TY - JOUR
T1 - Beyond GWAS
T2 - from simple associations to functional insights
AU - Ishigaki, Kazuyoshi
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/1
Y1 - 2022/1
N2 - Each human, when born, has slightly different DNA sequences, which make each of us unique. The variations in DNA sequences are called genetic variants. The primary aim of genome-wide association study (GWAS) is to detect associations between genetic variants and human phenotypes. Since GWAS focuses on germ-line variants, there is no reverse causation. Therefore, GWAS is one of the few tools that can assess the causality of human diseases. In the past 10 years, many large-scale GWAS have been conducted. Although the primary outputs of GWAS are just a series of statistics, its downstream analyses provided many insights beyond simple associations: the causal mechanisms for autoimmune diseases and shared etiology between diseases. Moreover, GWAS downstream analyses generated scores potentially helpful in predicting clinical outcomes of each patient. This review focuses on GWAS for autoimmune diseases and introduces significant achievements of its downstream analyses. We also provide future directions that potentially overcome current limitations. We restrict our discussion to common autoimmune diseases (e.g., rheumatoid arthritis) since rare Mendelian diseases possess distinct genetic etiologies and are not tested by GWAS.
AB - Each human, when born, has slightly different DNA sequences, which make each of us unique. The variations in DNA sequences are called genetic variants. The primary aim of genome-wide association study (GWAS) is to detect associations between genetic variants and human phenotypes. Since GWAS focuses on germ-line variants, there is no reverse causation. Therefore, GWAS is one of the few tools that can assess the causality of human diseases. In the past 10 years, many large-scale GWAS have been conducted. Although the primary outputs of GWAS are just a series of statistics, its downstream analyses provided many insights beyond simple associations: the causal mechanisms for autoimmune diseases and shared etiology between diseases. Moreover, GWAS downstream analyses generated scores potentially helpful in predicting clinical outcomes of each patient. This review focuses on GWAS for autoimmune diseases and introduces significant achievements of its downstream analyses. We also provide future directions that potentially overcome current limitations. We restrict our discussion to common autoimmune diseases (e.g., rheumatoid arthritis) since rare Mendelian diseases possess distinct genetic etiologies and are not tested by GWAS.
KW - Causal variants
KW - Expression quantitative trait locus (eQTL)
KW - Fine-mapping
KW - Genome-wide association study (GWAS)
KW - Polygenic risk score (PRS)
UR - http://www.scopus.com/inward/record.url?scp=85116273870&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85116273870&partnerID=8YFLogxK
U2 - 10.1007/s00281-021-00894-5
DO - 10.1007/s00281-021-00894-5
M3 - Review article
C2 - 34605948
AN - SCOPUS:85116273870
SN - 1863-2297
VL - 44
SP - 3
EP - 14
JO - Seminars in Immunopathology
JF - Seminars in Immunopathology
IS - 1
ER -