative to suggest clinical implications such as routine renal screening i.e. eGFR and urine analysis.
Future studies are warranted to confirm or reject our results, preferably including a urine analysis for protein leakage and using a follow-up study design. Furthermore, experimental studies on the mechanisms promoting a possible renal dysfunction in HS are needed possibly using kidney biopsies.
The authors would like to thank the Region Zealand Foundation in Denmark for making this project financially possible, and Associate Professor Knud Rasmussen for his valuable comments.