Insulin Resistance and Metabolic Syndrome in Patients with Seborrheic Dermatitis: A Case

Abstract

Background:

Our knowledge of the systemic effects of seborrheic dermatitis (SD) as a chronic inflammatory skin disease remains limited. We aimed to evaluate metabolic syndrome (MS) and glucose metabolism disorders in patients with SD.

Methods:

The study includes 53 patients over the age of 18 diagnosed with SD and 50 age-, gender-, and body mass index-matched healthy controls. Demographic data, anthropometric measurements, blood pressure levels, family history of SD and metabolic disorder, smoking history, and severity of the disease in SD patients were obtained. Fasting plasma glucose, insulin, hemoglobin A1c, lipid profile levels, and two-hour plasma glucose in the oral glucose tolerance test (OGTT 2-h PG), homeostasis model assessment of insulin resistance (HOMA-IR), and presence of MS were determined.

Results:

Weight, waist circumference, family history of SD, family history of metabolic disorder, and smoking status were significantly higher in the SD group compared with the control group (P = 0.04, P = 0.007, P = 0.004, P = 0.004, and P = 0.048, respectively). The levels of fasting plasma insulin and triglyceride, HOMA-IR and OGTT 2-h PG were also significantly higher in the SD group than in the control group (P = 0.0001, P = 0.033, P = 0.0001, and P = 0.049, respectively). In addition, the number of those with insulin resistance was significantly higher in the group with SD (n = 31, 58.49%) than in the control group (n = 11, 22%) (P = 0.0001). Although the rate of MS was higher in patients with SD (n = 12, 22.64%) than the controls (n = 6, 12%), the difference was not significant (P = 0.155).

Conclusion:

Our findings suggest an association between SD and insulin resistance, which may be due to their common inflammatory pathogenesis. This may be an indicator of susceptibility to diabetes, and these patients can be followed up for conditions associated with insulin resistance and encouraged to adopt a healthy lifestyle.

Introduction

Seborrheic dermatitis (SD) is a common chronic recurrent skin disease that causes erythema and desquamation of the skin in areas rich in sebaceous glands.¹ The global prevalence of SD is ∼5%.² Although there is no known cause of SD, some risk factors are known to contribute to its development, including sex hormones such as androgens, immunodeficiency, neurological and psychiatric diseases, overgrowth of commensal Malassezia species.³ Few previous studies have shown an association between SD and diet,⁴ hypertension,⁵ obesity,^5,6 alcohol consumption,⁷ and chronic alcoholic pancreatitis.⁸

The literature contains various studies investigating the relationship between metabolic syndrome (MS) and insulin resistance and inflammatory skin diseases, such as psoriasis, lichen planus, and hidradenitis suppurativa.^9
–11 In this study, we aimed to determine the relationship of SD, as another chronic inflammatory skin disease, with the disorders of glucose metabolism and MS parameters.

Materials and Methods

We designed a prospective clinical, observational, analytical study to evaluate MS and glucose metabolism disorders in patients with SD. Ethics committee approval was obtained from the local ethics committee. Institutional review board (IRB) approval was waived because local ethics committee approval was obtained.

Inclusion and exclusion criteria

The study included 53 patients over the age of 18 who were diagnosed with SD between 2018 and 2019, and agreed to participate in the study. Patients with hypertension, cardiovascular disease, diabetes, hyperlipidemia, thyroid disease, and chronic inflammatory diseases, such as psoriasis and rheumatoid arthritis, and those who were taking medication that could affect glucose metabolism, lipid profile, or arterial blood pressure were not included in the study. The control group was composed of 50 healthy volunteers with no known disease, matched to the SD group in terms of age, gender, and body mass index (BMI). Written consent was obtained from all participants.

Study design

SD was diagnosed based on clinical findings. Age, gender, weight, height, waist circumference, smoking status, family history of SD, and family history of metabolic disorder, including hypertension, diabetes, and cardiovascular disease, were recorded for all the participants. BMI was calculated using the formula, weight (kg)/height (m)². In the SD group, disease duration, subjective disease severity, and SD area severity index (SDASI) were also obtained. Subjective disease severity was evaluated by scoring the level of itching, burning, erythema, and presence of dandruff between 0 and 3 points, and the total was recorded as the subjective score (range, 0–12). A score of 0 was interpreted as none, 1 as mild, 2 as moderate, and 3 as severe. According to the SDASI scoring system, erythema and desquamation of nine different anatomical regions were graded as 0 (none), 1 (mild), 2 (moderate), and 3 (severe). The score for each region was multiplied by the corresponding constant value (0.1 for the forehead, nasolabial fold, eyebrow, postauricular and auricular areas, and cheek or chin; 0.2 for the intermammary area and back; and 0.4 for the scalp) to obtain the total SDASI score (range, 0–12.6).¹²

In all participants, diastolic and systolic blood pressures were measured after resting for ∼20 min. Blood samples were taken from the SD and control groups after 12 hr of fasting to determine the levels of fasting plasma glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride using an autoanalyzer (ARCHITECT C16000; Abbott), and low-density lipoprotein (LDL) was automatically calculated. The fasting plasma insulin levels were estimated with an immune assay analyzer (ARCHITECT i2000SR; Abbott). Hemoglobin A1c (HbA1c) was determined using an TOSOH G8 HPLC analyzer. Insulin resistance was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR) with the following formula: fasting insulin level (μIU/mL) x fasting glucose level (mg/dL)/405. The HOMA-IR value being >2.5 was defined as insulin resistance.¹³ Plasma glucose (2-h PG) was measured 2 hr after the administration of the oral glucose tolerance test (OGTT, 75 grams glucose), and an internal medicine specialist was consulted in cases where interpretation was difficult. MS was defined as the presence of any three or more of the following five risk abnormalities according to the criteria presented in the National Cholesterol Education Program Adult Criteria Treatment Panel III (NCEP-ATP III): waist circumference ≥102 cm in males and ≥88 cm in females, hypertriglyceridemia ≥150 mg/dL or drug treatment for elevated triglycerides, HDL <40 mg/dL in males and <50 mg/dL in females or drug treatment for low HDL, blood pressure ≥130/85 mmHg or drug treatment for hypertension, and fasting plasma glucose ≥100 mg/dL or drug treatment for elevated blood glucose.¹⁴

Statistical analyses

Descriptive statistical methods [frequency, percentage, mean, standard deviation, median, and interquartile range (IQR)] were used to evaluate the data. In the comparison of quantitative data, t-test was used to determine the differences between the two groups if the data were normally distributed, and the Mann–Whitney U-test was conducted if the data did not show normal distribution. The Kolmogorov–Smirnov test was employed for the normality analysis. Relationships were investigated using the Spearman correlation coefficient. The chi-square and Fisher's exact tests were undertaken to determine the differences between the two groups in terms of discrete data. The obtained findings were evaluated at a 95% confidence interval and P < 0.05 significance level.

Results

The study included a total of 103 patients, of whom 53 had SD and 50 formed the control group. The groups were similar in terms of mean age, BMI, and gender distribution (Table 1). For the patients with SD, the median (IQR) disease duration was 60 (75) (range, 1–312) months, the mean disease subjective severity score was 7.43 ± 2.54 (range, 2–12), and the mean SDASI score was 2.44 ± 0.91 (range, 0.6–4.4).

Table 1.

Comparison of the Demographic Data and Characteristics Between the Patients with Seborrheic Dermatitis and Control Group

Characteristic	Groups				P value
	Patients with seborrheic dermatitis		Controls
	n	%	n	%
Gender
Female	25	47.17	22	44	0.75
Male	28	52.83	28	56	0.75
Family history of seborrheic dermatitis
Absent	38	71.70	47	94	0.004
Present	15	28.30	3	6	0.004
Family history of metabolic disorder
Absent	18	33.96	31	62	0.004
Present	35	66.04	19	38	0.004
Smoking
Absent	27	50.94	35	70	0.048
Present	26	49.06	15	30	0.048
	Mean ± standard deviation	Median (IQR)	Mean ± standard deviation	Median (IQR)
Age, year	34.87 ± 10.08	35 (14)	34.04 ± 10.15	34 (12.5)	0.59
Weight, kg	83.22 ± 20.73	83 (24.5)	75.45 ± 13.93	77 (17.75)	0.04
Height, cm	168.67 ± 9.94	170 (12)	167.58 ± 9.22	167 (12.5)	0.80
Waist circumference, cm	100.89 ± 15.90	102 (20)	92.98 ± 12.70	95 (16.25)	0.007
BMI, kg/m²	29.38 ± 7.81	27.4 (8.45)	26.81 ± 4.35	26.1 (5.77)	0.123
Systolic blood pressure, mmHg	119.58 ± 14.98	120 (20)	118.58 ± 22.54	120 (20)	0.84
Diastolic blood pressure, mmHg	76.08 ± 10.29	80 (10)	74.32 ± 10.13	71 (10)	0.303

A value of P < 0.05 was accepted as statistical significance and highlighted in bold.

BMI, body mass index; IQR, interquartile range.

There was no statistically significant difference between the SD group and the control group in terms of height, systolic blood pressure, diastolic blood pressure, presence of MS and fasting plasma glucose, HbA1c, total cholesterol, HDL, and LDL values (Tables 2 –3). Weight, waist circumference, family history of SD, family history of metabolic disorder, and smoking status were significantly higher in the SD group compared with the control group (Table 1). The levels of fasting plasma insulin and triglyceride, HOMA-IR, and two-hour plasma glucose in the oral glucose tolerance test (OGTT 2-h) PG were significantly higher in the SD group compared with the control group (Table 2). In addition, the number of insulin-resistant patients was significantly higher in the SD group (n = 31, 58.49%) than in the control group (n = 11, 22%) (Table 3).

Table 2.

Comparison of the Biochemical Data Between the Patients with Seborrheic Dermatitis and the Control Group

Biochemical data	Groups				P value
	Patients with seborrheic dermatitis		Controls
	Mean ± standard deviation	Median (IQR)	Mean ± standard deviation	Median (IQR)
Fasting plasma glucose, mg/dL	96.70 ± 18.48	94 (14.05)	91.92 ± 12.61	90.50 (15.25)	0.12
Fasting plasma insulin, μIU/mL	14.02 ± 7.45	11.8 (11.88)	9.34 ± 5.56	8.15 (4.3)	0.0001
OGTT 2-h PG, mg/dL	114.50 ± 41.85	108 (44.5)	97.78 ± 27.25	94.5 (44.5)	0.049
HOMA-IR	3.82 ± 3.47	2.88 (2.87)	2.21 ± 1.65	1.82 (1.13)	0.0001
HbA1c, %	5.50 ± 0.77	5.4 (0.4)	5.39 ± 0.54	5.5 (0.3)	0.092
Triglyceride, mg/dL	132.86 ± 86.11	120 (93)	99.81 ± 43.89	90.8 (58)	0.033
Total cholesterol, mg/dL	178.21 ± 31.78	178 (55.5)	182.86 ± 37.50	177 (51.25)	0.497
HDL, mg/dL	47.58 ± 11.70	46.2 (17.25)	50.18 ± 13.44	50.05 (21.5)	0.27
LDL, mg/dL	106.47 ± 29.11	107 (36)	114.02 ± 32.67	114 (42.5)	0.218

A value of P < 0.05 was accepted as statistical significance and highlighted in bold.

HbA1c, hemoglobin A1c; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL, low-density lipoprotein; OGTT 2-h PG, oral glucose tolerance test two-hour plasma glucose.

Table 3.

Comparison of the Metabolic Syndrome and Insulin Resistance Rates Between the Patients with Seborrheic Dermatitis and the Control Group

	Groups				P value
	Patients with seborrheic dermatitis		Controls
	n	%	n	%
Insulin resistance (predefined as HOMA-IR values >2.5)
Absent	22	41.51	39	78	0.0001
Present	31	58.49	11	22	0.0001
Metabolic syndrome (assessed by NCEP-ATP III)
Absent	41	77.36	44	88	0.155
Present	12	22.64	6	12	0.155

A value of P < 0.05 was accepted as statistical significance and highlighted in bold.

NCEP-ATP III, National Cholesterol Education Program Adult Criteria Treatment Panel III.

A positive significant relationship was found between the SDASI score and age, BMI, smoking, and fasting plasma insulin, triglyceride and OGTT 2-h PG, HOMA-IR values in patients with SD (Table 4). In addition, there was a significant positive correlation between the SDASI score and the disease subjective severity score (Table 4). However, the disease subjective severity score was not correlated with age, gender, disease duration, BMI, smoking, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, insulin, HbA1c, triglyceride, total cholesterol, HDL, LDL and OGTT 2-h PG, and HOMA-IR values (Table 4). No correlation was found between disease duration and the investigated parameters except the OGTT 2-h PG value and smoking (Table 4).

Table 4.

Relationship of the Seborrheic Dermatitis Area Severity Index Score, Subjective Disease Severity Score, and Disease Duration with Clinical and Biochemical Parameters in Patients with Seborrheic Dermatitis

Characteristic	SDASI score (Spearman's rho)		Subjective disease severity score (Spearman's rho)		Disease duration (Spearman's rho)
	r	P	r	P	r	P
Age, years	0.393	0.004	0.125	0.374	−0.06	0.68
Gender	0.182	0.192	−0.141	0.315	0.22	0.12
BMI, kg/m²	0.298	0.030	0.082	0.560	−0.07	0.62
Systolic blood pressure, mmHg	0.088	0.530	0.005	0.973	0.15	0.30
Diastolic blood pressure, mmHg	0.028	0.845	0.027	0.849	0.03	0.82
Fasting plasma glucose, mg/dL	0.099	0.480	0.006	0.968	−0.14	0.30
Fasting plasma insulin, μIU/mL	0.337	0.014	0.012	0.931	−0.08	0.57
OGTT 2-h PG, mg/dL	0.223	0.024	0.173	0.080	0.217	0.028
HOMA-IR	0.300	0.029	−0.017	0.904	−0.12	0.40
HbA1c, %	−0.104	0.297	−0.144	0.148	−0.179	0.071
Triglyceride, mg/dL	0.355	0.009	0.077	0.582	−0.01	0.97
Total cholesterol, mg/dL	0.094	0.501	−0.089	0.527	0.01	0.92
HDL, mg/dL	−0.067	0.631	0.250	0.071	0.09	0.51
LDL, mg/dL	0.054	0.699	−0.162	0.247	−0.09	0.50
Smoking	0.220	0.025	0.154	0.120	0.200	0.042
SDASI score			0.551	0.00001	0.11	0.45
Subjective disease severity score	0.551	0.00001			0.09	0.52
Disease duration	0.107	0.446	0.090	0.523

A value of P < 0.05 was accepted as statistical significance and highlighted in bold.

SDASI, seborrheic dermatitis area severity index.

Discussion

In previous studies, MS^9,11 and its components, namely obesity,^9,15 hypertension,^16,17 dyslipidemia,^9,18,19 and glucose metabolism disorders,^9,19,20 were found to be associated with chronic inflammatory skin diseases, such as hidradenitis suppurativa and psoriasis. Considering the chronic inflammatory nature of SD, in this cross-sectional case–control study, we evaluated the relationship between SD and MS criteria and glucose metabolism in adults, and we observed a positive relationship similar to that previously reported for other inflammatory diseases.

MS is a proinflammatory and prothrombotic condition characterized by insulin resistance, hyperglycemia, hypertension, atherogenic dyslipidemia, and abdominal obesity, which constitute risk factors for certain diseases, including cardiovascular disease, diabetes mellitus, and fatty liver.²¹ In our study, the waist circumference and triglyceride levels, which are among the criteria for MS, were found to be significantly higher in the SD group than in the control group. Increased adipose tissue plays an important role in the development of insulin resistance. Abdominal obesity increases the amount of free fatty acids (FFAs) in the body, which, in turn, reduces insulin-mediated glucose uptake at the muscle cell level. FFAs increase the production of glucose, triglyceride, and very LDLs in the liver.²² It is known that most chronic inflammatory skin diseases are associated with dyslipidemia, possibly through the secretion of proinflammatory cytokines.²³ Studies have shown that dyslipidemia is increased in various skin diseases, such as psoriasis, lichen planus, pemphigus, granuloma annulare, and histiocytosis, and connective tissue diseases; for example, lupus erythematosus.²³ Similarly, we found the triglyceride and waist circumference values to be higher in patients with SD than in the controls.

In our study, the fasting plasma insulin and OGTT 2-h PG levels, which are indicators of glucose metabolism, were significantly higher in patients with SD compared with the control group. However, although the fasting plasma glucose level was higher in patients with SD, this was not statistically significant. In the SD group, the HOMA-IR value and the number of patients with an HOMA-IR value of >2.5; that is, insulin resistance were also significantly higher compared with the control group. Although the MS rate was higher in the SD group according to the NCEP-ATP III criteria, the difference was not statistically significant compared with the controls. Insulin resistance is defined as the reduced response of target tissues to normal insulin levels, and it is widely accepted as the primary mechanism of the pathophysiology of MS.²⁴ In insulin resistance, muscle, fat, and liver cells do not respond appropriately to the insulin hormone and cannot maintain blood sugar levels. To reach a normal blood glucose level, pancreatic β-cells secrete excessive insulin, leading to hyperinsulinemia.²⁵ The pancreas gradually becomes unable to keep up with the increasing insulin demand, which results in the buildup of excess glucose in the bloodstream.²² Cases where plasma glucose levels are higher than normal but do not reach the diagnostic limits of diabetes are called prediabetics. The most commonly used glycemic targets in the diagnosis of prediabetes are fasting plasma glucose (100–125 mg/dL), postprandial plasma glucose (2-h PG during 75-grams OGTT 140 to 199 mg/dL), and HbA1C (5.7%–6.4%) values. At least one of these criteria being within the defined limits is sufficient for a diagnosis of prediabetes.²⁶ The fasting blood glucose level of our patients being similar to the controls while the fasting insulin and OGTT 2-h PG levels being higher in the former may indicate the susceptibility of SD cases to diabetes and MS.

Three main factors play a role in the etiology of SD: sebaceous gland secretion, changes in the colonization and metabolism of cutaneous microflora, and individual susceptibility.²⁷ A potential etiopathological mechanism involves lipase activity from Malassezia lipases and fatty acid release from the major sebaceous triglycerides. FFAs, especially those that are unsaturated, may cause inflammation and hyperproliferation.²⁸ SD being more common in males and beginning to develop in adolescence indicates a significant hormonal effect, especially that of androgens.^29,30 Due to the transfer of hormones from the mother, there is a significant frequency of SD in infants, which may support the hyperandrogenic hypothesis for SD.³⁰

Hyperinsulin can stimulate factors involved in the development of SD through the increase in androgen levels and sebum production. Both insulin and insulin-like growth factor 1 (IGF-1) stimulate the synthesis of ovarian and testicular androgens. In addition, insulin and IGF-1 inhibit the hepatic synthesis of sex hormone-binding globulin and increase the bioavailability of circulating androgens. In addition, they stimulate sebum production.^{31

–38} In a hyperinsulinemic state, while IGF-1 levels increase, IGF-binding protein-3 levels decrease, resulting in an imbalance that leads to the hyperproliferation of keratinocytes,³⁹ which is another factor that plays a role in the pathogenesis of SD.²⁸

In a recent study, HDL levels were significantly lower, and first-degree family history of metabolic disorder was significantly higher in patients with SD compared with the control group. Furthermore, an inverse correlation was observed between disease severity and HDL levels. Based on these findings, the authors suggested that SD could be a predictive factor for MS.⁴⁰ In another study examining adolescent men, the SD of the scalp was found to be associated with higher body fat content.⁶ In the same study, no relationship was found between smoking and SD.⁶ In a prospective population-based cohort study, SD was not shown to be associated with hypertension, alcohol consumption, and smoking.⁷ In a further study, the SD patients were determined to be more likely to be obese and hypertensive, but their likelihood of smoking or having diabetes was lower.⁵ In contrast, Lancar et al. found that history of tobacco use and that of regular alcohol consumption were associated with SD.⁴¹ In our study, a family history of SD and metabolic disorder, and smoking were found to be higher in the SD patients than in the controls. In addition to previous studies, we determined high values of insulin resistance, triglyceride, and OGTT 2-h PG, which are either components of MS or contribute to this syndrome, which further supports the susceptibility of SD patients to MS.

MS is a chronic inflammatory condition characterized by increased proinflammatory cytokine levels, inflammatory biomarkers, and altered adipokines. In diseases such as psoriasis and atopic dermatitis, some cutaneous inflammatory mediators may enter the systemic circulation, resulting in a condition called inflammatory skin march.^42,43 The release of these proinflammatory cytokines may cause chronic systemic inflammation, inducing insulin resistance, obesity, hypertension, and MS,^44,45 and may be one of the main mechanisms underlying the link between MS and certain skin diseases.⁴⁶ In SD lesions, the immunocytochemical analysis of skin biopsy samples reveals elevated levels of various inflammatory mediators, such as interleukin (IL)-lα, IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12, tumor necrosis factor-α, and interferon-γ.⁴⁷

In light of the results we obtained on SD, we consider it beneficial to conduct further research on MS susceptibility and insulin resistance in these patients. Thus, these conditions can be diagnosed early, and their complications can be prevented. By providing counseling for patients in terms of weight and diet control, healthy lifestyle changes can be encouraged, and the risk of developing MS and insulin resistance can be reduced.

The cross-sectional design and the relatively small sample size are the main limitations of this study. In addition, the absence of an evaluation of parameters associated with insulin resistance and MS, such as proinflammatory cytokines, adipokines, IGF-1 and C-peptide, and alcohol use, can be considered as another limitation. Finally, the physical activity and exercise levels of the participants were not noted.

Conclusion

Our data show that patients with SD are at risk of developing insulin resistance. However, there are only few studies supporting the relationship between SD and insulin resistance and glucose metabolism. Therefore, there is a need for further research involving a larger number of participants to confirm our findings.

Authors' Contributions

S.S.E. contributed to approval of the final version of the article; critical literature review; data collection, analysis, and interpretation; effective participation in research orientation; intellectual participation in propedeutic and/or therapeutic management of studied cases; article critical review; preparation and writing of the article; statistical analysis; study conception and planning. T.F.G. contributed to approval of the final version of the article; data collection, analysis, and interpretation; effective participation in research orientation; intellectual participation in propedeutic and/or therapeutic management of studied cases; article critical review. E.Ö. carried out approval of the final version of the article; data collection, analysis, and interpretation; article critical review. B.D. performed approval of the final version of the article; article critical review; study conception and planning.

Footnotes

Acknowledgments

The authors thank Dr. Tuba Elif Şenel for her contributions to the interpretation of the oral glucose tolerance test.

Author Disclosure Statement

No conflicting financial interests exist.

Funding Information

The authors report no involvement in the research by the sponsor, which could have influenced the outcome of this work.

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Insulin Resistance and Metabolic Syndrome in Patients with Seborrheic Dermatitis: A Case–Control Study

Abstract

Background:

Methods:

Results:

Conclusion:

Introduction

Materials and Methods

Inclusion and exclusion criteria

Study design

Statistical analyses

Results

Discussion

Conclusion

Authors' Contributions

Footnotes

Acknowledgments

Author Disclosure Statement

Funding Information

References