Sage Journals: Discover world-class research

Abstract

Objective

To investigate the possible association of periorbital melanosis (POM) with insulin resistance (IR) and vitamin D serum levels.

Methods

In this pilot, case-control study, we included 100 adult patients with POM and 100 age- and sex-matched healthy control subjects. Vitamin D levels and IR indices (i.e., homeostatic model assessment-insulin resistance [HOMA-IR], triglycerides/high-density lipoprotein cholesterol (TG/HDL-c) ratio, adiponectin/leptin (A/L) ratio) were compared between cases and controls.

Results

Compared with controls, POM cases had significantly higher values of HOMA-IR and TG/HDL-c ratio, and significantly lower values of A/L and vitamin D. HOMA-IR and TG/HDL-c ratio were statistically significantly positively correlated with POM severity while Vitamin D and A/L ratio were statistically significantly negatively correlated.

Conclusion

POM was associated with indices of IR and vitamin D deficiency. However, the exact causal link among POM, IR, and vitamin D needs to be established. However, the results of this pilot study suggest that POM may have potential as a cutaneous non-invasive marker of these metabolic disorders which would assist in detecting and treating them at an early stage.

Keywords

Insulin resistance Periorbital melanosis Skin pigmentation Vitamin D

Introduction

Skin can serve as a window to a patient’s overall health and its changes can occasionally indicate underlying disorders.¹ Periorbital melanosis (POM) is a common benign skin condition that can affect men and women of any age and is characterized by bilateral skin hyperpigmentation that can be periorbital or infraorbital.² POM can occur as a primary disorder independent of any systemic or local illness and in these cases is described as idiopathic cutaneous hyperchromia of the orbital region (ICHOR).³ It can also occur secondary to genetic, constitutional, inflammatory, allergic, or vascular factors.⁴ The degree of pigmentation changes with tiredness, menstrual cycle, and other physical and emotional stressors.⁵

Insulin resistance (IR) is defined as an insufficient insulin response combined with impaired glucose uptake by target tissues (i.e., skeletal muscles, adipose tissue, and liver), that results in hyperinsulinemia, hyperglycaemia, hypertension, dyslipidaemia, visceral obesity, and endothelial dysfunction.^6,7 Several skin disorders such as, acanthosis nigricans, hirsutism, and acne, have been linked with IR because hyperinsulinemia is associated with elevated levels of leptin, testosterone, and insulin-like growth factor-binding protein 3 (IGFBP3); these hormones play an important role in controlling gene expression essential for skin cell proliferation.^8,9 Using cutaneous indicators as a marker of IR would certainly be a convenient, easier, and faster way of identifying the disorder than using standard IR indices such as homeostatic model assessment-insulin resistance (HOMA-IR),⁴ triglycerides/high-density lipoprotein cholesterol (TG/HDL-c) ratio,¹⁰ or the adiponectin/leptin (A/L) ratio.¹¹

Vitamin D is a fat-soluble steroid hormone synthesized in the skin by a photochemical reaction caused by exposure to the sun's ultraviolet B (UVB) wavelength.¹² It is responsible for calcium homeostasis as well as bone and mineral metabolism.^13,14 Age, pigmented skin, use of sunscreen and clothes inhibit vitamin D production.^15,16 Vitamin D deficiency is also linked to several conditions, including IR, cancer, and obesity.^17,18 Importantly, several studies suggest that skin pigmentation is associated with low vitamin D levels.¹⁹

The purpose of this study was to investigate the possible association of POM with three IR indices (i.e., HOMA-IR, TG/HDL-c ratio, and A/L ratio) and vitamin D serum levels in a sample of Egyptian patients with POM and compare the results with matched control subjects. Our aim was to discover a convenient and fast indicator for insulin status and vitamin D deficiency.

Methodology

Subjects

This pilot, case-control study was performed at Ain Shams University Hospital, Cairo, Egypt. A randomly selected sample of 100 adult patients with POM were recruited from the Dermatology Clinic at the hospital. A further 100 age- and sex-matched healthy control subjects were identified from the relatives of the patients attending the clinic. Subjects with overt diabetes or those using glucose-lowering medications or vitamin D supplementation were excluded from the study. The study was approved by the Research Ethics Committee (FMASU R327/2023), Faculty of Medicine, Ain Shams University, Cairo, Egypt. All patients provided written informed consent. All data were collected and retained anonymously. The reporting of this study conforms to STROBE guidelines.²⁰

Clinical evaluation

Detailed medical history was recorded for each participant, including age, family history of POM, history of allergy or atopy, anaemia, endocrine disorders, refraction error, eyestrain, and associated habits or lifestyle. POM diagnosis was made by a dermatologist [M.E.] and depended on the presence of bilateral periorbital round or semi-round homogenous brown pigmentation and skin discoloration compared with other facial skin areas. An eyelid stretch test confirmed POM diagnosis and excluded skin laxity and subdermal vascularity, and a gaze test excluded periorbital oedema.^2,21 POM severity was determined by comparison with the surrounding skin and graded into five categories as follows: 0, no colour change from the rest of the face; I, faint pigmentation in the infraorbital fold; II, more pronounced pigmentation; III, deep dark pigmentation of all eyelid skin; IV, deep dark pigmentation beyond the infraorbital fold.^2,22 The dermatologist also evaluated pigmentation in other areas of the face, such as presence of acanthosis nigricans.²³ Other clinical characteristics, including body mass index (BMI),²⁴ systolic and diastolic blood pressure (BP),²⁵ and waist/hip ratio (WHR),²⁴ were also recorded.

Laboratory investigations

All laboratory investigations were performed at the Central Laboratories of Ain Shams University Hospital according to standard methods. Following a 12 hour-fast, all participants had 5 ml venous blood withdrawn every morning at the same time into a serum separation vacutainer under complete aseptic conditions. Blood was allowed to clot completely before being centrifuged at 3500 rpm for 20 minutes. Separated sera were used immediately to measure the lipid profile (i.e., total cholesterol, triglycerides, and HDL-c), and fasting blood glucose (FBG) using AU680 Beckman Coulter autoanalyzer (Beckman Coulter, Inc., Brea, CA). Sera were stored at −80°C until further analysis. Of the following:

Serum 25-hydroxy vitamin D concentrations using a COBAS e411 electrochemiluminescence autoanalyzer (Roche Diagnostics, Switzerland), according to the manufacturer’s protocol. The detection limit was 4 ng/ml.

Fasting insulin levels in sera using a human enzyme-linked immunosorbent assay (ELISA) kit (Cusabio, Houston, USA; CAT no.: CSB-E05069h) with a detection range of 10 µU/ml–160 µU/ml and a sensitivity of 2 µU/ml.

Leptin levels in sera using a human ELISA kit (Cusabio, Houston, USA; CAT no.: CSB-E04649h), after being diluted by sample diluent (1:5), with a detection range of 0.156 ng/ml–10 ng/ml and a sensitivity of 0.060 ng/ml.

Adiponectin levels in sera using a human ELISA kit (Cusabio, Houston, USA; CAT no.: CSB-E07270h), after being diluted by sample diluent (1:500), with a detection range of 1.562 ng/ml–100 ng/ml and a sensitivity of 1.102 ng/ml. Results were expressed in µg/ml after multiplying by the dilution factor.

Low-density lipoprotein cholesterol (LDL-c) was calculated using the Friedewald formula (i.e., LDL-c mg/dl =Total cholesterol mg/dl – [HDL-c mg/dl + Triglycerides mg/dl/5) if triglyceride levels were <400 mg/dl.²⁶

HOMA-IR using the following formula: (fasting insulin in µU/ml × fasting glucose in mg/dl)/405.²⁷

TG/HDL-c ratio using values in units of mg/dl. High ratios indicate IR.¹⁰

A/L ratio; adiponectin µg/ml divided by leptin ng/ml. Low ratios indicate IR.¹¹

Statistical analysis

Statistical analysis was performed using SPSS software (version 25.0 for Windows®; IBM Corp, Armonk, NY, USA). A P-value <0.5 was considered to indicate statistical significance. Continuous variables were presented as means ± SD and categorical variables were reported as numbers and percentages. Student’s t test was used to compare continuous variables and categorical variables were analysed using χ² tests. Pearson correlation analysis was used to investigate the possible relationship between POM severity and four variables (i.e., IR indices [HOMA-IR; TG/HDL-c ratio; A/L ratio] and vitamin D levels). To investigate the possible predictors of POM severity, the aforementioned four variables were included in univariate and multivariate Cox proportional hazards regression analysis. The results were presented as odds ratio (OR) and 95% confidence intervals (CIs).

To find the most sensitive and specific cut-offs for discrimination of POM grade I from the grades II-IV, receiver operating characteristic (ROC) curves were used to calculate area under the curve (AUC) values to assess the predictive ability of HOMA-IR, A/L ratio, TG/HDL-c ratio and vitamin D, for grade I. Cutoff points were calculated by obtaining the best Youden index (sensitivity + specificity − 1). In addition, a multi-ROC was created to assess the efficacy of combined prediction of POM severity using A/L ratio (1.45) and Vitamin D levels (12 ng/ml).

Results

In total, 100 adult patients with POM and 100 healthy control subjects were included in the study. Details of the participants’ characteristics are shown in Table 1. Overall, there were 112 (52%) women and 88 (44%) men but there was no significant difference in the female-to-male ratio between POM cases and controls. There was also no difference between POM cases and controls in mean age (i.e., 39.6 ± 10.7 vs 38.6 ± 10.7 years). By contrast with control subjects, POM cases had statistically significantly higher values for BMI, WHR, systolic and diastolic BP, fasting insulin, total cholesterol, triglycerides, LDL-c, and leptin. Although there was no difference between groups in FBG, compared with controls, POM cases had statistically significantly higher values of HOMA-IR, and TG/HDL-c ratio than controls (P < 0.001). However, A/L ratio, vitamin D, HDL-c and adiponectin levels were statistically significantly lower in the POM cases compared with controls (P < 0.001).

Table 1.

Participants’ characteristics.

Variable	POM Casesn = 100	Controlsn = 100	Statistical significance
Age, y	39.6 ± 10.7	38.6 ± 10.7	ns
Sex
Female	52 (52)	60 (60)	ns
Male	48 (48)	40 (40)	ns
BMI, kg/m²	29.6 ± 5.8	23.1 ± 2.9	P < 0.001
Systolic BP, mmHg	127 ± 17	120 ± 9	P < 0.001
Diastolic BP, mmHg	81 ± 12	74 ± 8	P < 0.001
Waist-hip ratio	0.87 ± 0.15	0.79 ± 0.07	P < 0.001
Fasting insulin, μU/ml	9.66 ± 6.21	3.74 ± 0.95	P < 0.001
FBG, mg/dl	88.1 ± 22.1	84.6 ± 14.0	ns
HOMA-IR	2.20 ± 1.69	0.77 ± 0.20	P < 0.001
Total cholesterol, mg/dl	160 ± 76	109 ± 12	P < 0.001
Triglycerides, mg/dl	127.1 ± 64.5	84.0 ± 12.2	P < 0.001
HDL-c, mg/dl	38.3 ± 5.1	39.9 ± 3.4	P = 0.013
LDL-c, mg/dl	96.0 ± 64.9	55.2 ± 13.7	P < 0.001
TG/HDL-c ratio	3.5 ± 2.3	2.1 ± 0.3	P < 0.001
Leptin, ng/ml	22.4 ± 6.5	14.8 ± 1.6	P < 0.001
Adiponectin, µg/ml	18.7 ± 5.6	22.7 ± 5.3	P < 0.001
A/L ratio	0.9 ± 0.5	1.5 ± 0.4	P < 0.001
Vitamin D, ng/ml	17.4 ± 6.5	24.1 ± 4. 8	P < 0.001

Data are expressed as, n (%) or mean ± standard deviation.

Abbreviations: A/L ratio: adiponectin/leptin ratio; BMI: body mass index; BP: blood pressure; FBG: fasting blood glucose; HDL-c: high density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; LDL-c: low density lipoprotein cholesterol; POM, periorbital melanosis.

Most POM cases (65%) were of grade II severity (Figure 1). The next most common severity grade was grade I (26%), followed by grade IV (5%) and grade III (4%). The most commonly conditions noted in the POM cases were: positive family history of POM (78%); history of anaemia (52%); stress or anxiety (39%); inadequate sleep (39%); smoking (38%). We also noticed pigmentation in other face areas in 14% cases and acanthosis nigricans in 12% cases (Table 2).

Figure 1.

Distribution of periorbital melanosis (POM) severity grades (I-IV) among cases (n = 100).

Table 2.

Conditions noted in POM cases.

Condition	% of POM cases
Family history of POM	78
Anaemia	52
Stress/Anxiety	39
Inadequate sleep	39
Smoking	38
Refraction error/eye strain	32
Premenstrual aggravation	27
Atopy/Allergy	19
Pigmentation in other face areas	14
Endocrine disorders	13
Acanthosis nigricans	12

Abbreviations: POM, periorbital melanosis.

Vitamin D (r: −0.745; P < 0.001) and A/L ratio (r: −0.635; P < 0.001) were statistically significantly negatively correlated with POM severity while HOMA-IR (r: 0.431; P < 0.001) and TG/HDL-c ratio (r: 0.363; P < 0.001) were statistically significantly positively correlated (Figure 2).

Figure 2.

Correlation of three insulin resistance (IR) indices (i.e., homeostatic model assessment-insulin resistance [HOMA-IR], adiponectin/leptin ratio [A/L ratio], triglycerides high density lipoprotein cholesterol (TG/HDL-c) and vitamin D with POM severity (n = 100). Vitamin D and A/L ratio showed statistically significantly negative correlations with periorbital melanosis (POM) severity, while HOMA-IR and TG/HDL-c ratio showed statistically significant positive correlations (P < 0.001).

Multivariate regression analysis showed that only vitamin D serum level was a statistically significant (P = 0.007) independent risk factor for POM severity with an odds ratio (OR) of 3.99 and 95% CIs 1.46–10.89 (Table 3). A diagnostic validity test showed that the highest efficacies were for A/L ratio and vitamin D (95% and 90%, respectively). The multi-ROC of their combination (i.e., A/L ratio 1.45 and vitamin D 12 ng/ml) gave a final efficacy of 98%, a diagnostic sensitivity of 95%, a diagnostic specificity of 95%, a negative predictive value of 82% and a positive predictive value 99% (Figure 3).

Table 3.

Regression analyses for predictors of POM severity.

Variable	Univariate analysis			Multivariate analysis
Variable	OR	95% CI	Statistical significance	OR	95%CI	Statistical significance
HOMA.IR	11.45	6.02–19.34	P = 0.001	2.05	1.05–4.08	ns
TG/HDL-c ratio	5.56	2.77–9.23	P < 0.001	2.12	0.63–2.65	ns
A/L ratio	6.03	2.56–10.43	P < 0.001	0.81	0.37–1.79	ns
Vitamin D	3.30	1.69–7.26	P = 0.003	3.99	1.46–10.89	P = 0.007

Abbreviations: OR, odds ratio; CI, confidence interval; A/L ratio: adiponectin/leptin ratio; HDL-c: high density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; POM, periorbital melanosis; TG: triglycerides.

Figure 3.

Receiver operating characteristic (ROC) curve analysis showing the predictive ability of vitamin D levels and insulin resistance (IR) indices (i.e., HOMA-IR, TG/HDL-c ratio, and A/L ratio) for discriminating grades (I vs II-IV) of periorbital melanosis (POM) patients. Abbreviations: A/L ratio: adiponectin/leptin ratio; HDL-c: high density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; NDL: non-diagnostic line; Sn: Sensitivity; Sp: Specificity; TG: triglycerides.

Table 4.

Receiver operating characteristic (ROC) curve analysis to assess the predictive ability of variables for grade I POM

Variable	Cut off	AUC	95 % CI	SP%	SN%	PN%	PP%	Eff%
HOMA-IR	0.89	0.79	0.66–0.92	60	84	74	43	88
TG/HDL-c ratio	2.08	0.73	0.60–0.87	64	53	79	37	88
A/L ratio	1.45	0.82	0.69–0.94	60	95	73	91	95
Vitamin D	12 ng/ml	0.68	0.54–0.82	53	96	77	90	90
Multi-ROC	A/L ratio 1.45 Vitamin D 12 ng/ml	0.96	0.89–1.02	95	95	82	99	98

Abbreviations: A/L ratio: adiponectin/leptin ratio; AUC: Area under curve; CI: confidence interval; Eff: Efficacy; HDL-c: high density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; PN: Negative predictive value; PP: Positive predictive value; SN: Sensitivity; SP: Specificity; POM, periorbital melanosis; TG: triglycerides.

Discussion

POM is a prevalent cosmetic dermatological condition and a complex disorder which is thought to occur as a consequence of several factors including genetic, lifestyle and medical.²⁸ Its use as a cutaneous marker of IR is uncertain. IR is considered an early subclinical stage in the progression of impaired glucose tolerance and diabetes. Identifying people with IR using an easy, rapid, and non-invasive indicator such as a cutaneous marker, will undoubtedly facilitate early intervention and prevention of diabetes and metabolic syndrome.⁴ Therefore, the aim of the current study was to investigate if an association between POM severity and three IR indices (i.e., HOMA-IR, TG/HDL-c ratio, and A/L ratio) existed. In addition, we investigated the possible interaction between POM severity and vitamin D levels. For this study we used 100 patients with POM and 100 healthy age- and sex-matched control subjects.

Unlike two previous studies that found POM was most common in young female adults,^28,29 the mean age of our patients was 39.6 years and there was no significant difference in female-to-male ratio of cases. However, similar to a previous study most of our patients (65%) had grade II POM.²⁸ Consistent with previous findings, we found that the most commonly associated conditions with POM were positive family history of POM and history of anaemia.^2,30,31

Our study showed that POM severity was significantly positively correlated with the IR indices, HOMA-IR and TG/HDL-c ratio, and significantly negatively correlated with the A/L ratio. In addition, our POM patients had higher BMI, BP, WHR, total cholesterol LDL-c, fasting insulin, FBG and leptin levels, than the matched control subjects. These results are similar to those from a previous study, also in 100 POM patients and 100 healthy matched controls, that reported serum levels of leptin, FBG, fasting insulin, HOMA-IR, and A/L ratio were higher in POM patients than in controls.

It has been suggested that POM is a proinflammatory disorder linked to post-inflammatory conditions such as atopic and allergic contact dermatitis.² Interestingly, several studies have linked IR to inflammation; proinflammatory cytokines can disrupt insulin signalling in target tissues, decreasing glucose uptake and utilization in response to normal insulin levels resulting in compensatory hyperinsulinemia and hyperglycaemia as well as metabolic syndrome.^6,7,32–34 Previously, studies have linked increased levels of leptin to both BMI and IR; leptin is a proinflammatory cytokine that promotes inflammation by trigging interleukin-6 (IL-6) and C-reactive protein (CRP) generation.^35–38

We found that vitamin D serum levels were significantly lower among POM patients than controls and were significantly negatively correlated with POM severity. Consistent with our findings, several studies have reported that skin pigmentation was associated with low vitamin D levels.^19,39 Another explanation for the decreased vitamin D levels among our POM patients is that they had a higher BMI and WHR than controls. Vitamin D is fat-soluble and easily retained in adipose tissue, suggesting that it may be sequestered in excess body fat in obese people.⁴⁰ To our knowledge, there are no previous studies investigating vitamin D levels and their significance in POM cases. However, we identified various publications that linked vitamin D with other skin pigmentation disorders, such as, acanthosis nigricans and vitiligo.^41,42 We found that vitamin D serum levels and the A/L ratio were the best predictors of POM severity; their combination in a multi-ROC raised the diagnostic efficacy to 98%.

The study had several limitations including its single-centre design and a relatively small sample size. In addition, although we observed associations among the parameters, we did not establish a causal link. Future controlled investigations involving a large, multicentre population are required to confirm out results.

In conclusion, our study showed that POM, IR, and vitamin D deficiency were strongly associated. However, vitamin D deﬁciency is thought to be involved in several cardiometabolic disorders, including IR and diabetes.^43–49 Therefore, the exact causal link among POM, IR, and vitamin D needs to be established. However, the results of this pilot study suggest that POM may have potential as a cutaneous non-invasive marker of these metabolic disorders which would assist in detecting and treating them at an early stage.

Footnotes

Declaration of conflicting interests

The authors declare there are no conflicts of interest.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

ORCID iD

Sara I. Taha

References

Napolitano M, Megna M and Monfrecola G. Insulin resistance and skin diseases. ScientificWorldJournal 2015; 2015: 479354.

Sheth PB, Shah HA and Dave JN. Periorbital hyperpigmentation: a study of its prevalence, common causative factors and its association with personal habits and other disorders. Indian J Dermatol 2014; 59: 151–157.

Verschoore M, Gupta S, Sharma VK, et al. Determination of Melanin and Haemoglobin in the Skin of Idiopathic Cutaneous Hyperchromia of the Orbital region (ICHOR): A Study of Indian Patients. J Cutan Aesthet Surg 2012; 5: 176–182.

Thappa DM, Chandrashekar L, Rajappa M, et al. Assessment of Patients with Periorbital Melanosis for Hyperinsulinemia and Insulin Resistance. Indian Dermatol Online J 2021; 12: 244–249.

Roh MR and Chung KY. Infraorbital dark circles: definition, causes, and treatment options. Dermatol Surg 2009; 35: 1163–1171.

Lebovitz HE. Insulin resistance: definition and consequences. Exp Clin Endocrinol Diabetes 2001; 109: S135–48.

Pedersen O. [Insulin resistance–a physiopathological condition with numerous sequelae: non-insulin-dependent diabetes mellitus (NIDDM), android obesity, essential hypertension, dyslipidemia and atherosclerosis]. Ugeskr Laeger 1992; 154: 1411–1418. [Article in Danish].

El Safoury OS, Shaker OG and Fawzy MM. Skin tags and acanthosis nigricans in patients with hepatitis C infection in relation to insulin resistance and insulin like growth factor-1 levels. Indian J Dermatol 2012; 57: 102–106.

Patidar PP, Ramachandra P, Philip R, et al. Correlation of acanthosis nigricans with insulin resistance, anthropometric, and other metabolic parameters in diabetic Indians. Indian J Endocrinol Metab 2012; 16 (Suppl 2): S436–S437.

10.

Uruska A, Zozulinska-Ziolkiewicz D, Niedzwiecki P, et al. TG/HDL-C ratio and visceral adiposity index may be useful in assessment of insulin resistance in adults with type 1 diabetes in clinical practice. J Clin Lipidol 2018; 12: 734–740.

11.

Frühbeck G, Catalán V, Rodríguez A, et al. Adiponectin-leptin Ratio is a Functional Biomarker of Adipose Tissue Inflammation. Nutrients 2019; 11: 454.

12.

AlGhamdi K, Kumar A and Moussa N. The role of vitamin D in melanogenesis with an emphasis on vitiligo. Indian J Dermatol Venereol Leprol 2013; 79: 750–758.

13.

Miao Z, Wang S, Wang Y, et al. A Potential Linking between Vitamin D and Adipose Metabolic Disorders. Can J Gastroenterol Hepatol 2020; 2020: 2656321.

14.

Polzonetti V, Pucciarelli S, Vincenzetti S, et al. Dietary Intake of Vitamin D from Dairy Products Reduces the Risk of Osteoporosis. Nutrients 2020; 12: 1743.

15.

Lips P. Vitamin D physiology. Prog Biophys Mol Biol 2006; 92: 4–8.

16.

Loomis WF. Skin-pigment regulation of vitamin-D biosynthesis in man. Science 1967; 157: 501–506.

17.

Wimalawansa SJ. Associations of vitamin D with insulin resistance, obesity, type 2 diabetes, and metabolic syndrome. J Steroid Biochem Mol Biol 2018; 175: 177–189.

18.

Amrein

Scherkl

Hoffmann

, et al. Vitamin D deficiency 2.0: an update on the current status worldwide. Eur J Clin Nutr. 2020; 74(11): 1498–1513. doi: 10.1038/s41430-020-0558-y. Epub 2020 Jan 20. PMID: 31959942; PMCID: PMC7091696.

19.

Libon F, Cavalier E and Nikkels AF. Skin color is relevant to vitamin D synthesis. Dermatology 2013; 227: 250–254.

20.

Von Elm E, Altman DG, Egger M, STROBE Initiative, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61: 344–349.

21.

Kartha NS and Kunjukunju BP. A Clinico Epidemiological Study of Periocular Hyperpigmentation. J Evolution Med Dent Sci 2020; 9: 687–691.

22.

Ranu H, Thng S, Goh BK, et al. Periorbital hyperpigmentation in Asians: an epidemiologic study and a proposed classification. Dermatol Surg 2011; 37: 1297–1303.

23.

Das A, Datta D, Kassir M, et al. Acanthosis nigricans: A review. J Cosmet Dermatol 2020; 19: 1857–1865.

24.

Folsom AR, Stevens J, Schreiner PJ, et al. Body mass index, waist/hip ratio, and coronary heart disease incidence in African Americans and whites. Atherosclerosis Risk in Communities Study Investigators. Am J Epidemiol 1998; 148: 1187–1194.

25.

Tholl U, Forstner K and Anlauf M. Measuring blood pressure: pitfalls and recommendations. Nephrol Dial Transplant 2004; 19: 766–770.

26.

Friedewald WT, Levy RI and Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18: 499–502.

27.

Wallace TM, Levy JC and Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27: 1487–1495.

28.

David BG, R RM and Shankar R. A clinico-epidemiological study of periorbital melanosis. Int J Res Dermatol 2017; 3: 245. Available from medip,+IJORD-133+O (3).pdf.

29.

Mendiratta V, Rana S, Jassi R, et al. Study of Causative Factors and Clinical Patterns of Periorbital Pigmentation. Indian Dermatol Online J 2019; 10: 293–295.

30.

Goodman RM and Belcher RW. Periorbital hyperpigmentation. An overlooked genetic disorder of pigmentation. Arch Dermatol 1969; 100: 169–174..

31.

Strachan T and Read AP. Genes in pedigrees and population. In: Strachan T, editor. Human Molecular Genetics. 3rd edition. New York: Garland Science; 2003: 106–107.

32.

Matulewicz N and Karczewska-Kupczewska M. Insulin resistance and chronic inflammation. Postepy Hig Med Dosw (Online) 2016; 70: 1245–1258.

33.

Shoelson SE, Lee J and Goldfine AB. Inflammation and insulin resistance. J Clin Invest 2006; 116: 1793–1801.

34.

Olefsky JM and Glass CK. Macrophages, inflammation, and insulin resistance. Annu Rev Physiol 2010; 72: 219–246.

35.

Wannamethee SG, Tchernova J, Whincup P, et al. Plasma leptin: associations with metabolic, inflammatory and haemostatic risk factors for cardiovascular disease. Atherosclerosis 2007; 191: 418–426.

36.

Abdella NA, Mojiminiyi OA, Moussa MA, et al. Plasma leptin concentration in patients with Type 2 diabetes: relationship to cardiovascular disease risk factors and insulin resistance. Diabet Med 2005; 22: 278–285.

37.

Uslu S, Kebapçi N, Kara M, et al. Relationship between adipocytokines and cardiovascular risk factors in patients with type 2 diabetes mellitus. Exp Ther Med 2012; 4: 113–120.

38.

Asakawa H, Tokunaga K and Kawakami F. Relationship of leptin level with metabolic disorders and hypertension in Japanese type 2 diabetes mellitus patients. J Diabetes Complications 2001; 15: 57–62.

39.

Wolf

Dillon

Alexander

, et al. Skin pigmentation is negatively associated with circulating vitamin D concentration and cutaneous microvascular endothelial function. Am J Physiol Heart Circ Physiol. 2022; 323(3): 490–498. doi: 10.1152/ajpheart.00309.2022. Epub 2022 Aug 5. PMID: 35930446; PMCID: PMC9448272.

40.

Holick MF. Vitamin D deficiency. N Engl J Med 2007; 357: 266–281.

41.

Sehrawat M, Arora TC, Chauhan A, et al. Correlation of Vitamin D Levels with Pigmentation in Vitiligo Patients Treated with NBUVB Therapy. ISRN Dermatol 2014; 2014: 493213.

42.

Slyper AH, Kashmer L, Huang WM, et al. Acanthosis nigricans, vitamin D, and insulin resistance in obese children and adolescents. J Pediatr Endocrinol Metab 2014; 27: 1107–1111.

43.

Sung CC, Liao MT, Lu KC, et al. Role of vitamin D in insulin resistance. J Biomed Biotechnol 2012; 2012: 634195.

44.

Parker J, Hashmi O, Dutton D, et al. Levels of vitamin D and cardiometabolic disorders: systematic review and meta-analysis. Maturitas 2010; 65: 225–236.

45.

Li YC. Vitamin D regulation of the renin-angiotensin system. J Cell Biochem 2003; 88: 327–331.

46.

Chiu KC, Chu A, Go VL, et al. Hypovitaminosis D is associated with insulin resistance and beta cell dysfunction. Am J Clin Nutr 2004; 79: 820–825.

47.

Zittermann A. Vitamin D and disease prevention with special reference to cardiovascular disease. Prog Biophys Mol Biol 2006; 92: 39–48.

48.

Li YC, Pirro AE, Amling M, et al. Targeted ablation of the vitamin D receptor: an animal model of vitamin D-dependent rickets type II with alopecia. Proc Natl Acad Sci U S A 1997; 94: 9831–9835.

49.

Panda DK, Miao D, Tremblay ML, et al. Targeted ablation of the 25-hydroxyvitamin D 1alpha -hydroxylase enzyme: evidence for skeletal, reproductive, and immune dysfunction. Proc Natl Acad Sci U S A 2001; 98: 7498–7503.

Periorbital melanosis and its possible association with insulin resistance and vitamin D deficiency: A pilot case-control study

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Methodology

Subjects

Clinical evaluation

Laboratory investigations

Statistical analysis

Results

Discussion

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

References