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Genome-Wide Association Studies (GWAS) of Schizophrenia (SCZ) have provided new biological insights; however, most cohorts are of European ancestry. As a result, derived polygenic risk scores (PRS) show decreased predictive power when applied to populations of different ancestries. We aimed to assess the feasibility of a large-scale data collection in Hanoi, Vietnam, contribute to international efforts to diversify ancestry in SCZ genetic research and examine the transferability of SCZ-PRS to individuals of Vietnamese Kinh ancestry. In a pilot study, 368 individuals (including 190 SCZ cases) were recruited at the Hanoi Medical University's associated psychiatric hospitals and outpatient facilities. Data collection included sociodemographic data, baseline clinical data, clinical interviews assessing symptom severity and genome-wide SNP genotyping. SCZ-PRS were generated using different training data sets: (i) European, (ii) East-Asian and (iii) trans-ancestry GWAS summary statistics from the latest SCZ GWAS meta-analysis. SCZ-PRS significantly predicted case status in Vietnamese individuals using mixed-ancestry (R2 liability = 4.9%, p = 6.83 × 10−8), East-Asian (R2 liability = 4.5%, p = 2.73 × 10−7) and European (R2 liability = 3.8%, p = 1.79 × 10−6) discovery samples. Our results corroborate previous findings of reduced PRS predictive power across populations, highlighting the importance of ancestral diversity in GWA studies. [ABSTRACT FROM AUTHOR]

Introduction: Genome-wide association studies (GWAS) have successfully revealed genetic risk variants for schizophrenia (SCZ). However, the vast majority of GWAS largely comprise European samples. As a result, the derived polygenic risk scores (PRS) show decreased predictive power when applied to non-European populations. Objectives: A long-term scientific cooperation between the Charité Universitätsmedizin Berlin and the Hanoi Medical University aims to address this limitation by recruiting a large genetic cohort of comprehensively phenotyped schizophrenia patients and controls in Vietnam. Methods: A pilot study was conducted at the Department of Psychiatry of the Medical University Hanoi in 2017. Data collection encompassed i) genome-wideSNPgenotyping of 200 schizophrenia patients and 200 control subjects ii) structured interviews to assess symptom severity (PANSS), iii) clinical parameters (e.g. duration of illness, medication) and demography. Results: SCZ-PRS of the pilot sample (N=400) were generated using different training data sets: i) European, ii) East-Asian and iii) mixed GWAS summary statistics from the Psychiatric Genomics Consortium's latest discovery sample. Most variance explained was observed using a mixed discovery sample (R2liability=0.053, p=3.11*10-8, Pd <0.5), followed by PRS based on the East-Asian summary statistics (R2liability=0.0503, p=6.78*10-8, Pd <1) and the European sample (R²liability=0.0363, p = 4.26*10-6, Pd <0.01.). Conclusions: With this pilot project we established an efficient recruitment, genotyping and data analysis pipeline. Our results corroborate previous findings indicating that transferability of PRS across populations depends on the ancestral composition of the initial discovery dataset. We therefore aim to expand data collection efforts in the future in order to improve risk prediction across diverse populations. [ABSTRACT FROM AUTHOR]

Sleep spindles are characteristic electroencephalogram (EEG) signatures of stage 2 non-rapid eye movement sleep. Implicated in sleep regulation and cognitive functioning, spindles may represent heritable biomarkers of neuropsychiatric disease. Here we characterize spindles in 11,630 individuals aged 4 to 97 years, as a prelude to future genetic studies. Spindle properties are highly reliable but exhibit distinct developmental trajectories. Across the night, we observe complex patterns of age- and frequency-dependent dynamics, including signatures of circadian modulation. We identify previously unappreciated correlates of spindle activity, including confounding by body mass index mediated by cardiac interference in the EEG. After taking account of these confounds, genetic factors significantly contribute to spindle and spectral sleep traits. Finally, we consider topographical differences and critical measurement issues. Taken together, our findings will lead to an increased understanding of the genetic architecture of sleep spindles and their relation to behavioural and health outcomes, including neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]