The percentage of patients who have failed to completely or partially respond to multiple trials of antidepressants at adequate doses and for an adequate duration of therapy has varied in the literature and is considered substantial. Numerous strategies exist to treat poor antidepressant response, but often medications are selected on a “trial and error” basis. Genetic factors may play a role in poor response or intolerance to treatment with antidepressants which lead to treatment failures. Currently, available genetic testing as well as genetic testing currently under research may help guide clinicians with proper medication and dose selection.

INTRODUCTION

Treatment failure with antidepressants commonly occurs in clinical practice. The definition of treatment resistant depression (TRD) varies widely but is most commonly defined as poor response to two trials of antidepressants of adequate dose and duration in patients diagnosed with major depressive disorder (MDD).1 It is estimated that between 29% and 46% of depressed patients fail to achieve remission when treated with an antidepressant of adequate dose and duration.2 Partial response, generally defined as <50% but ≥25% decrease from baseline depression scale scores or “minimally improved” on the Clinical Global Impressions (CGI) scale, has been estimated to occur in 12% to 15% of depressed patients with nonresponse estimated at 19% to 34%.2,3 Results from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, which prospectively administered up to four sequential trials of pharmacotherapy to 3671 patients with MDD, found that 63% of patients did not achieve symptom remission after 14 weeks on an adequate dose of citalopram, and among the 1439 patients who switched to another antidepressant in the next-step of the study, 69% did not achieve symptom remission.4,5 This leaves a substantial portion of patients still symptomatic and requiring further treatment.

Numerous treatment strategies exist for TRD and include switching of antidepressants, augmentation with the addition of another psychotropic to current treatment, and brain stimulation techniques such as electroconvulsive therapy (ECT), deep brain stimulation (DBS), and transcranial magnetic stimulation (TMS).69  If one were to follow standard guidelines, allowing each medication trial for two months before treatment resistance is declared, and one were to try at least three selective serotonin reuptake inhibitors (SSRIs) and three non-SSRIs before moving to augmentation strategies, the patient would spend one year in monotherapy medication trials alone. If each of the antidepressant trials were augmented with two different agents, an additional two years would be spent in augmentation trials. Indeed, Judd and colleagues found that 71% of patients with MDD remained symptomatic one year after diagnosis. It has also been estimated that fewer than half of patients with MDD are fully symptom free two years after the index episode.1011 

With this lengthy trial-and-error approach to treatment, there is a need to predict which patient will respond best to a particular medication. Treatment resistance in MDD has been associated with comorbid medical conditions such as hypothyroidism or coronary heart disease, chronic pain, comorbid psychiatric disorders including subsyndromal hypomanic symptoms, low socioeconomic status, early age of onset and severity of symptoms, and certain features of depression such as melancholic features, presence of dysthymia, or frequent recurrence of episodes.1214  Even with appropriate treatment of risk factors, patients still suffer from TRD.

Genetic factors may affect response to antidepressants by influencing drug distribution, metabolism, serum levels and targets of action. Genetic factors may also predict who is more susceptible to MDD. Pharmacogenomic testing is clinically available to assist with medication selection in TRD and may soon help with diagnosis.

HERITABILITY

Monozygotic twins, also known as identical twins, share the same DNA code since they are formed from the exact same sperm and egg. Dizygotic, or fraternal twins, are formed from two different sperm and egg pairs and share only 50% of their genetic code. In an effort to estimate the contribution of genes to MDD, McGuffin and colleagues evaluated monozygotic and dizygotic twins in which one member of the twin pair had MDD.15 The concordance rate was then determined as the portion of co-twins that also had MDD. They reported a concordance rate of 46% in monozygotic twins vs. 20% in dizygotic twins. Estimates of heritability, or the portion of cause due to inheritance, were between 48% and 75%. Prominent findings in susceptibility studies of MDD include several polymorphisms in the serotonin system, particularly with the serotonin transporter, and enzymes involved in serotonin synthesis, as well as the polymorphisms in the hypothalamic-pituitary-adrenocortical (HPA) axis.15 

PERSONALIZED MEDICINE

Until pharmacogenomics, medicines have been developed based on the high likelihood that each drug will work equally well in the entire population. Dose adjustments have been based on variations in certain physical parameters such as height and weight, but most drug manufacturers have applied a “one size fits all” approach. However, some patients experience significantly more or fewer side effects or a range in efficacy spanning from no benefit to significant improvement in symptoms when compared to others given the same medication, even when physical parameters are taken into consideration.

Personalized, or as it has been more recently named, precision medicine, allows for use of an optimal dose of the most appropriate medication based on the patient's individual genomic makeup. There are various ways in which pharmacogenomics is used to guide precision medicine. One of the most common ways pharmacogenomics is guiding treatment is through evaluation of drug metabolizing enzymes.

Cytochrome P450 (CYP) enzymes are involved with the metabolism of most medications, including antidepressants. Individuals can have changes in their genes that code for these enzymes, causing changes in the way they metabolize medications. Many of the medications used to treat the symptoms of depression are metabolized via CYP2D6, CYP2C19 and CYP1A2. There are a number of pharmacogenetic tests currently available on the market that will measure variants which may affect a patient's ability to tolerate or respond to medications metabolized by these pathways. Typically, a patient will have a genetic findings report generated after their genetic test that states whether the patient metabolizes a particular medication faster or slower. For example, with regard to the CYP 2D6 enzyme, individuals can be considered poor metabolizers (PM) with little to no enzyme activity, intermediate metabolizers (IM) with less than normal activity, extensive metabolizers (EM) with normal metabolism, or ultra-rapid metabolizers (UM) with greatly increased metabolizing capacity based on results of pharmacogenetic testing. If the patient is on venlafaxine, a medication highly metabolized by CYP2D6, variability in metabolizing capacity can cause tremendous variability in drug exposure, leading to intolerable or severe side effects from subtherapeutic doses in a patient who is a PM. Conversely, this variability could cause such rapid metabolism that therapeutic doses appear to be ineffective in a patient who is a UM. Table 1 shows common CYP substrates that would be affected by changes in metabolism.

Table 1:

Common CYP substrates

Common CYP substrates
Common CYP substrates

Another way in which genes may influence drug response is by varying the biological response of the drug at the target. For example, the genes for several serotonin receptors, such as 1A (5-HTR1A) or 2C (5-HTR2C) receptors, have been implicated in modulating the therapeutic response to SSRIs.16 It is thought that variation in the protein sequence of the receptor could affect its response to a drug. The genetic findings report would suggest medications that are thought to act through these pathways, such as SSRIs, would not be as effective as a medication with a different mechanism of action, such as bupropion, a noradrenergic-dopaminergic reuptake inhibitor.

Lastly, it is likely that there are many different biological mechanisms that can result in depression. These might result from different combinations of susceptibility genes that a patient inherited, that in turn disturb different pathways in the brain. These pathways may respond to different drugs with different mechanisms of action. In other words, a medication may work in one patient and not another because the cause and mechanism of their depressions are different.

LIMITATIONS

Although clinical laboratory tests exist for CYP enzymes 2C19, 2C9, and 1A2, not every lab evaluates the same single nucleotide polymorphism (SNPs) that may cause the change in gene function; however, this is anticipated to be less of a problem as more SNPs continue to be identified. CYP3A4 is also involved in the metabolism of a number of medications used in psychiatry. More than 30 SNPs have been identified in this gene, but none have been found to be of functional significance. As a result, there is currently not a genetic test available that would identify if a patient were a PM, IM, UM or EM with regard to this enzyme.17 

CONCLUSION

TRD is a significant health concern and has been associated with higher rates of relapse, poorer quality of life, and increased mortality rates.18 Unfortunately, many patients undergo a trial and error approach for medication selection until one is tolerated and effective, which can take years and adds to the overall burden of illness. Fortunately, pharmacogenomic testing is beginning to guide medication choices, allowing clinicians to choose a more effective drug at a more appropriate dose, thereby potentially decreasing the trial and error approach of medication selection. Although limitations to the application of pharmacogenomic information to pharmacotherapeutic choices for patients currently exist, additional research in this area is likely to have a significant impact in the care of patients with TRD.

The results from genetic testing can help clinicians understand the way a patient's unique genetic makeup may affect certain medications used in psychiatry. The analysis of the clinically important genetic variants is based on pharmacogenetics, the study of genetic factors that influence an individual's response to drug treatments, the FDA's approved manufacturer drug labeling, and published studies on the pharmacologic profiles of various medications. Armed with this information, doses may be adjusted or different medications may be chosen based on published guidelines and clinical research.1921 

REFERENCES

REFERENCES
1.
Souery
D
,
Amsterdam
J
,
de Montigny
C
,
Lecrubier
Y
,
Montgomery
S
,
Lipp
O
et al
.
Treatment resistant depression: methodological overview and operational criteria
Eur Neuropsychopharmacol
.
1999
;
9
(
1–2
):
83
91
. .
2.
Fava
M
,
Davidson
KG.
Definition and epidemiology of treatment-resistant depression
.
Psychiatr Clin North Am
.
1996
;
19
(
2
):
179
200
.
PubMed PMID: 8827185
.
3.
Nierenberg
AA
,
DeCecco
LM.
Definitions of antidepressant treatment response, remission, nonresponse, partial response, and other relevant outcomes: a focus on treatment-resistant depression
.
J Clin Psychiatry
.
2001
;
62
Suppl 16
:
5
9
.
PubMed PMID: 11480882
.
4.
Rush
AJ
,
Trivedi
MH
,
Wisniewski
SR
,
Nierenberg
AA
,
Stewart
JW
,
Warden
D
et al
.
Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report
.
Am J Psychiatry
.
2006
;
163
(
11
):
1905
17
. .
5.
Trivedi
MH
,
Rush
AJ
,
Wisniewski
SR
,
Nierenberg
AA
,
Warden
D
,
Ritz
L
et al
.
Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice
.
Am J Psychiatry
.
2006
;
163
(
1
):
28
40
. .
6.
Malhi
GS
,
Hitching
R
,
Berk
M
,
Boyce
P
,
Porter
R
,
Fritz
K.
Pharmacological management of unipolar depression
.
Acta Psychiatr Scand
.
2013
;(
443
):
6
23
.
DOI: 10.1111/acps.12122. PubMed PMID: 23586873
.
7.
Carvalho
AF
,
Machado
JR
,
Cavalcante
JL.
Augmentation strategies for treatment-resistant depression
.
Curr Opin Psychiatry
.
2009
;
22
(
1
):
7
12
. .
8.
Trivedi
MH
,
Fava
M
,
Wisniewski
SR
,
Thase
ME
,
Quitkin
F
,
Warden
D
et al
.
Medication augmentation after the failure of SSRIs for depression
.
N Engl J Med
.
2006
;
354
(
12
):
1243
52
.
DOI: 10.1056/NEJMoa052964. PubMed PMID: 16554526
.
9.
Crismon
ML
,
Trivedi
M
,
Pigott
TA
,
Rush
AJ
,
Hirschfeld
RM
,
Kahn
DA
et al
.
The Texas Medication Algorithm Project: report of the Texas Consensus Conference Panel on Medication Treatment of Major Depressive Disorder
.
J Clin Psychiatry
.
1999
;
60
(
3
):
142
56
.
PubMed PMID: 10192589
.
10.
Judd
LL
,
Akiskal
HS
,
Maser
JD
,
Zeller
PJ
,
Endicott
J
,
Coryell
W
et al
.
Major depressive disorder: a prospective study of residual subthreshold depressive symptoms as predictor of rapid relapse
.
J Affect Disord
.
1998
;
50
(
2–3
):
97
108
.
PubMed PMID: 9858069
.
11.
Kanai
T
,
Takeuchi
H
,
Furukawa
TA
,
Yoshimura
R
,
Imaizumi
T
,
Kitamura
T
et al
.
Time to recurrence after recovery from major depressive episodes and its predictors
.
Psychol Med
.
2003
;
33
(
5
):
839
45
.
PubMed PMID: 12877398
.
12.
Keitner
GI
,
Ryan
CE
,
Miller
IW
,
Kohn
R
,
Epstein
NB.
12-month outcome of patients with major depression and comorbid psychiatric or medical illness (compound depression)
.
Am J Psychiatry
.
1991
;
148
(
3
):
345
50
.
PubMed PMID: 1992837
.
13.
Souery
D
,
Oswald
P
,
Massat
I
,
Bailer
U
,
Bollen
J
,
Demyttenaere
K
et al
.
Clinical factors associated with treatment resistance in major depressive disorder: results from a European multicenter study
.
J Clin Psychiatry
.
2007
;
68
(
7
):
1062
70
.
PubMed PMID: 17685743
.
14.
Gaynes
BN.
Identifying difficult-to-treat depression: differential diagnosis, subtypes, and comorbidities
.
J Clin Psychiatry
.
2009
;
70
Suppl 6
:
10
5
. .
15.
McGuffin
P
,
Katz
R
,
Watkins
S
,
Rutherford
J.
A hospital-based twin register of the heritability of DSM-IV unipolar depression
.
Arch Gen Psychiatry
.
1996
;
53
(
2
):
129
36
.
PubMed PMID: 8629888
.
16.
Villafuerte
SM
,
Vallabhaneni
K
,
Sliwerska
E
,
McMahon
FJ
,
Young
EA
,
Burmeister
M.
SSRI response in depression may be influenced by SNPs in HTR1B and HTR1A
.
Psychiatr Genet
.
2009
;
19
(
6
):
281
91
.
DOI: 10.1097/YPG.0b013e32832a506e. PubMed PMID: 19829169; PubMed Central PMCID: PMC2783179
.
17.
Lamba
JK
,
Lin
YS
,
Schuetz
EG
,
Thummel
KE.
Genetic contribution to variable human CYP3A-mediated metabolism
.
Adv Drug Deliv Rev
.
2002
;
54
(
10
):
1271
94
.
PubMed PMID: 12406645
.
18.
Fekadu
A
,
Wooderson
SC
,
Markopoulo
K
,
Donaldson
C
,
Papadopoulos
A
,
Cleare
AJ.
What happens to patients with treatment-resistant depression? A systematic review of medium to long term outcome studies
.
J Affect Disord
.
2009
;
116
(
1–2
):
4
11
. .
19.
Hicks
JK
,
Swen
JJ
,
Thorn
CF
,
Sangkuhl
K
,
Kharasch
ED
,
Ellingrod
VL
et al
.
Clinical Pharmacogenetics Implementation Consortium guideline for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants
.
Clin Pharmacol Ther
.
2013
;
93
(
5
):
402
8
.
DOI: 10.1038/clpt.2013.2. PubMed PMID: 23486447; PubMed Central PMCID: PMC3689226
.
20.
Hall-Flavin
DK
,
Winner
JG
,
Allen
JD
,
Jordan
JJ
,
Nesheim
RS
,
Snyder
KA
et al
.
Using a pharmacogenomic algorithm to guide the treatment of depression
.
Transl Psychiatry
.
2012
;
2
:
e172
.
DOI: 10.1038/tp.2012.99. PubMed PMID: 23047243; PubMed Central PMCID: PMC3565829
.
21.
Hall-Flavin
DK
,
Winner
JG
,
Allen
JD
,
Carhart
JM
,
Proctor
B
,
Snyder
KA
et al
.
Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting
.
Pharmacogenet Genomics
.
2013
;
23
(
10
):
535
48
. .