Biology subjects

Aitchison, K. J.

Publications and source records attributed to Aitchison, K. J..

5 recordsLinked to original sources

bioRxiv2023

Haplotype phasing of CYP2D6: an allelic ratio method using Agena MassARRAY data

Pharmacogenomics aims to use the genetic information of an individual to personalize drug prescribing. There is evidence that pharmacogenomic testing before prescription may prevent adverse drug reactions, increase efficacy, and reduce cost of treatment. CYP2D6 is a key pharmacogene of relevance to multiple therapeutic areas. Indeed, there are prescribing guidelines available for medications based on CYP2D6 enzyme activity as deduced from CYP2D6 genetic data. The Agena MassARRAY system is a cost-effective method of detecting genetic variation that has been clinically applied to other genes. However, its clinical application to CYP2D6 has to date been limited by weaknesses such as the inability to determine which haplotype was present in more than one copy for individuals with more than two copies of the CYP2D6 gene. We report application of a new protocol for CYP2D6 haplotype phasing of data generated from the Agena MassARRAY system. For samples with more than two copies of the CYP2D6 gene for which the prior consensus data specified which one was present in more than one copy, our protocol was able to conduct CYP2D6 haplotype phasing resulting in 100% concordance with the prior data. In addition, for three reference samples known to have more than two copies of CYP2D6 but for which the exact number of CYP2D6 genes was unknown, our protocol was able to resolve the number for two out of the three of these, and estimate the likely number for the third. In addition, we demonstrate that our method is applicable to CYP2D6 hybrid tandem configurations.

genomics↗

bioRxiv2022

Single molecule long-read real-time amplicon-based sequencing of CYP2D6: a proof-of-concept with hybrid haplotypes

CYP2D6 is a widely expressed human xenobiotic metabolizing enzyme, best known for its role in the hepatic phase I cytochrome P450 enzyme system, where it metabolizes [~]20% of medications. It is also expressed in other organs including the brain, where its potential role in physiology and mental health traits and disorders is under further investigation. Owing to the presence of homologous pseudogenes in the CYP2D locus and transposable repeat elements in the intergenic regions, the gene encoding the CYP2D6 enzyme, CYP2D6, is one of the most hypervariable known human genes - with more than 165 core haplotypes. Haplotypes include structural variants, with a subtype of these known as hybrid haplotypes or fusion genes comprising part of CYP2D6 and part of its adjacent pseudogene, CYP2D7. The fusion genes are particularly challenging to identify. High fidelity (HiFi) single molecule real-time (SMRT) long-read sequencing can cover whole CYP2D6 haplotypes in a single continuous sequence, and is therefore ideal for structural variant detection. In addition, it is highly accurate and suitable for novel haplotype identification, which is necessary as new CYP2D6 haplotypes are continuously being discovered, and many more likely remain to be identified in relatively understudied populations such as Indigenous Peoples. The aim of the present work was to develop an efficient and accurate HiFi SMRT amplicon-based method capable of detecting the full range of CYP2D6 haplotypes including fusion genes. We report proof-of-concept for 24 amplicons including three positive controls, aligned to fusion gene haplotypes, with prior cross-validation data. Amplicons with CYP2D7-D6 fusion genes, including positive controls, aligned to the *13 subhaplotypes predicted (*13F, *13A2) with 100% accuracy, with the exception of one that aligned at 99.9%. Alignment of the *68 was 100% and above 99.9% to the CYP2D6*68 partial sequences EU5300606 and JF307779, respectively. The best alignments for the remaining CYP2D6-2D7 fusion genes were [≥]99.7% (to 3 significant figures). Lower percentage alignment for CYP2D6-2D7 fusion genes may reflect imperfect PCR optimization and/or the possibility that we may have haplotypes not yet in public databases. Further work on these is in progress. Moreover, we have adapted this method for non-hybrid haplotypes. This technique could therefore suffice for the characterization of the full range of CYP2D6 haplotypes. The method that we have developed could be extended to other complex loci and to other species in a multiplexed high throughput assay.

genomics↗

bioRxiv2019

Cross-validation of technologies for genotyping CYP2D6 and CYP2C19

BackgroundCYP2D6 and CYP2C19 are cytochrome P450 enzymes involved in the metabolism of many medications from multiple therapeutic classes. Associations between patterns of variants (known as haplotypes) in the genes encoding them (CYP2D6 and CYP2C19) and enzyme activities are well described. The genes in fact comprise 21% of biomarkers in drug labels. Despite this, genotyping is not common, partly attributable to its challenging nature (CYP2D6 having >100 haplotypes, including those with sequence from an adjacent pseudogene, and gene duplications). We cross-validated different methodologies for identifying haplotypes in these genes against each other. MethodsNinety-two samples with a variety of CYP2D6 and CYP2C19 genotypes according to prior AmpliChip CYP450 and TaqMan CYP2C19*17 data were selected from the Genome-based therapeutic drugs for depression (GENDEP) study. Genotyping was performed with TaqMan copy number variant (CNV) and single nucleotide variant (SNV) analysis, the next generation sequencing-based Ion S5 AmpliSeq Pharmacogenomics Panel, PharmacoScan, long-range polymerase chain reaction (L-PCR) followed by amplicon analysis, and Agena for CYP2C19. Variant pattern to haplotype translation was automated. ResultsThe inter-platform concordance for CYP2C19 was high (up to 100% for available data). For CYP2D6, the IonS5-PharmacoScan concordance was 94% for a range of variants tested apart from those with at least one extra copy of a CYP2D6 gene (occurring at a frequency of 3.8%, 33/853), or those with substantial sequence derived from pseudogene, known as hybrids (3%, 26/853). ConclusionsInter-platform concordance for CYP2C19 was high, and, moreover, the Ion S5 and PharmacoScan data were 100% concordant with that from a TaqMan CYP2C19*2 assay. We have also demonstrated feasibility of using an NGS platform for genotyping CYP2D6 and CYP2C19, with automated data interpretation methodology. This points the way to a method of making CYP2D6 and CYP2C19 genotyping more readily accessible.

genetics↗

bioRxiv2018

Assessing 42 inflammatory markers in 321 control subjects and 887 major depressive disorder cases: BMI and other confounders and overall predictive ability for current depression

Inflammatory markers such as cytokines represent potential biomarkers for major depressive disorder (MDD). Many, generally small studies have examined the role of single markers and found significant associations. We assessed 42 inflammatory markers, namely cytokines, in the blood of 321 control subjects and 887 MDD cases. We tested whether individual inflammatory marker levels were significantly affected by MDD case/control status, current episode, or current depression severity, co-varying for age, sex, body mass index (BMI), smoking, current antidepressant use, ethnicity, assay batch and study effects. We further used machine learning algorithms to investigate if we could use our data to blindly discriminate MDD patients, or those in a current episode. We found broad and powerful influences of confounding factors on log-protein levels. Notably, IL-6 levels were very strongly influenced by BMI (p = 1.37 x 10-43, variance explained = 18%), while Interleukin-16 was the most significant predictor of current depressive episode (p = 0.003, variance explained = 0.9%, q < 0.1). No single inflammatory marker predicted MDD case/control status when a subject was not in a depressed episode, nor did any predict depression severity. Machine learning results revealed that using inflammatory marker data with clinical confounder information significantly increased precision for differentiating MDD patients who were in an episode. To conclude, a wide panel of inflammatory markers alongside clinical information may aid in predicting the onset of symptoms, but no single inflammatory protein is likely to represent a clinically useful biomarker for MDD diagnosis or prognosis. We note that the potential influence of physical health related and population stratification related confounders on inflammatory biomarker studies in psychiatry is considerable.

neuroscience↗

bioRxiv2018

Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: meta-analysis of data from genome-wide association studies

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects.\n\nCYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2-4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group.\n\nAnalysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19-0.66) and higher remission rates (OR=1.55, CI=1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08-1.47), neurological (OR=1.28, CI=1.07-1.53) and sexual side effects (OR=1.52, CI=1.23-1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups.\n\nCYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).

genetics↗