Parkinson’s disease (PD) is the second most common neurodegenerative disorder worldwide, yet current diagnostic tools rely heavily on clinical symptoms, which often appear only after substantial neuronal loss has occurred. To address this diagnostic delay, my project proposes a novel rapid diagnostic test that integrates synthetic biology and genetic biosensors to simultaneously detect pathological forms of α-synuclein and microRNAs associated with PD. By combining conformational biosensing and miRNA detection into a single colorimetric output platform, this test aims to provide early, accessible, and non-invasive detection of Parkinson’s disease. Parkinson’s disease is a progressive neurodegenerative condition characterized by the loss of dopaminergic neurons in the substantia nigra and the presence of intracellular aggregates called Lewy bodies, primarily composed of misfolded α-synuclein. It affects over 10 million people globally, and its incidence is expected to rise due to aging populations [1]. The lack of reliable, early-stage biomarkers hinders timely diagnosis and treatment, which could otherwise slow disease progression and improve patient outcomes. Current diagnostic methods primarily depend on clinical evaluations and imaging techniques, which often detect the disease only after significant neurodegeneration has occurred. Molecular biomarkers such as misfolded α-synuclein and PD-specific microRNAs (miRNAs), including miR-153, miR-34b/c, and others [2], have shown promise in recent years for early diagnosis. However, most detection techniques for these biomarkers are time-consuming, expensive, and unsuitable for point-of-care use. Synthetic biology provides an exciting opportunity to engineer programmable biosensors capable of detecting specific molecular signatures. Recent advances in genetic circuit design, aptamer technology, and paper-based diagnostics enable the creation of low-cost, modular, and rapid detection platforms. In particular, logic-based gene circuits can be designed to produce color outputs in response to specific molecular cues, such as the presence or absence of conformational variants of α-synuclein or regulatory miRNAs. In this project, I propose a dual-output biosensor that suppresses color signal upon detecting normal α-synuclein conformation (i.e., no pathological signal), but activates color when pathogenic misfolded forms are present. In parallel, specific miRNA sequences will trigger distinct color changes, indicating their presence. This multiplex test aims to bridge the gap between molecular insight and practical application, offering a new tool for early Parkinson’s diagnosis with potential for translation to other neurodegenerative diseases.
Describe how your project is innovative (min. 3 sentences)
My project is innovative because it integrates two distinct molecular recognition systems—an RNA toehold switch and a specific aptamer for misfolded α-synuclein—into a single, logic-gated diagnostic tool. Unlike traditional tests that detect only one biomarker, this system generates different levels of signal depending on the presence of miR-153, misfolded α-synuclein, or both, allowing for nuanced detection of early Parkinson’s disease risk. Additionally, its modular design allows expression to be regulated by molecular folding states, enabling portable, cell-free diagnostics using saliva as a non-invasive sample.
Briefly expand upon the significance of your final project. (min. 5 sentences)
Parkinson’s disease is one of the most common neurodegenerative disorders, yet early and accurate diagnosis remains a major challenge, especially before motor symptoms appear. My project aims to address this gap by developing a sensitive, portable, and non-invasive diagnostic tool that can detect early molecular indicators of the disease—specifically miR-153 and misfolded α-synuclein. Detecting these biomarkers in saliva provides a painless and accessible method for screening at-risk populations. By combining RNA toehold switches and aptamer-based sensing in a logic-gated system, the test provides multiple layers of detection to improve specificity and reduce false results. This approach could significantly accelerate early intervention strategies and improve patient outcomes by enabling treatment at earlier disease stages.
Bioethical Considerations
The development of a diagnostic test for Parkinson’s disease based on biomarkers such as miR-153 and misfolded α-synuclein carries significant ethical implications. One major concern is the principle of non-maleficence, or “do no harm.” False positives could cause unnecessary psychological distress, while false negatives could delay life-changing treatment. Additionally, early diagnosis of a progressive and currently incurable disease raises questions of autonomy and the right to know—or not know—one’s condition. There is also the principle of justice, particularly in ensuring equal access to this test, especially for underserved populations or communities with limited healthcare infrastructure.
To ensure that this project remains ethical, clear measures should be taken throughout development and deployment. First, the test should undergo rigorous validation to minimize inaccuracies, and informed consent must be emphasized during trials, including transparent communication about what the results mean. Data privacy and protection are crucial if personal health data are collected. Potential unintended consequences may include the emotional burden of early diagnosis without clear treatment options or misuse of diagnostic data by insurance companies or employers. Our assumptions—for example, that miR-153 and misfolded α-synuclein in saliva are always reliable indicators—may be incorrect, requiring constant reevaluation of the test's performance. As an alternative or complementary approach, confirmatory clinical diagnosis by neurologists should always follow positive results. Ongoing oversight by bioethics committees and engagement with patient advocacy groups are vital to maintaining ethical integrity in both research and clinical application.