Polygenetic components for schizophrenia, bipolar disorder and rheumatoid arthritis predict risk of schizophrenia

Ohi, Kazutaka; Kikuchi, Masataka; Ikeda, Masashi; Yamamori, Hidenaga; Yasuda, Yuka; Fujimoto, Michiko; Fujino, Haruo; Miura, Kenichiro; Fukunaga, Masaki; Nakaya, Akihiro; Iwata, Nakao; Hashimoto, Ryota

doi:10.1016/j.schres.2016.04.009

Cited by 16 publications

(13 citation statements)

References 11 publications

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“…However, the mean allele frequency of the GVs did not differ between these populations. Consistently with the findings of polygenic risk score studies, 16 , 17 our results suggest that the sum of the GVs contributes to the pathogenesis of schizophrenia across ethnic populations.…”

Section: Discussionsupporting

confidence: 91%

Variability of 128 schizophrenia-associated gene variants across distinct ethnic populations

et al. 2017

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Schizophrenia is a common polygenetic disease affecting 0.5–1% of individuals across distinct ethnic populations. PGC-II, the largest genome-wide association study investigating genetic risk factors for schizophrenia, previously identified 128 independent schizophrenia-associated genetic variants (GVs). The current study examined the genetic variability of GVs across ethnic populations. To assess the genetic variability across populations, the 'variability indices' (VIs) of the 128 schizophrenia-associated GVs were calculated. We used 2504 genomes from the 1000 Genomes Project taken from 26 worldwide healthy samples comprising five major ethnicities: East Asian (EAS: n=504), European (EUR: n=503), African (AFR: n=661), American (AMR: n=347) and South Asian (SAS: n=489). The GV with the lowest variability was rs36068923 (VI=1.07). The minor allele frequencies (MAFs) were 0.189, 0.192, 0.256, 0.183 and 0.194 for EAS, EUR, AFR, AMR and SAS, respectively. The GV with the highest variability was rs7432375 (VI=9.46). The MAFs were 0.791, 0.435, 0.041, 0.594 and 0.508 for EAS, EUR, AFR, AMR and SAS, respectively. When we focused on the EAS and EUR population, the allele frequencies of 86 GVs significantly differed between the EAS and EUR (P<3.91 × 10−4). The GV with the highest variability was rs4330281 (P=1.55 × 10−138). The MAFs were 0.023 and 0.519 for the EAS and EUR, respectively. The GV with the lowest variability was rs2332700 (P=9.80 × 10−1). The MAFs were similar between these populations (that is, 0.246 and 0.247 for the EAS and EUR, respectively). Interestingly, the mean allele frequencies of the GVs did not significantly differ between these populations (P>0.05). Although genetic heterogeneities were observed in the schizophrenia-associated GVs across ethnic groups, the combination of these GVs might increase the risk of schizophrenia.

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Section: Discussionsupporting

confidence: 91%

Variability of 128 schizophrenia-associated gene variants across distinct ethnic populations

et al. 2017

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“…Eye movements were recorded in 60 patients with schizophrenia and 166 healthy control participants who were recruited at Osaka University. These subjects were included in previous studies 35 – 39 . All of the subjects were of Japanese descent and were biologically unrelated.…”

Section: Methodsmentioning

confidence: 99%

“…Genotype information from the JPT (Japanese in Tokyo, Japan), CHB (Han Chinese in Beijing, China), CEU (Utah residents with ancestors from northern and western Europe) and YRI (Yoruba in Ibadan, Nigeria) in HapMap 3 was compared with our dataset to check for population stratification. Genotyping was performed as described in previous studies 35 – 39 .…”

Section: Methodsmentioning

confidence: 99%

Genome-wide Association Analysis of Eye Movement Dysfunction in Schizophrenia

Kikuchi

Miura

Morita

et al. 2018

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Eye movements are considered endophenotypes of schizophrenia. However, the genetic factors underlying eye movement are largely unknown. In this study, we explored the susceptibility loci for four eye movement scores: the scanpath length during the free viewing test (SPL), the horizontal position gain during the fast Lissajous paradigm of the smooth pursuit test (HPG), the duration of fixations during the far distractor paradigm of the fixation stability test (DF) and the integrated eye movement score of those three scores (EMS). We found 16 SNPs relevant to the HPG that were located in 3 genomic regions (1q21.3, 7p12.1 and 20q13.12) in the patient group; however, these SNPs were intronic or intergenic SNPs. To determine whether these SNPs occur in functional non-coding regions (i.e., enhancer or promoter regions), we examined the chromatin status on the basis of publicly available epigenomic data from 127 tissues or cell lines. This analysis suggested that the SNPs on 1q21.3 and 20q13.12 are in enhancer or promoter regions. Moreover, we performed an analysis of expression quantitative trait loci (eQTL) in human brain tissues using a public database. Finally, we identified significant eQTL effects for all of the SNPs at 1q21.3 and 20q13.12 in particular brain regions.

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“…Discovery of disease‐specific biomarkers or behavioral indicators with sufficient sensitivity is an important issue to improve the clinical diagnosis of mental illness. Magnetic resonance images, near‐infrared spectroscopy, genetic markers, cognitive functions, and eye movements are candidates . Of them, eye movement is representative of sensorimotor functions of the brain, and eye movement abnormalities have been reported in subjects with schizophrenia .…”

Section: Introductionmentioning

confidence: 99%

“…Magnetic resonance images, near-infrared spectroscopy, genetic markers, cognitive functions, and eye movements are candidates. [1][2][3][4][5][6] Of them, eye movement is representative of sensorimotor functions of the brain, and eye movement abnormalities have been reported in subjects with schizophrenia. [7][8][9] It has been frequently reported that subjects with schizophrenia can be successfully distinguished from healthy individuals by using eye movements.…”

Section: Introductionmentioning

confidence: 99%

Comparison of eye movements in schizophrenia and autism spectrum disorder

Shiino

Miura

Fujimoto

et al. 2019

Neuropsychopharm Rep

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Aim Eye movement abnormalities are often associated with psychiatric illness. Subjects with either schizophrenia or autism spectrum disorder (ASD) have been reported to show eye movement abnormalities. However, it is still unclear whether eye movement abnormalities in schizophrenia and in ASD have common features. This study aimed to understand the similarities/differences in eye movement abnormalities of subjects with schizophrenia and those with ASD. Methods We analyzed 75 eye movement characteristics of 83 subjects with schizophrenia, 17 subjects with ASD and 255 healthy controls that were collected during fixation, smooth pursuit and free viewing tasks using analysis of covariance with the covariates age and sex. Results We found significant effects across groups on 21 eye movement characteristics, of which 4 characteristics had large effect sizes. Post hoc multiple comparisons indicated significant differences between the subjects with schizophrenia and healthy controls across all 21 characteristics. On the other hand, no significant difference between the ASD group and healthy control group was found. Instead, the subjects with ASD showed significant differences from the subjects with schizophrenia in 5 eye movement characteristics during the free viewing and smooth pursuit eye movements. Conclusions The present results suggest that eye movement abnormalities in the subjects with ASD are different from those with schizophrenia and that the tasks in this study are suitable to detect eye movement abnormality in schizophrenia. Thus, the eye movement examinations used here may distinguish subjects with schizophrenia from those with ASD.

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Polygenetic components for schizophrenia, bipolar disorder and rheumatoid arthritis predict risk of schizophrenia

Cited by 16 publications

References 11 publications

Variability of 128 schizophrenia-associated gene variants across distinct ethnic populations

Variability of 128 schizophrenia-associated gene variants across distinct ethnic populations

Genome-wide Association Analysis of Eye Movement Dysfunction in Schizophrenia

Comparison of eye movements in schizophrenia and autism spectrum disorder

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