Turku Bioscience Center, University of Turku and Åbo Akademi University, Turku, Finland.
Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Biol Psychiatry. 2021 Feb 1;89(3):288-297. doi: 10.1016/j.biopsych.2020.07.012. Epub 2020 Jul 25.
A key clinical challenge in the management of individuals at clinical high risk for psychosis (CHR) is that it is difficult to predict their future clinical outcomes. Here, we investigated if the levels of circulating molecular lipids are related to adverse clinical outcomes in this group.
Serum lipidomic analysis was performed in 263 CHR individuals and 51 healthy control subjects, who were then clinically monitored for up to 5 years. Machine learning was used to identify lipid profiles that discriminated between CHR and control subjects, and between subgroups of CHR subjects with distinct clinical outcomes.
At baseline, compared with control subjects, CHR subjects (independent of outcome) had higher levels of triacylglycerols with a low acyl carbon number and a double bond count, as well as higher levels of lipids in general. CHR subjects who subsequently developed psychosis (n = 50) were distinguished from those that did not (n = 213) on the basis of lipid profile at baseline using a model with an area under the receiver operating curve of 0.81 (95% confidence interval = 0.69-0.93). CHR subjects who became psychotic had lower levels of ether phospholipids than CHR individuals who did not (p < .01).
Collectively, these data suggest that lipidomic abnormalities predate the onset of psychosis and that blood lipidomic measures may be useful in predicting which CHR individuals are most likely to develop psychosis.
在对处于精神病高危状态(CHR)的个体进行管理时,一个关键的临床挑战是难以预测他们未来的临床结局。在这里,我们研究了循环分子脂质水平是否与该人群的不良临床结局相关。
对 263 名 CHR 个体和 51 名健康对照者进行了血清脂质组学分析,然后对他们进行了长达 5 年的临床监测。使用机器学习来识别区分 CHR 和对照组以及 CHR 个体具有不同临床结局的亚组的脂质谱。
与对照组相比,CHR 个体(无论结局如何)在基线时具有更高水平的具有低酰基碳数和双键数的三酰甘油,以及更高水平的一般脂质。随后发展为精神病的 CHR 受试者(n=50)与未发展为精神病的受试者(n=213)在基线时基于脂质谱进行区分,该模型的曲线下面积为 0.81(95%置信区间=0.69-0.93)。发生精神病的 CHR 受试者的醚磷脂水平低于未发生精神病的 CHR 个体(p<0.01)。
总的来说,这些数据表明脂质组学异常先于精神病的发生,并且血液脂质组学测量可能有助于预测哪些 CHR 个体最有可能发展为精神病。