Last update 01 Nov 2024

MMP3 x MMP1 x MMP9

Last update 01 Nov 2024

Basic Info

Related Targets

MMP3MMP1MMP9

Drugs associated with MMP3 x MMP1 x MMP9

KBR-7785

Target

MMP1 x MMP3 x MMP9

Mechanism

MMP1 inhibitors [+2]

Active Org.-

Originator Org.

Organon KK

Active Indication-

Inactive Indication

Diabetes Mellitus, Type 2 [+2]

Drug Highest PhaseDiscontinued

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with MMP3 x MMP1 x MMP9

100 Translational Medicine associated with MMP3 x MMP1 x MMP9

0 Patents (Medical) associated with MMP3 x MMP1 x MMP9

800

Literatures (Medical) associated with MMP3 x MMP1 x MMP9

01 Dec 2024·CARTILAGE

Low-Grade Inflammatory Mediators and Metalloproteinases Yield Synchronous and Delayed Responses to Mechanical Joint Loading

Article

Author: Mao, Michelle ; Hutcherson, Conner W. ; Dhaher, Yasin Y. ; Thakur, Bhaskar

Objective Mechanical loading is an essential factor for the maintenance of joint inflammatory homeostasis and the sensitive catabolic-anabolic signaling cascade involved in maintaining cartilage tissue health. However, abnormal mechanical loading of the joint structural tissues can propagate joint metabolic dysfunction in the form of low-grade inflammation. To date, few studies have attempted to delineate the early cascade responsible for the initiation and perpetuation of stress-mediated inflammation and cartilage breakdown in human joints. Design Fifteen healthy human male participants performed a walking paradigm on a cross-tilting treadmill platform. Blood samples were collected before exercise, after 30 minutes of flat walking, after 30 minutes of tilted walking, and after an hour of rest. Serum concentrations of the following biomarkers were measured: interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor alpha (TNF)-α, matrix metalloproteinase (MMP)-1, MMP-3, MMP-9, MMP-13, transforming growth factor beta (TGF)-β, tissue inhibitor of matrix metalloproteinase 1 (TIMP)-1, and cartilage oligomeric protein (COMP). Results Luminex Multiplex analysis of serum showed increased concentrations of COMP, IL-1β, TNF-α, IL-10, and TGF-β from samples collected after flat and cross-tilted treadmill walking compared to baseline. Serum concentrations of MMP-1 and MMP-13 also increased, but primarily in samples collected after tilted walking. Pearson’s correlation analysis showed positive correlations between the expression of COMP, TNF-α, IL-10, and MMP-13 at each study timepoint. Conclusion Stress-mediated increases in serum COMP during exercise are associated with acute changes in pro and anti-inflammatory molecular activity and subsequent changes in molecules linked to joint tissue remodeling and repair.

01 Oct 2024·Cytokine

Inflammatory biomarkers and long-term outcome in young patients three months after a first myocardial infarction

Article

Author: Silveira, Angela ; Cederström, Sofia ; Tornvall, Per ; Samnegård, Ann ; Jernberg, Tomas ; Johansson, Fredrik ; Lundman, Pia

BACKGROUNDStudies on predictive value of circulating inflammatory biomarkers after myocardial infarction (MI) have often been limited by blood sampling only in an acute setting and short follow-up time. We aimed to compare the long-term predictive value of nine inflammatory biomarkers, known to be involved in atherosclerosis, in young patients investigated three months after a first-time MI.METHODSNine biomarkers (high-sensitivity C-reactive protein, interleukin (IL)-6, IL-18, monocyte chemoattractant protein-1, matrix metalloproteinase (MMP)-1, MMP-3, MMP-9, serum amyloid A and tumor necrosis factor-alfa) were sampled in 382 young (<60 years) patients and in age and sex-matched controls, three months after a first-time MI between 1996 and 2000. Swedish national patient registers were used to determine cardiovascular (CV) outcomes during 20 years of follow-up.RESULTSIn cases, random forest models identified IL-6 as the most important predictor of the primary composite endpoint of death, heart failure (HF) or MI hospitalization, and the separate endpoints death and HF hospitalization. IL-18 was the most important predictor of MI hospitalization. In a Cox regression, the highest tertile of IL-6 was associated with the composite endpoint (HR (95% CI) 1.91 (1.31-2.79)), death (2.38 (1.42-3.98)) and HF hospitalization (2.70 (1.32-5.50)), when adjusting for age, sex and CV risk factors. The highest tertile of IL-18 was associated with MI hospitalization (2.31 (1.08-4.91)) when severity of coronary atherosclerosis was added to the same type of model.CONCLUSIONSWhen nine inflammatory markers involved in atherosclerosis were analyzed three months after the acute event in young MI patients, IL-6 and IL-18 were the most important biomarkers to predict long-term CV outcomes during 20 years of follow-up.

23 Sep 2024·Progress in orthodontics

Integrated bioinformatic analysis of protein landscape in gingival crevicular fluid unveils sequential bioprocess in orthodontic tooth movement.

Review

Author: Zhao, Zhihe ; Mei, Li ; Zheng, Wei ; Chen, Yao ; Li, Yu ; Qian, Yuran ; Zhou, Xinlianyi

BACKGROUNDThe biological mechanisms driving orthodontic tooth movement (OTM) remain incompletely understood. Gingival crevicular fluid (GCF) is an important indicator of the periodontal bioprocess, providing valuable cues for probing the molecular mechanisms of OTM.METHODSA rigorous review of the clinical studies over the past decade was conducted after registering the protocol with PROSPERO and adhering to inclusion criteria comprising human subjects, specified force magnitudes and force application modes. The thorough screening investigated differentially expressed proteins (DEPs) in GCF associated with OTM. Protein-protein interaction (PPI) analysis was carried out using the STRING database, followed by further refinement through Cytoscape to isolate top hub proteins.RESULTSA comprehensive summarization of the OTM-related GCF studies was conducted, followed by an in-depth exploration of biomarkers within the GCF. We identified 13 DEPs, including ALP, IL-1β, IL-6, Leptin, MMP-1, MMP-3, MMP-8, MMP-9, PGE₂, TGF-β1, TNF-α, OPG, RANKL. Bioinformatic analysis spotlighted the top 10 hub proteins and their interactions involved in OTM. Based on these findings, we have proposed a hypothetic diagram for the time-course bioprocess in OTM, which involves three phases containing sequential cellular and molecular components and their interplay network.CONCLUSIONSThis work has further improved our understanding to the bioprocess of OTM, suggesting biomarkers as potential modulating targets to enhance OTM, mitigate adverse effects and support real-time monitoring and personalized orthodontic cycles.

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