Am J Epidemiol. 2022 Oct 20;191(11):1926-1935. doi: 10.1093/aje/kwac106.
Epidemiological studies using lipidomic approaches can identify lipids associated with exposures and diseases. We evaluated the sources of variability of lipidomic profiles measured in blood samples and the implications when designing epidemiologic studies. We measured 918 lipid species in nonfasting baseline serum from 693 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, with 570 participants having serial blood samples separated by 1-5 years and 72 blinded replicate quality control samples. Blood samples were collected during 1993-2006. For each lipid species, we calculated the between-individual, within-individual, and technical variances, and we estimated the statistical power to detect associations in case-control studies. The technical variability was moderate, with a median intraclass correlation coefficient of 0.79. The combination of technical and within-individual variances accounted for most of the variability in 74% of the lipid species. For an average true relative risk of 3 (comparing upper and lower quartiles) after correction for multiple comparisons at the Bonferroni significance threshold (α = 0.05/918 = 5.45 ×10-5), we estimated that a study with 500, 1,000, and 5,000 total participants (1:1 case-control ratio) would have 19%, 57%, and 99% power, respectively. Epidemiologic studies examining associations between lipidomic profiles and disease require large samples sizes to detect moderate effect sizes associations.
采用脂质组学方法的流行病学研究可以确定与暴露和疾病相关的脂质。我们评估了在血液样本中测量的脂质组学谱的变异性来源,以及在设计流行病学研究时的影响。我们在前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验中对 693 名参与者的非禁食基线血清中测量了 918 种脂质,其中 570 名参与者的血液样本在 1-5 年内进行了分离,72 个盲法重复质量控制样本。血液样本于 1993 年至 2006 年期间采集。对于每种脂质,我们计算了个体间、个体内和技术方差,并估计了在病例对照研究中检测关联的统计功效。技术变异性中等,中位数组内相关系数为 0.79。技术和个体内方差的组合占 74%脂质物种的大部分变异。对于经过多重比较的 Bonferroni 显著性阈值(α = 0.05/918 = 5.45×10-5)校正后的平均真实相对风险为 3(比较上下四分位数),我们估计在 500、1000 和 5000 名总参与者(1:1 病例对照比)的研究中,分别具有 19%、57%和 99%的功效。研究脂质组学谱与疾病之间关联的流行病学研究需要大样本量来检测中等效应大小的关联。