Beng-Choon Ho

Bio: Beng-Choon Ho is an academic researcher from Roy J. and Lucille A. Carver College of Medicine. The author has contributed to research in topics: Schizophrenia & Psychosis. The author has an hindex of 46, co-authored 97 publications receiving 10329 citations. Previous affiliations of Beng-Choon Ho include University of Iowa Hospitals and Clinics & VU University Amsterdam.

Predictive Values of Neurocognition and Negative Symptoms on Functional Outcome in Schizophrenia: A Longitudinal First-Episode Study With 7-Year Follow-Up

Abstract: Objective: The relationship between cognition and outcome in people with schizophrenia has been established in studies that, for the most part, examined chronic patients and were cross-sectional in design. The purpose of this study was to analyze the relationships between neurocognitive variables assessed at illness onset and functional outcome in a longitudinal design. An additional area of interest was whether the severity of negative symptoms would predict outcome independently from neurocognitive variables or whether there would be an overlap in their predictive power. Method: The authors administered a comprehensive cognitive battery and clinical assessments to 99 subjects who were in their first episode of illness and analyzed the relationship of cognition and symptom severity at intake with community outcome after an average follow-up period of 7 years. Results: Verbal memory, processing speed and attention, and the severity of negative symptoms at intake were related to subsequent outcome. Global psychosocial functioning was predicted by negative symptoms and attention. Verbal memory was the significant predictor of the degree of impairment in recreational activities. Impairment in relationships was predicted by negative symptoms and memory, whereas attention and negative symptoms were predictive of work performance. There was an overlap in the variance in outcome explained by cognitive variables and negative symptoms. Conclusions: Verbal memory and processing speed and attention are potential targets for psychosocial interventions to improve outcome. Results from cross-sectional or chronic patient studies do not necessarily correspond to the findings of this prospective first-episode study in which cognition appears to explain less of the variance in outcome.

Long-term Antipsychotic Treatment and Brain Volumes: A Longitudinal Study of First-Episode Schizophrenia

Abstract: Context Progressive brain volume changes in schizophrenia are thought to be due principally to the disease. However, recent animal studies indicate that antipsychotics, the mainstay of treatment for schizophrenia patients, may also contribute to brain tissue volume decrement. Because antipsychotics are prescribed for long periods for schizophrenia patients and have increasingly widespread use in other psychiatric disorders, it is imperative to determine their long-term effects on the human brain. Objective To evaluate relative contributions of 4 potential predictors (illness duration, antipsychotic treatment, illness severity, and substance abuse) of brain volume change. Design Predictors of brain volume changes were assessed prospectively based on multiple informants. Setting Data from the Iowa Longitudinal Study. Patients Two hundred eleven patients with schizophrenia who underwent repeated neuroimaging beginning soon after illness onset, yielding a total of 674 high-resolution magnetic resonance scans. On average, each patient had 3 scans (≥2 and as many as 5) over 7.2 years (up to 14 years). Main Outcome Measure Brain volumes. Results During longitudinal follow-up, antipsychotic treatment reflected national prescribing practices in 1991 through 2009. Longer follow-up correlated with smaller brain tissue volumes and larger cerebrospinal fluid volumes. Greater intensity of antipsychotic treatment was associated with indicators of generalized and specific brain tissue reduction after controlling for effects of the other 3 predictors. More antipsychotic treatment was associated with smaller gray matter volumes. Progressive decrement in white matter volume was most evident among patients who received more antipsychotic treatment. Illness severity had relatively modest correlations with tissue volume reduction, and alcohol/illicit drug misuse had no significant associations when effects of the other variables were adjusted. Conclusions Viewed together with data from animal studies, our study suggests that antipsychotics have a subtle but measurable influence on brain tissue loss over time, suggesting the importance of careful risk-benefit review of dosage and duration of treatment as well as their off-label use.

Common genetic variants influence human subcortical brain structures.

Abstract: 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. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Abstract: 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. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Integrative analysis of 111 reference human epigenomes

Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Remission in Schizophrenia: Proposed Criteria and Rationale for Consensus

Abstract: New advances in the understanding of schizophrenia etiology, course, and treatment have increased interest on the part of patients, families, advocates, and professionals in the development of consensus-defined standards for clinical status and improvement, including illness remission and recovery As demonstrated in the area of mood disorders, such standards provide greater clarity around treatment goals, as well as an improved framework for the design and comparison of investigational trials and the subsequent evaluation of the effectiveness of interventions Unlike the approach to mood disorders, however, the novel application of the concept of standard outcome criteria to schizophrenia must reflect the wide heterogeneity of its long-term course and outcome, as well as the variable effects of different treatments on schizophrenia symptoms As an initial step in developing operational criteria, an expert working group reviewed available definitions and assessment instruments to provide a conceptual framework for symptomatic, functional, and cognitive domains in schizophrenia as they relate to remission of illness The first consensus-based operational criteria for symptomatic remission in schizophrenia are based on distinct thresholds for reaching and maintaining improvement, as opposed to change criteria, allowing for alignment with traditional concepts of remission in both psychiatric and nonpsychiatric illness This innovative approach for standardizing the definition for outcome in schizophrenia will require further examination of its validity and utility, as well as future refinement, particularly in relation to psychosocial and cognitive function and dysfunction These criteria should facilitate research and support a positive, longer-term approach to studying outcome in patients with schizophrenia