Systems Pharmacogenomics – Gene, Disease, Drug and Placebo Interactions: A Case Study in COMT

Hall, Kathryn T.; Loscalzo, Joseph; Kaptchuk, Ted J.

doi:10.2217/pgs-2019-0001

Cited by 13 publications

(11 citation statements)

References 157 publications

(194 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Conversely, in the tolcapone treatment arm, met/met individuals did worse than those with the val/val genotype. Although, without a no‐treatment control, it is not possible to conclude anything about the placebo effect, and it is well established that COMT has effects on executive function, we continue to support the notion that the additivity assumption would lead us to conclude that there was no difference between drug and placebo, as the drug and placebo responses are not simply additive ( Figure ).…”

Section: Genetics and Nonadditivity In Rctssupporting

confidence: 54%

Drug‐Placebo Additivity in Randomized Clinical Trials

Hall

Loscalzo

2019

Clin Pharma and Therapeutics

Self Cite

View full text Add to dashboard Cite

In randomized clinical trials (RCTs), it is assumed that nonspecific effects beyond action of pharmacological agents are roughly equivalent in drug and placebo treatment groups. Hence, since the inception of RCTs, drug efficacy is determined by comparing outcomes in active to those in placebo control arms. However, quantitation of efficacy is based on an unproven assumption, that drug and placebo responses are always additive. Response to treatment in RCTs can be differentially influenced by the perturbing effects of patient expectations, side effects, and pharmacogenomic interactions in both drug and placebo arms. Ability to control for these effects requires understanding of when and where they arise, how to mitigate, analyze, and even leverage their impact. Here, we examine three factors that influence additivity: expectation, side effects, and pharmacogenomics. Furthermore, to provide novel insights into nonadditivity and solutions for managing it, we introduce systems pharmacogenomics, a network approach to integrating and analyzing the effects of the numerous interacting perturbations to which a patient is exposed in RCTs.In randomized placebo controlled clinical trials (RCTs), the placebo treatment arm is designed to capture and control for the nonspecific variables that can influence clinical outcomes. These include regression to the mean, spontaneous remission, changes due to the natural course of the disease, and placebo effects. Placebo effects refer to clinical improvement derived from the patient's interactions with the clinician, the information they receive with regard to their condition and treatment, and the therapeutic ritual performed in the clinical setting. 1 Hence, factors that influence clinical outcomes in RCTs derive from the "players" engaged in the therapeutic encounter and their emergent properties. From the patient's characteristics, the physician's appearance and manner, and the information communicated, to the mise-en-scène, and the pharmacological agent's properties, this complexity of factors can make predicting that there will be a statistically significant drug-placebo difference difficult. It is this complexity that placebo controls, along with randomization and double-blinding, were designed to reduce, allowing us to use simple arithmetic to subtract the nonspecific effects captured in the placebo control arm to reveal the efficacy of the drug. Hence, determination of drug efficacy relies on the assumption that the placebo and drug responses are additive (i.e., drug efficacy = drug response -placebo response).For drugs like antimicrobials or chemotherapeutics that target well-defined exogenous pathogens or cellular processes not under the influence of placebo effects, the additivity assumption seems to hold, allowing us to establish successfully the efficacy of numerous medications. [2][3][4] In contrast, treatments for conditions such as pain, anxiety, and depression, and a wide variety of functional and central sensitization disorders defined less by pathophysiology and more...

show abstract

Section: Genetics and Nonadditivity In Rctssupporting

confidence: 54%

Drug‐Placebo Additivity in Randomized Clinical Trials

Hall

Loscalzo

2019

Clin Pharma and Therapeutics

Self Cite

View full text Add to dashboard Cite

show abstract

“…With respect to the behavioral phenotype of PWS, diminished working memory, selective attention, and impaired cognitive flexibility are several executive dysfunctions associated with low dopamine levels in the PFC (Fallon et al, 2012). Of interest, COMT gene expression has also been implicated in the placebo response, which is widely known anecdotally to occur in persons with PWS (Hall et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Pharmacodynamic Gene Testing in Prader-Willi Syndrome

Forster¹,

Duis

Butler

2020

Front. Genet.

View full text Add to dashboard Cite

Prader-Willi syndrome (PWS) is a rare genetic disorder with a complex neurobehavioral phenotype associated with considerable psychiatric co-morbidity. This clinical case series, for the first time, describes the distribution and frequency of polymorphisms of pharmacodynamic genes (serotonin transporter, serotonin 2A and 2C receptors, catechol-o-methyltransferase, adrenergic receptor 2A, methylene tetrahydrofolate reductase, and human leucocytic antigens) across the two major molecular classes of PWS in a cohort of 33 referred patients who met medical criteria for testing. When results were pooled across PWS genetic subtypes, genotypic and allelic frequencies did not differ from normative population data. However, when the genetic subtype of PWS was examined, there were differences observed across all genes tested that may affect response to psychotropic medication. Due to small sample size, no statistical significance was found, but results suggest that pharmacodynamic gene testing should be considered before initiating pharmacotherapy in PWS. Larger scale studies are warranted.

show abstract

“…Further, neurological placebo response pathways are thought to induce downstream immune function effects 51,52 . Genetic variation in putative placebo response pathway molecules has been shown to differentially influence placebo and drug arm outcomes 70–75 . Without concurrent placebo controls, it is not possible to identify any effects of study drug on the placebo response pathways or drug‐placebo interactions.…”

Section: Patient‐level Sources Of Heterogeneitymentioning

confidence: 99%

“…51,52 Genetic variation in putative placebo response pathway molecules has been shown to differentially influence placebo and drug arm outcomes. [70][71][72][73][74][75] Without concurrent placebo controls, it is not possible to identify any effects of study drug on the placebo response pathways or drug-placebo interactions. Hence, a major limitation in the use of historical controls is that it limits the direct comparison of a specific drug to placebo, which is a challenge for evaluating adverse and off-target effects and potential placebo-drug interaction effects.…”

Section: Pharmacogenomics Of Drug and Placebo Responsementioning

confidence: 99%

Historical Controls in Randomized Clinical Trials: Opportunities and Challenges

Hall

Vase

Tobias

et al. 2020

Clin Pharma and Therapeutics

View full text Add to dashboard Cite

Randomized control trials (RCTs) with placebo are the gold standard for determining efficacy of novel pharmaceutical treatments. Since their inception, over 75 years ago, researchers have amassed a large body of underutilized data on outcomes in the placebo control arms of these trials. Although rare disease indications have used these historical placebo data as synthetic controls to reduce burden on patients and accelerate drug discovery, broad use of historical controls is in its infancy. Large‐scale historical placebo data could be leveraged to benefit both drug developers and patients if warehoused and made more available to guide trial design and analysis. Here, we examine challenges in utilizing historical controls related to heterogeneity in trial design, outcome ascertainment, patient characteristics, and unmeasured pharmacogenomic effects. We then discuss the advantages and disadvantages of current approaches and propose a path forward to broader use of historical controls in RCTs.

show abstract

Systems Pharmacogenomics – Gene, Disease, Drug and Placebo Interactions: A Case Study in COMT

Cited by 13 publications

References 157 publications

Drug‐Placebo Additivity in Randomized Clinical Trials

Drug‐Placebo Additivity in Randomized Clinical Trials

Pharmacodynamic Gene Testing in Prader-Willi Syndrome

Historical Controls in Randomized Clinical Trials: Opportunities and Challenges

Contact Info

Product

Resources

About