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Relationship between alpha-2-macroglobulin, anthropometric parameters and lipid profiles in Thai overweight and obese in Bangkok
Nutrition Research 23 (2003) 1143–1152 www.elsevier.com/locate/nutres
Relationship between alpha-2-macroglobulin, anthropometric parameters and lipid profiles in Thai overweight and obese in Bangkok Rungsunn Tungtrongchitra, Praneet Pongpaewa, Niyomsri Vudhivaia, Supranee Changbumrunga, Anchalee Tungtrongchitrb, Benjaluck Phonratc, Duangkamol Viroonudomphola, Somchai Pooudonga, Frank Peter Schelpd,* a
Department of Nutrition and Food Science, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand b Department of Parasitology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand c Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand d Institute of International Health, Centre for Humanities and of Health Sciences, Free University Berlin and Humboldt University of Berlin, Berlin, Germany Received 1 May 2002; received in revised form 15 November 2002; accepted 20 November 2002
Abstract The aim of this study was to assess anthropometric variables and the lipid pattern in relation to alpha-2-macroglobulin in normal- and over-nourished Thai individuals, to further support the hypothesis that alpha-2-macroglobulin plays a beneficial role in the determination of nutritional status. The study sample comprised of 48 male and 166 female overweight and obese Thai volunteers and 26 male and 81 female normal subjects. The overweight individuals had statistically significant lower alpha2-macroglobulin (A2M) serum levels. The total serum cholesterol, low density lipoprotein-cholesterol (LDL-C) and triglycerides were significantly higher and high density lipoprotein-cholesterol (HDL-C) lower in the over-nourished group as compared with the normal subjects. The LDL/HDL ratio was slightly but significantly higher in the over-nourished group, but still well below the value of 5 for both groups. In using a stepwise multiple linear regression, the model, which best explained the variation of A2M for all individuals including age, HDL-C, BMI, and gender. The relationship of A2M to the variables under study differed between males and females. For males, a model which includes cholesterol and BMI explained best the variation of the proteinase inhibitor. For the females, the best
* Corresponding author. Tel.: ⫹49-30-84451281; fax: ⫹49-30-84451280. E-mail address: [email protected] (F.P. Schelp). 0271-5317/03/$ – see front matter © 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0271-5317(02)00529-8
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model includes age, HDL-C and BMI. The role of protease inhibitors has hardly been explored in human epidemiological studies despite its relationship to important public health issues including nutrition, smoking, cancer and cardiovascular diseases. The results of this study further support the hypothesis, that A2M might play a role in the interrelationship of the nutritional status with the occurrence and the prevention of diseases. © 2003 Elsevier Inc. All rights reserved. Keywords: Alpha-2-macroglobulin; Anthropometric parameters; Lipid Profiles; Obese
1. Introduction The general important physiological role of alpha-2-macroglobulin (A2M), an omnipotent inhibitor of endopeptidases, is indicated by its long evolutionary history [1]. The relevance of A2M in determining the nutritional status and beneficial aspects related to health and disease prevention have been explored in previous studies [2– 4]. Attention was focused on under-nutrition as well as over-nutrition. More recently, over-nutrition in the adult population is a major concern for countries experiencing epidemiological transition. In Thailand, as in other tropical countries, the epidemiological transition has an effect on the health of the population in various aspects, such as changes in eating habits, drinking alcohol and smoking [5–7]. Diseases related to obesity, such as hypertension and diabetes mellitus, have increased among the urban and rural population in Thailand [8]. The objective of this investigation is to assess the lipid pattern in relation to A2M in normal- and over-nourished Thai individuals to further support the hypothesis that A2M plays a beneficial role in determining the nutritional status.
2. Material and methods 2.1. Study population The study sample comprised of 44 male and 148 female overweight and obese Thai volunteers with body mass index (BMI) ⱖ25.0 kg/m2 Another group consisted of 24 male and 79 female normal subjects (BMI ⫽ 18.5–24.9 kg/m2). Thai volunteers who turned up regularly for a physical check-up at the obesity clinic, the out-patient department, general practice section of the Rajvithi Hospital, Bangkok, were investigated for this study. The age, marital status, place of origin, drinking and smoking habits were assessed through standardised questionnaires. Physical examination was conducted by the same medical doctor throughout the study. The individuals investigated generally belonged to the lower middle class, who attended a health check-up facility in the urban centre of Bangkok. Excluded were all volunteers diagnosed through physical and biochemical laboratory examination to be suffering from major ailments and typical diseases such as severe hypertension, liver, lung, cardiovascular diseases, and non-insulin dependent diabetes mellitus. Informed consent was obtained from the obese and the normal subjects before blood specimens were taken from them.
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2.2. Analytical methods The nutritional status of all the subjects was assessed by means of anthropometric measurements. The body weight of each individual dressed in light clothing was measured using a carefully calibrated beam balance (Detecto威). The height of each individual was measured using a vertical-measuring rod. BMI or Quetelet Index was calculated as weight in kg/height (in meters [2]. Standard techniques were applied in measuring triceps skinfold thickness (TSF) subscapular skinfold thickness (SST), waist circumference (WC) and arm circumference (ARM). Mid-arm muscle circumference (MAMC) was computed by applying the formula: MAMC (cm) ⫽ ARM (cm) ⫺ 60.314 ⫻ TSF (mm). About 20 ml of venous blood was drawn in the morning after an overnight fast from the study subjects. The serum samples were stored at 2–5°C for not more than 24 hours prior to lipid profile determination. A serum aliquot was stored frozen at ⫺20°C for quantification of serum A2M. 2.3. Laboratory techniques A commercially available Boehringer Mannheim (Germany) test kit was used to determine cholesterol, high density lipoprotein-cholesterol (HDL-C), low density lipoproteincholesterol (LDL-C) and triglycerides (TG). The rocket immunoelectrophoresis method was used for the quantitative determination of A2M concentration [9]. 2.4. Statistical analysis Standard statistical methods provided by the Minitab statistical computer program [10] were used to analyze the data. The median, range and 95% confidence intervals (C.I.) were calculated. The Mann Whitney U-Wilcoxon Rank Sum W test (two tailed) was used to calculate statistical differences between groups. The SPSS statistical software was used for multivariate regression.
3. Results The age, anthropometric measurements, serum levels of A2M and serum lipids of over-nourished and normal nourished subjects are given in Table 1. Since the study individuals were grouped according to their BMI (BMI ⱖ25 termed as over-nourished and below 25 termed as normal nourished), anthropometric variables, except height, differed between groups. The age range was the same in both groups. The group of overweight individuals had statistically significant (p ⱕ 0.05) lower A2M serum levels than the normals. The difference in lipid status between the two groups was also statistically significant (p ⱕ 0.00), in that total serum cholesterol, LDL-C and triglycerides were higher and HDL-C lower in the over-nourished group. The LDL/HDL ratio was slightly but significantly higher in the over-nourished group, but still well below the value of 5 for both groups.
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Table 1 Median, ranges and 95% confidence interval (CI) of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in over- and normal nourished individuals Variables
Age (yrs) Weight (kg) Height (m) Body mass index (BMI) (kg/m2) Midarm muscle circumference (MAMC) (cm) Subscapular skinfold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (A2M) (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL ratio Triglycerides (TG) (mg/dl)
Total Overweight (N ⫽ 192) Median (range) 38 (18–58) 76.0 (54.0–129.2) 1.56 (1.45–1.77) 30.92 (25.19–53.28)
95%CI
Normal nourished (N ⫽ 103) Median (range)
95%CI
P-value*
37.0–41.0 74.6–78.7 1.55–1.57 30.37–31.61
37.0 (18.0–55.0) 54.2 (42.5–72.2) 1.59 (1.43–1.85) 21.78 (18.5–25.0)
33.0–40.0 52.5–55.9 1.57–1.60 20.96–22.19
0.159 0.000 0.196 0.000
24.7 (16.2–39.0)
24.2–25.2
20.4 (16.9–25.4)
20.0–21.0
0.000
26.7 (14.9–212.0)
26.1–27.4
20.2 (10.1–30.1)
19.1–21.9
0.000
90.2 (66.5–127.0)
89.0–92.0
72.0 (60.0–88.0)
71.0–74.0
0.000
200.2 (112.7–467.2) 200.2–211.7 252.0 (137.5–509.2) 244.7–266.7 0.000 215.0 (106.0–302.0) 208.0–222.1 202.0 (124.0–354.0) 198.0–214.9 0.008 49.5 (26.0–83.0) 138.0 (44.0–230.0) 2.78 (1.05–6.85) 122.5 (45.0–740.0)
46.9–51.0 59.0 (8.0–99.0) 128.9–146.0 129.0 (65.0–266.0) 2.56–3.00 2.20 (1.18–4.59) 113.0–134.1 69.0 (32.0–426.0)
55.0–63.0 123.1–136.9 1.97–2.48 66.1–75.0
0.000 0.042 0.000 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ .05.
In Table 2 and Table 3 over-nourished individuals were compared with normal nourished individuals separately for males and females. Total serum cholesterol levels were only statistically significant (p ⱕ 0.05) different between the two groups of females but not between the groups of males. The difference in LDL-C levels between the two groups of females was almost statistically significant (p ⬍ 0.058), but not for the males. The results given in Table 2 and 3 are otherwise similar to those given in Table 1. The relationship of A2M to anthropometric variables and lipids was tested for all individuals under survey (Table 4), as well as for males (Table 5) and females (Table 6) separately, using a stepwise multiple linear regression. The model, which best explained the variation of A2M for all individuals, includes age, HDL-C, BMI, and gender (Table 4). The relationship of A2M to the variables under study differed between males and females. For males, a model which includes cholesterol and BMI best explained the variation of the proteinase inhibitor (Table 5). For the females, the best model includes age, HDL-C and BMI. 4. Discussion Interaction of A2M, a panproteinase inhibitor found in various tissues, including plasma and cerebrospinal fluid, is involved in various metabolic pathways. The original function
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Table 2 Medians, ranges and 95% CI of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in overweight and normal nourished males Males
Variables Age (yrs) Body mass index (BMI) (kg/m2) Mid-arm muscle circumference (MAMC) (cm) Subscapular skinfold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL Triglycerides (TG) (mg/dl)
Overweight (N ⫽ 44) Median (range)
95%CI
Normal nourished (N ⫽ 24) Median (range)
95%CI
P-value*
41 (18–54) 37–46 30.45 (25.35–38.65) 28.71–31.85
35 (19–54) 30–42 0.072 21.19 (18.68–24.39) 20.52–23.15 0.000
25.6 (18.2–32.3)
24.6–26.3
21.9 (17.7–25.4)
21.2–23.2
0.000
27.4 (14.9–50.6)
24.3–29.3
16.5 (10.1–30.1)
14.0–18.4
0.000
98.5 (66.5–122.0)
93.0–103.0
80.5 (71.0–88.0)
74.8–83.0
0.000
176.0 (112.7–467.2) 162.4–199.7 222.7 (137.5–382.2) 190.6–244.7 0.005 221.0 (136.0–284.0) 207.1–237.9 207.0 (155.0–280.5) 198.8–224.0 0.211 44.0 (26.0–73.0) 138.5 (55.0–206.0) 3.32 (1.59–4.60) 152.5 (56.0–740.0)
40.0–47.0 54.0 (43.0–84.0) 127.0–154.0 136.5 (81.0–193.0) 2.83–3.66 2.74 (1.27–3.78) 140.0–178.6 78.0 (45.0–426.0)
48.0–59.2 110.3–149.2 1.95–2.94 66.0–104.0
0.000 0.404 0.002 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ 0.05.
A2M as a proteinase scavenger complements its role as a binding protein for various growth factors, polypeptide hormones, and cytokines [11–13]. Alpha-2-macroglobulin neutralises collagenase, thrombin and plasmin and may play an important role in leukopoiesis, erythropoiesis and thymus maturation [14]. Alpha-2-macroglobulin is also a ligand for the LDL-C receptor-related protein [15,16], and there is an association of apolipoprotein E with A2M in human plasma [17]. The role of protease inhibitors has hardly been explored in human epidemiological studies despite its relationship to important public health issues including nutrition, smoking, cancer and cardiovascular diseases. In previous studies conducted in Thailand, A2M was inversely related to the nutritional status in children [18,19] men [3,20], and vegetarians [21]. The action of protease inhibitors was interpreted as a regulation mechanism in subclinical undernutrition and marginal nutritional status in that A2M interferes with catabolic processes by adjusting breakdown of metabolites to synthesis depending on dietary intake. The inverse relationship which exists between over or undernutrition and A2M concentration might be beneficial in the prevention of so-called “fat-related cancers”. The nutritionally-induced proteinase inhibitor (PI) elevation inhibits proteases released by cancer tissues, thus working against the spread of cancer in the promotion and progression phase [2]. Especially persons who are still sufficiently nourished or those who are slightly undernourished might benefit from this process. However, those persons with low A2M levels might be at greater risk to
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Table 3 Medians, ranges and 95% CI of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in overweight and normal nourished females Variables
Female
Age (yrs) Body mass index (BMI) (kg/m2) Mid-arm muscle circumference (MAMC) (cm) Sub-scapular skin-fold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL Triglycerides (TG) (mg/dl)
P-value*
Overweight (N ⫽ 148)
Normal nourished (N ⫽ 79)
Median (range)
Median (range)
95%CI
95%CI
37 (18–58) 36–41 30.99 (25.19–53.28) 30.41–31.71
37 (18–55) 33–40 0.591 21.91 (18.47–24.96) 20.95–22.28 0.000
24.5 (16.2–39.0)
23.9–24.9
20.1 (18.9–24.7)
19.5–20.4
0.000
26.4 (15.7–55.1)
26.0–27.2
21.2 (10.1–30.1)
20.1–22.2
0.000
89.0 (71.0–127.0)
85.3–90.5
71.0 (60.0–85.0)
70.0–72.0
0.000
211.7 (134.4–349.2) 200.2–223.8 261.2 (151.2–509.2) 248.4–278.6 0.000 213.0 (106.0–302.0) 205.0–220.4 200.0 (124.0–354.0) 193.3–215.0 0.017 51.0 (27.0–83.0) 138.0 (44.0–230.0) 2.69 (1.05–6.85) 117.0 (45.0–523.0)
49.0–52.4 62.0 (8.0–99.0) 127.6–145.4 127.0 (65.0–266.0) 2.48–2.82 2.09 (1.19–4.59) 104.0–124.4 69.0 (32.0–204.0)
55.7–64.0 121.3–136.0 1.94–2.28 65.0–74.0
0.000 0.058 0.000 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ 0.05.
develop “fat-related cancers” than their not-so-well nourished counterparts. The hypothesis that A2M plays a beneficial role in catabolism and prevention in cancer is underlined by the findings from this investigation. The findings indicated that generally overweight individuals Table 4 Stepwise multiple linear regression including all individuals with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1 2
Age HDL
0.088 0.174
29.219 31.829
0.000 0.000
3
BMI
0.203
11.632
0.001
SEX
0.234
12.433
0.000
⫺0.301 ⫺0.350 0.303 ⫺0.351 0.248 ⫺0.186 ⫺0.334 0.200 ⫺0.211 0.180
SSF, CHOL, LDL TG TG MAMC, WC
4
Age AGE HDL AGE HDL BMI Age HDL BMI SEX
* Independent variables included: Age, Sex; BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
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Table 5 Stepwise multiple linear regression including all males with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1
CHOL
0.187
16.410
0.000
CHOL
⫺0.446
2
BMI
0.245
6.097
0.016
CHOL BMI
⫺0.434 ⫺0.262
Age, MAMC, SSF, HDL, LDL, TG WC
* Independent variables included: Age, BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
have lower A2M levels compared to normal nourished persons. They are thus deprived of the protective effects resulting from the elevated A2M levels. The results obtained from investigating Thai males support the hypothesis that A2M plays a major role in regulating nutritional status, where dietary intake did not correlate with weight and BMI (kg/m2), but protein and fat intake significantly determined the variation of A2M [3]. The fact that protein and fat intake statistically correlated negatively with A2M serum concentration should not be interpreted as a direct cause-effect relationship. Rather it might be assumed that especially low or excess fat intake determines the nutritional status. According to the hypothesis, a complex, not yet fully understood mechanism in the metabolic events of obese and non-obese individuals, determines A2M concentrations. A dietary assessment was also done with the subjects of this study. The results are not mentioned in the result section and considered for data evaluation because A2M was measured before the dietary intake was assessed. The results show that energy intake, especially carbohydrate, protein and fat, was significantly higher in the obese persons in comparison with the controls. The results of the stepwise multiple linear regression in this investigation agree with previous findings. Alpha-2-macroglobulin is negatively related to BMI for both genders and also to cholesterol for males and HDL-C for females. The results are confusing in that there are not only differences in the relationship of A2M to the lipid pattern of males and females, but also the evaluation of the data in a descriptive way do not seem to go along with the results of the multivariate data assessment. Contrary to the results when applying a multivariate Table 6 Stepwise multiple linear regression including all females with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1
Age
0.084
21.627
0.000
Age
⫺0.296
2
HDL
0.171
24.758
0.000
4
BMI
0.211
12.312
0.001
AGE HDL-C Age HDL-C BMI
⫺0.368 0.310 ⫺0.369 0.249 ⫺0.216
SSF, TG, CHOL, LDL-C MAMC, WC
* Independent variables included: Age, BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
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statistical method, taking all obese and non-obese males and females respectively into account, the simple descriptive assessment of the data show no significant difference in cholesterol levels between obese and non-obese males, but there is a significant difference between the two groups for HDL-C (Table 2). Serum cholesterol and HDL-C are significantly different between obese and non-obese females (Table 3). The differences and controversies in the lipid pattern for males and females observed here needs further investigation and presently cannot be explained. It might be that A2M may also play a role in determining the serum lipid pattern. The influence of A2M on the lipid pattern might be modified by alcohol consumption. Males in Thailand usually drink alcohol, whereas females usually drink less or none at all. An inverse correlation of A2M with alcohol consumption was observed for a group of asymptomatic alcoholic males compared with non-alcohol drinking males [22]. Not mentioned in the result section is the observation that obese and normal nourished males in this investigation drink more alcohol (54.5 and 83.3%) than their female counterparts (29.7 and 32.9%). Further investigations are needed to clarify this issue. The median BMI value for over-nourished males and females in this study was above 30 indicating rather severe overweight. The median values for the serum lipid fractions are still in a normal range considering western standards, despite heavy overweight in the overnourished group of the Thai individuals. The median LDL/HDL ratios for the overweight groups were also well below the value of 5. This is important since it is shown that triglycerides and LDL-C are independently related to coronary heart disease incidence only where the LDL/HDL ratio is greater than 5 [23–25]. A previous investigation of the nutritional status and serum lipid pattern of a rural population in Northeast Thailand concluded that, although the risk of developing coronary heart disease for this population might be initially low, in the case of high triglyceride levels the danger of developing the insulin resistant syndrome might be high for overweight Thai individuals [26]. Whether and how A2M, in the situation found in Thailand, determines the development of Type2 diabetes will be another interesting research topic to be conducted. So far it is known that patients who already have the disease had higher A2M levels than the controls. However, it is not entirely clear, whether the elevated levels are due to insufficient inhibitory capacity, thus triggering the release of the proteinase inhibitor in serum, or what potential role A2M might have in the development or prevention of side effects in patients suffering from the disease, and whether elevated A2M levels are protective in preventing the development of Type2 diabetes [27–29]. So far it can be concluded that the serum levels of A2M might be part of a complex system regulating metabolic processes related to the nutritional status, which might have some influence on the occurrence and prevention of diseases, not only in the environment of a tropical country like Thailand, but also in western countries with different nutritional intakes.
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[25] Manninen V, Tenkanen I, Koskinen P, Huttunen JK, Maenttaeri M, Heinonen OP, Frick MH. Joined effects of serum triglyceride and LDL cholesterol and HDL cholesterol concentrations on coronary heart disease risk in the Helsinki Heart Study. Circulation 1992;85:37– 45. [26] Chaisiri K, Pongpaew P, Tungtrongchitr R, Phonrat B, Kulleap S, Sutthiwong P, Intarakhao C, Mahaweerawat U, Khongdee W, Sanchaisuriya P, Saowakontha S, Merkle A, Schelp FP. Nutritional status and serum lipids of a rural population in Northeast Thailand—An example of health transition. Int J Vit Nutr Res 1998;68(3):196 –202. [27] James K, Merriman J, Gray RS, Duncan L, Herd R. Serum alpha-2-macroglobulin levels in diabetes. J Clin Pathol 1980;33:163– 6. [28] Turecky L, Kupcova V, Szantova M. Alpha-2-macroglobulin in the blood of patients with diabetes mellitus. Bratisl Lek Listy 1999;100(1):25–7. [29] Paczek L, Gaciong Z, Bartlomiejczyk I, Sebekova K, Birkenmeier G. Protease administration decreases enhanced transforming growth factor-beta 1 content in isolated glomeruli of diabetic rats. Drugs Exp Clin Res 2001;27(4):141–9.
Relationship between alpha-2-macroglobulin, anthropometric parameters and lipid profiles in Thai overweight and obese in Bangkok Rungsunn Tungtrongchitra, Praneet Pongpaewa, Niyomsri Vudhivaia, Supranee Changbumrunga, Anchalee Tungtrongchitrb, Benjaluck Phonratc, Duangkamol Viroonudomphola, Somchai Pooudonga, Frank Peter Schelpd,* a
Department of Nutrition and Food Science, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand b Department of Parasitology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand c Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand d Institute of International Health, Centre for Humanities and of Health Sciences, Free University Berlin and Humboldt University of Berlin, Berlin, Germany Received 1 May 2002; received in revised form 15 November 2002; accepted 20 November 2002
Abstract The aim of this study was to assess anthropometric variables and the lipid pattern in relation to alpha-2-macroglobulin in normal- and over-nourished Thai individuals, to further support the hypothesis that alpha-2-macroglobulin plays a beneficial role in the determination of nutritional status. The study sample comprised of 48 male and 166 female overweight and obese Thai volunteers and 26 male and 81 female normal subjects. The overweight individuals had statistically significant lower alpha2-macroglobulin (A2M) serum levels. The total serum cholesterol, low density lipoprotein-cholesterol (LDL-C) and triglycerides were significantly higher and high density lipoprotein-cholesterol (HDL-C) lower in the over-nourished group as compared with the normal subjects. The LDL/HDL ratio was slightly but significantly higher in the over-nourished group, but still well below the value of 5 for both groups. In using a stepwise multiple linear regression, the model, which best explained the variation of A2M for all individuals including age, HDL-C, BMI, and gender. The relationship of A2M to the variables under study differed between males and females. For males, a model which includes cholesterol and BMI explained best the variation of the proteinase inhibitor. For the females, the best
* Corresponding author. Tel.: ⫹49-30-84451281; fax: ⫹49-30-84451280. E-mail address: [email protected] (F.P. Schelp). 0271-5317/03/$ – see front matter © 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0271-5317(02)00529-8
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model includes age, HDL-C and BMI. The role of protease inhibitors has hardly been explored in human epidemiological studies despite its relationship to important public health issues including nutrition, smoking, cancer and cardiovascular diseases. The results of this study further support the hypothesis, that A2M might play a role in the interrelationship of the nutritional status with the occurrence and the prevention of diseases. © 2003 Elsevier Inc. All rights reserved. Keywords: Alpha-2-macroglobulin; Anthropometric parameters; Lipid Profiles; Obese
1. Introduction The general important physiological role of alpha-2-macroglobulin (A2M), an omnipotent inhibitor of endopeptidases, is indicated by its long evolutionary history [1]. The relevance of A2M in determining the nutritional status and beneficial aspects related to health and disease prevention have been explored in previous studies [2– 4]. Attention was focused on under-nutrition as well as over-nutrition. More recently, over-nutrition in the adult population is a major concern for countries experiencing epidemiological transition. In Thailand, as in other tropical countries, the epidemiological transition has an effect on the health of the population in various aspects, such as changes in eating habits, drinking alcohol and smoking [5–7]. Diseases related to obesity, such as hypertension and diabetes mellitus, have increased among the urban and rural population in Thailand [8]. The objective of this investigation is to assess the lipid pattern in relation to A2M in normal- and over-nourished Thai individuals to further support the hypothesis that A2M plays a beneficial role in determining the nutritional status.
2. Material and methods 2.1. Study population The study sample comprised of 44 male and 148 female overweight and obese Thai volunteers with body mass index (BMI) ⱖ25.0 kg/m2 Another group consisted of 24 male and 79 female normal subjects (BMI ⫽ 18.5–24.9 kg/m2). Thai volunteers who turned up regularly for a physical check-up at the obesity clinic, the out-patient department, general practice section of the Rajvithi Hospital, Bangkok, were investigated for this study. The age, marital status, place of origin, drinking and smoking habits were assessed through standardised questionnaires. Physical examination was conducted by the same medical doctor throughout the study. The individuals investigated generally belonged to the lower middle class, who attended a health check-up facility in the urban centre of Bangkok. Excluded were all volunteers diagnosed through physical and biochemical laboratory examination to be suffering from major ailments and typical diseases such as severe hypertension, liver, lung, cardiovascular diseases, and non-insulin dependent diabetes mellitus. Informed consent was obtained from the obese and the normal subjects before blood specimens were taken from them.
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2.2. Analytical methods The nutritional status of all the subjects was assessed by means of anthropometric measurements. The body weight of each individual dressed in light clothing was measured using a carefully calibrated beam balance (Detecto威). The height of each individual was measured using a vertical-measuring rod. BMI or Quetelet Index was calculated as weight in kg/height (in meters [2]. Standard techniques were applied in measuring triceps skinfold thickness (TSF) subscapular skinfold thickness (SST), waist circumference (WC) and arm circumference (ARM). Mid-arm muscle circumference (MAMC) was computed by applying the formula: MAMC (cm) ⫽ ARM (cm) ⫺ 60.314 ⫻ TSF (mm). About 20 ml of venous blood was drawn in the morning after an overnight fast from the study subjects. The serum samples were stored at 2–5°C for not more than 24 hours prior to lipid profile determination. A serum aliquot was stored frozen at ⫺20°C for quantification of serum A2M. 2.3. Laboratory techniques A commercially available Boehringer Mannheim (Germany) test kit was used to determine cholesterol, high density lipoprotein-cholesterol (HDL-C), low density lipoproteincholesterol (LDL-C) and triglycerides (TG). The rocket immunoelectrophoresis method was used for the quantitative determination of A2M concentration [9]. 2.4. Statistical analysis Standard statistical methods provided by the Minitab statistical computer program [10] were used to analyze the data. The median, range and 95% confidence intervals (C.I.) were calculated. The Mann Whitney U-Wilcoxon Rank Sum W test (two tailed) was used to calculate statistical differences between groups. The SPSS statistical software was used for multivariate regression.
3. Results The age, anthropometric measurements, serum levels of A2M and serum lipids of over-nourished and normal nourished subjects are given in Table 1. Since the study individuals were grouped according to their BMI (BMI ⱖ25 termed as over-nourished and below 25 termed as normal nourished), anthropometric variables, except height, differed between groups. The age range was the same in both groups. The group of overweight individuals had statistically significant (p ⱕ 0.05) lower A2M serum levels than the normals. The difference in lipid status between the two groups was also statistically significant (p ⱕ 0.00), in that total serum cholesterol, LDL-C and triglycerides were higher and HDL-C lower in the over-nourished group. The LDL/HDL ratio was slightly but significantly higher in the over-nourished group, but still well below the value of 5 for both groups.
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Table 1 Median, ranges and 95% confidence interval (CI) of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in over- and normal nourished individuals Variables
Age (yrs) Weight (kg) Height (m) Body mass index (BMI) (kg/m2) Midarm muscle circumference (MAMC) (cm) Subscapular skinfold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (A2M) (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL ratio Triglycerides (TG) (mg/dl)
Total Overweight (N ⫽ 192) Median (range) 38 (18–58) 76.0 (54.0–129.2) 1.56 (1.45–1.77) 30.92 (25.19–53.28)
95%CI
Normal nourished (N ⫽ 103) Median (range)
95%CI
P-value*
37.0–41.0 74.6–78.7 1.55–1.57 30.37–31.61
37.0 (18.0–55.0) 54.2 (42.5–72.2) 1.59 (1.43–1.85) 21.78 (18.5–25.0)
33.0–40.0 52.5–55.9 1.57–1.60 20.96–22.19
0.159 0.000 0.196 0.000
24.7 (16.2–39.0)
24.2–25.2
20.4 (16.9–25.4)
20.0–21.0
0.000
26.7 (14.9–212.0)
26.1–27.4
20.2 (10.1–30.1)
19.1–21.9
0.000
90.2 (66.5–127.0)
89.0–92.0
72.0 (60.0–88.0)
71.0–74.0
0.000
200.2 (112.7–467.2) 200.2–211.7 252.0 (137.5–509.2) 244.7–266.7 0.000 215.0 (106.0–302.0) 208.0–222.1 202.0 (124.0–354.0) 198.0–214.9 0.008 49.5 (26.0–83.0) 138.0 (44.0–230.0) 2.78 (1.05–6.85) 122.5 (45.0–740.0)
46.9–51.0 59.0 (8.0–99.0) 128.9–146.0 129.0 (65.0–266.0) 2.56–3.00 2.20 (1.18–4.59) 113.0–134.1 69.0 (32.0–426.0)
55.0–63.0 123.1–136.9 1.97–2.48 66.1–75.0
0.000 0.042 0.000 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ .05.
In Table 2 and Table 3 over-nourished individuals were compared with normal nourished individuals separately for males and females. Total serum cholesterol levels were only statistically significant (p ⱕ 0.05) different between the two groups of females but not between the groups of males. The difference in LDL-C levels between the two groups of females was almost statistically significant (p ⬍ 0.058), but not for the males. The results given in Table 2 and 3 are otherwise similar to those given in Table 1. The relationship of A2M to anthropometric variables and lipids was tested for all individuals under survey (Table 4), as well as for males (Table 5) and females (Table 6) separately, using a stepwise multiple linear regression. The model, which best explained the variation of A2M for all individuals, includes age, HDL-C, BMI, and gender (Table 4). The relationship of A2M to the variables under study differed between males and females. For males, a model which includes cholesterol and BMI best explained the variation of the proteinase inhibitor (Table 5). For the females, the best model includes age, HDL-C and BMI. 4. Discussion Interaction of A2M, a panproteinase inhibitor found in various tissues, including plasma and cerebrospinal fluid, is involved in various metabolic pathways. The original function
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Table 2 Medians, ranges and 95% CI of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in overweight and normal nourished males Males
Variables Age (yrs) Body mass index (BMI) (kg/m2) Mid-arm muscle circumference (MAMC) (cm) Subscapular skinfold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL Triglycerides (TG) (mg/dl)
Overweight (N ⫽ 44) Median (range)
95%CI
Normal nourished (N ⫽ 24) Median (range)
95%CI
P-value*
41 (18–54) 37–46 30.45 (25.35–38.65) 28.71–31.85
35 (19–54) 30–42 0.072 21.19 (18.68–24.39) 20.52–23.15 0.000
25.6 (18.2–32.3)
24.6–26.3
21.9 (17.7–25.4)
21.2–23.2
0.000
27.4 (14.9–50.6)
24.3–29.3
16.5 (10.1–30.1)
14.0–18.4
0.000
98.5 (66.5–122.0)
93.0–103.0
80.5 (71.0–88.0)
74.8–83.0
0.000
176.0 (112.7–467.2) 162.4–199.7 222.7 (137.5–382.2) 190.6–244.7 0.005 221.0 (136.0–284.0) 207.1–237.9 207.0 (155.0–280.5) 198.8–224.0 0.211 44.0 (26.0–73.0) 138.5 (55.0–206.0) 3.32 (1.59–4.60) 152.5 (56.0–740.0)
40.0–47.0 54.0 (43.0–84.0) 127.0–154.0 136.5 (81.0–193.0) 2.83–3.66 2.74 (1.27–3.78) 140.0–178.6 78.0 (45.0–426.0)
48.0–59.2 110.3–149.2 1.95–2.94 66.0–104.0
0.000 0.404 0.002 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ 0.05.
A2M as a proteinase scavenger complements its role as a binding protein for various growth factors, polypeptide hormones, and cytokines [11–13]. Alpha-2-macroglobulin neutralises collagenase, thrombin and plasmin and may play an important role in leukopoiesis, erythropoiesis and thymus maturation [14]. Alpha-2-macroglobulin is also a ligand for the LDL-C receptor-related protein [15,16], and there is an association of apolipoprotein E with A2M in human plasma [17]. The role of protease inhibitors has hardly been explored in human epidemiological studies despite its relationship to important public health issues including nutrition, smoking, cancer and cardiovascular diseases. In previous studies conducted in Thailand, A2M was inversely related to the nutritional status in children [18,19] men [3,20], and vegetarians [21]. The action of protease inhibitors was interpreted as a regulation mechanism in subclinical undernutrition and marginal nutritional status in that A2M interferes with catabolic processes by adjusting breakdown of metabolites to synthesis depending on dietary intake. The inverse relationship which exists between over or undernutrition and A2M concentration might be beneficial in the prevention of so-called “fat-related cancers”. The nutritionally-induced proteinase inhibitor (PI) elevation inhibits proteases released by cancer tissues, thus working against the spread of cancer in the promotion and progression phase [2]. Especially persons who are still sufficiently nourished or those who are slightly undernourished might benefit from this process. However, those persons with low A2M levels might be at greater risk to
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Table 3 Medians, ranges and 95% CI of age, anthropometric variables, alpha-2-macroglobulin and lipid profiles in overweight and normal nourished females Variables
Female
Age (yrs) Body mass index (BMI) (kg/m2) Mid-arm muscle circumference (MAMC) (cm) Sub-scapular skin-fold thickness (SSF) (mm) Waist circumference (WC) (cm) Alpha-2-macroglobulin (mg/dl) Total serum cholesterol (CHOL) (mg/dl) Serum HDL-C (mg/dl) Serum LDL-C (mg/dl) LDL/HDL Triglycerides (TG) (mg/dl)
P-value*
Overweight (N ⫽ 148)
Normal nourished (N ⫽ 79)
Median (range)
Median (range)
95%CI
95%CI
37 (18–58) 36–41 30.99 (25.19–53.28) 30.41–31.71
37 (18–55) 33–40 0.591 21.91 (18.47–24.96) 20.95–22.28 0.000
24.5 (16.2–39.0)
23.9–24.9
20.1 (18.9–24.7)
19.5–20.4
0.000
26.4 (15.7–55.1)
26.0–27.2
21.2 (10.1–30.1)
20.1–22.2
0.000
89.0 (71.0–127.0)
85.3–90.5
71.0 (60.0–85.0)
70.0–72.0
0.000
211.7 (134.4–349.2) 200.2–223.8 261.2 (151.2–509.2) 248.4–278.6 0.000 213.0 (106.0–302.0) 205.0–220.4 200.0 (124.0–354.0) 193.3–215.0 0.017 51.0 (27.0–83.0) 138.0 (44.0–230.0) 2.69 (1.05–6.85) 117.0 (45.0–523.0)
49.0–52.4 62.0 (8.0–99.0) 127.6–145.4 127.0 (65.0–266.0) 2.48–2.82 2.09 (1.19–4.59) 104.0–124.4 69.0 (32.0–204.0)
55.7–64.0 121.3–136.0 1.94–2.28 65.0–74.0
0.000 0.058 0.000 0.000
* Mann-Whitney U-Wilcoxon Rank Sum W test (Two-Tailed). Significant difference between overweight and normal subjects p ⱕ 0.05.
develop “fat-related cancers” than their not-so-well nourished counterparts. The hypothesis that A2M plays a beneficial role in catabolism and prevention in cancer is underlined by the findings from this investigation. The findings indicated that generally overweight individuals Table 4 Stepwise multiple linear regression including all individuals with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1 2
Age HDL
0.088 0.174
29.219 31.829
0.000 0.000
3
BMI
0.203
11.632
0.001
SEX
0.234
12.433
0.000
⫺0.301 ⫺0.350 0.303 ⫺0.351 0.248 ⫺0.186 ⫺0.334 0.200 ⫺0.211 0.180
SSF, CHOL, LDL TG TG MAMC, WC
4
Age AGE HDL AGE HDL BMI Age HDL BMI SEX
* Independent variables included: Age, Sex; BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
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Table 5 Stepwise multiple linear regression including all males with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1
CHOL
0.187
16.410
0.000
CHOL
⫺0.446
2
BMI
0.245
6.097
0.016
CHOL BMI
⫺0.434 ⫺0.262
Age, MAMC, SSF, HDL, LDL, TG WC
* Independent variables included: Age, BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
have lower A2M levels compared to normal nourished persons. They are thus deprived of the protective effects resulting from the elevated A2M levels. The results obtained from investigating Thai males support the hypothesis that A2M plays a major role in regulating nutritional status, where dietary intake did not correlate with weight and BMI (kg/m2), but protein and fat intake significantly determined the variation of A2M [3]. The fact that protein and fat intake statistically correlated negatively with A2M serum concentration should not be interpreted as a direct cause-effect relationship. Rather it might be assumed that especially low or excess fat intake determines the nutritional status. According to the hypothesis, a complex, not yet fully understood mechanism in the metabolic events of obese and non-obese individuals, determines A2M concentrations. A dietary assessment was also done with the subjects of this study. The results are not mentioned in the result section and considered for data evaluation because A2M was measured before the dietary intake was assessed. The results show that energy intake, especially carbohydrate, protein and fat, was significantly higher in the obese persons in comparison with the controls. The results of the stepwise multiple linear regression in this investigation agree with previous findings. Alpha-2-macroglobulin is negatively related to BMI for both genders and also to cholesterol for males and HDL-C for females. The results are confusing in that there are not only differences in the relationship of A2M to the lipid pattern of males and females, but also the evaluation of the data in a descriptive way do not seem to go along with the results of the multivariate data assessment. Contrary to the results when applying a multivariate Table 6 Stepwise multiple linear regression including all females with alpha-2-macroglobulin as the dependent variable* Model
Included Variables
Adjusted R2
F change
Sig. F change
Variables in model
Standardized coefficient
Excluded variables
1
Age
0.084
21.627
0.000
Age
⫺0.296
2
HDL
0.171
24.758
0.000
4
BMI
0.211
12.312
0.001
AGE HDL-C Age HDL-C BMI
⫺0.368 0.310 ⫺0.369 0.249 ⫺0.216
SSF, TG, CHOL, LDL-C MAMC, WC
* Independent variables included: Age, BMI, MAMC, SSF, WC, CHOL, HDL-C, LDL-C, TG.
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statistical method, taking all obese and non-obese males and females respectively into account, the simple descriptive assessment of the data show no significant difference in cholesterol levels between obese and non-obese males, but there is a significant difference between the two groups for HDL-C (Table 2). Serum cholesterol and HDL-C are significantly different between obese and non-obese females (Table 3). The differences and controversies in the lipid pattern for males and females observed here needs further investigation and presently cannot be explained. It might be that A2M may also play a role in determining the serum lipid pattern. The influence of A2M on the lipid pattern might be modified by alcohol consumption. Males in Thailand usually drink alcohol, whereas females usually drink less or none at all. An inverse correlation of A2M with alcohol consumption was observed for a group of asymptomatic alcoholic males compared with non-alcohol drinking males [22]. Not mentioned in the result section is the observation that obese and normal nourished males in this investigation drink more alcohol (54.5 and 83.3%) than their female counterparts (29.7 and 32.9%). Further investigations are needed to clarify this issue. The median BMI value for over-nourished males and females in this study was above 30 indicating rather severe overweight. The median values for the serum lipid fractions are still in a normal range considering western standards, despite heavy overweight in the overnourished group of the Thai individuals. The median LDL/HDL ratios for the overweight groups were also well below the value of 5. This is important since it is shown that triglycerides and LDL-C are independently related to coronary heart disease incidence only where the LDL/HDL ratio is greater than 5 [23–25]. A previous investigation of the nutritional status and serum lipid pattern of a rural population in Northeast Thailand concluded that, although the risk of developing coronary heart disease for this population might be initially low, in the case of high triglyceride levels the danger of developing the insulin resistant syndrome might be high for overweight Thai individuals [26]. Whether and how A2M, in the situation found in Thailand, determines the development of Type2 diabetes will be another interesting research topic to be conducted. So far it is known that patients who already have the disease had higher A2M levels than the controls. However, it is not entirely clear, whether the elevated levels are due to insufficient inhibitory capacity, thus triggering the release of the proteinase inhibitor in serum, or what potential role A2M might have in the development or prevention of side effects in patients suffering from the disease, and whether elevated A2M levels are protective in preventing the development of Type2 diabetes [27–29]. So far it can be concluded that the serum levels of A2M might be part of a complex system regulating metabolic processes related to the nutritional status, which might have some influence on the occurrence and prevention of diseases, not only in the environment of a tropical country like Thailand, but also in western countries with different nutritional intakes.
References [1] Strakey PM, Barrett AJ. Evolution of alpha-2-macroglobulin. The demonstration in a variety of vertebrate species of a protein resembling human alpha-2-macroglobulin. Biochem J 1982;205:91–5.
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