Preliminary evidence suggests that genetic variability plays some role in predicting treatment response, but that results differ depending on whether parents or teachers are informants. Current studies are also constrained by the type of outcome measures used. Many studies rely on simple dichotomous outcomes, such as responder versus non-responder, which have limited power to detect effects compared with analyses of quantitative measures. Correlations between multiple outcome measures in the same subjects are also known to be fairly weak, raising the question as to which outcome measure best defines positive response [57
]. Future pharmacogenetic studies would benefit from consensus on the optimal measures to assess outcome. It remains uncertain, particularly in regards to symptom reduction, the relative contributions of direct genetic effects and effects resulting from medication dose and formulation, as well as individual patient variables including diet and gut motility.
Another contributor to differences in study findings is that pharmacogenetic effects may be different in different ethnic groups. This implies the variants being studies may only be in linkage disequilibrium with other variants.
The majority of ADHD pharmacogenetic studies published to date have examined response to methylphenidate. While this is an obvious choice given the known pathophysiology of DAT1, its association with ADHD, and its serving as a specific target for stimulant action, results from preliminary reports have been inconsistent and contradictory. Some of these discrepant findings might be due to methodological issues, as more consistent findings appear to be emerging from placebo controlled, prospective studies. In addition to small sample sizes, other limitations of most existing trials include open-label or retrospective assessment and medication doses that are not specified or considerably lower than used in community practice for optimal benefit [9
]. Since the effects of methylphenidate on ADHD symptoms often follow a linear dose response curve [27
], these lower doses might bias against finding significant treatment effects when a less robust dose is utilized.
A critical methodological issue that remains unaddressed is the proper approach to defining genotypes for analysis. In order to minimize the potential for spurious findings and increased Type I errors, investigators must limit their analyses to minimal genotype combinations. For some genes, the risk polymorphisms for ADHD are the less common variants (eg. the 7-repeat allele of DRD4), while for other genes, such as DAT1, it is the more common variant that is associated with the disorder. For DAT1, the 10/10 and 10/9 genotypes are most common. Notably, earlier studies of DAT1 combined these two common genotypes, which assumed a dominant effect of either the 9 or 10 allele, but failed to test for a recessive effect of the 9/9 genotype. Alternative grouping of genotypes based on the presence of one or more 9 allele has led to different results. Future candidate gene studies would benefit from consensus on optimal strategies to define genotype groupings. Most importantly, without previous evidence of dominance of one allele, genotypes should not be lumped together. Statistical power is a combination of sample size and effect size. Dominance (or lack thereof), may differ between association with etiology of disorder and response to treatment.
At a recent meeting of the ADHD Molecular Genetics Network in Brussels, Belgium, the Pharmacogenetics Working Group proposed several principals to promote research in future ADHD pharmacogenetic studies. These include:
- Pharmacogenetic studies of ADHD should be methodologically rigorous in terms of the pharmacological intervention, which means the trial should meet criteria for being published on its own. Typically, this means that there should be random assignment to treatment and a placebo or other control group, and preferably random assignment.
- Response should be measured several ways and at different time points. Secondary functional outcomes and adverse events should be evaluated as well as symptom ratings.
- Different doses or optimal dose should be evaluated, recognizing that dose ranging and forced titration designs will more likely elicit pharmacogenetics effects than flexible dosing.
- Multiple genes should be examined
- Genotyping quality control must be performed, ideally including cross-laboratory and cross-method reliability checks
- Samples large enough to look at gene by environment interactions should be obtained.
- Trials sponsored by pharmaceutical companies should routinely collect DNA for pharmacogenetic and subgroup analysis.