Mapping the Spatial Distribution of Neurotransmission Markers using Postmortem Cohorts

Miguel da Mata Moreira

Key information

Authors:

Miguel da Mata Moreira (Miguel da Mata Moreira)

Supervisors:

Rui Miguel Carrasqueiro Henriques (Rui Miguel Carrasqueiro Henriques); Guilherme Henrique Caçador Ramos (Guilherme Henrique Caçador Ramos)

Published in

November 7, 2024

Abstract

Mapping the spatial distribution of transcriptomic neuromarkers involves identifying differential regulatory activity in specific human brain tissues, highlighting tissue-specific transcriptomic signatures in homeostatic states or misregulated in disease. In this work, we primarily focus on protein-coding genes with important roles in neurotransmission systems, such as receptor-coding genes of the dopaminergic system. In this context, we are interested not only in studying how gene expression varies across tissues and individuals but also in capturing covariate effects, including those driven by demographic factors and varying agonal states. To accomplish this, we introduce a statistical framework to assess pairwise and multiwise differential expression by comparing brain-to-brain tissues, brain-to-peripheral tissues, and brain tissues under different conditions. Furthermore, we also propose an approach for pattern discovery in gene expression data using biclustering and triclustering algorithms for two-way and three-way data, respectively. Both approaches are used to retrieve tissue-specific and cross-tissue putative regulatory modules (patterns) with guarantees of statistical significance. As major outcomes, this thesis provides a tool for a parameterizable discovery of transcriptomic markers associated with specific neurotransmission systems and visual maps to guide the exploration of both individual and modular markers. The acquired results, validated against available knowledge using well-established biological networks and knowledge bases, confirm the relevance of the proposed tool. Particular attention is drawn to novel putative associations for the acquisition of actionable knowledge.