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\begin{document}

\title{tiRNA-Gly-GCC-001 in major depressive disorder: Promising diagnostic and
therapeutic biomarker}



\author[1]{Hiahua Tian}%
\author[1]{Shugui Gao}%
\author[1]{Miaomiao Xu}%
\author[1]{Mei Yang}%
\author[1]{Mengyuan Shen}%
\author[1]{Jimeng Liu}%
\author[1]{Guang Xue}%
\author[1]{Dingding Zhuang}%
\author[1]{Zhenyu Hu}%
\author[1]{chuang wang}%
\affil[1]{Ningbo University}%


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  \date{May 16, 2024}


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\begin{abstract}
Background and Purpose: In major depressive disorder (MDD), exploration
of biomarkers will be helpful in diagnosing the disorder as well as in
choosing a treatment, and predicting the treatment response. Currently,
tRNA-derived small ribonucleic acids (tsRNAs) have been established as
promising non-invasive biomarker candidates that may enable a more
reliable diagnosis or monitoring of various diseases. Herein, we aimed
to explore tsRNA expression together with functional activities in MDD
development. Experimental Approach: Serum samples were obtained from
patients with MDD and healthy controls, and small RNA sequencing
(RNA-Seq) was used to profile tsRNA expression. Dysregulated tsRNAs in
MDD were validated by quantitative real-time polymerase chain reaction
(qRT-PCR). The diagnostic utility of specific tsRNAs and the expression
of these tsRNAs after antidepressant treatment was analyzed. Key
Results: In total, 38 tsRNAs were significantly differentially expressed
in MDD samples relative to healthy individuals (34 upregulated and 4
downregulated). qRT-PCR was used to validate the expression of six
tsRNAs that were upregulated in MDD (tiRNA-1:20-chrM. Ser-GCT,
tiRNA-1:33-Gly-GCC-1, tRF-1:22-chrM.Ser-GCT, tRF-1:31-Ala-AGC-4-M6,
tRF-1:31-Pro-TGG-2, and tRF-1:32-chrM. Gln-TTG). Interestingly, serum
tiRNA-Gly-GCC-001 levels exhibited an area under the ROC curve of 0.844.
Moreover, tiRNA-Gly-GCC-001 is predicted to suppress brain-derived
neurotrophic factor (BDNF) expression. Furthermore, significant
tiRNA-Gly-GCC-001 downregulation was evident following an eight-week
treatment course and served as a promising baseline predictor of patient
response to antidepressant therapy. Conclusion and Implications: Our
current work firstly found that tiRNA-Gly-GCC-001 is a promising MDD
biomarker candidate that can predict patient responses to antidepressant
therapy.%
\end{abstract}%



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