Dataset Information

Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants.

ABSTRACT: Rare neurovascular diseases (RNVDs) have not been well-recognized in Korea. They involve the central nervous system and greatly affect the patients' lives. However, these diseases are difficult to diagnose and treat due to their rarity and incurability. We established a list of RNVDs by referring to the previous literature and databases worldwide to better understand the diseases and their current management status. We categorized 68 RNVDs based on their pathophysiology and clinical manifestations and estimated the prevalence of each disease in Korea. Recent advances in genetic, molecular, and developmental research have enabled further understanding of these RNVDs. Herein, we review each disease, while considering its classification based on updated pathologic mechanisms, and discuss the management status of RNVD in Korea.

SUBMITTER: Song Y

PROVIDER: S-EPMC8316781 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants.

Song Yunsun Y Kwon Boseong B Al-Abdulwahhab Abdulrahman Hamed AH Nam Yeo Kyoung YK Ahn Yura Y Jeong So Yeong SY Seo Eul Ju EJ Lee Jong Keuk JK Suh Dae Chul DC

Korean journal of radiology 20210520 8

Rare neurovascular diseases (RNVDs) have not been well-recognized in Korea. They involve the central nervous system and greatly affect the patients' lives. However, these diseases are difficult to diagnose and treat due to their rarity and incurability. We established a list of RNVDs by referring to the previous literature and databases worldwide to better understand the diseases and their current management status. We categorized 68 RNVDs based on their pathophysiology and clinical manifestatio ...[more]

PMID: 34047503

Similar Datasets

Project description:ObjectivesIdentifying drivers of complex traits from the noisy signals of genetic variation obtained from high-throughput genome sequencing technologies is a central challenge faced by human geneticists today. We hypothesize that the variants involved in complex diseases are likely to exhibit non-neutral evolutionary signatures. Uncovering the evolutionary history of all variants is therefore of intrinsic interest for complex disease research. However, doing so necessitates the simultaneous elucidation of the targets of natural selection and population-specific demographic history.MethodsHere we characterize the action of natural selection operating across complex disease categories, and use population genetic simulations to evaluate the expected patterns of genetic variation in large samples. We focus on populations that have experienced historical bottlenecks followed by explosive growth (consistent with many human populations), and describe the differences between evolutionarily deleterious mutations and those that are neutral.ResultsGenes associated with several complex disease categories exhibit stronger signatures of purifying selection than non-disease genes. In addition, loci identified through genome-wide association studies of complex traits also exhibit signatures consistent with being in regions recurrently targeted by purifying selection. Through simulations, we show that population bottlenecks and rapid growth enable deleterious rare variants to persist at low frequencies just as long as neutral variants, but low-frequency and common variants tend to be much younger than neutral variants. This has resulted in a large proportion of modern-day rare alleles that have a deleterious effect on function and that potentially contribute to disease susceptibility.ConclusionsThe key question for sequencing-based association studies of complex traits is how to distinguish between deleterious and benign genetic variation. We used population genetic simulations to uncover patterns of genetic variation that distinguish these two categories, especially derived allele age, thereby providing inroads into novel methods for characterizing rare genetic variation driving complex diseases.

Dataset Information

Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants.

Publications

Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets