Enhancing the discriminatory power of polygenic scores for ADHD and autism in clinical and non-clinical samples / James J. LI in Journal of Neurodevelopmental Disorders, 17 (2025)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 17 (2025) Titre : Enhancing the discriminatory power of polygenic scores for ADHD and autism in clinical and non-clinical samples Type de document : texte imprimé Auteurs : James J. LI, Auteur ; Quanfa HE, Auteur ; Stephen DORN, Auteur ; Zihang WANG, Auteur ; Qiongshi LU, Auteur Langues : Anglais (eng) Mots-clés : Humans  Attention Deficit Disorder with Hyperactivity/genetics/diagnosis/epidemiology  Multifactorial Inheritance/genetics  Autism Spectrum Disorder/genetics/diagnosis/epidemiology  Male  Female  Child  Adolescent  Cohort Studies  Autistic Disorder/genetics  Adhd  Asd  GenomicSEM  Neurodevelopment  Polygenic scores  Neurodevelopmental Cohort (PNC) and the Simons Foundation Powering Autism  Research for Knowledge (SPARK) datasets are both publicly available,  de-identified datasets. This study was exempt from requiring approval from the  University of Wisconsin-Madison Health Sciences Institutional Review Board (see  "Category 4" exemption: https://kb.wisc.edu/gsadminkb/page.php?id=29465 ).  Consent for publication: Not applicable. Competing interests: The authors declare  no competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their predictive power for focal outcomes. However, they lack discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD). METHODS: Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples - the Philadelphia Neurodevelopmental Cohort (N = 4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N = 5,045) cohort. RESULTS: PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes. CONCLUSIONS: Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications. En ligne : https://dx.doi.org/10.1186/s11689-025-09620-w Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=576 [article] Enhancing the discriminatory power of polygenic scores for ADHD and autism in clinical and non-clinical samples [texte imprimé] / James J. LI, Auteur ; Quanfa HE, Auteur ; Stephen DORN, Auteur ; Zihang WANG, Auteur ; Qiongshi LU, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 17 (2025) Mots-clés : Humans  Attention Deficit Disorder with Hyperactivity/genetics/diagnosis/epidemiology  Multifactorial Inheritance/genetics  Autism Spectrum Disorder/genetics/diagnosis/epidemiology  Male  Female  Child  Adolescent  Cohort Studies  Autistic Disorder/genetics  Adhd  Asd  GenomicSEM  Neurodevelopment  Polygenic scores  Neurodevelopmental Cohort (PNC) and the Simons Foundation Powering Autism  Research for Knowledge (SPARK) datasets are both publicly available,  de-identified datasets. This study was exempt from requiring approval from the  University of Wisconsin-Madison Health Sciences Institutional Review Board (see  "Category 4" exemption: https://kb.wisc.edu/gsadminkb/page.php?id=29465 ).  Consent for publication: Not applicable. Competing interests: The authors declare  no competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their predictive power for focal outcomes. However, they lack discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD). METHODS: Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples - the Philadelphia Neurodevelopmental Cohort (N = 4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N = 5,045) cohort. RESULTS: PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes. CONCLUSIONS: Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications. En ligne : https://dx.doi.org/10.1186/s11689-025-09620-w Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=576

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