Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes.

In four previous studies, a combinatorial multigene pharmacogenomic test (GeneSight) predicted those patients whose antidepressant treatment for major depressive disorder resulted in poorer efficacy and increased health-care resource utilizations. Here, we extended the analysis of clinical validity to the combined data from these studies. We also compared the outcome predictions of the combinatorial use of allelic variations in genes for four cytochrome P450 (CYP) enzymes (CYP2D6, CYP2C19, CYP2C9 and CYP1A2), the serotonin transporter (SLC6A4) and serotonin 2A receptor (HTR2A) with the outcome predictions for the very same subjects using traditional, single-gene analysis. Depression scores were measured at baseline and 8-10 weeks later for the 119 fully blinded subjects who received treatment as usual (TAU) with antidepressant standard of care, without the benefit of pharmacogenomic medication guidance. For another 96 TAU subjects, health-care utilizations were recorded in a 1-year, retrospective chart review. All subjects were genotyped after the clinical study period, and phenotype subgroups were created among those who had been prescribed a GeneSight panel medication that is a substrate for either CYP enzyme or serotonin effector protein. On the basis of medications prescribed for each subject at baseline, the combinatorial pharmacogenomic (CPGx™) GeneSight method categorized each subject into either a green ('use as directed'), yellow ('use with caution') or red category ('use with increased caution and with more frequent monitoring') phenotype, whereas the single-gene method categorized the same subjects with the traditional phenotype (for example, poor, intermediate, extensive or ultrarapid CYP metabolizer). The GeneSight combinatorial categorization approach discriminated and predicted poorer outcomes for red category patients prescribed medications metabolized by CYP2D6, CYP2C19 and CYP1A2 (P=0.0034, P=0.04 and P=0.03, respectively), whereas the single-gene phenotypes failed to discriminate patient outcomes. The GeneSight CPGx process also discriminated health-care utilization and disability claims for these same three CYP-defined medication subgroups. The CYP2C19 phenotype was the only single-gene approach to predict health-care outcomes. Multigenic combinatorial testing discriminates and predicts the poorer antidepressant outcomes and greater health-care utilizations by depressed subjects better than do phenotypes derived from single genes. This clinical validity is likely to contribute to the clinical utility reported for combinatorial pharmacogenomic decision support.

Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort.

OBJECTIVES: CSF levels of Aß1-42, t-tau, and p-tau181p are potential early diagnostic markers for probable Alzheimer disease (AD). The influence of genetic variation on these markers has been investigated for candidate genes but not on a genome-wide basis. We report a genome-wide association study (GWAS) of CSF biomarkers (Aß1-42, t-tau, p-tau181p, p-tau181p/Aß1-42, and t-tau/Aß1-42). METHODS: A total of 374 non-Hispanic Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative cohort with quality-controlled CSF and genotype data were included in this analysis. The main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed on each of 5 CSF biomarkers. The p values of all SNPs for each CSF biomarker were adjusted for multiple comparisons by the Bonferroni method. We focused on SNPs with corrected p<0.01 (uncorrected p<3.10×10(-8)) and secondarily examined SNPs with uncorrected p values less than 10(-5) to identify potential candidates. RESULTS: Four SNPs in the regions of the APOE, LOC100129500, TOMM40, and EPC2 genes reached genome-wide significance for associations with one or more CSF biomarkers. SNPs in CCDC134, ABCG2, SREBF2, and NFATC4, although not reaching genome-wide significance, were identified as potential candidates. CONCLUSIONS: In addition to known candidate genes, APOE, TOMM40, and one hypothetical gene LOC100129500 partially overlapping APOE; one novel gene, EPC2, and several other interesting genes were associated with CSF biomarkers that are related to AD. These findings, especially the new EPC2 results, require replication in independent cohorts.

Use of commercially available radiation hybrid panels.

Several panels are available for puchase, and this unit provides update information on the use of the three commercially available panels and on the interpretation of mapping results using the Internet. Radiation hybrid panels continue to serve as integral biological reagents in physical mapping projects and positional cloning.

A set of electrophoretic molecular markers for strain typing and population genetic studies of Histoplasma capsulatum.

A set of eleven biallelic and three multiallelic molecular markers have been developed to analyze populations of Histoplasma capsulatum. All markers are amplified by polymerase chain reaction (PCR) and can be readily scored using minimal amounts of template DNA. The 11 biallelic loci have polymorphic restriction endonuclease sites or small insertions or deletions which may be assessed by agarose gel electrophoresis. These markers are inherited in an unambiguous manner and are ideal for assessing structure and gene flow within US populations of H. capsulatum, but are monomorphic in non-US populations. Both length and sequence variation are present in the multiallelic loci, which can be scored by direct sequencing, polyacrylamide gel electrophoresis, or single-strand conformation polymorphism (SSCP): As they are hypervariable, the multiallelic loci can be used to type isolates and to assess the level of genetic variation within populations. Preliminary results indicate that the three multiallelic markers presented are sufficient to distinguish isolates at the individual level and are polymorphic in both US and non-US populations. This collection of molecular markers will be a useful tool in population and epidemiology studies of H. capsulatum.

Molecular markers reveal differentiation among isolates of Coccidioides immitis from California, Arizona and Texas.

Coccidioides immitis causes coccidioidomycosis, a fungal disease of both immuno-compromised and otherwise healthy people; it is capable of causing large epidemics and the disease is often refractory to chemotherapy. To quantify the magnitude of population differentiation and estimate levels of gene flow in C. immitis, multilocus genotypes were scored for 20-25 clinical isolates from each of Bakersfield (California), Tucson (Arizona), and San Antonio (Texas). The molecular markers used were PCR products with polymorphic restriction endonuclease sites, found and characterized in a previous study of the Tucson population. The data show very highly significant differences in allele frequencies between all three populations, and suggest very low levels of migration between populations. One isolate in the San Antonio sample was an outlier, showing the California-specific allele at all four of the loci distinguishing the two populations, and subsequent inquiries indicated that the infection had indeed been acquired in California. Thus, genetic information can be used to infer the geographical origin of a fungal infection.