Healthy dietary patterns, lipids and inﬂammation in human randomized controlled trials

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Healthy dietary patterns, lipids and inﬂammation in human

randomized controlled trials

Lena Leder

Dissertation for the degree of Philosophiae Doctor (Ph.D.)

Department of Nutrition Institute of Basic Medical Sciences

University of Oslo

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© Lena Leder, 2017

Series of dissertations submitted to the Faculty of Medicine, University of Oslo

ISBN 978-82-8377-000-1

reproduced or transmitted, in any form or by any means, without permission.

Cover: Hanne Baadsgaard Utigard.

Print production: Reprosentralen, University of Oslo.

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Acknowledgements

This work was carried out at the Department of Nutrition, Institute of Basic Medical Sciences at the University of Oslo, Norway from 2012 until 2016. The primary ﬁnancial support was a four-year doctoral fellowship from the Institute of Basic Medical Sciences, University of Oslo, Norway.

Prof. Dr. Kirsten Holven was my principal supervisor. Thank you for pro- viding an incredible environment for conducting my PhD in your expert su- pervision. The scientiﬁc guidance, critical questions, support, sharing extensive knowledge and never-ending optimism were greatly appreciated. Your positive and kind attitude was inspiring and always helped me to get back on track.

With the same gratitude I want to thank my co-supervisor Prof. Dr. Stine Ulven for sharing your invaluable knowledge, your patience, and encourage- ment means a lot to me. Thank you for taking this role and supporting me wherever and whenever you could.

Thank you to the SYSDIET consortium for allowing access to the study material and to all the people participating in the SYSDIET study. My special gratitude I want to express to Marjukka Kolehmainen for her tremendous help with the SYSDIET paper. Thank you for your inspiring suggestions, great ideas and very fruit-full discussions.

Thank you to the NoMa study team at UiO, HiOA and Mills DA for mak- ing this study possible. I express my gratitude to all people participating in the NoMa study.

All my colleagues formed an extremely friendly work environment that allowed to discuss ideas as well as critical issues. I am very grateful to Inger Ottes- tad, Gyrd Omholt Gjevestad, Ingunn Narverud, Jacob Juel Christensen, Patrik Hansson, Amanda Rundblad, Mari Myhrstad and Vibeke Telle-Hansen for the

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good and productive times in seminars, in our “Kollokvie”, in the lunch breaks, at conferences, at dinners, while running and cycling. A great thank you to Kristin Eckardt, Christin Zwaﬁnk and Rikke Nørgaard. Our discussions about lab methods, teaching and life in general were highly appreciated. Thank you to all who proofread my thesis and gave invaluable comments.

Thank you to Marit Sandvik, Navida Akhter Sheikh and Ellen Raael for their expertise and technical support in the lab.

Thank you to Anine Medin and Susanne Strohmaier for our master-mind group. It was extremely inspiring, funny, crazy, critical and knowledgeable. I hope we keep in touch and keep it running in one way or the other!

I want to express my gratitude to Carina Knudsen for her creative support with the ﬁgures in my thesis and to Magne Thoresen for all the biostatistical support during my PhD.

Deep gratitude goes to my dear family. My parents-in-law Beatrix and Rein- hard Leder always made it possible to help out even though there are 1500km between us. You are incredible. A huge thank you for in-depth revision of the language in my thesis. My parents Beate and Oskar Lückel have always encour- aged and believed in me whatever I have been up to; no matter if it was crazy, well-considered or just for fun. Thank you for your unfailing love and your never-ending support.

My deepest thank you I want to express to my beloved husband, Felix Leder, and my children, Finus and Nuka. I am deeply thankful for your motivation and inspiration, and that you always believed in me. Finus and Nuka are my sunshines showing me what really matters in life. I would not have made it as far without the three of you. You guys rock!

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Abstract

Healthy dietary patterns have been subject of considerable attention in recent years. A healthy Nordic diet may improve cardiovascular risk factors and thereby prevent cardiovascular diseases. In order to reduce plasma cholesterol and disease risk, one central aspect of the healthy Nordic diet is the combination of reduced dietary intake of saturated fatty acids and increased dietary intake of polyunsaturated fatty acids. However, although the effect of dietary fat quality on plasma cholesterol concentration is well established, the effects and mechanisms of whole diets on plasma lipids and inflammation are less examined.

Therefore, we aimed to investigate the role of healthy dietary patterns on lipids and inﬂammation with special focus on fat quality in populations with cardiometabolic risk.

Two randomized controlled dietary intervention studies were included in this thesis. In an eight-week double-blinded study, healthy adults aged 25-70 years with moderate hypercholesterolemia were assigned to an experimental diet or a control diet. The experimental diet group received commercially available food items in which saturated fat was replaced by vegetable sunﬂower and rapeseed oil. The control diet group received similar commercial food items with a higher content of saturated fat and lower content of polyunsaturated fat.

In an 18-24 week, Nordic multi-center study, subjects between 30-65 years with features of metabolic syndrome were assigned to follow a healthy Nordic diet or an isocaloric control diet. An oral glucose tolerance test was performed at baseline and at the end of the study.

Exchanging food products with improved fat quality reduced total- and LDL- cholesterol by 9% and 11%, respectively, and increased the serum levels of bile acid, but we did not detect an eﬀect on circulating inﬂammatory markers.

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The cholesterol-lowering effect observed seemed to be induced by a change in mRNA expression of theLDL receptor, potentially leading to increased cholesterol in the cell, increasing mRNA expression ofliver X receptor alpha (LXRA) and LXRAtarget genes in peripheral blood mononuclear cells (PBMCs). The increase in serum bile acid may reflect increased LXRA activity in liver, and thus our data confirm that changes in gene expression in PBMCs reflect changes in hepatic lipid metabolism, as has been shown by others. A long-term healthy Nordic diet modified the expression of genes involved in inflammation and lipid metabolism in PBMCs after a 2h oral glucose tolerance test (OGTT) in individuals at risk of metabolic diseases.

In conclusion, a healthy Nordic diet and an improvement of the fat quality, as part of a healthy dietary pattern, has positive eﬀects on a variety of markers of cardiovascular diseases and on the transcription of genes involved in lipid metabolism and inﬂammation.

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List of papers

Paper I

Ulven SM, Leder L, Elind E, Ottestad I, Christensen JJ, Telle-Hansen VH, Skjetne AJ, Raael E, Sheikh NA, Holck M, Torvik K, Lamglait A, Thyholt K, Byfuglien MG, Granlund L, Andersen LF and Holven KB:Exchanging few commercially regular-consumed food items with improved fat quality reduces total and LDL cholesterol– a double-blind randomized controlled trial. British Journal of Nutrition. In press.

Paper II

Leder L, Ulven SM,Ottestad I, Christensen JJ, Telle-Hansen VH, Granlund L, Andersen LF and Holven KB:Replacement of SFAs with PUFAs increases the ex- cretion of bile acids and up-regulates the mRNA expression level of the LDL receptor and LXR alpha in peripheral blood mononuclear cells: a double-blind randomized controlled trial.Submitted.

Paper III

Leder L, Kolehmainen M, Narverud I, Dahlman I, Myhrstad MCW, de Mello VD, Paananen J, Carlberg C, Schwab U, Herzig K-H, Cloetens L, Ulmius Storm M, Hukkanen J, Savolainen MJ, Rosqvist F, Hermansen K, Dragsted LO, Gun- narsdottir I, Thorsdottir I, Risérus U, Åkesson B, Thoresen M, Arner P, Pouta- nen KS, Uusitupa M, Holven KB and Ulven SM:Eﬀects of a healthy Nordic diet on gene expression changes in peripheral blood mononuclear cells in response to an oral glucose tolerance test in subjects with metabolic syndrome: a SYSDIET sub- study.Genes & Nutrition 2016 Mar 17;11:3.

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Abbreviations

AA arachidonic acid

ABCA1 ATP binding cassette subfamily A member 1

ABCG1 ATP binding cassette subfamily G member 1

ACAT acyl CoA cholesterol acyltransferase ADRB2 adrenoceptor beta 2 ADRB2 adrenoceptor beta 2 ALA α-linolenic acid

ALOX5AP arachidonate 5-lipoxygenase activating protein

apoB100 apolipoprotein B100

ARHGAP15 Rho GTPase activating protein 15

BMI body mass index

CCL C-C motif chemokine ligand CCR2 C-C motif chemokine receptor 2 CD14 CD14 molecule

CD19 CD19 molecule CD36 CD36 molecule CD40LG CD40 ligand CD72 CD72 molecule

cDNA complementary DNA CE cholesteryl ester CHD coronary heart disease ChREBP carbohydrate regulatory

element-binding protein CPT1A carnitine palmitoyltransferase

1A

CPT1B carnitine palmitoyltransferase 1B CRAT carnitine O-acetyltransferase CRP C-reactive protein

CVD cardiovascular disease CXCR2 C-X-C motif chemokine

receptor 2

CYP27A1 cytochrome P450 family 27 subfamily A member 1 Cyp7a1 cholesterol 7 alpha-hydroxylase

DGLA dihomo-c-linolenic acid DHA docosahexaenoic acid DNA deoxyribonucleic acid DPA docosapentaenoic acid E% percent of energy EPA eicosapentaenoic acid ER endoplasmatic reticulum

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ERK extracellular signal-regulated kinase

FASN fatty acid synthase FXR farnesoid X receptor GAPDH glyceraldehyde-3-phosphate

dehydrogenase

GPR G protein-coupled receptor HBEGF heparin binding EGF like

growth factor HDL-C HDL cholesterol

HETE hydroxyeicosatetraenoic acid HIF1A hypoxia inducible factor 1 alpha

subunit

HMGCR HMG-CoA reductase HODE hydroxyoctadecadienoic acid HPRT1 hypoxanthine

phosphoribosyltransferase 1 hs-CRP high-sensitive CRP

HSPA5 heat shock protein family A (Hsp70) member 5

ICAM1 intercellular adhesion molecule 1

IFN interferon

IFNG interferon gamma

IGHD immunoglobulin heavy constant delta

IKBKB inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta

IL interleukin

IL1B interleukin 1 beta

IL1RN interleukin 1 receptor antagonist

IL23A interleukin 23 subunit alpha IL23R interleukin 23 receptor IL7R interleukin 7 receptor INSIG insulin induced gene L2HGDH L-2-hydroxyglutarate

dehydrogenase LA linoleic acid LACTB lactamase beta

LDL low density lipoprotein LDL-C LDL cholesterol LDLR LDL receptor

LPAR2 lysophosphatidic acid receptor 2 LPS lipopolysaccharide

LTA4H leukotriene A4 hydrolase LTB4 leukotriene B4

LXR liver X receptor LXRA liver X receptor alpha LXRE LXR response element LY96 lymphocyte antigen 96

MAPK8 mitogen-activated protein kinase 8

MetS metabolic syndrome MIF macrophage migration

inhibitory factor MLX max-like factor X MMD monocyte to macrophage

diﬀerentiation associated MMP matrix metalloproteinase

mRNA messenger RNA

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MUFA monounsaturated fatty acid NAGPA N-acetylglucosamine-1-

phosphodiester

alpha-N-acetylglucosaminidase NFkB nuclear factor kappa B NFKBIA NFkB inhibitor alpha NK natural killer

OGTT oral glucose tolerance test OLR1 oxidized low density lipoprotein

receptor

OLTT oral lipid tolerance test PBMC peripheral blood mononuclear

cell

PCSK9 proprotein convertase subtilisin kexin type 9

PDGFA platelet derived growth factor subunit A

PDGFB platelet derived growth factor subunit B

PDK4 pyruvate dehydrogenase kinase 4 PEAR1 platelet endothelial aggregation

receptor 1 PGJ2 prostaglandin J2

PL phospholipid

PLIN2 perilipin 2

POLK DNA polymerase kappa

PPAR peroxisome proliferator activated receptor

PPARA peroxisome proliferator activated receptor alpha

PPARD peroxisome proliferator activated receptor delta

PPARG peroxisome proliferator activated receptor gamma

PPRE PPAR response element PREDIMED Primary Prevention of

Cardiovascular Disease PUFA polyunsaturated fatty acid qPCR real-time quantitative

polymerase chain reaction RCT randomized controlled trial RELA RELA proto-oncogene, NF-kB

subunit

RIN RNA integrity number RIPK1 receptor interacting

serine/threonine kinase 1 RNA ribonucleic acid

ROS reactive oxygen species RSAD2 radical S-adenosyl methionine

domain containing 2 RXR retinoid X receptor SELP selectin P

SFA saturated fatty acid

sICAM1 soluble intercellular adhesion molecule 1

SLC22A5 solute carrier family 22 member 5

SLC25A20 solute carrier family 25 member 20

SR scavenger receptor

SREBP sterol regulatory binding protein sTNFR soluble tumor necrosis factor

receptor

sVCAM1 soluble vascular cell adhesion molecule 1

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T2DM diabetes type 2

TAB2 TGF-beta activated kinase 1/MAP3K7 binding protein 2 TBP TATA box binding protein TG triglyceride

TGFB2 transforming growth factor beta 2

Th T helper

TLR Toll-like receptor TNF tumor necrosis factor

TNFRSF12A tumor necrosis factor receptor superfamily member 12A TNFSF10 tumor necrosis factor

superfamily member 10 total-C total cholesterol UCP2 uncoupling protein 2

VCAM1 vascular cell adhesion molecule 1 VEGFB vascular endothelial growth

factor B

XBP1 X-box binding protein 1

x

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Chapter 1 Introduction

1.1 Dietary patterns and cardiometabolic risk

The four major noncommunicable diseases cardiovascular diseases (CVDs), can- cer, chronic respiratory diseases and diabetes type 2 (T2DM) are responsible for 82% of noncommunicable disease deaths. CVDs are the leading cause of deaths worldwide. In 2012, 17.5 million people died from CVDs representing 31% of all global deaths [1, 2]. Lifestyle strategies are important for the reduction of noncommunicable diseases, and especially diet plays a crucial role [3, 4, 5].

The term "cardiometabolic risk" may be considered to represent the com- prehensive catalogue of factors that contribute to the development of both CVDs and T2DM [6]. According to the World Health Organization, a risk factor is "any attribute, characteristic or exposure of an individual that increases the likelihood of developing a disease or injury". In general, several factors contribute to cardiometabolic risk such as tobacco use, unhealthy diet and obesity, physical inactivity and alcohol abuse, hypertension and dyslipidemia. However, diet-related cardiometabolic risk factors are insulin resistance, obesity, dyslipidemia, hypertension and inﬂammation [7].

Nutrition research has traditionally focused on nutrients to identify the spe- ciﬁc mechanisms and health impact of diet. However, associations between single factors as nutrients as well as foods and chronic diseases can be diﬃcult to identify and to interpret. In contrast, studies of dietary patterns or whole diets examine the association between the combinations of many foods and nutrients

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CHAPTER 1. INTRODUCTION

and health. Therefore, more emphasis should be placed on the role of dietary patterns in contributing to the prevention of the major diet-related chronic diseases [8]. A very well-described dietary pattern is the Mediterranean-type of diet. As early as mid last century, Ancel Keys started to investigate the role of a diet and CVDs in the Seven Countries Study. The study has shown that populations in different countries have widely diverse incidence and mortality rates from coronary heart disease (CHD) as well as from other CVDs and overall mortality [9]. Higher rates were found in North America and Northern Europe, and lower rates in Southern Europe - i.e. the Mediterranean countries - and Japan. These differences in CHD rates were strongly associated with different levels of saturated fatty acid (SFA) consumption and average serum cholesterol levels, with lowest rates in Greece and Japan where the total fat intake was very different [10]. There is no standard definition of the term

"Mediterranean Diet", but the characteristics of healthy Mediterranean Diet are high intake of fruits, vegetables, legumes, ﬁsh, whole grains, nuts, and olive oil.

Dairy products and wine are of moderate intake, and red and processed meats as well as foods that contain high amounts of added sugar are of low intake [11, 12]. There is very strong evidence from the Primary Prevention of Car- diovascular Disease (PREDIMED) [13] and the Lyon Diet Heart Study [14]

showing that a Mediterranean-type diet is effective in primary and secondary prevention of CVDs, respectively. In observational studies, the association between the Mediterranean diet and inflammatory markers in healthy persons has been examined [15, 16, 17], and overall inverse correlations have been reported. Moreover, intervention studies have been shown that consumption of a Mediterranean diet resulted in a decline of inflammatory markers in healthy subjects [18, 19] as well as in those with metabolic syndrome (MetS) [20] or high risk of CVDs in the PREDIMED study [21]. Particularly, the results from large intervention studies strongly suggest that a Mediterranean diet can lead to reductions in chronic low-grade inflammation and improvements in endothelial function, and thereby offering cardioprotective effects [22].

The idea of a "healthy Nordic diet" conceived of the Mediterranean diet, which has long been related to improved health, but the acceptance of the Mediterranean diet in the Nordic countries is challenging, probably because of diﬀerent food preferences and eating habits in these countries [23, 24]. Thus, a

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Figure 1.1: Overview of a healthy Nordic diet and cardiometabolic health. A Healthy Nordic dietary pattern or foods present in healthy Nordic diets may improve cardiometabolic risk factors, such as blood lipids, endothelial function, inﬂammation, glucose metabolism, insulin sensitivity, blood pressure and obesity. Abbreviations: DHA, docosahexaenoic acid; EPA, eicosapentaenoic acid; LDL-C, low density lipoprotein cholesterol; MetS, metabolic syndrome; T2DM, diabetes type 2.

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healthy Nordic diet takes food culture, palatability and the environment into ac- count [25, 26]. Healthy Nordic diets are characterized by fatty ﬁsh (e.g. salmon and herring), whole grain cereals including rye, barley and oats, berries (e.g.

blueberries) and fruits (e.g. apples), vegetables, root vegetables and legumes and rapeseed oil [27, 28]. In randomized controlled intervention studies conducted in various Nordic populations it has been shown that healthy Nordic diets or foods present in healthy Nordic diets and in accordance to the Nordic Nutrition Recommendations improve key CVD risk factors (Figure 1.1), such as blood lipid profiles [29, 28, 30, 31], endothelial function [32], inflammation [32, 28, 33], glucose metabolism [34], insulin sensitivity [35, 36], and blood pressure [37, 38]. Ad libitum consumption of a healthy Nordic diet in overweight and obese subjects resulted in a weight reduction [29, 37], which may have an effect on cardiometabolic health [39].

In conclusion, improving fat quality, as part of a healthy dietary pattern such as the Mediterranean diet or the healthy Nordic diet, has shown to improve blood lipid proﬁle and inﬂammation and subsequently decreasing cardiometabolic risk.

1.2 Fatty acids

Fatty acids occur freely or as part of complex lipids such as triglycerides (TGs), phospholipids (PLs) and cholesteryl esters (CEs), and play a central role in energy metabolism, membrane formation, cell signaling, and as regulators of gene expression (see section 1.7) [40]. TGs are the main contributors to dietary fat in humans and are composed of one molecule of glycerol esteriﬁed with three fatty acid molecules. Typical dietary fatty acids have between 6 and 24 carbons and are either saturated, monounsaturated or polyunsaturated according to the number of double bonds between the carbon atoms. SFAs, monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) have none, one or two or more double bonds, respectively [8, 40] (Figure 1.2).

Fatty acids can be obtained from the diet and several can also be produced endogenously, either from glucose or protein sources by de novo lipogenesis or from other fatty acids due to the activity of desaturases (addition of double bonds) and elongases (addition of two carbon atoms) [41]. In the liver and

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Figure 1.2: Structures of some common dietary fatty acids. Fatty acids consist of a chain of carbon atoms with a carboxyl group (-COOH) at one end and a methyl group (-CH₃) at the other end. Dietary unsaturated fatty acids are classiﬁed as n-3, n-6 and n-9 specifying the ﬁrst position of the double bond by counting from the methyl end of the carbon chain.

in adipose tissue, even-numbered SFAs can be synthesized endogenously byde novolipogenesis with the main product being palmitic acid (16:0), which can further elongated and/or desaturated into palmitoleic acid (16:1n-7), stearic acid (18:0) and oleic acid (18:1n-9). The majority of dietary SFAs in a western diet is palmitic acid (16:0), stearic acid (18:0) and myristic acid (14:0) [42]. In humans, linoleic acid (LA) (18:2n-6) andα-linolenic acid (ALA) (18:3n-3) cannot be synthesized due to the lack of enzymes and therefore are called essential fatty acids which require adequate dietary intake. The main sources for these fatty acids are vegetable oils. Sunflower, rapeseed, soybean and corn oil are rich in LA. The main sources for ALA are rapeseed and soybean oil, nuts as well as flaxseed and flaxseed oil.

1.3 Dietary fat, lipids and cardiovascular risk

Dyslipidemia is a major risk factor for CVDs and is deﬁned as elevated blood total cholesterol (total-C), LDL cholesterol (LDL-C) or TGs, or low levels of HDL cholesterol (HDL-C). In Norway, the national guidelines for primary prevention of CVD recommend total-C < 5.0 mmol/L, LDL-C < 3.0 mmol/L, TGs ≤ 1.7 mmol/L and HDL-C ≥ 1.0 mmol/L (men) and ≥ 1.3

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0 0,4 0,8 1,2 1,6 2,0 2,4

-0,4 -0,8

12:0

0,00 0,01 0,02 0,03 0,04 0,05 0,06

-0,01 -0,02

14:0 16:0 18:0 18:1

n-9 18:2

n-6 mmol/L mg/dL

Figure 1.3: Eﬀects of dietary fatty acids on serum total-C (white bars), LDL-C (grey bars) and HDL-C (black bars) when 1 E% from carbohydrates in the diet is replaced by 1 E% from the fatty acid in question The values for lauric acid (12:0) are based on [48], for myristic acid (14:0) on [49], for palmitic acid (16:0) on [48, 49, 50, 51], for stearic acid (18:0) on [51, 52], and for oleic acid (18:1n-9) and LA (18:2n-6) on [46]. Abbreviations: HDL-C, high density lipoprotein cholesterol; LA, linoleic acid; LDL-C, low density lipoprotein cholesterol; total-C, total cholesterol. Adapted from [45] with permission.

mmol/L (women) [43]. Dietary fatty acid composition regulates lipoprotein metabolism, which may affect plasma lipids and thereby potentially CVD risk [44]. Several dietary SFAs such as lauric acid (12:0), myristic acid (14:0) and palmitic acid (16:0) have an total-C and LDL-C raising effect. Stearic acid (18:0) has a more neutral effect on LDL-C levels [45, 42, 41].

Human intervention studies that replace carbohydrates by SFAs, MUFAs or PUFAs have shown that SFAs increase LDL-C and HDL-C level, but do not change the total-C to HDL-C ratio compared with carbohydrates. The replacement of carbohydrates by MUFAs or PUFAs resulted in a decrease in the total-C to HDL-C ratio, a raise in total-C and LDL-C level and a slightly increase in HDL-C. The replacement of SFAs by PUFAs may lead to an even more favorable lipid proﬁle [46, 45, 47] (Figure 1.3).

A pooled analysis of 11 cohort studies found that replacing 5 percent of energy (E%) of SFAs with PUFAs was associated with a 13% lower risk of coronary events and a 26% lower risk of coronary deaths [53]. In a prospective cohort study, high circulating LA was inversely associated with total and CHD

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mortality [54]. A meta-analysis of prospective cohort studies showed that dietary LA was inversely associated with CHD risk in a dose–response manner [55]. The typical modern human diets contain more LA than ALA most likely due to the increased use of vegetable oils rich in LA [56, 41]. LA accounts for approximately 90% of the total dietary n-6 PUFA intake [57]. In 2012, a meta- analysis of seven randomized controlled trials (RCTs) confirmed this beneficial effect, with an estimated 10% reduction in CHD risk for each 5 E% increase in PUFA consumption [58]. Another meta-analysis with RCTs concluded that interventions with n-3 and n-6 PUFAs reduce the CHD risk whereas interventions with n-6 PUFAs alone tend to increase the CHD risk [59]. However, the overall evidence indicates that higher n-6 PUFA intake lowers the CHD risk [60, 57].

It has been well demonstrated in RCTs that LA lowers serum total-C and LDL-C concentrations, particularly when it replaces SFAs in the diet [46]. Also in a more recent study it has been shown that replacing 9.5E% from SFAs with MUFAs or n-6 PUFAs leads to a significant lower total-C and LDL-C and total-C to HDL-C ratio after 4 months [61]. Schwab and co-workers included 45 RCTs in a systematic review investigating the effect of different fatty acids on serum lipids and evaluated the reduction of total-C and LDL-C when SFAs are replaced bycis-MUFAs or PUFAs asconvincing [62]. These results have been incorporated into the Nordic Nutrition Recommendations from 2012, in which it is recommended to limit the intake of SFAs to <10 E%, whereas PUFAs (the sum of n-6 and n-3 PUFAs) should contribute 5-10 E%, including at least 1 E%

from n-3 PUFAs. LA and ALA should contribute at least 3 E%, including at least 0.5 E% from ALA. Likewise, because of the causal link between fat quality and total-C and LDL-C concentrations and between increased LDL-C and increased CVD risk, other countries and many authorities recommend restricting the intake of SFAs while maintaining suﬃcient intake of MUFAs and PUFAs [41].

1.4 LDL cholesterol metabolism

The low density lipoprotein (LDL) particles contain esteriﬁed cholesterol and TGs surrounded by a shell of phospholipids, free cholesterol and apolipopro-

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tein B100 (apoB100). They are the main carriers of cholesterol and can be taken up by LDL receptors (LDLRs) or scavenger receptors (SRs) [63]. The LDLR is the primary pathway for the removal of cholesterol from the circulation [64]

and LDLRs are mainly expressed in the liver, but also in smooth muscle cells, ﬁ- broblasts, and epithelial cells of the gastrointestinal tract and in blood cells such as peripheral blood mononuclear cells (PBMCs). The LDLR takes up mainly apoB100 but also apoE-containing lipoproteins and cluster in coated pits, the portals by which many receptor-bound ligands enter the cells. The pits invagi- nate to form coated endocytic vesicles and become endosomes. Within the endosomes, the LDL particle separates from the receptor and therefore allows the receptor to be recycled. Then, the endosome merges with the lysosome, where CEs are hydrolyzed [65]. The lysosomes release unesteriﬁed cholesterol which mediates cholesterol homeostasis in three ways: Inhibition of HMG-CoA reductase (HMGCR); increase of acyl CoA cholesterol acyltransferase (ACAT) activity; and decrease of the synthesis of LDLR [66]. Thus, the activity of the LDLR and HMGCR is homeostatically regulated and the cells obtain cholesterol either from exogenous lipoproteins or from endogenous synthesis (Figure 1.4).

LDL particles can also be taken up via SRs, which are mainly expressed by macrophages. The SR-mediated uptake predominately occurs after LDL particles have been modiﬁed, particularly by oxidation [63, 68]. The accumulation of oxidized LDL in macrophages results in their transformation into foam cells, which are involved in the pathogenesis of atherosclerosis (see section 1.5). The smallest, most dense LDLs are considered most vulnerable to oxidation and thus most prone to be taken up via the SRs. Importantly, in contrast with the LDLR, the uptake of LDL particles with the SRs is not rate-limited, as it is proportional to the LDL-C concentration in circulation [66].

A milestone in the cholesterol-lowering therapy is the discovery of statins which inhibit the HMGCR and therefore decrease the endogenous synthesis of cholesterol. In response, the sterol regulatory binding protein (SREBP) cleavage is increased and the nuclear form of the SREBP2 activates the expression of LDLRandHMGCRand other genes important for cholesterol uptake and synthesis. However, as statins inhibit HMGCR (synthesis) but not LDLR (uptake), the increased LDLRs lower LDL-C in plasma. A new cholesterol-lowering strat-

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SREBP-2

SRE

nucleus statin

HMGCR LDLR LDL LDLR LDLR

PCSK9

endosome degradation

endosome recycling

lysosome

Cellular cholesterol

Cellular cholesterol SREBP SCAP

INSIG

intracellular plasma

2 1

Figure 1.4: Mechanisms of LDLR regulation. (1) Cellular cholesterol low: Proteolytic cleavage of SREBP2 is increased. The cleaved SREBP2 enters the nucleus to activate genes controlling cholesterol synthesis (including HMGCR) and uptake (LDLR). (2) Cellular cholesterol high:

Proteolytic cleavage of SREBP2 is decreased, leading to decreased nuclear SREBP2 and decreased activation of target genes. The decrease in LDLR leads to an increase LDL in plasma [67]. Ab- breviations: HMGCR, HMG-CoA reductase; INSIG, insulin induced gene; LDL, low density lipoprotein; LDLR, low density lipoprotein receptor; PCSK9, proprotein convertase subtilisin kexin type 9; SCAP, SREBP cleavage activating protein; SREBP, sterol regulatory binding protein.

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egy is the therapy with proprotein convertase subtilisin kexin type 9 (PCSK9) inhibitors. PCSK9 is a protein secreted by hepatocytes that binds to an extracellular pocket of the LDLR and targets it for lysosomal degradation in the cells, eﬀectively increasing plasma LDL-C. Therefore, antibodies that inhibit PCSK9 lead to reduced lysosomal degradation of LDLRs, increased expression on the membrane surface and reduced LDL-C concentration in plasma [69, 70].

1.5 Atherosclerosis

1.5.1 Atherosclerotic process

Atherosclerosis is a chronic inflammatory disease of the blood vessels. The initial step of the atherosclerotic process is the subendothelial retention of circulating LDL particles and thus trapping of LDL particles in the intima of the vessel wall [71]. In the intima, LDL particles are prone to oxidation forming oxidized LDL. Moreover, endothelial cells may be activated by components of oxidized LDL leading to the expression of cell adhesion molecules, such as E-selectin and vascular cell adhesion molecule 1 (VCAM1) on the endothelial surface of the artery [72]. Cell adhesion molecules induce arresting, rolling and adherence of monocytes, dentritic cells and T cells onto the endothelial cell surface resulting in migration of these cells into the intima [73]. Here, monocytes respond to macrophage-colony stimulating factors and differentiate into macrophages [74]. Macrophages express SRs on the surface which mediate the uptake of oxidized LDL resulting in foam cell formation (Figure 1.5). The accumulation of foam cells in the intima constitutes the nascent atherosclerotic lesion referred to as fatty streaks [75]. Moreover, several inflammatory mediators are involved in the formation of the atherosclerotic plaque [76, 77]. In this process, immune cells such as T cells, macrophages as well as foam cells express, release and respond to several growth factors, matrix metalloproteinases (MMPs), chemokines and cytokines. In particular, macrophages release cytokines which may increase the endothelial cell expression of cell adhesion molecules leading to further migration of immune cells. T cells face antigens such as oxidized LDL in the intima and may polarize into T helper (Th) cells. Th1 cells secrete primarily pro-inflammatory cytokines (e.g. tumor necrosis factor (TNF)α, in-

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Figure 1.5: Development of atherosclerotic lesions. Initial step is the sub-endothelial retention of LDL particles. Thus, LDL particles are trapped in the intima of the vessel wall, where they are prone to oxidation forming oxLDL. Moreover, endothelial cells may be activated by oxLDL leading to the expression of CAMs [72]. CAMs induce arresting, rolling and adherence of immune cells onto the endothelial cell surface resulting in migration of these cells into the intima [73]. Here, monocytes transform into macrophages [74] and express SRs on the surface mediating the uptake of oxLDL. Cholesterol accumulation eventually turns these macrophages into foam cells that are characteristic of the atherosclerotic lesion (fatty streaks). Macrophages release cytokines that may increase the expression of CAMs on the endothelial cells, which supports migration of immune cells in the intima. T cells face antigens in the intima and may polarize into Th1 and Th2 cells [72]. Atherosclerosis is driven by the Th1 cell response. Ab- breviations: CAM, cell adhesion molecule; DC, dentritic cell; IFN, interferon; IL, interleukin;

LDL, low density lipoprotein; MMP, matrix metalloproteinase; oxLDL, oxidized LDL; ROS, reactive oxygen species; SR, scavenger receptor; Th, T helper; TNF, tumor necrosis factor.

Adapted from [72] with permission.

terleukin (IL)1 and IL6) and Th2 cells anti-inflammatory cytokines (e.g. IL4 and IL10) [74, 78, 75] (Figure 1.5). Thus, a chronic inflammation arises on top of a lipid accumulation. The lesion progresses as the core grows by accumulation of macrophages, endothelial cells and smooth muscle cells. These advanced plaque filling can lead to fibrous cap thinning, plaque rupture or erosion, and acute thrombotic vascular events such as myocardial infarction or stroke [71].

In summary, LDL particles and other apoB-containing lipoproteins can enter the subendothelium and are tightly linked to the initiation of the atherosclerotic process along with endothelial cell damage and inﬂammation [79, 80].

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1.5.2 Inﬂammation

Inflammation is the immediate response of the body to infection or cellular injury. Acute inflammatory reactions are usually self-limiting and resolve rapidly due to negative feedback mechanisms such as secretion of anti-inflammatory cytokines, inhibition of pro-inflammatory signaling cascades, loss of receptors for inflammatory mediators and activation of regulatory cells. Thus, regulated inflammatory responses are essential to remain healthy and maintain homeostasis.

However, inﬂammatory responses that fail to regulate themselves can become chronic and contribute to the maintenance and the progression of disease [78].

The characteristics of chronic inflammatory responses are loss of barrier function, responsiveness to a normally benign stimulus and increased production of oxidants, cytokines, chemokines, eicosanoids and MMPs. Moreover, inflammatory cells massively infiltrate compartments in which they are found only in low numbers in healthy conditions. Thus, chronic low-grade inflammation is characterized by increased concentrations of inflammatory markers in the systemic circulation and is a well recognized component of many diseases [81].

1.6 Dietary fat, inﬂammation and cardiovascular risk

In a healthy dietary pattern, intake of vegetable oils with LA and ALA is of high importance. In subgroup analysis of the Physicians’ Health Study and the Nurses’ Health Study, dietary intake of LA was not associated with alterations of C-reactive protein (CRP), IL6, soluble tumor necrosis factor receptor (sTNFR)1, or sTNFR2 concentrations [82]. Moreover, the LA concentration in blood lipids was not associated [83] or even inverse associated with CRP or IL6 concentration [84, 85, 86, 87]. In 2012, a systematic review analysis of RCTs concluded that there is no evidence for increased inﬂammation due to dietary LA intake in healthy humans [88]. Increasing the amount of ALA intake, either through the diet or as supplements, leads to proportional conversion to eicosapentaenoic acid (EPA) and docosapentaenoic acid (DPA), but not docosahexaenoic acid (DHA) [89, 90]. The conversion of ALA to DHA is limited and in general human studies show that the body conversion is below

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5% [90]. Thus, an important aspect of the anti-inﬂammatory action of ALA is the reduced production of eicosanoids from arachidonic acid (AA) and the increased production of EPA and DPA [41]. In controlled clinical trials, increasing the intake of ALA has been shown to decrease serum concentrations of CRP, which is strongly associated with reduced risk of cardiovascular events, such as myocardial infarction and stroke [91, 92, 93].

Eicosanoids are key mediators and regulators of inflammation and are formed from 20-carbon PUFAs. Inflammatory cells usually contain a high concentration of AA and therefore AA is typically the substrate for eicosanoid synthesis [94]. Eicosanoids produced from AA play a role in inflammation [95, 96, 81].

Likewise, EPA is a precursor for eicosanoids but the inﬂammatory properties of these eicosanoids are diﬀerent compared to the AA-derived once [97].

In vitro and animal studies suggest a pro-inflammatory role for SFAs, in particular of lauric acid (12:0) and palmitic acid (16:0) [41]. In a human observational study, the relationship between SFAs exposure and circulating inflammatory markers has been investigated reporting a positive association for CRP and IL6 [98]. Moreover, the ratios of SFAs to n-6 PUFAs or SFAs to n-3 PUFAs were positively associated with IL6 and CRP concentrations in overweight subjects [99]. In a human intervention study, SFA intake increased levels of CRP, fibrinogen, IL6, and soluble E-selectin compared with a diet enriched in oleic acid (18:1n-9) [100]. Thus, dietary SFAs (12:0- 16:0) may increase inflammation [41].

1.7 Fatty acids and gene regulation

Fatty acids are involved in gene regulation. This is achieved by direct fatty acid binding to speciﬁc transcription factors, or by indirect mechanisms where fatty acids regulate signaling pathways controlling the expression of transcription factors (Figure 1.6) [101, 102, 103]. The latter can include phosphorylation, ubiquitination, or proteolytic cleavage of transcription factors. In particular, unsaturated fatty acids modulate gene transcription by regulating the activity of numerous transcription factors, such as the nuclear receptors. Nuclear receptors are a large subfamily within the group of transcription factors, with 48 mem- bers [104]. The peroxisome proliferator activated receptors (PPARs), the liver

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X receptors (LXRs) and the farnesoid X receptors (FXRs) are nuclear receptors and function as ligand-activated transcription factors [105].

Fatty acid regulation of the PPAR family has been extensively studied. PPARs bind mainly unsaturated fatty acids, such as LA, EPA and DHA, but may be also regulated by enzymatically-modified fatty acids, such as eicosanoids. The latter include for example leukotriene B4 (LTB4), prostaglandin J2 (PGJ2), hydroxyoctadecadienoic acids (HODEs) and hydroxyeicosatetraenoic acids (HETEs) [107, 108, 106]. Three different PPAR isotypes have been identified: PPARα, PPARβ/δ and PPARγ. PPARα is predominately expressed in the liver, heart and brown adipose tissue. PPARδ (called PPARβ in rodents) is ubiquitously expressed and has a most important function in skeletal muscle, liver and heart, whereas PPARγis highly expressed in white adipose tissue. PPARs heterodimer- ize with the retinoid X receptor (RXR), which is another nuclear receptor. Lig- ands, such as fatty acids and retinoic acid, enter the cell and bind PPARs and RXR, respectively. The PPAR-RXR heterodimer binds to a specific genomic binding site, PPAR response element (PPRE), which is present in or near the promotor of the target genes. The ligand-activated nuclear receptors affect nuclear co-factors and the recruitment of additional proteins involved in gene transcription, such as ribonucleic acid (RNA) polymerase II [109, 110].

PUFAs can also suppress the nuclear abundance of several transcription factors, such as SREBP1, carbohydrate regulatory element-binding protein (ChREBP), max-like factor X (MLX) and nuclear factor kappa B (NFkB).

The fatty acid regulation of these transcription factors, however, may not in- volve direct fatty acid binding to the protein, but rather indirectly [111, 112, 113]. SREBPs are transcription factors and important regulators of cholesterol and fatty acid metabolism. They are encoded by the two genes, SREBP1 and SREBP2, resulting in the three proteins SREBP1a, SREBP1c and SREBP2.

UBXD8, an endoplasmatic reticulum (ER)–bound protein, was identiﬁed as a sensor for the unsaturated fatty acids. UBXD8 promotes the degradation of insulin induced gene (INSIG)1, which in general holds the SCAP-SREBP complex back in the ER and prevents its movement to the Golgi for cleavage and maturation [114]. Thus, PUFAs inhibit the activity of UBXD8 with the result that the SCAP-SREBP complex stays in the ER. Accordingly, the maturation of precursor membrane-bound SREBP1 to the mature SREBP1 is inhibited and

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FA

SFA FA GPR40-43

GPR120 TLR4

inflammatory gene regulation

gene expression ?

Fatty acid & cholesterol

synthesis Glycolysis Fatty acid catabolism

MLX ChREBP

bHLH RXR

PPAR

MLX ChREBP

PUFA

LXR?

bHLH

precursor SREBP-1

PUFA

mature SREBP-1

Figure 1.6: Mechanisms of gene regulation by FAs. 1. In hepatocytes, PUFAs may bind and in- activate UBXD8, and thereby inhibit proteolytic processing of SREBP1 leading to an inhibition of fatty acid and cholesterol synthesis. 2. PUFAs reduce expression of L-type pyruvate kinase (glycolysis) in the liver, most likely by inhibiting nuclear translocation of MAX-like protein X (MLX)–carbohydrate responsive element binding protein. 3. Activation of PPARαby PUFAs in the liver may lead to an increase of FA catabolism. In particular, PUFAs act as ligands for PPARs. DHA has been observed as ligand for RXR. GPR40–43 and GPR120 are membrane receptors for various types of fatty acids, which are expressed by enterocytes and other cell types. It is uncertain to what extent the activation of GPRs by fatty acids directly influences gene transcription. TLR4 is expressed by macrophages and other cell types. SFAs may promote inflammation by directly activating TLR4. The role of LXRs in mediating effects of PUFAs is controversial. Abbreviations: bHLH, basic helix-loop-helix; ChREBP, carbohydrate-responsive element binding protein; DHA, docosahexaenoic acid; FA, fatty acid; GPR, G protein-coupled receptor; INSIG, insulin induced gene; LXR, liver X receptor; PPARα, peroxisome proliferator activated receptor alpha; PUFA, polyunsaturated fatty acid; RXR, retinoid X receptor; SCAP, SREBP cleavage activating protein; SFA, saturated fatty acid; SREBP, sterol regulatory binding protein; TLR, Toll-like receptor. Adapted from [106] with permission.

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fatty acid synthesis decreased [106].

Fatty acids may also regulate gene expression indirectly by binding to membrane receptors such as Toll-like receptors (TLRs) and G protein-coupled receptors (GPRs) [106]. TLR4 is one of several TLRs responsible for activating the innate immune system. SFAs have been shown to active the TLR4 leading to activation of the NFkB signaling pathway [115]. In contrast, n-3 PUFAs have been shown to stimulate GPR120 in macrophages and adipocytes, and thereby mediate an anti-inﬂammatory eﬀect via inhibition of NFkB signaling [116, 117].

1.8 Peripheral blood mononuclear cells

To understand molecular mechanisms of food components and their effect on health, the investigation of metabolic relevant tissues such as liver, adipose tissue and skeletal muscle is of main interest. However, the availability of these tissues obtained from healthy individuals is very limited and in particular liver samples are almost impossible to access from healthy humans. Thus, easy ac- cessible surrogate tissues, as for example PBMCs are of major importance to be further investigated and may be used in human intervention studies. PBMCs have been suggested as a surrogate tissue reflecting the hepatic regulation of the cholesterol metabolism as well as metabolic and immune responses of hepatocytes and adipocytes [118]. In addition, PBMCs circulate in the body and are exposed to nutrients and bioactive food components in the blood and in metabolic tissues, and may therefore to a certain extent reflect systemic health [119].

PBMCs belong to the innate and adaptive immune system and include lymphocytes and monocytes. Usually, 95% of the PBMCs are lymphocytes, of which 75% are T cells, 15% B cells and 10% natural killer (NK) cells, and 5%

are monocytes (Figure 1.7). In humans, the occurrence of PBMCs varies across individuals, and with age and infections and disease states [120].

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Figure 1.7: Composition of PBMCs. PBMCs consist to about 95% of lymphcytes and to about 5% of monocytes. Of the lymphocytes, 75% are T cells, 15% B cells and 10% NK cells.

Abbreviations: NK cell, natural killer cell;

PBMC, peripheral blood mononuclear cell.

Lymphocytes can be divided into T lymphocytes, which originate in the thymus, and B lymphocytes, which are generated in the bone mar- row. Whereas, T lymphocytes are involved in cell-mediated immunity by releasing cytokines and interacting with pathogens directly. B lymphocytes are involved in humoral immunity by releasing antigen-speciﬁc antibodies. T lymphoctes can be cat- egorized further into Th cells, also known as CD4+ lymphocytes, and cytotoxic T cells, also known as CD8+ lymphocytes. Th cells release

cytokines, which direct the immune response, and cytotoxic T cells release tox- ics, which induce death of pathogen-infected cells [121]. Monocytes are cells of the innate immune system and provide the first line of defense against bacterial infections. They migrate from the blood stream to other tissues and differentiate into tissue-specific macrophages [122].

1.9 Use of challenge tests in interventions

In general, a healthy organism has an enormous capacity to maintain homeostasis. Challenge tests can be performed to temporarily disturb homeostasis in the body and to investigate how ﬂexible an organism can respond to stress, e.g.

nutritional stress. For this purpose glucose, lipid or protein tolerance tests, a mixture of these macronutrients or whole diet challenges are applied. For example, the oral lipid tolerance test (OLTT) can be used to detect impairments in lipid handling, while the oral glucose tolerance test (OGTT) is used for ana- lyzing glucose metabolism and hence mainly used for T2DM diagnosis [123].

The OGTT is the most standardized challenge test and widely used in both research and clinical settings. The aim of an OGTT is to investigate the func- tional ﬂexibility of the glucose metabolism system. In a healthy subject, plasma

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Figure 1.8: Challenge test during an intervention. On the left: a single marker-response proﬁle such as glucose response during homeostasis and after the challenge test (e.g. OGTT). The OGTT evokes a response in glucose concentration which returns to homeostatic levels after a period of time. On the right: single-marker response during homeostasis and after the challenge test before and after the intervention should ideally lead to an improved challenge response in terms of amplitude and duration. Abbreviations: OGTT, oral glucose tolerance test. Reprint with permission [123].

glucose concentrations return to the basal level (homeostasis) within 2h after a standardized dose of glucose (75g) given after an overnight fast, which is called optimal ﬂexibility. In subjects with impaired glucose tolerance, plasma glucose levels are elevated for a longer period, which is called impaired ﬂexibility [124].

After an OGTT, a modest increase in leukocyte numbers leading to a modest increase in inflammatory responses has been found [125]. Additionally, due to decrease in TG levels and blood pressure after glucose intake, oxidative stress may decrease [126, 123]. The transition from fasting to feeding is associated with changes in circulating metabolite concentration in order to achieve glucose homeostasis. Hence, in healthy subjects the phenotypic flexibility mechanisms that follow OGTTs prevent the onset of strong inflammatory reactions [127]. On the other hand, high fat challenge tests are known to induce a temporary postprandial pro-inflammatory and atherogenic response [119, 22], which has been shown as postprandial increase in plasma inflammatory markers and temporary adverse effects on vascular function [128, 129, 130]. Therefore, inflammation is considered a normal physiological response to a high-fat challenge test [78].

Postprandial effects of different fatty acids on inflammatory PBMC gene ex- 18

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pression have been examined in some human studies [119]. In whole genome analysis, postprandial inflammatory gene expression was significantly up- regulated after n-3 PUFA intake [131] and several gene sets related to inflammation were more pronouncedly up-regulated after MUFA intake relative to SFA intake [132]. Also, target gene approaches were used to examine inflammation- related responses of n-3 PUFA and/or MUFA intake [133, 134, 135]. Other studies reported modest inflammatory responses only after a mixed challenge of glucose and fat, not with a fat challenge alone [125]. This effect occurs pos- sibly because unsaturated fatty acids are more prone to oxidation than SFAs which might lead to more oxidative stress and consequently to inflammation.

However, another explanation could be that palmitic acid induces less stress to PBMCs because it is more regularly consumed and therefore the change in expression of inflammatory genes are lower compared to high doses of oleic acid or DHA [133]. Nevertheless, it seems like that repeated moderate exposure to stress-inducing fatty acids such as MUFAs or n-3 PUFAs will activate the transcriptional response, which leads to an increased flexibility of the cell. An improvement in cellular flexibility may lead to positive long-term health effects [132]. Moreover, a challenge test can be used to assess effects of diet. A dietary intervention should ideally lead to an improved challenge response with respect to duration and magnitude compared to a control group (Figure 1.8). Thus, findings about metabolic flexibility of an organism may be related to impaired health and the development of future diseases. By using a stress test, small differences in health status between subjects may be detected which cannot be measured in fasting conditions. Only few studies have applied a nutritional challenge test in the context of a dietary intervention study to investigate circulating markers [136, 137] or gene expression level of different targets [138, 139]. More- over, it has been suggested that analyses performed in the postprandial state may increase the sensitivity to detect alterations of gene expression in PBMCs [119].

In summary, an OGTT provides a powerful tool to detect subtle changes in health status. This might be important to detect persons with a high risk of developing a disease but also to detect eﬀects of nutrition-related prevention strategies [140].

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Chapter 2 Aims

The aim of this project has been to study the role of healthy dietary patterns on lipids and inﬂammation with special focus on fat quality in populations with cardiometabolic risk.

The speciﬁc aims have been to:

• study the intake of commercially available food products, in which SFAs have been replaced by mostly n-6 PUFAs, on lipid proﬁle and inﬂamma- tory markers in individuals with hypercholesterolemia (paper I)

• study the molecular mechanisms of the cholesterol-lowering eﬀect of replacing SFAs with mostly n-6 PUFAs in humans using PBMC gene expression as a model system (paper II)

• study the eﬀect of a healthy Nordic diet on PBMC gene expression after an OGTT in individuals with MetS (paper III)

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Chapter 3 Subjects and methods

3.1 The NoMa study

The NoMa ("Norsk Mat" - Norwegian Food) study is an eight-week double- blinded randomized controlled parallel study conducted at the University of Oslo and the Oslo and Akershus University College of Applied Sciences between 2012 and 2014. The experimental diet group consumed heart-friendly food products of the series "Vita hjertego" in which part of saturated fat is replaced with polyunsaturated fat (rapeseed and sunﬂower oil). These products also have a reduced content of sodium and a high content of dietary ﬁber.

The products are commercially available and produced by Mills DA. The control diet group consumed products among the most sold products of each food group in the 2011. The amount of food was based on a national food survey (Norkost 3). All participants included in the study had to eat the food products of the control diet group for two weeks before the start of the intervention (run- in period). At baseline, the participants (n=115) were randomized to either the control diet group (n=59) or the experimental diet group (n=56) (Figure 3.1).

The study protocol was approved by the Regional Ethics Committee for Med- ical Research in South East Norway and all participants provided their written informed consent.

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CHAPTER 3. SUBJECTS AND METHODS

1-4 weeks

Control group 2 weeks with

control diet

Screening Run-in

Experimental group Baseline

4-day food diaries:

before week 2 and 8 End (8 weeks) Randomization

Figure 3.1: Study design of the NoMa study. In the run-in period, all participants consumed the food products of the control diet group for two weeks before they were randomized to either the experimental diet group or the control diet group at baseline. The study duration was eight weeks.

3.2 The SYSDIET study

The SYSDIET study is a randomized controlled multi-center study performed in six study centers in the Nordic countries [Kuopio and Oulu (Finland), Lund and Uppsala (Sweden), Aarhus (Denmark) and Reykjavik (Iceland)] for 18 or 24 weeks in the period of October 2009 until November 2010. For the gene expression analysis, PBMCs from the study centers Kuopio, Oulu and Lund were used. After a screening visit the participants followed their habitual diet for four weeks. During this period, the consumption of foods with plant sterols and fish oil supplements was not allowed [28]. At baseline, the participants (n=213) were randomized to either the control diet group or the healthy Nordic diet group within each center (Figure 3.2). The key products were provided to the participants in both groups. The participants in the healthy Nordic diet group received whole-grain products (for example various kinds of bread), berry products as frozen berries (e.g. strawberries, black currants, bilberries) and dried berry powder as well as dietary fats including rapeseed oil- and vegetable oil- based spreads. Fish was either directly provided or the expenses for the fish purchase were covered, because fish is an extremely perishable food. The participants in the control diet group received low-fiber cereal products (for example bread with a fiber content <6 g per 100 g) and dairy fat-based spread (for example butter) [28]. The study protocol was approved by the local Ethical

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Figure 3.2: Study design of the SYSDIET study. At baseline, participants were randomized to the healthy Nordic diet group or the control diet group. The study duration was 18 to 24 weeks.

PBMCs were collected fasting and after the 2h OGTT at baseline and at the end of the study.

Abbreviations: OGTT, oral glucose tolerance test; PBMC, peripheral blood mononuclear cell.

Committees of all the participating centers and all participants provided their written informed consent.

Table 3.1 gives an overview of study populations and study designs.

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Table3.1:Overviewofthestudypopulationsandthestudydesigns Study nameDesignPopulationGroupsDurationAimPaper NoMaRandomized controlled double- blinded study Healthysubjectswith moderate hypercholesterolemia

PaperI: experimentaldiet group(n=47)and controldietgroup (n=52),PaperII: experimentaldiet group(n=45)and controldietgroup (n=50) 8weeksToinvestigatetheeﬀect ofreplacingSFAswith PUFAsontotal cholesterolandLDL-C andgeneexpressionin PBMCs

Iand II PaperI:n=99, PaperII:n=95 SYSDIETRandomized controlled multicenter study

SubjectswithMetSor featuresofMetSHealthyNordic dietgroup(n=49) andcontroldiet group(n=40) 18or24 weeksToinvestigatetheeﬀect ofahealthyNordicdiet ongeneexpressionin PBMCsafter2hOGTT

III n=89 Abbreviations:LDL-C,lowdensitylipoproteincholesterol;MetS,metabolicsyndrome;OGTT,oralglucosetolerancetest;PBMCs, peripheralbloodmononuclearcells;PUFAs,polyunsaturatedfattyacids;SFAs,saturatedfattyacids.

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3.3 Selection of candidate genes

The selection of inﬂammatory and lipid metabolism-related target genes was primarily based on a literature search. First, we searched for longer-term dietary intervention studies with focus on fatty acids and polyphenols studying gene expression in PBMCs. However, studies aiming for weight loss or not having a control group were not included. Secondly, we searched for studies investigating gene expression in PBMCs after a nutritional challenge test. An overview of the studies considered to select the target genes is presented in Table 3.2.

TaqMan Array Micro Fluidic Cards (Applied Biosystems) were used for real- time quantitative polymerase chain reaction (qPCR) analysis as they can be customized with primers to detect the target gene of choice. For each card, we have chosen a set-up of 48 target genes to be analyzed in eight samples.

Healthy dietary patterns, lipids and inﬂammation in human randomized controlled trials