Development of a genetic risk score to predict the risk of hypertension in European adolescents from the HELENA study

Introduction From genome wide association study (GWAS) a large number of single nucleotide polymorphisms (SNPs) have previously been associated with blood pressure (BP) levels. A combination of SNPs, forming a genetic risk score (GRS) could be considered as a useful genetic tool to identify individuals at risk of developing hypertension from early stages in life. Therefore, the aim of our study was to build a GRS being able to predict the genetic predisposition to hypertension (HTN) in European adolescents. Methods Data were extracted from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study. A total of 869 adolescents (53% female), aged 12.5–17.5, with complete genetic and BP information were included. The sample was divided into altered (≥130 mmHg for systolic and/or ≥80 mmHg for diastolic) or normal BP. Based on the literature, a total of 1.534 SNPs from 57 candidate genes related with BP were selected from the HELENA GWAS database. Results From 1,534 SNPs available, An initial screening of SNPs univariately associated with HTN (p < 0.10) was established, to finally obtain a number of 16 SNPs significantly associated with HTN (p < 0.05) in the multivariate model. The unweighted GRS (uGRS) and weighted GRS (wGRS) were estimated. To validate the GRSs, the area under the curve (AUC) was explored using ten-fold internal cross-validation for uGRS (0.802) and wGRS (0.777). Further covariates of interest were added to the analyses, obtaining a higher predictive ability (AUC values of uGRS: 0.879; wGRS: 0.881 for BMI z-score). Furthermore, the differences between AUCs obtained with and without the addition of covariates were statistically significant (p < 0.05). Conclusions Both GRSs, the uGRS and wGRS, could be useful to evaluate the predisposition to hypertension in European adolescents.

[1]  I. Huybrechts,et al.  High Fructose Intake Contributes to Elevated Diastolic Blood Pressure in Adolescent Girls: Results from The HELENA Study , 2021, Nutrients.

[2]  G. Messina,et al.  Obesity-Related Hypertension in Pediatrics, the Impact of American Academy of Pediatrics Guidelines , 2021, Nutrients.

[3]  N. Allen,et al.  Blood Pressure Trajectories Across the Life Course. , 2021, American journal of hypertension.

[4]  John E. Hall,et al.  Obesity, kidney dysfunction and inflammation: interactions in hypertension. , 2020, Cardiovascular research.

[5]  H. Snieder,et al.  Genetic Risk Scores for Complex Disease Traits in Youth , 2020, Circulation. Genomic and precision medicine.

[6]  L. Moreno,et al.  Energy Dense Salty Food Consumption Frequency Is Associated with Diastolic Hypertension in Spanish Children , 2020, Nutrients.

[7]  N. Mohammadifard,et al.  Essential hypertension in children, a growing worldwide problem , 2019, Journal of Research in Medical Sciences.

[8]  P. Munroe,et al.  Over 1,000 genetic loci influencing blood pressure with multiple systems and tissues implicated. , 2019, Human molecular genetics.

[9]  K. Rahimi,et al.  Global Prevalence of Hypertension in Children: A Systematic Review and Meta-analysis. , 2019, JAMA pediatrics.

[10]  L. Smeeth,et al.  A genome‐wide association and replication study of blood pressure in Ugandan early adolescents , 2019, Molecular genetics & genomic medicine.

[11]  C. Forsblom,et al.  CACNB2 Is a Novel Susceptibility Gene for Diabetic Retinopathy in Type 1 Diabetes , 2019, Diabetes.

[12]  C. Maffeis,et al.  Relation between Dietary Habits, Physical Activity, and Anthropometric and Vascular Parameters in Children Attending the Primary School in the Verona South District , 2019, Nutrients.

[13]  Christian Gieger,et al.  Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits , 2018, Nature Genetics.

[14]  V. Lesauskaitė,et al.  Association between ATP2B1 and CACNB2 polymorphisms and high blood pressure in a population of Lithuanian children and adolescents: a cross-sectional study , 2018, BMJ Open.

[15]  S. Ahn,et al.  Genetic Programming of Hypertension , 2018, Front. Pediatr..

[16]  N. Cook,et al.  Assessment of dietary sodium intake using a food frequency questionnaire and 24‐hour urinary sodium excretion: a systematic literature review , 2017, Journal of clinical hypertension.

[17]  S. Daniels,et al.  Clinical Practice Guideline for Screening and Management of High Blood Pressure in Children and Adolescents , 2017, Pediatrics.

[18]  Andrew D. Johnson,et al.  Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney , 2017, Hypertension.

[19]  Sicheng He,et al.  Tagging SNP‐set selection with maximum information based on linkage disequilibrium structure in genome‐wide association studies , 2017, Bioinform..

[20]  Jiang He,et al.  Race and Sex Differences of Long-Term Blood Pressure Profiles From Childhood and Adult Hypertension: The Bogalusa Heart Study , 2017, Hypertension.

[21]  F. Rodríguez‐Artalejo,et al.  The association between blood pressure and lipid levels in Europe: European Study on Cardiovascular Risk Prevention and Management in Usual Daily Practice , 2016, Journal of hypertension.

[22]  Zhanxiang Wang,et al.  A meta-analytical assessment of STK39 three well-defined polymorphisms in susceptibility to hypertension , 2016, Scientific Reports.

[23]  J. Staessen,et al.  STK39 and WNK1 Are Potential Hypertension Susceptibility Genes in the BELHYPGEN Cohort , 2016, Medicine.

[24]  M. Jarvelin,et al.  International Genome-Wide Association Study Consortium Identifies Novel Loci Associated With Blood Pressure in Children and Adolescents , 2016, Circulation. Cardiovascular genetics.

[25]  R. Motzer,et al.  A case for the use of receiver operating characteristic analysis of potential clinical efficacy biomarkers in advanced renal cell carcinoma , 2015, Future oncology.

[26]  H. Kiat,et al.  The mechanisms underlying fructose-induced hypertension: a review , 2015, Journal of hypertension.

[27]  Inge Huybrechts,et al.  Nutrition and lifestyle in european adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) study. , 2014, Advances in nutrition.

[28]  G. Chandak,et al.  FTO gene variant and risk of hypertension: a meta-analysis of 57,464 hypertensive cases and 41,256 controls. , 2014, Metabolism: clinical and experimental.

[29]  G. Kaspers,et al.  Why pediatricians fail to diagnose hypertension: a multicenter survey. , 2013, The Journal of pediatrics.

[30]  D. Lawlor,et al.  Genetic Influences on Trajectories of Systolic Blood Pressure Across Childhood and Adolescence , 2013, Circulation. Cardiovascular genetics.

[31]  Alison A. Motsinger-Reif,et al.  Evaluation of genetic risk score models in the presence of interaction and linkage disequilibrium , 2013, Front. Genet..

[32]  L. Peltonen,et al.  A Blood Pressure Genetic Risk Score Is a Significant Predictor of Incident Cardiovascular Events in 32 669 Individuals , 2013, Hypertension.

[33]  T. Lehtimäki,et al.  The Cardiovascular Risk in Young Finns Study , 2008 .

[34]  Y. Li Angiotensin‐converting enzyme gene insertion/deletion polymorphism and essential hypertension in the Chinese population: a meta‐analysis including 21 058 participants , 2012, Internal medicine journal.

[35]  T. Lehtimäki,et al.  Genetic Variants and Blood Pressure in a Population-Based Cohort: The Cardiovascular Risk in Young Finns Study , 2011, Hypertension.

[36]  T. Lehtimäki,et al.  Tracking of serum lipid levels, blood pressure, and body mass index from childhood to adulthood: the Cardiovascular Risk in Young Finns Study. , 2011, The Journal of pediatrics.

[37]  Christian Gieger,et al.  Genetic Variants in Novel Pathways Influence Blood Pressure and Cardiovascular Disease Risk , 2011, Nature.

[38]  Michael Sjöström,et al.  Objectively measured physical activity and sedentary time in European adolescents: the HELENA study. , 2011, American journal of epidemiology.

[39]  E. Trolle,et al.  Recommendations for a trans-European dietary assessment method in children between 4 and 14 years , 2011, European Journal of Clinical Nutrition.

[40]  Yurii S. Aulchenko,et al.  PredictABEL: an R package for the assessment of risk prediction models , 2011, European Journal of Epidemiology.

[41]  Y. Manios,et al.  Quality assurance of ethical issues and regulatory aspects relating to good clinical practices in the HELENA Cross-Sectional Study , 2008, International Journal of Obesity.

[42]  M. Ferrari,et al.  Sampling and processing of fresh blood samples within a European multicenter nutritional study: evaluation of biomarker stability during transport and storage , 2008, International Journal of Obesity.

[43]  Y. Manios,et al.  Socioeconomic questionnaire and clinical assessment in the HELENA Cross-Sectional Study: methodology , 2008, International Journal of Obesity.

[44]  M. Sjöström,et al.  Design and implementation of the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study , 2008, International Journal of Obesity.

[45]  M. Daly,et al.  Estimation of the multiple testing burden for genomewide association studies of nearly all common variants , 2008, Genetic epidemiology.

[46]  U. Ekelund,et al.  Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study , 2007, Diabetologia.

[47]  Nancy J. Brown,et al.  β-2 Adrenergic Receptor Diplotype Defines a Subset of Salt-Sensitive Hypertension , 2006 .

[48]  R. Asmar,et al.  Validation of two automatic devices for self-measurement of blood pressure according to the International Protocol of the European Society of Hypertension: the Omron M6 (HEM-7001-E) and the Omron R7 (HEM 637-IT) , 2006, Blood pressure monitoring.

[49]  Patty Freedson,et al.  Calibration of accelerometer output for children. , 2005, Medicine and science in sports and exercise.

[50]  C. Matthys,et al.  Young adolescents' nutrition assessment on computer (YANA-C) , 2005, European Journal of Clinical Nutrition.

[51]  G. Willemsen,et al.  Heritability of Daytime Ambulatory Blood Pressure in an Extended Twin Design , 2005, Hypertension.

[52]  J. Ott,et al.  Association of common variants in/near six genes (ATP2B1, CSK, MTHFR, CYP17A1, STK39 and FGF5) with blood pressure/hypertension risk in Chinese children , 2014, Journal of Human Hypertension.

[53]  A. Paterson,et al.  Genome-wide scan for loci of adolescent obesity and their relationship with blood pressure. , 2012, The Journal of clinical endocrinology and metabolism.