Mario Serrano-Sosa1, Kruthika Sampathgiri2, Christine DeLorenzo2, Ramin Parsey2, and Chuan Huang2,3
1Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States, 2Psychiatry, Stony Brook Medicine, Stony Brook, NY, United States, 3Radiology, Stony Brook Radiology, Stony Brook, NY, United States
Synopsis
Using voxel-based morphology we investigated the relationship between COMT gene polymorphism and
volumetric abnormalities in major depressive disorder patients and healthy controls. A significant difference in the right hippocampus
(p=0.015) was found between the interaction of diagnosis and genotype, which suggests that COMT polymorphism must be considered during any volumetric analysis for
depression.
Introduction
Major depressive disorder (MDD) affects 350 million
people worldwide and is a debilitating chronic disease that impacts 1 in 6
people in the United States during their1,2. Depression is a disorder based on
heterogeneous symptomology which makes it harder to detect and cure3. The
hippocampal region has been found to be associated with MDD, with patients
showing volumetric reductions in hippocampal size compared to healthy controls
(HC)4-8.
The COMTval158met
polymorphism produces a single nucleotide polymorphism (SNP)-rs4680- at codon
158, from G to A, resulting in a methionine (Met) amino acid instead of a
valine (Val) amino acid. Previous studies on
healthy controls have found that Val/Val homozygous COMT genotype has been
associated with decreased hippocampal and amygdala volumes in brain scans9. Therefore, we hypothesize that the COMT Val allele individuals with MDD
will have the greatest volumetric reductions in the hippocampus and amygdala
compared to COMT Met allele subjects.
Methods
Data used in this project were anonymized and previously
acquired in an IRB approved study. 60 subjects met the DSM-IV criteria for MDD
(37 females, 23 males) and 25 healthy controls (12 females, 13 males) were
included in this analysis. The acquisition of magnetic resonance imaging (MRI)
was performed as previously stated10. Volumetric analysis was performed using Freesurfer 5.3. The
hippocampus and amygdala were chosen because of prior referencing of their role
in depression and their volumetric differences in healthy Val/Val subjects. DNA was extracted from lymphocytes and epithelial cells of
the cheek using either a Puregene Kit or BuccalAmp DNA Extraction Kit11. The polymerase chain reaction-restriction fragment length
(PCR-RFLP) was used to identify the COMT genotype. Although MDD patients and controls differed
in terms of age, both linear regression and matched samples were used. The data
analysis was performed on SPSS for Windows, Version 23 (SPSS Inc., Chicago, IL,
USA).Results
Due to the
intrinsic limitations of the data set, there is an age difference between MDD
patient and healthy control groups, (Healthy Control=33.6, MDD = 40.3, p-value=
0.031). There were three genotypes: homozygous Val (GG; n= 32), homozygous Met
(AA; n=10) and heterozygous Met/Val (AG; n=43). No significant differences in
genotype frequencies were identified between the MDD patients and the healthy
control group (χ2=0.06, df=2, p=0.970). Of the three genotypes, they
were subsequently paired as Met allele (Met/Met & Val/Met) (A; n=53) and
Val allele (Val/Val) (G; n =32).
Between the 25 HCs
and 60 MDD subjects we found no significant difference in volumes between MDD
and HC. We found a significant difference between the interaction of diagnosis
and genotype in the right hippocampal volume (p=0.015). No significant
difference was found for either the amygdala (p=0.558) or the entire hippocampus
(p=0.059). Figure 1 shows the mean volume of the left, right and entire
hippocampus between subject diagnosis and combined genotype. Table 2 below
shows that the mean volume of the right hippocampus of HC.Discussion
In our Met dominant model, our data showed
that HC Val genotype subjects had lower hippocampal volumes compared to HC Met
genotype, which agrees with previous studies9. We did not found significant
difference in means between the interaction of diagnosis and paired genotypes
in either the amygdala (p=0.558) or the hippocampus (p=0.059). Although not
significant, Val genotype subjects with MDD, whom we hypothesized to have the
lowest mean hippocampal volumes across all groups, had the highest hippocampal
volume. Although no significance was found in entire hippocampal volume, we did
find significance in right hippocampal volume. We can clearly see in Figure
1a-b that the right hippocampal volumes of MDD patients differ depending on the
certain polymorphism that they have; where HC Val dominant genotypes have
smaller right hippocampal volumes compared to MDD counterparts, but HC Met
dominant genotypes have larger right hippocampal volumes than their MDD
counterparts. While some studies have found a statistically significant
volumetric difference within the hippocampus of depressed patients12, there are others that see no
difference in hippocampal volumes in adults13. Our study suggest that it is important
for researchers to take COMT polymorphism into account when measuring
volumetric differences in hippocampal volumes since our data suggests that
results may vary due to genetic variables such as COMT polymorphism. Conclusion
This study has provided insight to a possible association between the
COMT val158met polymorphism and volumetric difference in major depressive
disorder patients. Our data suggests that there is a significant difference
between the interaction of the COMT val158met
polymorphism and diagnosis when studying hippocampal volumes in MDD.Acknowledgements
No acknowledgement found.References
1. R. C. Kessler, P. Berglund, O. Demler,
R. Jin, K. R. Merikangas and E. E. Walters, Archives of general psychiatry 62 (6), 593-602 (2005).
2. W. H.
Organization, World Mental Health Day 10
(2012).
3. M. ten
Have, F. Lamers, K. Wardenaar, A. Beekman, P. de Jonge, S. van Dorsselaer, M.
Tuithof, M. Kleinjan and R. de Graaf, Journal of affective disorders 190, 395-406 (2016).
4. F. P.
MacMaster and V. Kusumakar, BMC medicine 2
(1), 2 (2004).
5. Y. I.
Sheline, Biological psychiatry 48
(8), 791-800 (2000).
6. J.
Cole, A. W. Toga, C. Hojatkashani, P. Thompson, S. G. Costafreda, A. J. Cleare,
S. C. Williams, E. T. Bullmore, J. L. Scott and M. T. Mitterschiffthaler,
Journal of affective disorders 126
(1-2), 272-277 (2010).
7. C.
Eker and A. S. Gonul, (Taylor &
Francis, 2010).
8. G. M.
MacQueen, K. Yucel, V. H. Taylor, K. Macdonald and R. Joffe, Biological
psychiatry 64 (10), 880-883 (2008).
9. W. D.
Taylor, S. Züchner, M. E. Payne, D. F. Messer, T. J. Doty, J. R. MacFall, J. L.
Beyer and K. R. R. Krishnan, Psychiatry Research: Neuroimaging 155 (2), 173-177 (2007).
10. R. V.
Parsey, R. T. Ogden, J. M. Miller, A. Tin, N. Hesselgrave, E. Goldstein, A.
Mikhno, M. Milak, F. Zanderigo and G. M. Sullivan, Biological psychiatry 68 (2), 170-178 (2010).
11. H. A.
Erlich, PCR technology. (Springer,
1989).
12. J. D.
Bremner, M. Narayan, E. R. Anderson, L. H. Staib, H. L. Miller and D. S.
Charney, American Journal of Psychiatry 157
(1), 115-118 (2000).
13. R. S. Hastings, R. V. Parsey, M. A.
Oquendo, V. Arango and J. J. Mann, Neuropsychopharmacology 29 (5), 952 (2004).