Genetic variation +
opioid overdose
The field of pharmacogenomics is offering the opportunity to identify individuals who may be at risk of opioid overdose due to their genetic variation.
A growing crisis
The increase in prevalence of opioid-related harms worldwide is a growing concern. In Canada alone, opioid-related hospitalizations increased by 27% between the years of 2013 to 2017 (Public Health Agency of Canada, 2018). In 2019, about 62% of opioid-related hospitalizations were accidental (Special Advisory Committee on the Epidemic of Opioid Overdoses, 2019). According to the Public Health Agency of Canada, more than 8000 Canadians lost their lives between January 2016 and March 2018 as a result of opioid-related overdose, and in 2019, 94% of opioid-associated deaths were accidental (Special Advisory Committee on the Epidemic of Opioid Overdoses, 2019). This opioid crisis affects a wide population: from individuals who consumed drugs for the first time, to those living with chronic pain, and individuals more experience with substance use. With the emergence of the coronavirus (COVID-19) pandemic in 2020, individuals battling addiction will have reduced access to healthcare providers, and thus further exacerbating the crisis.
Recent research shows that there is a wide variability in opioid efficacy and toxicity despite controlling for environment-related factors and patient-related factors, such as age, gender, weight and concomitant disease. Characterizing factors that predict an individual's response to opioid analgesics could help better tailor these medications to the patients mostly likely to benefit, while reducing side effects in patients most likely to have problems.
DID YOU KNOW?
The top 10 opioids consumed in Ontario according to the Chief Coroner of Ontario (OCC) are: fentanyl, methadone, morphine, hydromorphone, oxycodone, heroin, carfentanyl, codeine, tramadol, U-47700 “Utopics”.
The main goal of this project is to investigate whether genetic factors are associated with accidental opioid-related deaths. This goal will be achieved by evaluating single nucleotide polymorphisms (SNPs) or copy number variations (CNV), in genes with known functional relevance in opioid metabolism and opioid-receptor binding in deceased cases due to accidental-opioid-overdose.
Objectives
We hypothesize that genetic factors involved in metabolism and drug action play an important role in opioid-related deaths. To investigate this hypothesis, we will pursue the following objectives:
The primary objective will be to analyze the effects on CYP2B6 and CYP2D6 on various opioid plasma levels (and metabolites), where we hypothesize, that accidental overdosing is associated with poor/impaired enzymatic activity of CYP2B6 and CYP2D6.
The secondary objective will be to analyze ABCB1 and OPRM1 gene variant frequencies, known to have functional relevance on gene expression or opioid effects and their association with accidental opioid-overdosing.
The third objective is to analyze other gene variant frequencies in COMT and DRD2 and their association with accidental opioid-overdosing.
The fourth objective is to develop a genetic risk score adjusted for age and sex and other clinical variables based on our variants associated with opioid overdose
Preliminary Data
We hold REB approval at our institution and have received 41 DNA samples from the OCC/OFPS. Our initial results suggested a 2.5-fold over-representation of the minor CYP2B6 *4 allele which is reported to increase CYP2B6 gene expression compared to the general population (i.e., observed 13 allele carriers vs. 5 expected). Notably, we detected differences in the distribution of CYP2B6 rs3745274 between males and females in our sample, suggesting that the *9-allele is a particular risk factor for males (p=0.009, chi sq=9.455). With respect to the OPRM1 gene, we observed a threefold underrepresentation of the rs1799971-G allele in methadone overdosed cases (i.e., only 4 G-allele carriers vs. 12 expected).
Recruitment plan
In this pilot study on genetic factors influencing opioid-related death, we aim to include an additional N= 160 subjects (to have a total number of N=200 patients) who died from an accidental opioid overdose. Identification of appropriate cases ruled as opioid-related deaths will be done by the Ontario’s Chief Coroner (OCC). We will Blood samples and collect data pertaining to age at death, sex, ethnicity, duration of opioid intake, use of other medications/drugs (particularly those affecting CYP2B6 activities), plasma levels and co-intoxication at death
Funding
Selected Publications
Magarbeh, L., Gorbovskaya, I., Wells, R., Jhirad, R., Le Foll, B., Müller, D.J. (2023). Pharmacogenetics of Lethal Opioid Overdose. Journal of Personalized. Medicine, 13, 918. https://doi.org/10.3390/jpm13060918
Reviewing pharmacogenetics to advance precision medicine for opioids.
Magarbeh, L., Gorbovskaya, I., Le Foll, B., Jhirad, R., & Müller, D. J. (2021).. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, 142, 112060. https://doi.org/10.1016/j.biopha.2021.112060