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For: Ichikawa N, Kotake S, Hakoda M, Higami K, Kawasaki A, Furuya T, Nanke Y, Tsuchiya N, Tokunaga K, Kamatani N. Combining effects of polymorphism of tumor necrosis factor alpha 5'-flanking region and HLA-DRB1 on radiological progression in patients with rheumatoid arthritis. Mod Rheumatol 2009;19:134-9. [PMID: 19002558 DOI: 10.1007/s10165-008-0134-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2008] [Accepted: 09/29/2008] [Indexed: 10/21/2022]

For:	Ichikawa N, Kotake S, Hakoda M, Higami K, Kawasaki A, Furuya T, Nanke Y, Tsuchiya N, Tokunaga K, Kamatani N. Combining effects of polymorphism of tumor necrosis factor alpha 5'-flanking region and HLA-DRB1 on radiological progression in patients with rheumatoid arthritis. Mod Rheumatol 2009;19:134-9. [PMID: 19002558 DOI: 10.1007/s10165-008-0134-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2008] [Accepted: 09/29/2008] [Indexed: 10/21/2022]

Number

Cited by Other Article(s)

Zhang R, Luan M, Shang Z, Duan L, Tang G, Shi M, Lv W, Zhu H, Li J, Lv H, Zhang M, Liu G, Chen H, Jiang Y. RADB: a database of rheumatoid arthritis-related polymorphisms. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014;2014:bau090. [PMID: 25228593 PMCID: PMC4164886 DOI: 10.1093/database/bau090] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]

Affiliation(s)

Ruijie Zhang College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Meiwei Luan College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Zhenwei Shang College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Lian Duan College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Guoping Tang College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Miao Shi College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Wenhua Lv College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Hongjie Zhu College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Jin Li College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Hongchao Lv College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Mingming Zhang College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
Guiyou Liu College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China
He Chen College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China zhangruijie
Yongshuai Jiang College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China, Yiwu Hospital, Zhejiang University, Yiwu 322000, China, Genome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China, Depatment of Pathology, Harbin Medical University, Harbin 150086, China

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Juyal RC, Negi S, Wakhode P, Bhat S, Bhat B, Thelma BK. Potential of ayurgenomics approach in complex trait research: leads from a pilot study on rheumatoid arthritis. PLoS One 2012;7:e45752. [PMID: 23049851 PMCID: PMC3458907 DOI: 10.1371/journal.pone.0045752] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Accepted: 08/23/2012] [Indexed: 12/27/2022] Open

Abstract

Background

Inconsistent results across association studies including Genome-wide association, have posed a major challenge in complex disease genetics. Of the several factors which contribute to this, phenotypic heterogeneity is a serious limitation encountered in modern medicine. On the other hand, Ayurveda, a holistic Indian traditional system of medicine, enables subgrouping of individuals into three major categories namely Vata, Pitta and Kapha, based on their physical and mental constitution, referred to as Prakriti. We hypothesised that conditioning association studies on prior risk, predictable in Ayurveda, will uncover much more variance and potentially open up more predictive health.

Objectives and Methods

Identification of genetic susceptibility markers by combining the prakriti based subgrouping of individuals with genetic analysis tools was attempted in a Rheumatoid arthritis (RA) cohort. Association of 21 markers from commonly implicated inflammatory and oxidative stress pathways was tested using a case-control approach in a total cohort comprising 325 cases and 356 controls and in the three subgroups separately. We also tested few postulates of Ayurveda on the disease characteristics in different prakriti groups using clinico-genetic data.

Results

Inflammatory genes like IL1β (C-C-C haplotype, p = 0.0005, OR = 3.09) and CD40 (rs4810485 allelic, p = 0.04, OR = 2.27) seem to be the determinants in Vata subgroup whereas oxidative stress pathway genes are observed in Pitta (SOD3 rs699473, p = 0.004, OR = 1.83; rs2536512 p = 0.005; OR = 1.88 and PON1 rs662, p = 0.04, OR = 1.53) and Kapha (SOD3 rs2536512, genotypic, p = 0.02, OR = 2.39) subgroups. Fixed effect analysis of the associated markers from CD40, SOD3 and TNFα with genotype X prakriti interaction terms suggests heterogeneity of effects within the subgroups. Further, disease characteristics such as severity was most pronounced in Vata group.

Conclusions

This exploratory study suggests discrete causal pathways for RA etiology in prakriti based subgroups, thereby, validating concepts of prakriti and personalized medicine in Ayurveda. Ayurgenomics approach holds promise for biomarker discovery in complex diseases.

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