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Aitchison, K.

Publications and source records attributed to Aitchison, K..

2 recordsLinked to original sources

A novel pharmacogenetic testing panel for CYP2C19 genetic polymorphisms

Specific drug metabolism rates are defined by the constituency of the cytochrome P450 (CYP) genome, including polymorphic changes in any of 200+ CYP genes. An example is CYP2C19, where associations of gene polymorphisms with variability in certain drug metabolism rates have been linked to inter-individual and inter-ethnic differences in therapeutic outcomes. While pharmacogenomic screening for these variants prior to drug and dosage prescription has well-defined links to better treatment outcomes, current implementation is limited to complex and costly variant-probing and DNA sequencing protocols, which have limited availability in clinical laboratories, leading to slow turnaround times, impacting effective clinical intervention. Here we describe a novel, cost-effective, multiplex genotyping approach to screening CYP2C19 variants. Fluorescence nested allele-specific (FAS) PCR was used with primers to detect CYP2C19 variants of interest in specific hot spots, including the Tier 1 haplotypes identified by the Association for Molecular Pathology (AMP): CYP2C19*2, *3, and *17. The presence/absence of wild-type and mutant alleles were identified independently as haplotypes, and in a multiplex reaction as diplotypes representing the 10 possible genotype combinations/profiles. FAS-PCR achieved the same genotype calls as a pyrosequencing protocol optimized for validating genotypes, but with a simpler and more sensitive interface. The FAS-PCR method correctly identified the genotypes of both synthesized DNA and a human genomic DNA standard. Uniquely, the FAS-PCR protocol generates patterns using one fluorescently-labeled primer irrespective of the number of variants targeted, establishing it as considerably more cost-effective than other allele-specific PCR-based techniques that involve labeling both the forward and reverse primers.

pharmacology and toxicology↗

New insights on the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation.\n\nA meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at SNP, gene and pathway level. Coverage of genetic variants was increased compared to previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) served for replication.\n\n7,062,950 SNPs were analysed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (p=1.80e-08, ITGA9 (integrin alpha 9)) and rs76191705 (p=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At gene level, no consistent effect was found. At pathway level, the Gene Ontology terms GO:0005694 (chromosome) and GO:0044427 (chromosomal part) were associated with improvement (corrected p=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (p=0.047), while rs76191705 was not. The two SNPs did not replicate in NEWMEDS.\n\nITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, no convincing replication was achieved. Further studies may help in clarifying their role.

genomics↗