Evaluation of MMP1 and MMP3 gene polymorphisms in exfoliation syndrome and exfoliation glaucoma

Purpose: To investigate possible genetic associations of matrix metalloproteinase-1 (MMP1) and MMP3 gene polymorphisms with exfoliation syndrome (XFS) with (XFS/+G) and without (XFS/-G) glaucoma in a cohort of Greek patients. Methods: A total of 182 unrelated Greek patients with XFS, including 92 patients with XFS/+G, and 214 unrelated age- and gender-matched controls were enrolled in the study. MMP1-1607 1G/2G (rs1799750) and MMP3-1171 5A/6A (rs3025058) polymorphisms were determined using standard PCR/restriction fragment length polymorphism methods. Differences in allele and genotype distributions were analyzed using logistic regression. Results: The distribution of genotypes and alleles in MMP1 and MMP3 polymorphisms was not significantly different between cases with exfoliation syndrome, with or without glaucoma, and controls. However, the allele contrast for the MMP1 variant showed a trend for a significant association with XFS/-G (Odds Ratio=1.47 [1.03-2.10]), since after correction for multiple comparisons, this association was no longer statistically significant. Conclusions: Our study provided some evidence of a possible role of the MMP1 variant in the development of exfoliation syndrome in Greek patients

New Sequence Variants in HLA Class II/III Region Associated with Susceptibility to Knee Osteoarthritis Identified by Genome-Wide Association Study

Osteoarthritis (OA) is a common disease that has a definite genetic component. Only a few OA susceptibility genes that have definite functional evidence and replication of association have been reported, however. Through a genome-wide association study and a replication using a total of ∼4,800 Japanese subjects, we identified two single nucleotide polymorphisms (SNPs) (rs7775228 and rs10947262) associated with susceptibility to knee OA. The two SNPs were in a region containing HLA class II/III genes and their association reached genome-wide significance (combined P = 2.43×10−8 for rs7775228 and 6.73×10−8 for rs10947262). Our results suggest that immunologic mechanism is implicated in the etiology of OA

Translation of clinical problems in osteoarthritis into pathophysiological research goals

Osteoarthritis (OA) accounts for more disability among the elderly than any other disease and is associated with an increased mortality rate. The prevalence in Europe will rise in the future since this continent has a strongly ageing population and an obesity epidemic; obesity and age both being major risk factors for OA. No adequate therapeutic options, besides joint replacement, are available, although they are greatly needed and should be acquired by adequate research investments. However, the perspective on OA from a researcher's point of view is not always aligned with the perspective of a patient with OA. Researchers base their views on OA mainly on abnormalities in structure and function while patients consider OA as a collection of symptoms. In this viewpoint paper, we discuss the possibility of translating the most important clinical problems into pathophysiological research goals to facilitate the translation from bench to bedside and vice versa. This viewpoint is the outcome of a dialogue within the 'European League Against Rheumatism study group on OA' and People with Arthritis/Rheumatism across Europe (PARE) representatives

Central Role of SREBP-2 in the Pathogenesis of Osteoarthritis

Background: Recent studies have implied that osteoarthritis (OA) is a metabolic disease linked to deregulation of genes involved in lipid metabolism and cholesterol efflux. Sterol Regulatory Element Binding Proteins (SREBPs) are transcription factors regulating lipid metabolism with so far no association with OA. Our aim was to test the hypothesis that SREBP-2, a gene that plays a key role in cholesterol homeostasis, is crucially involved in OA pathogenesis and to identify possible mechanisms of action. Methodology/Principal Findings: We performed a genetic association analysis using a cohort of 1,410 Greek OA patients and healthy controls and found significant association between single nucleotide polymorphism (SNP) 1784G>C in SREBP-2 gene and OA development. Moreover, the above SNP was functionally active, as normal chondrocytes’ transfection with SREBP-2-G/C plasmid resulted in interleukin-1β and metalloproteinase-13 (MMP-13) upregulation. We also evaluated SREBP-2, its target gene 3-hydroxy-3-methylglutaryl-coenzymeA reductase (HMGCR), phospho-phosphoinositide3-kinase (PI3K), phospho-Akt, integrin-alphaV (ITGAV) and transforming growth factor-$\beta$ (TGF-$\beta$) mRNA and protein expression levels in osteoarthritic and normal chondrocytes and found that they were all significantly elevated in OA chondrocytes. To test whether TGF-$\beta$ alone can induce SREBP-2, we treated normal chondrocytes with TGF-$\beta$ and found significant upregulation of SREBP-2, HMGCR, phospho-PI3K and MMP-13. We also showed that TGF-$\beta$ activated aggrecan (ACAN) in chondrocytes only through Smad3, which interacts with SREBP-2. Finally, we examined the effect of an integrin inhibitor, cyclo-RGDFV peptide, on osteoarthritic chondrocytes, and found that it resulted in significant upregulation of ACAN and downregulation of SREBP-2, HMGCR, phospho-PI3K and MMP-13 expression levels. Conclusions/Significance: We demonstrated, for the first time, the association of SREBP-2 with OA pathogenesis and provided evidence on the molecular mechanism involved. We suggest that TGF-$\beta$ induces SREBP-2 pathway activation through ITGAV and PI3K playing a key role in OA and that integrin blockage may be a potential molecular target for OA treatment

Leptin as a critical regulator of hepatocellular carcinoma development through modulation of human telomerase reverse transcriptase

<p>Abstract</p> <p>Background</p> <p>Numerous epidemiological studies have documented that obesity is associated with hepatocellular carcinoma (HCC). The aim of this study was to investigate the biological actions regulated by leptin, the obesity biomarker molecule, and its receptors in HCC and the correlation between leptin and human telomerase reverse transcriptase (hTERT), a known mediator of cellular immortalization.</p> <p>Methods</p> <p>We investigated the relationship between leptin, leptin receptors and hTERT mRNA expression in HCC and healthy liver tissue samples. In HepG2 cells, chromatin immunoprecipitation assay was used to study signal transducer and activator of transcription-3 (STAT3) and myc/mad/max transcription factors downstream of leptin which could be responsible for hTERT regulation. Flow cytometry was used for evaluation of cell cycle modifications and MMP1, 9 and 13 expression after treatment of HepG2 cells with leptin. Blocking of leptin's expression was achieved using siRNA against leptin and transfection with liposomes.</p> <p>Results</p> <p>We showed, for the first time, that leptin's expression is highly correlated with hTERT expression levels in HCC liver tissues. We also demonstrated in HepG2 cells that leptin-induced up-regulation of hTERT and TA was mediated through binding of STAT3 and Myc/Max/Mad network proteins on <it>hTERT </it>promoter. We also found that leptin could affect hepatocellular carcinoma progression and invasion through its interaction with cytokines and matrix mettaloproteinases (MMPs) in the tumorigenic microenvironment. Furthermore, we showed that histone modification contributes to leptin's gene regulation in HCC.</p> <p>Conclusions</p> <p>We propose that leptin is a key regulator of the malignant properties of hepatocellular carcinoma cells through modulation of hTERT, a critical player of oncogenesis.</p

Integrative MicroRNA and Proteomic Approaches Identify Novel Osteoarthritis Genes and Their Collaborative Metabolic and Inflammatory Networks

BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103) and proteins (PPARA, BMP7, IL1B) to be highly correlated with Body Mass Index (BMI). Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic and clinical data provides a detailed picture of how a network state is correlated with disease and furthermore leads to the development of new treatments. This strategy will help to improve the understanding of the pathogenesis of multifactorial diseases such as osteoarthritis and provide possible novel therapeutic targets

Common genetic variation in the Estrogen Receptor Beta (ESR2) gene and osteoarthritis: results of a meta-analysis

Background: The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis.Methods: In the discovery study, the Rotterdam Study-I, 7 single nucleotide polymorphisms (SNPs) were genotyped and tested for association with hip (284 cases, 2772 controls), knee (665 cases, 2075 controls), and hand OA (874 cases, 2184 controls) using an additive model. In the replication stage one SNP (rs1256031) was tested in an additional 2080 hip, 1318 knee and 557 hand OA cases and 4001, 2631 and 1699 controls respectively. Fixed- and random-effects meta-analyses were performed over the complete dataset including 2364 hip, 1983 knee and 1431 hand OA cases and approximately 6000 controls.Results: The C allele of rs1256031 was associated with a 36% increased odds of hip OA in women of the Rotterdam Study-I (OR 1.36, 95% CI 1.08-1.70, p = 0.009). Haplotype analysis and analysis of knee- and hand OA did not give additional information. With the replication studies, the meta-analysis did not show a significant effect of this SNP on hip OA in the total population (OR 1.06, 95% CI 0.99-1.15, p = 0.10). Stratification according to gender did not change the results. In this study, we had 80% power to detect an odds ratio of at least 1.14 for hip OA (α = 0.05).Conclusion: This study showed that common genetic variation in the ESR2 gene is not likely to influence the risk of osteoarthritis with effects smaller than a 13% increase

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Funding Information: T.R.G. and J.Z. receive research funding from GlaxoSmithKline. T.R.G. receives research funding from Biogen. U.S., K.S., L. Stefánsdóttir, G.B., S.H.L., U.T., and G. T. are employed by deCODE genetics/Amgen Inc. A.M.V. is a consultant for Zoe Global Ltd. All other authors report no competing interests. All Regeneron Genetics Center banner authors are current employees and/or stockholders of Regeneron Pharmaceuticals. Funding Information: We thank Nigel W. Rayner and Ahmed Elhakeem for their input. This research was conducted using the UK Biobank Resource under application numbers 9979 and 23359. G.D.S. and T.R.G. work in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol MC_UU_00011/1&4. A.M.V. is funded by the NIHR Nottingham BRC. J.Z. is funded by a Vice-Chancellor Fellowship from the University of Bristol. This research was also funded by the UK Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/4). Study design and project coordination, E. Zeggini; Writing Group, U.S. J.B.J.v.M. J.M.W. M.T.M.L. K.S.E.C. L.S. C.G.B. K.H. Y.Z. R.C.d.A. L. Stef?nsd?ttir, E. Zeggini, A.P.M. G.T. P.C.S. J.Z. and T.R.G.; Core Analyses, C.G.B. K. Hatzikotoulas, L. Southam, L. Stef?nsd?ttir, Y.Z. R.C.d.A. T.T.W. J.Z. A.H. M.T.-L. and J.M.W.; Individual Study Design and Principal Investigators, E. Zeggini, U.S. J.B.J.v.M. M.T.M.L. I.M. J.M.W. T.E. K. Hveem, S.I. K.S.E.C. A.T. A.M.V. K.S. P.E.S. P.C. G.D.S. J.H.T. T.R.G. S.A.L. G.C.B. A.G.U. U.T. P.K. J.H.K. arcOGEN Consortium, HUNT All-In Pain, ARGO Consortium, and Regeneron Genetics Center; Analyses, Genotyping, and Phenotyping in Individual Studies, C.G.B. K.H. L. Southam, J.M.W. L. Stef?nsd?ttir, Y.Z. R.C.d.A. T.T.W. J.Z. A.H. M.T.-L. A.H.S. C.T. E. Zengini, A.B. G.T. G.B. H.J. T.I. R.M. H.T. M.K. M.T. R.R.G.H.H.N. M.M. J.P.Y.C. D.S. J.-A.Z. A.L. M.B.J. L.F.T. B.W. M.E.G. J.S. M.S. G.A. A.G. S.H.L. arcOGEN Consortium, HUNT All-In Pain, ARGO Consortium, and Regeneron Genetics Center. All authors contributed to the final version of the manuscript. T.R.G. and J.Z. receive research funding from GlaxoSmithKline. T.R.G. receives research funding from Biogen. U.S. K.S. L. Stef?nsd?ttir, G.B. S.H.L. U.T. and G. T. are employed by deCODE genetics/Amgen Inc. A.M.V. is a consultant for Zoe Global Ltd. All other authors report no competing interests. All Regeneron Genetics Center banner authors are current employees and/or stockholders of Regeneron Pharmaceuticals. Funding Information: We thank Nigel W. Rayner and Ahmed Elhakeem for their input. This research was conducted using the UK Biobank Resource under application numbers 9979 and 23359. G.D.S. and T.R.G. work in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol MC_UU_00011/1&4. A.M.V. is funded by the NIHR Nottingham BRC . J.Z. is funded by a Vice-Chancellor Fellowship from the University of Bristol . This research was also funded by the UK Medical Research Council Integrative Epidemiology Unit ( MC_UU_00011/4 ). Publisher Copyright: © 2021 The AuthorsOsteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.Peer reviewe