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\r\n\tMost part failures are generally caused by fatigue phenomena in which fatigue cracks appear due to application of repeated loads. In this sense, fatigue is a phenomena that requires special attention by engineers. This book will attempt to approach some fatigue topics that are generally not a good fit for classical text books. \r\n\tOne of the most important elements that contributes to fatigue failures are the welded joints due to different factors that act over the joint and are producing early failure. Fatigue cracks usually initiate from surface of the component and propagate across the transverse section, perpendicular to the stress direction. Consequently, the crack propagation and fracture mechanics theories should be studied if we want to understand and to find the causes that produce the component failures and to calculate the residual life. Another factor that affects the crack propagation and fatigue is the environment. A comprehensive understanding of the influence of environment over the crack propagation and fatigue has been blocked by the complexity of the problem. The difficulties in understanding the various micromechanisms governing crack initiation and crack propagation are caused by a lack of a truly interdisciplinary approach to the problem. \r\n\tFrom another side, currently, numerical models and simulation have become a good alternative to solve problems related to fatigue and crack propagation due the relatively low cost and short time expended in this labor, so the book will try to give an overview of the topic. Generally, the fatigue has been studied through the materials more used in engineering (steel, aluminum, bronze), but in recent years, the use of the non-conventional materials like naturals (bamboo, wood, natural fibers), composite materials and others has taken great relevance in engineering applications.
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"22103",title:"Association Between the Hypertriglyceridemic-Waist Phenotype in Mothers and in Their Offspring",doi:"10.5772/22287",slug:"association-between-the-hypertriglyceridemic-waist-phenotype-in-mothers-and-in-their-offspring",body:'\n\t\t
\n\t\t\t
1. Introduction
\n\t\t\t
The hypertriglyceridemic-waist phenotype(Htg-WP), the combination of an increased waist circumference and hypertriglyceridemia, could be a useful and inexpensive screening tool to identify people who are at an increased risk of coronary artery disease and type 2 diabetes. (1-3). The concept of the Htg-WP was introduced by Lemieux and colleagues who suggested that this simple phenotype could be a useful marker for cardiovascular risk and a better predictor of cardiovascular disease. (4)
\n\t\t\t
Imaging studies using techniques such as computed tomography or magnetic resonance imaging have shown that, among equally obese individuals, those with an excess of intra-abdominal or visceral adipose tissue have metabolic abnormalities and are at an increased risk for coronary artery disease and type 2 diabetes (5,6 ). The systematic measurement of waist circumference has been proposed as a crude anthropometric correlate of intra-abdominal adiposity (7). Because waist circumference cannot fully discriminate intra-abdominal from subcutaneous abdominal adiposity, it has been previously suggested that the presence of elevated triglyceride levels could be used as a marker of metabolic abnormalities in people with an increased waistline(4,8).
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An association between parental metabolic syndrome and metabolic syndrome in their offspring has been observed among Korean adolescents (9). Family risk factors include their genetic history as well as their shared environment (9). Parents are in a key position to shape the environments of children, and there is an increasing interest in the contribution of parental behaviors to cardiovascular risk. Maternal feeding practices have received particular attention as a risk factor for childhood OB. A previous study of our group showed that mother’s waist circumference predicted their child’s metabolic syndrome (10); however, as maternal Htg-WP includes two metabolic disorders, it could increase risk of her child’s cardiovascular risk. As far as we know, there are no large studies in elementary school children showing the role that maternal Htg-WP plays in relation to the development of children’s Htg-WP. The objective of this study was to determine the association between mothers’ Htg-WP and the presence of Htg-WP in their offspring.
\n\t\t
\n\t\t
\n\t\t\t
2. Methods
\n\t\t\t
Data were collected cross-sectionally from 1009 children between the ages of 5 and 15 years in 6 elementary schools between April 2007 and March 2008. The schools were randomly selected from 42 schools from the west side of Buenos Aires suburbs. Measurement of BMI, waist circumference, blood pressure, and serum glucose, lipids, and insulin were obtained in mothers and their offspring. Given the fact that the prevalence of OW/OB was approximately 33% among children in a similar population (11), the sample size was estimated to achieve that percentage with an error lower than 0.05. The sample size consistent with this error was 340 children. Five hundred and ninety-five children (296 boys) and their mothers were examined, which means that the sample error was less than 0.04.
\n\t\t\t
Exclusion criteria included: missing BMI and blood pressure information, missing lipid profile and glucose information, not being the biological offspring of their mothers, the informed consent not being signed, self-reported pregnancy at the time of the examination, not being in the fasting state for at least 10 hours, known diabetes or other chronic disease, and the use of medication that alters blood pressure or glucose or lipid metabolism. Only one child per family was included; because most families had more than one child, we randomized the sample to determine which child would be included. Originally 1009 children and their mothers were recruited from six elementary schools. All the offspring who attended on the day of the evaluation were examined (n=1009). To include only one child per mother, we assigned a random number to each child with uniform distribution. We chose the highest random number from the generated variable. This was the selection based on the random number assignment. As a result, 369 siblings were excluded from the study. Furthermore, one child taking a thyroid medication, eight who declined to participate, 16 missing BMI information, and 29 mothers with missing serum lipid and glucose measurements were also excluded. All subjects were examined by the same physician. The study was approved by the Human Rights Committee of Durand Hospital in Buenos Aires. Each parent gave written informed consent, and children gave assent after an explanation of the study and before its initiation.
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Sociodemographic characteristics included age and level of parental education and the presence or absence of a refrigerator or a dirt floor. Questionnaires for socio-economic status have been described in detail elsewhere (11).
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Measurements of height, weight, and waist circumference in mothers and in their offspring were determined as previously described (10). Because children BMI varies according to age and gender we standardized the values for age and sex by converting them to a z-score according to the Centers for Disease Control and Prevention (CDC) growth charts (12). The children were classified as normal weight (BMI<85 percentile) OW, (85<BMI<95percentile) or OB (BMI>95 percentile) per CDC norms (12). The physical examination also included determination of the stage of puberty according to the Tanner criteria (13). Three separate blood pressure measurements were recorded by a trained technician using a random-zero sphygmomanometer after the participant was seated at rest for five minutes. The averages of the three measurements of systolic and diastolic blood pressures were used (14).We used the National Heart, Lung and Blood Institute’s recommended cutoff point for hypertension (14).
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Risk factors for cardiovascular disease were defined using the same cut off as Cook et al (15) used: central OB (waist circumference >90th percentile); fasting triglycerides >110 mg/dL; HDL-C <40 mg/dL; blood pressure>90th percentile for age, sex, and height; and fasting glucose >100 mg/dL.
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Maternal Htg-WP was defined as a waist circumference of 85 cm or more and a triglyceride level of 132 mg/dL(1.5 mmol/L )or higher (16). The Htg-WP in children was defined using the same cut off for waist circumference and triglycerides as Cook et al used (15).
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Homeostasis model assessment of insulin resistance (HOMA-IR) was performed. The equation for HOMA-IR was:
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fasting insulin (in µU/L) × fasting glucose (in mmol/L)/22.5(17).
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Baseline blood samples were obtained from subjects while they were fasting to measure glucose, insulin, and lipid levels. Plasma glucose was assayed by the glucose oxidase technique, and serum lipids were measured with a Modular P analyzer (Hitachi High Technologies Corp., Tokyo, Japan). Serum insulin levels were determined by radioimmunoassay (Diagnostic Products, Los Angeles, CA), and insulin did not cross-react with proinsulin or C-peptide (percentage coefficient of variance, 5.2–6.8%).
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3. Results
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Characteristics of children
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Physical and metabolic profiles are shown in table 1. Five hundred and ninety five children (296 males) aged 9.0 ± 1.9 years were examined. One hundred and five (17.6%) children
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\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
Mothers (595)
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Offsping(595)
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\n\t\t\t\t\t
\n\t\t\t\t\t\t
Age (years)
\n\t\t\t\t\t\t
35.8± 7.0
\n\t\t\t\t\t\t
9.0 ± 1.9
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\n\t\t\t\t\t
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BMI (kg/m2)
\n\t\t\t\t\t\t
27.3± 5.9
\n\t\t\t\t\t\t
18.7 ± 3.5
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\n\t\t\t\t\t
\n\t\t\t\t\t\t
z-BMI ( per CDC)
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
0.6 ± 1.0
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
WC (cm)
\n\t\t\t\t\t\t
89 ± 13
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65± 11
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\n\t\t\t\t\t
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Systolic BP (mmHg)
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111± 16
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96± 13
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\n\t\t\t\t\t
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Fasting glucose (mg/dL)
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79± 18
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78 ± 8
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TC(mg/dL)
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174± 37
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152± 26
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TG (mg/dL)
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81(58-117)
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51(67-90)
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HDL-C (mg/dL)
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52± 12
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50± 12
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Fasting insulin (μIU/mL)
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5.7 (3.7-8.4)
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4.9 (2.8-7.4)
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\n\t\t\t\t\t
\n\t\t\t\t\t\t
HOMA –IR
\n\t\t\t\t\t\t
1.0 (0.7-1.6)
\n\t\t\t\t\t\t
0.9(0.5-1.4)
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
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OW
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182(30.6%)
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110 (18.5%)
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\n\t\t\t\t\t
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OB
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158 (26.6%)
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105 (17.6%)
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\n\t\t\t\t\t
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Centrally OB
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364 (61.2%)
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91 (15.3%)
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
High blood pressure
\n\t\t\t\t\t\t
57(9.8%)
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38 (6.4%)
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
High fasting glucose
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19(3.2%)
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5 (0.8%)
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
High triglyceride
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103(17.3%)
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75(12.6%)
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Low HDL-C
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276 (46.4%)
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129 (21.7%)
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\n\t\t\t\t\t
\n\t\t\t\t\t\t
Htg-WP
\n\t\t\t\t\t\t
93(15.6%)
\n\t\t\t\t\t\t
32(5.4%)
\n\t\t\t\t\t
\n\t\t\t\t
Table 1.
aist circumference (WC),blood pressure (BP), total Cholesterol (TC), triglyceride (TG) Data are mean +SD or median (interquartile range) for continuous variables and percentage for categorical variables. Significance: *p<0.05; **p<0.001. Children’s cardiovascular risk is defined by the following features: WC>90th percentile, fasting glucose level >100 mg/dL, BP >90th percentile, TG >110 mg/dL, and HDL-C <40 mg/dL.
Clinical and Metabolic Characteristics of 595 family members
\n\t\t\t
were obese, and 110 (18.5%) overweight. There was not a significant difference in the prevalence of overweight or obesity between genders. Sixty seven percent, 21.2%, 10.3%, and 1.2% were at Tanner stage 1, 2, 3, and 4 respectively. The prevalence of Htg-WP was 5.4% (n=32) in children.
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Approximately 40% of the children had at least 1 risk factor for cardiovascular disease and 13% had 2 or more risk factors. The risk factors of low HDL (129/595; 21.7%), central obesity (95/595; 15.3%) and high triglycerides (75/595; 12.6%), were common while hypertension (39/595; 6.4%) and impaired fasting glucose (5/595; 0.8%) were infrequent. One child had diabetes and none had all 5 risk factors. There was no significant difference in the prevalence of individual risk factors and in the prevalence of Htg-WP between boys and girls. There was not a significant difference in the distribution of Tanner stages between the group with and that without Htg-WP. The mean z BMI was higher (p<0.001) in the Htg-WP group (z BMI=1.9 + 0.3) than in the group without Htg-WP (z BMI=0.6 + 0.9).
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Characteristics of the Mothers
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Physical and metabolic profiles are presented in table 1. The average maternal BMI was 27.3 which indicates that, as a group, they were overweight. Approximately 27% of the mothers were obese (BMI >30), and 30.6% overweight (25<BMI<30). The educational backgrounds of the mothers were as follows: 1.2% had no formal education, 30% had completed elementary school, 52% had completed high school and 17% had university and/or advanced degrees. Participants came from a low and a middle socio-economic class. Overweight and obesity were more common (p=0.003) in mothers with a lower level of education (divided into high school or less and more).
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Approximately 70% of mothers had at least 1 risk factor for cardiovascular disease, 34% had 2 or more risk factors. The risk factors of low HDL –C (276/595; 46.4%), central obesity (306/595;51.4%) and high triglycerides (103/595; 17.3%) were common while hypertension (47/595; 8%) and impaired fasting glucose (19/595; 3.2%) were less frequent. Four mothers had diabetes and only one mother had all 5 risk factors. Htg-WP was present in 15.6% (93) overall, 2% (5) of the normal, 17.6% (32) of the overweight, and 35.4% (56) of the obese group (P < 0.01). There was not a significant difference in the educational backgrounds in the group with and without Htg-WP. The mean BMI (32.0 vs 26.4; p<0.01) and mean age (39.8 vs 35.0; p<0.01) were higher in the group with Htg-WP than without Htg-WP.
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Children’s characteristics according to the presence of Htg-WP in their mothers
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The prevalence of obesity was significantly higher in children with obese mothers than in the group of children whose mothers were not obese (27.2%vs 14.2%, p<0.001), respectively. The prevalence of obesity was significantly higher in children with mothers with Htg-WP than in the other group (29%vs 15.5%, p=0.002), respectively. The prevalence of Htg-WP was significantly higher in children with mothers with Htg-WP than in the group of children with mothers without Htg-WP( 16.1%vs 3.4%, p<0.001), respectively.
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Children of mothers with Htg-WP had values of z-BMI, waist circumference, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, insulin, and HOMA-IR which were higher (p<0.01) than those for the children of mothers without Htg-WP ( Figure 1 and Table 2). Compared with children whose mothers did not have Htg-WP, the OR in children with maternal Htg-WP was [OR, 4.5 (95% CI 1.7-11.4)] for offspring’s Htg-WP adjusted for age, Tanner stage, gender, maternal HOMA-IR, offspring’s HOMA-IR, and offspring’s hypertension. When socioeconomic class was included in the model, results did not change. The stepwise regression analysis showed that the most strongly predictive value of increased offspring’s hypertriglyceridemic waist was maternal increased hypertriglyceridemic waist. Therefore, compared with children whose mothers did not have Htg-WP, children of mothers with Htg-WP were four and a half times more likely to have Htg-WP.
\n\t\t\t
Figure 1.
Boxplot: the boxes define the 25th and 75th percentiles, and enclose the median; the extensions define the range of values. Median values and interquartile range for children’s z-BMI, children’s WC and children’s TG are presented separately for children without and with mothers with Htg-WP in Panel A, panel B and panel C, respectively. Waist circumference (WC) and triglyceride (TG)
\n\t\t
\n\t\t
\n\t\t\t
4. Discussion
\n\t\t\t
In this cross sectional analysis of school children and their mothers, our main finding was that Htg-WP in children was highly correlated with the maternal status of Htg-WP. We have previously demonstrated the association between maternal waist circumference and metabolic syndrome (a cluster of metabolic abnormalities that include glucose intolerance, central obesity, dyslipidemia, and hypertension) in their offspring (10). The maternal status of Htg-WP defined as an elevated waist circumference >85 cm in women) along with an elevated plasma triglyceride concentration (defined as a level >177 mg/dl) has been proposed and shown to be a stronger marker of cardiovascular risk and a better predictor of cardiovascular disease (4) than the waist circumference alone (18). As far as we know, there have not been large studies in elementary school children showing the association between maternal Htg-WP and their children’s Htg-WP. We found that compared to children whose mothers did not have high Htg-WP, children whose mothers had high Htg-WP were approximately four and a half times more likely to have high Htg-WP adjusted for confounding variables consistent with known familial associations of high Htg-WP and cardiovascular disease.
\n\t\t\t
The prevalence and severity of obesity has been increasing in children and adolescents, as well as in adults (19,20). Excess body fat in children is associated with insulin resistance and predicts development of the metabolic syndrome in adulthood (21). This research showed a high prevalence of overweight and obesity in children (35%) and in their mothers (57%). The
\n\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
Mothers without Htg-WP
\n\t\t\t\t\t\t
Mothers withHtg-WP
\n\t\t\t\t\t\t
P values
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
n (%)
\n\t\t\t\t\t\t
502(84.4)
\n\t\t\t\t\t\t
93 (15.6)
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Age (years)
\n\t\t\t\t\t\t
8.9±1.9
\n\t\t\t\t\t\t
9.4±1.8
\n\t\t\t\t\t\t
0.237
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Z-BMI
\n\t\t\t\t\t\t
0.6±1.0
\n\t\t\t\t\t\t
0.9±1.0
\n\t\t\t\t\t\t
0.004*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
BMI (Kg/m2)
\n\t\t\t\t\t\t
18.5±3.4
\n\t\t\t\t\t\t
19.9±3.9
\n\t\t\t\t\t\t
0.001*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Waist (cm)
\n\t\t\t\t\t\t
64±10
\n\t\t\t\t\t\t
70±12
\n\t\t\t\t\t\t
<0.001*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
DBP (mmHg)
\n\t\t\t\t\t\t
57±10
\n\t\t\t\t\t\t
61±8
\n\t\t\t\t\t\t
0.001*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
SBP (mmHg)
\n\t\t\t\t\t\t
95±13
\n\t\t\t\t\t\t
100±13
\n\t\t\t\t\t\t
0.001*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
TC (mg/dL)
\n\t\t\t\t\t\t
151±26
\n\t\t\t\t\t\t
157±27
\n\t\t\t\t\t\t
0.041*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
HDL-C (mg/dL)
\n\t\t\t\t\t\t
50±12
\n\t\t\t\t\t\t
47±11
\n\t\t\t\t\t\t
0.073
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
TG (mg/dL)
\n\t\t\t\t\t\t
65(50-85)
\n\t\t\t\t\t\t
87(63-121)
\n\t\t\t\t\t\t
<0.001*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Glucose (mg/dL)
\n\t\t\t\t\t\t
78±8
\n\t\t\t\t\t\t
79±7
\n\t\t\t\t\t\t
0.07
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Insulin (uUI/ml)
\n\t\t\t\t\t\t
4.8 (2.6-7.1)
\n\t\t\t\t\t\t
5.4 (3.3-9.0)
\n\t\t\t\t\t\t
0.03*
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
HOMA-IR
\n\t\t\t\t\t\t
0.9 (0.5-1.4)
\n\t\t\t\t\t\t
1.0 (0.6-1.8)
\n\t\t\t\t\t\t
0.02*
\n\t\t\t\t\t
\n\t\t\t\t
Table 2.
aist circumference (WC),blood pressure (BP), total Cholesterol (TC), triglyceride (TG) Data are means or median (interquartile range)+SD or percent. Group 1 (normal waist circumference and normal triglycerides; waist circumference<85 cm in women and triglycerides <132mg/dL, n =317); group 2 (high waist circumference and high triglycerides; waist circumference >85 cm in women and triglycerides <132mg/dL, n =278). Significance: *p<0.05
Characteristics of offspring according to the presence of Htg-WP in their mothers
\n\t\t\t
increasing prevalence of obesity in children could be due to interactions between genetic and environmental factors (22). Recent changes in nutritional and physical activity patterns are considered to have produced changes in the fatness of children (22).Garn et al (23) suggest that childhood eating and exercise patterns are modeled after parental behaviors, and that parental behavior serves as the basis for developing and changing the health habits of children. A recent study showed that parental leanness confers significant protection against development of overweight in children, whereas parental obesity is associated with a prevalence of overweight in their children more than double that for children of lean parents (24). Excessive BMI gains of parents during childhood and adulthood were associated with a higher BMI and risk of obesity in the offspring (25). Substantial evidence now exists which demonstrates the importance of obesity in childhood in creating the metabolic conditions for cardiovascular disease and type 2 diabetes in young adulthood (26). Consistent with this study, we found that the prevalence of obesity was significantly higher in children whose mothers were obese than in the other group. An important epidemiologic aspect of cardiovascular risk in children is the tracking of these risk factors over time. Such tracking has been demonstrated in a number of studies, most notably the Muscatine Study and Bogalusa Heart Study (27, 28) which had demonstrated the presence of early lesions of coronary heart disease in the heart vessels of children and adolescents.
\n\t\t\t
Despite the strong association of obesity, especially central obesity, to metabolic and cardiovascular disease, not all obese individuals carry the same metabolic and cardiovascular risk (18). Waist circumference is a simple and inexpensive marker of abdominal adiposity, but not all people with an increased waistline are at increased risk of coronary artery disease. The Htg-WP is a simple and inexpensive marker to help identify patients with intraabdominal obesity who have a deteriorated cardiometabolic risk profile and are thus at increased risk of coronary artery disease. An additional advantage is that the phenotype can be determined easily, without additional and expensive testing. Plasma triglyceride levels are available from any standard lipid profile obtained in clinical practice, and waist circumference can be measured at no cost. Therefore, elevated plasma triglyceride levels have been proposed as a marker of the metabolic alterations associated with excess intra-abdominal adiposity, such as ectopic fat deposition (liver, skeletal and epicardial fat) and insulin resistance (4). The association between mothers\' obesity and morbidity and their children’s obesity justifies looking for various markers of adiposity in all mothers. Parental obesity is a strong predictor of obesity in children (29,30). According to these studies, we showed that children of mothers with Htg-WP had significantly higher levels of z-BMI, waist circumference, blood pressure, insulin, and triglycerides than children whose mothers did not have Htg-WP. A previous study of our group showed that mother’s waist circumference predicted her child’s metabolic syndrome (11) consistent with known familial associations of OB and type 2 diabetes. However, maternal Htg-WP (the cluster) and its association with Htg-WP in their offspring have not been previously investigated. This study shows that children of mothers with Htg-WP had mean values of cardiovascular risk factors which were significantly higher than those for the children of mothers without Htg-WP. Furthermore, compared with children whose mothers did not have Htg-WP, children of mothers with Htg-WP were four and a half times more likely to have Htg-WP. As familial transmission is a risk factor for future cardiovascular disease, it is important to evaluate familial factors in order to identify strategies for the prevention and management of future diseases.
\n\t\t\t
This study has several potential limitations. First, it is a cross-sectional study. Our data only show the association with present risk factor conditions but do not directly predict the future risk of cardiovascular events. Second, the fact that only mothers were included in the sample might decrease the power of the study. Third, we used criteria (Htg-WP) that has not been previously established for children. The final limitation was that as the sample was drawn from Buenos Aires neighborhoods of a middle and low socioeconomic level, it cannot be viewed as representative of Buenos Aires as a whole. However, it can be seen as representative of a large portion of Buenos Aires.
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The strengths of our study include the large school age population-based sample, which was more likely to represent the general population, the high response rate of the children, the use of Tanner staging for measurement of puberty, the collection of fasting blood samples, and the use of multiple regression models, which allowed investigators to account for the complex interrelationships between these physiologic traits and potential confounders such as gender, pubertal development, children’s HOMA-IR and maternal BMI.
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\n\t\t
\n\t\t\t
5. Conclusions
\n\t\t\t
Markers for an increased risk of cardiovascular disease are already present in children consistent with known familial associations of cardiovascular risk. This study demonstrates the importance of maternal Htg-WP in predicting children’s Htg-WP even after adjustment for confounding variables. This criterion (Htg-WP) could be an easy and inexpensive tool to predict future cardiovascular disease. Health awareness efforts must include children whose mothers had Htg-WP and advocate lifestyle changes which may be easier to achieve in this group before they develop cardiovascular disease ant type 2 diabetes. Longitudinal studies should be conducted to confirm these findings.
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\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/22103.pdf",chapterXML:"https://mts.intechopen.com/source/xml/22103.xml",downloadPdfUrl:"/chapter/pdf-download/22103",previewPdfUrl:"/chapter/pdf-preview/22103",totalDownloads:1120,totalViews:78,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,dateSubmitted:"November 18th 2010",dateReviewed:"July 15th 2011",datePrePublished:null,datePublished:"November 4th 2011",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/22103",risUrl:"/chapter/ris/22103",book:{slug:"topics-in-the-prevention-treatment-and-complications-of-type-2-diabetes"},signatures:"Valeria Hirschler",authors:[{id:"47098",title:"Dr.",name:"Valeria",middleName:null,surname:"Hirschler",fullName:"Valeria Hirschler",slug:"valeria-hirschler",email:"vhirschler@intramed.net",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Methods",level:"1"},{id:"sec_3",title:"3. Results",level:"1"},{id:"sec_4",title:"4. Discussion",level:"1"},{id:"sec_5",title:"5. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBos\n\t\t\t\t\t\t\tG.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tDekker\n\t\t\t\t\t\t\tJ. M.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHeine\n\t\t\t\t\t\t\tR. J.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2004\n\t\t\t\t\tNon-HD. 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H.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2003\n\t\t\t\t\tPrevalence of a metabolic syndrome phenotype in adolescents\n\t\t\t\t\tArch Pediatr Adolesc Med.\n\t\t\t\t\t157\n\t\t\t\t\t821\n\t\t\t\t\t827\n\t\t\t\t\n\t\t\t'},{id:"B16",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBlackburn\n\t\t\t\t\t\t\tP.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLemieux\n\t\t\t\t\t\t\tI.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLamarche\n\t\t\t\t\t\t\tB.\n\t\t\t\t\t\t\n\t\t\t\t\t\tet al.\n\t\t\t\t\t\n\t\t\t\t\t2008\n\t\t\t\t\tType 2 diabetes without the atherogenic metabolic triad does not predict angiographically assessed coronary artery disease in women\n\t\t\t\t\tDiabetes Care\n\t\t\t\t\t31\n\t\t\t\t\t170\n\t\t\t\t\t2\n\t\t\t\t\n\t\t\t'},{id:"B17",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMatthews\n\t\t\t\t\t\t\tDR\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHosker\n\t\t\t\t\t\t\tJP\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRudenski\n\t\t\t\t\t\t\tAS\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tNaylor\n\t\t\t\t\t\t\tBA\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tTreacher\n\t\t\t\t\t\t\t DF\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tTurner\n\t\t\t\t\t\t\t RC\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1985\n\t\t\t\t\tHomeostasis model assessment: insulin resistance and ß-cell function from fasting plasma glucose and insulin concentrations in man\n\t\t\t\t\tDiabetologia\n\t\t\t\t\t28\n\t\t\t\t\t412\n\t\t\t\t\t4198\n\t\t\t\t\n\t\t\t'},{id:"B18",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tThamer\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRittig\n\t\t\t\t\t\t\tK.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBalletshofer\n\t\t\t\t\t\t\tB.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMachicao\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFritsche\n\t\t\t\t\t\t\tA.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHaring\n\t\t\t\t\t\t\tH. 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H.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCarnell\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWardle\n\t\t\t\t\t\t\tJ.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2009\n\t\t\t\t\tDevelopment of overweight in childrenin relation to parental weight socioeconomic status\n\t\t\t\t\tObesity (Silver Spring)\n\t\t\t\t\t17\n\t\t\t\t\t814\n\t\t\t\t\t820\n\t\t\t\t\n\t\t\t'},{id:"B25",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLi\n\t\t\t\t\t\t\tL.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLaw\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLo\n\t\t\t\t\t\t\tConte. R.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2009\n\t\t\t\t\tPower C: Intergenerational influences on childhood body mass index the effect of parental body mass index trajectories\n\t\t\t\t\t Am J Clin Nutr\n\t\t\t\t\t89\n\t\t\t\t\t551\n\t\t\t\t\t557\n\t\t\t\t\n\t\t\t'},{id:"B26",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFord\n\t\t\t\t\t\t\tA. L.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHunt\n\t\t\t\t\t\t\tL. P.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCooper\n\t\t\t\t\t\t\tA.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tShield\n\t\t\t\t\t\t\tJ. P.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2010\n\t\t\t\t\tWhat reduction in BMI SDS is required in obese adolescents to improve body composition and cardiometabolic health?\n\t\t\t\t\tArch Dis Child\n\t\t\t\t\t95\n\t\t\t\t\t256\n\t\t\t\t\t61 .\n\t\t\t'},{id:"B27",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLauer\n\t\t\t\t\t\t\tRM\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLee\n\t\t\t\t\t\t\t J\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tClarke\n\t\t\t\t\t\t\tWR.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1988\n\t\t\t\t\tFactors affecting the relationship between childhood and adult cholesterol levels: the Muscatine Study\n\t\t\t\t\tPediatrics\n\t\t\t\t\t82\n\t\t\t\t\t309\n\t\t\t\t\t318\n\t\t\t\t. '},{id:"B28",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWebber\n\t\t\t\t\t\t\tLS\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSrinivasan\n\t\t\t\t\t\t\tSR\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWattigney\n\t\t\t\t\t\t\tWA\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBerenson\n\t\t\t\t\t\t\t GS.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1991\n\t\t\t\t\tTracking of serum lipids and lipoproteins from childhood to adulthood: the Bogalusa Heart Study.\n\t\t\t\t\tAm J Epidemiol\n\t\t\t\t\t133\n\t\t\t\t\t884\n\t\t\t\t\t899 .\n\t\t\t'},{id:"B29",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBurke\n\t\t\t\t\t\t\tV.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBeilin\n\t\t\t\t\t\t\tL. J.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2001\n\t\t\t\t\tDunbar D: Family lifestyle and parental body mass index as predictors of body mass index in Australian children: a longitudinal study\n\t\t\t\t\tInt J Obes Relat Metab Disord\n\t\t\t\t\t25\n\t\t\t\t\t147\n\t\t\t\t\t157\n\t\t\t\t\n\t\t\t'},{id:"B30",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFrancis\n\t\t\t\t\t\t\tL. A.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLee\n\t\t\t\t\t\t\tY.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBirch\n\t\t\t\t\t\t\tL. L.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2003\n\t\t\t\t\t Parental weight status and girls’ television viewing, snacking, and body mass indexes\n\t\t\t\t\tObes Res\n\t\t\t\t\t11\n\t\t\t\t\t143\n\t\t\t\t\t151\n\t\t\t\t\n\t\t\t'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Hirschler Valeria",address:null,affiliation:'
Hospital Durand, Argentina
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San Biagio",authors:[{id:"57074",title:"Dr.",name:"Marta",middleName:null,surname:"Di Carlo",fullName:"Marta Di Carlo",slug:"marta-di-carlo"},{id:"137441",title:"Dr.",name:"Pasquale",middleName:null,surname:"Picone",fullName:"Pasquale Picone",slug:"pasquale-picone"},{id:"137443",title:"Dr.",name:"P",middleName:null,surname:"San Biagio",fullName:"P San Biagio",slug:"p-san-biagio"}]},{id:"22094",title:"Insulin Resistance and Alzheimer’s Disease",slug:"insulin-resistance-and-alzheimer-s-disease",totalDownloads:3674,totalCrossrefCites:1,signatures:"Sung Min Son, Hong Joon Shin and Inhee Mook-Jung",authors:[{id:"51957",title:"Prof.",name:"Inhee",middleName:null,surname:"Mook-Jung",fullName:"Inhee Mook-Jung",slug:"inhee-mook-jung"},{id:"57126",title:"MSc",name:"Sung Min",middleName:null,surname:"Son",fullName:"Sung Min Son",slug:"sung-min-son"},{id:"57127",title:"M.A.",name:"Hong Joon",middleName:null,surname:"Shin",fullName:"Hong Joon Shin",slug:"hong-joon-shin"}]},{id:"22095",title:"Incretin-Based Treatment Strategy - GLP-1 Receptor Agonists (GLP-1R) or So-Called Incretin Mimetics",slug:"incretin-based-treatment-strategy-glp-1-receptor-agonists-glp-1r-or-so-called-incretin-mimetics",totalDownloads:1405,totalCrossrefCites:0,signatures:"Jindra Perusicova and Klara Owen",authors:[{id:"45168",title:"Prof.",name:"Jindra",middleName:null,surname:"Perusicova",fullName:"Jindra Perusicova",slug:"jindra-perusicova"},{id:"57059",title:"Dr.",name:"Klara",middleName:null,surname:"Owen",fullName:"Klara Owen",slug:"klara-owen"}]},{id:"22096",title:"Carbohydrate Derivatives and Glycomimetic Compounds in Established and Investigational Therapies of Type 2 Diabetes Mellitus",slug:"carbohydrate-derivatives-and-glycomimetic-compounds-in-established-and-investigational-therapies-of-",totalDownloads:1622,totalCrossrefCites:0,signatures:"László Somsák, Éva Bokor, Katalin Czifrák, László Juhász and Marietta Tóth",authors:[{id:"52137",title:"Prof.",name:"László",middleName:null,surname:"Somsák",fullName:"László Somsák",slug:"laszlo-somsak"},{id:"57041",title:"Dr.",name:"Éva",middleName:null,surname:"Bokor",fullName:"Éva Bokor",slug:"eva-bokor"},{id:"57042",title:"Dr.",name:"Katalin",middleName:null,surname:"Czifrak",fullName:"Katalin Czifrak",slug:"katalin-czifrak"},{id:"57043",title:"Dr.",name:"László",middleName:null,surname:"Juhász",fullName:"László Juhász",slug:"laszlo-juhasz"},{id:"57044",title:"Dr.",name:"Marietta",middleName:null,surname:"Tóth",fullName:"Marietta Tóth",slug:"marietta-toth"}]},{id:"22097",title:"Effect of Dehydroepiandrosterone on Insulin Sensitivity and Adipocyte Growth in Otsuka Long-Evans Tokushima-Fatty Rats",slug:"effect-of-dehydroepiandrosterone-on-insulin-sensitivity-and-adipocyte-growth-in-otsuka-long-evans-to",totalDownloads:990,totalCrossrefCites:0,signatures:"Tatsuo Ishizuka, Kazuo Kajita, Kei Fujioka, Takayuki Hanamoto, Takahide Ikeda, Ichiro Mori, Masahiro Yamauchi, Hideyuki Okada, Taro Usui, Noriko Takahashi, Hiroyuki Morita, Yoshihiro Uno and Atsushi Miura",authors:[{id:"50023",title:"Dr.",name:"Tatsuo",middleName:null,surname:"Ishizuka",fullName:"Tatsuo Ishizuka",slug:"tatsuo-ishizuka"}]},{id:"22098",title:"A Review of Clinical Trials in Emerging Botanical Interventions for Type 2 Diabetes Mellitus",slug:"a-review-of-clinical-trials-in-emerging-botanical-interventions-for-type-2-diabetes-mellitus",totalDownloads:1743,totalCrossrefCites:0,signatures:"Cheow Peng Ooi, Seng Cheong Loke and Tengku-Aizan Hamid",authors:[{id:"40108",title:"Dr.",name:"Cheow Peng",middleName:null,surname:"Ooi",fullName:"Cheow Peng Ooi",slug:"cheow-peng-ooi"},{id:"52952",title:"Dr.",name:"Seng Cheong",middleName:null,surname:"Loke",fullName:"Seng Cheong Loke",slug:"seng-cheong-loke"},{id:"110585",title:"Prof.",name:"Tengku-Aizan",middleName:null,surname:"Hamid",fullName:"Tengku-Aizan Hamid",slug:"tengku-aizan-hamid"}]},{id:"22099",title:"Prevention of Diabetes: Effects of a Lifestyle Intervention",slug:"prevention-of-diabetes-effects-of-a-lifestyle-intervention",totalDownloads:1727,totalCrossrefCites:1,signatures:"Kátia Cristina Portero McLellan, Antonio Carlos Lerário and Roberto Carlos Burini",authors:[{id:"50383",title:"Dr.",name:"Katia",middleName:"Cristina",surname:"Portero-McLellan",fullName:"Katia Portero-McLellan",slug:"katia-portero-mclellan"},{id:"99684",title:"Dr.",name:"Antonio",middleName:null,surname:"Lerario",fullName:"Antonio Lerario",slug:"antonio-lerario"},{id:"99685",title:"Dr.",name:"Roberto",middleName:null,surname:"Burini",fullName:"Roberto Burini",slug:"roberto-burini"}]},{id:"22100",title:"Fiber and Insulin Sensitivity",slug:"fiber-and-insulin-sensitivity",totalDownloads:1821,totalCrossrefCites:0,signatures:"Kevin C. 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Arce-Esquivel, Aaron K. Bunker and M. Harold Laughlin",authors:[{id:"52255",title:"Dr.",name:"Arturo",middleName:"A.",surname:"Arce-Esquivel",fullName:"Arturo Arce-Esquivel",slug:"arturo-arce-esquivel"},{id:"59053",title:"Dr.",name:"Aaron",middleName:null,surname:"Bunker",fullName:"Aaron Bunker",slug:"aaron-bunker"},{id:"59054",title:"Dr.",name:"M. Harold",middleName:null,surname:"Laughlin",fullName:"M. Harold Laughlin",slug:"m.-harold-laughlin"}]},{id:"18543",title:"Antihypertensive Treatment in Type 2 Diabetic Patients",slug:"antihypertensive-treatment-in-type-2-diabetic-patients",signatures:"Angelo Michele Carella",authors:[{id:"48020",title:"Dr.",name:"Angelo Michele",middleName:null,surname:"Carella",fullName:"Angelo Michele Carella",slug:"angelo-michele-carella"}]},{id:"18544",title:"Managing Hypertension in Patients with Diabetes",slug:"managing-hypertension-in-patients-with-diabetes",signatures:"Arthur L.M. 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Lambert",authors:[{id:"40084",title:"Prof.",name:"Kazuko",middleName:null,surname:"Masuo",fullName:"Kazuko Masuo",slug:"kazuko-masuo"}]},{id:"18546",title:"Diabetic Nephropathy; Clinical Characteristics and Treatment Approaches",slug:"diabetic-nephropathy-clinical-characteristics-and-treatment-approaches",signatures:"Derun Taner Ertugrul, Emre Tutal and Siren Sezer",authors:[{id:"42960",title:"Dr.",name:"Derun Taner",middleName:null,surname:"Ertugrul",fullName:"Derun Taner Ertugrul",slug:"derun-taner-ertugrul"},{id:"57004",title:"Dr.",name:"Emre",middleName:null,surname:"Tutal",fullName:"Emre Tutal",slug:"emre-tutal"},{id:"57191",title:"Prof.",name:"Siren",middleName:null,surname:"Sezer",fullName:"Siren Sezer",slug:"siren-sezer"}]},{id:"18547",title:"Anemia of Chronic Kidney Disease in Diabetic Patients: Pathophysiologic Insights and Implications of Recent Clinical Trials",slug:"anemia-of-chronic-kidney-disease-in-diabetic-patients-pathophysiologic-insights-and-implications-of-",signatures:"Victoria Forte, Miriam Kim, George Steuber, Salma Asad and Samy I. McFarlane",authors:[{id:"53477",title:"Prof.",name:"Samy I.",middleName:null,surname:"McFarlane",fullName:"Samy I. 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Yu and M. Mazen Jamal",authors:[{id:"47155",title:"Dr.",name:"M. Mazen",middleName:null,surname:"Jamal",fullName:"M. 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1. Introduction
Primary and metastatic tumors are generally known as a complex ecosystem containing tumor cells and the surrounding environment, called tumor microenvironment (TME). Apart from autonomous changes by genetic alteration of tumor cells, the dynamic changes of TME progress the tumor progression [1]. TME is a multifaceted pool that consists of various cell types including neoplastic cells, stromal cells, and immune cells that interact with one another via numerous secreted cytokines, growth factors, and chemokines. Tumor-associated macrophages (TAMs) take up a large portion of recruited immune cells and constitute up to 50% of the tumor mass. It was reported that the high level of TAMs is associated with poor prognosis and decreasing overall survival in many cancers, such as liver, breast, gastric, and thyroid cancers, suggesting that TAMs certainly play essential roles during tumor development [2, 3, 4, 5, 6].
TAM recruitment and accumulation are regulated by various cytokines and chemokines, such as CCL2, CCL5, CCL7, CXCL12, etc., and growth factors including VEGF, PDGF, and CSF1, as well as other factors such as fibronectin and fibrinogen [7, 8, 9, 10]. CSF1 is the major regulator for monocyte proliferation and differentiation. CCL2 is a dominant attractant in many tumors. Since monocytes highly expressed the receptor of CCL2 (CCR2), most of tumors produced a high level of CCL2 that can intensely attract monocytes migrating toward CCL2-CCR2 axis [11, 12, 13, 14, 15, 16, 17]. However, CCL2 inhibition studies show that it could not completely suppress TAM accumulation, indicating that other factors affect this process [7, 17, 18, 19, 20, 21]. The CCL12-CXCR4 axis is reported to promote TAM regional accumulation under therapeutic treatments. In mice model, breast cancer highly expressed CCL20 and CCL5; Either inhibited CCL20 expression or treated with CCR5 antagonist, the number of TAMs was significantly reduced within tumors. These studies have shown that in breast cancer, CCL20-CCR6 and CCL5-CCR5 axes contribute to TAM accumulation. Another chemokine CCL11 can be induced under hypoxia condition and subsequently recruit TAMs to the hypoxic region.
In turn, TAMs can produce different molecules to remodel TME and influence fundamental aspects of tumor pathology. For instance, TAMs secrete endothelial growth factor (EGF) to increase neoplastic proliferation directly [22]; TAMs release vascular endothelial growth factors (VEGF) [23], angiogenic factor thymidine phosphorylase, and other chemokines including CCL2 and CXCL8 to enhance angiogenesis; TAMs produce metalloproteases (MMPs) to change TME matrix architecture for tumor metastasis [24]; and TAMs express immune regulatory molecules such as arginase-1 (ARG1), IL-10, and IL12 to modulate immune response [2]. The role of TAMs is accomplished by their phenotypic plasticity, either pro-inflammatory or anti-inflammatory phenotype, in response to the complex stimuli in TME. The double-edged sword feature of TAM polarization makes them as a novel and potent target for cancer prevention and treatments.
Traditional Chinese medicine is an integrated healthcare system composed of many practices that were rooted in China for over 5000 years. Due to its multi-target, multi-level, and coordinated intervention effects, Chinese medicine is widely used for therapeutic strategies. Recent studies reported that some of the Chinese herbal medicines have beneficial effects on cancer therapy via modulating TAM polarization, indicating a new mechanism for Chinese medicine treatment. In this chapter, we will explore the molecular mechanisms of TAM polarization and their roles in health and disease, and we will review the intervention by some of the Chinese herbal medicines on TAM polarization.
2. TAM polarization and molecular mechanisms
2.1 TAM polarization
It is widely accepted that the majority of TAMs are derived from circulating monocytes via cytokine recruitment and then differentiate to macrophages. And those at the metastatic sites are called metastatic-associated macrophages (MAMs) according to their location [25]. While recent studies have shown that the tissue-resident macrophages also contribute to TAM population [26, 27], these progenitors, also called embryonic macrophages, are derived from the yolk sac or fetal liver-derived progenitors, and they can maintain themselves by local proliferation in a hematopoietic system-independent way [28]. The selective depletion studies found that only the tissue-resident macrophages support the established tumor growth. Therefore, TAMs are heterogeneous cell populations from both tissue-resident macrophages and monocyte-derived macrophages and assist TME remodeling.
Besides their heterogeneity, TAMs are also characterized by high plasticity. In the general regard, macrophages can be overgeneralized to two extreme subsets based on the stimuli, surface markers, and secreted molecules, as well as functional properties: the classically activated M1 and alternatively activated M2 macrophages. The M1 phenotype is induced by the Th1 cytokine interferon-γ (IFN-γ), bacterial moieties such as lipopolysaccharide (LPS), and Toll-like receptor (TLR) agonists. The M1 macrophages are characterized by their capacity to produce inflammatory cytokines (e.g., IL-6, IL-1, IL-12, IL-23, and TNF-α) and stimulate immune response, express reactive oxygen species (ROS) and inducible nitric oxide synthase (iNOS), and have a cytotoxic effect toward neoplastic cells and phagocytic microorganisms [29, 30, 31, 32, 33, 34]. Generally, the M1-like macrophages act as sentries and display tumoricidal function, antimicrobial activity, and tissue destruction effect [33, 35].
In contrast, the M2 phenotype is promoted by Th2 mediators and produces immunosuppressive factors (e.g., IL-10, TGF-β) and growth factors (e.g., VEGF) and exerts anti-inflammatory and pro-tumorigenic activities [34, 36, 37]. Moreover, the M2-like macrophages can be further subdivided into three categories, M2a, M2b, and M2c, based on the type of stimuli. The M2a macrophages are driven by type II cytokines including IL4 and IL13 and expressed a high level of arginase-1; M2b macrophages are activated by immune complexes/TLR, while M2c macrophages by anti-inflammatory cytokines (e.g., IL-10) and glucocorticoids [38]. The M2-like macrophages promote angiogenesis, wound repair, and tumor growth, as well as resistance to parasitic infection. Many studies reported that TAMs mostly represent M2-like macrophages and play pro-tumoral roles.
2.2 Molecular mechanisms in regulating TAM polarization
2.2.1 The JNK signaling pathway
The c-Jun N-terminal kinase (JNK) proteins are a group of stress-activated serine threonine protein kinases of the MAPK and can be activated by various external stimuli including inflammatory cytokines, environmental stresses, growth factors, and GPCR agonists. The outside signals can be transduced by small GTPase to MAP3Ks and further activate MKK4/7. The MAP3Ks play key roles in the JNK pathway and affect tremendous downstream transcription factors including AP-1, Smad3, and STAT3, thus controlling many biological processes [39]. The studies on adipose tissue macrophages (ATMs) have demonstrated that the JNK pathway is indispensable in regulating M1/M2 phenotype formation. In HFD-/NAFLD-induced inflammation and obesity, the activated JNK pathway can promote the expression of the M1-associated genes via CCR2 and NF-κB signaling. The M1-like ATMs are related to the resistance to insulin [40, 41]. Recent studies found that normal adipocytes produce Th2 cytokines, such as IL-13 and IL-4 which can enhance M2-like macrophage polarization via activating STAT6 and PPAR𝛿/𝛽, as well as ACE to block the JNK pathway-induced M1-like phenotype [42]. Studies also found that vigorous exercise can promote M2 state through decrease phosphor-JNK [43].
2.2.2 The PI3K/Akt signaling pathway
Among different pathways, the PI3K/Akt pathway is playing a central role in regulating polarized phenotype alteration. It can be activated by many stimuli such as TLR4, PRRs, FcRs, and cytokines and modify downstream cytokine production [44, 45, 46, 47]. In turn, the PI3K/Akt pathway can affect the expression of stimuli and form a feedback loop. For example, the activated PI3K/Akt pathway can inhibit the transcription factors of TLR4 including TRAF6 and FOXO1 either directly or indirectly to suppress TLR4 stimulation. The PI3K has two transducers PIP2 and PIP3 which exert opposite functions during stimulation. It has been reported that PIP2 can enlarge LPS-induced M1-like macrophage polarization, while PIP3 can target mTORC2 via Akt recruitment and promote M2-like macrophage polarization. Other studies found that PTEN and SHIP play an inhibitory effect on PI3K/Akt transduction by transforming PIP3 to PIP2. The downstream signals mTORC1 and mTORC2 also participate in regulating M1/M2 alteration. Deletion of TSC1 can promote LPS-induced M1 polarization and inhibit IL-4-triggered M2 polarization via inhibiting mTORC1-induced Akt signaling, while the deletion of TSC2 gives an opposite response. Furthermore, the isoforms of Akt also contribute to influence the M1-/M2-polarized phenotype transformation in the opposite way. In knocked out Akt1, the expressions of iNOS and IL-12 were enhanced which is a hallmark of M1-like macrophages, and the transcription factor C/EBPβ of M2-related genes was decreased. The deletion of Akt2 led to C/EBPβ and M2 markers enhanced, including Arg1, Fizz1, and Ym1 [48].
2.2.3 The JAK/STAT signaling pathway
The JAK/STAT pathway is one of the principle regulators for transducing different signals and affects various gene expressions. The JAK family consists of JAK1–3 and TYK2 and can be recruited and bind to the intracellular domains of activated receptors. JAKs will subsequently become dimers after autophosphorylation and then phosphorylate their downstream STAT family which has seven members including STAT1–4, STAT5A/B, and STAT6. The activated STAT family will translocate to the nucleus and modulate the expression of their target genes [49]. Increasing evidence found that the JAK/STAT pathway is closely related to M1/M2 phenotypic polarization. Among different stimuli of JAK/STAT signaling pathway, the IFN-γ has been known as a strong inducer of M1 phenotype through STAT1 activation [50]. It is controlled by IRF5 and IRF4 which exert promotive and inhibitory effects, respectively [51]. The IL-4 and IL-10 can activate STAT3 and STAT6 to program the M2-like phenotype and also have cross talk with JNK pathway as mentioned in the JNK signaling pathway. The IL-13 can activate both M1- and M2-associated genes through STAT1, STAT3, and STAT6 activation [52]. There are two regulators of JAK/STAT pathway that affect M1/M2 reprogramming, SOCS1 and SOCS3. The SOCS1 exhibits a suppressive function on STAT1, thus leading to the M1-like phenotype inhibition, while activating STAT6 to induce M2 polarization. The SOCS3 can activate STAT1 activity to contribute M1 polarization [53, 54].
2.2.4 The Notch signaling pathway
The Notch pathway is generally known to play a fundamental role in regulating development and assist to govern the fate in response to different stimuli. There are four members of transmembrane receptors including Notch1–4. When the Notch receptors bind to their ligand family, such as Delta-like proteins (DLLs) and Jagged proteins, the Notch intracellular domain (NICD) receptors will be released into the cell nucleus and binds to RBP-J to form a transcription complex, thus driving the target gene expression [55]. For example, LPS stimulation can upregulate DLL4 which is one of the DLLs in the TLR4/NF-κB-dependent way. The increased DLL4 can lead to activated Notch signaling and induce pro-inflammatory genes, such as IL-12 and iNOS [56]. Apart from the direct function of RBP-J, it can also positively regulate IRF8 activation to promote pro-inflammatory cytokine production. And this regulation is associated with PI3K/Akt and TLR4/NF-κB pathways [57].
2.2.5 Other molecular mechanisms
Apart from the signaling pathways mentioned above, there are many other pathways involving in M1/M2 reprogramming. For example, the TLR/NF-κB pathway is important in regulating the innate immune response. TLRs can sense the microbial components and transduce signals to affect NF-κB activity. When the NF-κB is formed as p50/p65, it promotes M1-associated gene expression, while p50/p50 form has beneficial effects on M2-associated gene expression [58, 59]. It is worth noting that the hypoxia-dependent pathway also participates in M1/M2 phenotypic switch. The HIF-1α is induced under hypoxia condition and serves as a transcription factor to regulate protein production. It has been reported that HIF-1α promotes M1-like polarization by enhancing iNOS production and HIF-2α promotes M2 phenotype via increasing Arg-1 expression [60].
3. Roles of TAM polarization and Chinese medicine intervention
The roles of TAMs under physiological and pathological conditions depend on their dichotomic polarization. Generally, when infection of tissue or damage occurs, The first-responding TAMs show M1-like phenotype and secrete pro-inflammatory cytokines to defend against invading pathogens and eliminate necrotic cells. And at the latter stage, the M2-like macrophages have shown as a compensation mechanism to prohibit extensive inflammation and assist in wound healing. In cancers, the M1-like TAMs predominantly exert cytotoxicity effect on cancer cells, while the M2-like TAMs assist in modulating immunosuppressive and pro-tumoral TME for cancer progression. Nowadays, TAMs are becoming promising targets for therapeutic strategies [61, 62]. Many Chinese herbal medicines have been identified to have anti-microbial, anti-inflammatory, immune regulatory, and antitumor effects. It would be interesting to review the intervention of Chinese medicines on TAM polarization in different cancers and diseases. Here, we select some of the Chinese medicines to describe as examples.
3.1 Baicalein
Baicalein (5,6,7-trihydroxyflavone) is isolated from the Chinese herb Scutellaria baicalensis root and has many beneficial effects on antitumor, anti-inflammation, anti-fibrosis, and antimicrobial [63, 64]. The treatment of baicalein in breast cancer is the first to explain its effect on TAM regulation. In breast cancer, TAMs showed M2-like phenotype that produced TGF-β1 and enhanced tumor growth and EMT process via PI3K/Akt signaling pathway. In turn, the tumor cells secreted TGF-β1 to maintain TAMs in M2-like phenotype. The positive feedback loop between tumor cells and M2-like macrophages was formed and further contributed to tumor metastasis in the lung. Baicalein administration could block TGF-β1 via inhibiting PI3K/Akt pathway. Besides, instead of altering the population of TAMs, baicalein could drive M2-like macrophages to M1-like macrophage differentiation, with M1 markers increased. Therefore, the application of baicalein in regulating TAM polarization in breast cancer may provide a new understanding of other cancer treatments [65].
3.2 Panax notoginseng
The root of Panax notoginseng (PN) (Burk.) F.H. Chen is one of the popular Chinese herbs also known as sanqi, tianqi, or sanchi in Asia [66]. It has been widely used in many disorders for over 400 years due to its anticancer, anti-inflammatory, antiatherosclerotic, and hemostatic properties [67, 68]. Recent studies have shown that PN not only has cytotoxicity on cancer cells but also can redirect TAM polarization. It is commonly known that M2-like macrophages exert pro-tumorigenic effects on cancer, and to redirect M2 phenotype to antitumor M1 phenotype would be one of the promising strategies in cancer treatment. In many lung cancer studies, it has been reported that high doses of PN administration have direct cytotoxic effects on cancer cells, while the lower dose of PN still have inhibitory effects on tumor growth, suggesting there are other regulatory mechanisms. The in vitro study found that a lower dose of PN did not affect cancer cells, but it could reeducate M2-like macrophages toward M1 phenotypic differentiation [69]. It would help to better explain the pharmacological mechanism of PN.
3.3 Osthole
Osthole [7-methoxy-8-(3-methyl-2-butenyl)-2H-1-benzopyran-2-one] is isolated from Cnidium monnieri (Fructus Cnidii) and belongs to coumarin family, which is a benzopyrone and used as tumor-target drug carrier [70]. Osthole not only has cytotoxicity to cancer cells, such as breast cancer, lung cancer, HCC, and nasopharyngeal cancer (NPC) [71, 72, 73], but also has immunomodulatory effects on different tumors. In pancreatic tumors, osthole decreased M2-like macrophage population both in tumor site and spleen. But it did not affect M1-like macrophages. An in vitro study found that osthole could significantly inhibit STAT6 pathway and p-ERK1/2-C/EBP β signal, thus further inhibiting the M2-like macrophage polarization [74].
3.4 Emodin
Emodin (1,3,8-trihydroxy-6-methylanthraquinone) is a natural anthraquinone derivative from many Chinese herbs, and it has multiple pharmacological effects [75]. One study focused on the effects of emodin on macrophage polarization has shown that it could bidirectionally regulate both M1 and M2 phenotype programs via different signaling pathways, as well as participated in the epigenetic modification. It seems like that emodin can restrain excessive M1- or M2-like macrophages and assist in maintaining homeostasis in different pathologies. For example, in breast cancer, emodin decreased TAM infiltration and inhibited M2-polarized phenotype by suppressing STAT6 and C/EBPβ signaling pathway. Moreover, it could increase H3K27m3 to downregulate M2-related genes.
3.5 Other Chinese medicine
Many other Chinese medicines have protective functions on different diseases through regulating M1/M2 phenotypic switch (as shown in Table 1). For example, curcumin can promote macrophages toward M2-like phenotype to ameliorate liver fibrosis, and it also assists wound healing [76]. Smiglaside A and Ginsenoside Rb3 have protective functions against acute lung injury via inducing M2-like macrophage polarization [77, 78]. These findings may throw a new light for the regulatory mechanisms of Chinese medicines and promote their applications in health and diseases.
The intervention of Chinese medicine on M1/M2 switch in different diseases.
4. Conclusions
Current studies have described the heterogeneity and adaptive plasticity of TAMs in the intrinsic and dynamic TME. They are composed of both tissue-resident macrophages and monocyte-derived macrophages and interplay with TME. The latter one is attracted and recruited to the tumor site via various signals in TME, while TAMs can produce different molecules to remodel TME. In response to different stimuli, TAMs can differentiate into either classically activated/M1 macrophages or alternatively activated/M2 macrophage which involves multiple signaling pathways. The role of TAMs depends on their dichotomic polarization in health and disease. Therefore, they are becoming potential targets for many therapeutic strategies. Chinese medicine has been widely used in a long history of Asia and shows multiple effects on different diseases. Knowing the intervention of Chinese medicine on TAMs polarization may help to better understand the principle of Chinese medicine and contribute to the comprehensive applications in many diseases.
Acknowledgments
The study was financially supported by grants from the research council of the University of Hong Kong (Project Codes: 104004092, 104004460, 104004746); the Research Grants Committee (RGC) of Hong Kong, HKSAR (Project Codes: 764708, 766211, 17152116); Wong’s Donation on Modern Oncology of Chinese Medicine (Project code: 200006276); Gala Family Trust (Project Code: 200007008); and Innovation Technology Fund of Hong Kong (ITF. Project code: 260900263).
Conflict of interest
The authors have no conflict of interest.
Abbreviations
AP-1
activator protein 1
ARG1
arginase-1
ATM
adipose tissue macrophage
CCR
C-C motif chemokine receptors
CSF1
colony stimulating factor
DLL
Delta-like protein
EGF
endothelial growth factor
FcR
Fc receptor
FOXO1
Forkhead Box O1
GPCR
G-protein-coupled receptors
HFD
high-fat diet
HIF
hypoxia inducible factor
IFN
interferon
IL
interleukin
iNOS
inducible nitric oxide synthase
IRF
interferon regulatory factor
JAK
Janus kinase
JNK
c-Jun N-terminal kinase
LPS
lipopolysaccharide
MAM
metastatic-associated macrophage
MAPK
mitogen-activated protein kinase
MMP
metalloprotease
mTOR
mammalian target of rapamycin
NAFLD
nonalcoholic fatty liver disease
NICD
intracellular domain of notch receptor
NPC
nasopharyngeal cancer
PDGF
platelet-derived growth factor
PI3K
phosphoinositide-3-kinase
PIP2
phosphatidylinositol 4,5-bisphosphate
PIP3
phosphatidylinositol 3,4,5-trisphosphate
PN
Panax notoginseng
PPAR
peroxisome proliferator-activated receptor
PRR
pattern recognition receptor
RBP-J
recombination signal binding protein for immunoglobulin Kappa J region
ROS
reactive oxygen species
Smad3
SMAD family member 3
SOCS
suppressor of cytokine signaling
STAT
signal transducer and activator of transcription
TAM
tumor-associated macrophages
TGF
transforming growth factor
Th1
type 1 T helper
Th2
type 2 T helper
TLR
Toll-like receptor
TME
tumor microenvironment
TRAF
TNF receptor-associated factor
VEGF
vascular endothelial growth factor
Ym1
chitinase-like 3
\n',keywords:"tumor microenvironment, tumor-associated macrophage, polarization, Chinese medicine",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/67326.pdf",chapterXML:"https://mts.intechopen.com/source/xml/67326.xml",downloadPdfUrl:"/chapter/pdf-download/67326",previewPdfUrl:"/chapter/pdf-preview/67326",totalDownloads:173,totalViews:0,totalCrossrefCites:0,dateSubmitted:"December 4th 2018",dateReviewed:"April 24th 2019",datePrePublished:"May 29th 2019",datePublished:null,readingETA:"0",abstract:"Macrophage polarization is a spectrum of phenotypes and generally can be classified into two states: (1) classically activated or M1 macrophages, which can be driven by lipopolysaccharide (LPS) alone or in association with Th1 cytokines and produce pro-inflammatory cytokines such as TNF-α, IL-6 and, IL-12, and (2) alternatively activated M2 macrophages, which can be promoted by Th2 mediators IL-4 and IL-13 and produce anti-inflammatory cytokines such as TGF-β and IL-10. Current studies have found that the phenotypic switch between M1 and M2 macrophages governs the fate of an organ in inflammation or injury. The imbalance of M1/M2 polarization is closely involved in various pathological processes and is becoming a potential target for therapeutic strategies. Traditional Chinese medicine is an integrated healthcare system composed of many practices and is characterized by multi-target, multi-level, and coordinated intervention effects. Chinese medicines nowadays are applied to regulate phenotype polarization of macrophages to improve the microenvironment, thus ameliorating or even eliminating the symptoms. In this chapter, we will discuss the molecular mechanisms of macrophage polarization, their roles in health and disease, and the intervention with Chinese medicines to modulate the polarization of macrophages in tumor microenvironment (TME) for therapeutic purpose.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/67326",risUrl:"/chapter/ris/67326",signatures:"Yuanjun Lu, Hor Yue Tan, Ning Wang and Yibin Feng",book:{id:"8590",title:"Macrophage at the Crossroads of Innate and Adaptive Immunity",subtitle:null,fullTitle:"Macrophage at the Crossroads of Innate and Adaptive Immunity",slug:null,publishedDate:null,bookSignature:"Dr. Khalid Hussain Bhat",coverURL:"https://cdn.intechopen.com/books/images_new/8590.jpg",licenceType:"CC BY 3.0",editedByType:null,editors:[{id:"162478",title:"Dr.",name:"Khalid Hussain",middleName:null,surname:"Bhat",slug:"khalid-hussain-bhat",fullName:"Khalid Hussain Bhat"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"14428",title:"Prof.",name:"Yibin",middleName:null,surname:"Feng",fullName:"Yibin Feng",slug:"yibin-feng",email:"yfeng@hku.hk",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. TAM polarization and molecular mechanisms",level:"1"},{id:"sec_2_2",title:"2.1 TAM polarization",level:"2"},{id:"sec_3_2",title:"2.2 Molecular mechanisms in regulating TAM polarization",level:"2"},{id:"sec_3_3",title:"2.2.1 The JNK signaling pathway",level:"3"},{id:"sec_4_3",title:"2.2.2 The PI3K/Akt signaling pathway",level:"3"},{id:"sec_5_3",title:"2.2.3 The JAK/STAT signaling pathway",level:"3"},{id:"sec_6_3",title:"2.2.4 The Notch signaling pathway",level:"3"},{id:"sec_7_3",title:"2.2.5 Other molecular mechanisms",level:"3"},{id:"sec_10",title:"3. Roles of TAM polarization and Chinese medicine intervention",level:"1"},{id:"sec_10_2",title:"3.1 Baicalein",level:"2"},{id:"sec_11_2",title:"3.2 Panax notoginseng",level:"2"},{id:"sec_12_2",title:"3.3 Osthole",level:"2"},{id:"sec_13_2",title:"3.4 Emodin",level:"2"},{id:"sec_14_2",title:"3.5 Other Chinese medicine",level:"2"},{id:"sec_16",title:"4. 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