nach oben

Journal of Endocrinological Investigation

Erschienen in:

Open Access 13.10.2023 | Original Article

Adiponectin rs1501299 and chemerin rs17173608 gene polymorphism in children with type 1 diabetes mellitus: relation with macroangiopathy and peripheral artery disease

verfasst von: N. Y. Salah, S. S. Madkour, K. S. Ahmed, D. A. Abdelhakam, F. A. Abdullah, R. A. E. H. Mahmoud

Erschienen in: Journal of Endocrinological Investigation | Ausgabe 4/2024

Abstract

Aim

Although macrovascular complications represent the leading cause of mortality in type 1 diabetes mellitus (T1DM), the prevalence of subtle macrovascular affection including peripheral artery disease (PAD) among children with T1DM and its genetic predictors remains to be unraveled. Increasing evidence suggests a link between adiponectin rs1501299 and chemerin rs17173608 gene polymorphism and atherogenesis, and insulin resistance. Hence, this study assess the prevalence of these variants among children with T1DM in comparison to healthy controls and their association with macrovascular complications, namely PAD and hyperlipidemia.

Methods

Fifty children with T1DM and 50 matched controls underwent a thorough assessment including adiponectin rs1501299 and chemerin rs17173608 gene polymorphisms, fasting lipids, glycated hemoglobin (HbA1c), and ankle–brachial index (ABI). Cochran–Armitage trend test was used to decide the risk allele and evaluate the association between the candidate variant and PAD using a case–control design.

Results

Children with T1DM were found to have significantly higher ABI (p = 0.011) than controls. Chemerin gene polymorphism was detected in 41 children with T1DM (82.0%), while adiponectin gene polymorphism was detected in 19 children (38.0%). Children with T1DM having GG chemerin variant and those having TT adiponectin variant had significantly higher cholesterol with significantly lower HDL-C and ABI than those having the other two variants (p < 0.005). Children with T1DM having abnormal ABI had significantly higher chemerin G (p = 0.017) and adiponectin T (p = 0.022) alleles than those with normal ABI. Cholesterol and ABI were independently associated with chemerin and adiponectin gene polymorphism by multivariable regression analysis.

Conclusion

Children with T1DM having chemerin and adiponectin gene polymorphisms have significantly higher cholesterol and ABI than those without these polymorphisms and controls.

Trial registration

The Research Ethics Committee of Ain Shams University, approval number R 31/2021.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

ABI

Ankle–brachial index

BMI

Body mass index

HDL-C

High-density lipoproteins

IQR

Inter-quartile range

LDL

Low-density lipoproteins

MODY

Maturity-onset diabetes of the youth

PAD

Peripheral artery disease

RARRES2

Retinoic acid receptor responder 2

ROC

Receiver operating characteristic

T1DM

Type 1 diabetes

T2DM

Type 2 diabetes

Introduction

Diabetes with its two major types, type 1 (T1DM) and type 2 (T2DM), has long been recognized as a major risk factor for the development of vascular disease [1]. In adults, macrovascular complications are the leading cause of diabetes-related morbidity and mortality, namely coronary, cerebrovascular, and peripheral arterial disease (PAD) [2]. However, in childhood T1DM, the role of macrovascular complications is underestimated with more focus on diabetic microvascular complications.

While macrovascular complications are rare until adulthood, early subtle macrovascular changes have been shown to present since childhood, making children with T1DM at risk of early adult-onset vascular disease [3]. Predictors of PAD include glycemic and lipid derangements, diabetes duration, hypertension, and male gender [4]. However, not all people with T1DM having poor glycemic and lipid control develop PAD. Moreover, aggressive glycemic control to lower the HbA1c did not appear to reduce the rate of PAD in those at risk as observed in the DCCT/EDIC study [5]. Hence, understanding the genetic determinants of the risk of PAD among this vulnerable population is of utmost importance.

Ankle–brachial index (ABI), i.e., the ratio of ankle-to-brachial systolic blood pressure, is the gold standard noninvasive method for PAD diagnosis [6]. According to the AHA, an ABI ≤ 0.90 is considered PAD. ABI can detect PAD, with > 50% stenosis with sensitivity 61–73% and specificity 83–96% [7].

Increasing evidence suggests a link between adipokines, diabetes, and vascular diseases including PAD [8]. Two of the most well-known adipokines, adiponectin and chemerin, have been associated with metabolic, inflammatory, and atherosclerotic diseases. Serum adiponectin levels have been associated with vascular events and/or mortality from vascular diseases [9]. Chemerin, an adipokine highly expressed in the white adipose tissue, is associated with inflammation and adipogenesis. Chemerin not only regulates the expression of adipocyte genes linked with glucose and lipid homeostasis, but also affects innate and adaptive immunity as well as cytokine homeostasis. Furthermore, it has a role in fibrinolysis, coagulation, and inflammation [10]. Hence, adipokines could serve as a mechanistic link between diabetes, metabolic derangements, and PAD. There remains uncertainty, however, about the strength of associations between PAD and individual adipokines with some studies suggesting that these associations are mediated through diabetes [11].

Adiponectin level is influenced by the presence of genetic variation in its coding genes. Polymorphisms in ADIPOQ, which codes for adiponectin, have been associated with diabetes and metabolic syndrome in multiple populations [12]. Nonetheless, genetic variation in the ADIPOQ promoter has been associated with vascular disease independent of adiponectin level [13].

Variants of retinoic acid receptor responder 2 (RARRES2), the gene encoding chemerin, have been demonstrated to be associated with increased chemerin levels, visceral fat mass in nonobese individuals, and increased incidence of metabolic syndrome [14]. Several experimental studies suggest an inflammatory role for chemerin during the early stages of vascular diseases [15]. But it is currently still not clear whether an association between chemerin gene polymorphism and PAD exists. Some case–control studies have shown that higher circulating chemerin levels are associated with clinical and subclinical vascular diseases [16, 17], whereas others did not confirm these findings [18, 19].

Hence, this study aims to assess the frequency of adiponectin and chemerin gene polymorphism among children with T1DM in comparison to healthy control and to investigate their potential association with macrovascular complications, namely PAD and hyperlipidemia among this vulnerable cohort.

Methodology

Study design

This cross-sectional controlled study included 50 children with T1DM and 50 age—and gender-matched healthy controls. Children with T1DM were recruited from the pediatric and adolescents diabetes unit, Ain Shams University, while the controls were recruited from the outpatient clinic during the period from December 2021 to May 2022. T1DM was defined according to the criteria of the International Society of Pediatric and Adolescent Diabetes [20]. Inclusion criteria for T1DM children were age 8–18 years and diabetes duration of ≥ 1 year. Exclusion criteria included patients with other types of diabetes, e.g., T2DM and maturity-onset diabetes of the youth (MODY), patients with obesity, hypertension, or cardiovascular diseases, and patients with comorbid disorders that might cause PAD, e.g., systemic lupus and autoimmune thyroiditis.

Ethical considerations

The study was approved by the Research Ethics Committee of Ain Shams University with an approval number of R 31/2021. Written informed consent was obtained from each subject and his legal guardian before enrollment in the study.

Procedure

Clinical assessment

All included children were subjected to thorough medical history including patients' age, gender, family history of T1DM, diabetes duration, insulin therapy, and history of chronic microvascular diabetic complications (retinopathy, neuropathy, and nephropathy).

Clinical examination was done laying stress on anthropometric measures with the calculation of standard deviation score and body mass index (BMI) measured as kg/m² [21].

Blood pressure (BP) was measured manually, two consecutive times, by a sphygmomanometer in the right arm of a relaxed, seated child with comparison of values to normal reference percentiles [22].

Laboratory assessment

Blood sampling

All blood samples were drawn after an overnight (10–12 h) fasting. Under complete aseptic condition, ten (10) mL of venous blood was withdrawn by venipuncture from each subject. Samples were divided into three aliquots: the first one was collected in vacutainer tubes (BD Diagnostics) containing tri-potassium ethylenediaminetetraacetate (k3 EDTA) and mixed gently and transferred immediately into appropriate containers in the laboratory, whereby DNA extraction was performed, and the DNA yields were stored at − 80 °C for genotyping.

The second aliquot was collected in plain vacutainer tubes for serum preparation. The serum is intended for measurement of lipid profile. The third aliquot was separated on ethylenediaminetetraacetic acid (1.2 mg/mL) for analysis of HbA1c.

DNA isolation and single-gene polymorphism genotyping

Genomic DNA was extracted from peripheral blood leukocytes using DNA purification mini-kit; QIAamp^® (Qiagen, Switzerland). All centrifugation steps for QIAamp mini spin columns were done at 6000 × g (8000 rpm) for 1 min at room temperature. The concentration and purity of the isolated DNA were checked using UV–vis absorption spectroscopy at λ260 nm by the Invitrogen Qubit^® 3.0 Fluorometer to measure the quantity of extracted DNA.

The genes chemerin [rs17173608 (T > G)] located in chromosome 7:150339575 (GRCh38.p13) within the noncoding regions and adiponectin [rs1501299 (G > T)] located in chromosome 3:186853334 (GRCh38.p13) within the adiponectin gene intron variant listed in the National Center for Biotechnology Information SNP database (http://www.ncbi.nlm.nih.gov/SNP) [23] were analyzed by RT-PCR using TaqMan^® genotyping master mix (Applied Biosystems, USA).

Genotyping of chemerin rs17173608 and adiponectin rs1501299 variant was performed using TaqMan allelic discrimination assay as recommended by Applied Biosystems International (ABI) [24], using the readymade genotyping assay kit supplied by ThermoFisher^® (ThermoFisher Scientific, USA) containing sequence-specific forward and reverse primers and two fluorescents (VIC/FAM) labeled TaqMan probes for distinguishing between the two alleles. The presence to the absence of the SNP and the allelic discrimination was established according to the type of the emitted fluorescence of either of the reporter dyes or both at the same time.

The reaction plates were loaded into the DT-lite Real-Time PCR System and amplification was performed according to the following protocol: initial heat activation at 95 °C for 10 min, DNA denaturation at 95 °C for 15s, followed by annealing at 60 °C for 60s for 40 cycles.

The data were analyzed and presented on the multicomponent plot for allelic discrimination of alleles.

1 versus Allele.

2 using Applied.

Biosystem, step I version software analysis modules.

Biochemical assessment

Fasting triglycerides, high-density lipoproteins (HDL-C), and total cholesterol were measured by standard automated methods on AU680 Beckman Coulter autoanalyzer (Beckman Coulter, Inc., Brea, CA) at Central Laboratories at Ain Shams Hospitals. LDL-C was estimated by Friedewald equation. Results were clinically interpreted according to recommendations of the European Atherosclerosis Society [25]. HbA1c was assessed using D-10 (Bio-Rad, France) [26].

Radiological assessment

The ankle–brachial index was assessed by two blinded experienced radiologists who assessed the patients separately and the mean score of both was taken for each subject. The subject was instructed to lie in the supine position. For measuring the brachial pressure, a fitting sphygmomanometer cuff was placed on the arm, with the upper limb at the same level as the heart. The ultrasound probe was put on the patient's antecubital fossa over the site of brachial artery pulsation. The cuff was inflated to about 10–20 mmHg above the expected systolic blood pressure of the patient till the duplex color and pulsed wave signal disappeared. Then slowly the cuff was deflated at approximately 1 mmHg/s. The brachial systolic pressure is the pressure when the duplex color and pulse wave signal re-appeared.

For assessing the ankle pressure, the sphygmomanometer cuff was placed just proximal to the malleoli. The ultrasound probe was placed slightly lateral to the midline of the dorsum of the foot to detect the dorsalis pedis color flow and pulse wave signal to measure the systolic blood pressure in the same steps done in the brachial artery systolic blood pressure measurement. Then the ultrasound probe was located posterior to the medial malleolus to detect the color flow and pulse wave signal of the posterior tibial artery in the foot. Both measurements were recorded on both legs.

The ABI was calculated for each leg separately by taking the higher pressure of the dorsalis pedis artery and posterior tibial artery and dividing it by the highest brachial arterial systolic pressure in both arms. Then the mean ABI was calculated for each subject [27].

Statistical analysis

Data were collected, revised, coded, and entered into the Statistical Package for Social Science (IBM SPSS) version 25. The Kolmogorov–Smirnov test was used to examine the normality of data. Quantitative data were presented as mean, standard deviations, and ranges when their distribution was found parametric and median with inter-quartile range (IQR) when their distribution was found non-parametric. Qualitative data were presented as numbers and percentages. The one-way ANOVA test was used to compare parametric data sets, whereas non-parametric variables were compared using the Mann–Whitney test. Qualitative variables were compared using Chi-square (X²) test. To validate that genotype distribution follows Hardy–Weinberg equilibrium (HWE) model, goodness-of-fit Chi-square test was used. A Cochran–Armitage trend test was used to decide the risk allele and evaluate the association between the candidate variant and PAD using a case–control design [28]. Before multiple linear regression analysis, several variables were log-transformed to obtain an approximate normal distribution. Simple regression analysis was first performed to screen potential associations, followed by a multivariate stepwise linear regression model to identify and determine significant associations for chemerin and adiponectin gene polymorphism. Using the approach of stepwise variable selection, stepping up, only variables with a significance level of 0.05 were included in the model. Spearman correlation coefficients were used to assess the correlation between two quantitative parameters in the same group. The confidence interval was set to 95% and the margin of error accepted was set to 5%. So, the p value was considered significant at the level of < 0.05.

Results

Fifty children with T1DM (26 males and 24 females; ratio 1.08:1) were studied. Their mean age was 11.09 ± 2.26 years, range 8–16, and their mean HbA1c was 9.72 ± 2.03%, range 6.6–13.7. They were compared to 50 age—and gender-matched healthy controls (p = 0.07 and p = 0.42, respectively). The clinical, laboratory, and radiological data of the studied children with T1DM and controls are listed in Table 1.

Table 1

Clinico-laboratory and radiological characteristics of the studied children with T1DM and controls

		Children with T1DM	Controls	P value
		No. = 50	No. = 50	P value
Clinico-demographic data
Age (years)	Mean ± SD	11.09 ± 2.26	10.22 ± 2.47	0.070•
Age (years)	Range	8–16	6.08 ± 13.07	0.070•
Gender	Female	24 (48.0%)	20 (40.0%)	0.420*
Gender	Male	26 (52.0%)	30 (60.0%)	0.420*
Weight Z-score	Median(IQR)	− 0.75 (− 1.09 to − 0.11)	− 0.99 (− 1.12 to − 0.68)	0.076^‡
Weight Z-score	Range	− 1.78 to 0.56	− 1.2 to − 0.27	0.076^‡
Height Z-score	Median(IQR)	− 0.59 (− 1.16 to 0.55)	− 0.8 (− 1.54 to − 0.13)	0.055^‡
Height Z-score	Range	− 2.39 to 1.72	− 1.73 to 0.73	0.055^‡
BMI (kg/m²)	Mean ± SD	16.95 ± 1.85	16.39 ± 1.37	0.091•
BMI (kg/m²)	Range	13.85–20.93	13.85–19.76	0.091•
BMI Z-score	Median(IQR)	− 0.79 (− 0.86 to − 0.58)	− 0.79 (− 0.85 to − 0.72)	0.403^‡
BMI Z-score	Range	− 1.03 to − 0.31	− 1.03 to − 0.43	0.403^‡
Systolic blood pressure percentile	Mean ± SD	60.40 ± 17.72	55.60 ± 14.02	0.136•
Systolic blood pressure percentile	Range	50–90	50–90	0.136•
Diastolic blood pressure percentile	Mean ± SD	57.20 ± 15.52	55.60 ± 14.02	0.590•
Diastolic blood pressure percentile	Range	50–90	50–90	0.590•
Laboratory data
Cholesterol (mg/dl)	Mean ± SD	179.31 ± 50.58	153.12 ± 19.52	0.001•
Cholesterol (mg/dl)	Range	35–285	123–179	0.001•
HDL (mg/dl)	Mean ± SD	46.60 ± 11.49	58.28 ± 5.56	< 0.001•
HDL (mg/dl)	Range	30–70	48–68	< 0.001•
LDL (mg/dl)	Mean ± SD	109.30 ± 40.12	101.42 ± 18.96	0.212•
LDL (mg/dl)	Range	22–201	69–129	0.212•
Triglycerides (mg/dl)	Mean ± SD	115.49 ± 94.86	86.26 ± 16.16	0.034•
Triglycerides (mg/dl)	Range	25–503	48–114	0.034•
HbA1C%	Mean ± SD	9.72 ± 2.03	4.49 ± 0.50	< 0.001•
HbA1C%	Range	6.6–13.7	3.7–5.3	< 0.001•
Chimerin (RS17173608)	TT	3 (6.0%)	12 (24.0%)	0.041*
	TG	6 (12.0%)	5 (10.0%)
	GG	41 (82.0%)	33 (66.0%)
	T/G	0.12/0.88	0.29/0.71	0.003
Adiponectin (RS1501299)	GG	21 (42.0%)	31 (62.0%)	0.011*
	GT	10 (20.0%)	13 (26.0%)
	TT	19 (38.0%)	6 (12.0%)
	G/T	0.52/0.48	0.75/0.25	0.001
Radiological data
Ankle–brachial index	Mean ± SD	0.86 ± 0.26	1.05 ± 0.13	0.011•
Ankle–brachial index	Range	0.5–1.5	0.92–1.17	0.011•

Bold values indicates significant values

T1DM type 1 diabetes mellitus; BMI body mass index; HbA1C glycated hemoglobin; LDL low-density lipoproteins; HDL high-density lipoproteins

*Chi-square test

•Independent t test

^‡Mann–Whitney test; p value < 0.05: significant

Peripheral artery disease among children with T1DM

The mean ankle–brachial index of the studied children with T1DM was 0.86 ± 0.26; range 0.5–1.5, while that of the controls was 1.05 ± 0.13; range 0.92–1.17. Children with T1DM had significantly lower ABI than controls (p = 0.011).

Although ABI was significantly correlated to diabetes duration (r = 0.450), insulin dose (r = 0.318), cholesterol (r = 0.336), LDL (r = 0.441) and negatively correlated to HDL (r = − 0.280) among the studied children with T1DM, it was not correlated to HbA1C (r = 0.129), Table 2.

Table 2

Correlation of ankle–brachial index with various clinico-laboratory parameters among the studied children with T1DM

	Ankle–brachial index
	r	P value
Age (years)	− 0.188	0.192
Diabetes duration (years)	0.450**	0.001
Weight z-score	0.199	0.165
Height z-score	0.324*	0.022
BMI z-score	0.064	0.660
Insulin dosage (IU/kg/day)	0.318*	0.024
Cholesterol (mg/dl)	0.336*	0.017
HDL (mg/dl)	− 0.280*	0.049
LDL (mg/dl)	0.441**	0.001
Triglycerides (mg/dl)	0.005	0.975
HbA1C%	0.129	0.374

Bold values indicates significant values

T1DM type 1 diabetes mellitus; BMI body mass index; HbA1C glycated hemoglobin; LDL low-density lipoproteins; HDL high-density lipoproteins

Spearman correlation coefficients, P < 0.05: significant

Chemerin and adiponectin gene polymorphism among children with T1DM

Regarding chemerin and adiponectin gene polymorphisms, GG (mutant) chemerin genotype was detected in 41 children with T1DM (82.0%), while TT (mutant) adiponectin genotype was detected among 19 children with T1DM (38.0%).

Children with T1DM had significantly higher GG (mutant) chemerin polymorphism (p = 0.041) and TT (mutant) adiponectin polymorphism (p = 0.011) than controls, Table 1.

Upon assessing the relation of chemerin and adiponectin gene variants and clinico-laboratory and radiological parameters among the studied children with T1DM, those having GG chemerin variant and those having TT adiponectin variant had significantly higher cholesterol (p < 0.001 and p < 0.001) with significantly lower HDL-C (p = 0.012 and p = 0.023) and ABI (p = 0.017 and p = 0.035) than those having the other two variants; Table 3.

Table 3

Distribution of different chimerin and adiponectin gene variants in relation to the clinico-laboratory and radiological parameters among the studied children with T1DM

		Chimerin (RS17173608)			Test value	P value	Adiponectin (RS1501299)			Test value	P value
		TT	TG	GG			TT	TG	GG
		No. = 3	No. = 6	No. = 41			No. = 19	No. = 10	No. = 21
Diabetes duration (years)	Median (IQR)	6 (5–7)	7.5 (5–9)	7 (5–9)	0.481‡	0.786	7 (5–10)	7 (5–8)	6 (5–8)	1.523‡	0.467
Diabetes duration (years)	Range	5–7	4–12	2–13	0.481‡	0.786	2–13	2–12	2–13	1.523‡	0.467
BMI z score	Median (IQR)	− 0.48 (− 0.58–− 0.43)	-0.34 (-0.43–-0.31)	-0.32 (-0.61–0.02)	1.007‡	0.604	− 0.27 (− 0.50–0.10)	− 0.44 (− 0.60–− 0.18)	− 0.37 (− 0.61–− 0.18)	2.428‡	0.297
BMI z score	Range	− 0.58–− 0.43	− 0.45–-− 0.18	− 0.87–1.37	1.007‡	0.604	− 0.87–4.26	− 0.79–1.33	− 0.86–4.37	2.428‡	0.297
Nephropathy		0 (0.0%)	1 (16.7%)	8 (19.5%)	0.729*	0.694	4 (21.1%)	1 (10.0%)	4 (19.0%)	0.569*	0.752
Neuropathy		0 (0.0%)	0 (0.0%)	4 (9.8%)	0.954*	0.621	2 (10.5%)	1 (10.0%)	1 (4.8%)	0.518*	0.772
Cholesterol (mg/dl)	Mean ± SD	96.33 ± 53.35	128.33 ± 28.44	192.84 ± 42.39	12.598•	< 0.001	213.00 ± 50.97	152.10 ± 30.15	161.79 ± 41.83	9.253•	< 0.001
Cholesterol (mg/dl)	Range	35–132	78–156	138–285	12.598•	< 0.001	132–285	78–181	35–228	9.253•	< 0.001
HDL (mg/dl)	Mean ± SD	51.67 ± 16.50	58.50 ± 6.02	44.49 ± 10.77	4.859•	0.012	40.99 ± 9.10	50.20 ± 14.53	49.95 ± 10.31	4.101•	0.023
HDL (mg/dl)	Range	35–68	50–65	30–70	4.859•	0.012	30–60	30–70	35–68	4.101•	0.023
LDL (mg/dl)	Mean ± SD	86.33 ± 10.60	79.67 ± 38.40	115.32 ± 39.67	2.777•	0.072	117.79 ± 36.77	91.60 ± 27.88	110.05 ± 46.38	1.427•	0.250
LDL (mg/dl)	Range	75–96	30–130	22–201	2.777•	0.072	52–201	30–130	22–201	1.427•	0.250
Triglycerides (mg/dl)	Mean ± SD	58.33 ± 30.57	78.50 ± 32.56	125.08 ± 101.48	1.221•	0.304	149.00 ± 135.07	88.84 ± 39.50	97.86 ± 56.34	2.024•	0.143
Triglycerides (mg/dl)	Range	29–90	25–124	29–503	1.221•	0.304	56–503	29–153	25–196	2.024•	0.143
HbA1C %	Mean ± SD	9.20 ± 2.51	8.97 ± 2.40	9.87 ± 1.97	0.612•	0.546	9.73 ± 1.83	10.00 ± 1.81	9.58 ± 2.35	0.140•	0.870
HbA1C %	Range	6.8–11.8	7–12	6.6–13.7	0.612•	0.546	7–12.9	7–12	6.6–13.7	0.140•	0.870
Ankle–brachial index	Mean ± SD	0.97 ± 0.22	0.78 ± 0.23	0.65 ± 0.22	4.456•	0.017	0.78 ± 0.24	0.80 ± 0.14	0.98 ± 0.29	3.607•	0.035
Ankle–brachial index	Range	0.5–1.5	0.53–0.99	0.55–0.98	4.456•	0.017	0.5–1.49	0.53–0.98	0.65–1.5	3.607•	0.035

Bold values indicates significant values

T1DM type 1 diabetes mellitus; BMI body mass index; HbA1C glycated hemoglobin; LDL low-density lipoproteins; HDL high-density lipoproteins

•On–way ANOVA

^‡Kruskal–Wallis test

*Chi-square test; p value < 0.05: significant

Chemerin and adiponectin gene polymorphism in relation to peripheral artery disease

As shown in Fig. 1 and Table 4, the G chemerin allele and the T adiponectin allele were found to be significantly associated with abnormal ABI (p = 0.017 and p = 0.022, respectively). Moreover, the chemerin TT polymorphism was found to be significantly related to ABI in the co-dominant and recessive models (p = 0.017 and p = 0.030), while the adiponectin TT polymorphism was found to be significantly associated with abnormal ABI in the co-dominant model (p = 0.044).

Table 4

Associations of chimerin and adiponectin gene polymorphism with the risk of PAD among children with T1DM

Adiponectin (RS1501299)	Abnormal ABI	Normal ABI	OR (95% CI)	P value	OR (95% CI)*	P value	Chimerin (RS17173608)	Abnormal ABI	Normal ABI	OR (95% CI)	P value	OR (95% CI)*	P value
Adiponectin (RS1501299)	No. = 14	No. = 36	OR (95% CI)	P value	OR (95% CI)*	P value	Chimerin (RS17173608)	No. = 14	No. = 36	OR (95% CI)	P value	OR (95% CI)*	P value
Codominant
TT	8 (57.1%)	11 (30.6%)	Ref		Ref		TT	7 (50.0%)	34 (94.4%)	Ref		Ref
GT	3 (21.4%)	6 (16.7%)	0.217 (0.047–0.993)	0.049	0.198 (0.041–0.956)	0.044	TG	5 (35.7%)	1 (2.8%)	0.103 (0.008–1.298)	0.079	0.288 (0.018–4.511)	0.375
GG	3 (21.4%)	19 (52.8%)	0.316 (0.05–1.998)	0.221	0.343 (0.052–2.267)	0.267	GG	2 (14.3%)	1 (2.8%)	0.041 (0.004–0.409)	0.006	0.053 (0.005–0.591)	0.017
Recessive
TT	8 (57.1%)	11 (30.6%)	Ref		Ref		GG	2 (14.3%)	1 (2.8%)	Ref		Ref
GT + GG	6 (42.9%)	25 (69.4%)	3.03 (0.848–10.835)	0.088	3.461 (0.898–13.337)	0.071	TG + TT	12 (85.7%)	35 (97.2%)	5.833 (0.484–70.244)	0.165	2.371 (0.159–35.335)	0.531
Dominant
TG + TT	11 (78.6%)	17 (47.2%)	Ref		Ref		TG + GG	7 (50.0%)	3 (8.3%)	Ref		Ref
GG	3 (21.4%)	19 (52.8%)	4.098 (0.976—17.202)	0.054	4.211 (0.973—18.231)	0.055	TT	7 (50.0%)	33 (91.7%)	11.000 (2.267–53.372)	0.003	6.310 (1.195—33.329)	0.030
Allele
T	19 (67.9%)	28 (38.9%)	Ref		Ref		T	19 (67.9%)	69 (95.8%)	Ref		Ref
G	9 (32.1%)	44 (61.1%)	3.317 (1.317–8.357)	0.011	3.300 (1.191–9.140)	0.022	G	9 (32.1%)	3 (4.2%)	10.895 (2.682–44.262)	0.001	5.995 (1.375–26.136)	0.017

Bold values indicates significant values

*Adjusted for age and gender, p value < 0.05: significant

Upon performing univariate and multivariate regression analyses for factors associated with chemerin and adiponectin gene polymorphism among children with T1DM, cholesterol and ABI were the significant independent variables related to chemerin (p = 0.03 and p = 0.038, respectively); as for adiponectin gene polymorphism, it was independently related to cholesterol, triglycerides, and ABI (p = 0.016, p = 0.023, and p = 0.021), Table 5.

Table 5

Univariate and multivariate logistic regression analysis (using backward Wald method) for factors associated with chimerin GG polymorphism and adiponectin TT polymorphism among children with T1DM

	Chimerin				Adiponectin
	Univariate		Multivariate		Univariate		Multivariate
	OR (95% C.I.)	P value	OR (95% C.I.)	P value	OR (95% C.I.)	P value	OR (95% C.I.)	P value
Cholesterol (mg/dl)	1.143 (1.038–1.259)	0.007	1.212 (1.019–1.440)	0.030	1.032 (1.012–1.053)	0.002	1.028 (1.005–1.052)	0.016
HDL (mg/dl)	0.907 (0.842–0.978)	0.011			0.921 (0.864–0.981)	0.011	–	–
LDL (mg/dl)	1.027 (1.003–1.052)	0.031			1.007 (0.999–1.016)	0.093	–	–
Triglycerides (mg/dl)	1.017 (0.997–1.038)	0.094			23.388 (1.712–319.465)	0.018	17.541 (9.053–44.911)	0.023
Ankle–brachial index	11.000 (2.267–53.372)	0.003		6.512 (1.177–31.418)	0.038	16.250 (1.917–137.778)	0.011	13.232 (1.839–127.572)

Bold values indicates significant values

T1DM type 1 diabetes mellitus; LDL low-density lipoproteins; HDL high-density lipoproteins

P value < 0.05: significant

Discussion

Subclinical PAD detected as increased ABI has been documented among youth with T1DM. This subclinical vascular affection is recognized as a strong independent predictor for future cardiovascular and cerebrovascular morbidity and mortality [29, 30]. PAD is a complex dynamic process modified by a variety of molecular signaling pathways and genetic determinants [31]. An imbalance between pro-inflammatory and anti-inflammatory cytokines is among the suggested pathways.

Polymorphism of the genes encoding these adipokines may play a role in this process. Hence, assessing the role of these adipokines polymorphisms in the occurrence of PAD among children with T1DM is of utmost important aiming to avoid disease progression and prevent patients at high risk from developing cardiovascular and cerebrovascular events.

In the current study, abnormal ABI was detected in 28% of the studied children with T1DM, of which 85.7% had ABI < 0.9 and 14.3% had ABI higher than 1.2. Nattero-Chávez and colleagues reported an overall prevalence of PAD of 12.8% among children with T1DM [29]. Another study including adults with T1DM described a prevalence of PAD of 27.7% [32]. The high prevalence of subclinical PAD among this population highlights the importance of addressing its genetic determinants.

Overall, children with T1DM had significantly lower ABI than controls. Low ABI is known to be a strong predictor of cardiovascular morbidity and mortality in people with diabetes [33]. In agreement with the current results, Pastore and colleagues reported increased subclinical vascular diseases among children with T1DM compared to healthy controls manifested as reduced brachial artery flow-mediated dilatation reactivity and increased carotid–femoral pulse wave velocity [34].

Although the relation between T1DM and PAD is well established, the determinants of PAD among children with T1DM remains unclear. The proposed predictors of PAD include glycemic and lipid derangements, diabetes duration and hypertension, and male gender [4]. In the current study, PAD was found to be correlated with diabetes duration, insulin dose, and lipid derangements; interestingly, it was not correlated to HbA1C. This goes in line with the DCCT/EDIC study that observed that lowering HbA1c is not solely enough to reduce the rate of PAD in those at risk [5].

In the context of adipokines gene polymorphism, children with T1DM were found to have significantly higher GG chemerin and TT adiponectin gene polymorphisms than controls. The pro-inflammatory chemerin and the anti-inflammatory adiponectin gene polymorphisms have been investigated separately in obesity and T2DM. However, data about their role in T1DM is scarce and lacking. Perumalsamy and coworkers found a significant association between chemerin gene polymorphism and insulin resistance and cardiovascular disease among adults with T2DM [35]. Moreover, the frequency of the G allele of the chemerin rs17173608 polymorphism was found to be significantly higher in people with T2DM than in controls [36]. Regarding adiponectin rs1501299 polymorphism, it has been linked significantly to T1DM in adults [37]. In addition, Cui and coworkers found a significant association between adiponectin rs1501299 polymorphism and T2DM among adults [38].

Interestingly, children with T1DM having GG chemerin variant and those having TT adiponectin variant were found to have significantly higher cholesterol and significantly lower HDL-C than those having the other two variants. Chemerin expression and secretion are reported to increase significantly with adipogenesis. A previous study showed a significant relation between LDL and GG chemerin genotype among adults with metabolic syndrome [39].

Moreover, chemerin was previously reported to have a strong positive correlation with triglycerides, cholesterol, and LDL with a strong negative correlation with HDL-C [40]. As for adiponectin, a previous study by Tsuzaki and coworkers found that HDL-C was significantly and independently correlated with adiponectin and adiponectin rs1501299 G allele by multivariate regression analysis [41].

In the present study, adiponectin and chemerin gene polymorphism was found to be independently associated with PAD among children with T1DM, which suggests a possible role for these polymorphisms in the development of PAD among this population. This goes in agreement with the study by Kennedy and coworkers which identified increased expression of chemerin in atherosclerotic coronary arteries, aorta, and mesenteric arteries [42]. They found that mRNA and protein of chemerin receptors are widely expressed in smooth muscles and endothelial cells of human vessels, reinforcing the importance of their role in vasculature modulation. Interestingly, the expression of chemerin they found in the vascular smooth muscles is similar to that reported for adiponectin [43]. Moreover, adiponectin gene mutations were found to be strongly associated with impaired glucose tolerance, diabetes mellitus, and coronary artery disease in humans [44]. In mice, a high-fat and high-sucrose diet was found to cause marked elevation of plasma glucose and insulin levels, insulin resistance, and an increase in intimal smooth muscle cell proliferation in adiponectin knockout mice [45].

Conclusion

Subclinical PAD probably starts early in children with T1DM as denoted by abnormal ABI. This abnormal ABI is independently related to chemerin and adiponectin gene polymorphism.

Thus, chemerin and adiponectin gene polymorphisms could have a role in the pathogenesis of PAD among children with T1DM. Moreover, chemerin and adiponectin genes could be used as risk biomarkers for hyperlipidemia and vascular affection among children with T1DM.

Limitations of the study

The cross sectional nature of the study could not prove causality and the relatively small sample size. Therefore, further larger longitudinal studies are needed to identify the role of chemerin and adiponectin gene polymorphisms in predicting cytokine levels and PAD risk among children with T1DM.

Declarations

Conflict of interest

All authors declare no competing conflicts of interest.

Ethical approval

This research was approved by the Research Ethics Committee of Ain Shams University with an approval number of R 31/2021.

Written informed consent was taken from the legal guardians of all participants.

Not applicable.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Unsere Produktempfehlungen

e.Med Interdisziplinär

Kombi-Abonnement

Jetzt e.Med zum Sonderpreis bestellen!

Für Ihren Erfolg in Klinik und Praxis - Die beste Hilfe in Ihrem Arbeitsalltag

Mit e.Med Interdisziplinär erhalten Sie Zugang zu allen CME-Fortbildungen und Fachzeitschriften auf SpringerMedizin.de.

Jetzt bestellen und 100 € sparen!

Jetzt testen ¹

e.Med Innere Medizin

Kombi-Abonnement

Mit e.Med Innere Medizin erhalten Sie Zugang zu CME-Fortbildungen des Fachgebietes Innere Medizin, den Premium-Inhalten der internistischen Fachzeitschriften, inklusive einer gedruckten internistischen Zeitschrift Ihrer Wahl.

Jetzt bestellen und 100 € sparen!

Jetzt testen ²

Schofield J, Ho J, Soran H (2019) Cardiovascular risk in type 1 diabetes mellitus. Diabetes Ther 10(3):773–789. https://doi.org/10.1007/s13300-019-0612-8CrossRefPubMedPubMedCentral

Soedamah-Muthu S, Fuller J, Mulnier H, Raleigh V, Lawrenson R, Colhoun H (2006) High risk of cardiovascular disease in patients with type 1 diabetes in the U.K.: a cohort study using the general practice research database. Diabetes Care 29(4):798–804. https://doi.org/10.2337/diacare.29.04.06. (dc05-1433)CrossRefPubMed

Bjornstad P, Donaghue KC, Maahs DM (2018) Macrovascular disease and risk factors in youth with type 1 diabetes: time to be more attentive to treatment? Lancet Diabetes Endocrinol 6(10):809–820. https://doi.org/10.1016/S2213-8587(18)30035-4. (Epub 2018 Feb 20. Erratum in: Lancet Diabetes Endocrinol. 2018 Apr 10;: PMID: 29475800; PMCID: PMC6102087)CrossRefPubMedPubMedCentral

de Ferranti SD, de Boer IH, Fonseca V, Fox CS, Golden SH, Lavie CJ, Magge SN, Marx N, McGuire DK, Orchard TJ, Zinman B, Eckel RH (2014) Type 1 diabetes mellitus and cardiovascular disease: a scientific statement from the American Heart Association and American Diabetes Association. Diabetes Care 37(10):2843–2863. https://doi.org/10.2337/dc14-1720CrossRefPubMedPubMedCentral

Carter RE, Lackland DT, Cleary PA, Yim E, Lopes-Virella M, Gilbert G, Orchard T, The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study Research Group (2007) Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study Research Group Intensive treatment of diabetes is associated with a reduced rate of peripheral arterial calcification in the Diabetes Control and Complications Trial. Diabetes Care 30:2646–2648. https://doi.org/10.2337/dc07-0517CrossRefPubMed

Gerhard-Herman MD, Gornik HL, Barrett C, Barshes NR, Corriere MA, Drachman DE, Fleisher LA, Fowkes FG, Hamburg NM, Kinlay S, Marie D, Lookstein R, Misra S, Mureebe L, Olin J, Patel R, Regensteiner J, Schanzer A, Shishehbor M, Stewart K, Treat-Jacobson D, Walsh M (2017) AHA/ACC guideline on the management of patients with lower extremity peripheral artery disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 135:e726–e779. https://doi.org/10.1161/CIR.0000000000000471CrossRefPubMed

Criqui M, Matsushita K, Aboyans V, Hess C, Hicks C, Kwan T, McDermott M, Misra S, Ujueta F, On behalf of the American Heart Association Council on Epidemiology and Prevention; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular Radiology and Intervention; Council on Lifestyle and Cardiometabolic Health; Council on Peripheral Vascular Disease; and Stroke Council (2021) Lower extremity peripheral artery disease: contemporary epidemiology, management gaps, and future directions: a scientific statement from the American Heart Association. Circulation 144:e171–e191. https://doi.org/10.1161/CIR.0000000000001005CrossRefPubMedPubMedCentral

Liang W, Ye D (2019) The potential of adipokines as biomarkers and therapeutic agents for vascular complications in type 2 diabetes mellitus. Cytokine Growth Factor Rev 48:32–39. https://doi.org/10.1016/j.cytogfr.2019.06.002CrossRefPubMed

Bevan S, Meidtner K, Lorenz M, Sitzer M, Grant P, Markus H (2011) Adiponectin level as a consequence of genetic variation, but not leptin level or leptin adiponectin ratio, is a risk factor for carotid intima-media thickness. Stroke 42:1510–1514. https://doi.org/10.1161/STROKEAHA.110.602375CrossRefPubMed

10.

Zylla S, Dörr M, Völzke H, Schminke U, Felix S, Nauck M, Friedrich N (2018) Association of circulating chemerin with subclinical parameters of atherosclerosis. Results of a population-based study. Arteriosclerosis Thrombosis Vascular Biol 38:1656–1664. https://doi.org/10.1161/ATVBAHA.118.311219CrossRef

11.

Welsh P, Murray HM, Buckley BM, de Craen AJ, Ford I, Jukema JW, Macfarlane PW, Packard CJ, Stott DJ, Westendorp RG, Shepherd J, Sattar N (2009) Leptin predicts diabetes but not cardiovascular disease: results from a large prospective study in an elderly population. Diabetes Care 32:308–310CrossRefPubMedPubMedCentral

12.

Heid IM, Wagner SA, Gohlke H, Iglseder B, Mueller JC, Cip P, Ladurner G, Reiter R, Stadlmayr A, Mackevics V, Illig T, Kronenberg F, Paulweber B (2006) Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1727 healthy Caucasians. Diabetes 55:375–384CrossRefPubMed

13.

Patel S, Flyvbjerg A, Kozakova M, Frystyk J, Ibrahim IM, Petrie JR, Avery PJ, Ferrannini E, Walker M, RISC Investigators (2008) Variation in the ADIPOQ gene promoter is associated with carotid artery intima media thickness independent of plasma adiponectin levels in healthy subjects. Eur Heart J 29:386–393CrossRefPubMed

14.

Er LK, Wu S, Hsu LA, Teng MS, Sun YC, Ko YL (2018) Pleiotropic associations of RARRES2 gene variants and circulating chemerin levels: potential roles of chemerin involved in the metabolic and inflammation-related diseases. Mediators Inflamm 2018:4670521. https://doi.org/10.1155/2018/4670521CrossRefPubMedPubMedCentral

15.

Neves KB, Dinh Cat AN, Lopes RA, Rios FJ, Anagnostopoulou A, Lobato NS, de Oliveira AM, Tostes RC, Montezano AC, Touyz RM (2015) Chemerin regulates crosstalk between adipocytes and vascular cells through Nox. Hypertension 66:657–666. https://doi.org/10.1161/HYPERTENSIONAHA.115.05616CrossRefPubMed

16.

Ji Q, Lin Y, Liang Z, Yu K, Liu Y, Fang Z, Liu L, Shi Y, Zeng Q, Chang C, Chai M, Zhou Y (2014) Chemerin is a novel biomarker of acute coronary syndrome but not of stable angina pectoris. Cardiovasc Diabetol 13:145. https://doi.org/10.1186/s12933-014-0145-4CrossRefPubMedPubMedCentral

17.

Yoo HJ, Choi HY, Yang SJ, Kim HY, Seo JA, Kim SG, Kim NH, Choi KM, Choi DS, Baik SH (2012) Circulating chemerin level is independently correlated with arterial stiffness. J Atheroscler Thromb 19:59–66 (discussion 67)CrossRefPubMed

18.

Aronis KN, Sahin-Efe A, Chamberland JP, Spiro A, Vokonas P, Mantzoros CS (2014) Chemerin levels as predictor of acute coronary events: a case-control study nested within the veterans’ affairs normative aging study. Metabolism 63:760–766. https://doi.org/10.1016/j.metabol.2014.02.013CrossRefPubMed

19.

Aydin K, Canpolat U, Akin S, Dural M, Karakaya J, Aytemir K, Ozer N, Gurlek A (2016) Chemerin is not associated with subclinical atherosclerosis markers in prediabetes and diabetes. Anatol J Cardiol 16:749–755PubMed

20.

Mayer-Davis E, Kahkoska A, Jefferies C, Dabelea D, Balde N, Gong C, Craig M (2018) ISPAD Clinical Practice Consensus Guidelines 2018: Definition, epidemiology, and classification of diabetes in children and adolescents. Pediatr Diabetes 19:7–19CrossRefPubMedPubMedCentral

21.

Couch S, Urbina E, Crandell J, Liese A, Dabelea D, Kim G, Mayer-Davis E (2019) Body mass index z-score modifies the association between added sugar intake and arterial stiffness in youth with type 1 diabetes: the search nutrition ancillary study. Nutrients 11(8):1752CrossRefPubMedPubMedCentral

22.

Flynn J, Kaelber D, Baker-Smith C, Blowey D, Carroll A, Daniels S, de Ferranti S, Dionne J, Falkner B, Flinn S, Gidding S, Goodwin C, Leu M, Powers M, Rea C, Samuels J, Simasek M, Thaker V, Urbina E (2017) Clinical practice guideline for screening and management of high blood pressure in children and adolescents. Pediatrics 140(3):e20171904. https://doi.org/10.1542/peds.2017-1904CrossRefPubMed

23.

Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 29(1):308–311CrossRefPubMedPubMedCentral

24.

FMcGuigan F, Ralston S (2002) Single nucleotide polymorphism detection: allelic discrimination using TaqMan. Psychiatr Genet 12:133–136CrossRef

25.

Harley C, Gandhi S, Blasetto J, Heien H, Sasane R, Nelson SP (2008) Lipid levels and low-density lipoprotein cholesterol goal attainment in diabetic patients: rosuvastatin compared with other statins in usual care. Expert Opin Pharmacother 9:669–676CrossRefPubMed

26.

Goldstein D, Little R, Wie-dmeyer H, England J, McKenzie E (1986) Glycated hemoglobin: methodologies and clinical applications. Clin Chem 32(10):B64-70PubMed

27.

Aboyans V, Criqui MH, Abraham P, Allison M, Creager M, Diehm C, Fowkes F, Hiatt W, Jönsson B, Lacroix P, Marin B, McDermott M, Norgren L, Pande R, Preux P, Stoffers H, Treat-Jacobson D, American Heart Association Council on Peripheral Vascular Disease; Council on Epidemiology and Prevention; Council on Clinical Cardiology; Council on Cardiovascular Nursing; Council on Cardiovascular Radiology and Intervention, and Council on Cardiovascular Surgery and Anesthesia (2012) Measurement and interpretation of the ankle–brachial index: a scientific statement from the American Heart Association. Circulation 126:2890–2909. https://doi.org/10.1161/CIR.0b013e318276fbcbCrossRefPubMed

28.

Zheng G, Gastwirth J (2006) On estimation of the variance in Cochran-Armitage trend tests for genetic association using case-control studies. Stat Med 25:3150–3159CrossRefPubMed

29.

Nattero-Chávez L, Redondo López S, Alonso Díaz S, Garnica Ureña M, Fernández-Durán E, Escobar-Morreale HF, Luque-Ramírez M (2019) The peripheral atherosclerotic profile in patients with type 1 diabetes warrants a thorough vascular assessment of asymptomatic patients. Diabetes Metab Res Rev 35(2):e3088CrossRefPubMed

30.

Ferreira-Divino LF, Suvitaival T, Rotbain Curovic V, Tofte N, Trošt K, Mattila IM, Theilade S, Winther SA, Hansen TW, Frimodt-Møller M, Legido-Quigley C, Rossing P (2022) Circulating metabolites and molecular lipid species are associated with future cardiovascular morbidity and mortality in type 1 diabetes. Cardiovasc Diabetol 21(1):135. https://doi.org/10.1186/s12933-022-01568-8CrossRefPubMedPubMedCentral

31.

Brewer L, Chai H, Bailey K, Kullo I (2007) Measures of arterial stiffness and wave reflection are associated with walking distance in patients with peripheral arterial disease. Atherosclerosis 191(2):384–390CrossRefPubMed

32.

Nattero-Chávez L, López S, Díaz S, Ureña M, Fernández-Durán E, Escobar-Morreale H, Luque-Ramírez M (2019) Association of cardiovascular autonomic dysfunction with peripheral arterial stiffness in patients with type 1 diabetes. J Clin Endocrinol Metab 104(7):2675–2684. https://doi.org/10.1210/jc.2018-02729CrossRefPubMed

33.

Li J, Luo Y, Xu Y, Yang J, Zheng L, Hasimu B, Yu J, Hu D (2007) Risk factors of peripheral arterial disease and relationship between low ABI and mortality from all-cause and cardiovascular disease in Chinese patients with type 2 diabetes. Circ J 71:377–381CrossRefPubMed

34.

Pastore I, Bolla A, Montefusco L, Lunati M, Rossi A, Assi E, Zuccotti G, Fiorina P (2020) The impact of diabetes mellitus on cardiovascular risk onset in children and adolescents. Int J Mol Sci 21:4928. https://doi.org/10.3390/ijms21144928CrossRefPubMedPubMedCentral

35.

Perumalsamy S, Ahmad W, Huri H (2021) Single nucleotide polymorphism rs17173608 in the chemerin encoding gene: is it a predictor of insulin resistance and severity of coronary artery disease in non-obese type 2 diabetes? Healthcare 9(6):623. https://doi.org/10.3390/healthcare9060623CrossRefPubMedPubMedCentral

36.

Abdelhamid A, Zaafan M (2019) Association of Chemerin rs17173608 and Vaspin rs2236242 polymorphisms with type two diabetes mellitus and its impact on their corresponding serum levels in Egyptian population. Biomed J Sci Tech Res 15(3):1–6

37.

Howlader M, Sultana M, Akter F, Hossain M (2021) Adiponectin gene polymorphisms associated with diabetes mellitus: a descriptive review. Heliyon 7(8):e07851. https://doi.org/10.1016/j.heliyon.2021.e07851CrossRefPubMedPubMedCentral

38.

Cui M, Gao Y, Zhao Y, Pang H, Chen L, Wang Z, Zhao L, Li M (2020) Association between Adiponectin gene polymorphism and environmental risk factors of Type 2 diabetes mellitus among the Chinese population in Hohhot. Biomed Res Int 2020:6383906. https://doi.org/10.1155/2020/6383906CrossRefPubMedPubMedCentral

39.

Dahpy M, Khairallah M, Azoz N, Ezzat G (2020) The associations among RARRES2 rs17173608 gene polymorphism, serum chemerin, and non-traditional lipid profile in patients with metabolic syndrome. Egypt J Med Hum Genet 21:21. https://doi.org/10.1186/s43042-020-00063-7CrossRef

40.

Shin HY, Lee DC, Chu SH, Jeon J, Lee M, Im J, Lee J (2012) Chemerin levels are positively correlated with abdominal visceral fat accumulation. Clin Endocrinol 77:47–50CrossRef

41.

Tsuzaki K, Kotani K, Sano Y, Fujiwara S, Gazi I, Elisaf M, Sakane N (2012) The relationship between adiponectin, an adiponectin gene polymorphism, and high-density lipoprotein particle size: from the Mima study. Metab Clin Exp 61(1):17–21CrossRefPubMed

42.

Kennedy AJ, Yang P, Read C, Kuc RE, Yang L, Taylor EJ, Taylor CW, Maguire JJ, Davenport AP (2016) Chemerin elicits potent constrictor actions via chemokine-like receptor 1 (CMKLR1), not G-protein-coupled receptor 1 (GPR1), in human and rat vasculature. J Am Heart Assoc 5(10):e004421. https://doi.org/10.1161/JAHA.116.004421CrossRefPubMedPubMedCentral

43.

Ding M, Carrão AC, Wagner RJ, Xie Y, Jin Y, Rzucidlo EM, Yu J, Li W, Tellides G, Hwa J, Aprahamian TR, Martin KA (2012) Vascular smooth muscle cell-derived adiponectin: a paracrine regulator of contractile phenotype. J Mol Cell Cardiol 52:474–484CrossRefPubMed

44.

Araki T, Emoto M, Teramura M, Yokoyama H, Mori K, Hatsuda S, Maeno T, Shinohara K, Koyama H, Shoji T, Inaba M, Nishizawa Y (2006) Effect of adiponectin on carotid arterial stiffness in type 2 diabetic patients treated with pioglitazone and metformin. Metabolism 55:996–1001CrossRefPubMed

45.

Matsuzawa Y, Funahashi T, Kihara S, Shimomura I (2004) Adiponectin and metabolic syndrome. Arterioscler Thromb Vasc Biol 24:29–33CrossRefPubMed

Titel: Adiponectin rs1501299 and chemerin rs17173608 gene polymorphism in children with type 1 diabetes mellitus: relation with macroangiopathy and peripheral artery disease
verfasst von: N. Y. Salah
S. S. Madkour
K. S. Ahmed
D. A. Abdelhakam
F. A. Abdullah
R. A. E. H. Mahmoud
Publikationsdatum: 13.10.2023
Verlag: Springer International Publishing
Erschienen in: Journal of Endocrinological Investigation / Ausgabe 4/2024
Elektronische ISSN: 1720-8386
DOI: https://doi.org/10.1007/s40618-023-02215-z

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Abstract

Aim

Methods

Results

Conclusion

Trial registration

Publisher's Note

Introduction

Methodology

Study design

Ethical considerations

Procedure

Clinical assessment

Laboratory assessment

Blood sampling

DNA isolation and single-gene polymorphism genotyping

Biochemical assessment

Radiological assessment

Statistical analysis

Results

Peripheral artery disease among children with T1DM

Chemerin and adiponectin gene polymorphism among children with T1DM

Chemerin and adiponectin gene polymorphism in relation to peripheral artery disease

Discussion

Conclusion

Limitations of the study

Declarations

Conflict of interest

Ethical approval

Consent to participate

Consent for publication

Publisher's Note

Unsere Produktempfehlungen

e.Med Interdisziplinär

e.Med Innere Medizin

Weitere Artikel der Ausgabe 4/2024

HMGN1 down-regulation in the diabetic kidney attenuates tubular cells injury and protects against renal inflammation via suppressing MCP-1 and KIM-1 expression through TLR4

Gut microbiota, a potential cause of higher insulin sensitivity in children with Prader–Willi syndrome

Hyponatremia, hypernatremia and impairment of functional, psychological and sexual domains

Blood lipid profile, HbA1c, fasting glucose, and diabetes: a cohort study and a two-sample Mendelian randomization analysis

Lipoprotein(a) is associated with recurrent cardiovascular events in patients with coronary artery disease and prediabetes or diabetes

Adolescent polycystic ovary syndrome without obesity: HOTAIR rs1443512 genotype relates to fat mass and to the redistribution of fat mass on low-dose pioglitazone

Leitlinien kompakt für die Innere Medizin

Neu im Fachgebiet Innere Medizin

Erhebliches Risiko für Kehlkopfkrebs bei mäßiger Dysplasie

Nach Herzinfarkt mit Typ-1-Diabetes schlechtere Karten als mit Typ 2?

15% bedauern gewählte Blasenkrebs-Therapie

Costims – das nächste heiße Ding in der Krebstherapie?

Update Innere Medizin