Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine.

ABSTRACT:

Background

A large proportion of major depressive patients will experience recurring episodes. Many patients still do not response to available antidepressants. In order to meaningfully predict who will not respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables.

Methods

Eight hundred fifty-seven patients with recurrent major depressive disorder who were followed up 3-10 years involved 32 variables including socio-demographic, clinical features, and SSRIs treatment features when they received the first treatment. Also, 34 tagSNPs related to 5-HT signaling pathway, were detected by using mass spectrometry analysis. The training samples which had 12 clinical variables and four tagSNPs with statistical differences were learned

SUBMITTER: Zhang H 

PROVIDER: S-EPMC7283444 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature