Understanding the role of transforming growth factor beta signalling and epigenomics in osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis with a high socioeconomic burden, with an incompletely understood etiology. Evidence suggests a role for the transforming growth factor beta (TGF-ß) signalling pathway and epigenomics in OA. The aim of this thesis was to understand the involvement of the TGF-ß pathway in OA and to determine the DNA methylation patterns of OA-affected cartilage as compared to the OA-free cartilage. First, I found that a common SNP in the BMP2 gene, a ligand in the Bone morphogenetic protein (BMP) subunit of TGF-ß pathway, was associated with OA in the Newfoundland population. I also showed a genetic association between SMAD3 - a signal transducer in the TGF-ß subunit of the TGF-ß signalling pathway - and the total radiographic burden of OA. I further demonstrated that SMAD3 is over-expressed in OA cartilage, suggesting an over activation of the TGF-ß signalling in OA. Next, I examined the connection of these genes in the regulation of matrix metallopeptidase 13 (MMP13) - an enzyme known to destroy extracellular matrix in OA cartilage - in the context of the TGF-ß signalling. The analyses showed that TGF-ß, MMP13, and SMAD3 were overexpressed in OA cartilage, whereas the expression of BMP2 was significantly reduced. The expression of TGF-ß was positively correlated with that of SMAD3 and MMP13, suggesting that TGF-ß signalling is involved in up-regulation of MMP13. This regulation, however, appears not to be controlled by SMAD3 signals, possibly due to the involvement of collateral signalling, and to be suppressed by BMP regulation in healthy cartilage, whose levels were reduced in end-stage OA. In a genome-wide DNA methylation analysis, I reported CpG sites differentially methylated in OA and showed that the cartilage methylome has a potential to distinguish between OA-affected and non-OA cartilage. Functional clustering analysis of the genes harbouring differentially methylated loci revealed that they are enriched in the skeletal system morphogenesis pathway, which could be a potential candidate for further OA studies. Overall, the findings from the present thesis provide evidence that the TGF-ß signalling pathway is associated with the development of OA, and epigenomics might be involved as a potential mechanism in OA

Diagnostic utility of genome-wide dna methylation analysis in mendelian neurodevelopmental disorders

Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine

Glucose-induced, duration-dependent genome-wide DNA methylation changes in human endothelial cells

DNA methylation, a critical epigenetic mechanism, plays an important role in governing gene expressions during biological processes such as aging, which is well known to be accelerated in hyperglycemia (diabetes). In the present study, we investigated the effects of glucose on whole genome DNA methylation in small [human retinal microvascular endothelial cells (HRECs)] and large [human umbilical vein endothelial cells (HUVECs)] vessel endothelial cell (EC) lines exposed to basal or high glucose-containing media for variable lengths of time. Using the Infinium EPIC array, we obtained 773,133 CpG sites (probes) for analysis. Unsupervised clustering of the top 5% probes identified four distinct clusters within EC groups, with significant methylation differences attributed to EC types and the duration of cell culture rather than glucose stimuli alone. When comparing the ECs incubated for 2 days versus 7 days, hierarchical clustering analyses [methylation change \u3e10% and false discovery rate (FDR) \u3c0.05] identified 17,354 and 128 differentially methylated CpGs for HUVECs and HRECs, respectively. Predominant DNA hypermethylation was associated with the length of culture and was enriched for gene enhancer elements and regions surrounding CpG shores and shelves. We identified 88 differentially methylated regions (DMRs) for HUVECs and 8 DMRs for HRECs (all FDR \u3c0.05). Pathway enrichment analyses of DMRs highlighted involvement of regulators of embryonic development (i.e., HOX genes) and cellular differentiation [transforming growth factor- (TGF-) family members]. Collectively, our findings suggest that DNA methylation is a complex process that involves tightly coordinated, cell-specific mechanisms. Such changes in methylation overlap genes critical for cellular differentiation and embryonic development

Low density lipoprotein cholesterol control status among Canadians at risk for cardiovascular disease: findings from the Canadian Primary Care Sentinel Surveillance Network Database

Background To determine the prevalence of uncontrolled LDL-C in patients with high cardiovascular disease (CVD) risks across Canada and to examine its related factors. Methods Non-pregnant adults >20 years-old, who had a lipid test completed between January 1, 2009 and December 31, 2011 and were included in the Canadian Primary Care Surveillance Network (CPCSSN) database were studied. The Framingham-Risk-Score was calculated to determine the risk levels. A serum LDL-C level of >2.0 mmol/L was considered as being poorly controlled. Patients with a previous record of a cerebrovascular accident, peripheral artery disease, or an ischemic heart disease were regarded as those under secondary prevention. Logistic regression modeling was performed to examine the factors associated with the LDL-C control. Results A total of 6,405 high-risk patients were included in the study and, of this population, 68 % had a suboptimal LDL-C, which was significantly associated with the female gender (OR: 3.26; 95 % CI: 2.63–4.05, p < 0.0001) and no medication therapy (OR: 6.31, 95 % CI: 5.21–7.65, p < 0.0001). Those with comorbidities of diabetes, hypertension, obesity, and smokers had a better LDL-C control. Rural residents (OR: 0.64, 95 % CI: 0.52–0.78, p < 0.0001), and those under secondary prevention (OR: 0.42; 95 % CI: 0.35–0.51, p < 0.0001), were also more likely to have a better LDL-C control. Conclusion A high proportion of high-cardiac risk patients in Canadian primary care settings have suboptimal LDL-C control. A lack of medication therapy appears to be the major contributing factor to this situation

Genomic DNA Methylation-Derived Algorithm Enables Accurate Detection of Malignant Prostate Tissues.

Introduction: The current methodology involving diagnosis of prostate cancer (PCa) relies on the pathology examination of prostate needle biopsies, a method with high false negative rates partly due to temporospatial, molecular, and morphological heterogeneity of prostate adenocarcinoma. It is postulated that molecular markers have a potential to assign diagnosis to a considerable portion of undetected prostate tumors. This study examines the genome-wide DNA methylation changes in PCa in search of genomic markers for the development of a diagnostic algorithm for PCa screening. Methods: Archival PCa and normal tissues were assessed using genomic DNA methylation arrays. Differentially methylated sites and regions (DMRs) were used for functional assessment, gene-set enrichment and protein interaction analyses, and examination of transcription factor-binding patterns. Raw signal intensity data were used for identification of recurrent copy number variations (CNVs). Non-redundant fully differentiating cytosine-phosphate-guanine sites (CpGs), which did not overlap CNV segments, were used in an L1 regularized logistic regression model (LASSO) to train a classification algorithm. Validation of this algorithm was performed using a large external cohort of benign and tumor prostate arrays. Results: Approximately 6,000 probes and 600 genomic regions showed significant DNA methylation changes, primarily involving hypermethylation. Gene-set enrichment and protein interaction analyses found an overrepresentation of genes related to cell communications, neurogenesis, and proliferation. Motif enrichment analysis demonstrated enrichment of tumor suppressor-binding sites nearby DMRs. Several of these regions were also found to contain copy number amplifications. Using four non-redundant fully differentiating CpGs, we trained a classification model with 100% accuracy in discriminating tumors from benign samples. Validation of this algorithm using an external cohort of 234 tumors and 92 benign samples yielded 96% sensitivity and 98% specificity. The model was found to be highly sensitive to detect metastatic lesions in bone, lymph node, and soft tissue, while being specific enough to differentiate the benign hyperplasia of prostate from tumor. Conclusion: A considerable component of PCa DNA methylation profile represent driver events potentially established/maintained by disruption of tumor suppressor activity. As few as four CpGs from this profile can be used for screening of PCa

MALAT1: An Epigenetic Regulator of Inflammation in Diabetic Retinopathy

Despite possessing limited protein-coding potential, long non-coding RNAs (lncRNAs) have been implicated in a myriad of pathologic conditions. Most well documented in cancer, one prominent intergenic lncRNA known as MALAT1 is notorious for its role in impacting epigenetic mechanisms. In this study, we established a novel epigenetic paradigm for MALAT in diabetic retinopathy (DR) by employing siRNA-mediated MALAT1 knockdown in human retinal endothelial cells (HRECs), a Malat1 knockout animal model, vitreous humor from diabetic patients, pharmacological inhibitors for histone and DNA methylation, RNA immunoprecipitation, western blotting, and a unique DNA methylation array to determine glucose-related alterations in MALAT1. Our findings indicated that MALAT1 is capable of impacting the expressions of inflammatory transcripts through its association with components of the PRC2 complex in diabetes. Furthermore, the vitreous humors from diabetic patients revealed increased expressions of MALAT1, TNF-α, and IL-6. Intriguingly, our DNA methylation array demonstrated that transient high glucose exposure in HRECs does not contribute to significant methylation alterations at CpG sites across the MALAT1 gene. However, global inhibition of DNA methyltransferases induced significant increases in MALAT1 and associated inflammatory transcripts in HRECs. Our findings collectively demonstrate the importance of MALAT1 in inflammation and epigenetic regulation in DR

The long non-coding RNA HOTAIR is a critical epigenetic mediator of angiogenesis in diabetic retinopathy

PURPOSE. Diabetic retinopathy (DR) remains a pressing issue worldwide. Abnormal angiogenesis is a distinct vascular lesion in DR, and research has established that vascular endothelial growth factor A (VEGF-A) is a primary mediator of such changes. However, limitations in current anti-VEGF therapies suggest that our understanding of molecular networks underlying ocular angiogenesis remains far from complete. Based on our long non-coding RNA (lncRNA) array analyses, HOX antisense intergenic RNA (HOTAIR) was identified as one of the top upregulated lncRNAs in high glucose-cultured human retinal endothelial cells (HRECs). Given the well-documented roles of HOTAIR in cancer, no studies have examined the epigenetic implications of HOTAIR in DR, and we investigated such relationships herein. METHODS. We used HRECs exposed to various glucose concentrations and epigenetic modulators to examine HOTAIR, angiogenic, and DR-related molecular markers. Oxidative stress, angiogenesis, and mitochondrial dysfunction were assessed. Retinal tissues of diabetic rodents and the vitreous humor and serum of patients with proliferative DR were also investigated. RESULTS. Hyperglycemia significantly augmented HOTAIR expression in HRECs and promoted angiogenesis, oxidative damage, and mitochondrial aberrations. Similarly, vitreous humor and serum from proliferative DR patients and retinas from diabetic animals demonstrated increased HOTAIR expression compared to non-diabetic controls. HOTAIR knockdown protected against glucose-induced increases of angiogenic and diabetesassociated molecules in the retina. Mechanistically, we showed that HOTAIR exerts its capabilities by preventing oxidative stress and modulating epigenetic pathways involving histone methylation, histone acetylation, DNA methylation, and transcription factors. CONCLUSIONS. Our findings suggest that HOTAIR is a critical lncRNA in the pathogenesis of DR and may potentially be important for diagnostic and therapeutic targeting

Peripheral Blood Epi-Signature of Claes-Jensen Syndrome Enables Sensitive and Specific Identification of Patients and Healthy Carriers with Pathogenic Mutations in KDM5C.

Background: Claes-Jensen syndrome is an X-linked inherited intellectual disability caused by mutations in the KDM5C gene. Kdm5c is a histone lysine demethylase involved in histone modifications and chromatin remodeling. Males with hemizygous mutations in KDM5C present with intellectual disability and facial dysmorphism, while most heterozygous female carriers are asymptomatic. We hypothesized that loss of KDM5C function may influence other components of the epigenomic machinery including DNA methylation in affected patients. Results: Genome-wide DNA methylation analysis of 7 male patients affected with Claes-Jensen syndrome and 56 age- and sex-matched controls identified a specific DNA methylation defect (epi-signature) in the peripheral blood of these patients, including 1769 individual CpGs and 9 genomic regions. Six healthy female carriers showed less pronounced but distinctive changes in the same regions enabling their differentiation from both patients and controls. Highly specific computational model using the most significant methylation changes demonstrated 100% accuracy in differentiating patients, carriers, and controls in the training cohort, which was confirmed on a separate cohort of patients and carriers. The 100% specificity of this unique epi-signature was further confirmed on additional 500 unaffected controls and 600 patients with intellectual disability and developmental delay, including other patient cohorts with previously described epi-signatures. Conclusion: Peripheral blood epi-signature in Claes-Jensen syndrome can be used for molecular diagnosis and carrier identification and assist with interpretation of genetic variants of unknown clinical significance in the KDM5Cgene

Genetic and epigenetic profiling of BRCA1/2 in ovarian tumors reveals additive diagnostic yield and evidence of a genomic BRCA1/2 DNA methylation signature

Poly-ADP-ribose-polymerase inhibitor (PARPi) treatment is indicated for advanced-stage ovarian tumors with BRCA1/2 deficiency. The “BRCAness” status is thought to be attributed to a tumor phenotype associated with a specific epigenomic DNA methylation profile. Here, we examined the diagnostic impact of combined BRCA1/2 sequence, copy number, and promoter DNA methylation analysis, and evaluated whether genomic DNA methylation patterns can predict the BRCAness in ovarian tumors. DNA sequencing of 172 human tissue samples of advanced-stage ovarian adenocarcinoma identified 36 samples with a clinically significant tier 1/2 sequence variants (point mutations and in/dels) and 9 samples with a CNV causing a loss of function in BRCA1/2. DNA methylation analysis of the promoter of BRCA1/2 identified promoter hypermethylation of BRCA1 in two mutation-negative samples. Computational modeling of genome-wide methylation markers, measured using Infinium EPIC arrays, resulted in a total accuracy of 0.75, sensitivity: 0.83, specificity: 0.64, positive predictive value: 0.76, negative predictive value: 0.74, and area under the receiver’s operating curve (AUC): 0.77, in classifying tumors harboring a BRCA1/2 defect from the rest. These findings indicate that the assessment of CNV and promoter DNA methylation in BRCA1/2 increases the cumulative diagnostic yield by 10%, compared with the 20% yield achieved by sequence variant analysis alone. Genomic DNA methylation data can partially predict BRCAness in ovarian tumors; however, further investigation in expanded BRCA1/2 cohorts is needed, and the effect of other double strand DNA repair gene defects in these tumors warrants further investigations

Six-year time-trend analysis of dyslipidemia among adults in Newfoundland and Labrador: findings from the laboratory information system between 2009 and 2014

Background: Dyslipidemia, an increased level of total cholesterol (TC), triglycerides (TG), low-density-lipoprotein cholesterol (LDL-C) and decreased level of high-density-lipoprotein cholesterol (HDL-C), is one of the most important risk factors for cardiovascular disease. We examined the six-year trend of dyslipidemia in Newfoundland and Labrador (NL), a Canadian province with a historically high prevalence of dyslipidemia. Methods: A serial cross-sectional study on all of the laboratory lipid tests available from 2009 to 2014 was performed. Dyslipidemia for every lipid component was defined using the Canadian Guidelines for the Diagnosis and Treatment of Dyslipidemia. The annual dyslipidemia rates for each component of serum lipid was examined. A fixed and random effect model was applied to adjust for confounding variables (sex and age) and random effects (residual variation in dyslipidemia over the years and redundancies caused by individuals being tested multiple times during the study period). Results: Between 2009 and 2014, a total of 875,208 records (mean age: 56.9 ± 14.1, 47.6% males) containing a lipid profile were identified. The prevalence of HDL-C and LDL-C dyslipidemia significantly decreased during this period (HDL-C: 35.8% in 2009 [95% CI 35.5-36.1], to 29.0% in 2014 [95% CI: 28.8-29.2], P = 0.03, and LDL-C: 35.2% in 2009 [95% CI: 34.9-35.4] to 32.1% in 2014 [95% CI: 31.9-32.3], P = 0.02). A stratification by sex, revealed no significant trend for any lipid element in females; however, in men, the previously observed trends were intensified and a new decreasing trend in dyslipidemia of TC was appeared (TC: 34.1% [95% CI 33.7-34.5] to 32.3% [95%CI: 32.0-32.6], p < 0.02, HDL-C: 33.8% (95%CI: 33.3-34.2) to 24.0% (95% CI: 23.7-24.3)], P < 0.01, LDL-C: 32.9% (95%CI:32.5-33.3) to 28.6 (95%CI: 28.3-28.9), P < 0.001). Adjustment for confounding factors and removing the residual noise by modeling the random effects did not change the significance. Conclusion: This study demonstrates a significant downward trend in the prevalence of LDL-C, HDL-C, and TC dyslipidemia, exclusively in men. These trends could be the result of males being the primary target for cardiovascular risk management