Journal: Scientific Reports (Accepted for publication in May 2026)

Parkinson’s disease (PD) is a complex neurological condition, and despite decades of research, its molecular underpinnings remain only partially understood. While environmental and lifestyle factors play roles, the genetic contributors to PD are increasingly gaining attention. Among these, the SNCA gene—which encodes the alpha-synuclein (α-syn) protein—has emerged as a key player. The α-syn protein is heavily implicated in the degeneration of dopaminergic neurons, a hallmark of PD pathology.

In our recent study, we turned our focus to a specific genetic variant within the SNCA gene: rs356220. Although this non-coding downstream SNP (single nucleotide polymorphism) has often been associated with an increased risk of Parkinson’s disease and the development of motor symptoms such as rigidity, it is curiously classified as benign in most pharmacogenomic databases. This raises an intriguing question: how does a variant with no direct coding impact exert such influence on disease risk?

Hypothesizing a Hidden Role in PD

We hypothesized that rs356220, despite being a non-coding variant, could influence PD progression by affecting regulatory elements—particularly those governing transcription factor binding at the SNCA locus. If true, this could explain its consistent association with PD prevalence globally, even in the absence of known pharmacogenomic consequences.

Diving into the DNA with In-Silico Tools

To explore this hypothesis, we employed FABIAN-Variant, an advanced computational tool designed to analyze the impact of SNPs on transcription factor binding. Our analysis revealed notable changes due to rs356220:

• Gain of binding for transcription factors: BAD and IRF1
• Loss of binding for factors: CANX and SLC18A1

These shifts suggest that rs356220 alters the regulatory landscape around the SNCA gene—potentially influencing how and when α-syn is expressed.

Building the Bigger Picture: Network and Pathway Analysis

We didn’t stop at transcription factors. Using pathway enrichment analysis and protein interaction modeling, we uncovered a network of interactions involving the newly implicated transcription factors and SNCA. Among the highlights:

• BAD was found to interact with SNCA in a pathway-sensitive context.
• IRF1, CANX, and SLC18A1 all formed indirect or direct interactions, creating a regulatory web centered around SNCA.
• TP53—a well-known tumor suppressor protein—emerged as a central node linking many of these factors, suggesting it may act as a master regulator within this network.

Interestingly, SLC18A1 appeared to be directly connected to SNCA, further supporting the idea that rs356220 could modulate functional gene expression relevant to PD.

What This Means for Parkinson’s Research

Our findings provide computational evidence that even non-coding variants—once considered "junk" or irrelevant—can play pivotal roles in complex disorders like Parkinson's disease. The altered transcription factor binding and the resulting network-level effects offer a plausible explanation for how rs356220 contributes to disease pathology.

This study underscores the importance of integrative in-silico approaches in modern genomics, especially when working with disorders that defy simple explanations. As the field of personalized medicine advances, understanding these subtle genetic signals will be crucial to developing more targeted therapies and diagnostics for Parkinson’s and other neurodegenerative diseases.

Authors

Dr. Naushad Rais and Shradha Menon
School of Life Sciences, Manipal Academy of Higher Education, Dubai, United Arab Emirates (UAE)