Carl Brunius

Chalmers University of Technology

Key publications

Schillemans T, Yan Y, Ribbenstedt A, Donat-Vargas C, Lindh C, Kiviranta H, Rantakokko P, Wolk A, Landberg R, Åkesson A, Brunius C 2024. OMICs signatures linking persistent organic pollutants to cardiovascular disease in the Swedish Mammography Cohort. Environmental Science & Technology. doi: 10.1021/ACS.EST.3C06388

Skantze V, Wallman M, Sandberg A-S, Landberg R, Jirstrand M, Brunius C 2023.
Identification of metabotypes in complex biological data using tensor decomposition.
Chemometrics and Intelligent Laboratory Systems, 233, art. no. 104733. DOI: 10.1016/j.chemolab.2022.104733

Schillemans T, Shi L, Donat-Vargas C, Hanhineva K, Tornevi A, Johansson I, Koponen J, Kiviranta H, Rolandsson O, Bergdahl I, Landberg R, Åkesson A, Brunius C 2021.
Plasma metabolites associated with exposure to perfluoroalkyl substances and risk of type 2 diabetes – A nested case-control study.
Environment International 146, 106180.

Schillemans T, Shi L, Liu X, Åkesson A, Landberg R, Brunius C 2019.
Visualization and Interpretation of Multivariate Associations with Disease Risk Markers and Disease Risk—The Triplot.
Metabolites 9 (7), 133. DOI: 10.3390/metabo9070133

Shi L, Westerhuis JA, Rosén J, Landberg R, Brunius C 2019.
Variable selection and validation in multivariate modelling.
Bioinformatics 35(6), 972–980. DOI: 10.1093/bioinformatics/bty710

Shi L, Brunius C, Lehtonen M, Auriola S, Bergdahl I, Rolandsson O, Hanhineva K, Landberg R, 2018.
Plasma metabolites associated with type 2 diabetes in a Swedish population – A case-control study nested in a prospective cohort.
Diabetologia 61(4), 849-861. DOI: 10.1007/s00125-017-4521-y

We aim to discover and understand the molecular mechanisms underpinning how health status is affected by exposures, such as food, microbiota and environmental pollutants. We work on data from both population-based cohorts as well as human dietary intervention studies, with a strong focus on data-driven life science, including nutritional and molecular epidemiology. To understand regulation of the metabolic system in relation to exposures and health, we work with different Omics data, mostly reflecting metabolites, proteins and microbiota.

To perform molecular- and mechanism-oriented research, we actively contribute to the development of freely available data analytical tools. We typically combine our MUVR algorithm for machine learning analysis with linear models to identify Omics variables-of-interest that can be either biomarker candidates for exposure or health assessment.

We have also become fond of the “meet-in-the-middle” approach for molecular epidemiology, where potential mediators can be identified from the intersection of Omics variables related to both exposures and outcomes. We can then visualize and interpret how these potential molecular mediators link e.g. diet or pollutant exposures to type 2 diabetes, cardiovascular disease or other health conditions using our triPlot tool.

In addition, Dr Brunius is Scientific advisor to the Chalmers Mass Spectrometry Infrastructure which performs mass spectrometry-based metabolomics analysis as part of the SciLifeLab Metabolomics platform. He supplies the infrastructures with computational tools to monitor and improve data quality as well as to improve automation and reproducibility in the pre-processing of instrument data into actionable format for down-stream data analysis. This involvement highlights the effective interaction between data generation and data usage for life science research.

Group Members:

Carl Brunius, Associate Professor
Yingxiao Yan, doctoral student
Elise Nordin, doctoral student
Olle Hartvigsson, doctoral student
Anton Ribbenstedt, postdoc

Last updated: 2024-02-01

Content Responsible: Hampus Persson(