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Genetic Risk Scores for Complex Disease Traits in Youth.
Xie, Tian; Wang, Bin; Nolte, Ilja M; van der Most, Peter J; Oldehinkel, Albertine J; Hartman, Catharina A; Snieder, Harold.
Affiliation
  • Xie T; Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • Wang B; Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • Nolte IM; Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • van der Most PJ; Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • Oldehinkel AJ; Department of Psychiatry (A.J.O., C.A.H.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • Hartman CA; Department of Psychiatry (A.J.O., C.A.H.), University of Groningen, University Medical Center Groningen, the Netherlands.
  • Snieder H; Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands.
Circ Genom Precis Med ; 13(4): e002775, 2020 08.
Article in En | MEDLINE | ID: mdl-32527150
BACKGROUND: For most disease-related traits the magnitude of the contribution of genetic factors in adolescents remains unclear. METHODS: Twenty continuous traits related to anthropometry, cardiovascular and renal function, metabolism, and inflammation were selected from the ongoing prospective Tracking Adolescents' Individual Lives Survey cohort in the Netherlands with measurements of up to 5 waves from age 11 to 22 years (n=1354, 47.6% males) and all traits available at the third wave (mean age [SD]=16.22 [0.66]). For each trait, unweighted and weighted genetic risk scores (GRSs) were generated based on significantly associated single nucleotide polymorphisms identified from literature. The variance explained by the GRSs in adolescents were estimated by linear regression after adjustment for covariates. RESULTS: Except for ALT (alanine transaminase), all GRSs were significantly associated with their traits. The trait variance explained by the GRSs was highest for lipoprotein[a] (39.59%) and varied between 0.09% (ALT) and 18.49% (LDL [low-density lipoprotein]) for the other traits. For most traits, the variances explained in adolescents were comparable with or slightly smaller than those in adults. Significant increases of trait levels (except ALT) and increased risks for overweight/obesity (odds ratio, 6.41 [95% CI, 2.95-15.56]) and hypertension (odds ratio, 2.86 [95% CI, 1.39-6.17]) were found in individuals in the top GRS decile compared with those at the bottom decile. CONCLUSIONS: Variances explained by adult-based GRSs for disease-related traits in adolescents, although still relatively modest, were comparable with or slightly smaller than in adults offering promise for improved risk prediction at early ages.
Subject(s)
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Multifactorial Inheritance Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adolescent / Adult / Child / Female / Humans / Male Country/Region as subject: Europa Language: En Journal: Circ Genom Precis Med Year: 2020 Document type: Article Affiliation country: Netherlands Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Multifactorial Inheritance Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adolescent / Adult / Child / Female / Humans / Male Country/Region as subject: Europa Language: En Journal: Circ Genom Precis Med Year: 2020 Document type: Article Affiliation country: Netherlands Country of publication: United States