Phase II study of belinostat in patients with recurrent or refractory advanced thymic epithelial tumors
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Objective: Familial aggregation of autoimmune diseases likely reflects shared pathogenic factors between different diseases. Familial aggregation of autoimmunity has not been examined in juvenile dermatomyositis. Interferon-α is thought to be a pathogenic factor in both systemic lupus erythematosus and juvenile dermatomyositis, and we have previously demonstrated familial aggregation of serum interferon-α.

Methods: Family histories were obtained from 304 families of children with juvenile dermatomyositis via 3-generation structured interviews performed by the same person. Rates of autoimmune disease in families of children with juvenile dermatomyositis were compared with published population rates. Serum interferon-α, tumor necrosis factor-α, and neopterin were measured using standard techniques.

Results: A total of 51% of families of children with juvenile dermatomyositis reported at least 1 additional member affected by an autoimmune disease. In particular, both type 1 diabetes and systemic lupus erythematosus were significantly more common than would be expected (odds ratio >5, P ≤ 1 × 10(-7) for both). Pedigree analysis showed particularly strong familial clustering of systemic lupus erythematosus with little decrease in incidence across generations, suggesting the possibility of rare causal genes with large effect. Untreated subjects with juvenile dermatomyositis with a family history of systemic lupus erythematosus had higher serum interferon-α than those who did not (P = .047).

Conclusions: We find strong familial aggregation of specific autoimmune diseases in families of children with juvenile dermatomyositis, suggesting that these conditions share pathogenic factors. Higher serum interferon-α in juvenile dermatomyositis patients with a family history of systemic lupus erythematosus suggesting that interferon-α is one such shared factor.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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