The regulation of skeletal muscle mass depends on the balance between protein synthesis and degradation. The role of protein degradation and in particular, the ubiquitin proteasome system, and increased expression of the E3 ubiquitin ligases, MuRF1 and MAFbx/atrogin-1, in the regulation of muscle size in response to growth stimuli is unclear. Thus, the aim of this study was to measure both proteasome activity and protein synthesis in mice over a 14-day period of chronic loading using the functional overload (FO) model. Further, the importance of MuRF1 and MAFbx expression in regulating muscle hypertrophy was examined by measuring muscle growth in response to FO in mice with a null deletion (KO) of either MuRF1 or MAFbx. In wild type (WT) mice, the increase in muscle mass correlated with significant increases (2-fold) in protein synthesis at 7 and 14 days. Interestingly, proteasome activity significantly increased in WT mice after one day, and continued to increase, peaking at 7 days following FO. The increase in proteasome activity was correlated with increases in the expression of the Forkhead transcription factors, FOXO1 and FOXO3a, which increased after both MuRF1 and MAFbx increased and returned to baseline. As in WT mice, hypertrophy in the MuRF1 and MAFbx KO mice was associated with significant increases in proteasome activity after 14 days of FO. The increase in plantaris mass was similar between the WT and MuRF1 KO mice following FO, however, muscle growth was significantly reduced in female MAFbx KO mice. Collectively, these results indicate that muscle hypertrophy is associated with increases in both protein synthesis and degradation. Further, MuRF1 or MAFbx expression is not required to increase proteasome activity following increased loading, however, MAFbx expression may be required for proper growth/remodeling of muscle in response to increase loading.

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Advancements in biomedical research have contributed to increasing the life expectancy of humans, but we now observe an increase in age-related diseases such as Alzheimer's disease. Genome-Wide Association Studies (GWAS) and linkage studies have identified human genes associated with Alzheimer's disease (referred to as AD genes). A previous study by Vahdati in 2017 has revealed the human AD genes and counterparts in model species [1]. Thus, we further investigate the co-morbidity genes and alleles. Using ontology analysis combined with cluster analysis, the study identified functional pathways enriched among the human AD genes, including 179 genes out of 695 human AD genes (26%) that were associated with one or more of the four neurological diseases including Amyotrophic lateral sclerosis, Multiple sclerosis, Parkinson's disease, and Schizophrenia [1]. More importantly, the results indicate co-morbidities with Late-Onset Alzheimer's Disease (LOAD) and other neurological conditions, implying the complexity of the phenotypes in the human AD. The co-morbidity genes may account for mixed symptoms for human AD as well as age-related risks of infections. Of them, the three genes are well conserved (Angiotensin I Converting Enzyme gene, ACE; Methylenetetrahydrofolate Reductase gene, MTHFR; and tumor necrosis factor gene, TNF). In this study, we confirmed the comorbidity of the three genes associated with AD. We further identified the comorbidity of two alleles in the MTHFR gene, C677T and A222V, significantly associated with Alzheimer's disease. This study provides an example of evidencebased analysis that is cost-effective and may be an effective approach to develop cure-alls for multiple diseases.

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