Manesh Gopaldas1, Francesca Zanderigo2, Serena Zhan3, R Todd Ogden4, Jeffrey M Miller2, Harry Rubin-Falcone2, Thomas B Cooper5, Maria A Oquendo6, Gregory Sullivan7, J John Mann8, M Elizabeth Sublette9. 1. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States. 2. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States. 3. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States. 4. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States; Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States. 5. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States. 6. Psychiatry Department, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States. 7. Tonix Pharmaceuticals Holding Corp, New York, NY, United States. 8. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States; Department of Radiology, Columbia University, New York, NY, United States. 9. Department of Psychiatry, Columbia University, New York, NY, United States; Molecular Imaging and Neuropathology Area, New York State Psychiatric Institute, New York, NY, United States. Electronic address: elizabeth.sublette@nyspi.columbia.edu.
Abstract
BACKGROUND: Serotonin transporter (5-HTT) binding and polyunsaturated fatty acids (PUFAs) are implicated in major depressive disorder (MDD). Links between the two systems in animal models have not been investigated in humans. METHODS: Using positron emission tomography (PET) and [11C]DASB, we studied relationships between 5-HTT binding potential and plasma levels of PUFAs docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and arachidonic acid (AA) in medication-free MDD patients (n = 21). PUFAs were quantified using transesterification and gas chromatography. Binding potential BPP, and alternative outcome measures BPF and BPND, were determined for [11C]DASB in six a priori brain regions of interest (ROIs) using likelihood estimation in graphical analysis (LEGA) to calculate radioligand total distribution volume (VT), and a validated hybrid deconvolution approach (HYDECA) that estimates radioligand non-displaceable distribution volume (VND) without a reference region. Linear mixed models used PUFA levels as predictors and binding potential measures as outcomes across the specified ROIs; age and sex as fixed effects; and subject as random effect to account for across-region binding correlations. As nonlinear relationships were observed, a quadratic term was added to final models. RESULTS: AA predicted both 5-HTT BPP and depression severity nonlinearly, described by an inverted U-shaped curve. 5-HTT binding potential mediated the relationship between AA and depression severity. LIMITATIONS: Given the small sample and multiple comparisons, results require replication. CONCLUSIONS: Our findings suggest that AA status may impact depression pathophysiology through effects on serotonin transport. Future studies should examine whether these relationships explain therapeutic effects of PUFAs in the treatment of MDD.
BACKGROUND:Serotonin transporter (5-HTT) binding and polyunsaturated fatty acids (PUFAs) are implicated in major depressive disorder (MDD). Links between the two systems in animal models have not been investigated in humans. METHODS: Using positron emission tomography (PET) and [11C]DASB, we studied relationships between 5-HTT binding potential and plasma levels of PUFAsdocosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and arachidonic acid (AA) in medication-free MDDpatients (n = 21). PUFAs were quantified using transesterification and gas chromatography. Binding potential BPP, and alternative outcome measures BPF and BPND, were determined for [11C]DASB in six a priori brain regions of interest (ROIs) using likelihood estimation in graphical analysis (LEGA) to calculate radioligand total distribution volume (VT), and a validated hybrid deconvolution approach (HYDECA) that estimates radioligand non-displaceable distribution volume (VND) without a reference region. Linear mixed models used PUFA levels as predictors and binding potential measures as outcomes across the specified ROIs; age and sex as fixed effects; and subject as random effect to account for across-region binding correlations. As nonlinear relationships were observed, a quadratic term was added to final models. RESULTS: AA predicted both 5-HTT BPP and depression severity nonlinearly, described by an inverted U-shaped curve. 5-HTT binding potential mediated the relationship between AA and depression severity. LIMITATIONS: Given the small sample and multiple comparisons, results require replication. CONCLUSIONS: Our findings suggest that AA status may impact depression pathophysiology through effects on serotonin transport. Future studies should examine whether these relationships explain therapeutic effects of PUFAs in the treatment of MDD.
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