During the past 50 years, numerous dramatic changes in human environment as well as behavioral and lifestyle changes, have led to a global increase in obesity and type 2 diabetes mellitus (T2DM). Both diseases are reaching epidemic proportions in developed and developing countries and their co-occurrence represents one of the biggest health threats in the 21st century [1, 2].
Metabolic syndrome (MetS) has been described as a cluster of risk factors for cardiovascular diseases (CVDs) and T2DM, primarily due to the existence of abdominal obesity and insulin resistance [3]. Patients with MetS have a 3-fold higher risk of experiencing a heart attack or stroke and a 2-fold higher risk of fatal outcome compared to the general population. Recent findings revealed that MetS increases the risk for the prevalence of microalbuminuria, which is crucial in this syndrome because it accelerates the progression of chronic kidney disease and increases the prevalence of cardiovascular events [4]. Fujita [5] recently demonstrated the possible involvement of aldosterone/mineralocorticoid receptor activation in hypertension development and renal injury in obesity-induced hypertension with MetS. Pathophysiological abnormalities that contribute to the development of MetS include impaired mitochondrial oxidative phosphorylation and mitochondrial biogenesis, dampened insulin metabolic signaling, endothelial dysfunction, and associated myocardial functional abnormalities [6]. Introduction of drug therapy for MetS should not be delayed, as adherence to lifestyle modifications such as dietary changes, weight reduction, and exercise is not achieved in most cases [7].
All components of MetS are considered to be multifactorial traits. The identification of a genetic component of MetS is difficult due to the complexity of MetS and variability of lifestyle factors. However, linkage analysis, candidate gene approach and genome-wide association studies (GWAS) suggested that MetS is a polygenic and multifactorial disease, developing as a result of complex interactions of many genes and environmental factors [8]. Investigations of the genetic basis of this syndrome represent a major challenge [2-4]. Metabolic syndrome is a complex polygenetic disorder of metabolism including central obesity, dyslipidemia, hypertension, and hyperglycemia. Genetic predisposition is one of the risk factors that cannot be controlled, but the knowledge of genetic basis allows us to correct other, modifying, environmental factors, thereby disease can be delayed or prevented. Understanding the importance of genetic and environmental factors, as well as their interactions is critical for finding specific treatments and identifying individuals at high risk of becoming ill. Determining the genetic basis of MetS is one of the necessary steps in disease prevention, and in designing targeted therapies [9].
The
The LRP1 receptor is one of the major ApoE binding receptors in the liver, muscles, heart and adipose tissue. As participating in such a large number of physiological processes, functional clarification of these mechanisms and further identification of LRP1 partners can open up new aspects in the treatment of metabolic diseases, such as lipid metabolism disorders, atherosclerosis, obesity, Alzheimer’s disease and inflammatory processes [9,19,20]. Diet-induced obesity and its serious consequences, such as diabetes, cardiovascular disease and cancer, rapidly became one of the biggest global health problems. Thus, the clarification and understanding of the cellular and molecular mechanisms by which fat food intake causes obesity and diabetes is essential to identify preventive and therapeutic strategies [21]. Data findings identify LRP1 as a critical regulator of adipocyte energy homeostasis, where functional impairment of LRP1 leads to reduced lipid transport, increased insulin sensitivity and muscle power consumption [22]. Thanks to its role in these processes, associations of the
The main goals of the present study were to determine the association between individual alleles of the exon 3
The study included 93 individuals (males and females), aged from 19 to 65 [X ± standard deviation (SD)], attending the Clinical Center of Vojvodina, Novi Sad, Serbia. All subjects were divided in two groups. The MetS group consisted of 63 unrelated men and women who were diagnosed as MetS patients. The control group consisted of 30 unrelated healthy men and women, sex- and age-matched with the test group. The International Diabetes Federation (IDF) definition was applied to define the MetS group of patients [24]. To be diagnosed as MetS, participants needed to fulfill the following criteria: to have central obesity defined by waist circumference (WC) at least 94 cm in men and 80 cm in women, plus two of the following, hyperglycemia defined as fasting plasma glucose of at least 5.6 mmol/L, high blood pressure (BP) defined as resting BP of at least 130/85 mmHg or known treatment of hypertension hypertriglyceridemia defined as triglycerides (TG) at least 1.7 mmol/L low high-density lipoprotein (HDL) defined as fasting HDL cholesterol less than 1.0 mmol/L in men and less than 1.3 mmol/L in women [24,25]. Signed informed consent was obtained from all participants and the study was approved by the Institutional Ethics Review Committee and was performed according to the Declaration of Helsinki.
Anthropometric measurements [body mass (BM), body height (BH) and WC), and cardiovascular risk factors assessment [systolic and diastolic BP, fasting serum lipids levels, glucose levels, Creactive protein (CRP)] were determined. With the subjects wearing light indoor clothes and no shoes, BM and BH were measured using a calibrated beam-type balance to the nearest 0.1 kg and a Harpenden anthropometer to the nearest 0.1 cm, respectively, and body mass index (BMI) was calculated [BMI = (body weight) BW/BH2 (kg/m2)]. Waist circumference was measured using flexible tape to the nearest 0.1 cm at the level midway between the lowest point on the rib margin and the highest point on the iliac crest. Systolic and diastolic BP were measured in a fasting state, early in the morning, using sphygmomanometer by Scipione Riva-Rocci (Italian inventor of cuff-based version of the mercury sphygmomanometer for the measurement of blood pressure; 1863-1937) in sitting position after a 10-15 min. rest period. The mean of three measurements was taken as the most valid value. Total cholesterol (TC) and TG were determined using a commercial kit (Boehringer Manheim GmbH, Mannheim, Germany). Highdensity lipoprotein cholesterol was estimated using the method of precipitation with sodium phospho-wolframate, while LDL-cholesterol was calculated using the formula by Friedewald
Total genomic DNA was isolated from EDTA-anticoagulated blood using phenol chloroform isoamylalcohol extraction [27]. Exon 3 of the
The LRP1 fragments obtained were separated by electrophoresis on a 4.0% MetaPhor agarose gel in 1 × TAE buffer and visualized by ethidium bromide fluorescence. The genotype of each person was determined from the restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) profile.
Statistical analysis of data was performed by software package STATISTICA, version 10.0 (
In the study 93 subjects were examined and analyzed, a group of 63 MetS patients and the control group of 30 healthy subjects. Exon 3 of the
The Student’s Student’s Student’s Student’s Student’s Student’s Student’s Student’s Student’s BM: body mass; BH: body height; BMI: body mass index; WC: waist circumference; Systolic BP: systolic blood pressure; Diastolic BP: diastolic BP; TC: total cholesterol; TG: triglycerides; HDL cholesterol: high-density lipoprotein cholesterol; LDL cholesterol: low-density cholesterol; IRI: insulin level HOMA IR: homeostasis model assessment of insulin resistance; CRP: C-reactive protein.
Parameters
Arithmetic Mean
Control Group
MetS Group
Age (years)
38.70
42.10
−1.29
0.20
BM (kg)
87.33
123.30
−4.98
0.00
BH (cm)
170.13
170.86
−0.16
0.87
BMI (kg/m2)
25.99
41.50
−8.97
0.00
WC (cm)
88.90
125.67
−9.77
0.00
Systolic BP (mmHg)
120.50
139.37
−4.91
0.00
Diastolic BP (mmHg)
77.33
89.60
−4.20
0.00
TC (mmol/L)
5.18
5.48
1.01
0.31
Triglycerides (mmol/L)
3.57
2.12
2.33
0.02
HDL cholesterol (mmol/L)
1.45
0.97
5.47
0.00
LDL cholesterol (mmol/L)
2.29
3.68
−5.19
0.00
Non-HDL cholesterol (mmol/L)
4.03
4.51
−1.87
0.06
LDL/HDL cholesterol (mmol/L)
3.27
3.86
−2.79
0.01
Glycemia (mmol/L)
4.67
5.18
−1.93
0.06
IRI (μU/mL)
8.44
15.32
−3.97
0.00
HOMA IR (μU/mL)
1.80
3.65
−3.76
0.00
C-reactive protein (mg/L)
1.88
12.62
−4.58
0.00
There was a difference in the distribution of genotypes between the two groups. There was a higher frequency of genotypes CT and TT in the MetS group compared to the healthy group. In the MetS and healthy group, the CC genotype was found most often (MetS: 57.4%; control: 86.67%), while the TT genotype was determined only in the MetS group (7.94%). The most common genotype in the total sample was CC (66.67%). The presence of each allele of the
Frequencies of the
Group
Allele
Total
C (%)
T (%)
MetS group
74.60
25.40
100.00
Control group
93.33
6.67
100.00
Total
80.65
19.35
100.00
In both groups, the most frequent allele was allele C (MetS: 74.60%, control: 93.33%), while the T allele (25.4%) was more common in the MetS group. The most frequent allele in the total sample was the C allele (80.65%). Based on the results of the χ2 test of independence, it was found that there is an association between the presence of different exon 3
In order to test the relevance of the
One-way analysis of variance between the exon 3 ANOVA: analysis of variance; F = VA/VR: statistics of F test is the ratio of factorial and residual variance; BMI: body mass index; WC: waist circumference; Systolic BP: systolic blood pressure; LDL: low-density lipoprotein/high-density lipoprotein cholesterol.
ANOVA
Exon 3
Parameter
F = VA/VR
BMI (kg/m2)
4.47
0.010
WC (cm)
6.59
0.000
Systolic BP (mmHg)
4.67
0.012
LDL cholesterol (mmol/L)
40.54
0.000
Index of atherosclerosis LDL/HDL
11.52
0.000
Odds ratio analyses (Table 4) showed that the presence of the T allele in patients multiplies the chance of deviation from the reference values of each anthropometric and biochemical parameter, especially for BMI (4.24-fold) and LDL cholesterol (20.26-fold) compared to the C allele carriers. Calculating the value of OR in relation to the occurrence of MetS, it was found that the presence of the T allele in patients multiplies the chance (4.76-fold) for the occurrence of MetS in comparison to the C allele carriers.
Odds ratio for the exon 3 BMI: body mass index; OR: odds ratio; 95% CI: 95% confidence interval; LDL cholesterol: low-density lipoprotein cholesterol.
Parameters
Allele
C
T
BMI (<30 kg/m2)
OR
0.23
4.24
95% CI
0.07-0.70
1.42-12.65
>0.05
<0.05
LDL cholesteror (>3 mmol/L)
OR
0.04
20.26
95% CI
0.00-0.37
2.70-152.04
>0.05
<0.05
Based on the results presented in our study, the
In the MetS group, significantly higher values of BW, BMI, WC, systolic and diastolic BP, TG, HDL cholesterol, LDL cholesterol, index of atherosclerosis, insulin level (IRI), homeostasis model assessment of insulin resistance (HOMA IR) and CRP were noticed, which was expected, especially for the WC, systolic and diastolic BP, TG and HDL cholesterol, which are the determinants of MetS by the IDF definition. Although there were no significant differences for some expected parameters such as the level of non-HDL cholesterol (
The results revealed statistically significant connection between the presence of the CT genotype and the MetS group affiliation (
In our previous study, we investigated the connection between individual alleles of the apolipoprotein E (
A molecular genetic approach is the most reliable in the diagnosis of most diseases. Studies show that the implementation of routine screening, particularly in patients with hereditary load, contributes to the early diagnosis and prevention, which delays the process leading to the formation and development of CVD, diabetes, obesity, IR, thus leading to MetS, improves the quality of life and reduces the number of patients. Very early confirmation of a genetic predisposition for CVD, diabetes, obesity, IR, leading to MetS, allowed us to change habits that contribute to the emergence and development of the disease, also saving the cost of treatment [4]. The results of correlation found for the T allele of the