Pharmacosynthetics: Reimagining the pharmacogenetic approach

Pharmacology, in its broadest interpretation, is defined as the study of the interaction between physiological entities and drugs. In modern neuropsychopharmacology, this interaction is viewed as the drug itself on one side and signal transducer (receptor), the signal transduction cascade (effector proteins, second messengers), the cellular response (transcriptional regulation, activity modulation), the organ response (brain circuitry modulation), and, finally, the whole organism response (behavior) on the other. In other words, pharmacology has structured itself around the idea that the exogenous molecule (the drug) encodes a “signal” leading to everything on the other side including, in extreme renditions, a physiological response. The inference is that engaging a particular signal transduction pathway in a defined cell type leads inexorably to a prototypic physiological response. Thus, for instance, serotonergic activation of 5-HT2A receptors in rat aortic smooth muscle cells leads to an increase in intracellular Ca++ (via IP3 release) and smooth muscle contraction (Roth et al., 1986). Here, we suggest that the invention of synthetic ligand – GPCR pairs (aka DREADDs, RASSLS, ‘pharmacogenetics’) permits the study of pharmacology using a shifted equation: more of the signal transduction elements moved to the left and, subsequently, under experimental control. For the purposes of disambiguation and to clarify this new interpretation as a creation of pharmacological manipulation, we present the term pharmacosynthetics to describe what has heretofore been called pharmacogenetics or chemicogenetics. This review discusses this new interpretation and reviews recent applications of the technology and considerations of the approach

Assessing serotonin receptor mRNA editing frequency by a novel ultra high-throughput sequencing method

RNA editing is a post-transcriptional modification of pre-mRNA that results in increased diversity in transcriptomes and proteomes. It occurs in a wide variety of eukaryotic organisms and in some viruses. One of the most common forms of pre-mRNA editing is A-to-I editing, in which adenosine is deaminated to inosine, which is read as guanosine during translation. This phenomenon has been observed in numerous transcripts, including the mammalian 5-HT2C receptor, which can be edited at five distinct sites. Methods used to date to quantify 5-HT2C receptor editing are labor-intensive, expensive and provide limited information regarding the relative abundance of 5-HT2C receptor editing variants. Here, we present a novel, ultra high-throughput method to quantify 5-HT2C receptor editing, compare it to a more conventional method, and use it to assess the effect of a range of genetic and pharmacologic manipulations on 5-HT2C editing. We conclude that this new method is powerful and economical, and we provide evidence that alterations in 5-HT2C editing appear to be a result of regional changes in brain activity, rather than a mechanism to normalize 5-HT2C signaling

Elucidation of The Behavioral Program and Neuronal Network Encoded by Dorsal Raphe Serotonergic Neurons

Elucidating how the brain's serotonergic network mediates diverse behavioral actions over both relatively short (minutes–hours) and long period of time (days–weeks) remains a major challenge for neuroscience. Our relative ignorance is largely due to the lack of technologies with robustness, reversibility, and spatio-temporal control. Recently, we have demonstrated that our chemogenetic approach (eg, Designer Receptors Exclusively Activated by Designer Drugs (DREADDs)) provides a reliable and robust tool for controlling genetically defined neural populations. Here we show how short- and long-term activation of dorsal raphe nucleus (DRN) serotonergic neurons induces robust behavioral responses. We found that both short- and long-term activation of DRN serotonergic neurons induce antidepressant-like behavioral responses. However, only short-term activation induces anxiogenic-like behaviors. In parallel, these behavioral phenotypes were associated with a metabolic map of whole brain network activity via a recently developed non-invasive imaging technology DREAMM (DREADD Associated Metabolic Mapping). Our findings reveal a previously unappreciated brain network elicited by selective activation of DRN serotonin neurons and illuminate potential therapeutic and adverse effects of drugs targeting DRN neurons

In Vitro and In Vivo Characterization of the Alkaloid Nuciferine

RationaleThe sacred lotus (Nelumbo nucifera) contains many phytochemicals and has a history of human use. To determine which compounds may be responsible for reported psychotropic effects, we used in silico predictions of the identified phytochemicals. Nuciferine, an alkaloid component of Nelumbo nucifera and Nymphaea caerulea, had a predicted molecular profile similar to antipsychotic compounds. Our study characterizes nuciferine using in vitro and in vivo pharmacological assays.MethodsNuciferine was first characterized in silico using the similarity ensemble approach, and was followed by further characterization and validation using the Psychoactive Drug Screening Program of the National Institute of Mental Health. Nuciferine was then tested in vivo in the head-twitch response, pre-pulse inhibition, hyperlocomotor activity, and drug discrimination paradigms.ResultsNuciferine shares a receptor profile similar to aripiprazole-like antipsychotic drugs. Nuciferine was an antagonist at 5-HT2A, 5-HT2C, and 5-HT2B, an inverse agonist at 5-HT7, a partial agonist at D2, D5 and 5-HT6, an agonist at 5-HT1A and D4 receptors, and inhibited the dopamine transporter. In rodent models relevant to antipsychotic drug action, nuciferine blocked head-twitch responses and discriminative stimulus effects of a 5-HT2A agonist, substituted for clozapine discriminative stimulus, enhanced amphetamine induced locomotor activity, inhibited phencyclidine (PCP)-induced locomotor activity, and rescued PCP-induced disruption of prepulse inhibition without induction of catalepsy.ConclusionsThe molecular profile of nuciferine was similar but not identical to that shared with several approved antipsychotic drugs suggesting that nuciferine has atypical antipsychotic-like actions

Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65

At least 120 non-olfactory G protein-coupled receptors in the human genome are ”orphans” for which endogenous ligands are unknown, and many have no selective ligands, hindering elucidation of their biological functions and clinical relevance. Among these is GPR68, a proton receptor that lacks small molecule modulators for probing its biology. Yeast-based screens against GPR68 identified the benzodiazepine drug lorazepam as a non-selective GPR68 positive allosteric modulator. Over 3000 GPR68 homology models were refined to recognize lorazepam in a putative allosteric site. Docking 3.1 million molecules predicted new GPR68 modulators many of which were confirmed in functional assays. One potent GPR68 modulator—ogerin– suppressed recall in fear conditioning in wild-type, but not in GPR68 knockout mice. The same approach led to the discovery of allosteric agonists and negative allosteric modulators for GPR65. Combining physical and structure-based screening may be broadly useful for ligand discovery for understudied and orphan GPCRs

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe