2026 Nordics winner

Depression has become the leading cause of disability worldwide. It arises from a complex interaction between genetic, environmental and lifestyle factors, but despite decades of research, its biological underpinnings are still not fully understood, and robust predictive biomarkers are lacking. In recent years, the gut microbiome, a key modulator of metabolic and immune functions, has emerged as an important player in brain health, including depression. However, most existing studies have looked at the microbiome when depression has already been diagnosed, making it difficult to determine whether these changes are a cause or a consequence of the condition. In addition, it remains unknow if the gut microbiome interacts with a person’s genetic predisposition to influence depression risk, or how it relates to the immune and metabolic disturbances often seen in individuals with depression.

This project aims to address these gaps by identifying gut microbiome features that can predict future depression diagnosis. We will also assess how these predictive microbial features interact with host genetic risk to depression and with biological processes such as inflammation and metabolism. By integrating microbiome data with genetic, metabolomic and electronic health record information from the prospective, population-based Estonian Microbiome Cohort, we can study individuals before depression onset, which offers a unique opportunity to better understand early risk factors and biological mechanisms leading to disease. Our findings will be validated through collaborations with research teams in Sweden and Finland.

What will this grant bring to the research project?

With grant support from the Biocodex Microbiota Foundation, we aim to extend the knowledge on how the gut microbiome contributes to depression. In particular, the funding will enhance the scientific depth of the project by supporting the analyses of the inflammatory biomarkers, helping us better understand the biological pathways involved. The grant will also support the computational resources needed for large-scale data analysis and facilitate in-person collaboration with international partners to strengthen and validate our findings.