Pharmacotherapy for smoking cessation: effects by subgroup defined by genetically informed biomarkers

Ewoud Schuit1, Orestis A Panagiotou, Marcus R Munafò

  • 1Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.

Abstract

Insights

Smoking cessation pharmacotherapy effectiveness varies by genetic biomarkers. Nicotine replacement therapy (NRT) showed differential effects based on specific genotypes and nicotine metabolite ratio (NMR) in some subgroups.

Area of Science:

  • Pharmacogenomics
  • Clinical Pharmacology
  • Genetics

Background:

  • Smoking cessation therapies demonstrate variable effectiveness across individuals.
  • Identifying subgroups who respond best to specific treatments is crucial for personalized medicine.

Purpose of the Study:

  • To evaluate if smoking cessation rates differ by genotype-informed biomarkers within pharmacotherapy arms versus placebo.
  • To assess pharmacotherapy efficacy in subgroups defined by genetic polymorphisms.

Main Methods:

  • Systematic review and meta-analysis of randomized controlled trials (RCTs) of smoking cessation pharmacotherapies.
  • Included trials with pharmacogenomic data on single-nucleotide polymorphisms (SNPs) and nicotine metabolite ratio (NMR).
  • Analyzed treatment effects by genotype within treatment arms and active treatment versus placebo within genotype groups.

Main Results:

  • Statistically significant heterogeneity in quit rates by genotype (rs16969968) for nicotine replacement therapy (NRT) versus placebo in non-Hispanic Black participants.
  • NRT showed increased six-month abstinence in GG genotype individuals compared to GA/AA genotypes.
  • Active NRT was more effective for six-month abstinence in slow nicotine metabolite ratio (NMR) individuals compared to normal NMR.

Conclusions:

  • Widespread differential pharmacotherapy effects based on genotype were not identified.
  • Certain ethnic and genotype groups may respond differently to NRT or combination therapies.
  • Further research with larger datasets is needed to confirm findings and explore other pharmacotherapies.

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