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With advances in molecular biology and genomics technology, individualization
of smoking cessation therapy according to genotype is within our grasp. Such
research has the potential to improve treatment outcome, thereby reducing morbid-
ity and mortality from smoking-related disease.
Antidepressant Therapy for Smoking Cessation
It is known that variant alleles of the dopamine receptor D2 (DRD2) gene may play
a role in determining nicotine addiction. A dopamine receptor gene polymorphism
appears to infl uence the response of cigarette smokers to smoking cessation therapy
that includes an antidepressant medicine − venlafaxine. Individuals with at least one
copy of the A1 allele of the DRD2 gene have fewer and less-sensitive D2 dopamine
receptors than do individuals with two copies of the A2 allele. A clinical trial showed
no signifi cant difference between the active and placebo treatments for the smokers
with the A1 allele in terms of reduction in negative affect during their attempt to quit
but those with the A2 allele receiving venlafaxine have 25 % lower score on testing
for negative affect. This demonstrates the value of genotyping in designing a spe-
cifi c smoking cessation therapy for a subgroup of patients.
Effectiveness of Nicotine Patches in Relation to Genotype
In women the effectiveness of nicotine patches seems to be related to genotype.
Women with the variant T allele of the dopamine D2 receptor DRD2 32806 showed
considerable benefi t from patches, whereas those with the more common CC geno-
type did not (Yudkin et al. 2004 ). The increased effectiveness refl ected a tendency
to a higher quit rate with the active patches and a lower quit rate with placebo
patches. No signifi cant relation between genotype and patch effectiveness was seen
for men. The overall effectiveness of nicotine replacement therapy could be greater
if the therapy were targeted at those most likely to respond.
Future Prospects of Personalized Psychiatry
Limited number of applications of personalized medicine approach in psychiatry
has shown the usefulness of this approach and identifi ed this as an area for further
development. Pre-emptive approaches are an important part of personalized medi-
cine and preventive psychiatry requires predictive tools that are currently not ade-
quate. Biomarkers are needed to develop a clinical staging model for psychiatric
disorders. The staging model also facilitates integration of data on the biological,
social and environmental factors that infl uence mental illness into existing clinical
and diagnostic infrastructure, which will provide a major step forward in the devel-
opment of a truly pre-emptive psychiatry (McGorry et al. 2014 ).
13 Personalized Management of Psychiatric Disorders