James J. Crowley

Depletion of serotonin and catecholamines block the acute behavioral response to different classes of antidepressant drugs in the mouse tail suspension test

RationaleFew studies have investiga.ted whether the behavioral effects elicited by different types of antidepressant drugs are mediated by either serotonin (5-HT) or the catecholamines norepinephrine (NE) and dopamine (DA).ObjectivesBy depleting 5-HT, or NE and DA, the present study investigated the contributions of these monoamines to the acute behavioral effects of selective serotonin reuptake inhibitors (SSRIs; fluoxetine and citalopram) and norepinephrine reuptake inhibitors (NRIs; desipramine and reboxetine) in the mouse tail suspension test (TST).ResultsDepletion of 5-HT tissue content by para-chlorophenylalanine (PCPA), an inhibitor of tryptophan hydroxylase, completely blocked reductions of immobility by the SSRIs in the TST. In contrast, PCPA did not alter the behavioral effects of the NRIs. Inhibition of catecholamine synthesis by α-methyl-para-tyrosine (AMPT) reduced brain NE and DA tissue content, whereas disruption of vesicular storage with reserpine decreased brain NE, DA and 5-HT tissue content. However, neither treatment completely prevented responses to desipramine, fluoxetine, or citalopram in the TST. Depleting both newly synthesized and vesicular components of NE and DA transmission with a combination of reserpine and AMPT completely prevented the behavioral effects of desipramine, reboxetine, and fluoxetine and attenuated those of citalopram. Although PCPA did not alter baseline immobility, AMPT and reserpine increased baseline values in the TST.ConclusionsThese studies demonstrated that endogenous 5-HT synthesis mediates the behavioral effects of SSRIs, but not NRIs, in the TST. In contrast, disruption of the behavioral effects of NRI and SSRI antidepressants required disruption of both catecholamine synthesis and vesicular storage and release mechanisms.

Copy number variation in schizophrenia in Sweden

Schizophrenia (SCZ) is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare copy number variations (CNVs) in SCZ cases and identified multiple rare recurrent CNVs that increase risk of SCZ although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for SCZ CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with SCZ using a Swedish national sample (4719 cases and 5917 controls). High-confidence CNV calls were generated using genotyping array intensity data, and their effect on risk of SCZ was measured. Our data confirm increased burden of large, rare CNVs in SCZ cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not SCZ. Intriguingly, gene set association analyses implicate biological pathways previously associated with SCZ through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500 kb) in genes present in the postsynaptic density, in genomic regions implicated via SCZ genome-wide association studies and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry—genome-wide screens for CNVs, common variation and exonic variation—are converging on similar sets of pathways and/or genes.

Strain-dependent antidepressant-like effects of citalopram in the mouse tail suspension test.

RationaleVariations in the effects of antidepressant drugs between different mouse strains are important for drug discovery and could lead to the identification of genes that predict differences in drug efficacy.ObjectivesThis study compared behavioral baselines and dose-dependent responses to the selective serotonin reuptake inhibitor (SSRI) citalopram in eight inbred mouse strains (C57BL/6J, DBA/2J, C3H/HeJ, BALB/cJ, A/J, 129/SvEmsJ, 129/SvImJ, and BTBR) using the tail suspension test (TST).ResultsThe DBA/2J, BALB/cJ, and BTBR strains were the most responsive to the effects of citalopram. Citalopram was least effective in the C57BL/6J and A/J strains. The antidepressant-like effects of citalopram in the TST were not correlated with changes in locomotor activity or deprivation-induced feeding behavior across the individual mouse strains, suggesting that patterns of sensitivity to citalopram are behaviorally specific and unlikely to result from pharmacokinetic variables. As an initial search for genetic polymorphisms causing differences in citalopram sensitivity, polymorphic forms of the tryptophan hydroxylase 2 (tph2) gene were genotyped and found to be not correlated with citalopram responsive (DBA/2J and BALB/cJ) and nonresponsive (A/J and C57BL/6J) strains.ConclusionsThe TST strain survey described here: (1) suggested the most appropriate strains for screening potential antidepressants, (2) identified parental strains appropriate for quantitative trait loci mapping of genomic loci regulating SSRI sensitivity, and (3) indicated appropriate background strains for measuring an antidepressant-like response to the SSRI citalopram. The pattern of response agrees with a previous mouse strain survey that examined sensitivity to fluoxetine in the forced swim test (Lucki I, Dalvi A, Mayorga AJ (2001) Sensitivity to the effects of pharmacologically selective antidepressants in different strains of mice. Psychopharmacology 155:315–322).

A genetic association study of the mu opioid receptor and severe opioid dependence.

Objectives Twin, family and adoption studies have suggested that vulnerability to opioid dependence may be a partially inherited trait (Cadoret et al., 1986; Merikangas et al., 1998; Tsuang et al., 1998, 2001). Studies using animal models also support a role for genetic factors in opioid dependence, and point to a locus of major effect on mouse chromosome 10 (Berrettini et al., 1994; Alexander et al., 1996), which harbors the mu opioid receptor gene (Mor1) (Kozak et al., 1994). The gene encoding the human mu opioid receptor (OPRM1) is thus an obvious candidate gene for contributing to opioid dependence. A recent report (Hoehe et al., 2000) found a significant association between a specific combination of OPRM1 single nucleotide polymorphisms (SNPs) and substance dependence. Methods In the current study, we genotyped 213 subjects with severe opioid dependence (89 African-Americans, 124 European-Americans) and 196 carefully screened ‘supercontrol’ subjects (96 African-Americans, 100 European-Americans) at five SNPs residing in the OPRM1 gene. The polymorphisms include three in the promoter region (T–1793A, –1699T insertion and A–1320G) and two in exon 1 (C+17T [Ala6Val] and A+118G [Asp40Asn]). Results Statistical analysis of the allele frequency differences between opioid-dependent and control subjects for each of the polymorphisms studied yielded P values in the range of 0.444–1.000. Haplotype analysis failed to identify any specific combination of SNPs associated with the phenotype. Conclusions Despite reasonable statistical power we found no evidence of association between the five mu opioid receptor polymorphisms studied and severe opioid dependence in our sample. There were, however, significant allele frequency differences between African-Americans and European-Americans for all five polymorphisms, irrespective of drug-dependent status. Linkage disequilibrium analysis of the African-American genotypes indicated linkage disequilibrium (P<0.0001) across the five-polymorphism, 1911 base pair region. In addition, only four haplotypes of these five polymorphisms are predicted to exist in African-Americans.

Automated tests for measuring the effects of antidepressants in mice

The forced swim test (FST) and the tail suspension test (TST) are used widely for measuring the pharmacological effects of antidepressant drugs or changes in stress-evoked behavior in mice. However, inconsistent scoring techniques and poor reproducibility may result from their reliance on subjective ratings by observers to score behavioral changes. In this paper, automated versions of the mouse FST and TST were characterized and validated against observer ratings. For the FST, a commercially available video tracking system (SMART II; San Diego Instruments) measured the duration that mice swam in water-filled cylinders at a set velocity. For the TST, a commercially available automated device (Med Associates, St. Albans, VT) measured input from a strain gauge to detect movements of mice suspended from an elevated bar. Dose-dependent effects of the antidepressant desipramine on FST and TST immobility were measured in CD-1 mice using both automated devices and manual scoring from videotapes. Similar dose-response curves were obtained using both methods. However, a wide range of correlations for raters in the FST indicated that scoring criteria varied for individual raters despite similar instructions. Automated versions of the mouse FST and TST are now available and provide several advantages, including an opportunity to standardize methods across laboratories.

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance

Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Because regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in further characterizing these mechanisms. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. Effects from these variants influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. We also observe two types of parent-of-origin effects, including classical imprinting and a new global allelic imbalance in expression favoring the paternal allele. We conclude that, as with humans, pervasive regulatory variation influences complex genetic traits in mice and provide a new resource toward understanding the genetic control of transcription in mammals.

Pharmacogenomic Evaluation of the Antidepressant Citalopram in the Mouse Tail Suspension Test

The identification of genetic variants regulating antidepressant response in human patients would allow for more individualized, rational, and successful drug treatments. We have previously identified the BALB/cJ inbred mouse strain as highly responsive to the selective serotonin reuptake inhibitor (SSRI) citalopram in the tail suspension test (TST), a widely used and well-established screening paradigm for detecting compounds with antidepressant activity. In contrast, A/J mice did not show a significant response to citalopram in this test despite exposure to equivalent plasma levels of the drug. To identify genetic determinants of this differential response, 506 F2 mice from an intercross between BALB/cJ and A/J mice were phenotyped. Composite interval mapping of 92 mice from the phenotypic extremes revealed three loci on chromosomes 7, 12, and 19 affecting citalopram response in the TST. The quantitative trait locus (QTL) at the telomeric end of chromosome 19 showed the greatest level of significance. Three candidate genes residing in this locus include those for vesicular monoamine transporter 2 (VMAT2, slc18a2), alpha 2A adrenergic receptor (adra2a), and beta 1 adrenergic receptor (adrb1). The protein coding regions of these three genes in BALB/cJ and A/J mice were sequenced and two polymorphisms were found in VMAT2 (Leu117Pro and Ser505Pro), while the transcribed regions of adra2a and adrb1 were of identical sequence between strains. Follow-up studies are needed to determine if the VMAT2 polymorphisms are functional and if they could explain the chromosome 19 QTL. The present quantitative trait study suggests possible candidate genes for human pharmacogenetic studies of therapeutic responses to SSRIs such as citalopram.

Pharmacogenomic genome-wide association studies: lessons learned thus far.

Over the past four years, the once hotly debated question of whether genomewide genetic mapping of common SNPs would shed light on common diseases has been answered with a resounding “yes”. More than 100 publications have now reported the localization of common SNPs associated with a wide range of common diseases (e.g., age-related macular degeneration, type 2 diabetes, Crohn’s disease, obesity) as well as various individual traits (height, hair color, eye color, freckling). As these publications accrued, a number of lessons regarding genetic mapping by genomewide association studies (GWAS) began to emerge (for a review see Altshuler et al, 2008 [1]). These lessons include: 1) effect sizes for common variants are typically modest; 2) with currently typical sample sizes (e.g., 2000 cases and 2000 controls), the power to detect associations has been low; 3) a single genomic region can harbor both common variants of weak effect and rare variants of large effect; 4) most confirmed associations do not involve candidate genes suspected on the basis of prior theory; 5) some associations implicate non–protein-coding regions; and 6) correlations between genetic variants and phenotypes have been limited by the accuracy and validity of the phenotypic measurement. As the number of published pharmacogenomic GWAS begins to accumulate, it is prudent to search for lessons from these early studies. A search of PubMed up to January 15th, 2009 yielded 11 articles that examined the association between a drug-induced phenotype and at least 100,000 genome-wide SNP markers. Table 1 provides an overview of these studies and their most significant findings (as always, the reader is encouraged to examine the primary literature for a more thorough description of these studies). The most prominent characteristic that distinguishes these GWAS from their disease-oriented counterparts is sample size. While disease GWAS now routinely exceed 2,000 cases and 2,000 controls, all of these early pharmacogenomic GWAS had sample sizes under 400 drug-treated individuals. This is not surprising considering the scarcity of available DNA samples from clinical studies, particularly for rare side effects, and the considerable expense and effort required to phenotype individuals for a drug response. While the cost per subject in a disease case-control study is generally

Patterns of Nonrandom Mating Within and Across 11 Major Psychiatric Disorders

500–1000, the typical cost per subject in a clinical trial ranges from

Opportunities to discover genes regulating depression and antidepressant response from rodent behavioral genetics.

5,000–30,000. While these facts have been used to argue against the use of GWAS for pharmacogenomics, we believe that these early publications have helped identify a set of important lessons: Table 1 Summary of published pharmacogenomic GWAS studies GWAS of rare adverse drug reactions (ADRs) may be more likely to yield highly penetrant variants. ADRs have a major impact on patients, physicians, health care providers, regulatory agencies and pharmaceutical companies. Identifying the genetic contributions to ADR risk may lead to a better understanding of the underlying mechanisms, identification of patients at risk, and clinical testing could lead to a decrease in ADR incidence. The SEARCH Collaborative group [2] carried out a GWAS in 85 subjects who developed a rare simvastatin-induced myopathy and 90 simvastatin-exposed controls who did not develop this serious side effect. They identified common variants in SLCO1B1, a gene involved in statin hepatic transport, with odds ratios of 4.5 for each copy of the risk allele. Sarasquete et al [3] searched a large group of multiple myeloma patients for individuals who developed bisphosphonate-induced jaw osteonecrosis, a side effect that occurs in ~4% of patients. After genotyping 22 cases and 65 matched controls, they identified SNPs in the CYP2C8 gene that may increase risk for osteonecrosis. Kindmark et al [4] conduced a retrospective case–control pharmacogenetic study of elevated serum alanine aminotransferase (ALAT) during long-term treatment with the oral direct thrombin inhibitor ximelagatran. This relatively small study (74 cases and 130 treated controls) yielded a strong, replicated genetic association between elevated ALAT and genetic variation in the major histocompatibility complex, suggesting a possible autoimmune pathogenesis. Cooper et al [5] performed a GWAS for the daily maintenance dose of the anticoagulant warfarin. This study replicated previous candidate gene studies that associated common SNPs in VKORC1 and CYP2C9 with large effects on warfarin dose. Use quantitative measures if possible. For the same sample size, quantitative measures will generally be more powerful than discrete measures. The ADR studies by Kindmark and Cooper are consistent with this idea. Turner et al [6] conducted a GWAS to identify novel genes influencing diastolic blood pressure response to hydrochlorothiazide, a commonly prescribed diuretic. They discovered a novel gene cluster (encompassing LYZ and YEATS4) that is highly associated with blood pressure response in individuals of both African and European origin. Common events (e.g., treatment outcome or non-response) may be more multi-determined and intrinsically less tractable for GWAS. Two studies in Table 1 that examined much more common side effects (Inada et al [7] and Volpi et al [8]) failed to identify significant associations, supporting the idea that rare side effects may be more likely to resemble ‘monogenetic traits’ and yield highly penetrant variants whereas common events may be akin to common diseases like type 2 diabetes mellitus. The latter requires very large studies given greater heterogeneity and far smaller genetic effects. Define responders and non-responders as the extremes of a larger distribution. Therapeutic response to a pharmaceutical agent is generally a complex trait that is influenced by numerous genetic and environmental factors. Therefore, assuming adherence, the magnitude of the intended drug response generally shows a continuous phenotypic distribution in outbred populations. Most patients experience a partial therapeutic response, while patients at the tails of the distribution receive either no benefit or a full response. Selective genotyping of individuals at the extremes of the distribution often provides nearly equivalent power to complete genotyping. In addition, the accuracy to which patients are called responders or non-responders is likely to be highest for patients at the extremes of the distribution. In the antihypertensive GWAS study mentioned above, Turner et al [6] screened 600 individuals for response to hydrochlorothiazide and selected the 200 “best” and 200 “poorest” responders for genotyping. They discovered a novel gene cluster associated with blood pressure response in individuals of both African and European origin. Two studies in Table 1 that defined responders and non-responders within the entirety of a small population (Mick et al [9] and Byun et al [10]) failed to identify significant associations, supporting the idea that focusing on extreme responders may be the most fruitful approach. These are, of course, early days in the GWAS era for the field of pharmacogenomics and these lessons outlined above may not stand the test of time. However, the take-home message seems to be that the current question of whether or not GWAS will shed light on differential drug response is beginning to look like a “yes” – provided a GWAS is done with care, thoughtfulness, and an awareness of the intricacies of the phenotype.