Future Directions of Genomics Research in Rheumatic Diseases

Yukinori Okada; Toshihiro Kishikawa; Saori Sakaue; Jun Hirata

doi:10.1016/j.rdc.2017.04.009

Future Directions of Genomics Research in Rheumatic Diseases

Yukinori Okada, Toshihiro Kishikawa, Saori Sakaue, Jun Hirata

Research output: Contribution to journal › Review article › peer-review

5 Scopus citations

Abstract

Recent developments in human genome genotyping and sequencing technologies, such as genome-wide association studies and whole-genome sequencing analyses, have successfully identified several risk genes of rheumatic diseases. Fine-mapping studies using the HLA imputation method revealed that classical and non-classical HLA genes contribute to the risk of rheumatic diseases. Integration of human disease genomics with biological, medical, and clinical databases should contribute to the elucidation of disease pathogenicity and novel drug discovery. Disease risk genes identified by large-scale genetic studies are considered to be promising resources for novel drug discovery, including drug repositioning and biomarker microRNA screening for rheumatoid arthritis.

Original language	English
Pages (from-to)	481-487
Number of pages	7
Journal	Rheumatic Disease Clinics of North America
Volume	43
Issue number	3
DOIs	https://doi.org/10.1016/j.rdc.2017.04.009
State	Published - Aug 2017
Externally published	Yes

Keywords

Genome-wide association study
Human genetics
Human leukocyte antigen
Next-generation sequencing
Statistical genetics

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10.1016/j.rdc.2017.04.009

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title = "Future Directions of Genomics Research in Rheumatic Diseases",

abstract = "Recent developments in human genome genotyping and sequencing technologies, such as genome-wide association studies and whole-genome sequencing analyses, have successfully identified several risk genes of rheumatic diseases. Fine-mapping studies using the HLA imputation method revealed that classical and non-classical HLA genes contribute to the risk of rheumatic diseases. Integration of human disease genomics with biological, medical, and clinical databases should contribute to the elucidation of disease pathogenicity and novel drug discovery. Disease risk genes identified by large-scale genetic studies are considered to be promising resources for novel drug discovery, including drug repositioning and biomarker microRNA screening for rheumatoid arthritis.",

keywords = "Genome-wide association study, Human genetics, Human leukocyte antigen, Next-generation sequencing, Statistical genetics",

author = "Yukinori Okada and Toshihiro Kishikawa and Saori Sakaue and Jun Hirata",

note = "Publisher Copyright: {\textcopyright} 2017 Elsevier Inc.",

year = "2017",

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AU - Kishikawa, Toshihiro

AU - Sakaue, Saori

AU - Hirata, Jun

PY - 2017/8

Y1 - 2017/8

N2 - Recent developments in human genome genotyping and sequencing technologies, such as genome-wide association studies and whole-genome sequencing analyses, have successfully identified several risk genes of rheumatic diseases. Fine-mapping studies using the HLA imputation method revealed that classical and non-classical HLA genes contribute to the risk of rheumatic diseases. Integration of human disease genomics with biological, medical, and clinical databases should contribute to the elucidation of disease pathogenicity and novel drug discovery. Disease risk genes identified by large-scale genetic studies are considered to be promising resources for novel drug discovery, including drug repositioning and biomarker microRNA screening for rheumatoid arthritis.

AB - Recent developments in human genome genotyping and sequencing technologies, such as genome-wide association studies and whole-genome sequencing analyses, have successfully identified several risk genes of rheumatic diseases. Fine-mapping studies using the HLA imputation method revealed that classical and non-classical HLA genes contribute to the risk of rheumatic diseases. Integration of human disease genomics with biological, medical, and clinical databases should contribute to the elucidation of disease pathogenicity and novel drug discovery. Disease risk genes identified by large-scale genetic studies are considered to be promising resources for novel drug discovery, including drug repositioning and biomarker microRNA screening for rheumatoid arthritis.

KW - Genome-wide association study

KW - Human genetics

KW - Human leukocyte antigen

KW - Next-generation sequencing

KW - Statistical genetics

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SN - 0889-857X

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EP - 487

JO - Rheumatic Disease Clinics of North America

JF - Rheumatic Disease Clinics of North America

IS - 3

ER -

Future Directions of Genomics Research in Rheumatic Diseases

Abstract

Keywords

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