Substantia nigra and blood gene signatures and biomarkers for Parkinson’s disease from integrated multicenter microarray-based transcriptomic analyses - Hui-Hui Fan; Na-Na Hou; Na-Na Hou; Dao-Lu Zhang; Dan-Ni Liu; Rong-Ting Tang; Hai-Tao Luo; Ya-Dan Song; Lei Cui; Xiong Zhang; Jian-Hong Zhu; Jian-Hong Zhu (Frontiers in Aging Neuroscience)
BackgroundParkinson’s disease (PD) is a complex, common neurodegenerative disorder with unclear etiology. The pathogenic hallmark is the death of dopaminergic neurons in the substantia nigra. PD diagnosis depends on clinical manifestation of symptoms but is lack of effective biomarker.MethodsAvailable human microarray-based transcriptomic datasets of the substantia nigra and blood were acquired for PD cases and controls. Robust rank aggregation and Weighted Gene Co-expression Network analysis were performed to identify gene signatures in substantia nigra and blood of PD. An overlapping analysis and validation in an independent cohort were followed to identify PD blood biomarkers.ResultsEight datasets of substantia nigra and 3 datasets of blood were retrieved, which comprised 150 substantia nigra and 571 blood samples. Integrated differentially expressed genes (DEG) and module analyses showed that the substantia nigra gene signature in PD comprised 170 key genes, mainly involved in dopaminergic synapse, neuroactive ligand-receptor interaction, calcium signaling pathway, and Parkinson disease. The blood gene signature had only 65 DEGs, but with no robust co-expression module identified. Two genes, LRRN3 and TUBB2A, were both downregulated in the substantia nigra and blood of PD. But only TUBB2A was validated in the blood of independent cohort and showed a capacity of PD prediction.ConclusionThe present study identified PD-associated gene signatures of the substantia nigra and blood, and demonstrated that the reduced expression of TUBB2A in the blood is promising to predict PD. Our findings provide novel insight into the mechanisms underlying PD pathophysiology and the development of PD biomarkers.