Student Wins Junior Researcher Award in human genetics
The Portuguese Society of Human Genetics (SPGH), in collaboration with the European Society of Human Genetics (ESHG), recently awarded the SPGH/ESHG National Junior Researcher Award to João Nogueira, a student on the Molecular and Cellular Biology (MCBiology) Doctoral Programme at the University of Porto, whose research is being developed at i3S. The award recognises a young researcher under the age of 35 who has produced excellent work in the field of human genetics, and was presented at the 29th SPGH Annual Meeting in late November.
To encourage national research and strengthen links with European centres of excellence, the prize consists of funding for registration, travel, and accommodation for the next ESHG meeting, which will take place in Gothenburg, Sweden, in June 2026. João Nogueira said that this award “will allow me to establish contacts with leading researchers in the field, exchange innovative ideas, and disseminate my work internationally, strengthening the link between i3S and other leading European centres in human genetics.”
Receiving this award, the doctoral student continues, represents “a huge source of motivation, both on a personal and scientific level. It is extremely rewarding to see the work developed during my master’s dissertation recognised, especially now that the project continues to be explored in my doctorate, under the supervision of i3S researchers José Bessa and Fábio Ferreira.” For João Nogueira, it is “an important boost to continue deepening research in the field of human genetics, encouraging me to contribute significantly to the advancement of knowledge in this area.”
The winning work was “Dissecting and Predicting the Impact of Enhancer Variants in Type 2 Diabetes Using High-throughput Mutagenesis and Reporter Assays” and was developed in the Vertebrate Development and Regeneration group. It explored how changes in regulatory elements of the genome can influence the development of genetically complex diseases such as Type 2 Diabetes.
This study combined experimental techniques, such as genome sequence editing and large-scale functional assays, with computational approaches, including machine learning and artificial intelligence. The models that were developed, João Nogueira stresses, “allow us to understand how small changes in DNA, even rare or yet-to-be-identified variants, can affect the activity of these genetic enhancers and, consequently, the expression of genes critical to the disease.”
The project, the researcher emphasizes, “expands our knowledge of the impact of genetic variability on health and contributes to the development of predictive tools capable of anticipating the effects of non-coding variants and facilitating clinical interpretation. At the same time, it paves the way for more personalised approaches in research and, potentially, in the treatment of Type 2 Diabetes.”