Methodological development of novel Metabolomics technologies

To facilitate the transition of LC-MS-based OMICS technologies into the clinics, we develop robust and highly standardized metabolomics protocols that enable the rapid phenotyping of large sample cohorts.

Our lab established high-throughput, automated sample preparation for human plasma using a liquid handling platform, ensuring reproducible and seamless processing of large collections of biobank samples.

For metabolic profiling, we focus on two complementary approaches:

(1) DIA LC-MS Analysis: Using a combined pentafluorophenyl and reverse phase chromatography setup, we can profile ~100-120 metabolites per plasma sample at throughputs of up to 100 samples per day, allowing robust relative quantification across large studies. More details on this methodology here. (https://chemrxiv.org/engage/chemrxiv/article-details/670e647acec5d6c142390042)

2) FI-MS Analysis: In parallel, we are developing chromatography-free, flow injection-MS approaches reaching throughputs of >500 samples per day. To make sense of these highly complex spectra, we design custom analysis pipelines that integrate tools such as SIRIUS, MZmine, and MS-DIAL.

Heart failure (HF) is one of the leading causes of hospitalization in Europe for people over 65 and remains associated with poor long-term survival. Despite its prevalence, the underlying mechanisms driving HF are still incompletely understood, and effective treatment options remain limited.

To address this, we analyze large prospective cohorts of patients with HF and population-based individuals (including the MyoVasc cohort, the EmDia trial, and the Gutenberg Health Study) to investigate molecular fingerprints of HF. Our goal is to identify novel pathophysiological subphenotypes that could improve diagnosis and treatment.

In close collaboration with local partners, we apply both knowledge-mining strategies and machine-learning approaches to integrate molecular and clinical data, aiming to translate findings into clinical applications.

As part of this effort, we investigated how metabolic changes in type 2 diabetes and its treatments are reflected in blood plasma. Using the EmDia clinical trial, which studied the SGLT2 inhibitor empagliflozin in the context of HF, we demonstrated how drug treatment reshapes circulating metabolites linked to glycemic control, kidney function, and cardiovascular risk.