Abstract
When planning and performing large-scale population studies with metabolomics, all factors affecting metabolite concentrations must be considered. In addition to genetic and environmental factors, serum metabolite levels might also be affected by disease status or medication.
In this work we investigated the effects of disease status and medication on serum metabolite levels using the targeted metabolomics data set of the Cooperative Health Research in South Tyrol (CHRIS) study, consisting of 175 quantified metabolites in 6872 participants. For medication, Anatomical Therapeutic Chemical (ATC) codes of all prescribed drugs were used. To identify metabolites with different concentration between the groups, linear regression models were fitted separately to each analyte using the log2 transformed concentration as a response variable and sex, age, BMI, self-reported fasting status, disease status and a binary variable for medication as covariates.
Metabolites found significant for most considered ATC level 2 medication groups were serotonin (in 9 groups), lysoPC a C18:1 (in 7 groups), lysoPC a C18:0, lysoPC a C18:2, SM (OH) C22:1, SM C24:0 (in 6 groups), glutamate, PC ae C34:3, SM (OH) C14:1, SM (OH) C22:2m (in 5 groups). Whether observed differences represent the effect of the treatment or are a consequence of the disease is however unclear because both are inherently connected. For selected diseases, a comparison of significant metabolites from diagnosed, but untreated individuals and diagnosed treated individuals helped discriminating between treatment- and disease-related metabolites.
Our findings suggest that concentrations of blood metabolites are affected by medication and/or disease status. Adjustment for medication might not always be appropriate because of its potential direct relationship with disease status or the phenotype of interest but should at least be considered in result interpretation. Medication for a certain disease comprises agents potentially acting on different pathways, thus, also the detail level on which medication is considered is important.