Kurdistan Regional Government Ministry of Higher Education and Scientific Research Sulaimani University Faculty of Medical Sciences School of Medicine
Correlation of Serum Tryptase Levels with Healthy Obese Individuals and Co-morbidly Obese Patients in Sulaimani Governorate A Thesis Submitted to the Council of School of Medicine/Faculty of Medical Science at University of Sulaimani in Partial Fulfillment of the Requirements for the Degree of Master in Clinical Biochemistry By
Tebeen Jamal Nadir M.B.Ch.B. (2010) Supervised by
Asst. Prof. Dr. BestonFaiekNore PhD in Cellular Biochemistry and Genetics
Supervisor Certification I certify that this thesis conducted by (Tebeen Jamal Nadir) was prepared under my supervision at the School of Medicine, Faculty of Medical Science at the University of Sulaimani, as partial fulfillment of the requirements for the Degree of Master of Science in Clinical Biochemistry.
Asst. Prof. Dr. BestonFaiekNore PhD in Cellular Biochemistry and Genetics
In view of the available recommendation, I forward this thesis for debate by the examining committee.
Asst. Prof. Dr. Kamal Ahmed Saeed M.B.Ch.B, C.A.B.S Head of Postgraduate Studies Unite School of Medicine Faculty of Medical Science University of Sulaimani
Linguistic Evaluation Certification This is to certify that (I, Jutiar O. Saih) has proofread this thesis entitled(Correlation of Serum Tryptase Levels with Healthy Obese Individuals and Co-morbidly Obese Patients in Sulaimani Governorate), prepared by ( Tebeen Jamal Nadir). After marking and correcting the mistakes, the dissertation was handed again to the researcher to make the correction in this last copy.
Proofreader:Jutiar O. Salih Date: 18th Jan. 2015 Department of English, School of Language, Faculty of Humanities, University of Sulaimani.
Examining Committee Certification We, the Examining Committee, certify that we have read this thesis and discussed its context with the student. In our opinion the work is adequate as a thesis for the degree of Master of Science in Clinical Biochemistry.
Name: Dr. Taha Othman MahwiName: Dr. EsmailSalihKakeScientific Grade: ProfessorScientificGrade:Professor Date: 21/2/2015Date: 21/2/2015
Chairman
Member
Name: Dr. KawaAbdullahMohmmad Amin Name: Dr. BestonFaiekNore Scientific Grade: Asst. Professor Scientific Grade: Asst. Prof. Date: 21/2/2015 Date: 21/2/2015 MemberMember and supervisor
Approved by the council of the School of Medicine Assist. Prof. Dr. Ari Sami HussainNadhim M.B.Ch.B, FICMS, FRCS, FAANS Dean- School of Medicine Faculty of Medical ScienceUniversity of Sulaima
Dedication………. To My soulmate, friend, and husband, Hunar. The beautiful flower in my life, my mother. My lovely family.
Acknowledgements First and for most, I would like to thank God, the Compassionate and the Merciful, for giving me His showers of blessings throughout my research work to be able to proceed successfully. A number of wonderful people have greatly supported me to complete my study. To only some of them it is possible to give particular mention here. I would like to express the deepest appreciation to my supervisor Dr. BestonFaiekNore, who has shown the attitude and the substance of a genius. He continually and persuasively guided me in all time of research and throughout the course of my dissertation. My gratefulness and thanks to Dr. Ban Mousa for her generosity, kind care, and support. I wish to thanks my colleague Dr. Saman Hussein and his staff for letting me work part of my sample collection in their laboratory and helping me whenever I asked for it. Special thanks go to Dr. Taha Othman Mahwi and Dr. Govand Ali for helping me throughout my practical works. I want to thank Dr. Zhian Salah in the Community Department for doing statistical works for me. Finally, and most importantly, I would like to thank my husband Hunar. His encouragement, constant support, motivation and unwavering love were undeniably the bedrock upon which the past three years of my life have been built.
Abstract A. Background Obesity is an abnormal human condition, which has become one of the most serious public health challenges over the last few decades. The recent International Association for the Study of Obesity/International Obesity Taskforce (IASO/IOTF) analysis estimates that approximately one billion adults are currently overweight; in addition 475 millions are obese. Although obesity is not a disease per se, but it counts for the major risk factor for developing many human diseases, such as type2 diabetes, dyslipidemia, cardiovascular disease and certain types of cancer at later ages. Serum Tryptase (ST) is a protease secreted by mast cells. Thus, it is counted to be an indirect measure for obesity, since it is known that mast cell numbers are elevated in obese individuals.
B. Aims The major objectives of this study are: 1. To find any correlation between ages, gender, BMI, FBG, HbA1c, and lipid profile with Serum Tryptase a possible biomarker for obese severity. 2. To estimate and correlate the level of ST in individuals without obesity-relatedcomplications and those with obesity related complications like dyslipidaemia and type 2 diabetes mellitus (T2DM) in our locality. 3. To determine if the ST is a suitable biomarker for obesity or it is more appropriate for obesity-related complications such as type 2 diabetes mellitus (T2DM) and dyslipidemia.
I
C. Material and Methods The sample collection of the study was carried out in March 2014 to September 2014, obtained from 250 individuals. They were sub-divided into four groups including; 100 obese patientswithtype2diabetes mellitus(T2DM) admitted to (diabetic and endocrine glands center in Sulaimani), 78 obese patients with dyslipidemia, 22 healthy obese individuals admitted to central laboratory in Sulaimani, and 50 healthy volunteers with normal weight as control group. Venous blood has been taken from each individual for analysis of Serum Tryptase levels, lipid profiles, serum glucose, and HbA1c level.
D. Results There was a statistically significant difference (P<0.001) among study groups with higher ST found among diabetic obese individuals than obese dyslipidemic patients, healthy obese individuals, and normal weight participants. A significant increase of ST was found with BMI and age regardless of underlying complications. Furthermore, no significant correlation of ST with gender, HbA1c level, and FBG was found.
E. Conclusions 1. The ST level is elevated with age, but no differences in it is concentration have been found between genders.
2. The ST level was significantly higher in obese participants regardless of the status of obesity-related-complications, as compared to the healthy (control) participants.
3. The FBG and HbA1c level does not show significant correlation with the ST concentration. II
4. The obese-related-type 2 diabetes mellitus and dyslipidemia also demonstrate a significant elevation in the ST, as compared to healthy obese individuals.
5. Among dyslipidemia markers, only LDL and HDL show a significant correlation with the ST levels, while LDL shows a positive correlation, HDL shows a significantly inverse relation with ST.
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List of contents Subject Titles
Page No.
Abstract………………………………………………………………………….I List of contents………………………………………………………................IV List of figures…………………………………………………………………..XII List of tables...………………………………………………………………….XIV List of abbreviations………………………………………………...................XVI
Chapter One: Introduction and literature review Introduction …………………………………………………………….. Literature review…………………………………………………........... 1.1 Obesity………………………………………………………………………….1 1.1.1 Classification of obesity……………………………………….…...................1 1.2 Obesity prevalence……………………………………………………………...2 1.2.1 Demographic variation of obesity………………….………………………....3 1.2.1.1 Gender……………………………………………………………………....3 1.2.1.2 Race or ethnic groups……………………………………………………….4 1.2.1.3 Age………………………………………………………………………….4 1.2.1.4 Socioeconomic status………………………………...……………………..4 1.3 Consequence of obesity…………………………………………………………5
IV
1.3.1 Metabolic syndrome………………………………………………………….6 1.3.2 Type 2 diabetes mellitus (T2DM)…………………………………………….6 1.3.3 Dyslipidemia………………………………………………………………….7 1.4 Assessment of obesity…………………………………………………………..9 1.4.1 Anthropometric measures…………………………………………………….9 1.4.1.1 Body mass index……………………………………………………………9 1.4.1.1 .1 Body mass index in children and adolescent…………………………...10 1.4.1.2 Waist circumference and hip circumference……………………………...11 1.4.1.3 Skinfold thickness…………………………………………………………13 1.5 Pathogenesis of obesity………………………………………………………..13 1.5.1 Principle of energy balance………………………………………………….13 1.5.1.1 Energy intake………………………………………………………………14 1.5.1.2 Energy expenditure……………………………………………..................15 1.5.1.2.1 Resting energy expenditure…………………………………...................15 1.5.1.2.2 Physical activity related energy expenditure……………………………16 1.5.1.2.3 Thermic effect of food………………………..………………………….16 1.5.1.3 Energy stored in the body…………………………………………………17 1.5.1.4 Consequence of energy imbalance……………………………...................17 1.5.2 Etiology of obesity…………………………………………………………..18 V
1.5.2.1 Genetic factors…………………………………………………………….18 1.5.2.1.1 Genetic mutation………………………………………………………...18 1.5.2.1.2 Polygenic interaction……………………………………………………20 1.5.2.1.3 Epigenetics………………………………………………………………20 1.5.2.2 Medical causes of obesity…………………………………………………20 1.5.2.2.1 Congenital syndrome……………………………………………………21 1.5.2.2.2 Neuroendocrine causes………………………………………………….21 1.5.2.2.3 Psychiatric disorders…………………………………………………….21 1.5.2.2.4 Drug related causes……………………………………………………...22 1.5.2.3 Environmental factors…………………………………………………….22 1.6 Biochemical process of obesity……………………………………………….22 1.6.1 Adipose tissue……………………………………………………………….23 1.6.1.1 Adipocytes………………………………………………………………....25 1.6.1.2 Mechanism of lipid management in adipocyte……………………………26 1.6.1.3 Adipose tissue in obesity…………………………………………………..27 1.6.1.3.1 Histological changes in WAT…………………………………………...27 1.6.1.3.2 Functional changes in blood supply…………………………………….28 1.6.1.3.3 Changes in energy storage of adipose tissue……………………………28 1.6.1.3.4 Changes in adipokines profiles…………………………………………28 VI
1.6.1.3.5 Mitochondrial dysfunction……………………………………………...29 1.6.1.3.6 Adipose tissue fibrosis………………………………………………….29 1.7 Mast cells in obesity…………………………………………………………..29 1.7.1 Mast cells……………………………………………………………………29 1.7.1.1 Physiology of mast cells…………………………………………………..30 1.7.1.2 Mast cell functions……………………………………………..................31 1.7.1.3 Mast cell subtypes and heterogeneity………………………….................31 1.7.2 Role of mast cells in obesity………………………………………………..32 1.8 Human tryptase………………………………………………………………..33 1.8.1 Tryptase structure…………………………………………………………...33 1.8.2 Classification of tryptase……………………………………………………34 1.8.2.1 -tryptase………………………………………………………………….35 1.8.2.2 -tryptase………………………………………………………………….35 1.8.2.3 -tryptase………………………………………………………………….36 1.8.2.4 -tryptase…………………………………………………………………..36 1.8.3 Processing and activation…………………………………………………...36 1.8.4 Biological activities…………………………………………………………37 1.8.4.1 Pro-inflammatory effects………………………………………………….38 1.8.4.2 Tryptase substrate…………………………………………………………38 VII
1.8.4.3 Protease activated receptors……………………………………………….39 1.8.5 Mast cell tryptase as biomarkers……………………………………………39
Chapter Two: Materials and Methods 2.1Materials……………………………………………………………………….42 2.1.1 Laboratory equipments……………………………………............................42 2.1.2 Kits and reagents…………………………………………………………….43 2.1.3 Study design………………………………………………………………....43 2.2 Methods………………………………………………………………………..45 2.2.1 Inclusion and Exclusion criteria…………………………………………….45 2.2.1.1 Inclusion criteria…………………………………………………………...45 2.2.1.2 Exclusion criteria………………………………………………………….45 2.2.2 Questionnaire form…………………………………………………………..46 2.2.3 Measuring BMI……………………………………………………………...47 2.2.4 Sample collection…………………………………………………………....47 2.2.5 Measurement of biochemical markers………………………………………47 2.2.5.1 Human mast cell tryptase assay…………………………………………...47 2.2.5.1.1 Principle of the assay…………………………………………………....47 2.2.5.1.2 Assay procedure………………………………………………………....48 2.2.5.1.3 Calculation………………………………………………………………48
VIII
2.2.5.2 Measurement of serum total cholesterol………………………………….49 2.2.5.2.1 Test principle………………………………………………………….…49 2.2.5.3 Measurement of serum triglycerides……………………………………....50 2.2.5.3.1 Test principle…………………………………………………………….50 2.2.5.4 Determination of high density lipoprotein cholesterol……………………51 2.2.5.4.1 Test principle……………………………………………………………51 2.2.5.5 Determination of serum low density lipoprotein cholesterol and very low density lipoprotein cholesterol…………………………………………………….52 2.2.5.6 Measurement of serum glucose concentration……………………………53 2.2.5.6.1 Test principle…………………………………………………………….53 2.2.5.7 Measurement of glycated hemoglobin……………………………………53 2.2.5.7.1 Test principle……………………………………………………………53 2.3 Statistical analysis…………………………………………………………….54
Chapter Three: Results 3.1 Demography of the samples…………………………………….......................55 3.2 Serum Tryptase level inobese and control groups……………………………56 3.2.1 Chi-square test……………………………………………………………….56 3.2.2 ANOVA test………………………………..………………………………..56 3.2.3 Box-whiskers plot ………………………………………………………......57 3.3 Serum Tryptase concentration in relation to age and gender……………….....58 IX
3.3.1 Serum Tryptase and age……………………………………………………..58 3.3.2 Serum Tryptase and gender………………………………………………….60 3.4 Serum Tryptase in obesity...…………………………………………………...61 3.4.1 Serum Tryptase and BMI……………………………………………………61 3.4.2 Serum Tryptase in classes of obesity………………………………………..62 3.5 Serum Tryptase and type 2 diabetes mellitus (T2DM)………………………..63 3.5.1 Serum Tryptase in controlled and uncontrolled type 2 Diabetes……………63 3.5.2 Serum Tryptase fasting blood glucose……………………………………....64 3.6 Serum Tryptase and dyslipidemia…………………………………………......65
Chapter Four: Discussion 4.1 Body mass index………………………………………………………………69 4.2 Role of Serum Tryptase in obesity……………………………….....................69 4.3Role of serum Tryptase in type 2 diabetes mellitus (T2DM)…………………..70 4.4 Role of Serum Tryptase in obese patients with dyslipidemia…………………72 4.5 Serum Tryptase in obese individuals without its complications………………74 4.6 Serum Tryptase level and age…………………………………………………75 4.7 Influence of gender on Serum Tryptase……………………………………….76 4.8 Status of Serum Tryptase among smokers and alcoholics………………….....77
Conclusions…………………………………………............................78 X
Recommendations………………………………….............................79
References………………………………………….................80 Arabic abstract……………………………………………………….. Kurdish abstract……………………………………………………..
XI
List of figures Title
Page No.
Fig. 1.1: Epidemic of obesity worldwide………………………………………….3 Fig.1.2: Pathogenesis of dyslipidemia in obesity………………………………….8 Fig.1.3: Center for disease control and prevention growth chart, BMI for age percentile in boys (2-20)…………………………………………………………..11 Fig.1.4: The correlation of visceral fat and waist circumference…………………12 Fig.1.5: The factors that regulate appetite through effect on central neural circuits………………………………..……………………………………………15 Fig.1.6: A central pathway through which leptin acts to regulate appetite and body weight………………………..…………………………………………………….19 Fig.1.7: Biochemical changes during obesity……………………………………..23 Fig.1.8: Adipose tissue composition………………………………………………24 Fig.1.9: Some factors that secret by white adipose tissue…………………………25 Fig.1.10: Lipid management in the adipocytes…………………………………...27 Fig.1.11: Summary of mast cell function…………………………………………31 Fig.1.12 Human mast cell immune staining of white adipose tissue in lean and obese individuals…………………………………………………..........................33 Fig.1.13: Structure of human tryptase tetramer…………………………………...34 Fig.1.14: Activation and secretion of andtryptase ……………………….37
XII
Fig.2.1:
Standard
curve
diagram
of
mast
cell
tryptase
using
known
standard……………………………………………………………………………49 Fig.3.1: Serum Tryptase concentration according to study group by box-whisker plot…………….…………………………………………………………………..57 Fig.3.2: Linear regression analysis shows a positive correlation between Serum Tryptase and ages in years………………………………………………………...59 Fig.3.3: Box-whisker plot show ST concentration according to age……………..59 Fig.3.4: Box-whisker plot between serum tryptase and gender…………………..60 Fig.3.5: Box-whisker plot between serum tryptase in normal weight and obese individuals…………………………………………………………………………61 Fig.3.6: Illustrate significant correlation among three classes of obesity and serum tryptase by box-whisker plot………………………………………………………62 Fig.3.7: Shows a box-whisker plot between HbA1c and serum tryptase concentration………………………………………………………………………63 Fig.3.8: Box-whisker plot between fasting blood glucose and serum tryptase concentration……………………………………………………………………....65 Fig.3.9: Linear regression analysis shows a positive relation between serum tryptase and low density lipoproteins…………………………………………….68 Fig.3.10: Linear regression analysis shows a negative relation between serum tryptase and high density lipoprotein…………………………………………….68
XIII
List of tables Title
Page No.
Table 1.1: Classification of obesity based on body mass index……………………2 Table 1.2: Body mass index cut-off points for adults……………………………..10 Table 1.3: Obesity gene defects in human………………………………………...19 Table 2.1: Instruments……………………………………………………………..42 Table 2.2: Kits and reagents…………………………………………………….....43 Table 3.1: Characteristic of the study design……………………………………..55 Table 3.2: Chi-square test of Serum Tryptase level in obese and control groups……………………………………………………………………………...56 Table 3.3: ANOVA test between SerumTryptase and study group………………57 Table 3.4: ANOVA age in different groups with Serum Tryptase………………..58 Table 3.5: Chi-square test of Serum Tryptasein relation to gender………………60 Table 3.6: Shows significant correlation between Serum Tryptase in normal and obese groups based on their body mass index…………………………………….61 Table 3.7: ANOVA comparison between mean Serum Tryptase in all three classes of obesity………………………………………………………………………….62 Table 3.8: Illustrate non-significant correlation of Serum Tryptase among control and uncontrolled diabetic patients by independent T-test…………………………64 Table 3.9: Show non-significant correlation between Serum Tryptase and fasting blood glucose……………………………………………………………………...64 XIV
Table 3.10: Chi-square test between Serum Tryptase and triglyceride…………..65 Table 3.11: Chi-square test between Serum Tryptase and cholesterol…………..66 Table 3.12: Chi-square test between Serum Tryptase and very low density lipoprotein…………………………………………………………………………66 Table 3.13: Chi-square test between Serum Tryptase and low density lipoprotein…………………………………………………………………………67 Table 3.14: Chi-square test between Serum Tryptase and high density lipoprotein…………………………………………………………………………67
XV
List of abbreviations ANOVA: Analysis of variance BAT:
Brown adipose tissue
BMI:
Body mass index
CDC: Center for disease control and prevention CHOD:
Cholesterol oxidase
CPA:
Carboxypeptidase
CRP:
C-reactive protein
CT:
Computed tomography
CVD:
Cardiovascular disease
D.M:
Diabetes mellitus
EDTA:
Ethylenediaminetetraacetic acid
ELISA:
Enzyme linked immune sorbent assay
FBG:
Fasting blood glucose
FFA:
Free fatty acid
FFM:
Free fat mass
FTO:
Fat mass and obesity associated
G-6-PDH: Glucose-6- phosphate dehydrogenase GK:
Glucokinase XVI
GLP-1:
Glucagon-related peptide-1
GPO:
Glycerol phosphate oxidase
HbA1c:
Hemoglobin A1c
HC:
Hip circumference
HDL:
High density lipoprotein
HK:
Hexokinase
HSL:
Hormone sensitive lipase
IgE:
Immunoglobin E
IgG:
Immunoglobin G
IL-6:
Interleukin-6
LDL:
Low density lipoprotein
LPL:
Lipoprotein lipase
LST:
Lean soft tissue
MCH:
Melanin concentrating hormone
MCT:
Mast cell tryptase
MES:
2- Morpholinoethane sulfonic acid
MGL:
Monoacylglycerol lipase
MI:
Myocardial infarction
MRI:
Magnetic resonance imaging XVII
MSH:
Melanocyte stimulating hormone
PAEE:
Physical activity-related energy expenditure
PAI:
Plasminogen activator inhibitor
PARs:
Protease activated receptors
PKA:
Protein kinase-A
POD:
Peroxidase
PWS:
Prader-willi syndrome
REE:
Resting energy expenditure
SCF:
Stem cell factor
SD:
Standard deviation
SE:
Standard error
SREBP-1c: Sterol regulatory element binding protein- 1c ST:
Serum tryptase (mast cell)
TAG:
Triacylglycerols
TBW:
Total body water
TEE:
Total energy expenditure
TEF:
Thermic effect of food
TG:
Triglyceride
TINIA:
Turbidimetric inhibition immunoassay XVIII
TNF-:
Tumor necrosis factor-
TRIS:
Tris (hydroxyl methyl) aminomethane
TTAB:
Tetradecyltrimethyl ammonium bromide
T2DM:
Type 2 diabetes mellitus (T2DM)
VIP:
Vasoactive intestinal peptide
VLDL:
Very low density lipoprotein
WAT:
White adipose tissue
WC:
Waist circumference
WHO:
World health organization
WHtR:
Waist to hip ratio
XIX
CHAPTER ONE
INTRODUCTION And LITERATURES REVIEW
Chapter One
Introduction and Literatures Review
1.1 Obesity Obesity is a chronic metabolic disorder characterized by an increase in number and/or the size of adipocytes that leads to lipid deposits within and around tissues and organs involved in energy metabolism (Oliveros et al., 2014).Excess lipids are going to liver, skeletal muscle, heart, blood vessels, and the pancreaticcells. This ectopic fatty infiltrations is associated with higher rate of insulin resistance, type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, cardiovascular diseases (Clark et al., 2014), liver diseases (Sun and Karin, 2012), and some malignancies including breast, colon, endometrial cancer and many other type of cancer (Pi-Sunyer, 2002). Obesity is becoming a major public health concern, with high prevalence in both developed and developing countries and now it is a fifth leading risk factor for global death (Aronne and Segal). Therefore, obesity is a costly burden for healthcare systems and also affected individuals (Au, 2012).
1.1.1
Classification of obesity Although it is difficult to assess body fatness in population, the most widely
used method for evaluation and classification of obesity is by measuring body mass index (BMI) which is weight (kg)/height squared (m2) (Table 1.1). Obesity is defined when body mass index is equal or greater than 30kg/m2(Ross, 2014). There are also many other methods for assessment and classification of obesity that will be discussed in this chapter.
1
Chapter One
Introduction and Literatures Review
Table 1.1: Classification of obesity based on BMI values(Cecil et al., 2012).
Body Weight Underweight Normal Overweight Obesity Obesity Obesity
BMI Kg/M2 <18.5 18.5-24.9 25.0-29.9 30.0-34.9 35.0-39.9 ≥40
Obesity Classes
I II III
1.2 Obesity prevalence Evidence now suggested that obesity increases in both children as well as an adult very rapidly, the true heath consequences become only apparent in a future (Fig.1.1) (de Onis, 2004). By 1995 there were estimated 200 million obese adult worldwide, by 2000 the number of obese individuals has increased to over 300 million. In developing countries it is estimated that over 115 million people were suffering from obesity and its consequences (Derby et al., 2006). By 2005, 400 million adults were obese, and at least 20 million children below age 5 were suffering from obesity (Ross, 2014). The global prevalence of obesity has raised to a level that by 2008 over 200 million men and nearly 300 million women were obese, and more than 40 million children under age 5 were obese by 2012(Ross, 2014). Worldwide, theproportion of adults with(BMI) of 25 kg/m2 or greater increased between 1980 and 2013 from 28.8% to 36.9% in men, and from 29.8% to 38.0% in women, and the prevalence also increased in children and adolescents in developed countries from 23.8% of boys and 22.6% of girls were overweight or obese in 2013 (Ross, 2014). 2
Chapter One
Introduction and Literatures Review
Figure 1.1: Epidemics of obesity worldwide (de Onis, 2004).
1.2.1 Demographic variations of obesity 1.2.1.1 Gender Obesity affects both men and women, with some remarkable variations. Overweighs are most dominant in men, while obesity is more dominant in women(Ross, 2014)but still the reason is obscure. According to World Health Organization (WHO), individuals above 15 years old in the eastern Mediterranean covering 16 countries including Kuwait, Jordan, Egypt, United Arab Emirate, Saudi Arabia, and Bahrain, the prevalence of obesity and overweight in these countries ranges from 74% to 86% in women, and 69% to 77% in men respectively. This indicates high rates of obesity among women than men in neighboring countries (Mediterranean, 2010). Also in South Africa the prevalence of obesity is higher in women and 60% of women were either overweight or obese (Puoane et al., 2002). Recent data in Unites States of America found, that obesity prevalence between whites is similar in men (36.4%) and women (33.4%). On the other hand obesity rates are much higher in African-American women (58.6%) than in 3
Chapter One
Introduction and Literatures Review
African-American men (38.8%), and likewise, obesity rates are higher in Hispanic (Spanish speaking population) women (40.7%) than Hispanic men (35.3%) (Flegal et al., 2012).
1.2.1.2 Race or ethnic group Obesity affects all populations worldwide. However, certain ethnic and racial groups appear to be particularly predisposed. The Pima Indians of Arizona and other ethnic groups native to North America have a particularly high prevalence of obesity. In addition, Pacific islanders (e.g., Polynesians, Micronesians, and Maoris), African Americans, and Hispanic populations (either Mexican or Puerto Rican in origin) in North America also have particularly high predispositions to the development of obesity (Finucane et al., 2011). However, research data are missing for other parts of the world.
1.2.1.3 Age The prevalence of obesity elevates with age, and it is identical in boys and girls up to age 12. Then the patterns are diverged, with greater BMI among girls (Gonzalez-Casanova et al., 2013). Then the prevalence of obesity and overweight is increasing steadily from age 20 to 60 years. Thereafter at age 60 the obesity rates begin to decline (Allison and Saunders, 2000).
1.2.1.4 Socioeconomic status In developed countries among women there is an inverse relationship between obesity and socioeconomic status and less consistently among men, where as in developing countries the association is directly linked with poverty (Ball and Crawford, 2005, Kaluski et al., 2007).
4
Chapter One
Introduction and Literatures Review
1.3 Consequence of obesity Obesity is associated with increased mortality and morbidity. The following are some health consequences of excess body weight: A. Cardiovascular disease: 1. Ischemic heart disease (Yusuf et al., 2004). 2. Hypertension (Haslam and James, 2005). 3. Dyslipidemia (Haslam and James, 2005). 4. Deep venous thrombosis and pulmonary embolism (Darvall et al., 2007). B. Endocrine diseases: 1. Diabetes mellitus (Haslam and James, 2005). 2. Infertility (Arendas et al., 2008). 3. Polycystic ovary syndrome (Haslam and James, 2005). C. Neurological diseases: 1. Stroke (Haslam and James, 2005). 2. Migraine (Bigal and Lipton, 2008). 3. Dementia (Beydoun et al., 2008). D. Rheumatology and orthopedic problems: 1. Low back pain (Molenaar et al., 2008). 2. Osteoarthritis (Choi et al., 2005). 3. Gout (Haslam and James, 2005). E. Psychiatric problems (Haslam and James, 2005). F. Pulmonary diseases (Poulain et al., 2006). G. Cancer (Dobbins et al., 2013). H. Dermatological diseases (Yosipovitch et al., 2007).
5
Chapter One
Introduction and Literatures Review
1.3.1 Metabolic syndrome Metabolic syndrome is the major component of modern day epidemics that affect at least one in five adults. It is characterized by cluster of metabolic abnormalities including abdominal obesity, decreased HDL cholesterol, elevated TG level, elevated blood pressure, and impaired glucose regulation (Cameron et al., 2007). Diagnosis of metabolic syndrome can be made by the presence ofCentral obesity (defined as waist circumference ≥ 102cm in men, and ≥ 88cm in women) with any two of the four factors including; elevated plasma TG (≥ 150 mg/ml),reduced HDL cholesterol (<40mg/dl in men and <50mg/dl in women), elevated blood pressure (systolic blood pressure ≥130mmhg or diastolic blood pressure ≥85mmhg), or treatment of previously diagnosed blood pressure, elevated fasting blood glucose (≥100mg/dl)(Alberti et al., 2009). The importance of metabolic syndrome is its association with type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD). Individuals with metabolic syndrome is three times more likely to suffer myocardial infarction (MI) (Cho et al., 2013), and five times more likely to develop T2DM (Janghorbani and Amini, 2012).
1.3.2 Type 2 diabetes mellitus (T2DM) Diabetes mellitus is a widespread metabolic disease, characterized by hyperglycemia and it is associated with microvascular and macrovascular complications. T2DM is the most common type and it accounts for up to 85%-90% of diabetes cases (Zimmet et al., 2001). Obesity is a major risk factor for T2DM and insulin resistance. Although the underlying mechanism of insulin resistance in obese is uncertain, elevated free fatty acids (FFA) in obese is one of the factors that 6
Chapter One
Introduction and Literatures Review
is involved in the development of insulin resistance. Also secretion of proinflammatory cytokines produced from obese white adipose tissue (WAT) or infiltrating leukocytes in WAT is also an important mechanism of insulin resistance (Hotamisligil, 2006). WAT in obese individuals is a reservoir of many cells including T-cells, macrophages, and mast cells, and these cells are responsible for the secretion of pro-inflammatory cytokines. One of the important cytokines is tumor necrosis factor Alfa (TNF- which is able to mediate insulin resistance (Nieto-Vazquez et al., 2008). Other pro-inflammatory cytokines are interleukin-6 (IL-6), monocyte-chemoattractant protein-1 (MCP-1), and interleukin-1 (IL-1), many of these mediator are involves in development of insulin resistance (Zhang and Shi, 2012).
1.3.3 Dyslipidemia Dyslipidemia is frequently related to obesity. Obesity-related dyslipidemia is characterized by increased triglycerides (TG), elevated very low density lipoproteins (VLDL), decreased heavy density lipoprotein (HDL),elevated cholesterol, and elevated low density lipoproteins (LDL) particles (Fig.1.2). The concentration of apo-B is increased, partly due to hepatic overproduction of apo-B containing lipoprotein particles (VLDL, LDL) (Franssen et al., 2011).Obesityrelated dyslipidemia is accepted risk factor for cardiovascular diseases (Tewari et al., 2005).
7
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Figure 1.2: The hallmark of dyslipidemia in obesity is hypertriglyceridemia in part due to increased free fatty acid (FFA) fluxes to the liver, which leads to hepatic accumulation of triglycerides (TG). This leads to an increased hepatic synthesis of large very low density lipoproteins (VLDL), which hampers the lipolysis of chylomicrons due to competition mainly at the level of lipoprotein lipase (LPL) with increased remnant TG being transported to the liver. Lipolysis is further impaired in obesity by reduced mRNA expression levels of LPL in adipose tissue and reduced LPL activity in skeletal muscle. Hypertriglyceridemia further induces an increased exchange of cholesterol esters (CE) and TG between VLDL and HDL and low density lipoproteins (LDL) by cholesterol-estertransfer-protein (CETP). This leads to decreased HDL-C concentrations and a reduction in TG content in LDL. In addition, hepatic lipase (HL) removes TG and phospholipids from LDL for the final formation of TG-depleted small dense LDL. The intense yellow color represents cholesterol, whereas the light yellow color represents the TG content within the different lipoproteins. Obesity induced increases in metabolic processes are marked with green arrows, whereas reductions are marked with red arrows (Klop et al., 2013).
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1.4 Assessment of obesity Evaluation of excess body weight in human can be measured mainly by using anthropometric methods; in addition other tools are also available(Ross, 2014).
1.4.1 Anthropometric measures Anthropometric measurement includes simple, inexpensive, and noninvasive methods that are used for assessment of health and nutritional status of individuals; it includes body weight, height, skin-folds, circumferences, and body mass index (Harrison et al., 2013).
1.4.1.1 Body mass index (BMI) BMI is the most widely used indicator for obesity in population. BMI is calculated as weight in kilogram divided by height in square meter, and it is significantly correlated with total body fat content (Gallagher et al., 2000). BMI is commonly used to classify underweight, overweight, and obesity in adults and children worldwide(Table 1.2). Body mass index has many features in term of accessibility, simplicity, cost, and it is significantly correlated with body fat, morbidity and mortality. Furthermore recommendation for treatment of obesity in clinical setting is based on BMI. However BMI does not directly assess fat distribution in the body, especially of the most metabolically active intra abdominal fat. In this situation waist circumference is better for assessment of intra abdominal fat than BMI (Flint et al., 2010). On the other hand, BMI has low sensitivity (36% to 49%) but high specificity (95% to 99%) (Okorodudu et al., 2010).The validity and accuracy of 9
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BMI also declines by aging, as there are decreases in lean body mass in old population(Romero-Corral et al., 2008). Table 1.2: Body mass index cut-off points for adults. The international classification of underweight, overweight, and obesity (WHO, 2000).
Underweight
BMI (kg/m2) Principal cut-off points <18.50
BMI (kg/m2) Additional cut-off points <18.50
Severe thinness
<16.00
<16.00
Classification
Moderate thinness Mild thinness Normal range
16.00-16.99 17.00-18.49 18.50-24.99
16.00-16.99 17.00-18.49 18.50-22.99 23.00-24.99
≥ 25.00 25.00-29.99
>25.00 25.00-27.49 27.50-29.99
≥ 30.00 30.00-34.99
>30.00 30.00-32.49 32.50-34.99
35.00-39.99
35.00-37.49 37.50-39.99
Cut-off (Normal range)
Overweight Pre-obese Cut-off (Overweight)
Obese Obese class I Cut-off (Class I)
Obese class II Cut-off (class II)
Obese class III
≥ 40.00
> 40.00
1.4.1.1.1BMI in children and adolescents Children grow and obtain lean body mass and fat mass at different rate and there is a large population inter-individual and intra-individual variations. Growth pattern and maturation of children affect both body composition and BMI, made a BMI more complex in children than adults (Ng et al., 2014). Body mass index is used 10
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differently for children and adolescents, according to Center for Disease Control and Prevention (CDC). It is calculated the same as adult but then plotted on to BMI for age growth chart. Instead of set of thresholds for underweight and overweight, the BMI percentile allows comparison with children of the same sex and age. A BMI that is less than the 5th percentile is considered underweight and above the 95th percentile is considered obese for people 20 years old and under. BMI between the 85th and 95th percentile are considered to be overweight (Fig. 1.3) (Flegal et al., 2012).
Figure 1.3: Center for disease and control prevention (CDC) growth chart, BMI for age percentiles in boys (2-20 years old).
1.4.1.2 Waist circumference (WC) and hip circumference (HC)
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Waist circumference (WC) is a best anthropometric measure for the assessment of visceral fat (Fig.1.4). It is easy and feasible measure for central obesity. WC is a good predictor of the risk for a number of diseases especially cardiovascular diseases, type2 diabetes, dyslipidemia, and hypertension (Kinney, 2013).WC is good as BMI and skin fold thickness as indicator of total body fat; it can be measured at midpoint between lower rib margin and top of the iliac crest using stretch resistant tape (David Haslam, 2006 29). WHO cut-points that are recommended for waist circumference to define abdominal obesity are WC greater than 102 cm (40 inch) in men and WC greater than 88 cm (35 inch) in women (Ghandehari et al., 2009). Individuals with large waist circumferences have more than a fivefold greater risk of multiple cardio-metabolic risk factors (Haslam and James, 2005).
Figure 1.4: The correlation of visceral fat and waist circumference are strong (David Haslam, 2006).
Hip circumference (HC) measurement can be taken from the widest portion of the buttocks. Hip circumferences also have a relation with health and disease but in an inverse way, such that relatively larger HC associated with lower risk of 12
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coronary artery disease and type2 diabetes, because HC reflects the muscle mass other than fat mass (Derby et al., 2006).Abdominal obesity by waist to hip ratio is defined as more than 0.90 for men and more than 0.85 for women (Flint et al., 2010). A newer anthropometric index is waist to height ratio (WHtR). It is sensitive, cheap, and a useful indicator for central obesity and it is related cardiovascular disease (Nambiar et al., 2010). WHtR cut-points of 0.5 have been recommended to classify obesity in adults and children and for different ethnic groups (Ashwell and Hsieh, 2005). Study found that WHtR is independent on age and, by this, it will terminate the need for percentile in children (Weili et al., 2007).
1.4.1.3 Skinfold thickness Skinfolds are composed of two layers of subcutaneous tissue, including small and relatively constant amount of skin and different amount of adipose tissue. They are used to describe the anatomical variation in subcutaneous fat pattern (Freedman et al., 2013). Skinfold thickness can be measured by specially designed caliper at different anatomical locations in human body including: biceps, triceps, subscapular, suprailiac, thigh and calf (Ross, 2014). These measures are correlated but not a direct representative of subcutaneous fat thickness, and it is not useful in detecting intra abdominal adipose tissue (Hussain et al., 2014).
1.5 Pathogenesis of obesity 1.5.1 Principles of energy balance
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Obesity is resulting from imbalance between energy intake and energy expenditure (Goran, 2000). Energy balance equation states that any change in body weight (∆Body weight) must be caused by difference between energy intake (E in) and energy expenditure (Eout). Positive energy balance occurs when energy intake is greater than energy expenditure that promotes energy storage and weight gain. Conversely negative energy balance occurs when energy intake is lower than expenditure resulting in decrease in body weight (Kurpad et al., 2005).Basic components of energy balance are energy intake, energy expenditure, and energy storage (Hill et al., 2012).
1.5.1.1 Energy intake It is defined as the caloric or energy content of food that is provided by a major source of diet including: carbohydrate, protein, fat, and alcohol. Human body regulate food intake in a complex way(Guyenet and Schwartz, 2012). Appetite and food intake are influenced by many factors that integrated in the brain specially the hypothalamus. Signals that impinge on hypothalamus are; neural afferents, hormones and metabolites (Hagobian and Braun, 2010). Vagal input is particularly important bringing information from viscera such as gut distension. Hormonal signals such as leptin, insulin, cortisol, and gut peptides such as ghrelin, peptide YY, and cholecystokinin, which signal to the brain (Owyang and Heldsinger, 2011). Metabolites such as glucose through the effect of hypoglycemia can induce hunger; however, glucose is not a major regulator of appetite. These neural, hormonal, and metabolites act by influencing the release and expression of various hypothalamic peptides such as neuropeptide Y (NPY), Agouti related peptide 14
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(AgRP), Melanocyte stimulating hormone MSH), and melanin concentrating hormone (MCH) are known to influence eating behavior (Neary and Batterham, 2009).Longer range signals of satiety are related to energy stores of body (Fig.1.5)(Hill et al., 2012).
Figure 1.5: The factors that regulate appetite through effects on central neural circuits. Some factors that increase or decrease appetite are listed. NPY, neuropeptide Y; MCH, melanin-concentrating hormone; AgRP, Agouti-related peptide; α-MSH, α-melanocytestimulating hormone; CART, cocaine- and amphetamine-related transcript; GLP-1, glucagon-related peptide-1; CCK, cholecystokinin (Harrison and Longo, 2013).
1.5.1.2 Total Energy expenditure (TEE) Total energy expenditure (TEE) is composed of resting energy expenditure (REE), thermic effect of food (TEF), and physical activity-related energy expenditure (PAEE).
1.5.1.2.1
Resting energy expenditure (REE) 15
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It is the largest use of energy expenditure in human at rest, REE is the energy expended by the body to maintain basic physiologic functions such as heart beat, muscle contraction, and maintaining body temperature. REE comprises about 60% to 80% of TEE in most people (Goran, 2000). Basal metabolic rate (BMR) is minimum level of energy that is required by the body to sustain life. REE is slightly(3%) higher than BMR because of the energy required for arousal (Roberts et al., 2004). Basal metabolic rate can be measured by the following equation (Whitney and Rolfes, 2005). Men: (10×wt) + (6.25×ht) - (5×age) +5 Women: (10×wt) + (6.25×ht) - (5×age) -161, when wt is weight in kg, ht is height in cm, and age is in years.
1.5.1.2.2
Physical activity-related energy expenditure (PAEE)
PAEE or the thermic effect of exercise is a term used to describe increase in metabolic rate cause by skeletal muscles for any type of physical movements such as daily activity and exercise. PAEE is the most variable component of TEE ranging from 10% in sedentary persons to 40% of TEE in highly active persons (Hill et al., 2012).
1.5.1.2.3 Thermic effect of food (TEF) TEF or meal induced thermogenesis increases in energy expenditure associated with digestion, absorption, metabolism, and storage of macronutrients. It is about 7% to 10% of caloric content of food that is consumed (Guyenet and Schwartz, 2012). The energy cost of meal is depending on macronutrient composition of food consumed. The TEF is higher for carbohydrate and protein than fat, because the storage of ingested fat is very efficient, while storage of 16
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carbohydrate and protein requires additional energy to convert to storage form glucose to glycogen, amino acids to protein (Butler and Kozak, 2010). Weather obese individuals have lower TEF than lean individuals is a matter of great controversy, if such differences are present, it is not clear whether they existed before the development of obesity and thus as a contributor to weight gain or they arise as a consequence of obesity (Granata and Brandon, 2002).
1.5.1.3 Energy stored in the body Human body stores energy in the form of protein, carbohydrate, and fat. The body has limited capacity for storage of proteins in muscles and organs, and carbohydrates in form of glycogen in liver and muscles, while the capacity of body to store fat is virtually unlimited (Goran, 2000).Triglycerides are stored very compactly inside the fat cells, thereby accounting for 85% for its weight, and it liberates 9.3kcal/g when oxidized, by comparison glycogen and proteins that yields 4.1kcal/g (Ross, 2014).
1.5.1.4 Consequence of energy imbalance The average adult human consumes up to 1 million calories per year, yet healthiest individuals are able to maintain equilibrium, the accurate balance between energy expenditure and energy intake are examples of homeostatic regulation and results in maintenance of body weight and energy stores(Goran, 2000, Harrison and Longo, 2013). An error in matching intake to expenditure of only 5% would result in a change of 15 kg over the course of years. Studies suggest that energy expenditure is affected when energy intake is altered. During food restriction, energy expenditure declines, attenuating the loss of body weight that results from the negative energy 17
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balance, while During overfeeding, some increase in energy expenditure occurs to diminish the increase in body weight that would occur as a result of positive energy balance (Garrow, 2013). The changes in energy expenditure are much greater with underfeeding than with overfeeding, a finding suggesting that the body has a strong capability to protect against loss of body weight and a much weaker capability to protect against body weight gain (Butte et al., 2007).
1.5.2
Etiology of obesity Obesity is single disorder with multiple causes. Body weight is determined
by interaction between genetic, environmental, and psychological factors acting through the mediators of energy intake and expenditure (Harrison and Longo, 2013).
1.5.2.1 Genetic factors Genetic factors accounts for up to 40% of variation in body weight among individuals(Wangensteen et al., 2005). Evidence from family studies found that BMI is correlated between first degree family members, a child of two obese parents has about an 80% chance to become obese, while those of normal weight parents have 15% chance to become obese, identical twin have very similar BMI whether reared together or apart, also adoptees usually resemble their biological parents than adoptive parents (Andreoli et al., 2007).
1.5.2.1.1
Genetic mutations
Recently only a few gene defects have been found as a cause of obesity in humans (Clement and Ferre, 2003).The two most predominant genes that cause obesity in humans and/or animals are (ob/ob) and (db/db) gene that encodes for 18
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leptin and leptin receptor respectively (Chagnon et al., 2003). Leptin is a hormone secreted mainly from adipocytes; it consists of 167amino acids and signals the hypothalamus through leptin receptor (Fig.1.6). High levels of leptin decreases energy intake and increases energy expenditure (Paracchini et al., 2005).Mutations in several other genes have been identified to cause severe obesity in humans (Table 1.3)(Harrison and Longo, 2013).
Figure 1.6: A central pathway through which the leptin acts to regulate appetite and body weight (Harrison and Longo, 2013).
Table 1.3: Some of the obesity related genes and their products and mechanism of actions(Harrison and Longo, 2013).
Gene
Gene Products
Mechanism of obesity
Lep (ob)
Leptin, a fat derived hormone
LepR (db)
Leptin receptor
Mutation prevents leptin from delivering satiety signal; brain perceives starvation Same as above
POMC
Proopiomelanocortin, a precursor of several hormones and neuropeptides
Mutation prevents synthesis of melanocyte- stimulating hormone (MSH), a satiety signal
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Introduction and Literatures Review Pro-hormone convertase-1, a processing enzyme
1.5.2.1.2
Mutation prevents synthesis of neuropeptides probably (MSH)
Polygenic interactions
More than 250 genes, markers, and chromosomal regions have been associated with obesity, but a clinical importance of most of them is still unknown. Obesity is a highly polygenic and a complex disorder in most of the cases; it is likely caused by input of multiple genes that affect food intake and energy expenditure with additional interactions between genes and environments (Clement and Ferre, 2003). Polymorphism of these genes could increase individual susceptibility to obesity (Korner et al., 2008). A common variant in the fat mass and obesity associated (FTO) gene on chromosome 16 is strongly associated with increase BMI in multiple populations. FTO is a gene of unknown function and unknown mechanism of action, but some studies suggest that FTO gene product may be involved in regulation of food intake (Frayling et al., 2007).
1.5.2.1.3Epigenetics Epigenetics is defined as heritable changes, which affect gene function without modifying the DNA sequence. It can affect different biological processes like effect on a methylation pattern of specific genes and imprinting that increase the risk of obesity, an example of imprinted disorder is prader-willi syndrome (PWS) (Herrera et al., 2011). 20
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1.5.2.2 Medical causes of obesity There are several medical conditions that can cause obesity.
1.5.2.2.1
Congenital syndrome
Several congenital syndromes can results in obesity including Prader-Willi Syndrome in which seven genes on chromosome 15q11.2 are deleted or unexpressed on the paternal chromosome (Bittel et al., 2006). A common congenital condition is Down syndrome or Trisomy 21; individuals with Trisomy 21 are at higher risk to become obese as a result of reduced metabolic rate (Melville et al., 2005). In addition, there other congenital syndromes that increase the risk of development of obesity these are Bardet-Biedel Syndrome (Iannello et al., 2002), Alstrom Syndrome (Joy et al., 2007), and Cohen Syndrome(Perlyn and Marsh, 2008), and Carpenter Syndrome (Kivitie-Kallio and Norio, 2001).
1.5.2.2.2
Neuroendocrine causes
It includes; Cushing Syndrome (Guignat and Bertherat, 2014),(Nieman and Ilias, 2005), Hypothyroidism (Reinehr et al., 2008), Polycystic Ovary Syndrome (Gambineri et al., 2002), Growth Hormone Deficiency (Barreto-Filho et al., 2002), Damage to hypothalamus (Williams, 2012), and Insulinoma(Sotoudehmanesh et al., 2007).
1.5.2.2.3
Psychiatric disorders
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They could also contribute to the development of obesity like; Night Eating Syndrome (Lundgren et al., 2008), Binge Eating Disorder (van Zutven et al., 2014), and Depression (Luppino et al., 2010, Fowler-Brown et al., 2012).
1.5.2.2.4
Drug related causes
Iatrogenic weight gain can be caused by using medication of certain classes such as steroids, anti-diabetics, and anti-depressant(Aronne and Segal, 2003).
1.5.2.3 EnvironmentalFactors The rapid increases in the global epidemics of obesity in recent years occurred in time too short for any significant changes in the gene pool to occur within populations. This finding suggests that environmental factors are promoting weight gain. The modern environments encourage food intake because of presence of inexpensive, plentiful, palatable, energy dense fast-food, stress and physical inactivity because of increasing technologic advances. The end result are environments and life-style that serve to increase energy intake and decrease energy expenditure (Hill et al., 2003). Recently, many studies have found additional environmental factors that contribute to the development of obesity; including, prenatal and postnatal influences (Gluckman and Hanson, 2004), toxins (Newbold et al., 2007), viruses (van Ginneken et al., 2009), smoking cessation, and sleep deprivation (Nielsen et al., 2011).
1.6
Biochemical processes of obesity 22
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Biochemically, obesity is excessive accumulation of triacylglycerols in fat cells of adipose tissue that occurs during positive energy balance (Fig.1.7). Accumulation of triacylglycerols is the only way to gain excess body weight because other energy storage as carbohydrate and protein in liver and muscles, do not have the unlimited capability like adipose tissue (Cao, 2014).
Figure1.7: biochemical changes in obesity. Increased food intake stimulates insulin secretion. Insulin in turn, stimulates lipoprotein lipase (LPL), permitting uptake of circulating TG by adipocyte, and insulin simultaneously inhibits hormone-sensitive lipase (HSL) and the release of adipocyte free fatty acids (FFA). The overfed adipocyte may hypertrophy, or a stimulus currently unknown, may trigger differentiation of preadipocytes. The well-fed adipocyte secretes leptin, which circulates and bind to receptors in the hypothalamus, causing glucagon-like peptide-1 (GLP-1) release and inhibiting neuropeptide-Y (NPY), a powerful stimulator of appetite and feeding. Reduced food intake, in contrast, lowers insulin, leading to LPL suppression, activation of HSL, and FFA release. Additionally fasting stimulates release of ghrelin from the stomach, which stimulate GH, but more importantly it stimulates food intake, decrease lipid metabolism, and improve carbohydrate use (Andreoli et al., 2007).
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1.6.1 Adipose tissue Adipose tissues are embedded in a connective tissue matrix, and they compose of pre-adipocytes, mature adipocytes, immune cells such as macrophages, endothelial cells, smooth muscle cells as well as fibroblasts (Fig.1.8). There are two types of adipose tissue: white adipose tissue (WAT) and brown adipose tissue (BAT), in adults brown adipose tissue is scarce and probably non-functional (Saely et al., 2012). On the other hand WAT is well developed in adult humans. It is a metabolically dynamic organ that is a primary site for energy storage in the form of triacylglycerols. It is a major source of fatty acids in the body and it is used as a substrate for generation of energy (ATP) via oxidative phosphorylation (Gesta et al., 2007). WAT also serves as important endocrine organ in human body capable of synthesis of number of biologically active compounds as adipokines that regulate metabolic homeostasis (Fig.1.9) (Ottaviani et al., 2011).
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Figure 1.8: Adipose tissue composition (Schaffler et al., 2005).
Figure 1.9: Some of the factors that secreted by white adipose tissue (WAT), which underlie multifunctional effect of this endocrine organ: FFA, free fatty acids; IL-6, interleukin-6; TNF-, tumor necrosis factor-; PAI-1, plasminogen activator inhibitor (Coelho et al., 2013).
1.6.1.1 Adipocytes In WAT, adipocytes or fat cells emerge from mesenchymal stem cells. It is main function is lipid storage. Fat cells are able to increase their diameter 20-folds and their volume by several thousand-folds the condition called (hypertrophy) or differentiation of pre-adipocytes to mature adipocyte that is called (hyperplasia) in order to accommodate for excess lipid storage in form of triacylglycerols(Halberg et al., 2008).
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1.6.1.2 Mechanism of lipid management in adipocytes Adipose tissue store and manages fatty acids within the body. Fatty acids reaches the adipocytes via three pathways; first free fatty acids (FFA) is associated with albumin in the serum, second lipoprotein lipase (LPL) which is an enzyme associated with outer membrane of fat cells via heparanesulphate proteoglycans, hydrolysis of FFA from triglyceride rich chylomicrons and thirdly via very low density lipoproteins (VLDL) (Tacken et al., 2001). Up on entry into adipocytes, fatty acids are used to synthesize triacylglycerols (TAG) with glycerol via acyl-coA synthetase enzyme in endoplasmic reticulum (ER)(Coleman and Lee, 2004).
TAG is incorporated into lipid droplets, which form at the ER and are covered with PAT family proteins such as perilipin. These pathways are mainly driven by insulin in the fed stat, which in turn stimulates the major transcription factor for fatty acid and triglyceride synthesis, sterol regulatory element binding protein 1c (SREBP-1c) (Azzout-Marniche et al., 2000).
During fasting state lipolysis is stimulated in adipocytes and leads to the release of free fatty acids and glycerol, which then is metabolized by other tissues. Hydrolysis of TAG occurs in three-steps driven by adipose triglyceride lipase (ATGL), hormone sensitive lipase (HSL) and mono-acylglycerol lipase (MGL). The major signaling pathways activating lipolysis are β-adrenergic stimulation and the fasting hormone glucagon. Conversely, Insulin suppresses lipolysis (Fig.1.10) (Carmen and Victor, 2006). 26
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Figure1.10: Lipid management in the adipocyte. Free fatty acids are released lipoprotein lipase (LPL), taken up by the cell and incorporated into triglycerides. Lipid droplets coated with PAT family proteins (TIP47, ADRP, S3-12, perilipin) emerge from the ER. After βadrenergic stimulation, activation of protein kinase- A (PKA) leads to phosphorylation of perilipin (PER) and hormone sensitive lipase (HSL) and free fatty acids are released by lipolysis. ASC: acyl-coA-synthetase, GPAT: glycerol-three phosphate acyl-transferase, PAP: phosphatidic-acid phosphorylase, MGAT: monoacylglycerol acyl-transferase, DGAT: diacylglycerol acyl-transferase(Shi and Burn, 2004).
1.6.1.3 Adipose tissue in obesity The changes in adipose tissues during obesity include many patterns:
1.6.1.3.1
Histological changes in WAT
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There is increase in both number and size of adipose tissue, infiltration of adipose tissue by mononuclear cells, and relative rarefaction of blood vessels and neural structures (Wellen and Hotamisligil, 2003).
1.6.1.3.2Functional changes in blood supply Blood flow and capillary permeability per unit weight of adipose tissue is reduced in obesity(Ardilouze et al., 2004).
1.6.1.3.3
Changes in energy storage of adipose tissue
Glucose uptake and fatty acid uptake increase in obese states (Kersten, 2001). Also in obese WAT there is increase in lipolysis with an excess release of non-esterifiedfatty acids (FFA). It is thought that this increase in FFA is a major cause of secondary complications of obesity especially insulin resistance and type 2 diabetes mellitus (T2DM) and the mechanism underlying these conditions are diverse (Lam et al., 2003).
1.6.1.3.4
Changes in adipokines profiles
Adipokines in white adipose tissue undergo major changes in obesity. The release of most adipokines is increase during obesity except is adiponectin hormone, which, in contrary, will deceases in obese individuals (Yatagai et al., 2003). Inflammatory cytokines are also elevated in obese WAT; an example is monocyte chemoattractant protein-1 (MCP-1) that attracts macrophages to adipose tissue. Other pro-inflammatory cytokines are tumor necrosis factor (TNF interleukin-6 (IL-6), interleukin-1 (IL-1 and C-reactive protein (CRP). The 28
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release of these cytokines induces a chronic low-grade inflammation and insulin resistance (Fain et al., 2004), (Guilherme et al., 2008), respectively.
1.6.1.3.5
Mitochondrial dysfunction
Because -oxidation of fatty acids occurs in mitochondria of adipocytes, decrease number and function of mitochondria in obese states results in lipid overload and it is associated with obesity (Wilson-Fritch et al., 2004).
1.6.1.3.6Adipose tissue fibrosis Another dysfunctional change in obesity is up-regulation of matrix protein of WAT in obese states, this makes adipose tissue scaffold more rigid (Henegar et al., 2008).
1.7Mast cells in obesity 1.7.1 Mast cells Mast cells are multi-functional tissue dwelling cells. They are inflammatory cells similar to macrophage and neutrophils but they localize in almost all major 29
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organs and tissue. Normally, they reside in the area which is in contact with the external environments such as skin, airway, gastrointestinal tract, and urogenital tract, where pathogens and allergens frequently reside (Galli et al., 2005b). Therefore, mast cells are first-line immune cells defending against bacterial and viral infections, and are essential in immediate hypersensitivity reactions, skin allergies, and food anaphylaxis. Mast cells are not just a first line immune cells, they are also found in atherosclerotic lesions (Heikkila et al., 2010), tumors (Maltby et al., 2009), and inflamed adipose tissues(Liu et al., 2009).
1.7.1.1 Physiology of mast cells Mast cell is a hematopoietic cell that originates from CD34 +/CD117+ bone marrow progenitor cells. The progression to mature mast cells depends on the KIT activation [receptor on mast cells for stem cell factor (SCF)] which occurs as a result of SCF-induced KIT dimerization and autophosphorylation then mast cells move via blood circulation and become mature mast cells once they enter the homing tissues under the effect of cytokines within the local milieu (Krishnaswamy et al., 2001). Human mast cell progenitors and mature mast cells express a large array of adhesion molecules and chemokines receptors which are important for the migration and distribution of mast cells to various tissues (Payne and Kam, 2004). Mast cells granules contain many mediators; these mediators can be classified into preformed and newly synthesized mediators. Preformed mediators are stored in secretory granules. Once mast cells are activated, they are released into extracellular environments. This process is called degranulation. Newly
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synthesized mediators are released into extracellular upon activation of mast cells (Moldering, 2010). Degranulation of mast cells may be induced by physical factors such as mechanical trauma, increase temperature, toxins, venoms, and endogenous mediators (proteins, tissue proteases) (Frieri et al., 2013). Activation and degranulation of mast cells could also occur through immunological mechanisms, first is IgE dependent mechanism, whichis the most common type. Human mast cells express the high affinity receptor for IgE, which is called (FcRI); this receptor is present on mast cell membrane. When IgE coated antigen binds to this receptor mast cell degranulation occurs (Galli et al., 2005a).The second mechanism is IgE independent activation and degranulation that could occur via IgG that mediate mast cell activation via a low affinity IgG receptor on surface of mast cells. Also complement activation can cause degranulation of mast cell through anaphylatoxins C5a, C3a, and C4a that are formed during complement activation (Gilfillan and Tkaczyk, 2006).
1.7.1.2 Mast Cell Functions Mast cell function can be summarized into immunological and nonimmunological functions as shown in figure 1.11.
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Figure 1.11: Summary of mast cell functions (Frieri et al., 2013).
1.7.1.3 Mast cell subtypes and heterogeneity There are four types of human mast cells(Krishnaswamy et al., 2001, Dougherty et al., 2010): 1. T-Mast cells express tryptase predominantly and is usually located in mucosal surfaces like alveolar walls and small intestinal mucosa 2. TC-Mast cells express both tryptase and chymase predominantly, and they located in the dermis of the skin, the intestinal submucosa and blood vessels. 3. C-Mast cells contain only chymase and are a rare subtype found in the intestine. 4. T-CPA-Mast cells, which are a newly revealed and unusual type of mast cells, contain tryptase and carboxypeptidase A (CPA). They are found predominantly in asthmatic patients. 32
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1.7.2 Role of mast cells in obesity Despite their main function in allergic responses (Galli et al., 2005a), mast cells have also involved in the pathogenesis of many diseases such as multiple sclerosis (Secor et al., 2000), cancer (Maltby et al., 2009), rheumatoid arthritis (Lee et al., 2002a), atherosclerosis (Xiang and Wang, 2007), and aortic aneurysm (Sun et al., 2007b). Recent study provides evidence that mast cells also contribute to dietinduced obesity in human and mice (Liu et al., 2009). White adipose tissue in obese shows the state of chronic low-grade inflammation with massive recruitment of immune cells. Although macrophages have been the first immune cells explored, lately other cell types have been discovered (Dalmas et al., 2011). Previous studies have found that T cells also accumulate in WAT (Wu et al., 2007). Mast cells are also inflammatory cells similar to macrophage and T cells, but the exact mechanism in which these cells involve in the pathogenesis of human obesity is unclear. However, new studies show direct participation of mast cells in WAT of diet-induced obese mice. They used mast cell-deficient Kitw-sh/W-sh mice, which, lacks mature mast cells due to inversion mutation in promoter region in gene encoding c-Kit13. This gene codes for the stem cell factor (SCF)receptor,a molecule require for mast cell survival and differentiation. When fed a western type diet for 12 weeks, these mice gain significantly less body weight compared with wild-type mice (control) (Liu et al., 2009), (Altintas et al., 2011). Staining human WAT section with a mast cell tryptase monoclonal antibody reveals an increased number of mast cells in WAT in obese individuals compared with lean individuals (Fig.1.12) (Liu et al., 2009).
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Figure 1.12: Human mast cell immune staining of white adipose tissue (WAT) in lean (Right) and obese (Left) individuals (Zhang and Shi, 2012).
1.8Human tryptase Tryptase is the most abundant protein produced by human mast cells, it is also found in basophils. However, mean levels of tryptase in basophils are less than 1% of those found in mast cells. The granules of tryptase are released from mast cells when they are activated; therefore, tryptase may be considered as a marker of mast cell activation or mast cell burden (Schwartz et al., 2003).
1.8.1 Tryptase structure Tryptase is a neutral serine protease from mast cells. The tryptase gene allocated on the short arm of chromosome 16. Tryptase has a molecular weight of 134 kDa. Structure of human tryptase is a tetramer, which consists of four monomers arranged in flat frame-like structure (Fig.1.13). Each monomer contacts its neighbors at two different interfaces through six loop segments. The four active centers of the tetramer are directed towards an oval central pore, restricting access for macromolecular substrates and enzyme inhibitors (Schwartz, 2001). Heparin and other polymer that maintain high anionic charge stabilize the tryptase tetramer. Without heparin tryptase tetramer losses activity and dissociate into inactive monomer. Another way to keep the monomers stable in heparin-free 34
Chapter One
Introduction and Literatures Review
environment is the presence of NaCl which produces hydrophobic interactions that keep monomers together as active tetramer (Liang et al., 2012).
Figure 1.13: Structure of human tryptase tetramer. The four monomers A, B, C, and D (clockwise) are shown as blue, red, green, and yellow ribbons, each surrounded by a semitransparent surface(McGrath et al., 2006).
1.8.1 Classification of tryptase Tryptase protein in human has four isoforms, but only two of them, namely alpha () and beta () are medically important, and these two have nearly 90% sequence identity. The other types are gamma (), and delta ().
1.8.1.1 tryptase
-tryptase is a predominant form of tryptase stored in mast cell granule and
is not normally released into circulation. However, increase level of -tryptase can be seen during sever inflammation such as systemic anaphylaxis (Schwartz, 2006). It is also classified into I, II, and III subtypes. I and III differ from II in that amino acid in position 142 is Asn in first two whereas II has Lys at that position.
35
Chapter One
Introduction and Literatures Review
As a result, I- and III-tryptase is glycosylated, while II-tryptase is unglycosylated at the 142 amino acid position (Vitte, 2014).
1.8.1.2 tryptase
tryptase is of two subtypes;I and II. The pro-tryptase along with
protryptase is secreted constitutively from mast cells even in the absence of mast cell degranulation. In contrast tryptase, which is stored in granules, is not released unless degranulating agents challenges the mast cells. As a result,
tryptase is the predominant form of tryptase in serum under normal condition (Soto et al., 2002). (Fig.1.14). The activity of tryptase is extremely low compared with tryptase, perhaps due to site directed mutagenesis of aspartate 216 into glycin, which is the corresponding amino acid in tryptase. Another cause could be due to the crystal structure of tryptase that makes the substratebinding region kinked in the tryptase tetramer, which makes substrate binding and processing unproductive (Marquardt et al., 2002).
1.8.1.3 tryptase tryptase is also of two subtypes; I and II-tryptase, the two isoforms are closely identical except in one amino acid position. tryptase has a premature stop codon which results in shorter mature protein affect significantly on substrate specificity (Wang et al., 2002).
36
Chapter One
Introduction and Literatures Review
1.8.1.4 tryptase There are two different tryptaseI and II. In contrast to and tryptase, tryptase contain an extended hydrophobic C-terminal and a small cytoplasmic tail that facilitatesanchoring to plasma membranes (Caughey et al., 2000).
1.8.2 Processing and activation Mast cell tryptase is similar to all other proteases synthesized from Nterminal signal peptide, which is followed by propeptide. Studies tried to address the processing mechanism of tryptase; their results suggested a two step process; activation of II pro-tryptase involves two catalytic steps; (Fig.1.14) the first is intermolecular autocatalytic cleavage at Val2-Arg3which occurs at acidic PH in the presence of heparin or dextran sulfate resulting in the formation of monomeric protryptase. The second step involves the removal of propeptide by dipeptidyl peptidase I. This step does not require heparin, and the result is formation of an active tetramer (Caughey, 2006). Because tryptase has site directed mutagenesis, prevents the removal of pro-peptide and it will directly be secreted into the circulation (Marquardt et al., 2002). Besides the active tryptase tetramer, the active monomer has been suggested that explains the ability of tryptase to cleave the large substrates that can not fit into a central pore of tetramer (Fajardo and Pejler, 2003).
37
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Figure 1.14: Activation and secretion of α, β, and tryptase. Catalytically inactive protryptases in the endoplasmic reticulum (ER) follow regulated or constitutive secretory pathways; tryptase processed by removal of the propeptide is assembled into catalytically active, heparin stabilized tetramers and stored within the mast cell secretory granule, along with other preformed mediators. tryptase activated by propeptide removal remains membrane associated. α –Tryptase, which has a mutation preventing removal of the propeptide are directly secreted, along with residual pro-β tryptase. On secretion, some mature β tryptase make their way to the bloodstream, where they are detected by tryptase immunoassays, along with secreted pro-α and pro-β tryptase(Caughey, 2006.)
1.8.3 Biological activities Tryptase is the most abundant mediator stored in MC granules and plays a critical role in several inflammatory conditions.
1.8.3.1 Pro-inflammatory effects
38
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During inflammation the mast cell degranulation occurs and results in the release of its predominant protease which is tryptase. Thus tryptase is expected to have a role in the regulation of inflammatory process. It was suggested that tryptase induces inflammation by stimulating endothelial cells to release granulocyte chemoattractant IL-8 (Compton et al., 2000).On the cellular level tryptase upregulate expression of IL-8, IL-1, and stimulate the expression of intracellular adhesion molecules on epithelial cells (Kinoshita et al., 2005).
1.8.3.2 Tryptase substrate Tryptase has been suggested to involve in different biological processes through cleavage of different substrate. One of the substrates that were identified was fibrinogen, suggesting anticoagulant activity of tryptase(Prieto-Garcia et al., 2012). It has been shown that tryptase increases vascular permeability through activation of pre-kallikrein and by producing bradykinin from kininogens(Coffman et al., 2008). Tryptase may also have a role in atherosclerosis via degradation of highdensity lipoprotein (HDL) and results in decrease cholesterol removal by HDL (Lee et al., 2002b). Other substrates are neuropeptides such as; vasoactive intestinal peptides (VIP), peptide histidine methionine, and calcitonin gene related peptide. The degradation of these peptides of bronchodilation may lead to increased bronchial responsiveness and contribute to the involvement of tryptase in asthma (Fenger et al., 2012).
1.8.3.3 Protease activated receptors 39
Chapter One
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Mast cell tryptase activates protease receptors (PARs). PARs belong to the large superfamily of G-protein seven transmembrane domains receptor (Lan et al., 2002). PARs activation requires cleavage of extracellular N-terminal part of receptor. The newly formed amino-terminus 'tethered ligand' interacts with second extracellular loop of receptor which results in the activation of G-protein and confers cellular signaling (Schmidlin and Bunnett, 2001). There are four PARs (PAR-1, PAR-2, PAR-3, and PAR-4).
tryptase activated PAR-2 receptor. PAR-2 activation may have broncho-
protective effect in lungs via tryptase, which stimulates the release of bronchodilator and anti-inflammatory mediators (Lan et al., 2002). However some studies demonstrate the pro-inflammatory effects after PAR-2 activation. For example, in the sensory neurons tryptase via activation of PAR-2 receptor stimulate release of inflammatory mediators such as calcitonin-gene-related peptide and substance P. Moreover, these mediators stimulate mast cell degranulation, which is another indicator that PAR-2 involves in inflammation (Steinhoff et al., 2000). In cardiovascular system PAR-2, activation induces nitric oxide-mediated vascular relaxation (Kawabata and Kuroda, 2000).Also PARs are highly expressed in the gastrointestinal tract. PAR-2 receptors are expressed in gastrointestinal smooth muscles and by enterocytes; they have a role in regulation of intestinal transport (Vergnolle, 2000).
1.8.4 Mast cell tryptase as biomarkers Nowadays, total serum tryptase are increasingly used in clinical practice. Tryptase level in biological fluid indicates the body burden of mast cells and are useful as biomarker of clonal mast cell disorders, mastocytosis. Tryptase is also a 40
Chapter One
Introduction and Literatures Review
useful marker for a differential diagnosis of systemic anaphylaxis (Schwartz, 2006). Individuals who are allergic to hymenoptera venom, increase level of tryptase indicate sever reactions (Bonadonna et al., 2009). -tryptase is also over expressed in asthma. This suggests mast cell involvement in late asthmatic response and in chronic inflammation. (Fenger et al., 2012). It is also a potential marker for some hematological conditions such as hypereosinophilic syndrome (HES) (Klion et al., 2003), and myeloid neoplasm (Sperr et al., 2009). Although studies reveals a positive association between obesity and increase number of mast cells in WAT of both animals and humans, the exact mechanism of mast cell in pathogenesis of obesity is not fully understood (Liu et al., 2009). There is little evidence to show the relation between obesity and serum tryptase. (Gonzalez-Quintela et al., 2010), (Fenger et al., 2012). The association between serum tryptase and obese diabetics was not fully revealed. Previous works show a direct contribution of mast cells in type 2 diabetes mellitus(T2DM) and insulin resistance in animal models (Liu et al., 2009). Another study shows a positive correlation between mast cells and obese diabetics. It also shows that mast cells in these patients tend to release more inflammatory cytokines than
obese
non-diabetic
patients
41
(Divoux
et
al.,
2012).
Objectives
Aims of the study 1. Association of estimated serum tryptase levels with age, gender, BMI, and lipid profile in all groups. The special emphasis is on two-major groups, a group without obesity related complications and a group with obesity related complications, like dyslipidemia and type 2 diabetes mellitus (T2DM)in our locality.
2. Identify the degree of relation between serum tryptaselevels in diabetes patients, as one of the complication of obesity.
3. Identify if HbA1c and FBG level in diabetics patients plays a significant role in variation of serum tryptase level.
4. Determine if the tryptase level in serum is a suitable biomarker for obesity or it is more appropriate to obesity- related complications.
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2.1 Materials 2.1.1 Laboratory equipment All instruments used in this study are listed in the table 2.1. Table 2.1: Instruments used in the study
No. Equipment
Source
1
ELISA plate reader
BioTek, USA
2
Centrifuge
3
Ultra low-temperature freezer (-65 C)
Kendro laboratory product, Labofuge 200, Germany SANYO, Japan
4
Water bath
Taeesa, Hanover-Germany
5
Automatic water stills
LabTech, India
6
Cobas c 311 analyzer
Roche/Hitachi, Germany
7
Cobas c 111 analyzer
Roche, Germany
8
Incubator
INCD 2, memmert, Germany
9
Refrigerator (-20)
Konka, China
10
Micropipette plate shaker
J.P. Selectia, s.a., Spain
11
Multi channel pipette
Rainin, USA
12
Micropipettes (5-50 μl, 20-200 μl, 100-1000 μl)
Transferpette, brand, Germany
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Chapter two
Materials and methods
2.1.2 Kits and reagents: The reagents and kit used in this study are listed in table 2.2. Table 2.2: Reagents and kits used in the study
No.
Chemicals
Source
1
Mast cell tryptase ELISA kit
YH Bioresearch laboratory, Shanghai- China
2
Serum glucose cobas c 311kit
Roche/Hitachi- Germany
3
Serum triglyceride cobas c 311 kit Roche/Hitachi- Germany
4
Serum cholesterol cobas c 311 kit
Roche/Hitachi- Germany
5
Serum high density lipoprotein (HDL) kit
Roche/Hitachi- Germany
6
Glycosylated hemoglobin kit
Roche/Hitachi- Germany
2.1.3 Study Design This study involves a total of 250 participants, samples from 150 individuals collected in central laboratory of sulaimani city, and 100samples collected from patients visited the center of diabetes and endocrine glands, between periods of March to September 2014. Thetests were done in the research lab in the medical school -university of sulaimani. The Ethics Committee of school of medicine approved the studyand written informed consent has been obtained from all involved participants.
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Materials and methods
The participants were divided into four groups: Group I: Includes one hundred patients out of 250 participants were obese based on their body mass index (BMI) equal and more than 30kg/m2with type 2 diabetes mellitus (T2DM). Group II: Includes seventy-eight patients out of 250 were obese with dyslipidaemia. Group III: includes twenty-two obese individuals without obesity related complications. Group IV: includes fifty individuals out 250 participants who were normal weight control healthy volunteers based on their body mass index (BMI between 18.5 to 24.9kg/m2).
44
Chapter two
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Participants (250)
Obese (200)
Control (50
Without complications (22) (non-symptomatic)
With complications (178)
Dyslipidemia (78)
T2DM (100)
Participants (250)
Obese (200)
Without complications (22) (non-symptomatic)
Dyslipidemia (78)
Control (50
With complications (178)
T2DM (100)
45
Chapter two
Materials and methods
Participants (250)
Obese (200)
Control (50
Without complications (22) (non-symptomatic)
With complications (178)
Dyslipidemia (78)
T2DM (100)
A diagram illustrates all participants in this research, clarifying the study design, grouping and the case number.
2.2 Methods
2.2.1 Inclusion and Exclusion criteria 2.2.1.1 Inclusion criteria Participant that included in the study was obese based on BMI (≥30 kg/m2) patients in group I that were diagnosed previously by physicians as having type 2 diabetes mellitus (T2DM), dyslipidemic group (group II) was obese patients with one or more elevation in their lipid parameters without any other known diseases, healthy obese was chosen based on the questions that asked by participant and filled in information paper, and the investigations done for them including renal function test, liver function test, lipid profile, and fasting blood glucose.
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Finally control group was normal weight based on their BMI (18.524.99kg/m2) and they were chosen as a healthy candidate for the study.
2.2.1.2 Exclusion criteria For all participants, a number of diseases were excluded that thought to affect the level of Serum Tryptase. They are not asthmatic, no cardiac problems, no renal and liver diseases, cancer and infertile patients. In addition,athleticsand handicap individuals were also excluded in the study.
2.2.2 Questionnaire form Questionnaire information paper was filled by interview for all of individuals as the following: Sample No. (
)
Name:…………………………….. 47
Chapter two
Materials and methods
Age:……….. Gender: ♂
♀
Residency: Urban Rural Occupation: ………………………. Chronic disease: DM HTN Heart disease, other………… Smoker:
Yes
Alcoholic: Yes
No No
Family history of obesity and chronic illness: Yes
No……………..
Drug history: …………………. Body weight……... (kg),
Body Height:……. (m)
BMI:………………(kg/m2)
2.2.3 Measuring BMI Measurements of body height and weight were done for all individuals in light clothing without shoes, and with empty bladder. Weight was measured by calibrated physician scale and height by a sliding bar attached to the scale. BMI was calculated as weight/height2 (kg/m2), and all individuals in this study were classified as normal weight and obese according to their BMI (LEE GOLDMAN, 2012).
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2.2.4 Sample collection Ten milliliters of venous blood was drawn from each individual cubital vein using disposable syringes. Five milliliter blood has been collected in plain tubes and allowed for 20 minutes at room temperature to clot. Serum was separated by centrifugation at 3000 rpm for approximately 20 minutes, also 5 milliliter of blood collected in EDTA tubes, and both tubes stored at -20°Cin the research lab in medical school until assayed.
2.2.5 Measurement of biochemical markers 2.2.5.1 Human mast cell tryptase (MCT) assay 2.2.5.1.1 Principle of the assay Total serum tryptase is a measure of mast cell activity or mast cell burden. The MCT test uses enzyme linked immune sorbent assay (ELISA) based on biotin double antibody sandwich technology to assay human mast cell tryptase. MCT is added to each well that is pre-coated with mast cell tryptasemonoclonal antibody and then incubate. After incubation, anti MCT antibodies labeled with biotin are added to unit with streptavidin-HRP, which forms the immune complex. Then unbound enzymes are removed after washing and then developed using substrate A and B to each well. The solution will turn blue and change to yellow after the addition of the stop solution. The shades of solution and the concentration of human mast cell tryptase (MCT) are positively correlated.
2.2.5.1.2 Assay procedure The assay procedure was done according to the following table: Specimen
Blank
Standard
49
Assay
Chapter two
Materials and methods
Serum
40microliter
Standard
50microliter
Streptavidin-HRP
50microliter
Anti MCT antibody
10microliter
50microliter
50microliter 10microliter
Reagents were added, mixed, and incubated for 60 minute at 37°C and then washed with washing solution. Chromogen reagent A
50microliter
50microliter
50microliter
Chromogen reagent B
50microliter
50microliter
50microliter
Reagents were added, mixed, and incubated for 10 minute at 37°C for color development (blue). Stop solution
50microliter
50microliter
50microliter
The absorbance measured at wavelength of 450 nm.
2.2.5.1.3 Calculation According to the standard concentration (ng/ml) and corresponding absorbance we construct the standard curve (Fig.2.1), and then according to the absorbance of samples, we calculate the concentration of corresponding sample.
50
Chapter two
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MCT Standard Curve 1.4
Absorbance (450 nm)
1.2 1
0.8 0.6 0.4 0.2 0 0
1
2
3
4
5
6
7
Concentration ng/ml Figure 2.1: Standard curve diagram for mast celltryptase using known standards
2.2.5.2 Measurement of serum total cholesterol These tests were done by cobas c automated analyzer system.
2.2.5.2.1 Test principles Determination of serum cholesterol was done based on both enzymatic, colorimetric method (Kohlmeier, 1986). Cholesterol esters are cleaved by action of cholesterol esterase to yield free cholesterol and fatty acids, and then cholesterol oxidase catalyses the oxidation of cholesterol to cholest-4-en-3-one and hydrogen peroxide. In the presence of peroxidase, the hydrogen peroxide formed effects the oxidative coupling of phenol and 4-aminophenazone to form a red quinine-imine dye.
Cholesterol esters + H2O CE
cholesterol + RCOOH 51
Chapter two
Cholesterol + O2
Materials and methods
CHOD
2H2O2 + 4-AAP + phenol POD
cholest-4-en-3-one + H2O2
quinine-imine dye +4 H2O
The color intensity is directly proportional to the serum cholesterol concentration. It is determined by measuring the increase in absorbance.
2.2.5.3 Measurement of serum triglycerides (TG) The test was done by cobas c automated analyzer.
2.2.5.3.1 Test principle The test is based on enzymatic colorimetric method. Free glycerol is eliminated prior to hydrolysis of triglycerides in a preliminary reaction in which lipase and 4- aminophenazone are omitted. This reaction is followed by enzymatic hydrolysis of triglycerides and determination of the liberated glycerol by a fully enzymatic colorimetric reaction (Kohlmeier, 1986).
Preliminary reaction Sample and addition of R1 Free glycerol+ ATP (GK)glycerol-3- phosphate + ADP
Glycerol-3-phosphate +O2GPO
H2O2 + 4-chlorophenol
dihydroxyacetone phosphate + H2O2
peroxidase
oxidation product
(The oxidation product does not react with 4- aminophenazone.) 52
Chapter two
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Assay reaction Addition of R2:
Triglyceride + 3 H2O
Glycerol +ATP
GK
Glycerol-3-phosphate +O2
lipase
glycerol + fatty acids
glycerol-3-phosphate + ADP
GPO
dihydroxyacetone phosphate + H2O2
H2O2 + 4-aminophenazone + 4-chlorophenol
peroxidase
4-
(p -benzoquinone- monoimino)-phenazone + 2 H2O + HCl
2.2.5.4 Determination of serum high density lipoprotein- cholesterol (HDL-C) High density lipoproteins were also measured by cobas c automated analyzer.
2.2.5.4.1 Test principle It is a homogenous, enzymatic, and colorimetric test. The cholesterol concentration of HDL is determined enzymatically by cholesterol esterase and cholesterol oxidase coupled with polyethylene glycol (PEG) to the amino groups (approx. 40%). Cholesterol esters are broken down quantitatively into free cholesterol and fatty acids by cholesterol esterase(Sugiuchi et al., 1995).
53
Chapter two
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HDL- cholesterol esters + H2O
PEG-cholesterol esterase
HDL-cholesterol
+RCOOH In the presence of oxygen cholesterol is oxidized by cholesterol oxidase to 4
- cholestenone and hydrogen peroxide.
HDL- cholesterol + O2
PEG-cholesterol oxidase
4-
cholestenone + H202
In the presence of peroxidase, the hydrogen peroxide generated reacts with 4amino-antipyrine and sodium N-(2-hydroxy-3-sulfopropyl)-3, 5-dimethoxy aniline (HSDA) to form a purple blue dye. The color intensity is directly proportional to the cholesterol concentration and measured spectrophotometrically. 2H2O + 4-amino-antipyrine +HSDA + H+ + H2O peroxidase
purple-blue
pigment + 5H2O
2.2.5.5Determination of serum low density lipoprotein-cholesterol (LDL-C), and very low density lipoprotein-cholesterol (VLDL-C) Low density lipoprotein was calculated by Friedwald equation (Crook, 2006)by the following formula: LDL = cholesterol − HDL − TG /2.2 Very low density lipoprotein was calculated automatically by the cobas c automated analyzer system.
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2.2.5.6 Measurement of serum glucose concentration Fasting serum glucose was measured by automated analyzer cobas.
2.2.5.6.1 Test principle UV test: enzymatic reference method with hexokinase (Wu, 2006). Hexokinase catalyzes the phosphorylation of glucose to glucose-6-phosphate by ATP. Glucose + ATP
Hexokinase (HK)
G-6-P + ADP
Glucose-6-phosphate dehydrogenase oxidizes glucose-6-phosphate in the presence of NADP to gluconate-6-phosphate. No other carbohydrate is oxidized. The rate of NADPH formation during the reaction is directly proportional to the glucose concentration and is measured photometrically. G-6-P + NADP+
G-6-PDH
gluconate -6-p + NADPH + H+
2.2.5.7. Measurement of glycated hemoglobin (HbA1c): Estimation of HBA1c was done by cobas 111 automated analyzer.
2.2.5.7.1 Test principle This method uses TTAB (Tetradecyltrimethylammonium bromide) as the detergent in the hemolyzing reagent to eliminate interference from leukocytes (TTAB does not lyse leukocytes). The HbA1c determination is based on the turbidimetric inhibition immunoassay (TINIA) for hemolyzed whole blood (Hamwi et al., 1995).
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2.3Statistical analysis: Statistical analysis was carried out using SPSS (Statistical Package for Social Science) version 20 computer software. Descriptive statistical analysis was done for all data including mean, standard deviation, standard error, range, minimum and maximum value. Association between serum tryptase (ST) concentration and obesity, age, and gender were done by Chi-Square test. It was confirmed by ANOVA or F-test any value less than 0.05 was regards as statistically significant. Most of the data were plotted on Box-Whisker plot and linear regression curve. To show the effect of diabetes on serum tryptase independent sample T-Test was used to see the association between mean of ST and HbA1c and FBG (fasting blood glucose), P-value less than 0.05 was regard as statistically significant.
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3.1Demography of the samples Samplecharacteristics,biochemical markers were included(Table3.1). Table 3.1: Characteristics of the study Groups:
Sample
Frequency
Gender Female Male Age (year) 12-30 31-40 41-50 51-60 61-70 >70 BMI groups Normal weight Obese Classes of Obesity Class I obesity Class II obesity Class III obesity S. Tryptase classes 0.18-6 ng/mL >6 ng/mL S. Triglycerides Normal<160 mg/dl Abnormal ≥160 mg/dl S. Cholesterol Normal (200-239 mg/dl) Abnormal (≥240 mg/dl) S. LDL Normal (<100 mg/dl) Abnormal (≥100mg/dl) S.VLDL Normal (2-30mg/dl) Abnormal (>30mg/dl)
160 90 55 49 65 55 20 6 50 200 139 41 20 102 148 91 109 178 22 80 120 26 87
S. HDL Abnormal female (<65mg/dl) Abnormal male (<55mg/dl)
131 69
Fasting blood glucose Normal (80-110 mg/dl) Abnormal (>110mg/dl) Hemoglobin A1c Control diabetes (4.5-7%) Uncontrolled diabetes (>7%)
11 89 20 71
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Chapter three
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3.2 Serum Tryptase (ST)levels in obese and control group 3.2.1 Chi-square test There is a statistically significant (P<0.05) association between Serum Tryptaseconcentration in the study groups by Chi-Square test (X2) (Table 3.2). Table 3.2:Chi-square test of Serum Tryptase level in obese and control groups
Level of Serum Tryptase in control and obese groups Sample groups
S. Tryptase category by ng/ml 0.18-6 ng/ml
>6ng/ml
50
0
Obese + Type 2 D.M
0
100
Obese+ Dyslipidemias
37
Control
Obese
without
obesity
related
15
P-value
41 <0.001 7
complications
3.2.2 ANOVA test The chi-square test was confirmed by ANOVA test or F- test (Table 3.3.), which also shows a statistically significant variation (P<0.05) between mean of Serum Tryptase in the study groups. This is also confirmed by (Robust tests of equality of means).
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Chapter three
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Table 3.3: ANOVA tests between means and standard deviation of Serum Tryptase among study groups and its P-value (SD: standard deviation, SE: standard error).
Mean of Serum Tryptase level within obese and control group Sample groups
Number
ST (mean ± SD)
SE
P-value
Control
50
2.72 ± 1.01
0.14
<0.001
Obese + Type 2 D.M
100
11.97 ±1.74
0.17
Obese+ Dyslipidemias
78
6.27 ± 1.11
0.12
obesity 22
5.34 ± 1.21
0.25
Obese
without
related complications
3.2.3 Box-whisker plot Figure 3.1 shows Serum Tryptase concentration in study groups by box- whisker plot.
Figure 3.1: Serum Tryptase concentrations according to study groups by Box-Whisker plot.Horizontal lines represent median values, and boxes represent the inter-quartile range. 57
Chapter three
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3.3 Serum Tryptase concentration in relation to age and gender 3.3.1 Serum Tryptase and age Serum Tryptase increased significantly with increasing age (Table 3.4). The estimate for the variation of ST level among different age groups was shown by ANOVA test, and confirmed by (Robust tests of equality of means), correlation between ST and age was also clarified by linear regression line, which shows a positive correlation (Fig.3.2, Fig.3.3).
Table 3.4: ANOVA test between mean ST concentrations in relation to age classes
Serum Tryptase in different age group Ageclasses (years)
Number
ST (Mean±SD)
SE
12-30
55
4.39±2.65
0.36
31-40
49
6.72 ± 2.75
0.39
41-50
65
9.18±3.60
0.45
51-60
55
9.86±3.74
0.50
60-70
20
9.16±3.84
0.86
>70
6
7.91±4.95
2.02
58
P-value
<0.005
Chapter three
Results
Figure 3.2: linear regression analysis shows a positive correlation between ST concentration and age in years.
Figure 3.3: Box-whisker plot show ST concentration according to age strata 59
Chapter three
Results
3.3.2 Serum Tryptase and gender There was no statistically significant association between ST among males and females by linear regression line (Fig.3.4), which was confirmed by ChiSquare tests (Table 3.5). Table 3.5: Chi-Square test of ST in relation to gender (P-value <0.319).
Serum Tryptase level in relation to gender Gender
S. tryptase classes by ng/ml
Female / Number % within gender Male /
Number % within gender
0.18-6ng/ml
>6ng/ml
69
91
43.1%
56.9%
33
57
36.7%
63.3%
Figure 3.4: Box-Whiskers plot between Serum tryptase and gender. 60
P-value
<0.319
Chapter three
Results
3.4 ST in obesity 3.4.1 ST and BMI Serum Tryptase is increasing with increasing weight regardless of their health status. Chi-Square test shows a statistically significant association between ST and obesity (Table 3.6) which was also showed by box-whisker plot (Fig.3.5). Table 3.6: Statistically significant association found between ST classes in normal and obese group based on their BMI.
Serum Tryptase classes in relation to BMI BMI groups S. Tryptase classes 0.18-6 ng/ml >6ng/ml 2 Normal BMI (18.5-24.9 kg/m ) Number 50 0 Percent % 100.0% 0.0% 2 Obese (≥ 30 kg/m ) Number 52 148 Percent % 26.0% 74.0%
P-value
<0.001
Figure 3.5: Illustrates Box-Whiskers plot between ST in normal weight (control) individuals and obese individuals. 61
Chapter three
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3.4.2 ST in classes of obesity ANOVA test (Table 3.7) shows a statistically significant differences between ST and all three classes of obesity based on BMI: (class I obesity: 30.0-34.9 kg/m2, class II obesity: 35.0- 39.9 kg/m2, class III obesity: >40 kg/m2), this was shown in (Fig.3.6) which illustrates a statistically significant variation between ST and classes of obesity based on their BMI by Box-Whisker plot. Table 3.7: ANOVA comparisons between mean SerumTryptase all three classes of obesity
Mean of Serum Tryptase in relation to classes of obesity Classes of obesity
Number
ST (Mean ± SD)
SE
Class I obesity
139
9.00 ±3.29
0.27
Class II obesity
41
8.52 ±2.98
0.46
Class III obesity
20
10.11 ±3.98
0.89
P-value
< 0.001
Figure 3.6: illustrate statistically significant variation among three classes of obesity and ST by Box-Whisker plot. 62
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3.5Serum Tryptase level in type 2 diabetes mellitus (T2DM) 3.5.1 Serum Tryptase in controlled and uncontrolled T2DM Comparing Serum Tryptase level among control (HbA1c 4.5-7%) and uncontrolled (HbA1c >7%) type 2 D.M regarding hemoglobin A1c (HbA1c) level by independent sample T-Test (Table 3.8), the test shows non-significant differences (P-value <0.656) between controlled and uncontrolled diabetes by their HbA1c level regarding serum tryptase. Association was also shown by BoxWhisker plot between controlled and uncontrolled D.M regarding their HbA1c levels (Fig. 3.7)
Figure 3.7: Serum Tryptase concentration according to HbA1c in diabetic patients. 63
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Table 3.8: Non-significant difference of Serum Tryptase found among controlled and uncontrolled diabetes by independent sample T-Test.
Mean of Serum Tryptase level in controlled and uncontrolled diabetes HbA1c classes
Number ST (Mean ±SD)
SE
Control diabetes (4.5-7%)
20
11.89 ±1.50
0.33
Uncontrolled diabetes (>7%)
71
12.08 ±1.82
0.21
P-value
<0.656
3.5.2 Serum Tryptase and fasting blood glucose (FBG) Independent sample T-Test (Table 3.9) shows that there is statistically nonsignificant variation between Serum Tryptase and FBG among type II diabetes cases (P-value <0.541), which is shown in (Fig. 3.8) that illustrates non-significant association between FBG and ST by box-whisker plot. Table 3.9: Non-significant difference between FBS and mean of Serum Tryptasefoundby independent sample T-Test
Level of Serum Tryptase in relation to FBG FBG
Number ST (Mean ±SD)
SE
P-value
Normal FBG (80-110 mg/dl)
11
12.27 ±0.73
0.22
<0.541
Abnormal (>110 mg/dl)
89
11.93 ±1.83
0.19
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Figure 3.8: Box-Whisker plot between normal and abnormal FBG and ST among diabetics.
3.6 Serum Tryptase and dyslipidaemia Among different markers of dyslipidaemia, serum low density lipoproteins (LDL) and high density lipoproteins (HDL) were the only one that was statistically associated with ST. Serum total cholesterol, triglyceride (TG) and serum very low density lipoproteins (VLDL) did not appear to be associated with ST (as shown below in following tables and figures). Table 3.10: Relation between Serum Tryptase and S.triglycerides.
Serum Tryptase level in relation to S. triglycerides S.T classes
S. triglycerides
P-value
<160mg/dl (normal) ≥160mg/dl (abnormal) 0.18-6 ng/ml 25
>6ng/ml
27
48.1%
51.9%
66
82
44.6%
55.4% 65
<0.664
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Table 3.11: There is non-significant association between Serum Tryptase and S. cholesterol with P- value< 0.711
Serum Tryptase level in relation to S. cholesterol S.T classes
0.18-6ng/ml
>6ng/ml
S. cholesterol 200-239 mg/dl
>240 mg/dl
47
5
90.4%
9.6
131
17
88.5%
11.5
P-value
<0.711
Table 3.12: Chi-squared test between Serum Tryptase and serum very low density lipoproteins with P-value <0.570 (statistically non-significant association seen).
SerumTryptase in relation to S. VLDL ST classes
0.18-6ng/ml
>6ng/ml
S. VLDL 2-30mg/dl (normal)
>30mg/dl (abnormal)
13
38
25.5%
74.5%
13
49
21.0%
79.0%
66
P-value
<0.570
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Table 3.13: Chi-square test between ST and Serum low density lipoproteins with significant association between the two variables (P-value < 0.041)
Serum Tryptase in relation to S. LDL ST classes
S.LDL
P-value
<100ng/ml (normal) ≥100ng/ml (abnormal) 0.18-6ng/ml
>6ng/ml
27
25
51.9%
48.1%
53
95
35.8%
64.2%
<0.041
Table 3.14: There is a statistically significant association between ST and high density lipoproteins (HDL) by chi-square test (P-value < 0.011).
Serum Tryptase in relation to S. HDL ST classes
0.18-6ng/ml
>6ng/ml
S.HDL <40 mg/dl(abnormal)
40-60 mg/dl(normal)
34
18
65.4%
34.8%
122
26
82.4%
17.6%
67
P-value
<0.011
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Figure 3.9: Linear regression analysis shows a positive correlation between ST concentration and S.LDL.
Figure 3.10: Linear regression analysis shows a negative correlation between ST concentration and S.HDL. 68
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Discussion
4.1 Body mass index (BMI) In the current study 250 participants were recruited. They were divided into groups and subgroups based on their body mass index (BMI), including the healthy individuals. Among these 80% are obese regardless of their status for relateddiseases and/or obesity-related-complication and 20% are healthy normal weight (healthy control group) group based on their BMI, including personal and family history information. BMI has been identified as the best option among other obese parameter measures, since it can be easily assessed and has a strong association with body fat and health risks. The standard measure for BMI is weight/height2 (kg/m2). In this study we used BMI values classified by World Health Organization (WHO, 2000), normal weight (18.5-24.9), overweight (25-29.9), class I obesity (30.0-34.9), class II obesity (35-39.9), and class III obesity (>40) (Table 1.1).
4.2 Role of Serum Tryptase (ST) in obesity It is now well accepted that obesity is an abnormal human physiology that is increasing worldwide with its related co-morbidity risks, such as type 2 diabetes mellitus (T2DM), dyslipidemias, cardiovascular diseases, cancer, and many other obese-related-complications. In the present study body-fat composition was reflected by BMI and it was found that significantly associated with ST. This was independent of possible confounding factors (Table 3.6 and Fig.3.5). As indicated, a significant variance in level of ST among obese participants and normal weight control group were found in sulaimani city. Essentially comparable results were noted in two different publications on European populations and thus the results seem to be independent of environmental, cultural and life-style difference, among the findings of a 69
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Discussion
Spanish and (Gonzalez-Quintela et al., 2010), Dutch(Fenger et al., 2012) general population, they found a clear positive association between ST and BMI. Possible explanation for the association between ST and obesity is that white adipose tissue in obese individuals is more abundant and contains more mast cell numbers than the lean counterparts. However, the exact mechanisms of mast cell in the pathogenesis of obesity are not fully understood. Previous studies did a staining of human WAT section with mast cell tryptase monoclonal antibody and they found a higher number of mast cells in WAT from obese tissues compared with WAT from lean subjects (Zhang and Shi, 2012). Since higher ST is reflecting the mast cell burden or mast cell activity, this may explain why ST is higher in obese than normal weight humans (Shi and Shi, 2012). At the same time a present study showed that there is a significantly increasing level of ST in all the classes of obesity (Table 3.7, Fig.3.6), with highest level in class III obesity than class II, and class I obesity.
4.3 Role of ST in type 2 diabetes mellitus (T2DM) Type 2 diabetes mellitus (T2DM) is the most common type of the disease that is associated with insulin resistance and abnormal insulin signaling on target tissues, 80% or more of patients with T2DM are suffering from obesity that is considered as a major risk factor for the development of insulin resistance and T2DM, particularly central obesity (visceral obesity) (Harrison, 2005). Previous investigations show that BMI, absolute weight gain, and abdominal adiposity all are independent risk factors for diabetes. Although family history and age are accepted risk factors (Bianco et al., 2014), only weight change is controllable (Colditz et al., 1995), (Koh-Banerjee et al., 2004).
70
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Discussion
However, how obesity promotes insulin resistance is unclear. The increased adipocyte mass leads to increased levels of circulating free fatty acids and other cellular fat derivatives (non-esterified free fatty acids, retinol-binding protein 4, leptin, TNF-α, resistin, and adiponectin). These adipokines modulate insulin sensitivity (Zhang and Shi, 2012).
In the current study, the measurement of ST shows that there is a significant elevation in obese patients with type 2 diabetes compared to obese non-diabetic group (Table 3.2, Table 3.3, and Fig.3.1). The exact role of ST in the Pathophysiology of T2DM has not yet been fully understood in humans (Liu et al., 2009). In mouse model, it is believed to be a direct contribution of mast cell in insulin resistance and T2DM developments. It has been demonstrated genetically that mast cell deficient mice has higher insulin sensitivity and glucose tolerance and reduces body weight compared to wild-type mice (Liu et al., 2009). Divouxet al have found that mast cell was increased in type 2 D.M humans, and the secretion of tryptase was increased is obese participants especially obese diabetic patients (Divoux et al., 2012). Regarding HbA1c in present study there was no significant association between ST in controlled and uncontrolled diabetes based on their HbA1c level (Table 3.8, Fig.3.7). In similar fashion, there was no significant association between ST and fasting blood glucose (FBG) in diabetic patients (Table 3.9, Fig.3.8). However, a previous work shows a positive correlation between ST and HbA1c and FBG (Divoux et al., 2012).
71
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Discussion
This difference in the result between this current and the previous study could have originated from different variables, which could not be resolved in a single study. Other confirmatory research studies needed to resolve this issue. A number of factors that may contribute in these variations are cultural background, geographical changes and the life style.
4.4 Role of ST in obese patients with dyslipidemia Dyslipidemia is frequently associated with obesity. Markers for dyslipidemia are serum cholesterol, serum TG, serum VLDL, serum HDL, and serum LDL. Dyslipidemia condition in obese patients has elevation in cholesterol, TG and LDL, but HDL level is suppressed, if all occurred together called atherogenic lipid profile(Howard et al., 2003), ((Heikkila et al., 2010). The current study shows a significantly higher level of ST among obese patients with dyslipidemia than obesity without complication but slightly lower ST than obese diabetic group (Table 3.2, Table 3.3, and Fig.3.1). The significant, positive association between ST and dyslipidemia could point to an important contribution of mast cells in obese dyslipidemic patients that may induce subclinical atherosclerosis. A previous work by Moreno et al.(Moreno et al., 2014)show that mast cells are involved in the development of atherosclerosis by releasing cytokines that induce mast cell protease expression specially circulating ST. This has been proven as the true relation between ST and carotid intima-media thickness (c-IMT) and they concluded that ST has proatherogenic role in subclinical atherosclerosis. Among dyslipidemic parameters, high serum triglyceride (TG) level ≥160mg/dl is found in 43.6% of our obese patients, while normal TG <160mg/dl is found in 36.4% of patients. This shows that most of the obese patients have 72
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elevated TG than normal TG. This phenomenon has been shown in previous studies (Gormsen et al., 2009). Since both TG and ST increase in obese patients, we examined the relation between ST and TG among obese participants, but no association was found between them among our participants (Table 3.10). This finding is consistent with a previous study (Fenger et al., 2012). Similar to TG, the present study didn’t find significant association between serum cholesterol, VLDL and ST among obese participants. This result is consistent with the study conducted by (Fenger et al., 2012). Conversely, in the current study there was a significant (P<0.041) association between ST and LDL found among other markers of lipid profile (Table 3.13, Fig.3.9), with a positive relation. This result is in disagreement with the previous study done byFenger, showing that mast cell activation does not influence serum LDL in humans and another study shows that no association on mice (Sun et al., 2007a) as like in humans. What could contribute to these differences is either the assay method for LDL, which is not accurate, or the data which depends on lifestyle. On the other hand, the data in the present study are consistent with other studies done on mice that show activation of mast cells rise LDL level(Heikkila et al., 2010). It is well accepted that accumulation of LDL particle in the intima (the inner layer of arterial wall) is taken up by macrophage and leads to the formation of foam cells. In addition to macrophage, mast cells also present in the arterial intima and leads to stabilization of foam cells (Divoux et al., 2012). Activation of mast cells increases LDL uptake by macrophage this will stimulates IgE-dependent sensitized mast cell and release of its component such as neutral proteases, including ST and 73
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histamine (Zhang and Shi, 2012). Therefore, this may explain how the relation between ST and LDL is regulated. Unlike LDL, HDL, in the current study, demonstrates the inverse relation with ST (Table 3.14, Figure 3.9). The data show a statistically significant negative association between ST and HDL (Table 3.14, Figure 3.10).This result is consistent with recent studies, showing also similar association between ST and HDL (Lee et al., 2002b),(Fenger et al., 2012). This inverse relation between ST and HDL could be due to the finding that mast cells degrade apolipoproteins on HDL (ApoE, ApoA-I, ApoA-IV), thereby causing a functional change in HDL by decreasing its ability to remove cholesterol from arterial intima back to the blood stream (Lee et al., 2002b).
4.5 Level of ST in obese without its complication Among one hundred patients obtained as healthy obese people, only twentytwo were unaffected by obesity-related-complications. This data were obtained based on history from questioner form and also confirmed by biochemical investigation. The remaining seventy-eight patients, so called “healthy-obese” had dyslipidemia, mainly due to their obesity condition. In the present study, the ST levels were significantly different among patient subgroups; lowest ST was found in healthy obese participant lacking obesityrelated-complications compared to obese diabetic patients and obese with dyslipidemias (Table 3.2, Table 3.3, and Fig.3.1). The concluding results from this study indicate that obese individuals without any metabolic defects or complication of obesity tend to have lower ST level compare to those with metabolic complication, while normal weight individuals have the lowest ST level (Table 3.2, Table 3.3, and Fig.3.1).This data 74
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clearly indicate that obese individuals, despite absence or existence of any metabolic defect, have higher ST concentration, and the results were consistent with other study(Gonzalez-Quintela et al., 2010).
4.6 ST level and age In this work, recruited patient group ages are ranged from 12-82 years. We subdivide the age groups into sixdistinct classes; class I: 12-30 years (22%), class II: 31- 40 years (19.6%), class III: 41-50 years (26%), class IV: 51-60 years (22%), Class V: 61-70 years (8%), and class VI: > 70 years (2.4%).The tendency of obesity is increasing with age until nearly age 60years, but in later ages it starts to decline. The relation between weight gain until this age could be due to an decrease in energy expenditure as a result of reduction in resting metabolic rate(Janssen and Ross, 2005). But the weight reduction at an old age could be due to a decrease in fat-free mass in human body as a result of loss of most metabolically active and energy burning muscle tissue (Janssen and Ross, 2005). Since there is a positive relation between obesity and age as confirmed by previous studies, we try to find if there is a relation between ST and age according to distinct age classes. The data clearly shows a statistically significant positive variation between ST and age groups (Table 3.4, Fig.3.2, and Fig.3.3).This result is consistent with the previous study (Sperr et al., 2009), where individuals younger than 16 years have significantly lower ST compared to adult groups above 16 years of age. In the Fenger's study (Fenger et al., 2012) the age group is divided into two groups (15-50 years, and >50 years), and the researcher finds that ST increases significantly with increasing age. Another study reported increased ST concentration with age in patients allergic to hymenoptera venom (Kucharewicz et al., 2007). Also in Gonzales-Quintelastudy(Gonzalez-Quintela et al., 2010), ST is
75
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influenced by age, showing individuals >50 years old has 30% ST higher than adults under 50 years age. In this study, the age influence on ST was independent of potential confounders, including metabolic abnormalities such as T2DM and dyslipidemia. It is not clear whether elderly individuals have more mast cells, if the mast cells are more active or whether they simply degrade circulating serum tryptase slower than younger individuals. Interestingly ST concentration is found to be higher among infants younger than 1 year old especially in infants younger than 3 months. The study suggests that mast cell involvement in the physiologic as well as in allergic immune responds in infants. Unfortunately, we couldn’t collect samples from pediatric ages in the present study because it was not involved in the original plan, hopefully in future works we involve this age group.
4.7 Influence of gender on ST Among 250 participants in this study, 160 were females (64%) and 90 were males (36%). The results could not find any statistical significant ST level difference between females and male individuals independent on their BMI status (Table 3.5, Fig.3.4). The influence of gender on ST is still controversial. This study is in agreement with Gonzales-Quintelawork (Gonzalez-Quintela et al., 2010). Conversely Fenger(Fenger et al., 2012) shows that males have higher ST concentration than females, similarly Komarow(Komarow et al., 2009) find higher level of ST in male atopic children. However, a study by Min (Min et al., 2004) demonstrates the effect of sex and haplotype on plasma tryptase level in healthy adult which has a higher value of ST in females than males. These differences in the results among males and 76
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females in relation to ST could be related to various factors, mainly the healthstatus of individuals and partially racial differences, geographical localities, social life-style, and sample group numbers. These results suggest that the effect of gender, if any, is probably small. Thus, gender should not be considered an important factor for the interpretation of tryptase concentration in routine clinical practice.
4.8 Status of ST among smokers and alcoholics In this study, among two hundred fifty patients, only five patients were alcoholics, and eleven patients were smokers, according to the questionnaire information sheet. These data could not be taken as confident, due to social acceptance dilemma in telling full-truth about personal life-style, especially where the patients were accompanied by close family members. So we couldn't find any statistical relevant data between these two parameters due to small sample numbers. Previous studies on relation between ST among smokers and alcoholics found a positive association between ST and smoking, and inverse relation between ST and alcohol consumption (Fenger et al., 2012), (Gonzalez-Quintela et al., 2010).
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Conclusions and Recommendations
Conclusions According to the results obtained we reached to the conclusions that: 1. Level of ST increases with age, being much more pronounced in adults older than > 16 years old than individuals < 16 years old regardless of their BMI. 2. The ST concentration does not differing among male and female participants. 3. The level of ST is significantly higher in serum of all obese participants regardless of their obesity-related-complications compared to the healthy participants. 4. Obesity related T2DM shows a significantly higher level of ST than obese individuals without complications. 5. FBG and HbA1c status have no significant association with ST concentration. 6. Dyslipidemia related to obesity demonstrates a higher ST than healthy obese individuals. 7. Among dyslipidemia markers, only LDL and HDL show a significant association between ST, with LDL showing a positive relation, while HDL showing a significantly inverse relation with ST.
8. Finally ST concentration could reflect the pathophysiology status of the obese, including the obese-related-complications like type 2 D.M and dyslipidemia as a pro-inflammatorymediator.
78
Conclusions and Recommendations
Recommendations Based on our results and conclusions we recommend:
1. To study a randomized higher-scale of obese and healthy participants, at least 2500 individuals are recommended. It is expected that the results would be more elusive.
2. To combine other obese markers, such Chymase together with ST is more accurate to measure the mast cell activity in obese individuals. Serum Chymase is another important protease of mast cell similar to ST.
3. To develop and select sensitive ELISA methods, such as Fluorescence or Enhanced Chemiluminescence (ECL), to determine ST and/or Chymase. These methods are far-more sensitive than absorbance measurements.
4. To involve additional obese individuals in the study group with other chronic diseases, such coronary artery diseases, renal dysfunction and various forms/stages of cancer.
79
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جمعت عٌنات الدم و عزل مصل الدم الجراء التحلٌل و قٌاس مستوى التربتٌز و مستوٌات الدهون المصلٌة و مستوى سكر الكلوكوز و .HbA1c النتائج: اضهرت الىخائج ارتفاع مستوى انزٌم التربتٌز المصلً فً االشخاص البدٌنٌن المصابٌن بداء السكر غٌر معتمد على االنسولٌن مقارنة لبقٌة المجامٌع .اضهرت الىخائج زٌادة فً مستوى التربتٌزبزٌادة مؤشر الجسم BMIو تقدم العمربغض النظر عن المضاعفات المرضٌة .كما اضهرت الىخائج عنه عدم وجود عالقة بٌن مستوى انزٌم التربتٌز و الجنس وكذلك مع مستوٌات سكركلوكوز و HbA1cالمصلً. األستنتاجات: من خالل تحلٌل النتائج فهذه الدراسة تشتنتج: .1ان مستوى التربتٌز المصلً دورا فعاال فً حاالت السمنة على انفراد و مع مضاعفات المصاحبة بالسمنة مثل داء السكر غٌر المعتمد على االنسولٌن و فرط الدهون. .2كذالك فان مستوى انزٌم التربتٌز ٌزداد بتقدم العمرمع عدم وجود فرق فً مستواه باختالف الجنس. .3كذلك ٌستنتج ارتفاع معنوي فً مستوى التربتٌز فً االشخاص البدٌنٌن بغض النظر على مستوى مضاعفات السمنة مع زٌادة مستوى التربتٌز فً البدٌنٌن االصحاء. .4استنتج عدم وجود عالقة بٌن مستوى انزٌم التربتٌز من جهه مع مستوٌات سكر الكلوكوز و .HbA1c .5واظهر البروتٌن الدهنً الواطىء الكثافة LDLعالقة طردٌه مع مستوى التربتٌز فً حٌن اظهر البروتٌن الدهنً العالً الكثافة HDLعالقة عكسٌة مع مستوى هذا االنزٌم.
الملخص أسس البحث: تعتبر السمنة ظاهرة طبٌة غٌر صحٌة والتً اصبحت خالل العقود االخٌرة من اكبرالمشاكل الصحٌة ,وقد أظهرت المنظمة العالمٌة المتخصصة بدراسة السمنة ان هناك ملٌار شخص تزٌد اوزانهم عن الحد الطبٌعً ,الى جانب وجود 475ملٌون من الذٌن ٌعانون من السمنة ,ومع ذلك فأن السمنة ال تعد من األمراض ,لكنها وفً اعمار معٌنة تعد السبب الرئٌسً للعدٌد من الحاالت الغٌر صحٌة ومنها أرتفاع نسبة الدهون فً الدم ,والنوع الثانً من السكري ,وامراض القلب والشراٌٌن والعدٌد من انواع السرطانات ,وان انزٌم الـتربتٌز التً تفرز من خالٌا الدهنٌة لذا اعدت من المقاسات ذات العالقة بالسمنة خصوصا وقد لوحظ زٌادة اعداد الخالٌا الفارزة منها فً حاالت السمنة و مضاعفاتها كاالصابة بالسكري الغٌر معتمد على االنسولٌن و كذالك حاالت ارتفاع نسبة الدهون فً الدم. األهداف: اهتدفت الدراسة الى: .1اٌجاد العالقة بٌن العمر و الجنس و مؤشر السمنة BMIومستوى سكر الدم FBGو مستوى HbA1cو مستوٌات الدهون فً الدم مع مستوى انزٌم الترٌبتٌز كمؤشر السمنة. .2تقدٌر انزٌم التربتٌزفً االشخاص البدٌنٌن االصحاء واألشخاص البدٌنٌن الذٌن ظهرت علٌهم مضاعفات للسمنة مثل أرتفاع نسبة الدهون فً الدم والنوع الثانً من مرض السكري ,وللمقارنة بٌنهم وبٌن األشخاص المعتدلون فً الوزن والذٌن ٌتمتعون بصحة جٌدة. .3تحدٌد ان كانت التربتٌز مؤشرا جٌدا للسمنة او لمضاعفات المصاحبة للسمنة كداء السكرمن النوع الثانً و ارتفاع مستوٌات الدهون. الطرق البحث: جمعت عٌنات البحث خالل الفترة بٌن الشهر 9-3من العام 2114حٌث اخذ 251شخصا وقسموا الى اربعة مجامٌع بٌنهم 111عٌنة مصابة بالسمنة مرتاوي (مركز السكري فً السلٌمانٌة) ,كذلك 77عٌنة ٌعانون من ارتفاع نسبة الدهون فً الدم ,باالضافة الى 22عٌنة من بدٌنٌن اصحاء من مراجعً المختبر المركزي فً مدٌنة السلٌمانٌة كما جمٌع عٌنات الدم من 51شخصا بأوزان معتدلة وصحة جٌدة.
حكومة اقلٌم كوردستان/العراق وزارة التعلٌم العالً و البحث العلمً جامعة السلٌمانٌة فاكلتً العلوم الطبٌة /سكول الطب قسم باٌوكٌمستري
العالقة نسبة انزٌم الـتربتٌزفً االشخاص البدٌنٌن االصحاء و البدٌنٌن المرضى ذوى المضاعفات الصاحبة للسمنة فً محافظة السلٌمانٌة رسالة مقدمة الى مجلس سكول الطبٌة \ فاكلتً العلوم الطبٌة فً جامعة السلٌمانٌة كجزء من متطلبات نٌل شهادة ماجستٌر فً الكٌمٌاء الحٌاتٌة السرٌرٌة
من قبل ت ٌَبٌن جمال نادر (بكالورٌوس فى الطب و الجراحة العامة) 2111
اشراف الدكتور بٌستون فاٌق نورى دكتورا فً الكٌمٌاء الحٌاتٌة الخلوٌة و الوراثة
وؤسمته بىوة و حتوذسوسج شاسي سلَُماوً مؤمشاووتحتوة ،وة 50متسٍ دَنت مت مَُشُان َ بىون. سامثلًَ خىََه لت خىََه هَُىتسي هتمىو بتشذاسبىوةمان وةسطُشاوة بت متبتسخٍ ثَُىاوت مشدوً ئاسخً ئتوضَمً حشثختص ِ ،سََزةي جؤسةماوً ضتوسي ( ، )lipid profilesطلىمؤط ( serum )glucoseلتطت َه .HbA1c ئتوجام: جُاواصَُتمً ئاماسي طشوظ ) (P<0.001لت وَُىان طشووثتماوذا دؤصساوةحتوة ،وة ِسََزةٌ ئتوضَمً حشثختص بتسصحش دؤصساوةحتوة لت وَُىان ئتو قتلَتواوتي مت شتمشةَان هتَت لتطت َه لتطته سامثلَتماوً طشووثتماوً حش .بتسصبىووتوةَتمً طشوطً ئتوضَمً حشثختص دؤصساوةحتوة َ بٍ ِسةضاو مشدوً دةسةوجامت خشاثتماوً. باسسخاٌ لتش BMIو حتمتن بت َ لت الَتمً حشةوة هُض ثتَىةوذَُتمً طشوطً ئتوضَمً حشثختص لت و َُىان ِسةطتص و ئاسخً ِ HbA1cسََزةي شتمش لت خىََىذا ( )FBGوتدؤصساوةحتوة. دةسةوجام: لتطته صؤسبىووً حتمتوذا بتسصدةبَُختوة ,بتِم هُض جُاواصَُتك .1ئاسخٍ ئتوضَمً حشثختص َ مٍ. لت ئاسخً ئتوضَمً حشَثختط وُت لت وَُىان ِسةطتصٌ وَُش و َ بٍ ِسةضاو مشدوً دةسةوجامتماوً .2ئاسخً ئتوضَمً حشثختص لت بترداسبىوة قتلَتوةماوذا بت َ قتلَتوي بتسصحشة لت بترداسبىوة حتوذسوسختمان. .3هُض ثتَىةوذَُتمً طشوظ لت وَُىان ئاسخً ئتوضَمً حشثختص و ِسََزةي HbA1cو ِسََزةي شتمش لت خى ََىذا ( )FBGوُت. .4ئاسخً ئتوضَمً حشثختص لتو بترداس بىوة قتلَتواوتي مت جؤسي دووةمً شتمشةَان لتطت َه ئتو بترداس بىوة قتلَتواوتي مت ضتوسي خىََىُان صؤسة بتسصحشة لت بترداسبىوة حتوذسوسختمان. .5لت وَُىان هتمىو جؤسةماوً ضتوسٌ خىََه دا حتوُا LDLو HDLثتَىةوذي طشوظ لتطته ئتوضَمً حشثختص ثُشان دةداث LDL .ثتَىةوذي ئتسََىٍ بتالَم HDLثتَىةوذي َ ثَُضتواوت ثُشان دةداث.
ثىخخت بىتماي حى ََزَىتوة: قتلَتوي باسََنً ثضَشنً وائاساَُت مت مت لت 30-20سالًَ ِسابشدوودا بىوةحت َتمَُل لت هتسة طشفخت حتوذسوسخُُت طتوسةمانِ .س ََنخشاوي و َُىدةولَتحً International Association for )the Study of Obesity/International Obesity Taskforce (IASO/IOTF analysisرماسةي ئتو متساوتي مت مَُشُان لت باسي ئاساٍَ صَاحشة بت 1ملُاس متط و رماسةي متساوٍُ قتلَتو بت 475ملُؤن دةختملَ َُى َُج. بىتسةحذا قتلَتوي بت وتخؤشٍ ئترماس وامشََج ،بتالَم بت هؤماسي ستسةمً لتطته ئتوةشذا مت لت َ ِ دادةوش ََج بؤ دسوسج بىووً ضتوذ حالَتح َُنً حتوذسوسخً لت حتمتو َُنً دَاسَنشاودا 00لتواوت: ده و بؤسَُتماوً جؤسٌ دووةمً شتمشة ،بتسصبىووتوةي ضتوسي خىََه ،وتخؤشُُتماوً َ هتوذٌ جؤسٌ شَُشضتوجت .وا دةسدةمتوََج مت ئتوضَمً حشثختص لت خىََىذا بترداسة لت خىََه و َ حالَتحً قتلَتوٌ و دةسةوجامت خشاثتماوً لتواوت :جؤسي دووةمً شتمشة و بىسص بىووتوةي ضتوسٌ خى ََه. ئاماوجتمان: 1بؤ خسخىت ِسووٌ ثتَىةوذي وَُىان ئتوضَمً حشثختص بت ضتوذ فامختسََنتوة لتواوت :حتمتن، ِسةطتص ،باسسخاٍَ لتش (ِ ،)BMIس ََزةي شتمش لت خى ََىذا (ِ ، )FBGس ََزةي جؤسةماوً لتطته Hba1cلت هتمىو طشووثتماوذا. ضتوسي ((lipid profile َ 2بؤ دةسخسخىً ِسََزة و ثتَىةوذي ئاسخً ئتوضَمً حشثختص ئتو بترداسبىوة قتلَتواوتي مت دةسةوجامً خشاثً قتلَتوَُان وُُت و ئتو وتخؤشاوتي مت دةسةوجامت خشاثتماوً قتلَتوَُان حُا دةسمتوحىوة لتواوت بتسصبىووتوةي ضتوسي خىََه و جؤسي دووةمً شتمشة بؤ لتطته ئتو متساوتي مَُشُان ئاساَُت و حتوذسوسخه .ئتمتش بت بتساوسدمشدوً ئتو 3طشووثت َ متبتسخً دؤصَىتوةي ئاماسي طشوظ لت وَُىان طشووثتماوذا ريَطاكانى تويَذينةوةكة: مؤمشدوتوةي سامثلًَ حىََزَىتوةمت لت وَُىان ماوطً 3بؤ 9ي 2014ئتوجام دساوة مت 250 متسً لت خؤطشحىوة مت بتستس 4طشووثذا دابتش مشاون ،لت وَُىاوُشُاوذا 100وتخؤشٍ قتلَتوي حَُذاَت مت لت ستوختسي شتمشةو مىََشة طالوذةمان لت سلَُماوً مؤمشاووتحتوة ,وة هتسوةها 78وتخؤشٍ قتلَتوي دَنت مت ضتوسي خى ََىُان بتسص بىوة ،ئتمت جطت لت 22 قتلَتوي حش مت حتوذسوسج بىون و لت حاقُطتي واوةوذي
حنىمتحً هتس ََمً مىسدسخان/ع َُشاق وةصاسةحً خى ََىذوً باالَو حى ََضَ َىتوةي صاوسخً صاونىي سل َُماوً َ َ فامتلَخً صاوسخت ثضَشنُتمان /سنىلً ثضَشنً لقً با َىمُمسخشي
ثت َىة وذي ئا سخً ئت وضَمً حشَثختط لت ئتو متست قتلتواوتي مت حتوذسوسخه لتطت َه ئتومتساوتي دةسئتوجامت خشاثتماوً قتلَتوَُان حَُذا دةسمتوحىوة وةك بتسصبىووتوةي ئاسخً ضتوسي خىََه و جؤسٌ دووةمً شتمشة لت شاسي سلَُماوً دا ماسختس وامتَتمت ثُشنتش مشاوة بت ئتوجىمتوً سنىلًَ ثضَشنً /فامتلَخً صاوسخت ثضَشنُتمان لت صاونؤي بشواوامتي ماسختس لت مُمُاي ر َاوً سلَُماوً وةك بتشَُل لت ثَُذاوَسخُتماوً بتدةسخهَُىاوً ِ ملُىُنً لتالَتن
حَُبُه جتماه وادس بتمالؤسَؤط لت ثضَشنً و وتشختسطتسي طشخً دا 2010 بتستسبتسشخً
د.بَُسخىن فاَتق وىسي بىماوة َُذا دمخىسا لت مُمُاي ر َاوً خاوت و َ
