Cortical Deficit Pattern Biomarkers for MDD are Linked to Lower CBF in a Regionally Specific Pattern
Poster No:
441
Submission Type:
Abstract Submission
Authors:
Bhim Adhikari1, David Keator2, Daniel Amen3, Si Gao1, Paul Thompson4, Danny Wang5, Braxton Mitchell6, Jessica Turner7, Theo van Erp8, Neda Jahanshad9, Yizhou Ma1, Xiaoming Du1, William Burroughs1, Shuo Chen6, Tianzhou Ma10, Jair Soares1, L. Elliot Hong1, Peter Kochunov1
Institutions:
1UT Health Science Center at Houston, Houston, TX, 2Amen Clinics Inc., Costa Mesa, CA, 3Change Your Brain Change Your Life Foundation, Costa Mesa, CA, 4University of Southern California, Los Angeles, CA, 5University of Souther California, Los Angeles, CA, 6University of Maryland School of Medicine, Baltimore, MD, 7Wexner Medical Center, The Ohio State University, Columbus, OH, 8University of California, Irvine,, Irvine, CA, 9University of Southern California,, Marina del Rey, CA, 10University of Maryland at College Park, College Park, MD
First Author:
Co-Author(s):
Introduction:
Major depressive disorder (MDD) is a severe mental illness characterized by functional rather than structural brain abnormalities. The pattern of regional homogeneity (ReHo) deficits in MDD may relate to underlying regional hypoperfusion. Capturing this deficit pattern provides a brain pattern-based biomarker for MDD that is linked to the underlying pathophysiology. As ReHo values were linked to regional cerebral blood flow (rCBF) in healthy people (Adhikari et al., 2022), we hypothesized that the regional ReHo effects in MDD may serve as a proxy for rCBF deficit in MDD.
Methods:
We examined whether cortical ReHo patterns provide a replicable biomarker for MDD that is more sensitive than reduced cortical thickness. The second goal was to evaluate whether ReHo MDD deficit pattern reflects rCBF deficit patterns in MDD, and whether a regional vulnerability index (RVI) thus constructed may provide a concise brain pattern-based biomarker for MDD. N=2,220 recurrent MDD and N=2,590 controls with ReHo and structural measurements were included from UK Biobank. N=2,148 MDD patients and N=7,957 controls were included for measuring the MDD structural cortical deficit pattern from the ENIGMA Consortium. The UKBB ReHo and ENIGMA cortical thickness effect sizes for MDD were used to test the deficit patterns in N=68 patients with a lifetime diagnosis of MDD and N=136 controls from Amish Connectome Project (ACP) with ReHo, structural, and rCBF data. Finally, N=296 patients with MDD and N=76 controls in Amen Clinic Inc had rCBF data measured using single photon emission computed tomography.
The resting state analysis workflow developed by the ENIGMA consortium was used to process the rsfMRI data; processing steps have been detailed in prior publications (Adhikari et al. 2018a, 2018b). The processed data was then used for ReHo map calculations using '3dReHo' command. CBF perfusion was estimated by using a standard single compartment ASL model, partial volume effects correction was performed with a spatially regularized method (Chappell et al., 2011). Structural T1-weighted MRI scans collected by ENIGMA, UKBB and ACP were analyzed using the ENIGMA harmonized analysis and quality-control protocol and SPECT data from ACI using a standardized processing pipeline. Regional values were extracted using cortical gray matter regions based on the Desikan–Killiany atlas. All statistical analyses were performed in RStudio v4.1.1 (RStudioTeam, 2020)).
The resting state analysis workflow developed by the ENIGMA consortium was used to process the rsfMRI data; processing steps have been detailed in prior publications (Adhikari et al. 2018a, 2018b). The processed data was then used for ReHo map calculations using '3dReHo' command. CBF perfusion was estimated by using a standard single compartment ASL model, partial volume effects correction was performed with a spatially regularized method (Chappell et al., 2011). Structural T1-weighted MRI scans collected by ENIGMA, UKBB and ACP were analyzed using the ENIGMA harmonized analysis and quality-control protocol and SPECT data from ACI using a standardized processing pipeline. Regional values were extracted using cortical gray matter regions based on the Desikan–Killiany atlas. All statistical analyses were performed in RStudio v4.1.1 (RStudioTeam, 2020)).
Results:
MDD participants had lower cortical ReHo in the cingulum, superior temporal, frontal and several other regions, with no detectable significant differences in cortical thickness. The regional pattern of ReHo MDD effect sizes were significantly correlated with that of rCBF obtained from the independent datasets (corr. coefficient: r=0.52 and 0.46, p<10-4) (Figure1). ReHo and rCBF functional RVIs showed numerically stronger effect sizes (Cohen's d=0.33-0.90) compared to structural RVIs (d=0.09-0.20). Elevated RVI-MDD values in MDD participants were associated with higher depression symptom severity in all three cohorts.
·Regional effect sizes maps based on ReHo and CBF.
Conclusions:
We examined the pattern of the ReHo deficits in individuals with MDD and report three novel
findings: A) the regional effect sizes (ESs) for ReHo in participants with MDD vs controls were replicable across independent cohorts and were stronger than those for cortical thickness, B) the regional pattern of lower ReHo signal agreed with the regional pattern of lower rCBF and this finding was consistent regardless of the methodological approach to measure rCBF; and C) the
functional RVI for MDD that used ReHo deficit patterns showed stronger ESs than any structural
RVI measurements and was significantly correlated with the severity of depression symptoms
across samples. We interpret these findings as evidence for a reproducible pattern of regional
hypoperfusion in MDD, suggested previously (Mayberg, 2001; Mayberg et al., 1994, 1997)
and that this pattern can be captured from widely available resting fMRI data.
findings: A) the regional effect sizes (ESs) for ReHo in participants with MDD vs controls were replicable across independent cohorts and were stronger than those for cortical thickness, B) the regional pattern of lower ReHo signal agreed with the regional pattern of lower rCBF and this finding was consistent regardless of the methodological approach to measure rCBF; and C) the
functional RVI for MDD that used ReHo deficit patterns showed stronger ESs than any structural
RVI measurements and was significantly correlated with the severity of depression symptoms
across samples. We interpret these findings as evidence for a reproducible pattern of regional
hypoperfusion in MDD, suggested previously (Mayberg, 2001; Mayberg et al., 1994, 1997)
and that this pattern can be captured from widely available resting fMRI data.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 2
Keywords:
Cerebral Blood Flow
Other - Major depressive disorder; Regional homogeneity
1|2Indicates the priority used for review
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5. RStudioTeam. (2020). RStudio: Integrated Development for R.
6. Mayberg, H. (2001). Depression and frontal-subcortical circuits: Focus on prefrontallimbic interactions. Frontal-subcortical circuits in psychiatric and neurological disorders., 1,1.
7. Mayberg HS, et al. (1994). Paralimbic hypoperfusion in unipolar depression. Journal of nuclear medicine, 35(6):929-34.