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Genome-scale metabolic modelling predicts biomarkers and therapeutic targets for neuropsychiatric disorders
Computers in Biology and Medicine ( IF 7.7 ) Pub Date : 2020-09-17 , DOI: 10.1016/j.compbiomed.2020.103994
S T R Moolamalla 1 , P K Vinod 1
Affiliation  

Distinguishing neuropsychiatric disorders is challenging due to the overlap in symptoms and genetic risk factors. People suffering from these disorders face personal and professional challenges. Understanding the dysregulation of brain metabolism under disease condition can aid in effective diagnosis and in developing treatment strategies based on the metabolism. In this study, we reconstructed the metabolic network of three major neuropsychiatric disorders, schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) using transcriptomic data and constrained based modelling approach. We integrated brain transcriptomic data from six independent studies with a recent comprehensive genome-scale metabolic model Recon3D. The analysis of the reconstructed network revealed the flux-level alterations in the peroxisome-mitochondria-golgi axis in neuropsychiatric disorders. We also extracted reporter metabolites and pathways that distinguish these three neuropsychiatric disorders. We found differences with respect to fatty acid oxidation, aromatic and branched chain amino acid metabolism, bile acid synthesis, glycosaminoglycans synthesis and modifications, and phospholipid metabolism. Further, we predicted network perturbations that transform the disease metabolic state to a healthy metabolic state for each disorder. These analyses provide local and global views of the metabolic changes in SCZ, BD and MDD, which may have clinical implications.



中文翻译:

基因组规模的代谢建模可预测神经精神疾病的生物标志物和治疗靶标

由于症状和遗传风险因素的重叠,区分神经精神疾病具有挑战性。患有这些疾病的人面临着个人和职业挑战。了解疾病条件下脑代谢的失调可以帮助有效诊断和制定基于代谢的治疗策略。在这项研究中,我们使用转录组数据和基于约束的建模方法,重建了三种主要的神经精神疾病,精神分裂症(SCZ),双相情感障碍(BD)和主要抑郁症(MDD)的代谢网络。我们将来自六项独立研究的脑转录组数据与最新的全面基因组规模的代谢模型Recon3D整合在一起。重建网络的分析显示神经精神疾病中过氧化物酶体-线粒体-高尔基体轴的通量水平改变。我们还提取了区分这三种神经精神疾病的记者代谢产物和途径。我们发现在脂肪酸氧化,芳族和支链氨基酸代谢,胆汁酸合成,糖胺聚糖合成和修饰以及磷脂代谢方面存在差异。此外,我们预测了网络扰动,可将每种疾病的疾病代谢状态转化为健康代谢状态。这些分析提供了SCZ,BD和MDD代谢变化的局部和全局视图,这可能具有临床意义。我们还提取了区分这三种神经精神疾病的记者代谢产物和途径。我们发现在脂肪酸氧化,芳族和支链氨基酸代谢,胆汁酸合成,糖胺聚糖合成和修饰以及磷脂代谢方面存在差异。此外,我们预测了网络扰动,可将每种疾病的疾病代谢状态转化为健康代谢状态。这些分析提供了SCZ,BD和MDD代谢变化的局部和全局视图,这可能具有临床意义。我们还提取了区分这三种神经精神疾病的记者代谢产物和途径。我们发现在脂肪酸氧化,芳族和支链氨基酸代谢,胆汁酸合成,糖胺聚糖合成和修饰以及磷脂代谢方面存在差异。此外,我们预测了网络扰动,可将每种疾病的疾病代谢状态转化为健康代谢状态。这些分析提供了SCZ,BD和MDD代谢变化的局部和全局视图,这可能具有临床意义。我们预测了网络扰动,可将每种疾病的疾病代谢状态转化为健康代谢状态。这些分析提供了SCZ,BD和MDD代谢变化的局部和全局视图,这可能具有临床意义。我们预测了网络扰动,可将每种疾病的疾病代谢状态转化为健康代谢状态。这些分析提供了SCZ,BD和MDD代谢变化的局部和全局视图,这可能具有临床意义。

更新日期:2020-09-24
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