Downregulated transferrin receptor in the blood predicts recurrent MDD in the elderly cohort: A fuzzy forests approach.
Background: At present, no predictive markers for Major Depressive Disorder (MDD) exist. The search for such markers has been challenging due to clinical and molecular heterogeneity of MDD, the lack of statistical power in studies and suboptimal statistical tools applied to multidimensional data. Ma...
| Publicado en: | Journal of Affective Disorders Vol. 267; pp. 42 - 49 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Apr2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=142250407&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 142250407 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01650327 3M9 jtl: Journal of Affective Disorders issn: 01650327 maglogo: N pubinfo: dt: Apr2020 vid: 267 pid: 1004 pub: Elsevier B.V. artinfo: ui: 142250407 142250407 NLM32063571 142250407 10.1016/j.jad.2020.02.001 NLM32063571 142250407 ppf: 42 ppct: 7 formats: tig: atl: Downregulated transferrin receptor in the blood predicts recurrent MDD in the elderly cohort: A fuzzy forests approach. aug: au: Ciobanu, Liliana G. Sachdev, Perminder S. Trollor, Julian N. Reppermund, Simone Thalamuthu, Anbupalam Mather, Karen A. Cohen-Woods, Sarah Stacey, David Toben, Catherine Schubert, K. Oliver Baune, Bernhard T. affil: Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, South Australia, Australia sug: subj: Depression Recurrence Aged Human Receptors, Cell Surface Validation Studies Comparative Studies Evaluation Research Multicenter Studies Aged: 65+ years ab: Background: At present, no predictive markers for Major Depressive Disorder (MDD) exist. The search for such markers has been challenging due to clinical and molecular heterogeneity of MDD, the lack of statistical power in studies and suboptimal statistical tools applied to multidimensional data. Machine learning is a powerful approach to mitigate some of these limitations.Methods: We aimed to identify the predictive markers of recurrent MDD in the elderly using peripheral whole blood from the Sydney Memory and Aging Study (SMAS) (N = 521, aged over 65) and adopting machine learning methodology on transcriptome data. Fuzzy Forests is a Random Forests-based classification algorithm that takes advantage of the co-expression network structure between genes; it allows to alleviate the problem of p >> n via reducing the dimensionality of transcriptomic feature space.Results: By adopting Fuzzy Forests on transcriptome data, we found that the downregulated TFRC (transferrin receptor) can predict recurrent MDD with an accuracy of 63%.Limitations: Although we corrected our data for several important confounders, we were not able to account for the comorbidities and medication taken, which may be numerous in the elderly and might have affected the levels of gene transcription.Conclusions: We found that downregulated TFRC is predictive of recurrent MDD, which is consistent with the previous literature, indicating the role of the innate immune system in depression. This study is the first to successfully apply Fuzzy Forests methodology on psychiatric condition, opening, therefore, a methodological avenue that can lead to clinically useful predictive markers of complex traits. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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