Stephen J. Glatt

Bio: Stephen J. Glatt is an academic researcher from State University of New York Upstate Medical University. The author has contributed to research in topics: Bipolar disorder & Schizophrenia. The author has an hindex of 48, co-authored 173 publications receiving 16381 citations. Previous affiliations of Stephen J. Glatt include Syracuse University & Massachusetts Mental Health Center.

Analysis of protein-coding genetic variation in 60,706 humans

Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Abstract: Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies. A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

Hypomethylation of MB-COMT promoter is a major risk factor for schizophrenia and bipolar disorder

Abstract: The variability in phenotypic presentations and the lack of consistency of genetic associations in mental illnesses remain a major challenge in molecular psychiatry. Recently, it has become increasingly clear that altered promoter DNA methylation could play a critical role in mediating differential regulation of genes and in facilitating short-term adaptation in response to the environment. Here, we report the investigation of the differential activity of membrane-bound catechol-O-methyltransferase (MB-COMT) due to altered promoter methylation and the nature of the contribution of COMT Val158Met polymorphism as risk factors for schizophrenia and bipolar disorder by analyzing 115 post-mortem brain samples from the frontal lobe. These studies are the first to reveal that the MB-COMT promoter DNA is frequently hypomethylated in schizophrenia and bipolar disorder patients, compared with the controls (methylation rate: 26 and 29 versus 60%; P = 0.004 and 0.008, respectively), particularly in the left frontal lobes (methylation rate: 29 and 30 versus 81%; P = 0.003 and 0.002, respectively). Quantitative gene-expression analyses showed a corresponding increase in transcript levels of MB-COMT in schizophrenia and bipolar disorder patients compared with the controls (P = 0.02) with an accompanying inverse correlation between MB-COMT and DRD1 expression. Furthermore, there was a tendency for the enrichment of the Val allele of the COMT Val158Met polymorphism with MB-COMT hypomethylation in the patients. These findings suggest that MB-COMT over-expression due to promoter hypomethylation and/or hyperactive allele of COMT may increase dopamine degradation in the frontal lobe providing a molecular basis for the shared symptoms of schizophrenia and bipolar disorder.

Hypermethylation of the reelin (RELN) promoter in the brain of schizophrenic patients: a preliminary report.

Abstract: DNA methylation changes could provide a mechanism for DNA plasticity and dynamism for short-term adaptation, enabling a type of cell memory to register cellular history under different environmental conditions. Some environmental insults may also result in pathological methylation with corresponding alteration of gene expression patterns. Evidence from several studies has suggested that in schizophrenia and bipolar disorder, mRNA of the reelin gene (RELN), which encodes a protein necessary for neuronal migration, axonal branching, synaptogenesis, and cell signaling, is severely reduced in post-mortem brains. Therefore, we investigated the methylation status of the RELN promoter region in schizophrenic patients and normal controls as a potential mechanism for down regulation of its expression. Ten post-mortem frontal lobe brain samples from male schizophrenic patients and normal controls were obtained from the Harvard Brain Tissue Resources Center. DNA was extracted using a standard phenol–chloroform DNA extraction protocol. To evaluate differences between patients and controls, we applied methylation specific PCR (MSP) using primers localized to CpG islands flanking a potential cyclic AMP response element (CRE) and a stimulating protein-1 (SP1) binding site located in the promoter region. For each sample, DNA extraction, bisulfite treatment, and MSP were independently repeated at least four times to accurately determine the methylation status of the target region. Forty-three PCR trials were performed on the test and control samples. MSP analysis of the RELN promoter revealed an unmethylated signal in all reactions (43 of 43) using DNA from the frontal brain tissue, derived from either the schizophrenic patients or normal controls indicating that this region of the RELN promoter is predominantly unmethylated. However, we observed a distinct methylated signal in 73% of the trials (16 of 22) in schizophrenic patients compared with 24% (5 of 21) of controls. Thus, the hypermethylation of the CpG islands flanking a CRE and SP1 binding site observed at a significantly higher level (t = −5.07, P = 0.001) may provide a mechanism for the decreased RELN expression, frequently observed in post-mortem brains of schizophrenic patients. We also found an inverse relationship between the level of DNA methylation using MSP analysis and the expression of the RELN gene using semi-quantitative RT-PCR. Despite the small sample size, these studies indicate that promoter hypermethylation of the RELN gene could be a significant contributor in effecting epigenetic alterations and provides a molecular basis for the RELN gene hypoactivity in schizophrenia. Further studies with a larger sample set would be required to validate these preliminary observations. © 2005 Wiley-Liss, Inc.

Association between a functional catechol O-methyltransferase gene polymorphism and schizophrenia: meta-analysis of case-control and family-based studies.

Abstract: OBJECTIVE: There is strong evidence for a genetic contribution to schizophrenia, but efforts to identify susceptibility genes have been largely unsuccessful because of the low power of individual studies. The authors’ goal was to evaluate the collective evidence for an association between the Val158/108Met polymorphism of the catechol O-methyltransferase (COMT) gene and schizophrenia. METHOD: They performed separate meta-analyses of existing case-control and family-based association studies. RESULTS: Overall, case-control studies showed no indication of an association between either allele and schizophrenia, and family-based studies found modest evidence implicating the Val allele in schizophrenia risk. The pooled analyses of studies from diverse geographical regions may have obscured ethnic differences in patterns of genetic risk for schizophrenia. Stratification of the studies by ethnicity of the subjects yielded evidence for an association with the Val allele in case-control studies of European samples...

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

The mutational constraint spectrum quantified from variation in 141,456 humans

Abstract: Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases. A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.

The UK Biobank resource with deep phenotyping and genomic data

Abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

Genetic effects on gene expression across human tissues.

Abstract: Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.