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The 22q11.2 deletion syndrome (22q11DS) is associated with a 20-25% risk of schizophrenia. In a cohort of 962 individuals with 22q11DS, we examined the shared genetic basis between schizophrenia and schizophrenia-related early trajectory phenotypes: sub-threshold symptoms of psychosis, low baseline intellectual functioning and cognitive decline. We studied the association of these phenotypes with two polygenic scores, derived for schizophrenia and intelligence, and evaluated their use for individual risk prediction in 22q11DS. Polygenic scores were not only associated with schizophrenia and baseline intelligence quotient (IQ), respectively, but schizophrenia polygenic score was also significantly associated with cognitive (verbal IQ) decline and nominally associated with sub-threshold psychosis. Furthermore, in comparing the tail-end deciles of the schizophrenia and IQ polygenic score distributions, 33% versus 9% of individuals with 22q11DS had schizophrenia, and 63% versus 24% of individuals had intellectual disability. Collectively, these data show a shared genetic basis for schizophrenia and schizophrenia-related phenotypes and also highlight the future potential of polygenic scores for risk stratification among individuals with highly, but incompletely, penetrant genetic variants.
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http://dx.doi.org/10.1038/s41591-020-1103-1 | DOI Listing |
Background: Schizotypy (ST) and psychotic-like experiences and negative symptoms (PENS) are commonly used phenotypes in high-risk and early intervention research for schizophrenia and other non-affective psychoses. However, the origin of these phenotypes in the general population is poorly understood and their association with the genetic predisposition to psychoses has not yet been proven.
Aim: The aim of this study is to answer the question of whether data on the relations of ST and PENS with polygenic risk scores for schizophrenia (SZ-PRS) support the hypothesis that these phenotypes are subclinical manifestations of genetic liability for schizophrenia.
Ann Clin Transl Neurol
September 2025
23andMe, Inc., Sunnyvale, California, USA.
Objective: To examine the associations of LRRK2 p.G2019S, GBA1 p.N409S, polygenic risk scores (PRS), and APOE E4 on PD penetrance, risk, and symptoms.
View Article and Find Full Text PDFDev Psychopathol
September 2025
Faculty of Behavioral and Social Sciences, Department of Pedagogy and Educational Sciences, University of Groningen, Groningen, the Netherlands.
Despite the growing body of research on the intergenerational transmission of problem behavior, there is a need for more integrative approaches that consider the interplay between genetic and environmental factors. This study uses unique longitudinal data from TRAILS (analytic sample = 2202), a prospective multiple-generation cohort study in the Netherlands to examine whether parents' problem behavior (parents' self-reported lifetime antisocial behavior and substance use, reported at mean age 40 years) predicts offspring problem behavior nearly two decades later (offspring self-reported aggression and delinquency at mean ages 29 and 32 years). In path analyses, independent and relative contributions of genetic (polygenic scores of parents and offspring) and environmental (harsh parenting) pathways were tested.
View Article and Find Full Text PDFJ Alzheimers Dis
September 2025
Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
Genetic risk prediction for Alzheimer's disease (AD) has high potential impact, yet few studies have assessed the reliability of various polygenic risk score (PRS) methods at the individual level. Here, we evaluated the reliability of AD PRS estimates among 6338 participants from the Multi-Ethnic Study of Atherosclerosis. We compared four PRS models that have been previously associated with dementia risk.
View Article and Find Full Text PDFInvest Ophthalmol Vis Sci
September 2025
The University of Leicester Ulverscroft Eye Unit, School of Psychology and Vision Sciences, University of Leicester, Leicester, United Kingdom.
Purpose: To define the genetic architecture of foveal morphology and explore its relevance to foveal hypoplasia (FH), a hallmark of developmental macular disorders.
Methods: We applied deep-learning algorithms to quantify foveal pit depth from central optical coherence tomography (OCT) B-scans in 61,269 UK Biobank participants. A genome-wide association study (GWAS) was conducted using REGENIE, adjusting for age, sex, height, and ancestry.