New data on the pharmacology of tricyclic antidepressants (TCAs), their affinities for human cloned CNS receptors and their cytochrome P450 enzyme inhibition profiles, allow improved deductions concerning their effects and interactions and indicate which of the TCAs are the most useful. The relative toxicity of TCAs continues to be more precisely defined, as do TCA interactions with selective serotonin reuptake inhibitors (SSRIs). TCA interactions with monoamine oxidase inhibitors (MAOIs) have been, historically, an uncertain and difficult question, but are now well understood, although this is not reflected in the literature. The data indicate that nortriptyline and desipramine have the most pharmacologically desirable characteristics as noradrenaline reuptake inhibitors (NRIs), and as drugs with few interactions that are also safe when coadministered with either MAOIs or SSRIs. Clomipramine is the only available antidepressant drug that has good evidence of clinically relevant serotonin and noradrenaline reuptake inhibition (SNRI). These data assist drug selection for monotherapy and combination therapy and predict reliably how and why pharmacodynamic and pharmacokinetic interactions occur. In comparison, two newer drugs proposed to have SNRI properties, duloxetine and venlafaxine, may have insufficient NRI potency to be effective SNRIs. Combinations such as sertraline and nortriptyline may therefore offer advantages over drugs like venlafaxine that have fixed ratios of SRI/NRI effects that are not ideal. However, no TCA/SSRI combination is sufficiently safe to be universally applicable without expert knowledge. Standard texts (e.g. the British National Formulary) and treatment guidelines would benefit by taking account of these new data and understandings.

British Journal of Pharmacology (2007) 151, 737–748; doi:10.1038/sj.bjp.0707253

Abbreviations:

CYP450: cytochrome P450 enzymes
HCR: human cloned receptor
NAT: noradrenaline transporter
PM, IM, UM: poor, intermediate, ultrarapid, metabolizer
SERT: serotonin transporter
SS: serotonin syndrome
ST: serotonin toxicity
(S)SRIs: selective serotonin reuptake inhibitors
(S)NRIs: serotonin and noradrenaline reuptake inhibitors
TCAs: tricyclic antidepressants
TYR30: pressor response to tyramine

Introduction

There are significant new data concerning the pharmacological properties of tricyclic antidepressants (TCAs), and particularly new data resulting from assays using human cloned receptors (HCRs), the primary focus in this review, which allow more accurate measurement of affinities at a range of CNS receptors. There are gaps in the data and further information that would be useful, such as estimates using the identified subtypes of 5-HT₂ and α₁ and α₂ adrenoceptors. This review indicates which drugs might best be prioritized in further work. It also highlights areas where data are lacking, such as systematic assessment of interactions with ion channels, needed to allow comparison with human overdose fatality and animal toxicity studies. Knowledge of cytochrome P450 (CYP450) enzyme inhibition profiles and interactions continues to increase and these data assist in the prediction of drug–drug interactions. It is therefore useful to reconsider TCAs, especially in relation to newer drugs. The main post-selective serotonin reuptake inhibitor (SSRI), ‘third generation’, drugs that are achieving clinical or commercial success are those that are proposed to have dual action as both serotonin and noradrenaline reuptake inhibitors (SNRIs), which is a property also possessed by one or more of the TCAs. These data are relevant to confirming which TCAs are the optimal SNRIs and the safest, both in overdose, and in respect of their interactions with SSRIs and with monoamine oxidase inhibitors (MAOIs). These interactions have been, historically, a difficult area to research and have been surrounded by uncertainty and controversy. Although it is generally stated to be unsafe to combine TCAs with MAOIs, or TCAs with SSRIs, such combinations are widely used in practice. Approximately 5% of all prescriptions for SSRIs involved coadministration with other antidepressants in an Australian sample (^{McManus et al., 2001}), and in a recent Canadian study, the figure was 9% (^{Patten and Beck, 2004}). Combinations may be the subject of medico-legal actions and allegations of professional misconduct. Some authorities continue to view the combination of TCAs with MAOIs as an appropriate treatment in special situations (^{Cowen, 2005}). Recent new data about serotonin syndrome (SS), now usually referred to as serotonin toxicity (ST), indicate clearly which TCAs are risky in combination with MAOIs (^{Gillman, 2006a}).

Uncertainty remains about which pharmacological properties of antidepressants are relevant for antidepressant efficacy, or for efficacy in migraine and pain syndromes. Generally speaking clear evidence for superiority of one member of the class, over the others, is lacking. However, there is closer agreement on which properties produce side effects and how these vary between different TCAs.

General pharmacology

The main advances in our understanding of the TCA pharmacology relate to interactions with other drugs, especially interactions involving CYP450 enzymes, prediction of metabolism from genotyping and to the relative toxicity in overdose of individual drugs. Also, it has recently become possible to estimate what potency, at the serotonin and the noradrenaline transporters (SERT and NAT), is necessary for a drug to exhibit useful clinical effects.

A brief summary of TCA general pharmacology is given below, but for a detailed review see ^{Rudorfer and Potter (1999)}. The structures of all antidepressants are available via PubChem (see websites).

Pharmacokinetics

All TCAs are rapidly absorbed after oral administration and bind strongly to plasma albumin, 90–95% at therapeutic plasma concentrations. They bind to extravascular tissues, which accounts for their large distribution volumes (10–50 l kg⁻¹) (^{Dawson, 2004}; ^{Brunton et al., 2006}). Inactivation occurs largely via CYP450 enzymes, by demethylation of tertiary TCAs to their secondary amine metabolites, hydroxylation, then glucuronidation and excretion in the urine. Plasma concentrations for therapeutic effect are usually stated to be between 50 and 300 ng ml⁻¹ (molecular weights, range 263–314). Ranges for particular drugs remain approximations and will be improved with further data. Both of the secondary amine drugs, desipramine and nortriptyline, have higher tissue and red blood cell concentrations than the others (^{Amitai and Frischer, 2004}, ²⁰⁰⁶), which are tertiary amines as well as greater NRI potency. Further research is needed to provide data concerning brain concentrations and receptor occupancy at the NAT (but see the data below on the SERT; ^{Meyer et al., 2004}), but there is no NAT radiotracer available as yet to permit the necessary measurements.

Toxic effects and fatalities are expected when plasma concentrations reach approximately 1000 ng ml⁻¹. ‘Patients with plasma TCA concentrations greater than 450 ng ml⁻¹ tend to develop cognitive or behavioural toxicity (agitation, confusion, memory impairment, pacing). Major toxicity and death is associated with concentrations above 1000 ng ml⁻¹ (^{Dawson, 2004}). Toxicity and death are regularly reported at levels of 2000–3000 ng ml⁻¹ with most TCAs (^{Schulz and Schmoldt, 2003}), particularly with dothiepin where levels of only 1000 ng ml⁻¹ have been fatal (^{Schulz and Schmoldt, 1994}; ^{Keller et al., 2000}).

Relative toxicities

It is now clearly established, from the prospectively recorded data in the Hunter Area Toxicity Service (HATS) database of thousands of intoxications with antidepressants, that dothiepin is substantially more toxic in overdose than all the other TCAs; the odds ratio for seizures with dothiepin vs other TCAs was 3.4 (95% CI 1.2–9.9), and for venlafaxine vs TCAs it was 4.4 (95% CI 1.4–13.8) (^{Whyte et al., 2003}). It may be noted that desipramine's apparent greater than average toxicity may be an artefact of excessive defined daily dose and tablet sizes: if, when positron emission tomography (PET) studies with NRIs become possible, it were to be shown to have equivalent NAT occupancy at doses of 5–25 mg, then it would be much less toxic at a reduced defined daily dose. This serves as an example of how improved understanding of pharmacology may lead to a re-examination of previous data (about dose equivalence) that are sometimes based on incomplete evidence (a lack of direct dose range comparisons between antidepressants).

The HATS data are the first prospectively collected large series that enable confident estimates of the relative cardiac and CNS (pro-convulsant) toxicity of the TCAs. This unique database illustrates the value of systematically collected data (^{Gillman and Whyte, 2004}; ^{Whyte, 2004}). Larger scale collection of toxicity data on drugs (i.e., from multiple centres) would be expected to speedup this important process in the future. Such data are of great importance, because current estimates of the relevance of different ion channel properties of all psychotropic drugs require confirmation from data on human overdoses in order to improve confidence concerning correlations between various kinds of toxicity and ion channels (^{Sala et al., 2006}). These mechanisms are not yet well elucidated. It is not possible to predict either cardiac or CNS toxicity with pharmacological data of receptor profiles (^{Buckley and Mcmanus, 1998}). The role of particular ion channels in cardiac or CNS toxicity has not been systematically investigated by screening of all TCAs (or other antidepressants) at known ion channels (^{Khalifa et al., 1999}; ^{Witchel et al., 2003}; ^{Thanacoody and Thomas, 2005}). There are insufficient accurate comparative data on either the cardiac or CNS toxicity of TCAs in humans to correlate reliably with ion channel blockade. HERG potassium channels are implicated for neuroleptics, but the relationship is not yet clear or reliable for drug screening during development (^{Kongsamut et al., 2002}; ^{Shah, 2005}). The effects of relatively few TCAs have been assayed at ion channels (^{Teschemacher et al., 1999}; ^{Jo et al., 2000}; ^{Nicholson et al., 2002}).

Nevertheless, what is clear from current toxicity data is that nortriptyline is less toxic than other TCAs and also than venlafaxine (the non-TCA SNRI antidepressant), both for complications following overdose and for overall deaths. The mortality from nortriptyline in overdose (5.5 deaths per million scripts (CI 2.2–11.4)) is similar to that from SSRIs, and better than both dothiepin (53.3 (CI 50.5–56.1)) (^{Buckley, 2002}; ^{Whyte et al., 2003})) and venlafaxine (13.2 deaths per million scripts (CI 9.2–18.5)).

Cytochrome P450 enzyme interactions

Data on TCAs and CYP450 enzymes continue to accumulate: it is now clear that the TCAs are less problematic for such interactions than the SSRIs. There has been no systematic screening of TCAs for CYP450 interactions; the most recent data from available sources are summarized in Table 1. These data allow estimates of what differential doses are indicated for subjects with known CYP450 allelic variants (Table 2a and b). For instance, poor (slow) metabolizers (PMs) of nortriptyline are likely to require approximately 50 mg daily, whereas ultrarapid metabolizers (UMs) will require 150 mg. Current commercial assays such as the ‘Amplichip’ will require regular updating. Indeed, it has only recently been discovered that 18% of Swedes have an ultrarapid CYP450 2C19 isoform (^{Sim et al., 2006b}), which is likely to cause therapeutic failures with the usual doses of CYP2C19 substrates, such as proton pump inhibitors and antidepressants. Current data and important links may be found on the home page of the ‘Human Cytochrome P450 (CYP) Allele Nomenclature Committee’; this website covers the nomenclature for polymorphic alleles of CYP isoforms (^{Sim and Ingelman-Sundberg, 2006a}).

Table 1. Degree of CYP450 enzyme inhibition of antidepressant drugs at their usual therapeutic dose

Drug	Cytochrome P450 enzyme inhibition
	2D6	1A2	3A4	2C9	2C19
Nortriptyline	+	0	0	0	+
Desipramine	+	0	0	0	+
Amitriptyline	+	++	0	+	+++
Imipramine	+	++	+	+	+++
Dothiepin	+	+?	0?	+?	+++?
Doxepin	+	+?	0?	+?	+++?
Clomipramine	+?	++?	0	+?	+++
Sertraline	+	0	0	0	0
Fluoxetine	+++	0	+	++	+++
Fluvoxamine	+	+++	++	+++	+++
Paroxetine	+++	0	0	0	0
Citalopram	++	0	0	0	0
Escitalopram	++	0	0	0	0
Venlafaxine	+	0	0	0	0
Duloxetine	++	0	0	0	0

Guide to approximate ranking of effect.
+=measurable, but likely to be clinically insignificant.
++=clinically significant, possibly serious with other drugs with narrow safety margins.
+++=large, often clinically significant, serious interactions highly predictable with certain drugs.
‘?’ indicates an estimate from structurally related drugs, because there are no data available for that specific drug.
No data known for lofepramine.
Data from ^{Albers et al. (2000)}, ^{Brosen (2004)}, ^{Danie et al. (2001)}, ^{Ingelman-Sundberg (2005)}, ^{Preskorn et al. (2006a}, ^2006b), ^{Preskorn (2003)}, ^{Shin et al. (2002)}, ^{Skinner et al. (2003)}, ^{Szewczuk-Boguslawska et al. (2004)} and ^{von Moltke et al. (1995)}. See also http://medicine.iupui.edu/flockhart/clinlist.htm.

Table 2a. Cytochrome P450 enzyme metabolism of tertiary amine TCAs

	1A2	2C19	3A4	2D6	T_1/2	T_max
Polymorphisms	CYP1A2^a	PM – 5% UM – 18%	^a	See 2b
Amitriptyline	++	+++	++?	+	10–46	2–4
Imipramine	++	+++	++?	+	4–34	1–3
Dothiepin	++?	+++?	++?	+	15–30	1–3
Doxepin	++?	+++?	++?	+	8–36	1–3
Clomipramine	++	+++	++	+	15–37	1–3

Abbreviation: TCA, tricyclic antidepressants.
See for allelic variants http://www.cypalleles.ki.se/ (^{Sim and Ingelman-Sundberg, 2006a}).
^a For prevalence of 3A4 in different populations (^{Lamba et al., 2002}; ^{Westlind-Johnsson et al., 2006}), of other CYP450s (^{Mizutani, 2003}; ^{Solus et al., 2004}). Clomipramine desmethylclomipramine ratio averaged 1 in Japanese vs 0.5 in Swedes (^{Shimoda et al., 1999}), related to higher rate of UMs in Swedes. CYP2C19 is also important for amitriptyline metabolism (^{Jiang et al., 2002}; ^{Vandel et al., 1995}), role of CYP3A4 and 2C19 (^{Nielsen et al., 1996}). CYP2D6, vs 2C19, inhibitors have a lesser effect on amitriptyline and imipramine levels (^{Leucht et al., 2000}). CYP1A2 genotype shows more than 60-fold inter-individual differences in constitutive expression, but no SNP or haplotype has yet been identified that can predict the metabolic phenotype (^{Jiang et al., 2006}). Other references (^{Geister et al., 2001}; ^{Ullmann et al., 2001}).

Table 2b. Cytochrome P450 enzyme 2D6 metabolism of secondary amine antidepressant drugs

Polymorphisms	PM – 5.5%, UM – 5%. Dose adjustment- PM 50=UM 150 mg day⁻¹	T_1/2	T_max
Nortriptyline	+++	13–90 (UM 13–35)	2–6
Desipramine	+++	15–50 (UM 15–24)	2–6

CYP2D6 substrates are lipophilic bases with a protonable nitrogen atom, which include all TCAs (^{Bertilsson et al., 2002}; ^{Ingelman-Sundberg, 2005}; ^{Johansson et al., 1993}, but see also ^{Bogni et al., 2005} concerning variation in substrate specificity). Usually stated value ranges for T_1/2, T_max (^{Bezchlibnyk-Butler and Jeffries, 2005}; ^{Brunton et al., 2006}). Data on desipramine (^{Furman et al., 2004}) and nortriptyline (^{Yue et al., 1998}). For allelic variants see http://www.cypalleles.ki.se/cyp2d6.htm.

Desipramine and nortriptyline are the least problematic of the TCAs in terms of drug interactions, being only weak CYP450 2D6 inhibitors (Table 1). They are unlikely to be involved in clinically relevant interactions unless the serum levels are high, for example following overdose, or in PMs. The tertiary amine TCAs amitriptyline, imipramine, clomipramine, dothiepin and doxepin are more potent CYP450 inhibitors, and significantly inhibit CYP450 2C19 and 1A2 (Table 1). However, there are significant gaps in these data that are indicated by a question mark against the suggested likely degree of inhibition for those drugs where actual estimations are wanting. Doxepin, used as a sedative in doses of 5–25 mg, is unlikely to cause clinically significant interactions, but an interaction with phenytoin and other drugs dependent on CYP2C19 is possible if it is used in larger doses. TCAs are less troublesome than the SSRIs in relation to CYP450 interactions. Indeed, of the SSRIs, Preskorn has suggested that fluoxetine and fluvoxamine, ‘… would likely not be approved today for this reason and should be used cautiously, if at all’ (^{Preskorn and Flockhart, 2006a}), and other authors have made similar comments (^{Gillman, 2005a}). Just one-tenth of the minimum recommended dose (100 mg) of fluvoxamine (i.e., 10 mg) significantly inhibits caffeine metabolism via CYP450 1A2 (^{Christensen et al., 2002}). Most SSRIs inhibit the metabolism of many other commonly used drugs via CYP450 enzymes to a clinically significant extent (Table 1), including the metabolism of most TCAs. It is essential to be fully informed about these pharmacokinetic interactions between TCAs and SSRIs to avoid the many possible problematic and even dangerous combinations, and to make compensatory dosage adjustments. It is notable that fluvoxamine has been documented to raise concentrations of clomipramine (in patients taking a usual therapeutic dose) to greater than 1200 ng ml⁻¹ (^{Szegedi et al., 1996}), and it would be expected to raise concentrations of dothiepin also. These data suggest that dothiepin and fluvoxamine may be the most toxic of all possible combinations of SSRIs and TCAs and should probably not be used. However, there is a paucity of actual reports of toxicity with this combination and no specific pharmacokinetic interaction data. This emphasizes the importance of further research to fill in the missing data. It may be noted that dosage adjustments are also essential in patients not in danger of drug–drug interactions. This is because of the significant proportion of genotypic PMs and UMs in all populations (Tables 2a and b) who require similar care and monitoring for side effects and toxic effects as do those experiencing drug–drug interactions. Therapeutic drug monitoring has been both under used and misused (^{Preskorn, 1986}; ^{Baumann et al., 2004}; ^{Mann et al., 2006}); although not always economical in a narrowly defined sense, its more widespread use may foster increased knowledge and awareness. Administering CYP450 inhibiting SSRIs adds phenotypic emulation to the genotypic poor metabolizers (PMs) that already exist. The ‘AmpliChip CYP450 Test’ for assessing CYP450 2D6 and 2C19 genotype has recently been approved by the FDA in America (^{de Leon et al., 2006}). Table 2a and b shows the CYP450 enzymes involved in the pathways for inactivation of the TCAs and it is noteworthy that only desipramine and nortriptyline are dependent on only one isoform, CYP2D6, for their inactivation, which is thus more predictable with genetic data.

Receptor pharmacology

Previous estimations of the postsynaptic receptor affinities relied on experiments carried out in various animal tissues and subsequently in human cortical postmortem tissue (^{Richelson, 1984}, ¹⁹⁹¹; ^{Bolden-Watson and Richelson, 1993}). Such work is expensive and time-consuming and, until the advent of HCRs, it was less easy to do extensive batteries of receptor assays (Table 3) that produce results allowing improved accuracy of comparisons between assays performed in different laboratories. The variations between different HCR assays are approximately tenfold (ranges are given in Table 4). ^{Richelson (2001}, ²⁰⁰³) has previously reviewed the results of his own HCR studies. However, no review of the range of data now available for TCAs has been undertaken. Much of these data have been collected by the Psychoactive Drug Screening Programme (PDSP) (^{Kroeze et al., 2003}), and other data have been found by the author, and added to that data base. These latest HCR data are therefore collated and presented in Table 3 (which gives all available values for TCAs) and Table 4 (which gives all available values relevant for comparison with proposed SNRI drugs). There are no new data for lofepramine, and a paucity of data on subtypes of 5-HT2 and α-adrenoceptors, makes it difficult to compare between drugs.

Table 3. Receptor profile, K_i (nmol/l), of TCAs and comparator drugs: uptake inhibition and receptor antagonism (HCR data)

Drug	Reuptake inhibition		Post-synaptic receptor antagonism
	5-HT	NA	H1	α₁	Musc	5-HT_2A
Mirtazapine*	>10 000	4600	0.14	500	670	16
Mianserin*	>4000	71	0.40	34	820	7
Doxepin	68	29.5	0.24	24	83	25
Amitriptyline	20	50	1	27	18	29
Imipramine	7	60	40	32	46	80
Clomipramine	0.14	54	15	32	25	35
Nortriptyline	100	10	6.3	55	37	44
Dothiepin	78	70	4	400	38	260
Desipramine*	18	0.83	110	100	100	280
Reboxetine*	58	7.2	310	>1000	>1000	>1000

Abbreviations: HCR, human cloned receptor.
Smaller K_i values represent greater potency. Note: where values are available from different laboratories and different experiments, affinities can vary by about one order of magnitude; mid-range values are given (Table 2a and b gives ranges).
Receptors: H1, Histamine type 1; Musc, acetylcholine muscarinic; α₁, α₁ adrenoceptor. Note that no HCR data are known for lofepramine.
All data have been extracted from PDSP K_i database, http://pdsp.med.unc.edu/pdsp.php (except *^{Richelson, 2001}).

Table 4. Human cloned receptor data for the affinity of antidepressants at the serotonin and noradrenaline transporters

Drug	TYR30	NA	5-HT	NA/5-HT
SSRIs (for comparison)		>1000	0.1–20	∼1:1000
Amitriptyline	N/A	19–102	2.8–36	∼1:1.5
Nortriptyline	+++	1.8–21	15–280
Clomipramine	N/A	54	0.14–0.3	∼2:1
Desmethylclomipramine*	+++	<1*	—
Imipramine	N/A	20–142	1.3–20	∼1:2
Desipramine	+++	0.63–8.6	22–180
Duloxetine**	0/+	7.5–20	0.8–3.7	∼10:1
Venlafaxine**	0/+	1420–6300	7.5–145	∼200:1
Sibutramine	—	No HCR data	No HCR data
Milnacipran**	—	151–200	68–123	∼1.7:1

Abbreviation: HCR, human cloned receptor.
TYR30 (tyramine pressor response) at recommended therapeutic dose, degree of reduction placebo NRI: +++=nearly complete inhibition of pressor response, that is, potent NRI effect.
For human in vivo considerations, the TCAs are grouped as pairs (because amitriptyline is metabolized into nortriptyline, clomipramine to desmethylclomipramine, and imipramine to desipramine. For TYR30 data, ‘N/A’ indicates that in vivo, parent drug cannot be present without greater effect from more potent NRI metabolite). The NA/5-HT ratio is approximated because varying in vivo levels of metabolites occur. Clomipramine is the only available drug with combined K_i's for both transporters greater than 1 (nM). It is unlikely that differing tissue levels would be sufficient to compensate for the low affinity of venlafaxine as an NRI (see text).
K_i (nM) data have been extracted from PDSP K_i database (http://pdsp.med.unc.edu/pdsp.php accessed June 2006), except:
* approximation from human cortex data, no HCR data available
** additional HCR values from ^{Vaishnavi et al. (2004)}.

The pharmacological origins of TCAs are reflected by their most potent common property, that of histamine H1 receptor antagonism. The neuroleptics and TCAs were developed from the antihistamines in the 1950s (^{Shen, 1999}; ^{Lopez-Munoz et al., 2004}). If they were now reclassified on the basis of present knowledge some, would be placed in different categories, for example, doxepin and trimipramine would be classified as antihistamines, not antidepressants, because of potent H1 antagonism and low NRI affinity, accompanied by failure to alter the tyramine pressor response (TYR30). The antihistamine chlorpheniramine is a more potent SRI than most of the TCAs currently used (^{Carlsson and Lindqvist, 1969}; ^{Gruetter et al., 1992}), although there are still no HCR data on this drug. The variation in the potency of TCAs as NRIs and SRIs is approximately 1000-fold (Tables 3 and 4). It is probable that it has an impact on their antidepressant efficacy; therefore, a reassessment of relative potency and efficacy would constitute a valuable test of the monoamine hypothesis of depression (see below). It can be argued that Bayesian reasoning makes it logical and necessary to require a higher standard of evidence for the antidepressant effect of a drug if it is not a reuptake inhibitor with sufficient potency to reduce the TYR30 response. If the monoamine hypothesis is correct, it would be surprising if clear differences in antidepressant efficacy could not be demonstrated between drugs whose transporter affinity differs by several orders of magnitude.

Sedation via histamine receptor H1 antagonism may add to therapeutic efficacy, but can also be a disadvantage in ambulant patients, if excessive. It is the most potent common property possessed by all tricyclic psychotropics, including the antihistamines and the neuroleptics. For all these classes of drugs, it is the potency at H1 receptors that best correlates with the degree of weight gain (^{Kroeze et al., 2003}) and sedation. Tables 3 and 6 indicate that the most potent and selective H1 antagonist is doxepin and it is sedative at doses of 5–25 mg. In view of its selectivity, it is the logical drug to use in combinations to obtain improvement in sleep. The 5-HT_2A, 5-HT_2B and 5-HT_2C receptors have roles in the regulation of sleep patterns, and antagonism of 5-HT_2A or 5-HT_2C receptors may improve sleep in depression (^{Sharpley et al., 2000}; ^{Thase, 2006}). The affinity of some TCAs at the 5-HT_2A receptor (Table 3) is clinically relevant, and may be responsible, at least to some degree, for their sleep-improving properties. As yet there are insufficient HCR data on 5-HT_2B or 5-HT_2C receptors to make comparisons. The affinity as α₁ adrenoceptor antagonists is very similar for all drugs except dothiepin. These values are reflected in the clinical experience of the degree of postural hypotension induced, which is least for dothiepin. Measurement of blood pressure assists dose increment decisions by identifying poor metabolizers who exhibit pronounced postural BP decreases (^{Smith, 2001}). The drop-out rates from side effects in clinical trials confirm that most patients tolerate a therapeutic dose without disabling postural hypotension. Postural hypotension therefore constitutes a useful clinical marker of the magnitude of these drugs' effect. The affinity for muscarinic receptors is responsible for the typical atropinic side effects of dry mouth, blurry vision, constipation, urine retention, recumbent tachycardia and memory impairment, which is especially relevant in the elderly, where delirium can result even from ‘therapeutic’ doses. Desipramine has significantly less affinity for muscarinic receptors than any other member of the class. There are insufficient data on muscarinic receptor subtypes (m1–6) to compare drugs (PDSP data).

Table 6. Comparative degree of potency of other TCAs when used at the equivalent sedative (H1 antagonist) dose of doxepin

Drug	H1	Musc	α₁
Amitriptyline	1:4	18:1	4:1
Nortriptyline^a	1:25	50:1	10:1
Dothiepin	1:15	10:1	1:1
Imipramine	1:170	85:1	100:1

Abbreviation: TCA, tricyclic antidepressants.
This table is like Table 5, but illustrates the relative potency for producing other effects if the listed drugs are compared as sedatives, at a dose that represents an equivalent H1 antagonist dose vs doxepin (given to one decimal rounded to nearest half).
^a eg NTP is 25 times less potent at H1 receptors, therefore at an H1 equivalent dose it is × 15 more potent at the muscarinic receptors (dry mouth, constipation, and so on) and × 15 more potent at α₁ receptors (hypotension).

The relationship of receptor affinity and therapeutic effect: serotonin reuptake inhibition and serotonin toxicity

If the monoamine theory of depression possesses heuristic utility, then what degree of affinity for the NAT represents a clinically effective level for an antidepressant effect? Clomipramine is effective for obsessive compulsive disorder and has high affinity for the SERT, but it remains uncertain if amitriptyline is significantly serotonergic: it has been regarded as an SNRI by many observers and included in meta-analyses comparing SNRIs with other antidepressants. Highly selective reuptake inhibitors now exist for both the NAT and the SERT and these appear to be effective antidepressants, although it is not yet established that they are as effective as TCAs in severe melancholic and psychotic depressions. ST data elucidate the clinical relevance of HCR data and thereby suggest what degree of potency is clinically meaningful. A detailed explanation and discussion of this is contained in a recent review (^{Gillman, 2006a}), including a discussion of the possible role of 5-HT_2A receptors. The SERT affinities of amitriptyline, imipramine and clomipramine have been correlated with their therapeutic profile. ST data and the putative serotonin-mediated disorders, obsessive compulsive disorder (^{Stein et al., 1995}; ^{Fineberg and Gale, 2005}) and cataplexy (^{Bassetti, 1999}; ^{Vignatelli et al., 2005}), illustrate the differences in the propensity to precipitate serotonin-related changes. These are proportional to the increasing affinity for the SERT of amitriptyline – weak, imipramine – intermediate, clomipramine – potent (Table 3). The most dramatic and serious drug interaction in humans is ST it can rapidly culminate in death from hyperthermia. This occurs predictably when a potent SRI is added to a therapeutic dose of an MAOI. Weakly serotonergic drugs such as L-tryptophan precipitate typical, dose-dependent, but mild, ST symptoms when combined with MAOIs (^{Oates and Sjoerdsma, 1960}). This indicates that even small elevations of serotonin, added to the effects of an MAOI, are sufficient to precipitate clinical features of ST (for a detailed exposition of this argument see ^{Gillman, 2006a}). Amitriptyline does not produce ST when added to an MAOI (^{Gillman, 1998}). It may thus be inferred that amitriptyline does not significantly raise serotonin levels in humans. In contrast, clomipramine frequently precipitates severe ST with MAOIs and causes fatalities. This indicates the SERT affinity at which TCAs become effective in raising serotonin; imipramine is intermediate. Although there are other potentially relevant factors such as variations in brain levels between different drugs, it is still possible to make an approximation allowing a comparison of TCAs with newer drugs proposed as SNRIs, such as venlafaxine.

The PET study of SERT binding from ^{Meyer et al. (2004)} demonstrates comparable SERT antagonism in human striatum (∼80%) from the minimum therapeutic dose of all the SSRIs and venlafaxine. That suggests two probable inferences: first, some other factor, for example, higher tissue levels, does indeed compensate for the low SERT affinity displayed by venlafaxine (Table 4), which is consonant with its relatively higher incidence of ST in overdose (twice that of SSRIs; ^{Whyte et al., 2003}). Second, a higher CNS tissue level (of venlafaxine compared to TCAs) is likely to be less than one order of magnitude of difference. If it was more than that, then venlafaxine would exhibit ST at therapeutic doses. This reasoning in turn indicates that the discrepancy between venlafaxine's SRI/NRI potency (approximately 200/1) is too large to enable substantial NRI effects at therapeutic doses, without engendering excessive serotonergic effects. That conclusion is congruent with the TYR30 data reviewed below. Data on ST indicate that the SERT affinity of amitriptyline and other tricyclics of lesser SERT affinity is insufficient to cause meaningful serotonergic effects in humans, whereas clomipramine causes marked and clinically relevant effects. This is in accordance with published reviews, which report ST only with imipramine and clomipramine, as reviewed in detail elsewhere (^{Gillman, 1998}, ^2006a). The difference in their affinity for the SERT is the most parsimonious explanation for this crucial difference. Further PET-derived SERT-binding studies, comparing all the TCAs directly under similar conditions, may further elucidate this important issue.

The relationship of receptor affinity and therapeutic effect: noradrenaline reuptake inhibition and the pressor response to tyramine

Similar considerations may give an indication of what degree of potency constitutes a clinically useful effect on the NAT. The most widely used experimental approach possible in humans is the pressor response to tyramine, the TYR30 test, which provides an in vivo index of peripheral NRI potency. This approach has recently been used in the first direct comparison between the posited SNRI, venlafaxine, and a TCA, desipramine (^{Blier et al., 2007}). Further systematic studies with a wider range of NRIs are needed: however, those available are reviewed below. When tyramine is administered intravenously, blood pressure increases and this response is greatly potentiated by MAOIs. Tyramine utilizes, and requires, the NAT to enter the pre-synaptic terminal, where it then induces depolarization-independent release of NA. NRIs inhibit tyramine uptake and thus attenuate the response, which gives an in vivo measure of their NRI potency: indeed the NRIs with the highest affinity for the NAT (reboxetine, desipramine and nortriptyline; Table 3) have all been demonstrated to block this response almost completely, even when it has been potentiated in the presence of MAOIs (^{Doggrell and Woodruff, 1977}; ^{Dostert et al., 1994}). The effect of TCAs on the TYR30 is proportional to their relative NRI potency in Tables 3 and 4 and only affinities such as that exhibited by nortriptyline, or greater, are associated with marked attenuation of the TYR30. The newer drugs (duloxetine and venlafaxine) that are posited to have SNRI properties have little or no effect on TYR30 (there are no known data for sibutramine or milnacipran). This appears proportional to their weaker NRI potency. Duloxetine, at the recommended maximum dose of 60 mg daily, attenuates TYR30 slightly (^{Turcotte et al., 2001}), in a dose-related manner which does not plateau, even at 240 mg day⁻¹ (^{Vincent et al., 2004}). ^{Chalon et al. (2003)} found no effect of duloxetine at a dose of 80 mg. Since the most parsimonious assumption is that a large effect on the TYR30 is required, rather than a barely detectable one, it is curious that these authors concluded, ‘the lack of a detectable impact of duloxetine on TYR PD30 suggests that this may not be the most sensitive indirect measure of NE reuptake when assessing dual reuptake inhibitors.’ Likewise, venlafaxine only marginally attenuates the pressor response, even at the usual maximum dose of 375 mg day⁻¹ (^{Harvey et al., 2000}). ^{Debonnel et al. (2007)} describe, with doses of 375 mg ‘… a significant attenuation of the pressor effect of tyramine. … it acted as a dual 5-HT and NE reuptake inhibitor.’ The magnitude of this ‘significant’ effect was small and was not directly compared with other more potent NRIs to provide a relative potency estimation. The sole direct comparison of venlafaxine with a TCA has been performed recently with desipramine. This demonstrates abolition of TYR30 response by desipramine 100 mg day⁻¹, and a small effect from venlafaxine 375 mg (^{Debonnel et al., 2007}).

A complete set of data comparing all the clinically used NRIs under the same conditions would be revealing, and would clarify further what constitutes clinically efficacious NRI potency, in the same way that ST data do for the serotonergic system. The present evidence indicates that drugs with an NRI potency less than nortriptyline may be suboptimally effective, because they produce only weak attenuation of the TYR30 response: that is, they do not produce a maximal effect on noradrenaline reuptake at therapeutic doses. There is no special evidence suggesting that the cerebral drug levels, or effects, differ much between TCAs; so the provisional supposition that the central effects would mirror the TYR30 data relatively closely seems reasonable. When a PET NAT ligand becomes available, the situation may be clarified.

Dothiepin (dosulepine), doxepin and trimipramine (not in table, because no HCR data are available), mianserin and mirtazapine (6-aza-mianserin) all have weak affinity for the NAT, and likewise have little or no effect on TYR30 (^{Ghose et al., 1976}; ^{Coppen et al., 1978}; ^{Pare et al., 1982}). If the monoamine theory is valid and NRIs are antidepressants, and if these drugs have no other mechanism of antidepressant action, this suggests that they may be insufficiently potent NRIs to be optimally effective. In contrast, clomipramine (via its in vivo metabolite, desmethylclomipramine), desipramine and nortriptyline produce marked attenuation of the TYR30 (^{Seppala et al., 1981}; ^{Blier et al., 2007}). A degree of SRI potency, as revealed by amitriptyline's small reduction of platelet serotonin, may constitute measurable serotonergic activity, but that cannot be equated logically with clinical efficacy via serotonin: that probably requires considerably more potent antagonism, as exemplified by clomipramine. Similarly, the observation that duloxetine and venlafaxine have a small effect on TYR30 does not adequately justify the assumption that their effect is clinically optimal. However, it does demonstrate that it is insufficient for maximal NRI efficacy and that they are substantially weaker NRIs in vivo than nortriptyline or desipramine. It may also be noted that the correlation between NRI affinity and the TYR30 response does suggest that widely varying tissue levels between different drugs are unlikely to be a major factor for comparisons between the structurally similar TCAs.

Discussion

Research in psychiatry is difficult and, despite many years of effort, it has proved surprisingly hard to produce unequivocal evidence to support the monoamine theory of depression. Most trials have necessarily involved assessments of drugs over relatively short periods of time. This, combined with the subjectivity involved in assessing depressive symptoms and the doubt about the longer term benefits of antidepressants, for instance on reducing suicide, presents considerable difficulties. This is not a review of efficacy trials, but a reminder that the uncertainties in the evidence serves to place in context the additional complicating factor of the difficultly in determining what clinical trial evidence to rely on.

The evidence is that double-blind trials are failing to remove observer and sponsorship bias and that the problems are made more significant because of lack of independent replication of research. One observer, Melander, has used the title ‘evidence b(i)ased medicine’ (^{Melander et al., 2003}) to convey this notion, and there are some concerns that undue weight is being given to biased evidence (^{Goodman, 1999}). ^{Melander et al. (2003)} examined SSRI trials specifically and concluded, ‘… the degree of multiple publication, selective publication, and selective reporting differed between products. Thus, any attempt to recommend a specific selective serotonin reuptake inhibitor from the publicly available data only is likely to be based on biased evidence’. Findings from meta-analyses are that SSRIs are significantly less effective than TCAs in more severe depression (^{Anderson, 1998}) and that venlafaxine may be more effective than SSRIs (^{Smith et al., 2002}). However, Anderson's meta-analyses have also demonstrated that pharmaceutical company sponsorship has an effect on outcome that accounted for as much of the effect size, as other variables (^{Anderson, 2001}; ^{Smith et al., 2002}). That result accords with a review covering 37 studies about sponsorship that showed a significant association between industry sponsorship and pro-industry conclusions (^{Bekelman et al., 2003}). ^{Parker et al. (2001)} discuss the evidence that in treatment of severe depression of the melancholic subtype, ECT, TCAs and MAOIs are the most effective treatments and that SSRIs are less effective. The lack of independent replication of studies is a significant weakness of methodology and has been shown to apply to both animal and human research. Thus, the assumption that mirtazapine is a dual action drug (^{Gupta et al., 2003}) has been shown to be based on unreliable and unreplicated evidence in both humans (^{Gillman, 2006b}) and animals (^{Millan et al., 2000}). A reassessment of the TCAs may be assisted by using new pharmacological data and Bayesian logic to guide further studies of these drugs. One pertinent example of this necessity for further studies is lofepramine. It is an analogue of imipramine, whose main active metabolite is thought to be desipramine. However, it is not included in this paper because there are no modern HCR data on its receptor-affinity profile its CYP450 enzyme profile, or other properties. Previous evidence strongly suggests that it has an excellent side-effect profile and low toxicity in overdose (^{Mason et al., 2000}; ^{Anderson, 2001}). It remains uncertain whether or not its clinical effect is via the metabolite, desipramine (^{Sanchez and Hyttel, 1999}): and no further significant research has been published since that review.

Psychiatrists continue to struggle to understand the antidepressant drug–drug interactions of TCAs. Disagreements of both opinion and fact are evident in reference texts (^{Ellis, 2004}; ^{Anon, 2005}; ^{Cowen, 2005}; ^{Rossi, 2007}) and in review papers (^{Amsterdam et al., 1997}; ^{DeBattista et al., 1998}; ^{Bonnet, 2003}). This applies particularly to TCA interactions with MAOIs (^{Gillman, 1998}, ^2006a; ^{Gillman and Whyte, 2004}). Specifically, it may be noted that it is now established why it is unsafe to combine some TCAs with MAOIs and also that there are no problematic pharmacokinetic interactions between these two groups of drugs. The problem with combining MAOIs with re-uptake inhibitors (i.e., either SSRIs or TCAs) is the pharmacodynamic interaction of ST (SS). This reaction only occurs with drugs that possess potency as SRIs. Of the TCAs, this only includes imipramine and clomipramine. The other TCAs are safe to combine with the MAOIs because they do not possess significant SRI potency (Table 3). Some other important and widely used drugs that have sufficient SRI potency to be potentially at risk of precipitating ST are tramadol, meperidine (pethidine) and chlorpheniramine. NRIs such as nortriptyline attenuate the hypertensive ‘cheese reaction’ (due to tyramine in cheese and some other foods) (^{Pare et al., 1982}; ^{Dostert et al., 1994}) that can be problematic occasionally in patients on MAOIs. This combination would be expected to provide partial or complete (depending on dose) protection against a tyramine-induced hypertensive episode.

The management of medical patients with migraine and pain syndromes can be complicated by concerns about drug interactions, particularly those with the potential to precipitate ST, and there has been discussion and comment concerning these interactions (^{Gillman, 2003}, ²⁰⁰⁴; ^{Lawrence et al., 2006}; ^{Sola et al., 2006}; ^{Taylor et al., 2006}). Patients with depression and pain syndromes may be on one or more types of antidepressant as well as other serotonergic drugs (e.g., tramadol). The new antibiotic, linezolid, is an MAOI, and will precipitate ST with SRIs; however, it does not lead to ST, or pharmacokinetic interactions with nortriptyline. The information herein (see also ^{Gillman, 2005b}, ^2006a) is important in predicting which combinations are safe and which multidrug regimes including nortriptyline (or other TCAs) may be added to with safety and confidence.

The increasing evidence that SNRIs like clomipramine may be more effective antidepressants makes it especially important to establish the criteria and evidence for valid claims of SNRI action. Recent evidence from ST studies indicates that amitriptyline does not have clinically significant serotonergic effects and is probably not an SNRI drug (^{Gillman, 1998}, ^2006a); so it is probably wrong to include it in meta-analyses of SNRI effects. A recent review of individual studies suggests superiority for clomipramine over non-TCAs in severe and psychotic depression (^{Wijkstra et al., 2006}). Clomipramine more closely conforms to the criteria for SNRI status than the more recently marketed SNRI drugs, duloxetine and venlafaxine (Table 4). The HCR data summarized herein form a congruent picture when considered along with TYR30 and ST data. These data do not support the assumption of clinically effective SNRI for venlafaxine or duloxetine, or other TCAs except clomipramine. The evidence that SNRI strategies are of superior efficacy in severe depression continues to increase (^{Nelson et al., 2004}, ²⁰⁰⁵) and is becoming accepted by experts in the field (^{Hirschfeld et al., 2002}). It may prove desirable to be able to adjust the SRI/NRI ratio separately by using two drugs: a desirability that becomes greater when the phenotypic and genotypic variation in response, which is known to exist between different individuals and illnesses, is taken into account. This factor would be expected to make single SNRI drugs of suitability for only a small proportion of any given population. The data reviewed herein indicate that it is possible to combine safely certain particular SSRIs and NRIs in a way that gives a flexible and potent dual SNRI effect. This requires extensive knowledge of possible risks and complications. Such strategies will probably be acceptably safe only if they remain the domain of psychopharmacology specialists, because none of them is sufficiently simple to be universally applicable without expert knowledge.

Desirable pharmacological characteristics for antidepressant drugs suitable for use in humans include a half-life suitable for once daily administration with linear pharmacokinetics in the therapeutic dose range and absence of active metabolites, a lack of propensity to interact with other drugs, an ability to monitor levels both clinically and by therapeutic drug monitoring and a safe margin between clinical potency and other undesirable effects, including toxicity. Nortriptyline and desipramine compare more favourably on the above criteria to the remaining TCAs; some SSRIs also compare less well. The tertiary TCAs have lower NRI potency, lower selectivity for the side-effect profile (Tables 1, 5 and 6) and greater toxicity. There is a need for direct comparisons between TCAs, as well as further dose ranging studies, because these do not exist to current standards.

Table 5. Comparative potency of other TCAs when used at the equivalent NRI dose of amitriptyline

Drug	NRI	Musc	α₁	H1	5-HT_2A
Doxepin	1:1.5	2:1	1.5:1	8:1	2:1
Nortriptyline^a	5:1	1:10^a	1:10	1:25	1:15
Dothiepin	1:1.5	1:2	1:10	1:2	1:7
Imipramine	1:3	1:2	1:1	1:35	1:2

Abbreviation: NRI, noradrenaline reuptake inhibitors.
The table illustrates the relative (approximated) potency for producing other (side) effects when the listed drugs are used at a dose that produces equivalent NRI potency to AMI (given to one decimal rounded to nearest half).
^a Nortriptyline is approximately five times the NRI potency of amitriptyline (mid-range values from Table 1) and one-half of the potency at muscarinic receptors. At an NRI equivalent dose to amitriptyline, it therefore has one-tenth of the anti-muscarinic effect and 1/15 of the sedative effect.

Conclusions

The disadvantages and risks of TCAs have been exaggerated in comparison to newer drugs, perhaps as the result of commercial influences, sponsorship bias and advertising. Nortriptyline has superior pharmacological properties to all other TCAs as a psychotropic; it is potent as an NRI and has a wide margin between desired effects, side effects and toxicity. It is safe to combine it with either MAOIs (including moclobemide) or selected SSRIs (sertraline and possibly citalopram). This is an advantage when treating refractory patients who may require combination antidepressant treatment: neither changes from one drug to another, nor additions to initiate combined treatments with either an MAOI or an SSRI, require drug washout times, as they do for most SSRIs. All SSRIs are strongly contra-indicated with all MAOIs.

Clomipramine is still the ‘gold standard’ SNRI drug and may be more effective than other antidepressants in severe depression. Its HCR affinities indicate that it is the most potent and effective single SNRI drug available. Amitriptyline has strong evidence for efficacy, but possibly not greater than that for nortriptyline, which may therefore be preferred in many situations (probably including use in migraine and pain syndromes) because of its advantageous pharmacological characteristics. A direct comparison of nortriptyline vs clomipramine, which has strong evidence for clinically relevant superiority via serotonergic effects, would be useful. Dothiepin (dosulepine) is more toxic than all other TCAs, without sufficient compensatory advantages. Doxepin is the most potent antihistamine sedative of any drug clinically available (almost equal in potency to mirtazapine) and has found a use in dermatology: an appropriate dose range is 5–25 mg day⁻¹.

The present evidence casts doubt on the proposal that the newer SNRI drugs exhibit satisfactory SNRI properties. Hence, to achieve the maximum efficacy from SNRI strategies, it may be necessary, and perhaps preferable, to combine two different drugs to achieve individual tailoring of the NRI/SRI ratio. For this purpose, nortriptyline has favourable characteristics, including minimal CYP450 interaction propensity and, because of this, it may be combined with sertraline without the need for therapeutic drug monitoring, except in special circumstances. All the other SSRIs are unsuitable for combination with TCAs (and many other drugs, particularly neuroleptics), with the possible exception of citalopram/escitalopram (^{Preskorn et al., 2006b}). Combinations enable flexibility of timing and dosage adjustment of each treatment component over the course of an illness. However, psychiatrists face a challenge in updating their pharmacological knowledge and this is not assisted by the difficulties that standard texts and databases are experiencing in keeping abreast of current research (such as the British National Formulary). Furthermore, pharmaceutical company product information summaries may not have clinically balanced and up to date drug interaction information (^{Gillman, 2005a}).

Suggestions for future research include consideration of specific funding for the screening of ‘out of patent’ drugs at CNS receptors, ion channels and CYP450 enzymes, and for PET studies. TCAs have now been in use for 50 years and this review highlights the continuing need for updating pharmacological data concerning key aspects of their properties as new methods and knowledge become available (e.g., lofepramine). The need for independently organized and funded trials of their clinical efficacy is clear (^{Sotelo, 2006}), especially their long-term ability to prevent suicide. This is an essential step forward for scientific knowledge concerning the effects of these drugs. It is unlikely that the 1000-fold difference in NRI and SRI affinity between different TCAs is not reflected in differences in their antidepressant effects; yet, 50 years on, high-quality, direct and long-term comparisons are still required to advance knowledge and to serve as a test of the monoamine hypothesis. An increased focus on collecting quality long-term data on the ability of these drugs to prevent suicide and cause toxicity in over-dose would be valuable.

Acknowledgments

I acknowledge the work and expertise of my wife Isobel, who maintained the computers and programs essential in achieving this review. This review uses data from the National Institute of Mental Health Psychoactive Drug Screening Program (PDSP): thanks are due to them for maintaining this publicly accessible resource at http://pdsp.med.unc.edu/pdsp.php.

Websites used

Websites (accessed September 2006)

Drug structures at Pubchem Compound (part of the ‘National Centre for Biotechnology information’) http://www.ncbi.nlm.nih.gov/entrez/query.fcgidb=pccompound

example amitriptyline: http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgicid=2160

Human Cytochrome P450 (CYP) Allele Nomenclature Committee: http://www.cypalleles.ki.se/

Psychoactive Drug Screening Program (PDSP): http://pdsp.med.unc.edu/pdsp.php

CYP450 interactions: http://medicine.iupui.edu/flockhart/clinlist.htm

Conflict of interest

The author states no conflict of interest.

References

Albers LJ, Reist C, Vu RL, Fujimoto K, Ozdemir V, Helmeste D et al. (2000). Effect of venlafaxine on imipramine metabolism. Psychiatry Res 96: 235–243.
10.1016/S0165-1781(00)00213-4
CASPubMedWeb of Science®Google Scholar
Amitai Y, Frischer H (2004). Excess fatality from desipramine and dosage recommendations. Ther Drug Monit 26: 468–473.
10.1097/00007691-200410000-00002
CASPubMedWeb of Science®Google Scholar
Amitai Y, Frischer H (2006). Excess fatality from desipramine in children and adolescents. J Am Acad Child Adolesc Psychiatry 45: 54–60.
10.1097/01.chi.0000184931.26176.4a
PubMedWeb of Science®Google Scholar
Amsterdam JD, Garcia-Espana F, Rosenzweig M (1997). Clomipramine augmentation in treatment-resistant depression. Depress Anxiety 5: 84–90.
10.1002/(SICI)1520-6394(1997)5:2<84::AID-DA4>3.0.CO;2-5
CASPubMedGoogle Scholar
Anderson IM (1998). SSRIS versus tricyclic antidepressants in depressed inpatients: a meta- analysis of efficacy and tolerability. Depress Anxiety 7 (Suppl 1): 11–17.
10.1002/(SICI)1520-6394(1998)7:1+<11::AID-DA4>3.0.CO;2-I
PubMedGoogle Scholar
Anderson IM (2001). Meta-analytical studies on new antidepressants. Br Med Bull 57: 161–178.
10.1093/bmb/57.1.161
CASPubMedWeb of Science®Google Scholar
Anon (2005). British National Formulary. Pharmaceutical Press: London, ISBN 9780853696698.
Google Scholar
Bassetti C (1999). Narcolepsy. Curr Treat Opt Neurol 1: 291–298.
10.1007/s11940-999-0019-3
PubMedGoogle Scholar
Baumann P, Hiemke C, Ulrich S, Gaertner I, Rao ML, Eckermann G et al. (2004). Therapeutic monitoring of psychotropic drugs: an outline of the AGNP-TDM expert group consensus guideline. Ther Drug Monit 26: 167–170.
10.1097/00007691-200404000-00014
CASPubMedWeb of Science®Google Scholar
Bekelman JE, Li Y, Gross CP (2003). Scope and impact of financial conflicts of interest in biomedical research: a systematic review. JAMA 289: 454–465.
10.1001/jama.289.4.454
PubMedWeb of Science®Google Scholar
Bertilsson L, Dahl ML, Dalen P, Al-Shurbaji A (2002). Molecular genetics of CYP2D6: clinical relevance with focus on psychotropic drugs. Br J Clin Pharmacol 53: 111–122.
10.1046/j.0306-5251.2001.01548.x
CASPubMedWeb of Science®Google Scholar
Bezchlibnyk-Butler KZ, Jeffries JJ (2005). Clinical Handbook of Psychotropic Drugs, 15 edn. Hogrefe and Huber: Toronto.
Google Scholar
Blier P, Saint-Andre E, Hebert C, de Montigny C, Lavoie N, Debonnel G (2007). Effects of different doses of venlafaxine on serotonin and norepinephrine reuptake in healthy volunteers. Int J Neuropharmacol 10: 41–50.
CASPubMedWeb of Science®Google Scholar
Bogni A, Monshouwer M, Moscone A, Hidestrand M, Ingelman-Sundberg M, Hartung T et al. (2005). Substrate specific metabolism by polymorphic cytochrome P450 2D6 alleles. Toxicol In Vitro 19: 621–629.
10.1016/j.tiv.2005.04.001
CASPubMedWeb of Science®Google Scholar
Bolden-Watson C, Richelson E (1993). Blockade by newly-developed antidepressants of biogenic amine uptake into rat brain synaptosomes. Life Sci 52: 1023–1029.
10.1016/0024-3205(93)90194-8
CASPubMedWeb of Science®Google Scholar
Bonnet U (2003). Moclobemide: therapeutic use and clinical studies. CNS Drug Rev 9: 97–140.
10.1111/j.1527-3458.2003.tb00245.x
CASPubMedWeb of Science®Google Scholar
Brosen K (2004). Some aspects of genetic polymorphism in the biotransformation of antidepressants. Therapie 59: 5–12.
10.2515/therapie:2004003
PubMedWeb of Science®Google Scholar
Brunton LL, Lazo JS, Parker KL (2006). Goodman and Gilman's The Pharmacologicl Basis of Therapeutics, 11th edn. McGraw-Hill: New York.
Google Scholar
Buckley N (2002). Fatal toxicity of serotoninergic and other antidepressant drugs: analysis of United Kingdom mortality data. BMJ 325: 1332–1333.
10.1136/bmj.325.7376.1332
PubMedWeb of Science®Google Scholar
Buckley NA, Mcmanus PR (1998). Can the fatal toxicity Of antidepressant drugs be predicted with pharmacological and toxicological data. Drug Saf 18: 369–381.
10.2165/00002018-199818050-00006
CASPubMedWeb of Science®Google Scholar
Carlsson A, Lindqvist M (1969). Central and peripheral monoaminergic membrane-pump blockade by some addictive analgesics and antihistamines. J Pharm Pharmacol 21: 460–464.
10.1111/j.2042-7158.1969.tb08287.x
CASPubMedWeb of Science®Google Scholar
Chalon SA, Granier LA, Vandenhende FR, Bieck PR, Bymaster FP, Joliat MJ et al. (2003). Duloxetine increases serotonin and norepinephrine availability in healthy subjects: a double-blind, controlled study. Neuropsychopharmacology 28: 1685–1693.
10.1038/sj.npp.1300209
CASPubMedWeb of Science®Google Scholar
Christensen M, Tybring G, Mihara K, Yasui-Furokori N, Carrillo JA, Ramos SI et al. (2002). Low daily 10-mg and 20-mg doses of fluvoxamine inhibit the metabolism of both caffeine (cytochrome P4501A2) and omeprazole (cytochrome P4502C19). Clin Pharmacol Ther 71: 141–152.
10.1067/mcp.2002.121788
CASPubMedWeb of Science®Google Scholar
Coppen A, Ghose K, Swade C, Wood K (1978). Effect of mianserin hydrochloride on peripheral uptake mechanisms for noradrenaline and 5-hydroxytryptamine in man. Br J Clin Pharmacol 5 (Suppl 1): 13S–17S.
10.1111/j.1365-2125.1978.tb04569.x
PubMedWeb of Science®Google Scholar
Cowen PJ (2005). New drugs, old problems: revisiting pharmacological management of treatment-resistant depression. Adv Psychiatr Treat 11: 11–27.
10.1192/apt.11.1.19
Google Scholar
Danie WA, Syrek M, Rylko Z, Wojcikowski J (2001). Effects of antidepressant drugs on the activity of cytochrome P-450 measured by caffeine oxidation in rat liver microsomes. Pol J Pharmacol 53: 351–357.
CASPubMedWeb of Science®Google Scholar
Dawson AH (2004). The tricyclic antidepressants. In: Dart RC (ed). Med Toxicol vol. 1, 3rd edn, pp 851–861. Lippincott Williams & Wilkins: Baltimore.
Web of Science®Google Scholar
de Leon J, Armstrong SC, Cozza KL (2006). Clinical guidelines for psychiatrists for the use of pharmacogenetic testing for CYP450 2D6 and CYP450 2C19. Psychosomatics 47: 75–85.
10.1176/appi.psy.47.1.75
PubMedWeb of Science®Google Scholar
DeBattista C, Sofuoglu M, Schatzberg AF (1998). Serotonergic synergism: the risks and benefits of combining the selective serotonin reuptake inhibitors with other serotonergic drugs. Biol Psychiatry 44: 341–347.
10.1016/S0006-3223(98)00161-9
CASPubMedWeb of Science®Google Scholar
Debonnel G, Saint-Andre E, Hebert C, de Montigny C, Lavoie N, Blier P (2007). Differential physiological effects of a low dose and high doses of venlafaxine in major depression. Int J Neuropharmacol 10: 51–61.
CASPubMedWeb of Science®Google Scholar
Doggrell SA, Woodruff GN (1977). Effects of antidepressant drugs on noradrenaline accumulation and contractile responses in the rat anococcygeus muscle. Br J Pharmacol 59: 403–409.
10.1111/j.1476-5381.1977.tb08393.x
CASPubMedWeb of Science®Google Scholar
Dostert P, Castelli MG, Cicioni P, Strolin Benedetti M (1994). Reboxetine prevents the tranylcypromine-induced increase in tyramine levels in rat heart. J Neural Transm 41: 149–153.
CASPubMedGoogle Scholar
Ellis P (2004). Australian and New Zealand clinical practice guidelines for the treatment of depression. Aust NZ J Psychiatry 38: 389–407.
10.1111/j.1440-1614.2004.01377.x
PubMedGoogle Scholar
Fineberg NA, Gale TM (2005). Evidence-based pharmacotherapy of obsessive-compulsive disorder. Int J Neuropharmacol 8: 107–129.
CASPubMedWeb of Science®Google Scholar
Furman KD, Grimm DR, Mueller T, Holley-Shanks RR, Bertz RJ, Williams LA et al. (2004). Impact of CYP2D6 intermediate metabolizer alleles on single-dose desipramine pharmacokinetics. Pharmacogenetics 14: 279–284.
10.1097/00008571-200405000-00002
CASPubMedWeb of Science®Google Scholar
Geister U, Gaupp M, Arnold P, Schaarschmidt D, Doser K, Renner J (2001). Bioavailability investigation of two different oral formulations of doxepin. Arzneimittelforschung 51: 189–196.
CASPubMedWeb of Science®Google Scholar
Ghose K, Coppen A, Turner P (1976). Autonomic actions and interactions of mianserin hydrochloride (Org. GB 94) and amitriptyline in patients with depressive illness. Psychopharmacology (Berl) 49: 201–204.
10.1007/BF00427291
CASPubMedWeb of Science®Google Scholar
Gillman PK (2003). Linezolid and serotonin toxicity. Clin Infect Dis 37: 1274–1275.
10.1086/378895
PubMedWeb of Science®Google Scholar
Gillman PK (2004). Comment on: serotonin syndrome due to co-administration of linezolid and venlafaxine. J Antimicrob Chemother 54: 844–845.
10.1093/jac/dkh404
CASPubMedWeb of Science®Google Scholar
Gillman PK (2005a). Drug interactions and fluoxetine: a commentary from a clinician's perspective. Expert Opin Drug Saf 4: 965–968.
10.1517/14740338.4.6.965
CASPubMedGoogle Scholar
Gillman PK (2005b). Monoamine oxidase inhibitors, opioid analgesics and serotonin toxicity. Br J Anaesth 95: 434–441.
10.1093/bja/aei210
CASPubMedWeb of Science®Google Scholar
Gillman PK (2006a). A review of serotonin toxicity data: implications for the mechanisms of antidepressant drug action. Biol Psychiatry 59: 1046–1051.
10.1016/j.biopsych.2005.11.016
CASPubMedWeb of Science®Google Scholar
Gillman PK (2006b). A systematic review of the serotonergic effects of mirtazapine: implications for its dual action status. Hum Psychopharmacol 21: 117–125.
10.1002/hup.750
CASPubMedWeb of Science®Google Scholar
Gillman PK (1998). Serotonin syndrome: history and risk. Fund Clin Pharmacol 12: 482–491.
10.1111/j.1472-8206.1998.tb00976.x
CASPubMedWeb of Science®Google Scholar
Gillman PK, Whyte IM (2004). Serotonin Syndrome. Oxford University Press: Oxford.
Google Scholar
Goodman NW (1999). Who will challenge evidence-based medicine J R Coll Physicians London 33: 249–251.
CASPubMedWeb of Science®Google Scholar
Gruetter CA, Lemke SM, Anestis DK, Szarek JL, Valentovic MA (1992). Potentiation of 5-hydroxytryptamine-induced contraction in rat aorta by chlorpheniramine, citalopram and fluoxetine. Eur J Pharmacol 217: 109–118.
10.1016/0014-2999(92)90827-Q
CASPubMedWeb of Science®Google Scholar
Gupta RK, Tiller JW, Burrows GD (2003). Dual action antidepressants and some important considerations. Aust NZ J Psychiatry 37: 190–195.
10.1046/j.1440-1614.2003.01169.x
PubMedWeb of Science®Google Scholar
Harvey AT, Rudolph RL, Preskorn SH (2000). Evidence of the dual mechanisms of action of venlafaxine. Arch Gen Psychiatry 57: 503–509.
10.1001/archpsyc.57.5.503
CASPubMedWeb of Science®Google Scholar
Hirschfeld RM, Montgomery SA, Aguglia E, Amore M, Delgado PL, Gastpar M et al. (2002). Partial response and nonresponse to antidepressant therapy: current approaches and treatment options. J Clin Psychiatry 63: 826–837.
10.4088/JCP.v63n0913
CASPubMedWeb of Science®Google Scholar
Ingelman-Sundberg M (2005). Genetic polymorphisms of cytochrome P450 2D6 (CYP2D6): clinical consequences, evolutionary aspects and functional diversity. Pharmacogenomics J 5: 6–13.
10.1038/sj.tpj.6500285
CASPubMedWeb of Science®Google Scholar
Jiang Z, Dragin N, Jorge-Nebert LF, Martin MV, Guengerich FP, Aklillu E et al. (2006). Search for an association between the human CYP1A2 genotype and CYP1A2 metabolic phenotype. Pharmacogenet Genomics 16: 359–367.
10.1097/01.fpc.0000204994.99429.46
CASPubMedWeb of Science®Google Scholar
Jiang ZP, Shu Y, Chen XP, Huang SL, Zhu RH, Wang W et al. (2002). The role of CYP2C19 in amitriptyline N-demethylation in Chinese subjects. Eur J Clin Pharmacol 58: 109–113.
10.1007/s00228-002-0445-6
CASPubMedWeb of Science®Google Scholar
Jo SH, Youm JB, Lee CO, Earm YE, Ho WK (2000). Blockade of the HERG human cardiac K(+) channel by the antidepressant drug amitriptyline. Br J Pharmacol 129: 1474–1480.
10.1038/sj.bjp.0703222
CASPubMedWeb of Science®Google Scholar
Johansson I, Lundqvist E, Bertilsson L, Dahl ML, Sjoqvist F, Ingelman-Sundberg M (1993). Inherited amplification of an active gene in the cytochrome P450 CYP2D locus as a cause of ultrarapid metabolism of debrisoquine. Proc Natl Acad Sci USA 90: 11825–11829.
10.1073/pnas.90.24.11825
CASPubMedWeb of Science®Google Scholar
Keller T, Schneider A, Tutsch-Bauer E (2000). Fatal intoxication due to dothiepin. Forensic Sci Int 109: 159–166.
10.1016/S0379-0738(99)00234-0
CASPubMedWeb of Science®Google Scholar
Khalifa M, Daleau P, Turgeon J (1999). Mechanism of sodium channel block by venlafaxine in guinea pig ventricular myocytes. J Pharmacol Exp Ther 291: 280–284.
CASPubMedWeb of Science®Google Scholar
Kongsamut S, Kang J, Chen XL, Roehr J, Rampe D (2002). A comparison of the receptor binding and HERG channel affinities for a series of antipsychotic drugs. Eur J Pharmacol 450: 37–41.
10.1016/S0014-2999(02)02074-5
CASPubMedWeb of Science®Google Scholar
Kroeze WK, Hufeisen SJ, Popadak BA, Renock SM, Steinberg S, Ernsberger P et al. (2003). H1-histamine receptor affinity predicts short-term weight gain for typical and atypical antipsychotic drugs. Neuropsychopharmacology 28: 519–526.
10.1038/sj.npp.1300027
CASPubMedWeb of Science®Google Scholar
Lamba JK, Lin YS, Thummel K, Daly A, Watkins PB, Strom S et al. (2002). Common allelic variants of cytochrome P4503A4 and their prevalence in different populations. Pharmacogenetics 12: 121–132.
10.1097/00008571-200203000-00006
CASPubMedWeb of Science®Google Scholar
Lawrence KR, Adra M, Gillman PK (2006). Serotonin toxicity associated with the use of linezolid: a review of postmarketing data. Clin Infect Dis 42: 1578–1583.
10.1086/503839
CASPubMedWeb of Science®Google Scholar
Leucht S, Hackl HJ, Steimer W, Angersbach D, Zimmer R (2000). Effect of adjunctive paroxetine on serum levels and side-effects of tricyclic antidepressants in depressive inpatients. Psychopharmacology (Berl) 147: 378–383.
10.1007/s002130050006
CASPubMedWeb of Science®Google Scholar
Lopez-Munoz F, Alamo C, Rubio G, Cuenca E (2004). Half a century since the clinical introduction of chlorpromazine and the birth of modern psychopharmacology. Prog Neuropsychopharmacol Biol Psychiatry 28: 205–208.
10.1016/S0278-5846(03)00165-9
CASPubMedWeb of Science®Google Scholar
Mann K, Hiemke C, Schmidt LG, Bates DW (2006). Appropriateness of therapeutic drug monitoring for antidepressants in routine psychiatric inpatient care. Ther Drug Monit 28: 83–88.
10.1097/01.ftd.0000189897.16307.65
PubMedWeb of Science®Google Scholar
Mason J, Freemantle N, Eccles M (2000). Fatal toxicity associated with antidepressant use in primary care. Br J Gen Pract 50: 366–370.
CASPubMedWeb of Science®Google Scholar
McManus P, Mant A, Mitchell P, Birkett D, Dudley J (2001). Co-prescribing of SSRIs and TCAs in Australia: how often does it occur and who is doing it Br J Clin Pharmacol 51: 93–98.
10.1046/j.1365-2125.2001.01319.x
CASPubMedWeb of Science®Google Scholar
Melander H, Ahlqvist-Rastad J, Meijer G, Beermann B (2003). Evidence b(i)ased medicine – selective reporting from studies sponsored by pharmaceutical industry: review of studies in new drug applications. BMJ 326: 1171–1173.
10.1136/bmj.326.7400.1171
PubMedWeb of Science®Google Scholar
Meyer JH, Wilson AA, Sagrati S, Hussey D, Carella A, Potter WZ et al. (2004). Serotonin transporter occupancy of five selective serotonin reuptake inhibitors at different doses: an [¹¹C]DASB positron emission tomography study. Am J Psychiatry 161: 826–835.
10.1176/appi.ajp.161.5.826
PubMedWeb of Science®Google Scholar
Millan MJ, Gobert A, Rivet JM, Adhumeau-Auclair A, Cussac D, Newman-Tancredi A et al. (2000). Mirtazapine enhances frontocortical dopaminergic and corticolimbic adrenergic, but not serotonergic, transmission by blockade of alpha2-adrenergic and serotonin2C receptors: a comparison with citalopram. Eur J Neurosci 12: 1079–1095.
10.1046/j.1460-9568.2000.00982.x
CASPubMedWeb of Science®Google Scholar
Mizutani T (2003). PM frequencies of major CYPs in Asians and Caucasians. Drug Metab Rev 35: 99–106.
10.1081/DMR-120023681
CASPubMedWeb of Science®Google Scholar
Nelson JC, Mazure CM, Jatlow PI, Bowers Jr MB, Price LH (2004). Combining norepinephrine and serotonin reuptake inhibition mechanisms for treatment of depression: a double-blind, randomized study. Biol Psychiatry 55: 296–300.
10.1016/j.biopsych.2003.08.007
CASPubMedWeb of Science®Google Scholar
Nelson JC, Portera L, Leon AC (2005). Are there differences in the symptoms that respond to a selective serotonin or norepinephrine reuptake inhibitor Biol Psychiatry 57: 1535–1542.
10.1016/j.biopsych.2005.03.030
CASPubMedWeb of Science®Google Scholar
Nicholson GM, Blanche T, Mansfield K, Tran Y (2002). Differential blockade of neuronal voltage-gated Na(+) and K(+) channels by antidepressant drugs. Eur J Pharmacol 452: 35–48.
10.1016/S0014-2999(02)02239-2
CASPubMedWeb of Science®Google Scholar
Nielsen KK, Flinois JP, Beaune P, Brosen K (1996). The biotransformation of clomipramine in vitro, identification of the cytochrome P450s responsible for the separate metabolic pathways. J Pharmacol Exp Ther 277: 1659–1664.
CASPubMedWeb of Science®Google Scholar
Oates JA, Sjoerdsma A (1960). Neurologic effects of tryptophan in patients receiving a monoamine oxidase inhibitor. Neurology 10: 1076–1078.
10.1212/WNL.10.12.1076
CASPubMedWeb of Science®Google Scholar
Pare CM, Kline N, Hallstrom C, Cooper TB (1982). Will amitriptyline prevent the ‘cheese’ reaction of monoamine-oxidase inhibitors Lancet 2: 183–186.
10.1016/S0140-6736(82)91030-3
CASPubMedWeb of Science®Google Scholar
Parker G, Roy K, Wilhelm K, Mitchell P (2001). Assessing the comparative effectiveness of antidepressant therapies: a prospective clinical practice study. J Clin Psychiatry 62: 117–125.
10.4088/JCP.v62n0209
CASPubMedWeb of Science®Google Scholar
Patten SB, Beck C (2004). Major depression and mental health care utilization in Canada: 1994 to 2000. Can J Psychiatry 49: 303–309.
10.1177/070674370404900505
PubMedWeb of Science®Google Scholar
Preskorn S, Flockhart D (2006a). 2006 guide to psychiatric drug interactions. Primary Psychiatry 13: 35–64.
Google Scholar
Preskorn SH (1986). Tricyclic antidepressant plasma level monitoring: an improvement over the dose-response approach. J Clin Psychiatry 47 (Suppl 1): 24–30.
CASPubMedWeb of Science®Google Scholar
Preskorn SH (2003). Reproducibility of the in vivo effect of the selective serotonin reuptake inhibitors on the in vivo function of cytochrome P450 2D6: an update (part I). J Psychiatr Pract 9: 150–158.
10.1097/00131746-200303000-00006
PubMedGoogle Scholar
Preskorn SH, Baker B, Klick-Davis A, Ramadan M, Coyner L, Flockhart DA et al. (2006b). The effect of duloxetine, escitalopram, and sertraline on CYP 2D6 function. Clin Pharmacol Ther 79: 52.
10.1016/j.clpt.2005.12.188
Web of Science®Google Scholar
Richelson E (1984). Antagonism by antidepressants of neurotransmitter receptors of normal human brain in vitro. J Pharmacol Exp Ther 23: 94–102.
Google Scholar
Richelson E (1991). Biological basis of depression and therapeutic relevance. J Clin Psychiatry 52: 4–10.
PubMedWeb of Science®Google Scholar
Richelson E (2001). Pharmacology of antidepressants. Mayo Clin Proc 76: 511–527.
10.4065/76.5.511
CASPubMedWeb of Science®Google Scholar
Richelson E (2003). Interactions of antidepressants with neurotransmitter transporters and receptors and their clinical relevance. J Clin Psychiatry 64 (Suppl 13): 5–12.
CASPubMedWeb of Science®Google Scholar
Rossi S (Ed.) (2007). Australian Medicines Handbook 2007. Adelaide ISBN 0-9757919-5-8.
Google Scholar
Rudorfer MV, Potter WZ (1999). Metabolism of tricyclic antidepressants. Cell Mol Neurobiol 19: 373–409.
10.1023/A:1006949816036
CASPubMedWeb of Science®Google Scholar
Sala M, Coppa F, Cappucciati C, Brambilla P, D'allio G, Caverzasi E et al. (2006). Antidepressants: their effects on cardiac channels, QT prolongation and Torsade de Pointes. Curr Opin Investig Drugs 7: 256–263.
CASPubMedWeb of Science®Google Scholar
Sanchez C, Hyttel J (1999). Comparison of the effects of antidepressants and their metabolites on reuptake of biogenic amines and on receptor binding. Cell Mol Neurobiol 19: 467–489.
10.1023/A:1006986824213
CASPubMedWeb of Science®Google Scholar
Schulz M, Schmoldt A (1994). Successful physostigmine treatment of acute dothiepin intoxication. Pharmazie 49: 614.
CASPubMedWeb of Science®Google Scholar
Schulz M, Schmoldt A (2003). Therapeutic and toxic blood concentrations of more than 800 drugs and other xenobiotics. Pharmazie 58: 447–474.
CASPubMedWeb of Science®Google Scholar
Seppala T, Linnoila M, Soundergaard I, Elonen E, Mattila MJ (1981). Tyramine pressor test and cardiovascular effects of chlorimipramine and nortriptyline in healthy volunteers. Biol Psychiatry 16: 71–77.
CASPubMedWeb of Science®Google Scholar
Shah RR (2005). Drug-induced QT interval prolongation – regulatory guidance and perspectives on hERG channel studies. Novartis Found Symp 266: 251–280.
10.1002/047002142X.ch19
CASPubMedGoogle Scholar
Sharpley AL, Vassallo CM, Cowen PJ (2000). Olanzapine increases slow-wave sleep: evidence for blockade of central 5-HT(2C) receptors in vivo. Biol Psychiatry 47: 468–470.
10.1016/S0006-3223(99)00273-5
CASPubMedWeb of Science®Google Scholar
Shen WW (1999). A history of antipsychotic drug development. Compr Psychiatry 40: 407–414.
10.1016/S0010-440X(99)90082-2
CASPubMedWeb of Science®Google Scholar
Shimoda K, Jerling M, Bottiger Y, Yasuda S, Morita S, Bertilsson L (1999). Pronounced differences in the dispositon of clomipramine between Japanese and Swedish patients. J Clin Psychopharmacol 19: 393–400.
10.1097/00004714-199910000-00002
CASPubMedWeb of Science®Google Scholar
Shin JG, Park JY, Kim MJ, Shon JH, Yoon YR, Cha IJ et al. (2002). Inhibitory effects of tricyclic antidepressants (TCAs) on human cytochrome P450 enzymes in vitro: mechanism of drug interaction between TCAs and phenytoin. Drug Metab Dispos 30: 1102–1107.
10.1124/dmd.30.10.1102
CASPubMedWeb of Science®Google Scholar
Sim SC, Ingelman-Sundberg M (2006a). The human cytochrome P450 Allele Nomenclature Committee Web site: submission criteria, procedures, and objectives. Methods Mol Biol 320: 183–191.
CASPubMedGoogle Scholar
Sim SC, Risinger C, Dahl ML, Aklillu E, Christensen M, Bertilsson L et al. (2006b). A common novel CYP2C19 gene variant causes ultrarapid drug metabolism relevant for the drug response to proton pump inhibitors and antidepressants. Clin Pharmacol Ther 79: 103–113.
10.1016/j.clpt.2005.10.002
CASPubMedWeb of Science®Google Scholar
Skinner MH, Kuan HY, Pan A, Sathirakul K, Knadler MP, Gonzales CR et al. (2003). Duloxetine is both an inhibitor and a substrate of cytochrome P4502D6 in healthy volunteers. Clin Pharmacol Ther 73: 170–177.
10.1067/mcp.2003.28
CASPubMedWeb of Science®Google Scholar
Smith D, Dempster C, Glanville J, Freemantle N, Anderson I (2002). Efficacy and tolerability of venlafaxine compared with selective serotonin reuptake inhibitors and other antidepressants: a meta-analysis. Br J Psychiatry 180: 396–404.
10.1192/bjp.180.5.396
PubMedWeb of Science®Google Scholar
Smith RL (2001). The Paton Prize Award. The discovery of the debrisoquine hydroxylation polymorphism: scientific and clinical impact and consequences. Toxicology 168: 11–19.
CASPubMedWeb of Science®Google Scholar
Sola CL, Bostwick JM, Hart DA, Lineberry TW (2006). Anticipating potential linezolid-SSRI interactions in the general hospital setting: an MAOI in disguise. Mayo Clin Proc 81: 330–334.
10.4065/81.3.330
CASPubMedWeb of Science®Google Scholar
Solus JF, Arietta BJ, Harris JR, Sexton DP, Steward JQ, McMunn C et al. (2004). Genetic variation in eleven phase I drug metabolism genes in an ethnically diverse population. Pharmacogenomics 5: 895–931.
10.1517/14622416.5.7.895
CASPubMedWeb of Science®Google Scholar
Sotelo J (2006). Regulation of clinical research sponsored by pharmaceutical companies: a proposal. PLoS Med 3: e306 http://www.ncbi.nlm.nih.gov/entrez/query.fcgicmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16805651.
10.1371/journal.pmed.0030306
PubMedWeb of Science®Google Scholar
Stein DJ, Spadaccini E, Hollander E (1995). Meta-analysis of pharmacotherapy trials for obsessive-compulsive disorder. Int Clin Psychopharmacol 10: 11–18.
10.1097/00004850-199503000-00002
CASPubMedWeb of Science®Google Scholar
Szegedi A, Wetzel H, Leal M, Hartter S, Hiemke C (1996). Combination treatment with clomipramine and fluvoxamine: drug monitoring, safety, and tolerability data. J Clin Psychiatry 57: 257–264.
CASPubMedWeb of Science®Google Scholar
Szewczuk-Boguslawska M, Kiejna A, Beszlej JA, Orzechowska-Juzwenko K, Milejski P (2004). Doxepin inhibits CYP2D6 activity in vivo. Pol J Pharmacol 56: 491–494.
CASPubMedWeb of Science®Google Scholar
Taylor JJ, Wilson JW, Estes LL (2006). Linezolid and serotonergic drug interactions: a retrospective survey. Clin Infect Dis 43: 180–187.
10.1086/504809
CASPubMedWeb of Science®Google Scholar
Teschemacher AG, Seward EP, Hancox JC, Witchel HJ (1999). Inhibition of the current of heterologously expressed HERG potassium channels by imipramine and amitriptyline. Br J Pharmacol 128: 479–485.
10.1038/sj.bjp.0702800
CASPubMedWeb of Science®Google Scholar
Thanacoody HK, Thomas SH (2005). Tricyclic antidepressant poisoning: cardiovascular toxicity. Toxicol Rev 24: 205–214.
10.2165/00139709-200524030-00013
CASPubMedGoogle Scholar
Thase ME (2006). Depression and sleep: pathophysiology and treatment. Dialogues Clin Neurosi 8: 217–226.
PubMedGoogle Scholar
Turcotte JE, Debonnel G, de Montigny C, Hebert C, Blier P (2001). Assessment of the serotonin and norepinephrine reuptake blocking properties of duloxetine in healthy subjects. Neuropsychopharmacology 24: 511–521.
10.1016/S0893-133X(00)00220-7
CASPubMedWeb of Science®Google Scholar
Ullmann U, Lehnfeld R, Bliesath H, Birkel M, Gebbing H, Grave M et al. (2001). Relative bioavailability of imipramine (Tofranil) coated tablets in healthy volunteers. Int J Clin Pharmacol Ther 39: 271–276.
CASPubMedWeb of Science®Google Scholar
Vaishnavi SN, Nemeroff CB, Plott SJ, Rao SG, Kranzler J, Owens MJ (2004). Milnacipran: a comparative analysis of human monoamine uptake and transporter binding affinity. Biol Psychiatry 55: 320–322.
10.1016/j.biopsych.2003.07.006
CASPubMedWeb of Science®Google Scholar
Vandel S, Bertschy G, Baumann P, Bouquet S, Bonin B, Francois T et al. (1995). Fluvoxamine and fluoxetine: interaction studies with amitriptyline, clomipramine and neuroleptics in phenotyped patients. Pharmacol Res 31: 347–353.
10.1016/1043-6618(95)80088-3
CASPubMedWeb of Science®Google Scholar
Vignatelli L, D'Alessandro R, Candelise L (2005). Antidepressant drugs for narcolepsy. Cochrane Database Syst Rev 3: CD003724.
PubMedWeb of Science®Google Scholar
Vincent S, Bieck PR, Garland EM, Loghin C, Bymaster FP, Black BK et al. (2004). Clinical assessment of norepinephrine transporter blockade through biochemical and pharmacological profiles. Circulation 109: 3202–3207.
10.1161/01.CIR.0000130847.18666.39
CASPubMedWeb of Science®Google Scholar
von Moltke LL, Greenblatt DJ, Court MH, Duan SX, Harmatz JS, Shader RI (1995). Inhibition of alprazolam and desipramine hydroxylation in vitro by paroxetine and fluvoxamine: comparison with other selective serotonin reuptake inhibitor antidepressants. J Clin Psychopharmacol 15: 125–131.
10.1097/00004714-199504000-00008
PubMedWeb of Science®Google Scholar
Westlind-Johnsson A, Hermann R, Huennemeyer A, Hauns B, Lahu G, Nassr N et al. (2006). Identification and characterization of CYP3A4*20, a novel rare CYP3A4 allele without functional activity. Clin Pharmacol Ther 79: 339–349.
10.1016/j.clpt.2005.11.015
CASPubMedWeb of Science®Google Scholar
Whyte IM (2004). Serotonin uptake inhibitors. In: Dart RC (ed). Med Toxicol, vol. 1, 3rd edn, pp 843–851. Lippincott Williams & Wilkins: Baltimore.
Google Scholar
Whyte IM, Dawson AH, Buckley NA (2003). Relative toxicity of venlafaxine and selective serotonin reuptake inhibitors in overdose compared to tricyclic antidepressants. Q J Med 96: 369–374.
10.1093/qjmed/hcg062
CASPubMedWeb of Science®Google Scholar
Wijkstra J, Lijmer J, Balk FJ, Geddes JR, Nolen WA (2006). Pharmacological treatment for unipolar psychotic depression: systematic review and meta-analysis. Br J Psychiatry 188: 410–415.
10.1192/bjp.bp.105.010470
PubMedWeb of Science®Google Scholar
Witchel HJ, Hancox JC, Nutt DJ (2003). Psychotropic drugs, cardiac arrhythmia, and sudden death. J Clin Psychopharmacol 23: 58–77.
10.1097/00004714-200302000-00010
CASPubMedWeb of Science®Google Scholar
Yue QY, Zhong ZH, Tybring G, Dalen P, Dahl ML, Bertilsson L et al. (1998). Pharmacokinetics of nortriptyline and its 10-hydroxy metabolite in Chinese subjects of different CYP2D6 genotypes. Clin Pharmacol Ther 64: 384–390.
10.1016/S0009-9236(98)90069-8
CASPubMedWeb of Science®Google Scholar

Citing Literature

Volume151, Issue6

July 2007

Pages 737-748

Tricyclic antidepressant pharmacology and therapeutic drug interactions updated

Abstract

Abbreviations:

Introduction

General pharmacology

Pharmacokinetics

Relative toxicities

Cytochrome P450 enzyme interactions

Receptor pharmacology

The relationship of receptor affinity and therapeutic effect: serotonin reuptake inhibition and serotonin toxicity

The relationship of receptor affinity and therapeutic effect: noradrenaline reuptake inhibition and the pressor response to tyramine

Discussion

Conclusions

Acknowledgments

Websites used

References

Citing Literature

References

Information

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Tricyclic antidepressant pharmacology and therapeutic drug interactions updated

Abstract

Abbreviations:

Introduction

General pharmacology

Pharmacokinetics

Relative toxicities

Cytochrome P450 enzyme interactions

Receptor pharmacology

The relationship of receptor affinity and therapeutic effect: serotonin reuptake inhibition and serotonin toxicity

The relationship of receptor affinity and therapeutic effect: noradrenaline reuptake inhibition and the pressor response to tyramine

Discussion

Conclusions

Acknowledgments

Websites used

References

Citing Literature

References

Related

Information