TY  - GEN
N2  - Despite their devastating impacts on millions of people, most rare and congenital disorders remain poorly understood, leaving the patients with these disorders with no FDA-approved treatment.  To inform the development of treatments for these diseases, it is crucial that we understand their root cause.  Therefore, we propose the development of two novel computational pipelines to discover the cellular etiology of diseases.  Based on the well-supported observation that disorders with a shared phenotype arise from overlapping molecular processes, we hypothesize that these processes are, in many cases, localized to a small set of cell types at specific developmental stages.  For our first aim, we will design a novel computational pipeline to discover the cell types whose disrupted intrinsic processes putatively cause a specific phenotype of interest.  Our second aim will be devoted to the development of the first computational pipeline for uncovering the pairs of cell types whose disrupted communication initiates the phenotype.  In addition, our pipelines will be the first to offer insight into the putative developmental stages at which these cell types are impacted.

A major challenge in studying rare and congenital disorders is the difficulty in collecting disease-specific data.  Our focus on shared phenotypes of disorders will eliminate any dependence on knowing the mutated gene for any one disorder, and our pipelines will be designed to use single-cell gene expression data from healthy tissues, eliminating the need to collect samples directly from patients.  Our project will provide the research community with a dedicated tool for uncovering the cellular etiology of diseases based on their shared molecular processes.
DO  - 10.6083/bpxhc41312
DO  - doi
AB  - Despite their devastating impacts on millions of people, most rare and congenital disorders remain poorly understood, leaving the patients with these disorders with no FDA-approved treatment.  To inform the development of treatments for these diseases, it is crucial that we understand their root cause.  Therefore, we propose the development of two novel computational pipelines to discover the cellular etiology of diseases.  Based on the well-supported observation that disorders with a shared phenotype arise from overlapping molecular processes, we hypothesize that these processes are, in many cases, localized to a small set of cell types at specific developmental stages.  For our first aim, we will design a novel computational pipeline to discover the cell types whose disrupted intrinsic processes putatively cause a specific phenotype of interest.  Our second aim will be devoted to the development of the first computational pipeline for uncovering the pairs of cell types whose disrupted communication initiates the phenotype.  In addition, our pipelines will be the first to offer insight into the putative developmental stages at which these cell types are impacted.

A major challenge in studying rare and congenital disorders is the difficulty in collecting disease-specific data.  Our focus on shared phenotypes of disorders will eliminate any dependence on knowing the mutated gene for any one disorder, and our pipelines will be designed to use single-cell gene expression data from healthy tissues, eliminating the need to collect samples directly from patients.  Our project will provide the research community with a dedicated tool for uncovering the cellular etiology of diseases based on their shared molecular processes.
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
AD  - Oregon Health and Science University
T1  - A novel computational framework for inferring the developmental and cellular origins of rare and congenital disorders using scRNA-seq data
DA  - 2023-07-20
AU  - Sullivan, Jennifer
AU  - Adey, Andrew
AU  - Schweitzer, Ronen
AU  - McWeeney, Shannon
L1  - https://digitalcollections.ohsu.edu/record/41312/files/ResearchWeek.2023.Sullivan.Jennifer.pdf
PB  - Oregon Health and Science University
LA  - eng
PY  - 2023-07-20
ID  - 41312
L4  - https://digitalcollections.ohsu.edu/record/41312/files/ResearchWeek.2023.Sullivan.Jennifer.pdf
KW  - Systems Biology
KW  - Rare Diseases
KW  - Developmental Biology
KW  - Single-Cell Gene Expression Analysis
KW  - Genomics
KW  - Mutation
KW  - scrna-seq
KW  - congenital disorders
KW  - fetal anomalies
KW  - orphan disease
KW  - data pipeline
KW  - rare disorders
TI  - A novel computational framework for inferring the developmental and cellular origins of rare and congenital disorders using scRNA-seq data
Y1  - 2023-07-20
L2  - https://digitalcollections.ohsu.edu/record/41312/files/ResearchWeek.2023.Sullivan.Jennifer.pdf
LK  - https://digitalcollections.ohsu.edu/record/41312/files/ResearchWeek.2023.Sullivan.Jennifer.pdf
UR  - https://digitalcollections.ohsu.edu/record/41312/files/ResearchWeek.2023.Sullivan.Jennifer.pdf
ER  -