Identify Unique Subtypes in Recurrent Major Depression Disorder Restricted; Files Only

Abstract

Major Depressive Disorder (MDD) is a multifaceted mental health condition with varying

symptomatology and treatment responses among individuals. This study aims to elucidate the

heterogeneity within MDD by identifying distinct subcategories characterized by symptom

severity and treatment resistance. Leveraging data from 922 patients, we employed

hierarchical clustering to reveal significant differences in anxiety and depression symptoms,

as identified through the PHQ-9 and GAD-7 questionnaires. Furthermore, the application of

Hadamard Autoencoders facilitated the imputation of missing data and feature extraction,

highlighting the importance of specific questionnaire items in distinguishing between MDD

subtypes. Our findings suggest the existence of a severe MDD subtype, potentially analogous

to Treatment-Resistant Depression (TRD), exhibiting pronounced anxiety and depression

symptoms and differential responses to conventional treatments. The identification of these

subcategories underscores the need for personalized treatment approaches in MDD

management. Future research should integrate treatment response data to further refine MDD

subtyping and enhance therapeutic strategies. 

Table of Contents

1.Introduction .......................................... 1

2.Method ........................................ 2

Data Acquisition and Utilization ........................................ 2

Alignment and quantification of RNA-seq reads ........................................ 3

Cell type deconvolution and validation ........................................ 4

Exon read counts ........................................ 4

Missing value imputation and dimensionality reduction ........................................ 4

Statistical analysis ........................................ 6

Feature Ranking ........................................ 6

3.Results ................................................ 7

Cluster analysis for female patients ................................................ 10

Cluster analysis for male patients ................................................ 13

Overall cluster analysis ................................................ 15

4.Discussion .......................................... 17

5.References .......................................... 19

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Biology, Cell Biology, Bioinformatics Biology, Genetics
Stichwort	Major Depression Disorder Immune Cell Components Data Mining
Committee Chair / Thesis Advisor	Qin, Steve, Emory University
Committee Members	Hu, Yijuan, Emory University

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