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Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence
by
Taylor, Bright A
, Naviaux, Robert K
, Monk, Jonathan M
, Li, Kefeng
, Schene, Aart H
, Ruhé, Henricus G
, Wang, Lin
, Figueroa, Caroline A
, Assies Johanna
, Mocking Roel J T
, Naviaux, Jane C
in
Mental depression
/ Metabolism
/ Metabolites
/ Remission (Medicine)
2021
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Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence
by
Taylor, Bright A
, Naviaux, Robert K
, Monk, Jonathan M
, Li, Kefeng
, Schene, Aart H
, Ruhé, Henricus G
, Wang, Lin
, Figueroa, Caroline A
, Assies Johanna
, Mocking Roel J T
, Naviaux, Jane C
in
Mental depression
/ Metabolism
/ Metabolites
/ Remission (Medicine)
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence
by
Taylor, Bright A
, Naviaux, Robert K
, Monk, Jonathan M
, Li, Kefeng
, Schene, Aart H
, Ruhé, Henricus G
, Wang, Lin
, Figueroa, Caroline A
, Assies Johanna
, Mocking Roel J T
, Naviaux, Jane C
in
Mental depression
/ Metabolism
/ Metabolites
/ Remission (Medicine)
2021
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Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence
Journal Article
Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence
2021
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Overview
Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. This was a prospective pilot study to examine the potential diagnostic and prognostic value of targeted plasma metabolomics in the care of patients with rMDD in remission. We used an established LC-MS/MS platform to measure 399 metabolites in 68 subjects with rMDD (n = 45 females and 23 males) in antidepressant-free remission and 59 age- and sex-matched controls (n = 40 females and 19 males). Patients were then followed prospectively for 2.5 years. Metabolomics explained up to 43% of the phenotypic variance. The strongest biomarkers were gender specific. 80% of the metabolic predictors of recurrence in both males and females belonged to 6 pathways: (1) phospholipids, (2) sphingomyelins, (3) glycosphingolipids, (4) eicosanoids, (5) microbiome, and (6) purines. These changes traced to altered mitochondrial regulation of cellular redox, signaling, energy, and lipid metabolism. Metabolomics identified a chemical endophenotype that could be used to stratify rrMDD patients at greatest risk for recurrence with an accuracy over 0.90 (95%CI = 0.69–1.0). Power calculations suggest that a validation study of at least 198 females and 198 males (99 cases and 99 controls each) will be needed to confirm these results. Although a small study, these results are the first to show the potential utility of metabolomics in assisting with the important clinical challenge of prospectively identifying the patients at greatest risk of recurrence of a depressive episode and those who are at lower risk.
Publisher
Nature Publishing Group
Subject
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