Novel biomarkers of changes in muscle mass or muscle pathology

Abstract

Muscle protein turnover is a dynamic equilibrium that regulates the body composition and homeostasis through various cytokines and proteases. When the balance between protein synthesis and protein degradation is altered, proper muscle function and regeneration is being hampered, affecting patient’s quality of life. In these conditions, a constellation of symptoms as inflammation, fibrosis and muscle wasting has been widely observed despite different onsets. Many of these pathologies are incurable and can only be treated symptomatically. A wide array of biomarkers has been used to monitor qualitative and quantitative changes in muscle. Unfortunately, there has not been an ideal panel of biomarkers that can be readily applied in studies and assist with prognosis of the disease or response to treatment. Protein biomarkers in serum are easily obtainable, not as invasive as other methods and can be used as targets for sensitive antibody-based assays. The overall hypothesis is that both the ECM and myofibrillar biomarkers are released in circulation of people with muscle pathologies and can be used to develop bioassays. We wanted to test if those protein fingerprint biomarkers can characterize and distinguish between healthy individuals and patients with different myopathy diseases, describe the underlying mechanisms of muscle conditions and possibly putative response to an intervention. There were three different studies where biomarkers were applied in this thesis. Study I involved 51 myositis patients (28 Dermatomyositis, DM and 23 Polymyositis, PM) compared to a control group. A range of biomarkers derived from cleavage of collagens I (C1M and PINP), III (C3M and PRO-C3), VI (C6M) and C-reactive protein (CRPM) was applied to distinguish between the diseases in this cross-sectional cohort. Both DM and PM significantly affect several of the biomarkers levels measured in this study, most prominently CRPM and PINP, indicative of significantly altered turnover of extracellular matrix components and CRPM. C3M correlated with Interferon gene score, in PM and DM, and CRPM with MMT8 score in DM. We further developed an assay directed at the C-terminal of troponin T1 (TNNT1) that was measured in studies II and III. In study II, a group of cancer patients after radiotherapy was admitted to a resistance-training program alongside to a control group that followed the same training regime. Serum samples were obtained right after radiotherapy, before and during the training period. TNNT1 levels were significantly elevated in the patient group compared to the control group, even before engaging in any form of physical activity. After engaging in physical training, the biomarker levels further increased through time, reaching a significant difference both compared to the patients baseline (T24vsT0, p<0.05 ) as well as to the control group (T1 and T24 vs control, p<0.0001). In study III, healthy subjects were put in 56 days of bed rest, split in a group with resistance vibration exercise as a countermeasure and a group with no countermeasure at all. After the bed rest period, both groups entered the same rehabilitation process for a period of 128 days. There was a significant difference between the two groups in the bed rest stage that demonstrates a distinct response to the RVE counter measure. The increased levels of circulating TNNT1 for the RVE group in this study could be explained by the unloading of troponin from the muscle. During the remobilization stage, the TNNT1 levels were increased significantly in both groups in a very similar manner, compared to the baseline as well as the levels during the bed rest period. In day 28 of recovery were the maximum levels of TNNT1 observed and by the time of training completion, the levels were almost returned back to baseline. The results of this thesis point to the fact that that a panel of biomarkers could fill in the need to characterize complex processes in rare neuromuscular diseases. Addressing the main manifestation of the diseases in well-described clinical cohorts could expedite pharmaceutical trials and provide valuable information on the pathology of the disease.