Restoring value to stalled Phase II compounds: the case for developing a novel compound for depression using pharmacogenetics.
Explore the source record for details and available documents.
Antidepressive Agents↗
Biomedical subjects
Richard Judson
Publications and source records attributed to Richard Judson.
New and confirmatory evidence of an association between APOE genotype and baseline C-reactive protein in dyslipidemic individuals.
We have investigated the association between APOE genotypes and C-reactive protein (CRP) levels in a cohort of approximately 600 individuals who were candidates for statin therapy. An association had been previously reported between the APOE3 allele and elevated CRP levels. That study only examined men. We have reproduced that association in men and have extended the finding to women. We also investigated the effect of the interaction between APOE genotype and hormone replacement therapy (HRT) status on CRP levels, adjusting for body mass index (BMI) and other covariates. BMI and HRT are also significant predictors of CRP, as previously reported. The effect of HRT is strong enough that the contribution of APOE genotype is no longer statistically significant among women on HRT. We also demonstrate that the presence or absence of the single SNP Cysl30Arg (which distinguishes APOE4 from APOE2 and APOE3) is sufficient to determine whether an individual is predisposed to higher or lower CRP levels. Essentially, the presence of one or two copies of APOE4 is associated with a reduction of CRP levels by approximately 34% relative to individuals with zero copies (1.73 mg/L for subjects with one or two copies versus 2.63 mg/L for subjects with zero copies of APOE4). We also tested previously reported associations between CRP levels and polymorphisms in the CRP and IL6 genes. These associations were not reproduced in our cohort.
Adolescent↗
Spectrum and prevalence of cardiac sodium channel variants among black, white, Asian, and Hispanic individuals: implications for arrhythmogenic susceptibility and Brugada/long QT syndrome genetic testing.
OBJECTIVES: The purpose of this study was to determine the prevalence and spectrum of nonsynonymous polymorphisms (amino acid variants) in the cardiac sodium channel among healthy subjects. BACKGROUND: Pathogenic mutations in the cardiac sodium channel gene, SCN5A, cause approximately 15 to 20% of Brugada syndrome (BrS1), 5 to 10% of long QT syndrome (LQT3), and 2 to 5% of sudden infant death syndrome. METHODS: Using single-stranded conformation polymorphism, denaturing high-performance liquid chromatography, and/or direct DNA sequencing, mutational analysis of the protein-encoding exons of SCN5A was performed on 829 unrelated, anonymous healthy subjects: 319 black, 295 white, 112 Asian, and 103 Hispanic. RESULTS: In addition to the four known common polymorphisms (R34C, H558R, S1103Y, and R1193Q), four relatively ethnic-specific polymorphisms were identified: R481W, S524Y, P1090L, and V1951L. Overall, 39 distinct missense variants (28 novel) were elucidated. Nineteen variants (49%) were found only in the black cohort. Only seven variants (18%) localized to transmembrane-spanning domains. Four variants (F1293S, R1512W, and V1951L cited previously as BrS1-causing mutations and S1787N previously published as a possible LQT3-causing mutation) were identified in this healthy cohort. CONCLUSIONS: This study provides the first comprehensive determination of the prevalence and spectrum of cardiac sodium channel variants in healthy subjects from four distinct ethnic groups. This compendium of SCN5A variants is critical for proper interpretation of SCN5A genetic testing and provides an essential hit list of targets for future functional studies to determine whether or not any of these variants mediate genetic susceptibility for arrhythmias in the setting of either drugs or disease.
Bundle-Branch Block↗
Using multiple drug exposure levels to optimize power in pharmacogenetic trials.
Large-scale pharmacogenetic trials testing tens to hundreds of thousands of single-nucleotide polymorphisms (SNPs) will become possible in the near future given rapidly decreasing costs of genotyping. Devising optimal designs for these trials will be a significant challenge. The author demonstrates how the level of drug exposure may strongly affect the power to detect true associations between genetic polymorphisms and drug response. An analytic model of drug response is described that is used to simulate pharmacogenetic trials. Analytical and numerical sensitivity analyses are performed on the model to demonstrate possible exposure-sensitivity behaviors. This model shows that the power to detect an association can be a nonlinear, nonmonotonic function of drug exposure. This model is further investigated using two clinical trial designs. The conclusion is that trial designs that use more than one drug exposure or dose will have an increased likelihood of discovering statistically significant pharmacogenetic associations.
Computer Simulation↗
Genome-wide evaluation of the public SNP databases.
The public SNP databases are an important resource for groups performing genetic association and linkage studies. Both academic and commercial groups are developing large numbers of genotyping assays for SNPs in candidate genes or spread across the genome. These databases now contain in excess of 6 million SNPs that have been generated using a large number of methods and cohorts. Today, however, only a small fraction of these SNPs are well characterized and validated. The latest release of dbSNP contains approximately 3.7 million non-redundant entries, only 0.5 million of which are validated, and 0.2 million of which have frequency information. Users of these databases have several common questions. How many of the SNPs are real? What is the frequency spectrum of the SNPs in these databases? What is the distribution picture of these SNPs across different ethnic and geographical populations? What fraction of the total number of SNPs is already captured by these databases? In order to address these questions, we compared the public SNPs against a well-characterized collection of gene-centric SNPs that we have developed. From this comparison, we find that > 50% of high frequency SNPs in the genome (> 20% minor allele frequency) have already been captured by these databases. The coverage drops dramatically below frequencies of 10%. At high frequencies, there is no sampling bias with respect to ethnicity or to regions of the genome. Finally, a relatively large fraction (> 40%) of SNPs in these databases were not seen in our study, which means that they are either of very low frequency, mismapped, or not polymorphic at all.
Databases, Genetic↗
How many SNPs does a genome-wide haplotype map require?
We derive and compare several estimates of the number of SNPs that would be required to form the basis of a complete haplotype survey of the human genome. Our estimates make use of reports published by Stephens et al. [1], Patil et al. [2] and Daly et al. [3]. The estimated number of SNPs required for a genome-wide haplotype survey ranges from 180K (based on a European sample of 16 chromosomes) to 600K (based on an ethnically diverse sample of 164 chromosomes). We discuss the implications of using cohorts of different size and ethnic composition and the usefulness of public SNP databases for this effort. Finally, we estimate the experimental effort and cost required to complete a genome-wide haplotype survey.
Algorithms↗