Cardiometabolic risk factors in 12-year-old children : the role of insulin sensitivity, low-grade inflammation, birth weight and maternal preeclampsia

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DISSERTATIONS | SATU SEPPÄ | CARDIOMETABOLIC RISK FACTORS IN 12-YEAR-OLD CHILDREN... | No 568

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ISBN 978-952-61-3406-2

Dissertations in Health Sciences

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THE UNIVERSITY OF EASTERN FINLAND

SATU SEPPÄ

CARDIOMETABOLIC RISK FACTORS IN 12-YEAR-OLD CHILDREN: THE ROLE OF INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND MATERNAL PRE-ECLAMPSIA

Several cytokines derived from adipose tissue, muscle, liver and bone have been considered potential biomarkers for reduced

insulin sensitivity, low-grade inflammation and cardiovascular disease risk in adults.

This thesis addresses cytokines associated with unfavourable cardiometabolic features

in 12-year-old children. Because low birth weight and exposure to maternal pre- eclampsia predispose to later metabolic and cardiovascular disturbances, their influence on

these markers was evaluated.

SATU SEPPÄ

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CARDIOMETABOLIC RISK FACTORS IN 12- YEAR-OLD CHILDREN: THE ROLE OF

INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND

MATERNAL PRE-ECLAMPSIA

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Satu Seppä

CARDIOMETABOLIC RISK FACTORS IN 12- YEAR-OLD CHILDREN: THE ROLE OF

INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND

MATERNAL PRE-ECLAMPSIA

To be presented by permission of the Faculty of Health Sciences, University of Eastern Finland for public examination in Auditorium MS 300, Kuopio

on Friday August 7^th, 2020, at 12 noon Publications of the University of Eastern Finland

Dissertations in Health Sciences No 568

Department of Paediatrics, Kuopio University Hospital and

Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland

Kuopio 2020

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Series Editors

Professor Tomi Laitinen, M.D., Ph.D.

Institute of Clinical Medicine, Clinical Physiology and Nuclear Medicine Faculty of Health Sciences

Associate professor (Tenure Track) Tarja Kvist, Ph.D.

Department of Nursing Science Faculty of Health Sciences Professor Ville Leinonen, M.D., Ph.D.

Institute of Clinical Medicine, Neurosurgery Faculty of Health Sciences

Professor Tarja Malm, Ph.D.

A.I. Virtanen Institute for Molecular Sciences Faculty of Health Sciences

Lecturer Veli-Pekka Ranta, Ph.D.

School of Pharmacy Faculty of Health Sciences

Distributor:

University of Eastern Finland Kuopio Campus Library

P.O.Box 1627 FI-70211 Kuopio, Finland

www.uef.fi/kirjasto

Grano, 2020

ISBN: 978-952-61-3406-2 (print/nid.) ISBN: 978-952-61-3407-9 (PDF)

ISSNL: 1798-5706 ISSN: 1798-5706 ISSN: 1798-5714 (PDF)

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Author’s address: Department of Paediatrics

University of Eastern Finland and Kuopio University Hospital

KUOPIO FINLAND

Doctoral programme: Doctoral Programme of Clinical Research

Supervisors: Professor emeritus Raimo Voutilainen, M.D., Ph.D.

Department of Paediatrics

University of Eastern Finland and Kuopio University Hospital

KUOPIO FINLAND

Sirpa Tenhola, M.D., Ph.D.

Department of Paediatrics Kymenlaakso Central Hospital KOTKA

FINLAND

Reviewers: Docent Päivi Tapanainen, M.D., Ph.D.

Department of Children and Adolescents

Oulu University Hospital and PEDEGO Research Unit, Medical Reseach Centre

University of Oulu OULU

FINLAND

Professor emeritus Sture Andersson, M.D., Ph.D.

Pediatric Research Center, Children’s Hospital

University of Helsinki and Helsinki University Hospital HELSINKI

FINLAND

Opponent: Professor Harri Niinikoski, M.D., Ph.D.

Institute of Biomedicine University of Turku TURKU

FINLAND

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Seppä, Satu

Cardiometabolic risk factors in 12-year-old children: the role of insulin sensitivity, low-grade inflammation, birth weight and maternal pre-eclampsia

Kuopio: University of Eastern Finland

Publications of the University of Eastern Finland Dissertations in Health Sciences 568. 2020, 136 p.

ISBN: 978-952-61-3406-2 (print) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3407-9 (PDF) ISSN: 1798-5714 (PDF)

ABSTRACT

Cardiovascular disease (CVD) is a leading cause for death in adults. Its metabolic programming begins prenatally or in early childhood, and the cardiometabolic risk tracks to adulthood. Insulin resistance (IR) is the reverse of insulin sensitivity (IS) and is a common metabolic alteration related to cardiovascular disturbances. Adipose tissue has been proposed to have a role in the pathogenesis of IR by secreting adipocytokines that affect insulin action. Metabolic stress in the white adipose tissue leads to dysregulated adipocytokine synthesis and secretion, which may contribute to obesity-associated metabolic, inflammatory, and cardiovascular comorbidities. In addition to adipocytokines, also certain cytokines derived from muscle, liver and bone have been related to energy homeostasis, glucose metabolism, adipogenesis, inflammation and endothelial function.

Unfavourable conditions in utero increase later CVD risk. Intrauterine growth restriction and maternal pre-eclampsia have been associated with an increased risk for metabolic and CVDs in the offspring.

In this thesis we evaluated whether biochemical markers that have recently been linked to IS and low-grade inflammation associate with cardiometabolic characteristics in 12-year-old children. Furthermore, we investigated whether these measures are altered with regard to low birth weight or exposure to maternal pre- eclampsia. The cohort of 192 children [70 small for gestational age (SGA), 78 appropriate for gestational age and 44 from pre-eclamptic pregnancies (PRE)] born in 1984-1986 were studied at Kuopio University Hospital at the age of 12 years. When evaluating only the effect of pre-eclampsia on IR, we examined 60 PRE children matched with 60 controls born from normotensive pregnancies in the same cohort.

Blood glucose, serum insulin, Quantitative Insulin Sensitivity Check Index, serum lipids, interleukin-1 receptor antagonist (IL-1Ra), high-molecular-weight (HMW) adiponectin, fibroblast growth factor 21 (FGF-21), irisin, total osteocalcin (tOC), high sensitivity C-reactive protein (hs-CRP), glucocorticoids and blood pressure (BP) were determined.

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At 12 years of age, serum IL-1Ra associated with lower IS, higher hs-CRP, measures of body weight and a less favourable lipid profile. Serum irisin associated negatively with IS markers independently of body mass index (BMI). Serum HMW adiponectin was a positive predictor for high-density lipoprotein cholesterol, whereas its associations with IS markers were dependent on BMI. FGF-21 and tOC had no association with IS. Instead, higher tOC levels were associated with a lower free cortisol index, indicating glucocorticoid-dependent regulation of serum tOC already within physiological cortisol concentrations.

In this study, being born SGA contributed independently to lower IS and higher 24-hour ambulatory BP values. Exposure to maternal pre-eclampsia associated independently with higher ambulatory systolic BP, but not with decreased IS. Serum IL-1Ra, irisin, FGF-21, HMW adiponectin and tOC were similar with regard to birth weight and exposure to maternal pre-eclampsia. The PRE children with the lowest IS had higher systolic BP and triglyceride concentrations than PRE children with higher IS. Finally, the PRE children had higher serum cortisol/cortisone ratio than those without exposure to maternal pre-eclampsia, which may reflect altered activation of the hypothalamo-pituitary-adrenal axis or peripheral cortisol metabolism.

We conclude that in 12-year-old normoglycaemic children, serum IL-1Ra and irisin associated with unfavourable metabolic features, although the associations were rather weak. The association between HMW adiponectin and IS was dependent on adiposity. FGF-21 and tOC were poor predictors of IS. Being born SGA or exposure to maternal pre-eclampsia associated with unfavourable cardiometabolic characteristics. However, increased cardiometabolic risk may remain undetectable by the new IS and low-grade inflammation markers used in this study.

National Library of Medicine Classification: QU 120, WB 286, WD 210, WK 880, WQ 215, WS 130, WS 290, WS 440

Keywords/Medical Subject Headings: Adipokines; Adiponectin; Adiposity; Biomarkers; Birth Weight; Blood Pressure; Body Mass Index; Cardiovascular Diseases; Child; Cohort Studies;

Glucocorticoids; Infant, Small for Gestational Age; Inflammation; Insulin Resistance;

Interleukin 1 Receptor Antagonist Protein; Metabolism; Osteocalcin; Pediatric Obesity; Pre- Eclampsia; Risk Factors

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Seppä, Satu

Kardiometaboliset riskitekijät 12-vuotiailla lapsilla: insuliiniherkkyyden, matala- asteisen tulehduksen, syntymäpainon ja äidin pre-eklampsian merkitys

Kuopio: Itä-Suomen yliopisto

Publications of the University of Eastern Finland Dissertations in Health Sciences 568. 2020, 136 s.

ISBN: 978-952-61-3406-2 (nid.) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3407-9 (PDF) ISSN: 1798-5714 (PDF)

TIIVISTELMÄ

Sydän- ja verisuonitaudit ovat aikuisiän tavallisin kuolinsyy. Niihin liittyvä metabolinen ohjelmoituminen alkaa jo ennen syntymää tai varhaislapsuudessa, ja kardiometabolinen riski säilyy aikuisuuteen saakka. Insuliiniresistenssi (IR) on insuliiniherkkyyden vastakohta, ja tavallinen kardiovaskulaarisairauksiin liittyvä aineenvaihdunnallinen muutos. Rasvakudoksen on ehdotettu liittyvän IR:n patogeneesiin erittämällä insuliinin vaikutusta muokkaavia adiposytokiineja.

Metabolinen stressi valkeassa rasvakudoksessa johtaa sytokiinisynteesin ja - erityksen häiriöihin, jotka voivat myötävaikuttaa lihavuuteen liittyvien metabolisten, inflammatoristen ja kardiovaskulaaristen sairauksien kehittymiseen.

Adiposytokiinien lisäksi tietyt lihaksesta, maksasta ja luusta peräisin olevat sytokiinit on liitetty energiatasapainoon, sokeriaineenvaihduntaan, rasvakudoksen kehittymiseen, inflammaatioon ja endoteelin toimintaan.

Sikiöaikaisten epäedullisten olosuhteiden on osoitettu lisäävän myöhempää sydän- ja verisuonitautiriskiä. Sikiöaikainen kasvun hidastuminen ja äidin pre- eklampsia on yhdistetty jälkeläisten kohonneeseen metabolisten ja kardiovaskulaarisairauksien kehittymiseen.

Tässä väitöskirjassa arvioimme, liittyvätkö hiljattain insuliiniherkkyyteen ja matala-asteiseen tulehdukseen yhdistetyt biokemialliset markkerit kardiometabolisiin piirteisiin 12-vuotiailla lapsilla. Lisäksi tutkimme em.

parametrien muutoksia raskauden kestoon nähden pienikokoisena ja pre- eklampsiaraskaudesta syntyneillä lapsilla. Vuosina 1984-1986 syntynyt 192 lasta käsittävä kohortti [70 raskauden kestoon nähden pienikokoisena syntynyttä (small for gestational age, SGA); 78 normaalikokoisena syntynyttä ja 44 pre- eklampsiaraskaudesta syntynyttä (PRE)] tutkittiin Kuopion yliopistollisessa sairaalassa 12 vuoden iässä. Pelkästään pre-eklampsian vaikutusta IR:iin arvioidessamme tutkimme samasta kohortista 60 PRE-lasta ja 60 normotensiivisesta raskaudesta syntynyttä verrokkia. Verensokeri, seerumin insuliini ja niistä laskettu insuliiniherkkyyden indeksi (Quantitative Insulin Sensitivity Check Index),

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seerumin lipidit, interleukiini-1-reseptoriantagonisti (IL-1Ra), suurimolekulaarinen [high-molecular-weight (HMW)] adiponektiini, fibroblastikasvutekijä 21 (FGF-21), irisiini, kokonaisosteokalsiini (total, tOC), herkkä C-reaktiivinen proteiini (high sensitivity, hs-CRP), glukokortikoidit ja verenpainetaso määritettiin.

12 vuoden iässä seerumin IL-1Ra assosioitui matalampaan insuliiniherkkyyteen, korkeampaan hs-CRP-pitoisuuteen, painoindeksiin (BMI), vyötärönympäryksen ja pituuden suhdelukuun sekä huonompaan lipidiprofiiliin. Seerumin irisiini assosioitui negatiivisesti insuliiniherkkyyden markkereihin BMI:stä riippumattomasti. Korkeampi HMW-adiponektiinipitoisuus ennusti korkeampaa HDL-kolesterolitasoa, mutta sen assosiaatio insuliiniherkkyyteen oli BMI- riippuvaista. FGF-21 ja tOC eivät assosioituneet insuliiniherkkyyden markkereihin.

Sen sijaan korkeampi tOC-pitoisuus assosioitui matalampaan vapaan kortisolin indeksiin viitaten seerumin tOC-tason glukokortikoidiriippuvaiseen säätelyyn jo fysiologisilla kortisolipitoisuuksilla.

Tässä tutkimuksessa syntymäpienikokoisuus liittyi itsenäisesti matalampaan insuliiniherkkyyteen ja korkeampaan 24 tunnin ambulatoriseen verenpainetasoon.

Pre-eklampsia-altistus assosioitui itsenäisesti korkeampaan 24 tunnin ambulatoriseen systoliseen verenpainetasoon, mutta ei matalampaan insuliiniherkkyyteen. Seerumin IL-1Ra-, irisiini-, HMW-adiponektiini- ja tOC- pitoisuuksissa ei ollut eroa syntymäkoon tai pre-eklampsia-altistuksen osalta. PRE- lapsilla, joilla oli matalin insuliiniherkkyys, oli korkeampi systolinen verenpaine- ja triglyseriditaso verrattuna PRE-lapsiin, joilla oli korkeampi insuliiniherkkyys. PRE- lapsilla oli korkeampi kortisoli/kortisoni-suhde verrattuna normotensiivisista raskauksista syntyneisiin lapsiin, mikä voi heijastaa muuttunutta hypotalamus- aivolisäke-lisämunuaisakselin toimintaa tai perifeeristä kortisolimetaboliaa.

Yhteenvetona, 12-vuotiailla normoglykeemisillä lapsilla seerumin IL-1Ra ja irisiini liittyivät epäedullisiin metabolisiin piirteisiin, joskin yhteydet olivat melko heikkoja. HMW-adiponektiinin ja insuliiniherkkyyden välinen yhteys oli BMI- riippuvaista. FGF-21 ja tOC olivat heikkoja insuliiniherkkyyden markkereita.

Syntymäpienikokoisuus ja äidin pre-eklampsia assosioituivat epäedullisiin kardiometabolisiin piirteisiin. Suurentunut kardiometabolinen riski voi kuitenkin jäädä havaitsematta tässä työssä käytetyillä uusilla insuliiniherkkyyden ja matala- asteisen tulehduksen markkereilla arvioituna.

Luokitus: QU 120, WB 286, WD 210, WK 880, WQ 215, WS 130, WS 290, WS 440 Yleinen suomalainen ontologia: adiponektiini; aineenvaihdunta; glukokortikoidit;

insuliiniresistenssi; kehonkoostumus; kohorttitutkimus; lapset (ikäryhmät); lihavuus;

markkerit; painoindeksi; pre-eklampsia; rasva-arvot; riskitekijät; sydän- ja verisuonitaudit;

syntymäpaino; sytokiinit; tulehdus; verenpaine; ylipaino

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ACKNOWLEDGEMENTS

This study was conducted at the Department of Paediatrics, Kuopio University Hospital, and the Institute of Clinical Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, during 2011-2020. The doctoral studies were carried out in the Doctoral Programme of Clinical Research. This work was financially supported by the Kuopio University Hospital, University of Eastern Finland, the Paediatric Research Foundation, the Finnish Medical Foundation, the Finnish Cultural Foundation, the Finnish Cultural Foundation’s Kymenlaakso Regional Fund, and the Sigrid Jusélius Foundation.

I owe my deepest gratitude to my supervisors, Professor emeritus Raimo Voutilainen, and Sirpa Tenhola, M.D., Ph.D., for their skillful guidance and support over these years. I feel privileged to have had them as my supervisors. I am especially thankful to Raimo for his kind guidance, immediate responses, diligence and accuracy. I truly admire his spectacular scientific skills and passion for science. I am grateful to Sirpa for introducing me to the data she had carefully collected, and for all the conversations during these years. I sincerely thank both Raimo and Sirpa for their warm encouragement, for sharing their vast knowledge in the field of paediatric endocrinology, and for transmitting enthusiasm about scientific research to me.

I want to sincerely thank Professor Jarmo Jääskeläinen, Head of the Institute of Clinical Medicine, University of Eastern Finland, and Docent Pekka Riikonen, Head of the Department of Paediatrics, Kuopio University Hospital, for giving me the opportunity to carry out this study. I am grateful to Docents Sami Remes and Hanna Huopio for enabling me to combine research and clinical work during the years 2017- 2020 of my specialization in paediatrics. They all as well as Professor Marjo Renko are thanked for their encouragement.

I am sincerely thankful to the official reviewers of this thesis, Professor emeritus Sture Andersson and Docent Päivi Tapanainen for their constructive and valuable comments and advice.

I am honoured to have Professor Harri Niinikoski accept the invitation to be the opponent for the public examination of my doctoral dissertation.

I express my gratitude to laboratory technician Leila Antikainen for carefully conducting biochemical analyses. I warmly thank biostatistician Tuomas Selander for valuable advice on analysing the data and answering even the simplest statistical questions. For the linguistic revision of the previously unpublished parts of this thesis, I thank Docent David Laaksonen.

I’m grateful for all the encouragement from my colleagues and co-workers in the Departments of Paediatrics, Kuopio University Hospital and Kymenlaakso Central Hospital. I thank all my fellow researchers for their support and for sharing thoughts of the troubled waters of scientific research. Special thanks to Jani Liimatta for practical advice in the late parts of this work.

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I also thank all of my friends for memorable moments and bringing joy to my life.

Thanks go to Jussi for his help in editing this thesis. I am grateful to Mervi for helping our family by many ways.

I am greatly thankful to my family members for their understanding and support during several years. I express my warmest gratitude to my parents Marja and Keijo for the love and support for me throughout my life. I am deeply grateful to my sister Suvi and my brother Ville, who both have provided me invaluable support in information technology problems. I especially thank Suvi for the illustrations of this thesis. Many warm thanks also go to my parents-in-law Sirpa and Ari, sister-in law Suvi and brother-in-law Tommi and their families for being there for our family.

My deepest thanks go to my dear children Ilona, Milla and Veikka, for bringing so much happiness and love in my life. Finally, most of all, I am deeply grateful to my beloved husband Mikko for his endless patience, support and love during these years. Thank you for sharing your life with me.

Kotka, May 2020 Satu Seppä

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LIST OF ORIGINAL PUBLICATIONS

This dissertation is based on the following original publications:

I Seppä S, Voutilainen R, Tenhola S. Markers of insulin sensitivity in 12-year-old children born from preeclamptic pregnancies. J Pediatr 167(1):125-130, 2015.

II Seppä S, Tenhola S, Voutilainen R. Serum IL-1 receptor antagonist

concentrations associate with unfavorable metabolic features in 12-year-old children. J Endocr Soc 2(8):870-881, 2018.

III Seppä S, Tenhola S, Voutilainen R. Fibroblast growth factor 21, adiponectin and irisin as markers of unfavorable metabolic features in 12-year-old children.

J Endocr Soc 3(4):825-837, 2019.

IV Seppä S, Tenhola S, Voutilainen R. Association of serum total osteocalcin concentrations with endogenous glucocorticoids and insulin sensitivity markers in 12-year-old children: a cross-sectional study. Front Endocrinol 10:

798, 2019.

The publications were adapted with the permission of the copyright owners.

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ABBREVIATIONS

AGA Appropriate for gestational age ALP Alkaline phosphatase ANCOVA Analysis of covariance ANOVA Analysis of variance apoB Apolipoprotein B AUC Area under the curve B Breast development BMI Body mass index BMIadj BMI adjusted for sex

and adult age

BP Blood pressure

Ca Calcium

CBG Corticosteroid-binding globulin

CI Confidence interval CRP C-reactive protein

CS Cushing’s syndrome

CV Coefficient of variation CVD Cardiovascular disease ELISA Enzyme-linked

immunosorbent assay

FCI Free cortisol index FFA Free fatty acid

FGF-21 Fibroblast growth factor 21

FSIVGTT Frequently sampled intravenous glucose tolerance test FNDC5 Fibronectin type III

domain-containing protein 5

G Genital development

GH Growth hormone

GGT 𝛾-glutamyl transferase GTT Glucose tolerance test HDL-C High-density

lipoprotein cholesterol HMW High-molecular-weight HOMA-IR Homeostasis model

assessment for insulin resistance

HPA Hypothalamus-

pituitary-adrenal hs-CRP High-sensitivity C-

reactive protein IGF Insulin-like growth

factor

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IGFBP Insulin-like growth factor-binding protein IGT Impaired glucose

tolerance

IL Interleukin

IL-1Ra IL-1 receptor antagonist IR Insulin resistance IS Insulin sensitivity IUGR Intrauterine growth

restriction LBW Low birth weight LDL-C Low-density

lipoprotein cholesterol LGA Large for gestational

age

NOD Nucleotide-binding and oligomerization domain non-PRE Normotensive

pregnancy

OC Osteocalcin

OGTT Oral glucose tolerance test

PRE Pre-eclamptic pregnancy

PSEH Parent-specific expected height

QUICKI Quantitative Insulin Sensitivity Check Index ROC Receiver operating

characteristic

SAT Subcutaneus adipose tissue

SDS Standard deviation score

SGA Small for gestational age SHBG Sex hormone-binding

globulin

TNF-𝛼 Tumor necrosis factor-𝛼 tOC Total osteocalcin ucOC Undercarboxylated

osteocalcin

VAT Visceral adipose tissue WHtR Waist-to-height ratio

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1 INTRODUCTION

Cardiovascular disease (CVD) is a leading cause of death in adults (Yach et al. 2004, WHO 2018). Metabolic changes related to subclinical CVD begin prenatally or in early childhood (Crispi et al. 2018), and cardiometabolic risk tracks to adulthood (Mahoney et al. 1991, Webber et al. 1991, Raitakari et al. 2003, Li et al. 2003, Juhola et al. 2011). A major cardiometabolic risk factor is obesity. Insulin resistance (IR) is the most common metabolic alteration linking adiposity to metabolic and cardiovascular complications (Chiarelli and Marcovecchio 2008).

IR is a state in which glucose uptake is reduced in response to physiological insulin levels (Chiarelli and Marcovecchio 2008). Adipose tissue may play a crucial role in the pathogenesis of IR by secreting several metabolites, hormones and adipocytokines that affect insulin action (Chiarelli and Marcovecchio 2008).

Metabolic stress in the white adipose tissue leads to dysregulated adipocytokine synthesis and secretion, which may contribute to metabolic, inflammatory, and cardiovascular comorbidities (Fasshauer and Blüher 2015, Scheja and Heeren 2019).

Not only adipocytokines, but also certain cytokines derived from the muscle, liver and bone have been related to glucose metabolism, energy homeostasis, adipogenesis, inflammation and endothelial function (Fasshauer and Blüher 2015, Li F. et al. 2017, Lin et al. 2018).

Developmental and metabolic programming for later diseases begins in utero and continues in early childhood (Friedman 2018). The developmental origins of health and disease, Barker’s hypothesis, states that unfavourable in utero conditions affect later CVD risk (Barker et al. 1989, Barker 2003). In epidemiological studies, intrauterine growth restriction (IUGR) and low birth weight (LBW) have been shown to associate with cardiovascular morbidity in later life (Risnes et al. 2011, Finken et al. 2018). Furthermore, maternal pre-eclampsia has been associated with increased risk for metabolic and CVDs in the offspring (Davis et al. 2012, Goffin et al. 2018).

The clinical symptoms of CVD do not generally appear until adulthood.

However, the metabolic changes related to subclinical CVD may be visible already in childhood or adolescence (Juhola et al. 2011, Crispi et al. 2018). Therefore, several biochemical characteristics, such as glucose, insulin, IR indices, lipids, markers of low-grade inflammation, blood pressure (BP) and body size measurements can be used when assessing the future cardiometabolic risk (Chiarelli and Marcovecchio, 2008, Juhola et al. 2011, Nimptsch et al. 2019).

The aim of this thesis was to evaluate whether biochemical markers that have recently been linked to IS and low-grade inflammation associate with cardiometabolic characteristics in a cohort of 12-year-old children. We especially wanted to assess whether these parameters are altered with regard to small birth size or exposure to maternal pre-eclampsia.

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2 REVIEW OF THE LITERATURE

2.1 CARDIOMETABOLIC DISEASE RISK

CVDs are the leading cause of morbidity and mortality in adulthood (Yach et al. 2004, WHO 2018). The clinical manifestations of atherosclerosis generally appear in middle-age or even later, but their origins are prenatal or in early childhood (Friedman 2018). Autopsy studies have shown preclinical atherosclerotic lesions to associate with multiple antemortem cardiovascular risk factors already in childhood (Berenson et al. 1992, 1998). Cardiometabolic risk factors, such as increased BP, serum lipids and body mass index (BMI) measured in childhood or adolescence track to adulthood (Mahoney et al. 1991, Webber et al. 1991, Raitakari et al. 2003, Li et al. 2003, Juhola et al. 2011, Geserick et al. 2018), and the associations seem to strengthen with increased age at measurements (Juhola et al. 2011).

Obesity is the strongest cardiometabolic risk factor. Major pathways connecting adiposity to disease risk are the insulin/insulin-like growth factor (IGF) axis and chronic low-grade inflammation (reviewed in Nimptsch et al. 2019). IR is the most common metabolic alteration related to obesity representing a link between adiposity and other metabolic and cardiovascular disturbances (Chiarelli and Marcovecchio 2008), such as hyperlipidaemia, hyperinsulinemia, type 2 diabetes, hypertension and fatty liver disease (Tagi et al. 2019). During years 2016-2017 in Finland, the approximate prevalence for overweigth and obesity were 26% and 7% in boys, and 16% and 3% in girls, respectively (Mäki et al. 2018). Childhood obesity is a strong independent risk factor for adult CVD, even after adjustment for risk factors in adulthood (Laitinen et al. 2013).

Early risk factors in the intrauterine and postnatal environment influence the genesis of childhood obesity (Friedman 2018) and cardiometabolic disturbances (Finken et al. 2018). Important independent risk factors for future CVD are IUGR and LBW, exposure to maternal pre-eclampsia, and rapid postnatal growth (Barker et al.

1989, Davis et al. 2012, Finken et al. 2018). Nonetheless, rapid weight gain in infancy has been shown to associate with unfavourable cardiometabolic features in childhood and young adults independently of LBW (Finken et al. 2018).

2.2 INSULIN RESISTANCE

2.2.1 Definition and background

Insulin regulates glucose homeostasis by acting in muscular, adipose and hepatic tissues. In muscular and adipose tissues, insulin enhances glucose uptake, storage and use; in the liver, it inhibits gluconeogenesis and glycogenolysis, thus reducing glucose production and inducing glycogen storage (Figure 1) (Tagi et al. 2019). IR is the reverse of insulin sensitivity (IS): a decreased tissue response to physiological

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insulin levels and its consequent effects on glucose and insulin metabolism (Levy- Marchal et al. 2010, Tagi et al. 2019). Specifically, it is characterized by a relative decline in insulin action to stimulate use of glucose in muscle and adipose tissue and to suppress hepatic glucose production and output. Furthermore, IR is also characterized by a resistance to insulin action on lipid and protein metabolism and vascular endothelial function (Chiarelli and Marcovecchio 2008). In addition to obesity, gender, ethniticity (Hispanic, South-Asian, Black and Pima Indian), polycystic ovary syndrome, perinatal factors, family history of diabetes or gestational diabetes, puberty and rare genetic or acquired conditions characterized by lipodystrophy are risk factors for IR (Chiarelli and Marcovecchio 2008, Maffeis et al.

2018, Tagi et al. 2019). Although IR is usually associated with obesity, not all obese people are insulin-resistant, and IR may occur in children and adults without obesity (reviewed in Levy-Marchal et al. 2010, Tagi et al. 2019). IR in childhood can track to adulthood independently of BMI (Sinaiko et al. 2006).

Figure 1. Insulin action in the liver, adipose tissue and muscle in response to elevated blood glucose concentrations. In the liver, insulin reduces glucose production either directly or indirectly by suppressing glucagon secretion from pancreatic α-cells; consequently, glycogenolysis is inhibited. In adipose tissue, insulin enhances glucose uptake and inhibits lipolysis, thus reducing the release of glycerol and free fatty acids (FFAs). Glycerol is a substrate for gluconeogenesis; reduced FFA concentrations cause glycogen degradation to lactate instead of glucose. In muscle, insulin enhances glucose uptake and inhibits proteolysis, and thus reduces substrates for gluconeogenesis in the liver.

Pancreas

Liver

Adipose tissue

Muscle - insulin secretion

- gluconeogenesis

- glucose uptake

less substrates for gluconeogenesis

- proteolysis - lipolysis - glucagon

- glycogenolysis glycogen

glycerol

amino acids

lactate FFAs

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2.2.2 Insulin resistance of puberty

Puberty is characterized by a physiological transient hyperinsulinemia in midpuberty. IR will resolve after puberty is completed (Kelsey and Zeitler 2016, Tagi et al. 2019). During puberty, multiple hormonal changes occur. Gonadotropins and sex steroids rise gradually until the end of pubertal growth (Kelsey and Zeitler 2016).

Furthermore, growth hormone (GH) and insulin-like growth factor I (IGF-I), which is released in response to GH, reach their maximal concentrations during puberty but decline thereafter (Kelsey and Zeitler 2016). GH causes IR by increasing lipolysis and free fatty acid (FFA) concentrations, which are linked to reduced glucose uptake (reviewed in Kopchick et al. 2020). IGF-I levels rise and fall in parallel to IR during puberty (Moran et al. 2002). Pubertal hyperinsulinemia also suppresses circulating serum insulin-like growth factor-binding protein-1 (IGFBP-1) concentrations, which may increase free IGF-I and thus promote growth (Travers et al. 1998, Caprio 1999).

Contrary to normal-weight adolescents, in obese adolescents IR has been shown to persist (Kelsey and Zeitler 2016). Furthermore, despite similar degrees of glycaemic status and adiposity, obese adolescents had higher IR than obese adults (Arslanian et al. 2018).

2.3 INSULIN RESISTANCE IN RELATION TO OTHER CARDIOMETABOLIC RISK MARKERS

IR is an important mediator between adiposity and chronic diseases, such as CVDs (Chiarelli and Marcovecchio 2008, Nimptsch et al. 2019, Tagi et al. 2019). In adults and children, IR has been shown to predispose to high BP, impaired liver enzyme levels and glucose metabolism, type 2 diabetes and increased CVD risk (Cruz et al.

2002, Sinha et al. 2002, Burgert et al. 2006, Sinaiko et al. 2006, Chiarelli and Marcovecchio 2008, Lurbe et al. 2008). Cardiometabolic risk markers seem to persist even after short-term improvement in glycaemia in high-risk youths (Weinstock et al. 2013).

2.3.1 Adiposity and body composition

The human body consists of water, proteins, carbohydrates, minerals and fat, and it can be divided into fat and fat-free compartments (Bosy-Westphal et al. 2019). Body composition diverges between the sexes, and it changes with age already in childhood (Fomon et al. 1982). Body composition influences IS independently of the degree of obesity (reviewed in Caprio et al. 2017).

Excess adiposity in children has been shown to associate strongly with the development of hypertension and atherosclerosis in adulthood (Mahoney et al. 1996, Raitakari et al. 2003, Li et al. 2003, Petkeviciene et al. 2015), and negatively with IS (reviewed in Maffeis and Morandi 2018). In other studies, higher childhood BMI was associated with the risk of adult obesity, metabolic syndrome, high-sensitivity C- reactive protein (hs-CRP), hyperglycaemia and diabetes, whereas the risk for raised

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triglyceride and reduced high-density lipoprotein cholesterol (HDL-C) concentrations, hypertension and stroke were affected by BMI gain from childhood to adulthood (Petkeviciene et al. 2015, Ohlsson et al. 2017). Especially obesity at later stages of youth increases the risk for cardiometabolic diseases in adulthood (Juonala et al. 2011, Bjerregaard et al. 2018).

Visceral adipose tissue (VAT) is associated with IR and metabolic risk factors already in children and adolescents (Bennett et al. 2012, Hatch-Stein et al. 2016). VAT is metabolically more active than subcutaneous adipose tissue (SAT) and secretes more hormones and cytokines that prompt metabolic disturbances such as low-grade inflammation and IR (Nimptsch et al. 2019). In obese children and adolescents, visceral fat and the visceral/subcutaneous fat ratio were associated with adipose tissue IR index (expressed as the product of fasting insulin and FFAs concentration) (Hershkop et al. 2016).

Body composition diverges greatly during puberty, when boys gain more lean body mass than girls, and body fat percentage declines in boys (McCarthy et al. 2006).

Furthermore, the percentage of visceral fat tends to increase from puberty onwards (Hübers et al. 2017, Maffeis and Morandi 2018). Although visceral fat is an important determinant of IR in late and post-pubertal obese children and adolescents, characterized by significant percentage of VAT in relation to total adiposity (Maffeis and Morandi 2018), its role is less important for IR in prepubertal children, especially if they are not obese (Gower 1999). Thus, in the absence of obesity or in most population-based cohorts, total fat rather than visceral fat is the most important determinant of IR in children (Maffeis and Morandi 2018).

2.3.2 Blood pressure

In adulthood, elevated BP is a significant risk factor for CVD (Chobanian et al. 2003).

It associates with atherosclerotic vascular changes, including high carotid intima- media thickness (Qu and Qu 2015). Potential links between IR and increased BP are insulin-mediated activation of the sympathetic nervous system and renal sodium reabsorbtion (Rowe et al. 1981, Artunc et al. 2016). In children and adolescents, the prevalence of hypertension is approximately 3.5% (Hansen et al. 2007, McNiece et al.

2007, Flynn et al. 2017). Elevated BP in childhood can track to adulthood and increase the risk for hypertension and the metabolic syndrome (Sun et al. 2007, Juhola et al.

2011, 2012). Furthermore, if at least two abnormal BP measurements are observed in childhood, it may predict the risk of adult hypertension (Oikonen et al. 2016).

Elevated BP is increased in children and adolescents with overweight and obesity (Falkner et al. 2006, Flynn et al. 2017).

2.3.3 Lipids

Lipids regulate metabolism and inflammation, and hyperlipidaemia induces, in part, peripheral tissue IR and contributes to the development of atherosclerosis (Wellen and Hotamisligil 2005). Prospective cohort studies have demonstrated that

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dyslipidaemia tracks from childhood to adolescence and adulthood (Lauer et al.

1988, Webber et al. 1991, Porkka et al. 1994), and that it associates with surrogate markers of atherosclerosis (Li et al. 2003, Magnussen et al. 2009). Particularly an excess of low-density lipoprotein cholesterol (LDL-C) and other apolipoprotein B (apoB) containing lipoproteins (very low-density lipoprotein, intermediate-density lipoprotein and lipoprotein a) affect the risk for atherosclerosis (Carr et al. 2019). In atherogenesis, apoB-containing lipoproteins accumulate within arterial wall and vascular intima (reviewed in Carr et al. 2019). However, a report from the Framingham Heart Study showed that low HDL-C and high triglycerides were not significant risk factors for CVD events in the absence of IR (Robins et al. 2011).

2.4 INSULIN RESISTANCE IN RELATION TO LOW-GRADE INFLAMMATION

White adipose tissue located throughout the body is responsible for energy storage.

However, it has also been recognized as a metabolically active endocrine organ.

White, beige and brown adipose tissue secrete a variety of adipocytokines including classical hormones, growth factors, inflammatory mediators, metabolites and enzymes that are able to modulate immunological responses, appetite control, energy expenditure, thermogenesis, adipogenesis, endothelial function, glucose metabolism and IS (Fasshauer and Blüher 2015, Scheja and Heeren 2019). Metabolic stress in white adipose tissue leads to dysregulated cytokine synthesis and secretion, infiltration of proinflammatory immune cells, altered lipid handling in macrophages, decreased response of adipocytes to insulin (i.e. IR), and disturbed metabolism (Fasshauer and Blüher 2015, Scheja and Heeren 2019). Via low-grade inflammation, IR is associated with endothelial dysfunction, increased arterial stiffness, accelerated atherosclerosis and disordered fibrinolysis (Chiarelli and Marcovecchio 2008).

Low-grade inflammation in the adipose tissue induces IR through multiple molecular mechanisms (Figure 2), but the initial inflammatory trigger in the adipose tissue remains unknown (Reilly and Saltiel 2017). It has been suggested that gut- derived lipopolysaccharides might initiate an inflammatory cascade via the activation of pattern recognition receptors (such as the Toll-like receptor 4) in adipocytes. Furthermore, FFAs bind to Toll-like receptors, which promote downstream inflammatory signalling. Inflammatory signalling increase the synthesis and secretion of chemokines by adipocytes, which leads to the infiltration of proinflammatory macrophages into the adipose tissue. In macrophages, nucleotide-binding and oligomerization domain (NOD)-like receptors sense damage-associated molecular proteins derived from stressed adipocytes, and activate the inflammasome to induce e.g. interleukin-1β (IL-1β) and tumor necrosis factor-𝛼 (TNF-𝛼) production that promote IR (Figure 2) (reviewed in Reilly and Saltiel 2017). Activation of the inflammatory pathways inhibit insulin action in any insulin-sensitive tissue targeted by paracrine or systemic inflammatory stimuli, thus increasing IR (Odegaard and Chawla 2013, Reilly and Saltiel 2017). Furthermore,

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hypoxia related to the expansion of adipocytes may play a role in the inflammatory cascade, although the exact mechanism remains unknown (Reilly and Saltiel 2017).

Figure 2. Initiators of (obesity-associated) inflammation in adipocytes (modified from Reilly and Saltiel 2017). Abbreviations: DAMP, damage-associated molecular protein; FFA, free fatty acid; NLR, nucleotide-binding and oligomerization domain (NOD)-like receptor; TLR, Toll-like receptor

2.5 INSULIN RESISTANCE AND CARDIOVASCULAR DISEASE IN RELATION TO GLUCOCORTICOIDS

Glucocorticoids induce IR, hyperglycaemia and hyperlipidaemia via multiple pathways (Brennan-Speranza et al. 2012, Cooper et al. 2016). In humans, endogenous or exogenous glucocorticoid excess is associated with adverse clinical features, such as IR, impaired glucose tolerance (IGT) and diabetes, hypertension, osteoporosis, accumulation of visceral fat and dyslipidaemia (Moisiadis and Matthews 2014a, 2014b).

On the other hand, glucocorticoids are involved in the growth and maturation of many organ systems and are therefore crucial for normal fetal development. An increase in glucocorticoid levels during late gestation promote pulmonary surfactant

STRESSED ADIPOCYTE

ADIPOCYTE

Lipid droplets

Macrophage

Lipopolysaccharides

Hypoxia or low pO2

Activation of the pathways

synthesis

expression

Inhibition of insulin action

polarization of recruited TLR2

TLR4

signalling

?

NLR

DAMPs FFAs

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production and is thus essential for fetal lung maturation. In addition, endogenous glucocorticoids are essential for maturation in e.g. the pituitary, brain, thyroid and kidneys (Moisiadis and Matthews, 2014a, 2014b). Prenatal exposure to excess glucocorticoids, or exposure at an incorrect stage of maturation has been suggested to result in altered physiological function of the hypothalamo-pituitary-adrenal (HPA) axis, leading to increased glucocorticoid action throughout life (Moisiadis and Matthews 2014a, 2014b). Pre- and postnatal overexposure to glucocorticoids have adverse effects on the development of cardiovascular, metabolic, neurological and reproductive functions (Moisiadis and Matthews 2014a, 2014b). Furthermore, they may represent a mechanism linking restricted fetal growth with CVD (Seckl 2004).

During pregnancy, the placental barrier enzyme 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2) protects fetus against exposure to excess maternal cortisol by converting cortisol to inert cortisone (Moisiadis and Matthews 2014b).

However, the barrier is incomplete. Thus, maternal, fetal or neonatal stress or placental dysfunction may cause increased levels of endogenous glucocorticoids in the mother, fetus and neonate (Moisiadis and Matthews 2014a). Plasma cortisol and cortisone, and cortisol/cortisone ratio have been used as an indirect measure of 11β- HSD2 activity (Houang et al. 1999, Dötsch et al. 2000). 11β-HSD2 expression has been shown to be decreased in placentas complicated by IUGR (Shams et al. 1998, Dy et al. 2008), accompanied by higher cortisol/cortisone ratio in cord blood (Dy et al. 2008).

After the first years of life, the cortisol/cortisone ratio stays rather stable during childhood and adolescence (Dötsch et al. 2000).

Ninety-five per cent of the secreted cortisol is bound to carrier proteins, mainly to corticosteroid-binding globulin (CBG) and to a lesser extent to serum albumin. The remaining 5% of cortisol is considered active (Bae and Kratzsch 2015). By assessing free cortisol index (FCI), defined as the ratio of total cortisol to CBG, the effect of CBG variation in total cortisol values can be eliminated (le Roux et al. 2002).

2.6 EVALUATION OF THE CARDIOVASCULAR DISEASE RISK

Because the clinical manifestations of CVD are latent in childhood and adolescence, the CVD risk must be evaluated indirectly, e.g. by estimating IS and IR indices, lipids, low-grade inflammation, BP and body composition.

2.6.1 Assessment of insulin resistance

IR can be estimated by fasting serum insulin and glucose concentrations, insulin/glucose ratios, more complex IR or IS indices, the oral glucose tolerance test (OGTT), the insulin tolerance test, hyperinsulinemic euglycaemic clamp studies, and the frequently sampled intravenous glucose tolerance tests (FSIVGTT) (Chiarelli and Marcovecchio 2008). However, standards for IR in children have not been established due to the use of variety of techniques to measure IS, and lack of sufficient cohort sizes to determine normative distributions for IS and adequate longitudinal studies to relate definitions for IR to longitudinal outcomes (Levy-Marchal et al. 2010).

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2.6.1.1 Invasive methods and oral glucose tolerance test

The gold standard test to directly determine metabolic IS is the hyperinsulinemic euglycaemic clamp originally developed by DeFronzo et al. (1979). However, glucose tolerance tests (GTT) are easier to perform, and therefore more frequently used. GTT analyses the effects of either intravenously, orally or intraperitoneally administered glucose on systemic glucose clearance (Tagi et al. 2019). In addition to the hyperinsulinemic euglycaemic clamp, FSIVGTT utilizing the minimal model is considered a reliable method for assessing IS. These methods also allow differentiation between hepatic and muscular IR (Chiarelli and Marcovecchio 2008).

Hyperinsulinemic euglycaemic clamp studies have shown that IR is determined primarily by the response of skeletal muscle, and only minimally by that of adipose tissue (reviewed in Levy-Marchal et al. 2010). The insulin tolerance test measures the systemic glucose clearance in response to exogenous administration of insulin (Brown and Yanovski 2014, Tagi et al. 2019). Its adverse effect is severe hypoglycaemia, and no validation studies for children exist (Brown and Yanovski 2014). All these methods are invasive, time consuming, expensive and require a research setting (Chiarelli and Marcovecchio 2008, Tagi et al. 2019).

OGTT indices with insulin measurements correlate well with the hyperinsulinemic euglycaemic clamp findings in adults (Stumvoll et al. 2000).

Surrogate indices obtained during the OGTT include e.g. the whole-body IS index and the IS index. These indices have also been validated in obese children and adolescents, with a strong correlation between these indices and the euglycaemic clamp results (Yeckel et al. 2004). Furthermore, the OGTT allows to diagnose IGT or overt diabetes, to estimate first-phase insulin responses to glucose administration, and thus to evaluate the relationship between insulin secretion and IS (Yeckel et al.

2004, Chiarelli and Marcovecchio 2008). Therefore, the OGTT can be used as a screening test to estimate IR in obese children or in those with obesity-associated risk factors (Chiarelli and Marcovecchio 2008). However, the correlation between two OGTTs was low, as was the re-test reproducibility of the OGTT for impaired fasting glucose and IGT in overweight youths (Libman et al. 2008).

2.6.1.2 Fasting surrogate markers

Methods based on surrogate markers derived from fasting insulin and glucose or from OGTT have been suggested as potential alternatives for invasive methods to assess IR (Brown and Yanovski 2014, Tagi et al. 2019). They utilize the principle that in euglycaemic states, insulin secretion compensates IR. As insulin concentrations are relatively low in the fasting state, insulin acts primarily in the liver and adipose tissue rather than in the muscle (Brown and Yanovski 2014). Thus, fasting surrogates are considered to reflect primarily hepatic IS (Muniyappa et al. 2008, Brown and Yanovski 2014). Under most conditions, skeletal muscle and hepatic IS correlate with each other (Muniyappa et al. 2008). However, in hyperglycaemic states, surrogate

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measures based on fasting insulin are not valid, as insulin secretion can no longer compensate for IR (Muniyappa et al. 2008, Brown and Yanovski 2014).

Fasting insulin is considered a suboptimal tool for individual assessment of peripheral IS, but it may represent a valid index of compensatory hyperinsulinemia and liver insulin metabolism (Levy-Marchal et al. 2010). Its correlation with IR in children is uncertain (Schwartz et al. 2008). In a meta-analysis of prospective adult cohort studies, higher fasting insulin concentrations were associated with higher risk of hypertension and CVD (Xun et al. 2013).

The inverse 1/(fasting insulin) is a widely used surrogate for IS, which decreases concurrently with increasing IR of the subjects. However, its correlation with the glucose clamp is poor (Muniyappa et al. 2008).

The fasting glucose/insulin ratio is functionally equivalent to 1/(fasting insulin) in non-diabetic subjects, since glucose levels are within the normal range. However, it does not reflect the physiology underlying the determinants of IS (Quon 2001, Muniyappa et al. 2008).

The homeostasis model assessment for insulin resistance (HOMA-IR) (Table 1) is a surrogate model that determines the degree of IR using only the fasting glucose and insulin values (Matthews et al. 1985, Tagi et al. 2019). A higher HOMA-IR corresponds to more severe IR (Tagi et al. 2019). Its physiological basis is the feedback loop between the glucose production by the liver and insulin production by the β- cells to maintain euglycaemia (Muniyappa et al. 2008, Brown and Yanovski 2014).

However, in subjects with IGT to moderate diabetes, the logarithmic value of HOMA-IR may be useful. In subjects with severely impaired β-cell function, HOMA- IR may give inappropriate results (Muniyappa et al. 2008). HOMA2-IR is the updated computer model, which considers the variation in peripheral and hepatic glucose resistance. Thus, it is preferred when HOMA is compared with other models, such as the minimal model (Tagi et al. 2019).

Quantitative Insulin Sensitivity Check Index (QUICKI) is derived from the inverse of the sum of the logarithms of the fasting insulin and fasting glucose (Table 1) (Muniyappa et al. 2008, Tagi et al. 2019). Thus, it correlates almost perfectly inversely with HOMA-IR. QUICKI correlates quite well with the glucose clamp method (Katz et al. 2000, Mather et al. 2001, Uwaifo et al. 2002). The disadvantage of QUICKI and HOMA-IR is the lack of universal insulin assay standardization (Tagi et al. 2019). As numerical values for insulin may vary between laboratories and cannot be directly compared with each other, no reference values for HOMA-IR or QUICKI exist for clinical use (Brown and Yanovski 2014). However, Shashaj et al. (2016) have suggested age-, sex- and BMI-dependent HOMA-IR cut-off values for increased cardiometabolic risk in children and adolescents.

Insulin suppresses IGFBP-1 expression via an insulin-response element in the IGFBP-1 promoter region (reviewed in Haywood et al. 2019). IGFBP-1 has been proposed as a potential circulating marker to estimate IR (Yki-Järvinen et al. 1995). It correlates well with the FSIVGTT results, particularly in children younger than 10 years (Motaghedi et al. 2007).

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Although surrogate measures may not be optimal for assessing individual IS, they are considered applicable for screening purpose in studies using large populations and with well-defined cohorts (Levy-Marchal et al. 2010). Validation studies for surrogate measures have been performed in children and adolescents with normal glucose tolerance, with good correlation coefficients compared with the clamp and FSIVGTT methods (Conwell et al. 2004, Gungor et al. 2004, Chiarelli and Marcovecchio 2008).

Table 1. Main surrogate indices of insulin sensitivity (IS) or resistance (IR) used in children (modified from Tagi et al. 2019).

Method Formula

Fasting plasma

insulin fasting plasma insulin Fasting

glucose/insulin ratio

fasting glucose/insulin ratio

HOMA-IR [fasting insulin (µU/ml) x fasting glucose (mmol/l)]/22.5 HOMA2-IR Computer model

QUICKI 1/[log (fasting insulin, µU/ml) + log (fasting glucose, mg/dl)]

IGFBP-1 IGFBP-1

IS Index [1.9/6 x body weight (kg) x fasting glucose (mmol/l) + 520-1.9/18 x body weight x area under curve (AUC) for glucose (mmol/h x l) – urinary glucose (mmol/1.8)]/[AUC for insulin (pmol/h x l) x body weight]

Whole body IS index

10,000

#$fasting glucose 2mg

dl5 x fasting insulin 7µU

ml9: (mean glucose x mean insulin)

2.6.2 Assessment of body composition

Body composition can be measured by several methods. Individual differences must be considered when assessing body composition in children (Fomon et al. 1982). One of the simpliest methods is to calculate BMI, which is a measure of weight relative to height calculated as kg/m². BMI changes substantially during childhood and adolescence – at birth the median is 13 kg/m², at age one year it is 17 kg/m² decreasing to 15.5 kg/m² by 6 years age, and increasing to 21 kg/m² until 20 years of age (Cole et al. 2000). BMI percentiles (Cole et al. 2000, 2007) and BMI-for-age i.e. sex- and adult age-adjusted BMI values corresponding to the BMI values at the age of 18 have been published internationally as well as for Finnish children and adolescents (Saari et al.

2011, WHO 2019).

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BMI is widely accepted as a risk screening tool because of its simplicity and its association with cardiometabolic risk factors (Javed et al. 2015, Nimptsch et al. 2019).

However, BMI cannot distinguish fat mass and lean mass (Nimptsch et al. 2019).

Furthermore, although BMI approximates total adiposity with relatively high specifity, its sensitivity is low. In a meta-analysis by Javed et al. (2015), it failed to detect over a quarter of children with excess body fat percentage. However, a meta- analysis consisting of 5 to 15 year-old children reported that overweight (> 25 kg/m²) and obesity (> 30 kg/m²) determined by BMI significantly worsened CVD risk measures (Friedemann et al. 2012).

Waist circumference and waist-to-hip ratio are simple measurements to assess fat distribution, and they correlate more strongly with VAT than with BMI (Ping et al.

2018, Nimptsch et al. 2019). However, in adolescents, these parameters were poor predictors of relative visceral fat, and performed similarly to BMI as an estimate of VAT (Goodwin et al. 2013).

Waist-to-height ratio (WHtR) is an anthropometric index established in the 1990’s (Hsieh and Yoshinaga 1995, Ashwell et al. 1996). It has no specific cut-off points for differentiation by age, sex and ethnicity (Lo et al. 2016). WHtR greater than 0.5 has been suggested a boundary value to screen for CVD and diabetes risk (Browning et al. 2010). In children and adolescents, WHtR identified youth with cardiovascular risk factors better than age- and sex-specific BMI percentiles (Kahn et al. 2005).

Furthermore, in a cross-sectional study including over 14,000 children and adolescents, elevated WHtR associated with worsened cardiometabolic risk factor levels even in subjects with normal BMI (Khoury et al. 2013). On the contrary, in other studies WHtR was not superior to waist circumference or BMI in detecting cardiometabolic risk factors in children or adolescents (Morandi et al. 2014, Aristizabal et al. 2015, Lo et al. 2016, Qi et al. 2017).

Because weight does not scale with height squared during the period of rapid growth, tri-ponderal mass index (calculated as weight in kilograms divided by height in meters cubed) has been proposed as an alternate to BMI to estimate body fat levels in youth (Peterson et al. 2017). However, it was not superior to BMI at any age from childhood to young adulthood in the prediction of obesity-related outcomes in young adulthood (Wu et al. 2020).

Elaborate techniques to assess body compartments have been used mainly in research settings. These include e.g. bioelectrical impedance analysis, dual-energy X- ray absorbtiometry DXA, magnetic resonance imaging, and skinfold thickness that allow quantifying the volume and mass of VAT, SAT and coronary adipose tissue.

However, these techniques are rarely used in clinical practice (Javed et al. 2015, Nimptsch et al. 2019).

2.6.3 New insulin sensitivity markers

Many peptides released by non-endocrine cells, such as adipose tissue, muscle and intestine, have been linked to cellular energy homeostasis and regulation of metabolic function. Their effects are mainly paracrine or autocrine, as they act on the

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nearby cells or on the cells that produce them (Arhire et al. 2019). White and brown adipocytes secrete adipocytokines that have effects on pancreatic β-cells, brain, skeletal muscle, liver and the cardiovascular system (Fasshauer and Blüher 2015, Scheja and Heeren 2019). In adults and children, several adipocytokines have been related to adiposity indices and IR (Chiarelli and Marcovecchio 2008). In addition to adipose tissue-derived adipokines, also cytokines secreted from hepatocytes, skeletal muscle-derived myokines and osteoblast-produced osteocalcin (OC) have been proposed as markers of IS (Li F. et al. 2017, Lin et al. 2018), and to mediate the association between adiposity and chronic diseases.

2.6.3.1 Leptin

The adipocyte-derived satiety hormone leptin controls energy homeostasis through receptors in the central nervous system. Furthermore, it affects the immune response, bone turnover, hypothalamus-pituitary hormonal axis and regulation of fertility (Scheja and Heeren 2019). Its serum concentrations reflect body fat storage and adipose tissue mass, and associate with circulating inflammatory markers (Blüher and Mantzoros 2015). Although leptin levels have been shown to correlate with vascular risk factors, a meta-analysis of 13 epidemiological studies reported no association between higher circulating leptin and risk of CVD or stroke (Yang et al.

2017).

2.6.3.2 Adiponectin

The adipocytokine adiponectin has anti-inflammatory, insulin-sensitizing, energy expenditure increasing and anti-apoptotic properties (Ye and Scherer 2013, Fasshauer and Blüher 2015, Scheja and Heeren 2019). It decreases hepatic gluconeogenesis, increases fatty acid oxidation in skeletal muscle and liver, increases glucose uptake in white adipose tissue and muscle, and decreases white adipose tissue inflammation (Scheja and Heeren 2019). In clinical studies, circulating adiponectin correlated negatively with IR, type 2 diabetes, the amount of VAT, serum lipid levels and BP (reviewed in Ye and Scherer 2013, Fasshauer and Blüher 2015).

Lower adiponectin was associated with higher risk of type 2 diabetes in insulin- resistant individuals estimated by HOMA-IR but not in insulin-sensitive ones (Hivert et al. 2011). The high-molecular-weight (HMW) adiponectin has been shown to correlate better with systemic IS (reviewed in Fasshauer and Blüher 2015) and better reflect metabolic abnormalities compared with total adiponectin or its low- molecular-weight isoform (Araki et al. 2006, Mangge et al. 2008). Low circulating HMW adiponectin levels have been linked to obesity, especially abdominal obesity already in childhood (Araki et al. 2006) and adolescence (Mangge et al. 2008). The association between adiponectin and CVD is obscure. Regardless of the suggested cardioprotective and anti-atherogenic effects, a meta-analysis of 16 prospective cohort studies found no association between circulating adiponectin concentrations and coronary heart disease or stroke (Kanhai et al. 2013).

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2.6.3.3 Fibroblast growth factor 21

The cytokine fibroblast growth factor 21 (FGF-21) is produced primarily in the liver, but also in other tissues such as white and brown adipose tissue, brain and possibly pancreas and skeletal and cardiac muscle (Itoh 2014, Kharitonenkov and DiMarchi 2017). Its production is increased upon fasting and exercise, and with high carbohydrate or low protein intake (Scheja and Heeren 2019). Unlike most of the FGFs, it acts mainly in an endocrine manner (Itoh 2014). In experimental studies, FGF-21 has been shown to induce browning of white adipose tissue, inhibit lipolysis, promote pancreatic β-cell function and survival, and regulate thermogenesis (Fisher et al. 2012, Itoh 2014). Thus, it has beneficial effects on IS, glucose and lipid metabolism and energy homeostasis (Fisher et al. 2012, Itoh 2014).

In humans, elevated FGF-21 levels have been reported in insulin-resistant states, and to independently predict the metabolic syndrome and type 2 diabetes (Zhang et al. 2008, Chen et al. 2011, Bobbert et al. 2013). Therefore, it has been suggested to be a marker of adverse metabolic profile in adults (Bobbert et al. 2013, Ebert et al. 2018).

FGF-21 has been associated with obesity already in childhood (Reinehr et al. 2012), but this finding is not consistent (Li G. et al. 2017).

2.6.3.4 Irisin

Irisin is an adipomyokine, and a cleavage product of the fibronectin type III domain- containing protein 5 (FNDC5). It is primarily secreted by muscle, but also adipose and other tissues secrete small amounts of it. In mice, irisin enhances energy expenditure by stimulating the browning of white adipose tissue and improves glucose homeostasis and the lipid profile (reviewed in Perakakis et al. 2017).

However, in humans the physiological significance of irisin is controversial (reviewed in Perakakis et al. 2017).

In adults and children, elevated irisin concentrations have been observed in insulin-resistant states and obesity (Park et al. 2013, Blüher et al. 2014, Reinehr et al.

2015, Qiu et al. 2016, Perakakis et al. 2017). However, irisin levels have been reported to decrease in type 2 diabetes (Moreno-Navarrete et al. 2013). Conflicting results have been reported with regard to serum irisin levels and lipids – irisin has been shown to associate with either favourable (Oelmann et al. 2016, Buscemi et al. 2018) or unfavourable lipid profiles (Crujeiras et al. 2015, Jang et al. 2017).

2.6.3.5 Osteocalcin

The bone turnover marker OC is a non-collagenous polypeptide synthetized by osteoblasts. After being synthesized, OC undergoes vitamin K-dependent 𝛾- carboxylation, which increases its affinity for hydroxyapatite crystals. Thus, most of the produced OC is embedded in the bone matrix (Hauschka et al. 1989, Liu et al.

2016, Lin et al. 2018). A small amount of OC remains undercarboxylated (ucOC) and

Cardiometabolic risk factors in 12-year-old children : the role of insulin sensitivity, low-grade inflammation, birth weight and maternal preeclampsia

uef.fi

Dissertations in Health Sciences

SATU SEPPÄ

CARDIOMETABOLIC RISK FACTORS IN 12-YEAR-OLD CHILDREN: THE ROLE OF INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND MATERNAL PRE-ECLAMPSIA

SATU SEPPÄ

CARDIOMETABOLIC RISK FACTORS IN 12- YEAR-OLD CHILDREN: THE ROLE OF

INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND

MATERNAL PRE-ECLAMPSIA

Satu Seppä

CARDIOMETABOLIC RISK FACTORS IN 12- YEAR-OLD CHILDREN: THE ROLE OF

INSULIN SENSITIVITY, LOW-GRADE INFLAMMATION, BIRTH WEIGHT AND

MATERNAL PRE-ECLAMPSIA

ABSTRACT

TIIVISTELMÄ

ACKNOWLEDGEMENTS

LIST OF ORIGINAL PUBLICATIONS

CONTENTS

ABBREVIATIONS

1 INTRODUCTION

2 REVIEW OF THE LITERATURE

2.1 CARDIOMETABOLIC DISEASE RISK

2.2 INSULIN RESISTANCE

2.3 INSULIN RESISTANCE IN RELATION TO OTHER CARDIOMETABOLIC RISK MARKERS

2.4 INSULIN RESISTANCE IN RELATION TO LOW-GRADE INFLAMMATION

2.5 INSULIN RESISTANCE AND CARDIOVASCULAR DISEASE IN RELATION TO GLUCOCORTICOIDS

2.6 EVALUATION OF THE CARDIOVASCULAR DISEASE RISK