Genotyping, characterization, and imputation of known and novel CYP2A6 structural variants using SNP array data

Fine-mapping the CYP2A6 regional association with nicotine metabolism among African American smokers

The nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine) is a stable biomarker for CYP2A6 enzyme activity and nicotine clearance, with demonstrated clinical utility in personalizing smoking cessation treatment. Common genetic variation in the CYP2A6 region is strongly associated with NMR in smokers. Here, we investigated this regional association in more detail. We evaluated the association of CYP2A6 single-nucleotide polymorphisms (SNPs) and * alleles with NMR among African American smokers (N = 953) from two clinical trials of smoking cessation. Stepwise conditional analysis and Bayesian fine-mapping were undertaken. Putative causal variants were incorporated into an existing African ancestry-specific genetic risk score (GRS) for NMR, and the performance of the updated GRS was evaluated in both African American (n = 953) and European ancestry smokers (n = 933) from these clinical trials. Five independent associations with NMR in the CYP2A6 region were identified using stepwise conditional analysis, including the deletion variant CYP2A6*4 (beta = -0.90, p = 1.55 × 10-11). Six putative causal variants were identified using Bayesian fine-mapping (posterior probability, PP = 0.67), with the top causal configuration including CYP2A6*4, rs116670633, CYP2A6*9, rs28399451, rs8192720, and rs10853742 (PP = 0.09). Incorporating these putative causal variants into an existing ancestry-specific GRS resulted in comparable prediction of NMR within African American smokers, and improved trans-ancestry portability of the GRS to European smokers. Our findings suggest that both * alleles and SNPs underlie the association of the CYP2A6 region with NMR among African American smokers, identify a shortlist of variants that may causally influence nicotine clearance, and suggest that portability of GRSs across populations can be improved through inclusion of putative causal variants.

PharmVar GeneFocus: CYP2A6

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the human CYP2A gene locus containing the highly polymorphic CYP2A6 gene. CYP2A6 plays a role in the metabolism of nicotine and various drugs. Thus, genetic variation can substantially contribute to the function of this enzyme and associated efficacy and safety. This GeneFocus provides an overview of the clinical significance of CYP2A6, including its genetic variation and function. We also highlight and discuss caveats in the identification and characterization of allelic variation of this complex pharmacogene, a prerequisite for accurate genotype determination and prediction of phenotype status.

Systematic Review of Naturally Derived Substances That Act as Inhibitors of the Nicotine Metabolizing Enzyme Cytochrome P450 2A6

Tobacco smoking has been highlighted as a major health challenge in modern societies. Despite not causing death directly, smoking has been associated with several health issues, such as cardiovascular diseases, respiratory disorders, and several cancer types. Moreover, exposure to nicotine during pregnancy has been associated with adverse neurological disorders in babies. Nicotine Replacement Therapy (NRT) is the most common strategy employed for smoking cessation, but despite its widespread use, NRT presents with low success and adherence rates. This is attributed partially to the rate of nicotine metabolism by cytochrome P450 2A6 (CYP2A6) in each individual. Nicotine addiction is correlated with the high rate of its metabolism, and thus, novel strategies need to be implemented in NRT protocols. Naturally derived products are a cost-efficient and rich source for potential inhibitors, with the main advantages being their abundance and ease of isolation. This systematic review aims to summarize the natural products that have been identified as CYP2A6 inhibitors, validated through in vitro and/or in vivo assays, and could be implemented as nicotine metabolism inhibitors. The scope is to present the different compounds and highlight their possible implementation in NRT strategies. Additionally, this information would provide valuable insight regarding CYP2A6 inhibitors, that can be utilized in drug development via the use of in silico methodologies and machine-learning models to identify new potential lead compounds for optimization and implementation in NRT regimes.

A Specialized Reference Panel with Structural Variants Integration for Improving Genotype Imputation in Alzheimer's Disease and Related Dementias (ADRD)

We developed an imputation panel for Alzheimer's disease (AD) and related dementias (ADRD) using whole-genome sequencing (WGS) data from the Alzheimer's Disease Sequencing Project (ADSP). Recognizing the significant associations between structural variants (SVs) and AD, and their underrepresentation in existing public reference panels, our panel uniquely integrates single nucleotide variants (SNVs), short insertions and deletions (indels), and SVs. This panel enhances the imputation of disease susceptibility, including rare AD-associated SNVs, indels, and SVs, onto genotype array data, offering a cost-effective alternative to whole-genome sequencing while significantly augmenting statistical power. Notably, we discovered 10 rare indels nominal significant related to AD that are absent in the TOPMed-r2 panel and identified three suggestive significant (p-value < 1E-05) AD-associated SVs in the genes EXOC3L2 and DMPK, were identified. These findings provide new insights into AD genetics and underscore the critical role of imputation panels in advancing our understanding of complex diseases like ADRD.

Associating CYP2A6 structural variants with ovarian and lung cancer risk in the UK Biobank: replication and extension

CYP2A6 is a polymorphic enzyme that inactivates nicotine; structural variants (SVs) include gene deletions and hybrids with the neighboring pseudogene CYP2A7. Two studies found that CYP2A7 deletions were associated with ovarian cancer risk. Using their methodology, we aimed to characterize CYP2A6 SVs (which may be misidentified by prediction software as CYP2A7 SVs), then assess CYP2A6 SV-associated risk for ovarian cancer, and extend analyses to lung cancer. An updated reference panel was created to impute CYP2A6 SVs from UK Biobank array data. Logistic regression models analyzed the association between CYP2A6 SVs and cancer risk, adjusting for covariates. Software-predicted CYP2A7 deletions were concordant with known CYP2A6 SVs. Deleterious CYP2A6 SVs were not associated with ovarian cancer (OR = 1.06; 95% CI: 0.80-1.37; p = 0.7) but did reduce the risk of lung cancer (OR = 0.44; 95% CI: 0.29-0.64; p < 0.0001), and a lung cancer subtype. Replication of known lung cancer associations indicates the validity of array-based SV analyses.