New Knowledge Portal Adiposetissue.org Enhances Obesity and Metabolism Research with Centralized Data

Addressing the Challenge of Dispersed Data

For years, adipose tissue research has generated vast amounts of omics data, but these datasets remained scattered across different repositories, making comprehensive analysis challenging. Adiposetissue.org now brings insights together, integrating transcriptomic and proteomic with clinical data from more than 6,000 individuals, enabling researchers to explore obesity-related changes, weight-loss effects, and cellular mechanisms with unprecedented depth.

“We developed this knowledge portal to make adipose tissue data accessible to everyone, even those without expertise in bioinformatics.”
Dr. Lucas Massier, researcher at the Helmholtz Institute for Metabolic, Obesity and Vascular Research (short: HI-MAG) – a Helmholtz Munich institute at the University of Leipzig and the University of Leipzig Medical Center

A key part of this effort was led by early-career scientists Jiawei Zhong and Dr. Danae Zareifi from Karolinska Institutet. “We ensured that data from different sources could be compared by standardizing terminology. Since little proteomic data was available, we also generated new protein profiling datasets, improving the portal’s ability to verify gene activity findings,” Jiawei Zhong and Danae Zareifi explain.

“By breaking down barriers to data accessibility and enabling large-scale analysis, Adiposetissue.org is a powerful resource for researchers studying adipose biology and metabolic diseases,” says Prof. Mikael Rydén, head of the endocrinology unit and co-leader of the Rydén & Mejhert lab together with assoc. Prof. Niklas Mejhert at Karolinska Institutet and Steno Diabetes Center Copenhagen. “This has been a major collaborative effort, and we will continue expanding the portal with new results in future updates.”

Key Features of Adiposetissue.org

• Comprehensive data integration: The platform aggregates reprocessed datasets from 67 studies, ensuring consistency and statistical robustness.
• User-friendly access: It is designed for both experienced bioinformaticians and researchers without advanced computational expertise.
• Advanced analysis tools: The platform includes customizable modules for gene exploration, single-cell and spatial transcriptomics, and perturbation studies.
• Dynamic and evolving resource: Future expansions will incorporate brown adipose tissue data, additional clinical cohorts, and interspecies comparisons.

Visit adiposetissue.org