A genome-wide association study of tramadol metabolism from post-mortem samples.

Phase I tramadol metabolism requires cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) to form O-desmethyltramadol (M1). CYP2D6 genetic variants may infer metabolizer phenotype; however, drug ADME (absorption, distribution, metabolism, and excretion) and response depend on protein pathway(s), not CYP2D6 alone. There is a paucity of data regarding the contribution of trans-acting proteins to idiosyncratic phenotypes following drug exposure. A genome-wide association study identified five markers (rs79983226/kgp11274252, rs9384825, rs62435418/kgp10370907, rs72732317/kgp3743668, and rs184199168/exm1592932) associated with the conversion of tramadol to M1 (M1:T). These SNPs reside within five genes previously implicated with adverse reactions. Analysis of accompanying toxicological meta-data revealed a significant positive linear relationship between M1:T and degree of sample polypharmacy. Taken together, these data identify candidate loci for potential clinical inferences of phenotype following exposure to tramadol and highlight sample polypharmacy as a possible diagnostic covariate in post-mortem genetic studies.

A pathway-driven predictive model of tramadol pharmacogenetics.

Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have well-documented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathway-driven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.

Supervised Classification of CYP2D6 Genotype and Metabolizer Phenotype With Postmortem Tramadol-Exposed Finns.

Cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) may be used to infer the metabolizer phenotype (MP) of an individual as poor, intermediate, extensive/normal, or ultrarapid. Metabolizer phenotypes may suggest idiosyncratic drug responses as contributing factors to cause and/or manner of death in postmortem investigations. Application of CYP2D6 has used long-range amplification of the locus and restriction enzyme digestion to detect single-nucleotide variants (SNVs) associated with MPs. This process can be cumbersome and requires knowledge of genotype phase. Phase may be achieved using long-read DNA sequencing and/or computational methods; however, both can be error prone, which may make it difficult or impractical for implementation into medicolegal practice. CYP2D6 was interrogated in postmortem autopsied Finns using supervised machine learning and feature selection to identify SNVs indicative of MP and/or rate of tramadol O-demethylation (T:M1). A subset of 18 CYP2D6 SNVs could predict MP/T:M1 with up to 96.3% accuracy given phased data. These data indicate that phase contributes to classification accuracy when using CYP2D6 data. Of these 18 SNVs, 3 are novel loci putatively associated with T:M1. These findings may enable design of small multiplexes for easy forensic application of MP prediction when cause and/or manner of death is unknown.

Completed suicides of citalopram users-the role of CYP genotypes and adverse drug interactions.

Depression is known to be a risk factor for suicide. Currently, the most used antidepressants are selective serotonin reuptake inhibitors (SSRIs). Not all users, however, benefit from them. In such cases, treatment failure can be explained in part by genetic differences. In this study, we investigated the role of pharmacogenetic factors in citalopram-positive completed suicides (n = 349). Since citalopram is metabolized by CYP2C19 and CYP2D6 enzymes, the study population was genotyped for clinically relevant CYP2C19 and CYP2D6 polymorphisms and CYP2D6 copy number variation. To assess genetic differences between suicide cases and Finns in general, Finnish population samples (n = 855) were used as controls. Also, the role of drug interactions among suicide cases was evaluated. We found enrichment of a combined group of genetically predicted poor and ultrarapid metabolizer phenotypes (gMPs) of CYP2C19 among suicide victims compared to controls 0.356 [0.31-0.41] vs. 0.265 [0.24-0.30] (p = 0.0065). In CYP2D6 gMPs, there was no difference between cases and controls when the study population was analyzed as a whole. However, there were significantly more poor metabolizers among females who committed suicide by poisoning compared to female controls. In 8% of all drug poisoning deaths, lifetime drug-drug interaction was evaluated having a contribution to the fatal outcome. From clinical perspective, pharmacogenetic testing prior to initiation of SSRI drug could be beneficial. It may also be useful in medico-legal settings as it may elucidate obscure poisoning cases. Also, the possibility of unintentional drug interactions should be taken into account in drug poisoning deaths.

Post-mortem analysis of suicide victims shows ABCB1 haplotype 1236T-2677T-3435T as a candidate predisposing factor behind adverse drug reactions in females.

BACKGROUND: Genetic variation in efflux transporter, permeability glycoprotein (P-gp), has recently been associated with completed violent suicides and also violent suicide attempts. As depression is known to be a risk factor for suicide and many antidepressants are P-gp substrates, it has been speculated that inadequate antidepressant treatment response or adverse side effects could be involved. OBJECTIVES: The aim of this study was to investigate whether there is an association between the P-gp coding ABCB1 gene and completed suicides in citalopram users. Also, the effect of sex and suicide method used (violent vs. non-violent) was evaluated. MATERIALS AND METHODS: All cases included in the study population, 349 completed suicide victims and 284 controls, were shown to be positive for antidepressant citalopram in a post-mortem toxicological drug screen. ABCB1 1236C>T, 2677G>T/A and 3435C>T polymorphisms were determined by TaqMan genotyping assays. Haplotypes were constructed from genotype data using the PHASE software. The association between the manner of death and the ABCB1 haplotype was tested with logistic regression analysis. RESULTS: No statistically significant differences were observed in the ABCB1 allele or genotype frequencies between the suicide and control groups. However, the ABCB1 1236T-2677T-3435T haplotype was associated with completed suicides of female citalopram users (odds ratio: 2.23; 95% confidence interval: 1.22-4.07; P=0.009). After stratification by the method used for suicide, the association emerged in fatal intoxications (odds ratio: 2.51; 95% confidence interval: 1.29-4.87; P=0.007). In other groups, no statistically significant associations were observed. CONCLUSION: Our results suggest that female citalopram users with ABCB1 1236T-2677T-3435T are more vulnerable to adverse effects of the drugs as this haplotype was enriched in non-violent suicides of female citalopram users. Even though the biological mechanism behind this observation is unknown, the results provide another example of the importance of sex-based segregation in pharmacogenetics studies.

Serotonergic 5HTTLPR/rs25531 s-allele homozygosity associates with violent suicides in male citalopram users.

Depressive disorders are involved as a background factor in over 50% of suicide cases. The most widely used antidepressants today are serotonin selective reuptake inhibitors (SSRIs). However, not all users benefit from SSRI medication. Although the overall number of suicides in Finland have decreased notably during the last decade, the annual rate is still relatively high, particularly in male population. In this study, we tested the hypothesis that the genetic variants associated with decreased citalopram efficiency, 5HTTLPR/rs25531, and increased impulsive behavior, MAOA-uVNTR and HTR2B Q20*, are more frequent among citalopram users committing suicide than among the citalopram users in general. Also the effect of alcohol was evaluated. The study population comprised 349 suicide victims (184 males and 165 females). Based on the suicide method used, cases were divided into two groups; violent (88 males and 49 females) and non-violent (96 males and 116 females). The control group (284; 159 males and 125 females) consisted of citalopram users who died of causes other than suicide. We found that male citalopram users with low functioning s/s genotype of 5HTTLPR/rs25531 were in increased risk to commit violent suicide (OR 2.50, 95%CI 1.15-5.42, p = 0.020). Surprisingly, high blood alcohol concentration was observed to be a risk factor only in non-violent suicides (both males and females), but not in violent ones. No association between suicides and MAOA-uVNTR and HTR2B Q20*, which have been previously connected to violent and impulsive behavior, was detected.

DNA quality and quantity from up to 16 years old post-mortem blood stored on FTA cards.

Blood samples preserved on FTA cards offer unique opportunities for genetic research. DNA recovered from these cards should be stable for long periods of time. However, it is not well established as how well the DNA stored on FTA card for substantial time periods meets the demands of forensic or genomic DNA analyses and especially so for from post-mortem (PM) samples in which the quality can vary upon initial collection. The aim of this study was to evaluate the time-dependent degradation on DNA quality and quantity extracted from up to 16 years old post-mortem bloodstained FTA cards. Four random FTA samples from eight time points spanning 1998 to 2013 (n=32) were collected and extracted in triplicate. The quantity and quality of the extracted DNA samples were determined with Quantifiler(®) Human Plus (HP) Quantification kit. Internal sample and sample-to-sample variation were evaluated by comparing recovered DNA yields. The DNA from the triplicate samplings were subsequently combined and normalized for further analysis. The practical effect of degradation on DNA quality was evaluated from normalized samples both with forensic and pharmacogenetic target markers. Our results suggest that (1) a PM change, e.g. blood clotting prior to sampling, affects the recovered DNA yield, creating both internal and sample-to-sample variation; (2) a negative correlation between the FTA card storage time and DNA quantity (r=-0.836 at the 0.01 level) was observed; (3) a positive correlation (r=0.738 at the level 0.01) was found between FTA card storage time and degradation levels. However, no inhibition was observed with the method used. The effect of degradation was manifested clearly with functional applications. Although complete STR-profiles were obtained for all samples, there was evidence of degradation manifested as decreased peak heights in the larger-sized amplicons. Lower amplification success was notable with the large 5.1 kb CYP2D6 gene fragment which strongly supports degradation of the stored samples. According to our results, DNA stored on FTA cards is rather stable over a long time period. DNA extracted from this storage medium can be used as human identification purposes as the method used is sufficiently sensitive and amplicon sizes tend to be <400 bp. However, DNA integrity was affected during storage. This effect should be taken into account depending on the intended application especially if high quality DNA and long PCR amplicons are required.