Dact1 is expressed during chicken and mouse skeletal myogenesis and modulated in human muscle diseases

Contriciani, Renata Erbert; Veiga, Fernanda Cristina da; Amaral, Mariana J. do; Castelucci, Bianca Gazieri; Sousa, Lizandra Maia de; Consonni, Sílvio Roberto; Collares-Buzato, Carla Beatriz; Mermelstein, Cláudia; Dietrich, Susanne; Alvares, Lúcia Elvira

doi:10.1016/j.cbpb.2021.110645

Cited by 5 publications

(2 citation statements)

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“…Remarkably, among the 261 proteins highlighted in our results, we observed a positive correlation between certain proteins and CpG sites located within genes involved in essential biological processes. For instance, we found proteins positively correlated with CpGs located in genes related to fatty acid metabolism, such as COMMD9 (involved in LDL regulation), 100 ARHGAP42 (associated with hypertension), 101 APOBEC1 (linked to weight loss and muscle development), 102 PTPRT, PTPRN2 (implicated in obesity), 103–106 and DACT1, DIO2, RPTOR, and PLEKHM3 (involved in muscle myogenesis and hypertrophy) 107–111 . Conversely, these proteins were negatively correlated with CpG sites located in genes such as KCNMA1, NOTCH1, CAMKK2 (related to skeletal muscle regeneration, proliferation, and differentiation), 112–117 DHRS3, DGKG, LPIN1, WNT5A (associated with obesity, metabolic syndrome, and lipid regulation), 118–120 LRRC2 (a mediator of mitochondrial and cardiac function), 121 and PDE4A (linked to diabetes) 122,123 .…”

Section: Discussionmentioning

confidence: 90%

“…For instance, we found proteins positively correlated with CpGs located in genes related to fatty acid metabolism, such as COMMD9 (involved in LDL regulation), 100 ARHGAP42 (associated with hypertension), 101 APOBEC1 (linked to weight loss and muscle development), 102 PTPRT, PTPRN2 (implicated in obesity), [103][104][105][106] and DACT1, DIO2, RPTOR, and PLEKHM3 (involved in muscle myogenesis and hypertrophy). [107][108][109][110][111] Conversely, these proteins were negatively correlated with CpG sites located in genes such as KCNMA1, NOTCH1, CAMKK2 (related to skeletal muscle regeneration, proliferation, and differentiation), [112][113][114][115][116][117] DHRS3, DGKG, LPIN1, WNT5A (associated with obesity, metabolic syndrome, and lipid regulation), [118][119][120] LRRC2 (a mediator of mitochondrial and cardiac function), 121 and PDE4A (linked to diabetes). 122,123 These associations provide valuable insights into the intricate relationships between specific genes, proteins, and exercise response.…”

Section: Discussionmentioning

confidence: 99%

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Methylome and proteome integration in human skeletal muscle uncover group and individual responses to high‐intensity interval training

Jacques,

Landen,

Romero

et al. 2023

The FASEB Journal

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Exercise is a major beneficial contributor to muscle metabolism, and health benefits acquired by exercise are a result of molecular shifts occurring across multiple molecular layers (i.e., epigenome, transcriptome, and proteome). Identifying robust, across‐molecular level targets associated with exercise response, at both group and individual levels, is paramount to develop health guidelines and targeted health interventions. Sixteen, apparently healthy, moderately trained (VO2 max = 51.0 ± 10.6 mL min−1 kg−1) males (age range = 18–45 years) from the Gene SMART (Skeletal Muscle Adaptive Responses to Training) study completed a longitudinal study composed of 12‐week high‐intensity interval training (HIIT) intervention. Vastus lateralis muscle biopsies were collected at baseline and after 4, 8, and 12 weeks of HIIT. DNA methylation (~850 CpG sites) and proteomic (~3000 proteins) analyses were conducted at all time points. Mixed models were applied to estimate group and individual changes, and methylome and proteome integration was conducted using a holistic multilevel approach with the mixOmics package. A total of 461 proteins significantly changed over time (at 4, 8, and 12 weeks), whilst methylome overall shifted with training only one differentially methylated position (DMP) was significant (adj.p‐value < .05). K‐means analysis revealed cumulative protein changes by clusters of proteins that presented similar changes over time. Individual responses to training were observed in 101 proteins. Seven proteins had large effect‐sizes >0.5, among them are two novel exercise‐related proteins, LYRM7 and EPN1. Integration analysis showed bidirectional relationships between the methylome and proteome. We showed a significant influence of HIIT on the epigenome and more so on the proteome in human muscle, and uncovered groups of proteins clustering according to similar patterns across the exercise intervention. Individual responses to exercise were observed in the proteome with novel mitochondrial and metabolic proteins consistently changed across individuals. Future work is required to elucidate the role of these proteins in response to exercise.

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