University of Aberdeen, Rowett Institute of Nutrition and Health, Aberdeen, UK.
J Nutr. 2012 Jul;142(7):1370S-6S. doi: 10.3945/jn.111.157206. Epub 2012 May 30.
A low intake of fish and PUFA and high dietary trans- and SFA are considered to be among the main preventable causes of death. Unfortunately, epidemiological and preclinical studies have yet to identify biomarkers that accurately predict the influence of fatty acid intake on risk of chronic diseases, including cancer. Changes in protein profile and post-translational modifications in tissue and biofluids may offer important clues about the impact of fatty acids on the etiology of chronic diseases. However, conventional protein methodologies are not adequate for assessing the impact of fatty acids on protein expression patterns and modifications and the discovery of protein biomarkers that predict changes in disease risk and progression in response to fatty acid intake. Although fluctuations in protein structure and abundance and inter-individual variability often mask subtle effects caused by dietary intervention, modern proteomic platforms offer tremendous opportunities to increase the sensitivity of protein analysis in tissues and biofluids (plasma, urine) and elucidate the effects of fatty acids on regulation of protein networks. Unfortunately, the number of studies that adopted proteomic tools to investigate the impact of fatty acids on disease risk and progression is quite small. The future success of proteomics in the discovery of biomarkers of fatty acid nutrition requires improved accessibility and standardization of proteomic methodologies, validation of quantitative and qualitative protein changes (e.g., expression levels, post-translational modifications) induced by fatty acids, and application of bioinformatic tools that can inform about the cause-effect relationships between fatty acid intake and health response.
低鱼类和多不饱和脂肪酸(PUFA)摄入以及高膳食反式脂肪和饱和脂肪(SFA)被认为是主要的可预防死亡原因之一。不幸的是,流行病学和临床前研究尚未确定能够准确预测脂肪酸摄入对包括癌症在内的慢性疾病风险影响的生物标志物。组织和生物流体中蛋白质谱和翻译后修饰的变化可能为脂肪酸对慢性疾病病因学的影响提供重要线索。然而,传统的蛋白质方法学不足以评估脂肪酸对蛋白质表达模式和修饰的影响,也无法发现能够预测脂肪酸摄入对疾病风险和进展变化的蛋白质生物标志物。尽管蛋白质结构和丰度的波动以及个体间的差异常常掩盖了饮食干预引起的细微影响,但现代蛋白质组学平台为提高组织和生物流体(血浆、尿液)中蛋白质分析的灵敏度以及阐明脂肪酸对蛋白质网络调节的影响提供了巨大的机会。不幸的是,采用蛋白质组学工具研究脂肪酸对疾病风险和进展影响的研究数量相当少。要想在脂肪酸营养生物标志物的发现方面取得蛋白质组学的成功,未来需要改进蛋白质组学方法的可及性和标准化,验证脂肪酸引起的定量和定性蛋白质变化(例如表达水平、翻译后修饰),并应用能够提供关于脂肪酸摄入与健康反应之间因果关系信息的生物信息学工具。