ABO Genotype, "Blood-Type" Diet and Cardiometabolic Risk Factors

 
ABO Genotype, “Blood-Type” Diet and Cardiometabolic

                         Risk Factors

                                 by

                           Jingzhou Wang

        A thesis submitted in conformity with the requirements

             for the degree of Master of Science (M.Sc.)

            Graduate Department of Nutritional Sciences

                        University of Toronto

                © Copyright by Jingzhou Wang 2014
ABO Genotype, “Blood-Type” Diet and Cardiometabolic
                     Risk Factors

                                        Jingzhou Wang

                                       Master of Science

                         Graduate Department of Nutritional Sciences

                                     University of Toronto

                                             2014

Abstract

The ‘Blood-Type’ diet advises individuals to eat according to their ABO blood group to optimize

health without the support of science evidence. The objective of this study was to determine

whether consumption of a diet in accordance with an individual’s ABO genotype is associated

with various biomarkers of cardiometabolic health. Study subjects (n=1,455) were participants of

the Toronto Nutrigenomics and Health study. Dietary intake was assessed using a one-month,

196-item food frequency questionnaire and a diet score was calculated to determine relative

adherence to each of the four blood type diets. ABO blood group was determined by genotyping

rs8176719 and rs8176746 in the ABO gene. The results show that adherence to the Type-A,

Type-AB, and Type-O diets were associated with favourable profile of certain cardiometabolic

risk factors (P
Acknowledgments

       I would not have reached this stage without the help of others. Here, I want to express my

sincere gratitude to the people who made my life in the department truly enjoyable.

       First of all, I want to thank my supervisor, Dr. Ahmed El-Sohemy for his excellent

support throughout my Master’s training. His passion in the field of nutrigenomics attracts me to

pursue this graduate degree and his brilliant ideas allow me to work on an interesting project.

With his approachability and patience, I was able to learn and improve my thinking, writing,

speaking skills significantly. His generosity and flexibility has also enabled me to discover career

opportunities and to develop my soft skills in other settings. It was truly my honour to be a

student for Ahmed. I am very grateful for all the opportunities and knowledge he has offered. I

cannot imagine a better mentor.

       Second, I would like to thank Dr. Richard Bazinet and Dr. Elena Comelli for offering

wonderful support as my committee members. Their critical feedback and constructive advice

have helped me to further develop my critical thinking and to mature as a graduate student. It was

also a privilege to have two of my most admiring undergraduate professors to serve on my

advisory committee. I have also benefited tremendously from the teaching of Dr. Paul Corey and

Dr. Tony Hanley. Their high levels of expertise in statistics and epidemiology have helped me

build a solid foundation in my research project. I also want to specifically thank Dr. Harvey

Anderson, who has played a significant role in my undergraduate training. Without his guidance,

I would not fall in love with research. His consistent support, even after I leave the lab, has been

invaluable.

       Third, I want to thank all the past and present members in the El-Sohemy team. The thesis

would not be completed in a timely manner without the effort of all past students. I am also very
                                                iii
grateful to receive the support from Bibiana Garcia-Bailo, Daiva Nielsen, Ouxi Tian, Andre Dias,

Nanci Guest and Joseph Jamnik in both academic and social circumferences. The quality of my

research project improved significantly thanks to their input. It was a pleasure to be a part of the

big family.

        Fourth, I would like to thank all the staff members and students in the department. Louisa

Kung and Emeliana D'Souza were always there to give an extra hand. Clara Cho and Diana

Sanchez-Hernandez were my first mentors in the research field and have taught me a significant

amount of knowledge and skills that are useful in my future career. I am also equally grateful for

the experiences and encouragement offered by my colleagues and teammates in the departmental

student union and volleyball team. The assistances of all these fellows have no doubt facilitated

the completion of my research project.

        I also gratefully acknowledge the funding sources that made this thesis possible: the

Ontario Graduate Scholarship program and the Advanced Foods and Materials Network. In addition,

I was fortunate to be able to attend an international conference thanks to the generous support from

Dr. Ahmed El-Sohemy and School of Graduate Studies at University of Toronto.

        My last gratitude goes to my family. My parents have offered invaluable guidance in my

entire life. Without the support of my father, Song Wang, I would not have had the opportunity to

study aboard. I want to specifically thank for my mother, Yu Liu, who passed away from liver

cancer when I was 15 years old. Watching Animal Planet with my mother made me fall in love

with biology when I was young; losing my closest person due to cancer led me to pursue a career

in life sciences. To her I dedicate this thesis.

                                             Thank you all!

                                                   iv
“In a group of three people, there is always something I can learn from. Choose to follow the

                   strengths of others, use the shortcomings to reflect upon ourselves."

                                           Confucious, 500 BC

                                                    v
Table	
  of	
  Contents	
  

TABLE	
  OF	
  CONTENTS	
                                                                          VI	
  

LIST	
  OF	
  TABLES	
                                                                             IX	
  

LIST	
  OF	
  FIGURES	
                                                                              X	
  

LIST	
  OF	
  APPENDIX	
                                                                           XI	
  

Chapter	
  1:	
  Introduction	
  and	
  Literature	
  Review	
  
1.1	
   INTRODUCTION	
                                                                               1	
  

1.2	
   “BLOOD-­‐TYPE”	
  DIET	
                                                                     1	
  

1.3	
   ABO	
  BLOOD	
  GROUP	
                                                                      2	
  

1.3.1	
  	
  ABO	
  SYSTEM	
                                                                         2	
  

1.3.2	
  	
  ABO	
  BLOOD	
  GROUP	
  AND	
  DISEASES	
                                              3	
  

1.3.3	
  	
  BLOOD	
  GROUPS	
  AND	
  NUTRITION	
                                                   4	
  

1.4	
   CARDIOMETABOLIC	
  DISEASES	
                                                                6	
  

1.4.1	
  PREVALENCE	
  AND	
  ETIOLOGY	
                                                             6	
  

1.4.2	
  	
  BIOMARKERS	
  OF	
  RISK	
                                                              6	
  

1.4.3	
  	
  RISK	
  FACTORS	
                                                                       9	
  

1.5	
   SUMMARY	
  AND	
  RATIONALE	
                                                              10	
  

1.6	
   HYPOTHESIS	
  AND	
  ORGANIZATION	
  OF	
  THESIS	
                                        11	
  

Chapter	
  2:	
  Effect	
  of	
  ABO	
  Genotype	
  on	
  Cardiometabolic	
  Risk	
  Factors	
  
2.1	
  ABSTRACT	
                                                                                  12	
  

2.2	
  INTRODUCTION	
                                                                              13	
  

2.3	
  METHODS	
                                                                                   14	
  

                                                            vi
2.3.1	
  STUDY	
  DESIGN	
  AND	
  PARTICIPANTS	
                                                        14	
  

2.3.2	
  ABO	
  GENOTYP	
  IDENTIFICATION	
                                                              14	
  

2.3.3	
  CARDIOMETABOLIC	
  RISK	
  FACTOR	
  ASSESSMENT	
                                               15	
  

2.3.4	
  STATISTICAL	
  ANALYSIS	
                                                                       16	
  

2.4	
  RESULTS	
                                                                                         16	
  

2.5	
  DISCUSSION	
                                                                                      22	
  

Chapter	
  3:	
  Effect	
  of	
  "Blood-­‐Type"	
  Diet	
  on	
  Cardiometablic	
  Risk	
  Factors	
  
3.1	
  ABSTRACT	
                                                                                        23	
  

3.2	
  INTRODUCTION	
                                                                                    24	
  

3.3	
  MATERIAL	
  AND	
  METHODS	
                                                                      27	
  

3.3.1	
  STUDY	
  DESIGN	
  AND	
  PARTICIPANTS	
                                                        27	
  

3.3.2	
  DIETARY	
  ADHERENCE	
  SCORE	
  ASSESSMENT	
                                                   27	
  

3.3.3	
  CARDIOMETABOLIC	
  RISK	
  FACTOR	
  ASSESSMENT	
                                               28	
  

3.3.4	
  STATISTICAL	
  ANALYSIS	
                                                                       28	
  

3.4	
  RESULTS	
                                                                                         29	
  

3.5	
  DISCUSSION	
                                                                                      38	
  

Chapter	
  4:	
  Effect	
  of	
  matching	
  ABO	
  genotype	
  to	
  "Blood-­‐Type"	
  Diet	
  on	
  
Cardiometabolic	
  Risk	
  Factors	
  
4.1	
  ABSTRACT	
                                                                                        41	
  

4.2	
  INTRODUCTION	
                                                                                    42	
  

4.3	
  MATERIAL	
  AND	
  METHODS	
                                                                      42	
  

4.3.1	
  STUDY	
  DESIGN	
  AND	
  PARTICIPANTS	
                                                        42	
  

4.3.2	
  ABO	
  GENOTYPE	
  IDENTIFICATION	
                                                             43	
  

                                                               vii
4.3.3	
  DIETARY	
  ADHERENCE	
  SCORE	
  ASSESSMENT	
                43	
  

4.3.4	
  CARDIOMETABOLIC	
  RISK	
  FACTOR	
  ASSESSMENT	
            43	
  

4.3.5	
  STATISTICAL	
  ANALYSIS	
                                    43	
  

4.4	
  RESULTS	
                                                      44	
  

4.5	
  DISCUSSION	
                                                   54	
  

Chapter	
  5:	
  Overview	
  and	
  General	
  Discussion	
  
5.1	
  OVERVIEW	
                                                     56	
  

5.2	
  LIMITATIONS	
                                                  58	
  

5.3	
  FUTURE	
  DIRECTIONS	
                                         60	
  

5.4	
  IMPLICATION	
                                                  61	
  

REFERENCE	
                                                           62	
  

APPENDIX	
                                                            70	
  

	
                                         	
  

                                                               viii
List of Tables

TABLE	
  2-­‐1:	
  SUBJECT	
  CHARACTERISTICS	
  BY	
  ABO	
  GENOTYPE	
  	
                                                  	
      19	
  

TABLE	
  3-­‐1A:	
  THE	
  "TYPE-­‐A	
  "	
  DIET	
  CHARACTERISTICS	
  	
                                                    	
      34	
  

TABLE	
  3-­‐1B:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  TERTILES	
  OF	
  “TYPE-­‐A”	
  DIET	
  SCORE	
  	
           	
      34	
  

TABLE	
  3-­‐2A:	
  THE	
  "TYPE-­‐AB"	
  DIET	
  CHARACTERISTICS	
  	
                                                       	
      35	
  

TABLE	
  3-­‐2B:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  TERTILES	
  OF	
  “TYPE-­‐AB”	
  DIET	
  SCORES	
  	
         	
      35	
  

TABLE	
  3-­‐3A:	
  THE	
  "TYPE-­‐B"	
  DIET	
  CHARACTERISTICS	
                                                            	
     	
  36	
  

TABLE	
  3-­‐3B:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  TERTILES	
  OF	
  "TYPE-­‐B"	
  DIET	
  SCORES	
  	
          	
      36	
  

TABLE	
  3-­‐4A:	
  THE	
  "TYPE-­‐O"	
  DIET	
  CHARACTERISTICS	
  	
                                                        	
      37	
  

TABLE	
  3-­‐4B:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  TERTILES	
  OF	
  "TYPE-­‐O"	
  DIET	
  SCORES	
  	
          	
      37	
  

TABLE	
  4A:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  "TYPE-­‐A"	
  DIET	
  SCORES	
  AND	
  ABO	
  GENOTYPE	
  	
      	
      47	
  

TABLE	
  4B:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  "TYPE-­‐AB"	
  DIET	
  SCORES	
  AND	
  ABO	
  GENOTYPE	
   	
  	
        50	
  

TABLE	
  4C:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  "TYPE-­‐B"	
  DIET	
  SCORES	
  AND	
  ABO	
  GENOTYPE	
  	
      	
      52	
  

TABLE	
  4D:	
  CARDIOMETABOLIC	
  RISK	
  FACTORS	
  BY	
  "TYPE-­‐O"	
  DIET	
  SCORES	
  AND	
  ABO	
  GENOTYPE	
  	
      	
      53	
  

                                                                           ix
List of Figures

FIGURE	
  2-­‐1:	
  ABO	
  BLOOD	
  TYPE	
  ASSESSMENT	
  BY	
  GENOTYPING	
  SINGLE	
  NUCLEOTIDE	
  POLYMORPHISMS	
   15	
  

FIGURE	
  2-­‐2:	
  ABO	
  BLOOD	
  GROUP	
  DISTRIBUTION	
  IN	
  THE	
  ENTIRE	
  TNH	
  COHORT	
  (A)	
  AND	
  BY	
  
ETHNOCULTURAL	
  GROUPS	
  (B)	
  	
                                                                                              	
         17	
  

FIGURE	
  2-­‐3:	
  LEVELS	
  OF	
  FASTING	
  GLUCOSE	
  IN	
  INDIVIDUALS	
  WITH	
  DIFFERENT	
  ABO	
  BLOOD	
  GROUPS	
              	
  20	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  

FIGURE	
  2-­‐4:	
  LEVELS	
  OF	
  FASTING	
  INSULIN	
  IN	
  INDIVIDUALS	
  WITH	
  DIFFERENT	
  ABO	
  BLOOD	
  GROUPS	
  	
             21	
  

FIGURE	
  3-­‐1:	
  TOTAL	
  NUMBER	
  OF	
  RECOMMENDED	
  ITEMS	
  TO	
  EAT	
  (A)	
  OR	
  AVOID	
  (B)	
  IN	
  FOUR	
  MAJOR	
  FOOD	
  
GROUPS	
  LISTEDIN	
  THE	
  FFQ	
  FOR	
  EACH	
  "BLOOD-­‐TYPE"	
  DIET	
  	
                                                  	
      30	
  

FIGURE	
  3-­‐2:	
  DIET	
  SCORE	
  DISTRIBUTION	
  FOR	
  EACH	
  "BLOOD	
  TYPE”	
  DIET	
  	
                                 	
         31	
  

FIGURE	
  4-­‐1:	
  NUMBER	
  OF	
  INDIVIDUALS	
  WITH	
  MATCHED	
  AND	
  UNMATCHED	
  BLOOD	
  GROUPS	
  ACROSS	
  THE	
  
TERTILE	
  TERTILE	
  OF	
  EACH	
  “BLOOD-­‐TYPE”	
  DIET	
  SCORE	
  	
                                       	
       45	
  

FIGURE	
  4-­‐2:	
  THE	
  ASSOCIATION	
  BETWEEN	
  TERTILES	
  OF	
  “TYPE-­‐A”	
  DIET	
  SCORES	
  AND	
  FASTING	
  INSULIN	
  IN	
  
SUBJECTS	
  WITH	
  BLOOD	
  TYPE	
  A	
  AND	
  THE	
  OTHERS	
  	
                                                         	
       48	
  

FIGURE	
  4-­‐3:	
  THE	
  ASSOCIATION	
  BETWEEN	
  TERTILES	
  OF	
  “TYPE-­‐A”	
  DIET	
  SCORES	
  AND	
  FASTING	
  GLUCOSE	
  IN	
  
SUBJECTS	
  WITH	
  BLOOD	
  TYPE	
  A	
  AND	
  THE	
  OTHERS	
  	
                                                        	
       49	
  

FIGURE	
  4-­‐4:	
  THE	
  ASSOCIATION	
  BETWEEN	
  TERTILES	
  OF	
  “TYPE-­‐AB”	
  DIET	
  SCORES	
  AND	
  FASTING	
  GLUCOSE	
  
IN	
  SUBJECTS	
  WITH	
  BLOOD	
  TYPE	
  A	
  AND	
  THE	
  OTHERS	
  	
                                                  	
   51	
  

                                                                        x
List of Appendix

TABLE:	
  FOOD	
  ITEMS	
  INCLUDED	
  IN	
  THE	
  "BLOOD-­‐TYPE"	
  DIET	
  SCORE	
  CALCULATION	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  65	
  

                                                                                                                               xi
Chapter 1: Introduction and Literature Review

                                     1.1     Introduction

       The “Blood-Type” diet is a set of nutritional guidelines that advocate people to eat

according to their blood group. Although popular with the public, the diet remains controversial

because no scientific research has examined its validity. The proposed study will be the first

observational study to investigate whether consumption of a diet in accordance with one's blood

group is associated with favourable health outcomes.

                                 1.2     “Blood-Type” Diet

     The connection between blood group and diet was first suggested by P.J. D’Adamo, a

naturopathic physician, in his book “Eat Right For Your Type” published in 1996 [1]. The

“Blood-Type” diet theory has thereafter gained widespread attention from the public. With more

than 7 million copies sold in over 60 languages, this book was a New York Times bestseller [2].

Based on his perceptions of the blood group evolution and the action of lectins, D’Adamo

postulates that the ABO blood group reveals the dietary habits of our ancestors and people with

different blood groups process food differently; thus, adherence to a diet specific to one’s blood

group could improve health and decrease risk of chronic diseases such as cardiovascular disease.

Based on the “Blood-Type” diet theory, group O is considered the ancestral blood group in

humans, so their optimal diet should resemble the high animal protein diets typical of the hunter-

gatherer era. In contrast, those with group A should thrive on a vegetarian diet as this blood
                                                1
2

group was believed to have evolved when humans settled down into agrarian societies. Following

the same rationale, individuals with blood group B are considered to benefit from consumption of

dairy products because this blood group was believed to originate in nomadic tribes. Finally,

individuals with an AB blood group are believed to benefit from a diet that is intermediate to

those proposed for group A and group B. The “Blood-Type” diet also proposes that lectins,

which are sugar-binding proteins found in certain foods [3], could cause agglutination if they are

not compatible with an individual’s ABO blood group. However, there has been no scientific

research conducted to either support his explanations or validate the “Blood-Type” diet, making

this popular theory controversial.

                                     1.3   ABO Blood Group

1.3.1 ABO System

       Although little is known about the effectiveness of the “Blood-Type” diet, the ABO blood

group itself is well understood. A blood group is a classification of blood based on the presence

or absence of surface antigenic substance on red blood cells. Depending on the blood group

system, these antigens can be proteins, carbohydrates, glycoproteins or glycolipids. To date, 30

human blood groups are recognized by the International Society of Blood Transfusion [4].

Among them, the ABO blood group is the most important one in transfusion medicine and has

been studied extensively. Group O, A, B, and AB are the four subgroups within the ABO system,

which is estimated to account for 44%, 35%, 16% and 5% of global population, respectively [5].

The distinction of ABO blood group relies on the structural variation of a carbohydrate antigenic

substance, called H-antigen, found on red blood cells. Such variation is a result of different

                                                2
3

enzymatic activities determined by the alleles of the ABO gene locus. Specifically, the IA allele

encodes a glycosyltransferase that attaches α-N-acetylgalactosamine to H-antigen, producing the

A antigen. The IB allele encodes a glycosyltransferase that bonds α-D-galactose to the H antigen,

creating the B antigen. In contrast, the i allele does not produce any functional enzyme due to a

frameshift mutation that results in premature termination of the translation, so H antigen remains

intact in this case [6]. Because the IA and IB alleles are co-dominant to each other and both are

dominant over allele i, different combinations of IA, IB and i can produce different ABH antigens

on human red blood cells. For example, people with blood group AB will have genotype IAIB,

whereas those with blood group A can have either IAIA or IAi [7]. The discovery of the ABO

blood group not only was a major breakthrough in transfusion medicine, but also draws attention

to the potential importance of blood group in health and disease risk management.

1.3.2 ABO Blood Group and Diseases

       As one of the first recognizable genetic variants in humans, the ABO system has been

studied for its association with a variety of diseases, including cardiometabolic syndromes,

cancer and microorganism infections. As for cardiometabolic diseases, research has shown that

people with group O on average had 25% lower level of von Willebrand factor (VWF), which is

a critical protein involved in haemostasis [8]. Considering the fact that higher VWF levels could

increase the risk of ischemic stroke [9], a lower expression of VWF may explain the observation

that people with blood group O had a reduced risk of venous thromboembolism [10]. Although

blood group O demonstrates some degree of protection against thrombosis, it may increase the

risk of diabetes. One study has shown that blood group B was associated with a decreased risk of

type 2 diabetes compared to blood group O (OR = 0.44, 0.27-0.70) [11], suggesting that the

association between ABO blood group and cardiometabolic diseases is disease-specific.

                                                3
4

Regarding its association with cancers, people with blood group O may have lower risks of

pancreatic cancer [12] and gastric cancer [13], but a higher risk of non-melanoma skin cancer

[14]. Gates et al. have also found that the presence of the B antigen on the red blood cells was

positively associated with ovarian cancer incidence [15]. Thus, certain ABO groups may be

associated with different risks in different types of cancers. Besides its associations with

cardiometabolic diseases and cancers, the ABO blood group may also alter the incidences of

malaria and cholera. In a matched case-control study of 567 Malian children, Rowe et al. found

that group O was correlated with a 66% reduction in the odds of developing severe malaria

compared to the non-O blood groups. The difference in group O may be caused by the inhibition

of Plasmodium falciparum resetting, which is a parasite virulence phenotype associated with

severe malaria [16]. As for cholera, an observational study in Bangladesh found that both the

incidence and severity of diarrhea were higher in group O, but lower in group AB [17]. Overall,

the existing research suggests that ABO blood type may play a role in modifying an individual’s

susceptibility to certain diseases.

1.3.3 Blood Groups and Nutrition

        To date, research on the association between blood groups and nutrition is limited.

Nonetheless, the results from several published studies have suggested that blood groups might

indeed alter the relationship between diet and physiological outcomes to some extent. For

example, in a study on high-fat diet and intestinal phosphatase published in 1960s, Langman et

al. found that people with group A not only had the lowest level of enzyme activity at baseline,

but also had lowest increase of activity after giving a high-fat diet.[18] Because phosphatase

negatively regulates fat absorption in the gut [19], a lower enzyme activity may explain why

people with blood group A had higher levels of serum cholesterol in another study [20]. Although

                                               4
5

the findings suggested that ABO blood group might alter a metabolic pathway related to nutrient

absorption, the interpretation of the results is limited because no statistical analysis was

performed in these two early studies. In addition to the potential to influence nutrient absorption,

a Finnish group has demonstrated that ABO blood group might have an impact on the human gut

microbiota composition. Compared to individuals with the B antigen (blood group B and AB),

people with non-B antigens were shown to have lower diversity of the Eubacterium rectale-

Clostridium coccoides (EREC) and Clostridium leptum (CLEPT) –groups [21]. The linkage

between ABO blood group and microbiota has been further substantiated in recent studies. For

example, both Helicobacter pylori [22] and Lactobacillus spp. [23] have been shown to use ABO

antigens as adhesion receptors. Furthermore, research has shown that different species may have

different binding affinities to ABH antigen [23] and host ABO genotype can affect the enzyme

secretion and metabolism of gut microbiota [24]. Considering the role of gut microbiota on

nutrient breakdown and absorption [25], the results of these studies further imply that ABO blood

group could be a genetic host factor that modulates the relationship between diet and health.

Besides the ABO system, research on another glycoprotein-based blood group system, known as

MNS, has found that individuals with blood group NN tended to have a greater reduction in low

density lipoprotein (LDL) cholesterol in response to a low-fat diet compared to individuals with

MN and MM blood groups. [26] However, because ABO and MNS blood group systems are

functionally distinct, the generalization of the MNS finding on the current project is limited.

Overall, several studies have suggested that a potential interaction may exist among blood

groups, diet and health. However, the evidence, particularly for the ABO system, remains scarce.

                                                 5
6

                               1.4   Cardiometabolic Diseases

1.4.1 Prevalence and Etiology

       Cardiometabolic diseases, including Type 2 diabetes (T2D) and cardiovascular diseases

(CVD), are the leading causes of mortality and morbidity globally [27]. Patients with this type of

disease usually exhibit hypertension, hyperglycemia, dyslipidemia, inflammation and obesity

[28]. In Canada, over 3 million and 1.3 million of people suffer from T2D and CVD respectively

[29,30]. As a huge burden on the health care system, T2D is expected to cost the Canadian

healthcare system $16.9 billion a year by 2020 [31], and CVD alone costs Canadian more than

20.9 billion each year [29].

       The development of cardiometabolic diseases commonly involves excess accumulation of

body fat and insulin resistance in adipose, hepatic and muscle tissues [32]. Visceral and central

adiposity are known to increase the level of free fatty acids in the circulation [33,34]. High levels

of free fatty acids can cause hepatic gluconeogenesis and lead to excess secretion of glucose,

triglycerides and very low-density lipoprotein (VLDL). This process is usually accompanied by a

reduction in high-density lipoprotein (HDL) cholesterol secretion and elevation of low-density

lipoprotein (LDL) cholesterol. Eventually, these physiological states lead to dysglycemia and

dyslipidemia, which are early signs of cardiometabolic disorders [35].

1.4.2 Biomarkers of risk

       In order to prevent and manage T2D and CVD, a number of serum biomarkers along with

the anthropometric measurements are usually monitored during clinical visits to indicate the risk

of these two common diseases. These biomarkers are usually associated with glucose and fat

metabolism that are important in the disease pathology. Regarding glucose metabolism, insulin
                                                 6
7

regulates the cellular uptake of glucose from blood when its level is high after a meal, and

glucagon promotes gluconeogenesis and glycogenolysis in the liver when the level of glucose is

low [36]. In patients with insulin resistance, higher levels of insulin are required to maintain glucose

uptake in peripheral tissues [37]. Pancreatic β-cells produce and secrete more insulin in response,

resulting in the individual becoming hyperinsulinemic [38]. This process continues until β-cells

cannot meet the increased need of insulin secretion, which results in elevation of blood glucose

[39,40]. Therefore, high levels of glucose and insulin are strong predictors of the development of

T2D [36]. A number of approaches have been developed to monitor and indicate insulin resistance

and β-cell dysfunction. In epidemiologic studies, the homeostasis model assessment of insulin

resistance (HOMA-IR) and β-cell dysfunction (HOMA-Beta) is a method commonly used to

indicate the function of glycemic regulation. HOMA is based on the levels of fasting insulin and

glucose, which are indicators of the balance between insulin secretion and glucose maintenance in the

liver [41]. The equation of calculating HOMA is shown below.

HOMA-IR = (fasting plasma insulin x fasting plasma glucose) / 22.5

HOMA-Beta = (20 x fasting plasma insulin) / (fasting plasma glucose - 3.5), where insulin is

measured in mU/L and glucose is measured in mmol/L [42].

Results from the HOMA method have been proven to correlate well (r>0.7) with the traditional

hyperglycemic clamp method [43,44].

As for biomarkers of cardiometabolic diseases in lipid metabolism, high levels of serum

cholesterol and triglycerides are common indicators of dysregulation in lipid metabolism, which

is a main feature of cardiometabolic diseases. Although serum total cholesterol level is associated

with cardiometabolic risk, the lipoprotein carriers of cholesterol actually play a larger role in the

pathologic process [45]. Lipoprotein particles consist of triglycerides, cholesterol, phospholipids
                                                   7
8

and apolipoproteins. Based on the composition of apolipoproteins and the relative density of

triglycerides and cholesterol, lipoprotein particles can be classified into several categories [45].

Low-density lipoprotein (LDL) and high-density lipoprotein (HDL) are the two that are highly

related to cardiometabolic risk. The main role of LDL is to transport triglycerides and cholesterol

to tissues, whereas HDL is involved in returning cholesterol back to liver for excretion [46].

Elevated levels of LDL coupled with reduced levels of HDL are known to promote the formation

of atherosclerotic plaques and thus the development of the CVD [45,46]. The atherosclerotic

process begins when high amounts of LDL enter the vascular endothelium and become oxidized,

which attracts macrophages that engulf the extra lipids and form foam cells. Meanwhile, the

activated macrophages release high levels of pro-inflammatory cytokines, such as IL-6. This

attracts platelets to attach to the site of injury and promotes the proliferation of smooth muscle

cells. The process is also accompanied by an elevation of C-reactive protein (CRP) secretion,

which plays a critical role in the phagocytosis by macrophages [47]. As a well-established

biomarker of inflammation, CRP has been consistently associated with T2D and CVD [48].

Compared to healthy individuals, people with cardiometabolic diseases tend to have levels of

CRP that are two- to four-fold higher [48]. The effects of CRP and other pro-inflammatory

cytokines all perpetuate the accumulation of foam cells and smooth muscle cells at the plaque. As

a result, blood vessel narrows down and blood flow is diminished, which can lead to stroke and

myocardial infarction [46]. In contrast, high levels of HDL can inhibit the deposition of

cholesterol and prevent the formation of atherosclerotic plaques by transporting triglycerides and

cholesterol back to the liver [49].    In addition to LDL and HDL, serum triglyceride (TG)

concentration is another biomarker that strongly correlates with cardiometabolic diseases [50,51].

High levels of TG are known to both impede the scavenging capacity of HDL [52,53] and

promote the formation of small, dense LDL particles, which are more easily oxidized and thus
                                                 8
9

more atherogenic than their normal-sized counterpart [54]. In summary, the levels of biomarkers

involved in glucose and fat metabolism all play critical roles in the pathologic process of

cardiometabolic diseases and thus are often used as surrogate indicators during disease screening

[55,56].

1.4.3 Risk Factors

       Sex, age, family history, ethnicity are all known to alter the risk of cardiometabolic

diseases [32,57]. For example, South Asian individuals have a higher prevalence of CVD in

Canada compared to Caucasian or East Asian [57]. In addition to these demographic factors,

smoking, exercise and diet represent other risk factors that can be modified through lifestyle

habits [58,59]. As one of the most important modifiable risk factors, diet has been consistently

shown to alter the risk of cardiometabolic diseases. Regarding specific nutrients, consumption of

foods rich in dietary fiber [60,61], magnesium [62,63], and vitamin D [64,65], may be beneficial

in preventing the development of T2D and CVD. In contrast, diets with a high intake of dietary

cholesterol and high ratio of saturated /polyunsaturated fat can increase the risk of both T2D and

CVD [66,67,68]. As for general dietary patterns, diets high in fruit and vegetable intakes are

known to significantly reduce cardiometabolic disease risk. For example, in a recent landmark

study. the Mediterranean diet, which is characterised by a high intake of olive oil, nuts, fruits and

vegetables, a moderate intake of fish and poultry, and a low intake of dairy and red meat, has

been shown to substantially reduce the incidence of major cardiovascular events by 30% [69].

Overall, research suggests that a healthy diet is a significant modifiable lifestyle factor in the

prevention and management of cardiometabolic diseases.

                                                 9
10

                              1.5    Summary and Rationale

          In summary, both ABO blood group and dietary habits have been shown to alter the risk

of cardiometabolic diseases in previous research. The associations of these diseases with diet, as

well as with blood group, may imply that a potential interaction exists between diet and blood

group on subsequent cardiometabolic disease risk. Considering the popularity of the “Blood-

Type” diet and its lack of scientific evidence, it will thus be worthwhile to investigate whether

the effects of dietary intake on diseases are dependent on an individual’s blood group. The results

of this research has the potential to either substantiate or reject the health claims of the “Blood-

Type” diet, so that evidence-based recommendations can be made by health professionals in the

future.

                                                10
11

                    1.6     Hypothesis and Organization of Thesis

Hypothesis

Adherence to a diet specific to one's blood group is associated with a reduced disease risk profile.

Objectives

1.     To determine the effect of ABO genotype on cardiometabolic risk factors.

2.     To determine the effect of “Blood-Type” diet on cardiometabolic risk factors.

3.     To determine the effect of matching ABO genotype and “Blood-Type” diet on

       cardiometabolic biomarkers.

                                                11
Chapter 2: Effect of ABO Genotype on Cardiometabolic Risk

Factors

                                        2.1 Abstract

Background: Previous research has suggested that ABO blood group is associated with a variety

of chronic diseases, such as cancer, thrombosis and Type 2 diabetes. However, the results on

some of these linkages, such as the one with T2D risk, have largely remained inconsistent and

inconclusive. The objective of this chapter is to examine the relationship between ABO blood

group and cardiometabolic risk factors, which can further elucidate some of these linkages from a

biomarker perspective.

Methods: Subjects (n=1,455) were participants of the Toronto Nutrigenomics and Health study.

ABO blood group was determined by genotyping rs8176719 and rs8176746 in the ABO gene.

Overnight 12-hour fasting blood samples were collected to measure serum cardiometabolic

biomarkers by high performance liquid chromatography. ANCOVA, with age, sex, ethnicity, and

energy intake as covariates, was used to compare anthropometric measurements and biomarkers

of cardiometabolic health across different blood groups

Results: Subjects with blood group O had lower levels of serum insulin, HOMA-IR, and

HOMA-Beta compared to blood groups A and B (p
13

                                      2.2 Introduction

       The “Blood-Type” diet advises people to eat based on their blood group to optimize

health outcome. For each blood group, the recommended diet represents as a distinct dietary

pattern. For example, the Type-A diet is similar to a vegetarian diet, whereas the Type-O diet

resembles the low-carbohydrate diet that has high animal protein intake. Before examining

whether people with certain blood group may benefit more from following the corresponding

“Blood-Type” diet, it is critical to investigate the effect of different ABO genotypes on

cardiometabolic risk factors.

        As a well-known genetic variant among individuals, ABO blood group is not only

critical in blood transfusion, but may also alter the risk of a variety of diseases, including

cardiometabolic syndromes, cancers and microorganism infections [11,13,17]. Regarding

cardiometabolic diseases, research has shown that people with group O may have a reduced risk

of venous thromboembolism due to their lower level of von Willebrand factor [8], which is a

critical protein involved in blood clotting [10]. Although blood group O may confer some degree

of protection against thrombosis, it may increase the risk of diabetes. By using the data from the

Nurses’ Health Study, Qi et al. have shown that ABO blood group is not only associated with the

serum level of E-Selectin, a well-known risk factor for T2D, but also found that blood group O

was associated with an increased risk of Type 2 diabetes compared to blood group B [11].

However, the results on the some of these linkages, such as the one with T2D risk, have remained

inconsistent. For example, the higher risk of T2D in people with blood group O was reported in

two studies [11,70], but not replicated in others [71,72,73].         In order to address this

inconsistency, this study intends to elucidate the linkage between ABO blood group and

cardiometabolic disease risk in a young multiethnic population. This would allow us to further
                                               13
14

investigate the etiological relationship upstream before disease onset and to study the role of

ethnicity in the linkage between ABO blood group and cardiometabolic serum biomarkers.

                                 2.3 Material and Methods

2.3.1 Study Design and Participants

        Subjects (n=1,639) were participants of the Toronto Nutrigenomics and Health (TNH)

Study, which is a cross-sectional examination of young adults aged 20 to 29 years. All subjects

were recruited between October 2004 and December 2010 and completed a general health and

lifestyle questionnaire, which included information on age, sex, ethnocultural group and other

subject characteristics. Subjects who were likely under-reporters (less than 800 kcal per day) or

over-reporters (more than 3,500 kcal per day for females or 4,500 kilocalories per day for males)

of energy intake were excluded from the analyses. Subjects were also excluded if they had

missing data for any of the biomarkers of interest or ABO genotype (n=184). After exclusions,

1,455 subjects (993 women and 462 men) remained. Individuals were categorized into four major

ethnocultural groups: White (n=703), East Asians (n=491), South Asians (n=155), and others

(n=106).

2.3.3 ABO Genotype Identification

        The Sequenom MassArray® multiplex method was used to determine the blood group of

study     participants   by   genotyping   two    single   nucleotide   polymorphisms    (SNPs)

(rs8176719Del>G; rs8176746A>C) in the ABO gene. The rs8176719 SNP indicates O-allele-

specific 261delG while rs8176746 determines the galactose specificity of the encoded A/B

                                                 14
15

transferases and thus the expression of A and B alleles [7]. Previous studies have taken

advantages of the genetic information to infer blood type from single nucleotide polymorphism

(SNP), which can be more accurate and efficient compared to the traditional blood typing that is

based on antibody assay [11,74]. Figure 2.1 depicts the exact relationship between these SNPs

and ABO blood type assessment.

Figure 2-1: ABO blood group assessment by genotyping SNPs.

2.3.3 Cardiometabolic Risk Factor Assessment

       Anthropometric measurements including height, weight, blood pressure and waist

circumference were determined as previously described [75]. Body mass index (BMI; kg/m2) was

calculated and physical activity was measured by questionnaire and expressed as metabolic

equivalent (MET)-hours per week, as described previously [75,76]. Overnight 12-hour fasting

blood samples were collected to measure serum biomarkers of cardiometabolic disease, including

triglycerides, free fatty acids, C-reactive protein, fasting glucose, fasting insulin, and total-, HDL-

and LDL-cholesterol, as described previously [77]. After converting insulin concentrations from

pmol/L to IU/mL, the homeostasis model of insulin resistance (HOMA-IR) was calculated by

                                                  15
16

using the formula: (insulin * glucose)/22.5, and the homeostasis model of beta-cell function

(HOMA-Beta) was calculated by using the formula: (20 * insulin)/(glucose - 3.5).

2.3.5 Statistical Analysis

       Statistical analyses were performed using the Statistical Analysis Systems (SAS)

Software program (version 9.2; SAS Institute Inc., Cary, North Carolina). The a error was set at

0.05 and reported p-values are 2-sided. Subject characteristics were compared across different

ABO blood groups by using chi-square tests for categorical variables and analysis of variance

(ANOVA) for continuous variables. Analysis of covariance (ANCOVA) was used to compare

means of cardiometabolic biomarkers among different ABO blood groups. Variables that were

not normally distributed were either loge or square root transformed prior to analysis, but the

mean values and standard errors are displayed without transformation to facilitate interpretation.

Means compared between groups were adjusted for multiple comparisons using the Tukey-

Kramer procedure. Age, sex, ethnicity were used as covariates in the ANCOVA analysis.

                                         2.4 Results

       As for blood group determination, SNPS rs8176719 and rs8176746 were genotyped to

infer the ABO blood group of study subjects. Figure 2-2A shows that Group O, A, B and AB

represented 37%, 38%, 19% and 6% of the population, respectively. The frequency of each blood

group was different across ethnocultural groups (P
17

              A

                                                                                                                                         O	
  

                                                                                                                                         A	
  

                                                                                                                                         B	
  

                                                                                                                                         AB	
  

         	
  	
  B	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  Caucasian	
      	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  East	
  Asian	
  

                                     	
  	
  Others	
                          	
  	
  	
  	
  	
  	
  	
  	
  South	
  Asian	
  

                                                                                                                                                  O	
  

                                                                                                                                                  A	
  

                                                                                                                                                  B	
  

                                                                                                                                                  AB	
  

Figure 2-2: ABO blood group distribution in the entire TNH cohort (A) and by ethnocultural

groups (B).

                                                                          17
18

     Subject characteristics based on the ABO blood group are summarized in Table 2-1. After

adjusting for age, sex, and ethnocultural group, subject characteristics were similar across ABO

blood groups, except for insulin, HOMA-IR and HOMA-Beta. Group O individuals had lower

levels of fasting insulin, HOMA-IR and HOMA-Beta compared to group A or B. Although the

overall association between blood group and total cholesterol was significant (p=0.043), no

difference was observed among specific ABO blood group. Figure 2-3 and Figure 2-4

respectively show the levels of fasting glucose and insulin in individuals with different ABO

blood groups.

                                              18
19

    Table 2-1: Subject Characteristics by ABO Genotypea
                                                                          Genotype
    Characteristic                             O                 A                   B            AB         P value
    Subjects [n (% of total)]               543 (37)         544 (38)          277 (19)          91 (6)
                                                        b
    Age (y)                                22.7 ± 2.5        22.8 ± 2.5        22.4 ± 2.3      22.5 ± 2.6      0.13
    Sex [n (%)]                                                                                                0.31
         Female                             358 (36)         387 (39)          187 (19)          61 (6)
         Male                               185 (40)         157 (34)           90 (19)          30 (7)
    Ethnocultural group [n (%)]
20

                                        5	
  
                                     4.9	
  
                                     4.8	
  
 Fas`ng	
  Glucose	
  (mmol/L)	
  

                                     4.7	
  
                                     4.6	
  
                                     4.5	
  
                                     4.4	
  
                                     4.3	
  
                                     4.2	
  
                                     4.1	
  
                                        4	
  
                                                O	
     A	
          B	
     AB	
  

Figure 2-3: Levels of fasting glucose in individuals with different ABO blood groups.

                                                                20
21

                                      60	
  
                                                                    b	
  
                                                       b	
  
                                      55	
                                   ab	
  

                                      50	
     a	
  
  Fas`ng	
  Insulin	
  (pmol/L)	
  

                                      45	
  

                                      40	
  

                                      35	
  

                                      30	
  
                                               O	
     A	
          B	
      AB	
  

Figure 2-4: Levels of fasting insulin in individuals with different ABO blood group

                                                               21
2.5 Discussion

       Regarding the determination of ABO blood group, the reported frequency of blood group

distribution in our study population is similar to the frequency reported previously for Canada

[78], in which group O and A being the most common two blood groups. The higher frequency

of blood group B observed in people from Asian ethnocultural backgrounds is also consistent

with previous findings [5]. The consistency of our results with existing knowledge therefore

confirms the validity of our blood-typing method.

       An examination of the relationship between the ABO blood group and levels of

cardiometabolic risk factors showed no association for most of the biomarkers, except for fasting

insulin and the derived assessment of insulin resistance and beta-cell function. The lower levels

of these risk factors in subjects with blood group O were consistently shown in both men and

women and across different ethnocultural groups (data not shown). This finding is in line with

previous research suggesting that an association may exist between the blood groups and diabetes

risk [11,70,71,72,73]. However, it is not clear which ABO blood group is at higher risk. Some

studies reported that individuals with blood group O were at higher risk [11,70], but this was not

replicated in others [71,72,73]. The inconsistent results from these studies may be partly

explained by ethnicity, sample sizes and other unadjusted covariates. By investigating in a

multiethnic population, our study indicates that the linkage between ABO blood group and

diabetes risk exist consistently across ethnicities. The observed difference in fasting insulin levels

in healthy young adults also indicates that may indeed play a role in the development of insulin

resistance and the aetiology of T2D development and contribute to diabetes risk later in life.

Larger prospective studies will be helpful to further confirm the etiological relationship between

ABO blood group and T2D, which has the potential facilitate T2D screening and prevention.

                                                 22
23

Chapter 3: Effect of “Blood-Type” Diet on Cardiometabolic Risk

Factors

                                          3.1 Abstract

Background: Each of the four “Blood-Type” diets represents a distinct dietary pattern.

Promoting high vegetable and fruits consumption, the Type-A diet resembles to a vegetarian diet.

Recommending moderate intake of fish and dairy consumption, the Type-AB and Type B diets

are closely related to the well-known Mediterranean diet. As the only “Blood-Type” diet that

allows high intake of animal proteins, the Type-O diet is similar to a low-carbohydrate diet.

Before examining whether people with certain blood group may benefit more from following the

corresponding “Blood-Type” diet, it is critical to investigate the overall dietary effects in people

regardless of their ABO blood groups, which is the objective of this chapter.

Methods: Subjects (n=1,455) were participants of the Toronto Nutrigenomics and Health study.

Overnight 12-hour fasting blood samples were collected to measure serum cardiometabolic

biomarkers through by high performance liquid chromatography. Dietary intake was assessed

using a one-month, 196-item food frequency questionnaire and a diet score was calculated to

determine relative adherence to each of the four “Blood-Type” diets. ANCOVA, with age, sex,

ethnicity, and energy intake as covariates, was used to compare anthropometric measurements

and biomarkers of cardiometabolic health across tertiles of each blood type diet score.

Results: Adherence to the Type-A diet was associated with lower BMI, waist circumference,

blood pressure, serum cholesterol, triglycerides, insulin, HOMA-IR and HOMA-Beta (P
24

(P
25

diet. Therefore, each of the four “Blood-Type” diets is similar to some existing dietary patterns

that have been shown to reduce the disease risk and promote health.

       As for the Type-A diet pattern, vegetarian diets contain no meat, more grains, legumes,

vegetables and fruits, which therefore is associated with lower dietary intake of total fat, saturated

fat, and cholesterol and higher intake of fiber [79]. Consuming a vegetarian diet has been shown

to reduce the risk of hospital admission [80], cataract [81], cancers [82,83], T2D [84,85],

hypertension [86], ischemic heart disease [87], and all-cause mortality [88]. As for

cardiometabolic diseases specifically, people who follow a vegetarian diet are known to have

higher insulin sensitivity, lower blood pressure and LDL-cholesterol, which contribute to a lower

risk of diabetes [89] and ischemic heart disease [80] compared to non-vegetarians.

       As for dietary pattern that resembles to the Type-AB and Type-B diets, the Mediterranean

diet is characterized by a high consumption of whole grains, fruits and vegetables, legumes and

olive oil, and a moderate consumption of fish, dairy and wine [90]. This popular diet has recently

received wide attention from the public as many studies have demonstrated its health-promoting

effects [90]. Adherence to a Mediterranean diet has been shown to decrease the risk of preterm

delivery [91], gestational diabetes [92], Alzheimer’s Disease [93], Parkinson’s Disease [94], and

pancreatic [95], colorectal [96], breast [97,98], and esophageal cancers [98]. Regarding to

cardiovascular diseases and diabetes, research has shown that adhering to the Mediterranean diet

could have long-term beneficial effects on insulin sensitivity and blood pressure management,

which could lead to lower risks of Type 2 diabetes and cardiovascular diseases [69,99]. It has

been suggested that the observed beneficial effect may be attributed to higher intakes of anti-

oxidants, n-3 fatty acids, and fibre from the Mediterranean diet [69]. Therefore, as evident from

                                                 25
26

the aforementioned studies, following a Mediterranean diet may be beneficial for preventing

chronic diseases, such as cardiovascular diseases and Type 2 diabetes.

       As the “Blood-Type” diet that restrains the intake of grains and promotes the

consumption of animal products, the Type-O diet resembles to the low-carbohydrate diet and the

high-protein diet. With carbohydrate content contribute to 15%-40% of total energy intake, low-

carbohydrate diets have been shown to promote weight loss and enhance glycemic control

[100,101]. High-protein diets typically are characterized by 20-30% or more of total daily

calories coming from proteins [102]. High intakes of proteins have been suggested to enhance

appetite suppression [103] and insulin sensitivity [104]. Nonetheless, with its recommendation

for animal protein consumption, especially red meat, the Type-O diet also shares some similarity

with the high-fat diet, which is known to cause extra abdominal fat accumulation [105,106],

hyperphagia [107], and insulin resistance [108]. Therefore, the Type-O diet may represent as the

only non-healthy “Blood-Type” diet.

       Based on findings of these previous studies on different dietary patterns, it is interesting

to examine whether each of the four “Blood-Type” diets can influence serum biomarker profile in

our study population. The examination of this association requires the quantification of the

relative adherence to the “Blood-Type” diet based on the existing data from the Food Frequency

Questionnaire (FFQ). Considering the fact that the “Blood-Type” diet recommends the

consumption or avoidance of specific food items, the diet adherence score system needs to be

based on these items, instead of the general food group. Furthermore, because the

recommendations of the “Blood-Type” diet does not specify the exact amount of consumption for

each food item [1], the score system would assign points based on actual quantity of consumption

for each food item and assumes that higher consumption indicates closer adherence. Based on the

                                               26
27

food item and their quantities of consumption provided by the Food Frequency Questionnaire, the

scoring system aimed to generate a continuously scaled grade to capture relative diet adherence

of each individual. By examining the effect of “Blood-Type” diets in a population regardless of

ABO blood group, the goal of this chapter was to investigate whether following “Blood-Type”

diets is associated with a healthier biomarker profile in the general population.

                                 3.3 Material and Methods

3.3.1 Study Design and Participants

Refer to Chapter 2 (pages 14).

3.3.2 Dietary Adherence Score Assessment

      Dietary intake was assessed by a one-month, Toronto-modified Willet 196-item semi-

quantitative food frequency questionnaire (FFQ) as described previously [77]. Briefly, each

subject was given instructions on how to complete the FFQ by using visual aids of portion sizes

to improve the measurement of self-reported food intake. Subject responses to the individual

foods were converted into daily number of servings for each item. In order to quantify the

adherence to each of the four “Blood-Type” diets, four different diet scores were given to each

subject regardless of his or her own blood group. Based on the food items listed in the “Blood-

Type” diet [1], subjects received one positive point for consuming one serving of each

recommended food item and one negative point for consuming one serving of an item on the list

of foods to avoid. Foods that are listed as “Neutral” were not included in the equation and do not

contribute to the final score. The equation of calculating the diet score is attached below.

                                                 27
28

“Blood-Type” Diet Score = Σ (Recommended Food Groups to Eat * Servings) – Σ

(Recommended Food Groups to Avoid * Servings)

        The lists of recommended foods to eat or avoid for each ABO blood group are shown in the

Appendix. Subjects were then grouped into tertiles based on their scores for each diet, with the

top tertile representing those whose diet most closely resembles the corresponding blood type

diet.

3.3.3 Cardiometabolic Risk Factor Assessment

Refer to Chapter 2 (page 15).

3.3.4 Statistical Analysis

         Statistical analyses were performed using the Statistical Analysis Systems (SAS)

Software program (version 9.2; SAS Institute Inc., Cary, North Carolina). The a error was set at

0.05 and reported p-values are 2-sided. Subject characteristics were compared across ABO blood

groups by using chi-square tests for categorical variables and analysis of variance (ANOVA) for

continuous variables. Analysis of covariance (ANCOVA) was used to compare means of

biomarkers of cardiometabolic disease risk across tertiles of diet scores. Variables that were not

normally distributed were either loge or square root transformed prior to analysis, but the mean

                                                28
29

values and standard errors are displayed without transformation to facilitate interpretation. Means

compared between groups were adjusted for multiple comparisons using the Tukey-Kramer

procedure. Age, sex, ethnocultural group and energy intake were used as covariates in the

ANCOVA analysis. Physical activity and smoking were also considered; however, they did not

materially alter the results and were not included in the final model.

                                           3.4 Results

      Regarding the diet adherence assessment, the method used in this study was able to

generate scores that are continuously scaled and have a normal distribution. Figure 3-1A and

Figure 3-1B demonstrate the total number of recommended items to eat or avoid respectively in

four major food groups listed in the FFQ for each "Blood-Type” diet. Briefly, the Type-A diet

recommends high consumption of grains, fruits, and vegetables. The Type-B diet recommends

high intake of dairy products and moderate intakes of other food groups. The Type-AB diet is

similar to the Type-B diet in terms of recommended food groups, but has more restrictions on

specific food items. For example, only eggs and fish are recommended as sources of meat for

group AB individuals. The Type-O diet encourages high consumption of meats and avoidance of

grain products. In order to quantify the adherence to these four blood type diets, four different

scores were calculated for each subject, regardless of his or her own ABO genotype. Figure 3-2

shows the score distribution. All four scores were normally distributed and did not require any

transformation.

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