"Genetics and the placebo effect: the placebome", Hall et al 2015 https://www.dropbox.com/s/scvomodvnm6pbav/2015-hall.pdf / http://sci-hub.bz/bde1e7da626c7c68403259529fddee20/10.1016@j.molmed.2015.02.009.pdf(via http://pipeline.corante.com/archives/2015/04/15/finding_placebo_responders.php); excerpts:

"Placebos are indispensable controls in randomized clinical trials (RCTs), and placebo responses significantly contribute to routine clinical outcomes. Recent neurophysiological studies reveal neurotransmitter pathways that mediate placebo effects. Evidence that genetic variations in these pathways can modify placebo effects raises the possibility of using genetic screening to identify placebo responders and thereby increase RCT efficacy and improve therapeutic care. Furthermore, the possibility of interaction between placebo and drug molecular pathways warrants consideration in RCT design. The study of genomic effects on placebo response, 'the placebome', is in its infancy. Here, we review evidence from placebo studies and RCTs to identify putative genes in the placebome, examine evidence for placebo-drug interactions, and discuss implications for RCTs and clinical care.

...Recent innovative neuroimaging [4] and physiological experiments [5] have fostered the current viewpoint that placebo effects are biological responses to psychosocial environmental cues surrounding the administration of inactive (or active) treatments. Such placebo research has established that the placebo response is more than patient report bias, regression to the mean, or spontaneous remission [6-8]. - 4. Atlas, L.Y. and Wager, T.D. (2014) A meta-analysis of brain mechanisms of placebo analgesia: consistent findings and unanswered questions. Handb. Exp. Pharmacol. 225, 37-69 - 5. Benedetti, F. (2013) Placebo and the new physiology of the doctor-patient relationship. Physiol. Rev. 93, 1207-1246 - 6. Benedetti, F. (2009) Placebo Effects: Understanding The Mechanisms In Health And Disease, Oxford University Press
- 7. Finniss, D.G. and Benedetti, F. (2005) Mechanisms of the placebo response and their impact on clinical trials and clinical practice. Pain 114, 3-6 - 8. Wechsler, M.E. et al. (2011) Active albuterol or placebo, sham acupuncture, or no intervention in asthma. N. Engl. J. Med. 365, 119-126

...Predicting who will be a placebo responder could be of value to both researchers and patients. In drug development, detecting a difference between active intervention and the placebo control is an underlying goal of RCTs. Being able to identify and exclude individuals who are more likely to respond to placebos could enhance trial designs seeking to find such a difference. Potential cost savings due to reduction of sample size could be of benefit for drug development [9]...In the past, scientists used behavioral instruments such as personality measures to predict placebo responders [10,11]. This approach has had limited success because these blunt instruments proved no match for the complex interplay of shifting states that may modify an individual's placebo response. Not only do clinical trial researchers have to contend with the type, duration, and severity of the condition, but the practitioner's 'bedside manner' and the patient's beliefs, hopes, expectations, and previous experiences [12] also make predicting the placebo response an ongoing challenge.

- 9. Servick, K. (2014) Outsmarting the placebo effect. Science 345, 1446-1447 - 10. Horing, B. et al. (2014) Prediction of placebo responses: a systematic review of the literature. Front. Psychol. 5, 1079
- 11. Kaptchuk, T.J. et al. (2008) Do 'placebo responders' exist? Contemp. Clin. Trials 29, 587-595 - 12. Finniss, D.G. et al. (2010) Biological, clinical, and ethical advances of placebo effects. Lancet 375, 686-695

...there have been many placebo-controlled RCTs with GWAS data, but they all lack a key dimension: a no-treatment control (NTC). A NTC is one of the few methodologies that can disentangle genuine psychosocial and physiological placebo responses to the symbols, rituals, and behaviors of the clinical encounter ('placebo effects') from spontaneous remission, regression to the mean, and the natural waxing and waning of illness. The main reason for this gap is simple: trials are interested in testing drug efficacy, and randomization to active treatment or placebo is thought to be a sufficient measure by which to allow clinical trial researchers to discern specific drug responses. Any improvement in subjects in the placebo arm has generally been ignored and viewed as an intrusive but necessary hurdle to overcome. However, without studies that have NTCs as a control for the placebo arm, an accurate and comprehensive view of the set of potential placebo genetic biomarkers (the placebome) may
not easily become available.
Despite this limitation, we can cull information about the genes involved in the placebome from three types of available studies in the literature: (i) a small RCT investigating placebo responses that included a NTC and conducted a candidate gene analysis; (ii) placebo-controlled RCTs in patients that included an analysis of candidate genes that coincide with genes implicated in the placebo response mechanism; and (iii) experimental studies in healthy subjects that examined candidate placebo genes.

...first published in 1978 followed by a series of studies on placebo effects in molar extraction [13]. In this and subsequent studies, Levine et al. demonstrated that the pain suppression system of the body could be induced by placebo and was, in turn, blocked by naloxone, an opioid receptor antagonist. Further studies by this group hypothesized that morphine and placebo might share a common opioidergic mechanism and estimated the placebo analgesic effect to be equivalent to up to 8 mg of morphine [14,15]. As the opioid system emerged as a major underlying biochemical mechanism involved in placebo analgesia, the role of mu opioid receptors in placebo analgesia was further confirmed in neuroimaging studies [16-19]. These studies used pain models to demonstrate that expectation of analgesia induced activity in key areas in the brain involved in endogenous opioid transmission and analgesia. Since these early studies, placebo researchers also raised the possibility that the opioidergic system is not exclusively responsible for placebo analgesia [12]...This growing list of neurotransmitters and neurological pathways mediating the placebo response provides a framework for candidate gene analyses. Indeed, treatment outcomes in the placebo arms of trials that have assessed genetic variation in the dopaminergic, opioid, cannabinoid, and serotonergic pathways suggest that genetic variation in the synthesis, signaling, and metabolism of these neurotransmitters contributes to variation in the placebo response (Table 1).

...Rs4680, the most studied polymorphism in dopamine metabolism, is in the gene encoding catechol-O-methyltransferase (COMT), an enzyme that metabolizes dopamine and other catecholamines [33]. The rs4680 SNP has been implicated in modifying clinical outcomes in both the placebo and drug treatment arms of numerous diverse trials [34- 44]. Rs4680 encodes a valine (val)to-methionine (met) change at codon 158 (val158met), resulting in a three four times reduction in enzymatic activity. Homozygotes of the less-active met allele have been associated with higher levels of dopamine in the prefrontal cortex, a region implicated in the placebo response pathway [45,46]. Rs4680 is a common polymorphism, and the prevalence of the less-frequent met allele or minor allele (MAF) is reported as 0.37 in Caucasians [47], but varies by race and/or ethnicity [48,49]. The high MAF of rs4680 translates to an estimated 20-25% of met/met individuals in Caucasian populations. Finding common SNPs is an important criterion when considering the feasibility of using genotype as a predictive placebo-response marker.
To our knowledge, the only candidate genetic association study that included a NTC and examined the effect of genetic variation in COMT on the placebo response [38] used an RCT designed to test whether placebo treatment could incrementally combine three components related to placebos: diagnosis and observation (NTC arm), therapeutic apparatus (placebo acupuncture), and apparatus plus a supportive patient-practitioner relation (placebo acupuncture plus a warm-caring provider) [50]. The RCT was a 3week trial in patients with irritable bowel syndrome (IBS), and the main outcome was reduction in IBS symptom severity. Patients in the arm that combined all the components, the strongest placebo treatment, reported the greatest symptom relief. The candidate genetic analysis performed on a subset of these patients, who gave genetic informed consent, looked at the association of rs4680 with IBS symptom severity, adequate relief, and quality of life in each of the treatment arms. Patients homozygous for the rs4680 low-activity met allele (met/met), known to have high levels of dopamine, had the greatest placebo response. The high-activity val allele homozygous (val/val) patients had the lowest placebo response. The val/met heterozygotes had an intermediate response. Similar results were reported for another COMT SNP, rs4633, which is closely linked to rs4680.
A subsequent small acute-pain model placebo neuroimaging study in healthy volunteers looked at genetic variation in COMT in relation to brain activity in the reward system using resting-state functional magnetic resonance imaging [51]. These researchers showed that placebo response to pain in healthy volunteers supported the IBS results, such that the number of rs4680 met alleles was linearly correlated with suppression of pain in the placebo expectation laboratory paradigm. While not having a NTC, the pain stimulation in this experiment was momentary, precise, and calibrated, so we can assume that spontaneous remission and waxing and waning of illness were not potential confounders.
Interestingly, a recent laboratory study found that the rs4680 high-activity val allele was associated with a higher frequency of nocebo effects (negative placebo adverse effect) using a model of learned immunosuppression [52]. Similarly, in the IBS placebo study discussed previously, the rs4680 high-activity val allele was associated with a higher frequency of complaint reporting [40]. This association of nocebo effect with the high-activity rs4680 val allele is not necessarily unexpected, given that in the absence of any significant improvements in symptoms derived from a placebo response, val/val individuals may have more complaints or experience more adverse effects.

- 33. Lachman, H.M. et al. (1996) Human catechol-O-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics 6, 243–250
- 38. Hall, K.T. et al. (2012) Catechol-O-methyltransferase val158met polymorphism predicts placebo effect in irritable bowel syndrome. PLoS ONE 7, e48135
- 39. Hall, K.T. et al. (2014) Polymorphisms in catechol-O-methyltransferase modify treatment effects of aspirin on risk of cardiovascular disease. Arterioscler. Thromb. Vasc. Biol. 34, 2160–2167
- 40. Hall, K.T. et al. (2015) Conscientiousness is modified by genetic variation in catechol-O-methyltransferase to reduce symptom complaints in IBS patients. Brain Behav. 5, e00294
- 50. Kaptchuk, T.J. et al. (2008) Components of placebo effect: randomised controlled trial in patients with irritable bowel syndrome. BMJ 336, 999–1003
- 51. Yu, R. et al. (2014) Placebo analgesia and reward processing: integrating genetics, personality, and intrinsic brain activity. Hum. Brain Mapp. 35, 4583–4593

[I'm val/val on this according to my 23andMe results.]

...In addition to COMT, there are several other polymorphisms in the dopamine pathway that are potential placebome candidates. Monoamine oxidase A (MAO-A) has been implicated in reward pathways through its role in catalyzing the oxidation of monoamines, including dopamine...The association of MAOA with treatment response to placebo was examined in a candidate gene analysis of patients with clinical depression from four combined small placebo-controlled RCTs of three selective serotonin reuptake inhibitor antidepressants (SSRIs), venlafaxine, sertraline, or fluoxetine [55]. The primary outcome was determined by the 17-item Hamilton Depression Rating Scale (HAM-D 17 ). Consistent with the findings described above for COMT, individuals with the low-activity MAOA genotypes and, therefore, higher basal dopamine tone, had a higher placebo response than those with the high-activity MAOA genotypes. The COMT rs4680 association with placebo response was also examined in this study, but the results were not significant. It is unclear whether the nonsignificant results with COMT were due to lack of power, a basic difference in the subject population, or other factors.
To our knowledge, the largest study of genetic variation in RCT patients randomized to placebo treatment examined 34 candidate genes (500 polymorphisms) in four trials of bupropion for major depressive disorder [43]. Although results for rs4680 were not reported in this trial, several other COMT SNPs were associated with placebo response and placebo remission (although these associations did not survive correction for multiple comparisons). The placebo response association with MAOA rs6609257, a SNP associated with dopamine basal tone, was one of the associations with treatment response in the placebo arm that was significant after correction, supporting the candidacy of MAOA in the placebome.
Genetic variations in dopamine receptor genes that modify dopaminergic signaling also modify the function of the brain reward circuit [56,57]. Rs6280 is a common serine-to-glycine coding polymorphism in dopamine receptor 3 (DRD3) that results in the DRD3 glycine form having a higher affinity for dopamine compared with the serine form [58]. A recent placebo-controlled RCT of a novel drug for treating symptoms of schizophrenia (ABT-925) examined the effects of genetic variation in DRD3 on the Positive and Negative Syndrome Scale (PANSS) [59]. Subjects homozygous for rs6280 serine allele (S/S) had significantly better outcomes in the placebo arm than when they were treated with increasing doses of ABT-95. Consistent with other studies, this study also showed that the COMT rs4680 met/met subjects had a higher placebo response...DBH was also one of the genes examined in the largest 34-candidate gene analysis of the placebo arm of the bupropion trial discussed above [43]. The DBH SNP rs2873804 survived the correction for multiple comparisons, reinforcing DBH as a potential candidate for a placebo response gene.

- 55. Leuchter, A.F. et al. (2009) Monoamine oxidase a and catechol-O- methyltransferase functional polymorphisms and the placebo response in major depressive disorder. J. Clin. Psychopharmacol. 29, 372–377
- 43. Tiwari, A.K. et al. (2013) Analysis of 34 candidate genes in bupropion and placebo remission. Int. J. Neuropsychopharmacol. 16, 771–781
- 56. Diaz, J. et al. (2000) Dopamine D3 receptors expressed by all mesencephalic dopamine neurons. J. Neurosci. 20, 8677–8684
- 57. Bouthenet, M.L. et al. (1991) Localization of dopamine D3 receptor mRNA in the rat brain using in situ hybridization histochemistry: comparison with dopamine D2 receptor mRNA. Brain Res. 564, 203–219
- 59. Bhathena, A. et al. (2013) Association of dopamine-related genetic to dopamine D3 receptor antagonist ABT-925 clinical response. Transl. Psychiatry 3, e245

...Endogenous opioids signal through opioid receptors, and genetic variation in the mu opioid receptor gene (OPRM1) has been shown to modify treatment outcomes in pain studies. The analgesic effects of placebo have been shown to be mediated through activation of endogenous opioid as well dopaminergic mechanisms. In a small experimental placebo study performed on healthy volunteers, signaling in the dopamine pathway was linked to opioid receptor signaling in antinociceptive responses to placebo [26]. Rs1799971 is a functional polymorphism in the OPRM1 gene that results in an asparagine-to-aspartic acid change at codon 40. The aspartic acid variant of the receptor was found to reduce receptor function across several studies [67,68]. The association of rs1799971 with placebo response in healthy volunteers was studied in an experimental model of placebo-induced analgesia [69]. In this study, placebo-induced activation of dopamine neurotransmission in the nucleus accumbens was greater in asparagine homozygotes compared with aspartic acid-allele carriers, suggesting that genetic variation in OPRM1 also contributes to variability in the placebo response.

- 26. Scott, D.J. et al. (2008) Placebo and nocebo effects are defined by opposite opioid and dopaminergic responses. Arch. Gen. Psychiatry 65, 220–231
- 67. Zhang, Y. et al. (2005) Allelic expression imbalance of human mu opioid receptor (OPRM1) caused by variant A118G. J. Biol. Chem. 280, 32618–32624
- 68. Kroslak, T. et al. (2007) The single nucleotide polymorphism A118G alters functional properties of the human mu opioid receptor. J. Neurochem. 103, 77–87
- 69. Pecina, M. et al. (2015) Effects of the mu opioid receptor polymorphism (OPRM1 A118G) on pain regulation, placebo effects and associated personality trait measures. Neuropsychopharmacology 40, 957–965

...The efficacy of a drug is determined by the difference between the aggregate outcomes of individuals randomized to drug versus placebo treatment. Therefore, the accuracy of the estimate of drug efficacy, especially in smaller trials depends on the randomization balancing the numbers of placebo responders by genotype across treatment arms. If by chance, in trials where the placebo response is known to be high (such as IBS [76]), there are more genetically predisposed placebo responders in the placebo arm than in the drug arm, the estimate of drug efficacy will be confounded by genotype and the results biased towards the null. If this imbalance is not accounted for, it would be expected to be more of a problem in smaller trials than larger trials. Ideally, RCTs would be designed such that the randomization balanced genetically predisposed placebo responders across all arms of a trial.

- 76. Patel, S.M. et al. (2005) The placebo effect in irritable bowel syndrome trials: a meta-analysis. Neurogastroenterol. Motil. 17, 332–340

...While studies have not as yet been conducted to identify genes and drugs that modify placebo response, hypothetically there may even be situations in which one might opt to intentionally use a drug to modify the placebo response. For instance, purposefully using a drug to inhibit the placebo response in clinical trials could minimize the placebo response and allow for a more accurate measurement of the drug effect. In this case, the placebo-modifying drug would be administered to both the drug treatment and placebo arm of the trial, and any potential drug-drug or gene-drug interactions would have to be well characterized. Given that so many future RCTs already include a placebo treatment arm and plan to collect -omics data, we propose that a cost-effective approach to elucidating the placebome would be to simply add NTCs to these studies.

...For example, good evidence suggests that persons homozygous for the low-activity met allele at COMT rs4680 (met/met) are more likely to respond to morphine than those homozygous for the val allele (val/ val) [87,88].

- 87. Rakvag, T.T. et al. (2008) Genetic variation in the catechol-O-methyltransferase (COMT) gene and morphine requirements in cancer patients with pain. Mol. Pain 4, 64
- 88. Rakvag, T.T. et al. (2005) The Val158Met polymorphism of the human catechol-O-methyltransferase (COMT) gene may influence morphine requirements in cancer pain patients. Pain 116, 73–78

...A key goal of the RCT is to detect a drug-placebo difference. There is a long and unsuccessful history of attempts to increase the efficiency of RCTs with placebo run-in periods that eliminate placebo responders [97- 99]. Could placebome data lead to new 'enrichment' strategies that could eliminate a priori high placebo responders in RCTs? Our discussion of placebo-drug interactions suggests that genetic profiles have the possibility of becoming an alternative strategy to make detection of drug-placebo difference more efficient.

- 97. Katz, N. (2005) Methodological issues in clinical trials of opioids for chronic pain. Neurology 65 (Suppl. 4), S32–S49
- 98. Lee, S. et al. (2004) Does elimination of placebo responders in a placebo run-in increase the treatment effect in randomized clinical trials? A meta-analytic evaluation. Depress. Anxiety 19, 10–19
- 99. Straube, S. et al. (2008) Enriched enrollment: definition and effects of enrichment and dose in trials of pregabalin and gabapentin in neuropathic pain. A systematic review. Br. J. Clin. Pharmacol. 66, 266–275"

Most of these variants are SNPs and available through commercial SNP providers; given the extreme inflation of effect sizes in the mentioned IBS trials (something like a 6x difference!), pinning down the genetics could make self-experiments much more effective and improve discourse around them - you could discard anecdotes from met/met on the COMT SNP, eg, and pay more attention to self-reports from val/vals.

#nootropics #quantifiedself #placebo