The effect of non-steroidal anti-inflammatory drugs on the osteogenic activity in osseointegration: a systematic review

Non-steroidal anti-inflammatory drugs are commonly used in implant dentistry for management of post-operative pain. The objective of this systematic review was to analyse the effect of non-steroidal anti-inflammatory drugs on the osteogenic activity of osteoblasts with an emphasis on its effect on osseointegration. A systematic literature search for in vitro, animal models, and clinical trials was conducted using Ovid, PubMed, Scopus, and Web of Science databases. Articles published since the introduction of selective COX-2 inhibitors, between January 1999 and July 2018, were selected. The integrated search followed the PRISMA statement with the following key terms: non-steroidal anti-inflammatory drug/s, titanium, osseointegration, and osteoblast. The review is registered at PROSPERO database: CRD42016051448. The titles and abstracts of each research article in the initial search (n = 875) were independently screened by two reviewers. A third independent reviewer reviewed the articles that were included by one but excluded by the other reviewer. This resulted in the cataloguing of 79 full-text manuscripts where the articles were assessed for the following criteria: the study investigates the effects of NSAIDs on osteoblasts, explores the COX pathway and its effect on osteogenic activity, and compares the effects of NSAIDs on osteoblasts with a control group. A total of 13 articles have been included for qualitative synthesis. There is a lack of consensus in the literature to explicitly conclude that there is a relationship between the use of post-operative NSAIDs and failed osseointegration; however, osseointegration does not appear to be negatively affected by NSAIDs in the human clinical studies

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Effect of nonsteroidal anti-inflammatory drugs on the osteogenic activity of osteoprogenitor cells cultured on titanium surfaces

Purpose: The purpose of this study was to investigate the effects of celecoxib and ibuprofen on the proliferation, viability, and migration of MC3T3-E1 cells cultured on titanium surfaces. Materials and Methods: MC3T3-E1 cells were cultured on sandblasted titanium disks and allocated to one of the following six groups: (a) control (untreated); (b) celecoxib (5 µM and 10 µM); (c) ibuprofen (5 µM and 10 µM); and (d) prostaglandin E2 (10 µM). Proliferation of attached cells was assessed over 9 days using an alamarBlue assay. A trypan blue exclusion test was conducted to assess cell viability; the relative percentages of live and dead cells were quantified using a hemocytometer over 2 days. A Boyden-Chamber Assay was utilized to assess cell migration over 3 days. Results: The proliferation of cells treated with any intervention was not significantly different than that of the untreated group throughout the treatment period. However, celecoxib and ibuprofen significantly decreased the percentage of viable cells in a dose-dependent manner. Specifically, celecoxib (10 µM) and ibuprofen (5 µM and 10 µM, respectively) on day 1 and celecoxib (10 µM) on day 2 showed significantly higher percentages of dead cells compared to the untreated cells. There was a significant increase in migration of cells treated with ibuprofen (5 µM) compared to untreated cells on day 1; however, the migration of cells treated with any of the interventions was not significantly different from that of untreated cells on day 3. Conclusion: Nonsteroidal anti-inflammatory drugs at therapeutic doses did not significantly affect osteoblast proliferation and migration. However, higher dosages of celecoxib (10 µM) significantly reduced the cell viability and therefore can potentially affect the process of osseointegration

The effect of non-steroidal anti-inflammatory drugs on the osteogenic activity in osseointegration: a systematic review

Non-steroidal anti-inflammatory drugs are commonly used in implant dentistry for management of post-operative pain. The objective of this systematic review was to analyse the effect of non-steroidal anti-inflammatory drugs on the osteogenic activity of osteoblasts with an emphasis on its effect on osseointegration. A systematic literature search for in vitro, animal models, and clinical trials was conducted using Ovid, PubMed, Scopus, and Web of Science databases. Articles published since the introduction of selective COX-2 inhibitors, between January 1999 and July 2018, were selected. The integrated search followed the PRISMA statement with the following key terms: non-steroidal anti-inflammatory drug/s, titanium, osseointegration, and osteoblast. The review is registered at PROSPERO database: CRD42016051448. The titles and abstracts of each research article in the initial search (n = 875) were independently screened by two reviewers. A third independent reviewer reviewed the articles that were included by one but excluded by the other reviewer. This resulted in the cataloguing of 79 full-text manuscripts where the articles were assessed for the following criteria: the study investigates the effects of NSAIDs on osteoblasts, explores the COX pathway and its effect on osteogenic activity, and compares the effects of NSAIDs on osteoblasts with a control group. A total of 13 articles have been included for qualitative synthesis. There is a lack of consensus in the literature to explicitly conclude that there is a relationship between the use of post-operative NSAIDs and failed osseointegration; however, osseointegration does not appear to be negatively affected by NSAIDs in the human clinical studies

Dental implant placement in patients with a history of medications related to osteonecrosis of the jaws: a systematic review

The present systematic review evaluates the safety of placing dental implants in patients with a history of antiresorptive or antiangiogenic drug therapy. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed. PubMed, Cochrane Central Register of Controlled Trials, Scopus, Web of Science, and OpenGrey databases were used to search for clinical studies (English only) to July 16, 2019. Study quality was assessed regarding randomization, allocation sequence concealment, blinding, incomplete outcome data, selective outcome reporting, and other biases using a modified Newcastle-Ottawa scale and the Joanna Briggs Institute critical appraisal checklist for case series. A broad search strategy resulted in the identification of 7542 studies. There were 28 studies reporting on bisphosphonates (5 cohort, 6 case control, and 17 case series) and 1 study reporting on denosumab (case series) that met the inclusion criteria and were included in the qualitative synthesis. The quality assessment revealed an overall moderate quality of evidence among the studies. Results demonstrated that patients with a history of bisphosphonate treatment for osteoporosis are not at increased risk of implant failure in terms of osseointegration. However, all patients with a history of bisphosphonate treatment, whether taken orally for osteoporosis or intravenously for malignancy, appear to be at risk of “implant surgery-triggered” medication-related osteonecrosis of the jaw (MRONJ). In contrast, the risk of MRONJ in patients treated with denosumab for osteoporosis was found to be negligible. In conclusion, general and specialist dentists should exercise caution when planning dental implant therapy in patients with a history of bisphosphonate and denosumab drug therapy. Importantly, all patients with a history of bisphosphonates are at risk of MRONJ, necessitating this to be included in the informed consent obtained before implant placement

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care