József Bukszár

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidones effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

Association between glutamic acid decarboxylase genes and anxiety disorders, major depression, and neuroticism

Abnormalities in the gamma-aminobutyric acid (GABA) neurotransmitter system have been noted in subjects with mood and anxiety disorders. Glutamic acid decarboxylase (GAD) enzymes synthesize GABA from glutamate, and, thus, are reasonable candidate susceptibility genes for these conditions. In this study, we examined the GAD1 and GAD2 genes for their association with genetic risk across a range of internalizing disorders. We used multivariate structural equation modeling to identify common genetic risk factors for major depression, generalized anxiety disorder, panic disorder, agoraphobia, social phobia and neuroticism (N) in a sample of 9270 adult subjects from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. One member from each twin pair for whom DNA was available was selected as a case or control based on scoring at the extremes of the genetic factor extracted from the analysis. The resulting sample of 589 cases and 539 controls was entered into a two-stage association study in which candidate loci were screened in stage 1, the positive results of which were tested for replication in stage 2. Several of the six single-nucleotide polymorphisms tested in the GAD1 region demonstrated significant association in both stages, and a combined analysis in all 1128 subjects indicated that they formed a common high-risk haplotype that was significantly over-represented in cases (P=0.003) with effect size OR=1.23. Out of 14 GAD2 markers screened in stage 1, only one met the threshold criteria for follow-up in stage 2. This marker, plus three others that formed significant haplotype combinations in stage 1, did not replicate their association with the phenotype in stage 2. Subject to confirmation in an independent sample, our study suggests that variations in the GAD1 gene may contribute to individual differences in N and impact susceptibility across a range of anxiety disorders and major depression.

Genomewide Association Analysis Followed by a Replication Study Implicates a Novel Candidate Gene for Neuroticism

CONTEXT Neuroticism is a trait that reflects a tendency toward negative mood states. It has long been linked to internalizing psychiatric conditions, such as anxiety and depression, and it accounts for much of the substantial comorbidity seen between these disorders. OBJECTIVE To identify common genetic variants that affect neuroticism to better understand (the comorbidity between) a broad range of psychiatric disorders and to develop effective treatments. DESIGN, SETTING, AND PARTICIPANTS More than 420,000 genetic markers were tested for their association with neuroticism in a genomewide association study (GWAS). The GWAS sample consisted of 1227 healthy individuals ascertained from a US national sampling frame and available from the National Institute of Mental Health genetics repository. The most promising markers were subsequently tested in a German replication sample comprising 1880 healthy individuals. MAIN OUTCOME MEASURES A strict definition of replication (same marker, same direction of effects, and same measure) combined with a threshold we proposed previously for declaring significance in genetic studies that ensures a mean probability of producing false-positive findings of less than 10%. RESULTS The most promising results in the GWAS and replication samples were single-nucleotide polymorphisms (SNPs) in the gene MAMDC1. These SNPs all tagged the same 2 haplotypes and had P values of 10(-5) to 10(-6) in the GWAS sample and of .006 to .02 in the replication sample. Furthermore, the replication involved the same SNPs and the same direction of effects. In a combined analysis of all data, several SNPs were significant according to the threshold that allows for 10% false-positive findings. CONCLUSIONS The small effect sizes may limit the prognostic, diagnostic, and therapeutic use of SNP markers such as those in MAMDC1. However, the present study demonstrates the potential of a GWAS to discover potentially important pathogenic pathways for which clinically more powerful (bio)markers may eventually be developed.

Factor structure and external validity of the PANSS revisited

Considerable controversy exists concerning the positive and negative syndrome scale (PANSS), one of the most widely used instruments in schizophrenia research. In this article we revisited the factor structure and external validity of the PANSS in a sample of 500 participants with DSM IV diagnoses of schizophrenia. We found that a model with six latent factors provided a relatively good fit, considered adequate by two rules of thumb. Five factors corresponded closely to those typically derived in other studies: Negative, Positive, Excited/Activation, Anxious-Depressed/Dysphoric, and Disorganized/Autistic preoccupation. The sixth factor seemed to have face validity and was labeled Withdrawn. With the exception of Anxious-Depressed/Dysphoric, Cronbachs Alpha ranged from 0.70 to 0.85 suggesting an acceptable internal consistency. External validity was studied through correlations with socio-demographic variables, DSM IV (subtype) diagnoses, clinical characteristics, and drug use. The many significant correlations suggested that the six PANSS scales measure meaningful aspects of schizophrenia. Furthermore, the pattern of correlations varied, providing evidence that the scales assessed partly different aspects of the disease. Our analyses also suggested that some of the controversy about the PANSS can possibly be attributed to methodological factors where the substantial cross-loadings of some PANSS items may play an important role.

Genomewide Association Study of Movement-Related Adverse Antipsychotic Effects

BACKGROUND Understanding individual differences in the development of extrapyramidal side effects (EPS) as a response to antipsychotic therapy is essential to individualize treatment. METHODS We performed genomewide association studies to search for genetic susceptibility to EPS. Our sample consisted of 738 schizophrenia patients, genotyped for 492K single nucleotide polymorphisms (SNPs). We studied three quantitative measures of antipsychotic adverse drug reactions-the Simpson-Angus Scale (SAS) for Parkinsonism, the Barnes Akathisia Rating Scale, and the Abnormal Involuntary Movement Scale (AIMS)-as well as a clinical diagnosis of probable tardive dyskinesia. RESULTS Two SNPs for SAS, rs17022444 and rs2126709 with p = 1.2 x 10(-10) and p = 3.8 x 10(-7), respectively, and one for AIMS, rs7669317 with p = 7.7 x 10(-8), reached genomewide significance (Q value < .1). rs17022444 and rs7669317 were located in intergenic regions and rs2126709 was located in ZNF202 on 11q24. Fourteen additional signals were potentially interesting (Q value < .5). The ZNF202 is a transcriptional repressor controlling, among other genes, PLP1, which is the major protein in myelin. Mutations in PLP1 cause Pelizaeus-Merzbacher disease, which has Parkinsonism as an occurring symptom. Altered mRNA expression of PLP1 is associated with schizophrenia. CONCLUSIONS Although our findings require replication and validation, this study demonstrates the potential of genomewide association studies to discover genes and pathways that mediate adverse effects of antipsychotics.

Genome-Wide Pharmacogenomic Study of Neurocognition As an Indicator of Antipsychotic Treatment Response in Schizophrenia

Neurocognitive deficits are a core feature of schizophrenia and, therefore, represent potentially critical outcome variables for assessing antipsychotic treatment response. We performed genome-wide association studies (GWAS) with 492K single nucleotide polymorphisms (SNPs) in a sample of 738 patients with schizophrenia from the Clinical Antipsychotic Trials of Intervention Effectiveness study. Outcome variables consisted of a neurocognitive battery administered at multiple time points over an 18-month period, measuring processing speed, verbal memory, vigilance, reasoning, and working memory domains. Genetic mediation of improvements in each of these five domains plus a composite neurocognitive measure was assessed for each of five antipsychotics (olanzapine, perphenazine, quetiapine, risperidone, and ziprasidone). Six SNPs achieved genome-wide significance using a pre-specified threshold that ensures, on average, only 1 in 10 findings is a false discovery. These six SNPs were located within, or in close proximity to, genes EHF, SLC26A9, DRD2, GPR137B, CHST8, and IL1A. The more robust findings, that is those significant across multiple neurocognitive domains and having adjacent SNPs showing evidence for association, were rs286913 at the EHF gene (p-value 6.99 × 10−8, q-value 0.034, mediating the effects of ziprasidone on vigilance), rs11240594 at SLC26A9 (p-value 1.4 × 10−7, q-value 0.068, mediating the effects of olanzapine on processing speed), and rs11677416 at IL1A (p-value 6.67 × 10−7, q-value 0.081, mediating the effects of olanzapine on working memory). This study has generated several novel candidate genes for antipsychotic response. However, our findings will require replication and functional validation. To facilitate replication efforts, we provide all GWAS p-values for download.

Catechol-O-methyltransferase contributes to genetic susceptibility shared among anxiety spectrum phenotypes.

BACKGROUND Catechol-O-methyltransferase (COMT) has been investigated for its possible role in a wide range of psychiatric phenotypes. In particular, several studies support association of this gene with panic disorder and other anxiety-related traits. METHODS We examined the COMT gene for association with genetic risk across a range of anxiety spectrum phenotypes. We used multivariate structural equation modeling to select twin pairs scoring at the extremes of a latent genetic risk factor shared by neuroticism, several anxiety disorders, and major depression from a large population-based twin sample. With one member from each of these pairs, the resulting sample of 589 cases and 539 control subjects were entered into a two-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2. RESULTS The functional val158met polymorphism (rs4680) plus nine other single nucleotide polymorphism markers selected to capture the major allelic variation across the COMT locus were analyzed for differences between cases and control subjects. Although the val (G) allele of rs4680 showed marginally significant association in our combined stage 1 plus stage 2 sample, a high-risk haplotype of this allele with the A allele of rs165599 was significantly over-represented in cases (p = 1.97e-5, odds ratio = 1.95). This haplotype also predicted individual differences in neuroticism and risk for several anxiety disorders and major depression. Consistent with prior studies, our findings are female-specific. CONCLUSIONS Variations in the COMT gene contribute to genetic risk shared across a range of anxiety-related phenotypes.

Genome-wide association study of antipsychotic induced QTc interval prolongation

QT prolongation is associated with increased risk of cardiac arrhythmias. Identifying the genetic variants that mediate antipsychotic-induced prolongation may help to minimize this risk, which might prevent the removal of efficacious drugs from the market. We performed candidate gene analysis and five drug-specific genome-wide association studies (GWASs) with 492K single-nucleotide polymorphisms to search for genetic variation mediating antipsychotic-induced QT prolongation in 738 schizophrenia patients from the Clinical Antipsychotic Trial of Intervention Effectiveness study. Our candidate gene study suggests the involvement of NOS1AP and NUBPL (P-values=1.45 × 10−05 and 2.66 × 10−13, respectively). Furthermore, our top GWAS hit achieving genome-wide significance, defined as a Q-value <0.10 (P-value=1.54 × 10−7, Q-value=0.07), located in SLC22A23, mediated the effects of quetiapine on prolongation. SLC22A23 belongs to a family of organic ion transporters that shuttle a variety of compounds, including drugs, environmental toxins and endogenous metabolites, across the cell membrane. This gene is expressed in the heart and is integral in mouse heart development. The genes mediating antipsychotic-induced QT prolongation partially overlap with the genes affecting normal QT interval variation. However, some genes may also be unique for drug-induced prolongation. This study demonstrates the potential of GWAS to discover genes and pathways that mediate antipsychotic-induced QT prolongation.

MBD-seq as a cost-effective approach for methylome-wide association studies: demonstration in 1500 case–control samples

AIM We studied the use of methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq) as a cost-effective screening tool for methylome-wide association studies (MWAS). MATERIALS & METHODS Because MBD-seq has not yet been applied on a large scale, we first developed and tested a pipeline for data processing using 1500 schizophrenia cases and controls plus 75 technical replicates with an average of 68 million reads per sample. This involved the use of technical replicates to optimize quality control for multi- and duplicate-reads, an in silico experiment to identify CpGs in loci with alignment problems, CpG coverage calculations based on multiparametric estimates of the fragment size distribution, a two-stage adaptive algorithm to combine data from correlated adjacent CpG sites, principal component analyses to control for confounders and new software tailored to handle the large data set. RESULTS We replicated MWAS findings in independent samples using a different technology that provided single base resolution. In an MWAS of age-related methylation changes, one of our top findings was a previously reported robust association involving GRIA2. Our results also suggested that owing to the many confounding effects, a considerable challenge in MWAS is to identify those effects that are informative about disease processes. CONCLUSION This study showed the potential of MBD-seq as a cost-effective tool in large-scale disease studies.

Probability Bounds with Cherry Trees

A third order upper bound is presented on the probability of the union of a finite number of events, by means of graphs called cherry trees. These are graphs that we construct recursively in such a way that every time we pick a new vertex, connect it with two already existing vertices. If the latters are always adjacent, we call the cherry tree a t-cherry tree. A cherry tree has a weight that provides us with the upper bound on the union. Any Hunter-Worsley bound can be majorized by a t-cherry bound constructed by the use of the Hunter-Worsley tree. A cherry tree bound can be identified as a feasible solution to the dual of the Boolean probability bounding problem. A t-cherry tree bound can be identified as the objective function value of the dual vector corresponding to a dual feasible basis in the Boolean problem. This enables us to improve on the bound algorithmically, if we use the dual method of linear programming.