Objective: This study analyzes the structure and performance of the co-authorship network in nutrigenomics, aiming to uncover its collaboration dynamics and identify key influential researchers.

Method: Data from PubMed (2020–2024) were analyzed using Gephi 0.10.1 and NetworkX 3.4.1 to evaluate the network at macro and micro levels. Macro-level metrics—including density, clustering coefficient, modularity, and diameter—were calculated to assess the overall structure of the network. Micro-level analysis focused on centrality measures (degree, betweenness, eigenvector, and PageRank) to evaluate individual researchers' influence and to generate a ranked list of key contributors.

Results: Analysis was conducted on a total of 920 articles extracted from PubMed. The co-authorship network exhibits a highly modular structure (modularity score: 0.965) with 505 distinct communities, reflecting diverse research areas. Leaders in the network are distributed across several countries, with the United States, China, and Spain being the top three. Ordovas JM, Li H, and Wang D emerged as the most prolific authors, holding the highest degree centrality. Ordovas JM, Holscher HD, and Yan Y lead in betweenness centrality, connecting disparate parts of the network, while Ordovas JM, Wang D, and Yan Y have the highest eigenvector centrality, signifying strategic collaborations. PageRank highlights Ordovas JM and El-Sohemy A as the most impactful authors.

Conclusion: Nutrigenomics research is rapidly expanding due to its potential in chronic disease prevention. While key researchers enhance network diversity, their centrality makes the network vulnerable to their exit. Promoting collaboration among these researchers and integrating young talent can bolster the network’s resilience and growth.