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Neutrophils are considered as core immune cells involve in the early stage of rheumatoid arthritis (RA) and participate in the disease progression. The underlining mechanisms include the elevated chemotaxis and infiltration of neutrophils, the increase in the reactive oxygen species and the promotion of neutrophil extracellular traps formation. Accumulating studies demonstrated the important role of nutrients intake played in the initiation and progression of RA. This study summarized the effects of several macronutrients and micronutrients on regulating RA through the modulation of activated neutrophils and appealed for a healthy diet in RA-risk individuals as well as RA patients.

Abstract Background Although many causative genes have been uncovered in recent years, genetic diagnosis is still missing for approximately 50% of autosomal recessive cerebellar ataxia (ARCA) patients. Few studies have been performed to determine the genetic spectrum and clinical profile of ARCA patients in the Chinese population. Methods Fifty-four Chinese index patients with unexplained autosomal recessive or sporadic ataxia were investigated by whole-exome sequencing (WES) and copy number variation (CNV) calling with ExomeDepth. Likely causal CNV predictions were validated by CNVseq. Results Thirty-eight mutations including 29 novel ones were identified in 25 out of the 54 patients, providing a 46.3% positive molecular diagnostic rate. Ten different genes were involved, of which four most common genes were SACS, SYNE1, ADCK3 and SETX, which accounted for 76.0% (19/25) of the positive cases. The de novo microdeletion in SACS was reported for the first time in China and the uniparental disomy of ADCK3 was reported for the first time worldwide. Clinical features of the patients carrying SACS, SYNE1 and ADCK3 mutations were summarized. Conclusions Our results expand the genetic spectrum and clinical profiles of ARCA patients, demonstrate the high efficiency and reliability of WES combined with CNV analysis in the diagnosis of suspected ARCA, and emphasize the importance of complete bioinformatics analysis of WES data for accurate diagnosis.