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Polymorphisms in inflammation-related genes are associated with
susceptibility to major depression and antidepressant response
M-L Wong, C Dong, J Maestre-Mesa, and J Licinio
Department of Psychiatry and Behavioral Sciences, Center on Pharmacogenomics, University of
Miami Miller School of Medicine, Miami, FL, USA
Abstract
There are clinical parallels between the nature and course of depressive symptoms in major depressive
disorder (MDD) and those of inflammatory disorders. However, the characterization of a possible
immune system dysregulation in MDD has been challenging. Emerging data support the role of T-
cell dysfunction. Here we report the association of MDD and antidepressant response to genes
important in the modulation of the hypothalamic-pituitary-adrenal axis and immune functions in
Mexican Americans with major depression. Specifically, single nucleotide polymorphisms (SNPs)
in two genes critical for T-cell function are associated with susceptibility to MDD: PSMB4
(proteasome β4 subunit), important for antigen processing, and TBX21 (T bet), critical for
differentiation. Our analyses revealed a significant combined allele dose-effect: individuals who had
one, two and three risk alleles were 2.3, 3.2 and 9.8 times more likely to have the diagnosis of MDD,
respectively. We found associations of several SNPs and antidepressant response; those genes
support the role of T cell (CD3E, PRKCH, PSMD9 and STAT3) and hypothalamic-pituitary-adrenal
axis (UCN3) functions in treatment response. We also describe in MDD increased levels of CXCL10/
IP-10, which decreased in response to antidepressants. This further suggests predominance of type
1 T-cell activity in MDD. T-cell function variations that we describe here may account for 47.8% of
the attributable risk in Mexican Americans with moderate MDD. Immune function genes are highly
variable; therefore, different genes might be implicated in distinct population groups.
Keywords
TBX21; PSMB4; major depression; genetic; SNP; cytokine
Introduction
Major depressive disorder (MDD) is a common and complex disorder of unknown etiology
that affects about 15% of the population.
1
Despite recent scientific advances and its enormous
social costs,
2
MDD is still currently thought to be a gene-environment disorder of polygenic
nature with a descriptive diagnosis and no known biomarkers.
1
Although the contributions of
immune mediators to the pathophysiology and treatment of psychiatric disorders may be traced
back to over 80 years with the work of Nobel laureate Julius Wagner-Jauregg,
3
evidence from
clinical and basic research have recently supported a role for dysregulation of the immune
system in MDD.
4
Both acute stress and MDD are states of hyperarousal, in which a sustained
focus on the threatening stimulus, fear-related behaviors and stereotyped states of cognition
and affect are matched with indices of physiological hyperarousal, such as activation of the
Correspondence to: M-L Wong.
Correspondence: Dr M-L Wong, Department of Psychiatry and Behavioral Sciences, Center on Pharmacogenomics, School of Medicine
at the University of Miami, 1580 NW 10th Avenue, Room 633-A, Miami, FL 33136, USA. E-mail: mali@miami.edu.
NIH Public Access
Author Manuscript
Mol Psychiatry. Author manuscript; available in PMC 2009 March 3.
Published in final edited form as:
Mol Psychiatry. 2008 August ; 13(8): 800–812. doi:10.1038/mp.2008.59.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
hypothalamic-pituitary-adrenal (HPA) axis and sympathetic activation, and inhibition of
counterproductive neurovegetative functions during life-threatening situations.
5,6
Depression-like symptoms have been associated with activation of the HPA axis, sympathetic
nervous system and inflammatory response characterized by hypercortisolaemia,
7
increased
central corticotropin-releasing hormone (CRH)
8-10
and norepineprhine
11,12
functions,
increased numbers of peripheral leukocytes, positive acute phase proteins and proinflammatory
cytokines.
13
We and others have proposed a role for proinflammatory cytokines in the pathophysiology of
MDD, with activation of the immune system and of the cellular immune response.
14,15
Even
though still underexplored in MDD, the T-cell arm of the immune system has been emerging
as the centerpiece of the continued debate over the role of the immunomediators in depression.
15,16
Data supporting either a predominance of cytokine-producing helper T-cells, type 1
(Th1) or type 2 (Th2) have accumulated. The overactivity of the hallmarks of Th1 immunity,
such as interferon-γ (IFNγ), tumor necrosis factor-α or interleukin-1 (IL-1),
17
or predominant
Th2 patterns of production supported by increased levels of IL-6, IL-10 or IL-13
16
have
continued to fuel this discussion. At least two fundamental processes may contribute to the
role of the T-cell arm of adaptive immunity in MDD: T-cell programmed differentiation and
antigen processing.
Naive CD4
+
T lymphocytes proliferate and differentiate into two main lineages defined by
distinct cytokine profiles
18
after encountering antigen-carrying dendritic cells in secondary
lymphoid organs. The balance of two main subtypes of cytokine-producing Th1/Th2
determines the immune response to pathogens. Clinically, Th1 patterns of cytokine production
are associated with inflammation and autoimmune disease, whereas Th2 patterns are related
to allergic responses and asthma.
19
Th1 cell-lineage commitment is controlled by the key
transcriptional factor TBX21 (Tbet),
20
which is rapidly produced early in Th1 differentiation
and gradually decreases at later stages.
21
TBX21 has the ability to simultaneously drive Th1
genetic programs and repress the development of the opposing Th2 subset; it may also redirect
fully polarized Th2 cells into Th1 cells.
Proteasomes (prosome, macropain) are the major intracellular extralysosomal organelle for
protein degradation and a central source of antigenic peptides in the endogenous pathway; they
are utilized in major histocompatibility complex molecules class I (MHC1) antigen processing
and protein degradation. Proteasomes are highly abundant in the cytosol and nucleus and are
organized as multiunit protease complexes. Protein degradation is central to many important
biological functions, including cell-cycle progression, apoptosis, synaptic reorganization,
DNA repair, normal immune surveillance mechanisms and immune response networks.
Disruption of the proteasomal degradation pathway has been implicated in a wide range of
human disorders; immune abnormalities include the development of CD8
+
T lymphocytes
and MHC1 molecules, and MHC1-restricted antigen presentation have been described in mice
lacking proteasome subunits.
22
Independent lines of research have supported the role of
protein synthesis/degradation in MDD-like neuropsychiatric symptoms in autoimmune
disorders
23
and in the central actions of antidepressant drugs.
24
We used a combination strategy consisting of genetic analyses and functional assays to assess
the association of pivotal elements of acquired immunity relevant to the HPA axis modulation
and T-cell function with susceptibility to MDD and antidepressant response. We genotyped a
panel of single nucleotide polymorphisms (SNPs) focused on the steroid pathway
25
and on
proteasome subunit genes (Table 1). We also conducted multiplex assays of 21 circulating
cytokines in a subset of our patients.
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Methods
Genetic study
Study population—This study was approved by the institutional review boards of the
University of California Los Angeles and the University of Miami, and it has been registered
in the public database ClinicalTrials.gov (NCT00265292). The study population consisted of
284 depressed Mexican Americans enrolled in a pharmacogenetic study of antidepressant
treatment response as previously described.
26,27
We also studied 331 control individuals
recruited from the same Mexican-American community in Los Angeles and studied by the
same bilingual clinical research team. Controls for our genomic studies were in general good
health but were not screened for medical or psychiatric illness. All patients were Mexican-
American men and women aged 21-68 years, with a current episode of major depression as
diagnosed by DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edn).
28
In
our study, all Mexican-American subjects had at least three grandparents born in Mexico.
26
All patients had comprehensive psychiatric and medical assessments. We used diagnostic and
ratings instruments that have been fully validated in English and Spanish, and conducted all
assessments in the subject's primary language.
Inclusion criteria included DSM-IV diagnosis of current, unipolar major depressive episode,
with a 21-item Hamilton Depression Rating Scale (HAM-D21)
29
score of 18 or greater with
item number 1 (depressed mood) rated 2 or greater. There was no anxiety threshold for
inclusion. Subjects with any primary axis I other than MDD (for example, dementia, psychotic
illness, bipolar disorder, adjustment disorder), electroconvulsive therapy in the past 6 months
or previous lack of response to desipramine or fluoxetine were excluded. As anxiety can be a
manifestation of depression, patients who met criteria for depression and also anxiety disorder
were not excluded. Exclusion criteria included active medical illnesses that could be
etiologically related to the ongoing depressive episode (for example, untreated
hypothyroidism, cardiovascular accident within the past 6 months, uncontrolled hypertension
or diabetes), current, active suicidal ideation with a plan and strong intent, pregnancy, lactation,
current use of medications with significant central nervous system activity, which interfere
with electroencephalography (EEG) activity (for example, benzodiazepines) or any other
antidepressant treatment within the 2 weeks prior to enrollment, illicit drug use and/or alcohol
abuse in the past 3 months or current enrollment in psychotherapy.
Depressed subjects were enrolled in an outpatient double-blind study of antidepressant
treatment response to desipramine or fluoxetine.
26
The treatment had two phases. Phase 1 was
a 1-week, single-blind placebo lead-in phase to eliminate placebo responders. Subjects who
continued to meet the inclusion criteria after phase 1 were randomly assigned to one of two
treatment groups in a double-blind manner in phase 2; they received fluoxetine 10-40mg per
day or desipramine 50-200mg per day for 8 weeks, with a dose escalation based on clinical
outcomes. Depressed subjects had up to 9 weeks of structured follow-up assessments. The
effect of antidepressants on HAM-D21 score was measured by the relative reduction computed
as the difference in HAM-D21 score between pre- and post-treatment divided by the
pretreatment HAM-D21 score. Responders were defined as the patients who had a higher than
50% reduction in HAM-D21 score on the final week (week 8).
Genotyping assays—Blood samples were collected into ethylenediaminetetraacetic acid
(K
2
EDTA) BD Vacutainer EDTA tubes (Becton, Dickinson and Co., Franklin Lakes, NJ, USA)
and genomic DNA was isolated from those samples using Gentra Puregene DNA purification
kits (Gentra Systems Inc., Indianopolis, IN, USA). Genotyping of SNPs was performed using
a SEQUENOM MassARRAY MALDITOF mass spectrometer (Sequenom, San Diego, CA,
USA) for analysis of unlabeled single-base extension minisequencing reactions
27
or using the
Golden Gate assay (Illumina, San Diego, CA, USA) as part of a multiplex reaction as previously
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described.
26
Our SEQUENOM protocol implemented the very short extension method
proposed by Sun and colleagues
30
whereby sequencing products are extended by only one
base for three of the four nucleotides (due to the presence of dideoxynucleotides for three of
the four nucleotides in the minisequencing reaction) and by several additional bases for the
fourth nucleotide (specified in advance so as to represent one of the two alleles at a given SNP
locus). This allowed for clearly delineated mass separation of the two allelic variants at a given
locus. We addressed population stratification by stratifying our analysis by self-designated
ethnic group. A set of random markers across the genome was also genotyped. Cleaning and
filtering steps were performed as previously described
26,27
Only data generated by SNP
assays that were successfully genotyped on at least 80% of samples were included. Data quality
was assessed by duplicates DNAs across all plates. Genotypes from nonmatching or missing
duplicates were dropped.
Hardy-Weinberg equilibrium—We performed both standard asymptotic test and exact test
for Hardy-Weinberg equilibrium (HWE) described by Wigginton et al.
31
using PLINK
program (http://pngu.mgh.harvard.edu/~purcell/plink/). For a locus with two alleles, the locus
is in HWE in the population when the relationship between allele frequencies and genotype
proportions follows the equation p
2
+ 2pq + q
2
= 1, where p and q are the frequencies for major
and minor allele, respectively. Exact test of HWE is a more appropriate approach when one
allele is very rare. We detected deviation from HWE separately for control and depressed
groups, and excluded those SNPs that were not in HWE in the control group.
Data analyses
SNP-based analyses of susceptibility to MDD—We performed allelic association tests
using the PLINK program. Specifically, we employed χ
2
-test, or Fisher's exact test when the
minor allele was rare, to examine the allelic association with depression by comparing allele
frequencies between cases and controls. We used the following procedures to identify a list of
SNPs statistically associated with a diagnosis of depression: (1) study population and controls
were randomly divided into two groups: discovery and replication samples; (2) significance
level was set at P≤0.05 for both discovery and replication samples; (3) the minor allele
frequency in controls was ≥5% and (4) the Benjamini and Hochberg method was used to control
for false discovery rate and the significance threshold was set at FDR_BH≤0.05.
32
For the
SNPs associated with depression in the discovery sample, we compared the odds of having
depression in individuals having a risk allele with those homozygous for a nonrisk allele.
Odds ratios and population attributable fraction—We compared the odds of having
depression given the homozygous for major and minor, or heterozygous genotype for the SNPs
associated with diagnoses of depression. Odds ratios (ORs) and their 95% confidence intervals
(CIs) were calculated using the PLINK program. We also calculated population attributable
fraction (PAF) to estimate the proportional amount by which disease risk is due to the risk
genotypes in the population.
33
SNP-based analyses of drug response—We used χ
2
-test to investigate the allelic
association with drug response status by comparing allele frequencies between responders and
nonresponders; we used Fisher's exact tests when the minor allele was rare. We calculated the
allelic OR for response status and its 95% CI using Woolf's method or fitting exact logistic
regression model with SAS software when the frequency in a table cell is 0. For the SNPs with
a P < 0.05 in responder vs nonresponder analysis or nonsynonymous SNPs close to any of
these SNPs, we also employed a general linear regression model to examine the additive effect
of minor allele on the relative reduction of HAM-D21 score by controlling age, gender and
baseline HAM-D21 score using the PLINK program.
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Haplotype analyses—We used Haploview version 4.0 program
(http://www.broad.mit.edu/mpg/haploview/) and applied the four-gamete rule
34
to conduct
haplotype analysis with the depressed and control groups combined to test whether a certain
haplotype was associated with the risk for depression. Blocks are formed by consecutive
markers where only three gametes are observed, and htSNPs are defined in Haploview by using
aggressive tagging (two- and three-marker haplotypes). All haplotypes > 0% were examined,
and nontagging SNPs within haplotype blocks were omitted from the final analyses (Figure
1).
Analyses of combined effect—We used Rothman's synergy index (S) to assess the joint
effect of the two polymorphisms.
35
The S index is the ratio of the observed joint effect divided
by the expected joint effect assuming additivity of the effects, defined as: S = (OR
11
1)/
(OR
10
+OR
-01
-2) in which subscript 0 denotes the absence of the risk genotype at the SNP and
OR denotes the odds ratio. No interaction corresponds to S = 1, whereas S >1 (S < 1) can be
interpreted as a measure of relative increase (decrease) in the effect among those exposed to
risk genotypes at both SNPs. In addition, we conducted the Cochran-Armitage trend test to
examine dose-effect relationship between the sum of risk alleles at both SNPs and the OR for
depression. We used SAS Proc Genmod to calculate ORs and their 95% Wald CIs (SAS version
9.1.3;SAS Institute, NC, USA).
Immunoassay study
Study population—A subset of the genetic study population, consisting of 68 Mexican-
American MDD patients (51 women (36.0±8.3 years old and body mass index (BMI) 28.8±5.8;
mean s.d.) and 17 male (36.1±10.1 years old and BMI 28.2±5.2; mean+s.d.)) and 18 Mexican-
American controls (12 women (36.1±9.2 years old and BMI 28.9±3.6; mean+s.d.) and 6 men
(31.5±9.4 years old and BMI 29.1±6.1; mean+s.d.)), was assessed by 21-plex cytokine assay.
Controls were free of ongoing physical illness and showed no evidence of major psychiatric
illness in clinical and structured interviews. Fasting blood was collected for cytokine assays
one time in controls and two times in MDD patients (pretreatment at week-1 and post-treatment
at week 8). Among 68 patients, 29 were assessed for the cytokines at week 8 and 1 patient was
assessed only at week 8.
Immunoassays—Plasma samples were collected before the initiation of antidepressant
treatment in MDD patients. We used Human Cytokine 21 PLEX-Premixed immunoassay kits
(Linco Research Inc., St Charles, MO, USA) and a multi-analyte detection system (Luminex
100 instrumentation and xMAP technology; Luminex Corp., Austin, TX, USA) to
simultaneously obtain the level of several cytokines and chemokines. Assays were performed
accordingly to the manufacture's instructions. Assays were run in duplicates and coefficient of
variance was ≥15%.
Data analyses—Pearson's χ
2
-test was performed to test for the difference of gender
frequency and Student's t-test was conducted to compare the mean difference in age and BMI
between MDD patient and control groups. No significant difference was found in age and BMI
means and gender frequency between the two groups. We excluded 10 analytes from the
analyses because their frequencies of undetectable level were over 30%. Of the remaining 11
analytes, we used logarithmic transformation for chemokine CXCL10/IP10 levels because of
the high kurtosis (11.14) and skewness (2.73). After transformation, the kurtosis and skewness
for the log10 (CXCL10/IP10) were 1.33 and 0.27, respectively. We conducted analysis of
covariance analyses based on general linear model by including age, gender and BMI as
covariates to compare cytokine levels between controls and pretreatment MDD patients. We
performed paired t-test to compare pre- and post-treatment cytokine levels in MDD patients
with response to antidepressant treatment. All these analyses were performed using SAS.
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Results
SNP associated with MDD
In our discovery sample, the MDD diagnosis was significantly associated with SNPs in the
following genes (Table 2): PSMB4, POMC, CDC42SE2, NR3C1, ABCB1, TBX21 and
GTF2F1. The association of four SNPs was confirmed in our replication sample; two of those
untranslated regions (UTRs) SNPs: rs2296840 (T/C, 5′ UTR) in PSMB4 (proteasome β4
subunit, β7 hs, HN3, HsN3, PROS26, O(MIM) MIM 602177) and rs17244587 (G/A, 3′ UTR)
in TBX21 (T-bet, O(MIM) MIM 604895) remained significant after Benjamini and Hochberg
correction for multiple testing using the combined sample (Figure 1; Table 2). Mexican-
American individuals with the minor allele T at rs2296840 in PSMB4 were 70% more likely
to be in the MDD than in the control group (OR = 1.7; 95% CI: 1.3-2.1) and 23.2% of population
risk could be attributable to the genotypes (TC or TT) at 2296840 (Table 2). Individuals who
had the minor allele A at rs17244587 in TBX21 were twice more likely to be in the MDD than
in the control group (OR = 2.0; 95% CI: 1.4-2.7) and 20.1% of population risk could be
attributable to the genotypes (AG or AA) at rs17244587 (Table 2). Taken together, 47.8% of
the population risk could be attributable to the risk genotypes at rs2296840 in PSMB4 or
rs17244587 in TBX21 (Table 3). The joint effect of the combined genotypes of rs2296840
(recessive model) and rs17244587 (dominant model) was 26% greater than that predicted by
assuming additivity of effects (S = 1.26) (Table 3).
Trend SNPs were located in the 3′-flanking region of TBX21 in chromosome 17q21.3
(rs4151574 and rs2325717), and in the coding region of PSMB4 (rs4603) in chromosome 1q21.
Figure 1 depicts that we have identified three significant risk haplotypes: CCA and ATG
(TBX21, blocks 1 and 2, respectively), and TCT (PSMB4), and four protective haplotypes:
CCG and GCG (TBX21, block 1), and ACA (TBX21, block 2) and CCC (PSMB4). Notably,
the 5′ UTR SNP in PSMB4 is in linkage disequilibrium with the missense SNP rs4603 (C/T;
Ile234Thr).
SNP associated with antidepressant response
Five SNPS in the steroidal pathway and proteasome genes were significantly associated with
antidepressant response within the entire depressed group treated either with desipramine or
fluoxetine (Table 4). They were located in the following genes: CD3E (rs2231449, CD3
antigen-ε subunit, OMIM 186030), PRKCSH (rs34095, protein kinase C substrate 80 kD, heavy
chain, OMIM 177060), PSMD9 (rs1043307, proteasome 26S non-ATPase subunit 9),
STAT3 (rs3809758, signal transducer and activator of transcription 3, OMIM 102582) and
UCN3 (rs10904481, urocortin III). The association of three genes remained significant in our
general linear regression analyses after controlling for age, gender and baseline HAM-D score
(Figure 2a). Among these polymorphisms, the two nonsynonymous, rs104330 (Glu197Gly) in
PSMD9 and rs10904481 (Arg91Gly) in UCN3, and one 3′ UTR: rs2231449 (A/C) in CD3E
are most likely to be functionally relevant.
Fluoxetine treatment
Eight SNPs located in five genes were associated with treatment response during fluoxetine
treatment (Table 4). SNPs in CYP3A4 (rs2242480), PSMD13 (rs1045288 and rs3817629),
CDE3 (rs2231449), PRKCSH (rs160841) and PSMA7 (rs2057169, rs2057168, rs2281740,
rs3746651) had a difference in allele frequency with P≤0.05 for responders and nonresponders
within the subjects treated with fluoxetine. The association of four genes remained significant
in general linear regression analyses after controlling for age, gender and baseline HAM-D
score (Figure 2c). Patients who had minor allele A at missense SNP rs1045288 (Asn13Ser) in
PSMD13 had better response (β = 18.13; 95% CI: 8.29-27.96), whereas those who had minor
allele C at 3′ UTR SNP rs3746651 in PSMA7 had smaller relative reduction in HAM-D21 score
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(β = 11.5; 95% CI: -3.34 to -18.26). Patients who had minor allele A at 3′ UTR SNP rs2231449
in CDE3 showed much worse response (β = 37.17; 95% CI: -55.69 the to -18.65), but the
number in this group was very small. Two genes (CD3E and PRKCSH) associated with
response in the entire depression group were also associated with response in the fluoxetine
treated subjects.
Desipramine treatment
Six SNPs located in or near five genes were associated with treatment response during
desipramine treatment. SNPS in ABCB1 (rs1202186), CRHR2 (rs917195), PRKCSH
(rs34095), PSMD9 (rs1043307, missense) and STAT3 (rs3744483, 3′ UTR, and rs3809758)
had a difference in allele frequency with P≤0.05 for responders and nonresponders within the
subjects treated with desipramine (Table 4; Figure 2b). Three of these SNPs (rs1043307,
rs3809758, rs34095) were associated with response in the entire depression group were also
associated with response to desipramine treatment.
Immunoassays
To further understand aspects of immune dysfunction relevant to MDD and/or treatment
response, we examined patterns of cytokines in plasma and found increased circulating plasma
levels of the IFNγ-inducible chemokine CXCL10/IP10
36
in our MDD patients before initiation
of antidepressant treatment when compared to controls (P = 0.035; 95.50±1.06 and 67.61±1.16
pg ml
1
, respectively in MDD and control groups, mean±s.d. calculated by using logarithmic
transformation; Figure 3a) and significant decrements were found for IL-13 levels in MDD
patients when compared to controls (P = 0.043; 11.87±11.77 and 20.82±14.77 pg ml
1
,
respectively in MDD and control groups). Patients who responded to antidepressant treatment
had a significant decrement in levels of CXCL10 (P = 0.03; 1.20±1.38 pg ml
-1
, paired mean
difference ±s.d. calculated by using logarithmic transformation; Figure 3b).
Discussion
We found that two genes that are critical for T-cell function, PSMB4 and TBX21, are associated
with major depression. We found that together, 47.8% of the population risk could be
attributable to the risk genotypes at rs2296840 in PSMB4 or rs17244587 in TBX21. The joint
effect of the combined genotypes of rs2296840 (recessive model) and rs17244587 (dominant
model) was 26% greater than that predicted by assuming additivity of effects. Our analyses
revealed a significant combined allele dose-effect; therefore, individuals who had one, two and
three risk alleles in PSMB4 and TBX21 were 2.3, 3.2 and 9.8 times more likely to have the
diagnosis of MDD, respectively. We also found associations of several SNPs in genes relevant
to HPA axis and immune function and antidepressant response and describe in MDD increased
levels of CXCL10/IP-10, which decreased in response to antidepressants. These lines of
evidence are indicative of a predominance of Th1 activity in MDD.
Genetic variations in PSMB4 and TBX21 may also be relevant to two immune disorders,
psoriasis
37
and asthma,
38
that are known to be comorbid with MDD. These two disorders are
polygenic and reactive to psychosocial stressors. Susceptibility to psoriasis has been associated
to the area of chromosome 1q21 (PSORS4) that encodes PSMB4
,30
and susceptibility to
asthma and nasal polyps (O(MIM) MIM 208550)
14
has been associated with functional
promoter SNPs in TBX21 (1993T/C), in chromosome 17q21.3.
The UTR variations in TBX21 and PSMB4 that we found to be significantly associated with
MDD are in UTRs but they may nevertheless impact on immune response in our patients.
Several roles in gene expression have been attributed to UTRs, including mRNA stability,
localization and translational efficiency. The 5′ UTR, also known as the leader sequence, is a
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particular section of the mRNA that usually contains a ribosome-binding site; it is a major site
of translational regulation and may affect the stability or translation of mRNA and gene
expression. Evidence implicating the 3′ UTR of mRNA in the regulation of gene expression
has accumulated recently. The 3′ UTR may influence transcript cleavage, polyadenylation and
nuclear export, which determine transcript stability, level of translation and mRNA targeting.
39
It is therefore plausible that SNPs associated with treatment response may have contributed
to the increased plasma levels of the IFNγ-inducible chemokine CXCL10 found in our patients.
CXCL10 is a potent angiostatic factor with anti-fibrotic properties
40
and its elevation is
congruent with elevated leukocyte counts in peripheral blood that have been shown to be
dependent on severity and treatment outcome in MDD.
41
Inflammatory immune mediators
and specifically CXCL10 have also been implicated in arteriosclerosis, and they may be a link
between the presence of depressive symptoms and stress, and increased risk of, morbidity and
mortality in myocardial infarction.
42
The increase of an IFNγ-inducible chemokine supports
the presumption of a predominance of Th1 type activity during the symptomatic phase of MDD,
as well as its role in the pathophysiology, therapeutic outcome of this disorder and
immunoregulatory effects of antidepressants.
43
We found that genetic variations affecting T-cell function and HPA axis regulation were
associated with antidepressant treatment response. The following T-cell functions may be
implicated in treatment response: T-cell development (CD3E, T-cell antigen receptor-ε subunit
of T3),
44
antigen processing/degradation (PSMD9: proteasome 26S subunit, non-ATPase,
9,
45
and intracellular signaling (STAT3: signal transducer and activator of transcription 3).
46
The association of a variation in the urocortin III or stresscopin gene (UCN3)
47
suggests a
possible role for the adaptive stress response that mediates endocrine, autonomic,
cardiovascular and immune systems in treatment outcome. The association of a SNP in the
CRHR2 in the treatment response to desipramine indicates that HPA axis modulation may be
particularly important for tricyclic antidepressants. Notably, some of the SNPs associated with
treatment response could lead to differences in immune response such as nonsynonymous
variations in the PSMD9 and UCN3 genes, and 3′ UTR SNPs in CD3E, STAT3 and PSMA7
genes. Somatic variations in some of those genes have been implicated in immunodeficiencies
(CD3E),
48,49
polycystic liver disease (PRKCSH, protein kinase C substrate, 80 kD, heavy
chain,
50-52
type 2 diabetes
53
or autosomal dominant hyper-immunoglobulin E (IgE)
syndrome, also called `Job Syndrome'.
54-56
We found no clear Th1 or Th2 cytokine patterns in our patients. Our results of decreased IL-13
levels in MDD contrast with a recent report of increased levels of Th2 cytokines IL-13 and
IL-4 and decreased levels of Th1 cytokines.
16
Several factors could account for this
discrepancy, from differences in gender and age composition to differences in environment/
pathogens or differences in the phases of neuroendocrine, counterregulatory systems or
severity and stage of the disorder. Moreover, cytokine profiling in Th1 and Th2 cytokine
expression seem to be relative, not absolute as inconsistencies between cytokine profiles,
antibody and total serum IgE have been reported.
57
Therefore, chemokines (such as CXCL10),
which are low molecular weight chemotactic molecules, are emerging as a major
communication system in the brain
58
as their serum and CSF levels may be correlated.
59
Chemokines are key mediators of inflammation that have major effects on migration of cells
to inflammation sites as well as activation of recruited and resident central nervous system
(CNS) cells, which have been implicated in a number of human pathophysiological systemic
and CNS conditions
60
and their level or expression has been linked to the activity of CNS
disease.
Figure 4 summarizes our results of genetic variations associated with the diagnosis of MDD.
These implicate that specific UTR variations in TBX21 or PSMB4 increase the risks for and
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characterize a T-cell dysfunction in MDD in Mexican Americans. These genetic variations
may be involved in the immune system dysregulation described in this disorder and in known
comorbidity disorders such as psoriases
38
and asthma.
37
Our patients had increased peripheral
levels of the chemokine CXCL10, which decreased with response to antidepressant treatment.
These results lead to the presumption that an imbalance of Th1/Th2 activity toward a
predominance of Th1 response is present in the symptomatic phase of mild to moderate forms
of MDD. Replication of our findings in other ethnic groups is needed to validate the role of
TBX21 and PSMB4 in major depression here reported in Mexican Americans. Because genes
involved in immune function are highly polymorphic in human populations,
61
allele frequency
may vary considerably in different ethnic populations, and variations of T-cell function may
result from common variations in other genes/gene regions, which may cause a predominance
of net Th1 activity. The allele frequency for rs17244587 (TBX21) in our subjects was similar
to European populations; however, rs2296840 and rs4603 (PSMB4) were significantly less
frequent (respectively 0 and 10%) in Europeans than in the Mexican Americans we studied
(24% in Mexican-American controls and 34% in MDD). It is therefore unlikely that the
PSMB4 variations described here are significant in the susceptibility to MDD in individuals of
predominant European descendant. Consequently, characterization of neuroimmune profiles
may vary depending on specific genes and SNPs involved in T-cell function variations in
different populations. Moreover, given our n and limited numbers of patients in the desipramine
and fluoxetine treatment groups, these results need to be taken with caution, pending replication
by other independent studies.
Because chemokine networks already represent potentials targets for new therapies in several
CNS and systemic conditions,
58
further studies are needed to fully clarify the extent of CNS
immunedysregulation in the pathophysiology of MDD.
In spite of the limitations of this study, our data support the hypothesis that key T-cell functions
leading to Th1 net activity are features of immune dysfunction in MDD and may also have a
role in antidepressant treatment response. Different genes and polymorphisms might
characterize MDD immune dysfunctions in distinct populations, as genes that influence
immune functions are highly polymorphic and their allele frequency varies across human
populations. We suggest that interferon-γ-inducible chemokines, such as CXCL-10, may
provide viable biomarkers and might also be useful in predicting/following antidepressant
response. Our findings provide a basis for conceptually innovative pharmacological
approaches to MDD with a focus on T-cell function dysregulation and variations in T-cell
programmed differentiation, antigen processing and cellular proteasome organelle function.
Acknowledgments
This study was supported by NIH grants GM61394, RR017365, MH062777, RR000865, RR16996, HG002500 and
DK063240, and institutional funds from the University of Miami, Department of Psychiatry & Behavioral Sciences.
We thank the Mexican American individuals who have participated in this study. We are grateful for the contributions
to the care of our patients from Dr Israel Alvarado, Dr Deborah Flores and Dr Anil Sharma; our nursing staff Rita
Jepson and Lorraine Garcia-Teague; our social workers Patricia Reyes and Gabriela Marquez at the Semel Institute
for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA) and staff of the UCLA GCRC.
We thank Dr Kristopher Irizarry (UCLA), Dr Luciana Ribeiro (University of Miami) and Dr Joao Busnello (University
of Miami) who have helped us with bioinformatics and database aspects of the work. We are also grateful for the
contributions of Fiona O'Kirwan and Sarika Thakur (Semel Institute), and Dr Rita Cantor, Department of Genetics,
UCLA, in preliminary statistics analyses. We also thank Dr Scott Weiss for facilitating our interactions with the
Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston,
MA, and Dr Panos Deloukas for facilitating genotyping work at the Wellcome Trust Sanger Institute, UK.
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Figure 1.
Linkage disequilibrium pattern in TBX21 and PBSM4 genes. Standard color scheme: white, D
′ < 1 and logarithm of odds (LOD) < 2; blue, D′ = 1 and LOD < 2; shades of pink/red, D′ < 1
and LOD≥2; bright red, D′ = 1 and LOD≥2. D′-values represent percentages and appeared
inside each diamond; values of 100% are not labeled. At the top of the figure, gene structures
are illustrated schematically by a thick horizontal white rectangle. Short vertical lines indicate
genotyped single nucleotide polymorphisms (SNPs), which correspond to the numbers above
the triangular image for genes TBX21 and PSMB4. Haplotype blocks were defined using the
four game rule and haplotype tagging SNPs (htSNPs) are shown in bold. At the bottom of the
triangular figures, haplotypes are shown in blocks with frequency and connections from one
block to the next; only htSNPs are displayed. Blocks are connected with thin lines if frequency
is > 5% and thick lines if > 10%. Between the blocks, a value of multiallelic D′ is shown. D′
is a measure of the recombination between the two blocks. TBX21: two haplotype blocks were
defined; block 1 (1 kb; SNPs 3-5: rs17250953, rs11650354 and rs17244587) and block 2 (44
kb; SNPs 6-8: rs7502875, rs41515744 and rs2325717). Haplotype CCA in block 1 is the most
significantly association with major depressive disorder (MDD) diagnosis (P < 0.0001).
PSMB4: one haplotype block was defined; haplotype TCT was significantly associated with
MDD diagnosis (P = 0.0001). *P < 0.05, **P < 0.01 and ***P≤0.0001.
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Figure 2.
Genotypes and relative reduction of Hamilton Depression Rating Scale (HAM-D) score in the
patients treated with desipramine and fluoxetine. Histograms represent mean and standard error
of mean for relative reduction of HAM-D21 score in major depressive disorder (MDD) patients
who completed 8-week antidepressant treatment with desipramine (n = 68) or fluoxetine (n =
79) by genotypes (light blue, homozygous for minor allele; orange, heterozygote; dark blue,
homozygous for major allele). A general linear model was used to detect allelic additive effects
on treatment response after adjustment for age, sex and baseline HAM-D21 score. The analyses
were performed using all treated patients (a), desipramine-treated patients (b) and fluoxetine-
treated patients (c).
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Figure 3.
CXCL10 (IP10) and interleukin-13 (IL-13) levels in controls, major depressive disorder
(MDD) patients and drug responders. (a) Histograms represent mean and standard error for
CXCL10 and IL-13 levels in MDD patients before initiation of antidepressant treatment (n =
65) and controls (n = 14). Comparison levels between cases and controls were performed using
general linear model after adjustment for age, sex and body mass index (BMI). Log arithmetic
transformation was used for CXCL10 in our data analyses. (b) Histograms represent mean and
standard error for CXCL10 and IL-13 levels before and after 8 weeks of antidepressant
treatment in 19 antidepressant treatment responders (MDD patients who had higher than 50%
reduction in Hamilton Depression Rating Scale (HAM-D21 score). Paired t-test was used to
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compare pre- and post-treatment levels in drug responders. Log arithmetic transformation was
used for CXCL10 in our data analyses.
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Figure 4.
Schematic of sites where variations in TBX21 or PSMB4 could influence the T-cell arm of the
adaptive immunity and contribute to susceptibility to major depressive disorder (MDD): Two
crucial functions, specifically antigen processing and T cell-programmed differentiation are
involved in Mexican Americans with MDD and are highlighted in red. A naive helper T-cell
precursor (Th p) can become either a Th1 or Th2 cell under the instructive influence of
interleukin-12 (IL-12) or IL-4, respectively; Th1 cell expresses TBX21 and Th2 expresses
GATA3.
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Table 1
Number of SNPs investigated
Symbols Steroid pathway genes No. of SNPs
ABCB1 ATP-binding cassette, subfamily B (MDR/TAP), member 1 9
CD3E CD3e molecule, epsilon (CD3-TCR complex) 2
CD4 CD4 molecule 7
CD7 CD7 molecule 2
CRH Corticotropin-releasing hormone 8
CRHBP Corticotropin-releasing hormone-binding protein 4
CRHR2 Corticotropin-releasing hormone receptor 2 16
CYP3A4 Cytochrome P450, family 3, subfamily A, polypeptide 4 2
GTF2F1 General transcription factor IIF, polypeptide 1 3
IL18BP Interleukin 18-binding protein 7
IPO13 Importin 13 7
JUND Jun D proto-oncogene 2
MFNG MFNG O-fucosylpeptide 3-β-N-acetylglucosaminyltransferase 6
NR3C1 Nuclear receptor subfamily 3, group C, member 1 9
PFKFB4 6-Phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 3
POMC Proopiomelanocortin 4
PRKCSH Protein kinase C substrate 80K-H 4
RAC2 Ras-related C3 botulinum toxin substrate 2 6
CDC42SE2 CDC42 small effector 2 3
TBX21 T-box 21 9
STAT3 Signal transducer and activator of transcription 3 4
UCN Urocortin 1
UCN2 Urocortin 2 4
UCN3 Urocortin 3 2
Proteasome subunit genes
α A1, A6, A7 6
β B2, B4, B5, B8 6
26S (non-ATPase) D1, D2, D3, D5, D9, D13, D14 19
Inhibitor F1 6
Total 161
Abbreviation: SNPs, single nucleotide polymorphisms.
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Table 2
Polymorphisms associated with risk of depression
Polymorphism Allelic association
Combined sample (N = 559)
Gene SNP Chromosome Position SNP type P
(discovery
sample,
N
a
= 280)
P
(replication
sample, N
b
= 279)
P (FDR_BH) Risk/nonrisk allele Case risk
allele
frequency
Control
risk allele
frequency
OR (95% CI)
PSMB4
rs2296840
c
1 149638671 5′ UTR 0.002 0.002 0.0001 (0.007) T/C 0.34 0.24 1.65 (1.28, 2.12)
rs4603 149640649 Missense 0.07 0.07 0.01 (0.17) A/G 0.75 0.69 1.38 (1.07, 1.78)
POMC rs2118404 2 25230833 Flank 0.02 0.30 0.02 (0.17) T/C 0.55 0.47 1.35 (1.06, 1.73)
CDC42SE2 rs798412 5 130726373 3′ UTR 0.0009 0.53 0.005 (0.12) A/C 0.42 0.34 1.43 (1.11, 1.83)
rs798416 5 130720999 Intron 0.0033 0.43 0.008 (0.13) C/T 0.41 0.33 1.40 (1.09, 1.79)
NR3C1 rs852977 5 142667687 Intron 0.02 0.12 0.007 (0.13) A/G 0.89 0.83 1.61 (1.13, 2.27)
ABCB1 rs1002205 7 86979110 Intron 0.01 0.48 0.03 (0.25) C/G 0.19 0.14 1.45 (1.05, 2.02)
rs1922243 7 86981440 Intron 0.008 0.66 0.03 (0.25) T/C 0.20 0.15 1.45 (1.04, 1.99)
TBX21
rs17244587
d
17 43178034 3′ UTR 0.004 0.005 0.00005 (0.007) A/G 0.21 0.12 1.97 (1.41, 2.74)
rs41515744 17 43186946 Flank 0.04 0.004 0.0004 (0.01) T/C 0.21 0.13 1.80 (1.30, 2.50)
rs2325717 17 43222803 Flank 0.02 0.009 0.0004 (0.01) C/T 0.20 0.12 1.84 (1.31, 2.56)
Abbreviations: CI, confidence interval; FDR_BH, Benjamini and Hochberg false discovery rate; OR, odds ratio; SNP, single nucleotide polymorphism; UTR, untranslated region.
a
Includes 139 cases and 141 controls.
b
Includes 139 cases and 140 controls.
c
Population attributable fraction (PAF) = 23.2%.
d
PAF = 20.1%.
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Table 3
Combined effect of TBX21 and PSMB4 genes on the risk of depression
OR by total risk allele no.
a
OR by combined genotype
b
No. of
risk allele
Case/control OR (95% CI) P rs17244587 rs2296840 Case/control OR (95% CI) P
0 57/93 1.00 - GG CC/TC 133/154 1.00 -
1 123/88 2.28 (1.49-3.50) 0.0002 GG TT 19/8 2.75 (1.17-6.49) 0.02
2 58/30 3.15 (1.82-5.47) 0.00004 AG/AA CC/TC 90/49 2.13 (1.40-3.23) 0.0004
3 12/2 9.79 (2.11-45.3) 0.004 AG/AA TT 8/2 4.63 (0.97-22.2) 0.05
a
Sum of risk alleles at rs17244587 (AA = 2, AG=1, GG = 0) and rs2296840 (TT = 2, TC = 1, CC = 0); Cochran-Armitage trend test: Z = -5.095, d.f. = 1, P = 1.74-E7; PAF = 47.8%.
b
Rothman synergy index= (4.63-1)/(2.75 + 2.13-2) = 1.26.
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Table 4
Polymorphisms associated with response status in the treatment of depression
Minor allele frequency
Medication Gene SNP Chromosome Position SNP type Minor/major allele Responder Nonresponder
or (95% CI)
a
P
a
Desipramine or Fluoxetine UCN3 rs10904481 10 5405954 Missense G/A 0.431 0.586 0.53 (0.30, 0.97) 0.04
CD3E rs2231449 11 117691515 3′ UTR A/C 0.015 0.083 0.17 (0.04, 0.72) 0.007
PSMD9 rs1043307 12 120838179 Missense G/A 0.388 0.591 0.44 (0.25, 0.77) 0.004
STAT3 rs3809758 17 37725506 Intron A/G 0.119 0.031 4.18 (0.96, 18.2) 0.04
PRKCSH rs34095 19 11402685 Intron T/C 0.365 0.625 0.35 (0.18, 0.64) 0.0005
Desipramine CRHR2 rs917195 7 30694977 Flank T/C 0.333 0.125 3.50 (1.24, 9.91) 0.01
ABCB1 rs1202186 7 87051194 Intron G/A 0.107 0.265 0.33 (0.12, 0.93) 0.03
PSMD9 rs1043307 12 120838179 Missense G/A 0.359 0.591 0.39 (0.19, 0.81) 0.01
STAT3 rs3744483 17 37719964 3′ UTR C/T 0.150 0.000 9.15 (1.44, ∞) 0.009
rs3809758 17 37725506 Intron A/G 0.171 0.000 11.28 (1.81, ∞) 0.005
PRKCSH rs34095 19 11402685 Intron T/C 0.341 0.639 0.29 (0.13, 0.66) 0.002
Fluoxetine CYP3A4 rs2242480 7 99199402 Intron T/C 0.398 0.667 0.33 (0.13, 0.83) 0.02
PSMD13 rs3817629 11 227312 Intron T/C 0.170 0.000 6.17 (1.00, ∞) 0.04
CD3E rs2231449 11 117691515 3′ UTR A/C 0.008 0.125 0.06 (0.01, 0.60) 0.002
PRKCSH rs160841 19 11420158 Intron G/A 0.115 0.292 0.31 (0.11, 0.89) 0.02
PSMA7 rs2057169 20 60145679 Intron C/T 0.242 0.546 0.27 (0.11, 0.68) 0.004
rs2057168 20 60145742 Intron C/T 0.235 0.546 0.26 (0.10, 0.65) 0.003
rs2281740 20 60145906 Intron T/C 0.231 0.546 0.25 (0.10, 0.64) 0.002
rs3746651 20 60151815 3′ UTR C/T 0.230 0.500 0.30 (0.11, 0.79) 0.01
Abbreviations: SNPs, single nucleotide polymorphisms; UTR, untranslated region.
a
P-values, odds ratios (OR) and 95% confidence intervals (CI) were estimated on exact logistic regression model if any cell with the frequency is 0.
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