ArticleClinical and translational science2022
Functional characterization of novel rare CYP2A6 variants and potential implications for clinical outcomes.
Article in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Utility of long-read sequencing for All of Us.Nature communications · 2024Article
- Influence of CYP2A6 Genetic Variation, Nicotine Dependence Severity, and Treatment on Smoking Cessation Success.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023Article
- The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data.The pharmacogenomics journal · 2022Article
- Functional characterization of novel rare CYP2A6 variants and potential implications for clinical outcomes.Clinical and translational science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 10 institutions in 4 countries.
Funding
Abstract
CYP2A6 activity, phenotyped by the nicotine metabolite ratio (NMR), is a predictor of several smoking behaviors, including cessation and smoking-related disease risk. The heritability of the NMR is 60-80%, yet weighted genetic risk scores (wGRSs) based on common variants explain only 30-35%. Rare variants (minor allele frequency <1%) are hypothesized to explain some of this missing heritability. We present two targeted sequencing studies where rare protein-coding variants are functionally characterized in vivo, in silico, and in vitro to examine this hypothesis. In a smoking cessation trial, 1687 individuals were sequenced; characterization measures included the in vivo NMR, in vitro protein expression, and metabolic activity measured from recombinant proteins. In a human liver bank, 312 human liver samples were sequenced; measures included RNA expression, protein expression, and metabolic activity from extracted liver tissue. In total, 38 of 47 rare coding variants identified were novel; characterizations ranged from gain-of-function to loss-of-function. On a population level, the portion of NMR variation explained by the rare coding variants was small (~1%). However, upon incorporation, the accuracy of the wGRS was improved for individuals with rare protein-coding variants (i.e., the residuals were reduced), and approximately one-third of these individuals (12/39) were re-assigned from normal to slow metabolizer status. Rare coding variants can alter an individual's CYP2A6 activity; their integration into wGRSs through precise functional characterization is necessary to accurately assess clinical outcomes and achieve precision medicine for all. Investigation into noncoding variants is warranted to further explain the missing heritability in the NMR.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.