Mitochondrial dysfunction is linked to pathogenesis of Parkinson’s disease (PD). However, individual mitochondria-based analyses do not show a uniform feature in PD patients. Since mitochondria interact with each other, we hypothesize that PD-related features might exist in topological patterns of mitochondria interaction networks (MINs). Here we show that MINs formed nonclassical scale-free supernetworks in colonic ganglia both from healthy controls and PD patients; however, altered network topological patterns were observed in PD patients. These patterns were highly correlated with PD clinical scores and a machine-learning approach based on the MIN features alone accurately distinguished between patients and controls with an area-under-curve value of 0.989. The MINs of midbrain dopaminergic neurons (mDANs) derived from several genetic PD patients also displayed specific changes. CRISPR/CAS9-based genome correction of alpha-synuclein point mutations reversed the changes in MINs of mDANs. Our organelle-interaction network analysis opens another critical dimension for a deeper characterization of various complex diseases with mitochondrial dysregulation.

线粒体功能障碍与帕金森病 (PD) 的发病机制有关。然而，基于个体线粒体的分析在 PD 患者中并未显示出统一的特征。由于线粒体彼此相互作用，我们假设线粒体相互作用网络 (MIN) 的拓扑模式中可能存在 PD 相关特征。在这里，我们表明 MIN 在来自健康对照和 PD 患者的结肠神经节中形成了非经典的无标度超网络；然而，在 PD 患者中观察到改变的网络拓扑模式。这些模式与 PD 临床评分和仅基于 MIN 特征的机器学习方法高度相关，可准确区分患者和对照，曲线下面积值为 0.989。来自几个遗传性 PD 患者的中脑多巴胺能神经元 (mDAN) 的 MIN 也显示出特定的变化。α-突触核蛋白点突变的基于 CRISPR/CAS9 的基因组校正逆转了 mDAN 的 MIN 的变化。我们的细胞器相互作用网络分析为更深入地表征具有线粒体失调的各种复杂疾病开辟了另一个关键维度。