Publications by authors named "Beng-Choon Ho"

Article Synopsis
  • Subcortical brain structures play a crucial role in various developmental and psychiatric disorders, and a study analyzed brain volumes in 74,898 individuals, identifying 254 genetic loci linked to these volumes, which accounted for up to 35% of variation.
  • The research included exploring gene expression in specific neural cell types, focusing on genes involved in intracellular signaling and processes related to brain aging.
  • The findings suggest that certain genetic variants not only influence brain volume but also have potential causal links to conditions like Parkinson’s disease and ADHD, highlighting the genetic basis for risks associated with neuropsychiatric disorders.
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Article Synopsis
  • Subcortical brain structures play a crucial role in various disorders, and a study analyzed the genetic basis of brain volumes in nearly 75,000 individuals of European ancestry, revealing 254 loci linked to these volumes.
  • The research identified significant gene expression in neural cells, relating to brain aging and signaling, and found that polygenic scores could predict brain volumes across different ancestries.
  • The study highlights genetic connections between brain volumes and conditions like Parkinson's disease and ADHD, suggesting specific gene expression patterns could be involved in neuropsychiatric disorders.
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Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test).

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Background: We investigated how low marijuana (MJ) use levels, the typical use pattern in most adolescent users, affect cognitive maturation and schizophrenia risk.

Methods: In two complementary adolescent samples where the majority reported minimal MJ use, we compared cognitive performances before and after MJ use initiation. The Iowa sample (40 first-degree relatives and 54 second-degree relatives of patients with schizophrenia and 117 control subjects with no schizophrenia family history) underwent a battery of standardized neuropsychological tests at 0, 18, and 36 months.

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Importance: Proton magnetic resonance spectroscopy (1H-MRS) studies indicate that altered brain glutamatergic function may be associated with the pathophysiology of schizophrenia and the response to antipsychotic treatment. However, the association of altered glutamatergic function with clinical and demographic factors is unclear.

Objective: To assess the associations of age, symptom severity, level of functioning, and antipsychotic treatment with brain glutamatergic metabolites.

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Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness.

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Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry.

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Background: Schizophrenia (SZ) patients and their biological relatives are more impulsive than controls. Although greater impulsivity in SZ has been associated with dysfunction in prefrontal neural circuits implicated in reward processing, little is known regarding brain structural correlates of heightened impulsivity in unaffected adolescent relatives of SZ patients.

Methods: Impulsive decision-making was assessed using the delay discounting task in 174 adolescents: 36 first-degree relatives (FDR) and 50 second-degree relatives (SDR) of SZ patients, and 88 healthy controls with no SZ family history (NSFH).

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Article Synopsis
  • Subcortical brain structures play key roles in motion, emotions, learning, and consciousness, and their volumes are influenced by genetic variations.
  • A study analyzed nearly 40,000 individuals, discovering that variations in the volumes of key brain regions are heritable and identified 48 genetic loci linked to these volumes, with 40 being previously unknown.
  • The identified genes are connected to various biological processes, suggesting they could be crucial for understanding brain development, neurological disorders, and possible drug targets.
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Genetic factors are known to influence both risk for schizophrenia (SZ) and variation in brain structure. A pressing question is whether the genetic underpinnings of brain phenotype and the disorder overlap. Using multivariate analytic methods and focusing on 1,402 common single-nucleotide polymorphisms (SNPs) mapped from the Psychiatric Genomics Consortium (PGC) 108 regions, in 777 discovery samples, we identified 39 SNPs to be significantly associated with SZ-discriminating gray matter volume (GMV) reduction in inferior parietal and superior temporal regions.

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Objective: Although schizophrenia is not a prototypic impulse-control disorder, patients report more impulsive behaviors, have higher rates of substance use, and show dysfunction in brain circuits that underlie impulsivity. We investigate impulsivity in unaffected biological relatives of schizophrenia patients to further understand the relationships between schizophrenia risk and impulse control during adolescence.

Method: Group differences in impulsivity (UPPS-P Impulsive Behavior Scale and delay discounting) were tested in 210 adolescents contrasting 39 first- and 53 second-degree biological relatives of schizophrenia patients, and 118 subjects with no schizophrenia family history (NSFH).

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Article Synopsis
  • - The hippocampal formation is crucial for memory, navigation, and stress response, and its structural abnormalities are linked to various neuropsychiatric disorders.
  • - A genome-wide association study involving over 33,000 individuals identified six genetic loci related to hippocampal volume, including four that are new discoveries associated with specific genes.
  • - The study also reveals that genetic variants that result in smaller hippocampal volumes correlate with a higher risk of developing Alzheimer's disease, highlighting potential biological pathways related to mental health.
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Schizophrenia is a psychiatric disorder with high heritability. Recent genome-wide association studies have provided a list of risk loci reliably derived from unprecedentedly large samples. However, further delineation of the diagnosis-associated susceptibility variants is needed to better characterize the genetic architecture given the disease's complex nature.

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Currently available treatments have limited efficacy in remediating cognitive impairment in schizophrenia. Efforts to facilitate cognition-enhancing drug discovery recommend the use of varied experimental cognitive paradigms (including relational memory) as assessment tools in clinical drug trials. Although relational memory deficits are increasingly being recognized as a reliable cognitive marker of schizophrenia, relational memory performance among unaffected biological relatives remains unknown.

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The adolescent brain undergoes extensive structural white matter (WM) changes. Adolescence is also a critical time period during which cognitive, emotional and social maturation occurs in transition into adulthood. Compared to adults, adolescents are generally more impulsive with increased risk-taking behaviors.

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Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia.

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Objectives: Schizophrenia is a highly disabling psychiatric disorder with a heterogeneous phenotypic appearance. We aimed to further the understanding of some of the underlying genetics of schizophrenia, using left superior temporal gyrus (STG) grey matter thickness reduction as an endophenoptype in a genome-wide association (GWA) study.

Methods: Structural magnetic resonance imaging (MRI) and genetic data of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia were used to analyse the interaction effects between 1,067,955 single nucleotide polymorphisms (SNPs) and disease status on left STG thickness in 126 healthy controls and 113 patients with schizophrenia.

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Disruptions in white matter (WM) tract structures have been implicated consistently in the pathophysiology of schizophrenia. Global WM integrity--as measured by fractional anisotropy (FA)--is highly heritable and may provide a good endophenotype for genetic studies of schizophrenia. WM abnormalities in schizophrenia are not localized to one specific brain region but instead reflect global low-level decreases in FA coupled with focal abnormalities.

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The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts.

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Background: Cognitive deficits are prominent in schizophrenia and represent promising endophenotypes for genetic research.

Methods: The current study investigated the importance of two conceptually distinct genetic aggregates, one based on copy number variations (uncommon deletion burden), and one based on single nucleotide polymorphisms identified in recent risk studies (genetic risk score). The impact of these genetic factors, and their interaction, was examined on cognitive endophenotypes defined by principal component analysis (PCA) in a multi-center sample of 50 patients with schizophrenia and 86 controls.

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The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects.

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The neural mechanisms underlying genetic risk for schizophrenia, a highly heritable psychiatric condition, are still under investigation. New schizophrenia risk genes discovered through genome-wide association studies (GWAS), such as neurogranin (NRGN), can be used to identify these mechanisms. In this study we examined the association of two common NRGN risk single nucleotide polymorphisms (SNPs) with functional and structural brain-based intermediate phenotypes for schizophrenia.

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One application of imaging genomics is to explore genetic variants associated with brain structure and function, presenting a new means of mapping genetic influences on mental disorders. While there is growing interest in performing genome-wide searches for determinants, it remains challenging to identify genetic factors of small effect size, especially in limited sample sizes. In an attempt to address this issue, we propose to take advantage of a priori knowledge, specifically to extend parallel independent component analysis (pICA) to incorporate a reference (pICA-R), aiming to better reveal relationships between hidden factors of a particular attribute.

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