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Abstract

The two most prevalent age-related neurodegenerative diseases are Alzheimer's disease (AD) and Parkinson's disease (PD). In recent years, the number of affected individuals has been rapidly increasing. Research in this area has revealed that AD and PD share several common physiological and pathological characteristics. In both cases, the severity of patients' symptoms worsens over time, emphasizing the importance of early diagnosis and determining therapeutic targets. Understanding the genetics underlying the physiopathological manifestations of both diseases is crucial for designing early diagnostic mechanisms and new therapeutic interventions to treat affected patients. Therefore, we propose a framework for identifying the most promising genes highly correlated with disease pathogenesis. Initially, co-expression networks are constructed from sample data of each disease. Subsequently, gene co-expression patterns are analyzed using module preservation statistics. Furthermore, a multiobjective optimization-based method for disease marker identification is employed to identify marker genes associated with AD and PD. Finally, the biological significance of these markers are established through genomics and transcriptomics validation studies.

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