Early determinants of cardiovascular, metabolic and reproductive health --- EDCaR.

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Early determinants of cardiovascular, metabolic and reproductive health --- EDCaR. Harri Niinikoski MD, PhD, Pediatric endocrinologist Professor of Nutrition in Medicine University of Turku/Physiology and Pediatrics Turku, FINLAND HN 28.5.2018 1

Three Finnish child cohorts STRIP Cardiovascular risk intervention study Turku DIPP Diabetes (T1D) prediction and prevention study Turku, Tampere and Oulu (incl. nutrition study) Boycohort Male reproductive health study Turku HN 28.5.2018 2

Flow-charts of the 3 studies HN 28.5.2018 3

Data in the 3 studies DIPP STRIP Boy cohort Enrollment At birth At 7 months At birth N of subjects >200000 screened; >17000 follow-up 1062 1500 (119) Main study question T1D pathogenesis/prediction/prevention Heart disease risk factors Reproductive health Follow-up frequency 3, 6, 9, 12, 18, 24 mo, then every 12 mo 7, 13, 18, 24 mo, then every 6-12 mo 0, 3, 18* mo; from 8.5* yrs every 6 mo Clinical data Wt, Ht, infections,vaccines, medications Wt, Ht, waist-hip, BP, infections, medications Wt, Ht, waist-hip* Cognitive development Questionnaires and testing - Pubertal development Clical assessment if autoantibody+ Clinical assessment Clinical assessment* Psychosocial development Questionnaires and testing - Nutrition assesment Mother: pregn, lact food frequency questionnaire structured questionnaire* Infant 3-d- food records, feeding pattern 4-d food records (every 6-12 mo), feeding patt. feeding pattern (questionnaire)* Child 3-d food records at 3-12 mo intervals 4-d food records (every 6-12 mo) Adolescent, young adult structured questionnaire 4-d food records (every 6-12 mo) feeding pattern (questionnaire)* Child biomarkers* s-vitamin E, D & carotenoids, s-fatty acids s-vitamin D*, fatty acids, lipids Laboratory follow-up At every study visit Annually At 3 mo and from puberty start* Imaging / radiology Cardiac echo, endothelial function Testicular echo Other Parental education, Wt, Ht Physical activity and fitness Chemical exposure data* Tobacco smoke exposure Tobacco smoke exposure Tobacco exposure Autoimmune diseases in family Body composition Prenatal questionnaire Allergy and asthma Three generations involved Perinatal data from birth registers Perinatal data from birth registers T1D = type 1 diabetes mellitus * Subcohort HN 28.5.2018 4

EDCaR aims 1) To investigate the effect of early nutrition and environment on cardiovascular and metabolic morbidity (DIPP, STRIP, Boy cohort) 2) To investigate the effect of early nutrition and environment on the development overweight and obesity during childhood and adolescence (DIPP, STRIP) 3) To investigate the effect of early nutrition and environment on the development of asthma and allergic sensitization during childhood and adolescence (DIPP, STRIP) 4) To study effects of overweight on the development of islet autoimmunity and type 1 diabetes (DIPP, STRIP) 5) To study effects of puberty on the development of islet cell autoimmunity and type 1 diabetes (DIPP, STRIP, Boy cohort) 6) To study effects of early testicular function on metabolic morbidity (Boy cohort, STRIP) 7) To study effects of overweight on sex hormone production (Boy cohort, STRIP) HN 28.5.2018 5

Table 2: Data integration plan DIPP STRIP Boy cohort Infancy feeding history (aims 1-3) x x x Dietary intakes (aims 1-3) x x Dietary patterns (aims 1-3) x x Growth (Wt, Ht, BMI; aims 1,4-7) x x x Islet autoimmunity (aims 4,5) x Pubertal development (aims 5-7) x x x Reproductive hormones (aims 5-7) x x Metabolic markers (aims 1, 6-7) x x x Data are anonymized; study subjects can not be identified HN 28.5.2018 6

Very large databases of metabolic, nutritional and clinical information of children and adolescents collected during the last 2.5 decades. A unique possibility to investigate the effects of nutrition on the development of overweight and metabolic and reproductive health, including adverse serum lipid and lipoprotein as well as glucose and insulin metabolism more precisely than before. HN 28.5.2018 7

The Boy cohort enables the investigation of early sex hormone status on future metabolic diseases. Boy cohort and the STRIP study have detailed clinical and biochemical assessment of pubertal development together with detailed growth data, which can be utilized in the large DIPP study population to assess the start of puberty and its relation with the development of islet autoimmunity and type 1 diabetes. HN 28.5.2018 8

Sperm concentration in young men Incidence of testicular cancer Koskenniemi et al., 2017, Duodecim Skakkebaek et al., 2016 Physiol Rev

Current status Data harmonization Model construction for estimation of pubertal stage from growth and hormone data Ht, Wt, BMI (STRIP and Boycohort) Pubertal development, Tanner staging (STRIP and Boycohort) Testes echography (Boycohort) Pubertal hormones (STRIP and Boycohort) Implementation in DIPP data to study relationship between puberty and islet autoimmunity/diabetes HN 28.5.2018 10

Early determinants of cardiovascular, metabolic and reproductive health --- EDCaR. Harri Niinikoski, MD, PhD, Professor of Nutrition in Medicine, Department of Physiology and Pediatrics, University of Turku, Turku, Finland; STRIP study lead investigator (consortion leader). Helena Virtanen, MD, PhD, Docent of Reproductive Physiology, Department of Physiology, University of Turku, Turku, Finland; Boy Cohort investigator, management of Boy cohort data (consortion partner). Riitta Veijola, MD, PhD, Professor of Pediatrics, Department of Pediatrics, University of Oulu, Oulu, Finland; Chair of the DIPP Steering Committee (consortion partner). Suvi M. Virtanen, MD, PhD, Professor, School of Health Sciences, University of Tampere, Tampere, Finland, and Unit of Nutrition, National Institute for Health and Welfare, Helsinki, Finland;, DIPP Nutrition study lead investigator (consortion partner). Jaakko Nevalainen, PhD, Professor of Biostatistics, School of Health Sciences, University of Tampere, Finland. Statistical analyses (collaborator). Jaakko Peltonen, PhD, Associate Professor, School of Information Sciences. University of Tampere, Finland. Statistical analyses (collaborator). HN 28.5.2018 11

Q? HN 28.5.2018 12