Neurological disease genetics platform integrating genetic and clinical data
We study various aspects of neurogenetic disorders and develop systematical approaches to help the diagnosis. Neurogenetic disorders are a group of genetic diseases that affect the functioning of the nervous system. These disorders often arise from genetic mutations that cause alterations in the structure and function of neurons, the cells that transmit signals within the nervous system. These mutations may occur in genes that encode for proteins involved in the development, maintenance, and function of neurons. Neurogenetic disorders can manifest in a wide range of symptoms, including cognitive impairment, movement disorders, sensory disturbances, and psychiatric symptoms.
Diagnosis of neurogenetic disorders
The diagnosis of neurogenetic disorders typically involves several steps. The first step is to obtain a detailed medical history of the patient and their family, including any symptoms or medical conditions that may indicate a genetic disorder. This is followed by a physical examination to identify any clinical signs that may suggest a neurological disorder. The next step is genetic testing, which involves analyzing the DNA of the patient to identify any mutations or variations in genes that are associated with neurogenetic disorders. In some cases, additional tests such as brain imaging may be required to confirm the diagnosis or assess the extent of the disorder.
Aim of our project
During the diagnosis, large information sources must be utilized with systematical evaluations to assess the patient’s clinical phenotypes and genetic variations in comparison with that of the previously reported diseases. The aim of our project is to systematically automate large portion of such diagnosis processes, by analyzing and prioritizing candidate causal variants, systematically evaluating the similarities of patient’s phenotypes with that of known diseases, and finally suggesting likely disease candidates.
PREDICT (Prioritizing rare genetic disorders with combination of genotype and phenotypes) is a web-based software tool that predicts prioritized candidate diseases based on the patient’s genotype and phenotype information. A VCF file with germline DNA variations of the patient and HPO-based phenotypes are used as input. Prioritized list of candidate diseases with possible causal genes are given as output.
This data set consists of the VCF files that include the genetic variants of 249 Korean neurodevelopmental disorder patients. Detailed information about this data can be found from the following article.
(Frontiers in Genetic 2022 paper)
Soojin Park, Se Song Jang, Seungbok Lee , Minsoo Kim , Hyungtai Sim , Hyeongseok Jeon , Sung Eun Hong , Jean Lee , Jeongeun Lee , Eun Young Jeon , Jeongha Lee , Cho-Rong Lee , Soo Yeon Kim , Man Jin Kim, Jihoon G. Yoon , Byung Chan Lim , Woo Joong Kim , Ki Joong Kim , Jung Min Ko , Anna Cho , Jin Sook Lee , Murim Choi, Jong-Hee Chae "Systematic analysis of inheritance pattern determination in genes that cause rare neurodevelopmental diseases" Frontiers in Genetics, 2022
Neurological rare diseases are caused by pathological genes that affect the nervous system and cause clinical symptoms. To better understand and diagnose these diseases, researchers have studied neuroimaging endophenotypes, which are quantitative biological traits that reflect the function of a specific biological system and are heritable. In particular, studies have focused on using MRI to identify abnormal features that may be associated with these diseases. The researchers analyzed MRI data from 150 patients with neurological rare diseases, extracting quantitative features such as brain tissue volume, T2 hyperintensity, and myelination index, which can help diagnose and treat these diseases more accurately.