Abstract
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.
Highlights
Network-biology approaches are successfully employed for a better understanding of complex diseases that are caused through interactions between genetic and/or environmental factors[1,2,3,4,5,6]
The same network analysis was applied to midbrain dopaminergic neurons differentiated from induced pluripotent stem cells derived from skin fibroblasts of genetic Parkinson’s disease (PD) patients and the corresponding healthy controls
We analyzed the mitochondria interaction networks (MINs) in the samples from patients with heterozygous point mutations, namely in the SNCA gene (PARK1) encoding alpha-synuclein[14], in the PD-associated gene RHOT1 encoding a mitochondrial outer membrane GTPase[15,16] (MIRO1), and in the VPS35 gene (PARK17) encoding the vacuolar protein sortingassociated protein 35 (VPS35)[17,18,19]
Summary
Network-biology approaches are successfully employed for a better understanding of complex diseases that are caused through interactions between genetic and/or environmental factors[1,2,3,4,5,6]. Small- and macromolecules such as genes, proteins, and/or metabolites interact with each other and form networks with certain common underlying organization principles, in sharp contrast to random networks. All these molecular networks seem to obey to a general scale-free power-law distribution principle[7], the definition of power-law distribution might require fine adjustment[8]. Mitochondria, the key organelles regulating cellular metabolism and generating cellular energy, constantly interact with each other, i.e., via the fusion and fission processes. We here took advantage of the availability of various PD-derived tissues and analyzed in all of them whether a functional impairment of mitochondria is associated with any specific topological patterns or features of large-scale mitochondria interaction networks (MINs)
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