Journal of Molecular Biomarkers & Diagnosis

Our goal was to find novel protein associations that could serve as biomarkers for bipolar disorder that could be used in the real world. In order to accomplish this, we analyzed 201 distinct proteins found in blood serum from two distinct cohorts of patients with bipolar disorder and healthy controls using the proximity extension assay. After controlling for relevant covariates, we discovered 32 proteins that significantly correlated with bipolar disorder in both case-control cohorts. Despite the fact that ten proteins have previously been linked to bipolar disorder, twenty-two of these findings are novel to the disorder. Matrilysin, pro-adrenomedullin, chitinase-3-like protein 1, C-C motif chemokine 3, interleukin 10, growth/ differentiation factor 15. After that, we estimated the variance in serum protein concentrations that could have been explained by psychiatric medications and discovered that some case-control associations might have been driven by psychiatric medications. In post-hoc analyses, the serum concentration of MMP-7 was found to be positively associated with serum lithium concentration, the duration of lithium therapy, and inversely associated with estimated glomerular filtration rate in an interaction with lithium. The interaction between lithium use and MMP-7 explained the most variance.

Recent research has suggested that the risk factors for cancer and heart disease such as age, sex, smoking, genetics, obesity, diabetes mellitus, and hypertension as well as the pathophysiological pathways such as inflammation and oxidative stress share a significant amount of risk with HF. A provocative interpretation of this finding is that the two diseases are two manifestations of the same disease spectrum. By evaluating the prognostic value and clinical correlates of six commonly used tumor biomarkers in a large, well-defined cohort of HF patients, we aimed to provide evidence for this hypothesis in an unconventional manner. To begin, we demonstrate that four of the six biomarkers for tumors have independent prognostic value and can predict mortality from all causes. Additionally, we demonstrate a strong correlation between various tumor biomarkers, such as NT-proBNP and NYHA class, and indicators of HF severity. Finally, we demonstrate that, in comparison to NT proBNP, CYFRA 21 had comparable predictive power for all-cause mortality. We conclude that pathological signals and pathways that tumor biomarkers "sense" are also present in HF and have correlations with HF severity and outcomes.