Genomic heterozygosity is associated with a lower risk of osteoarthritis.

BACKGROUND: Genomic heterozygosity has been shown to confer a health advantage in humans and play a protective role in complex diseases. Given osteoarthritis (OA) is a highly polygenic disease, we set out to determine if an association exists between OA and genomic heterozygosity. RESULTS: End-stage knee and hip OA patients and healthy controls were recruited from the Newfoundland and Labrador (NL) population. The Arthritis Research UK Osteoarthritis Genetics (arcOGEN) consortium database was utilized as a replication cohort. DNA was extracted from blood samples and genotyped. Individual rates of observed heterozygosity (HetRate) and heterozygosity excess (HetExcess) relative to the expected were mathematically derived, and standardized to a z-score. Logistic regression modeling was used to examine the association between OA and HetRate or HetExcess. A total of 559 knee and hip OA patients (mean age 66.5 years, body mass index (BMI) 33.7 kg/m2, and 55% females) and 118 healthy controls (mean age 56.4 years, BMI 29.5 kg/m2, and 59% female) were included in the NL cohort analysis. We found that OA had an inverse relationship with HetRate and HetExcess with odds ratios of 0.64 (95% CI: 0.45-0.91) and 0.65 (95% CI: 0.45-0.93) per standard deviation (SD), respectively. The arcOGEN data included 2,019 end-stage knee and hip OA patients and 2,029 healthy controls, validating our findings with HetRate and HetExcess odds ratios of 0.60 (95% CI: 0.56-0.64) and 0.44 (95% CI: 0.40-0.47) per SD, respectively. CONCLUSIONS: Our results are the first to clearly show evidence, from two separate cohorts, that reduced genomic heterozygosity confers a risk for the future development of OA.

Osteoarthritis year in review 2023: metabolite and protein biomarkers.

OBJECTIVE: To highlight the advances over the past year in metabolite/protein biomarkers for osteoarthritis (OA). METHOD: A literature search of five databases including PubMed, Web of Science, Scopus, Ovid Medline, and Embase was performed for studies on metabolite/protein/peptide/biochemical markers for OA published between April 1st, 2022 and March 31st, 2023. Records were then screened to include only original research articles using directly collected human specimens, in English language, and with full text available. Data from eligible studies were systematically extracted and summarized. RESULTS: A total of 1600 unique records were extracted, out of which 46 fulfilled the inclusion criteria and were used for data extraction. Forty-one of these 46 studies focused on biomarkers for OA/OA severity/progression, four on OA clustering, and one on OA treatment outcomes. Twenty-nine studied protein markers for OA, thirteen studied metabolite markers, and four studied both. While many studies were the validation of the previously reported biomarkers, a number of novel metabolite/protein biomarkers and biomarker panels were reported in the past year. Biomarker panels might be useful to subset OA patients. CONCLUSION: The number of studies on OA clustering is rising. Although validation in larger cohorts is needed in order to utilize reported biomarkers in clinical practice, these discoveries help better understand the pathogenesis of OA, provide insights into possible mechanisms underlying poor treatment outcomes, and aid in developing personalized treatment based on OA subtypes.

Individual participant data meta-analysis of metabolomics on sustained knee pain in primary osteoarthritis patients.

OBJECTIVES: Knee pain is the major driver for OA patients to seek healthcare, but after pursuing both conservative and surgical pain interventions, ∼20% of patients continue to report long-term pain following total knee arthroplasty (TKA). This study aimed to identify a metabolomic signature for sustained knee pain after TKA to elucidate possible underlying mechanisms. METHODS: Two independent cohorts from St John's, NL, Canada (n = 430), and Toronto, ON, Canada (n = 495) were included in the study. Sustained knee pain was assessed using the WOMAC pain subscale (five questions) at least 1 year after TKA for primary OA. Those reporting any pain on all five questions were considered to have sustained knee pain. Metabolomic profiling was performed on fasted pre-operative plasma samples using the Biocrates Absolute IDQ p180 kit. Associations between metabolites and pair-wise metabolite ratios with sustained knee pain in each individual cohort were assessed using logistic regression with adjustment for age, sex and BMI. Random-effects meta-analysis using inverse variance as weights was performed on summary statistics from both cohorts. RESULTS: One metabolite, phosphatidylcholine (PC) diacyl (aa) C28:1 (odds ratio = 0.66, P = 0.00026), and three metabolite ratios, PC aa C32:0 to PC aa C28:1, PC aa C28:1 to PC aa C32:0, and tetradecadienylcarnitine (C14:2) to sphingomyelin C20:2 (odds ratios = 1.59, 0.60 and 1.59, respectively; all P < 2 × 10-5), were significantly associated with sustained knee pain. CONCLUSIONS: Though further investigations are needed, our results provide potential predictive biomarkers and drug targets that could serve as a marker for poor response and be modified pre-operatively to improve knee pain and surgical response to TKA.

Glutathione, polyamine, and lysophosphatidylcholine synthesis pathways are associated with circulating pro-inflammatory cytokines.

INTRODUCTION: Pro-inflammatory cytokines are responsible for initiating an effective defense against exogenous pathogens, and their regulation has a vital role in maintaining physiological homeostasis. The involvement of pro-inflammatory cytokines in pathological conditions have been explored in great detail, however, studies investigating metabolic pathways associated with these cytokines under normal homeostatic conditions are scarce. OBJECTIVES: The aim of the current study was to identify metabolites and metabolic pathways associated with circulating pro-inflammatory cytokines under homeostatic conditions using a metabolomics approach. METHODS: The study participants (n = 133) were derived from the Newfoundland Osteoarthritis Study (NFOAS) and the Complex Diseases in the Newfoundland population: Environment and Genetics (CODING) study. Plasma concentrations of cytokines including tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1ß), and macrophage migration inhibitory factor (MIF) were assessed by enzyme-linked immunosorbent assay. Targeted metabolomic profiling on fasting plasma samples was performed using Biocrates MxP® Quant 500 kit which measures a total of 630 metabolites. Associations between natural log-transformed metabolite concentrations and metabolite sums/ratios and cytokine levels were assessed using linear regression with adjustment for age, sex, body mass index (BMI), and osteoarthritis status. RESULTS: Seven metabolites and 11 metabolite sums/ratios were found to be significantly associated with TNF-α, IL-1ß, and MIF (all p ≤ 5.13 × 10- 5) after controlling multiple testing with Bonferroni method, indicating the association between glutathione (GSH), polyamine, and lysophosphatidylcholine (lysoPC) synthesis pathways and these pro-inflammatory cytokines. CONCLUSION: GSH, polyamine, and lysoPC synthesis pathways were positively associated with circulating TNF-α, IL-1ß, and MIF levels under homeostatic conditions.

Prediagnostic consumption of vitamin D, calcium and dairy products and colorectal cancer survival: results from the Newfoundland Colorectal Cancer Registry Cohort Study.

Vitamin D, Ca and dairy products are negatively associated with colorectal cancer (CRC) incidence, but little is known of their influence on CRC survival. To investigate prediagnostic intakes of vitamin D, Ca and dairy products for their relevance to CRC prognosis, we analysed 504 CRC patients enrolled in the Newfoundland Colorectal Cancer Registry Cohort Study who were diagnosed for the first time with CRC between 1999 and 2003. Follow-up for mortality and cancer recurrence was through April 2010. Data on diet and lifestyle factors were gathered via a validated, semi-quantitative FFQ and a Personal History Questionnaire. Multivariate Cox models estimated hazard ratios (HR) and 95 % CI for the relationship of prediagnostic intakes of vitamin D, Ca and dairy products with all-cause mortality (overall survival, OS) and disease-free survival (DFS) among CRC patients. We found that prediagnostic Ca intake from foods, but not total Ca intake, was negatively associated with all-cause mortality (HR for Q2 v. Q1, 0·44; 95 % CI, 0·26, 0·75). An inverse relationship was also seen in a dose-response fashion for prediagnostic cheese intake (HR for Q4 v. Q1, 0·57, 95 % CI, 0·34, 0·95, Ptrend = 0·029). No evidence for modification by sex, physical activity, alcohol drinking and cigarette smoking was observed. In summary, high prediagnostic intakes of cheese and Ca from foods may be associated with increased survival among CRC patients. By manipulating diet, this study may contribute to the development of novel therapies that add to the armamentarium against CRC. Replication studies are required before any nutritional interventions are made available.

Endotypes of primary osteoarthritis identified by plasma metabolomics analysis.

OBJECTIVE: To identify endotypes of osteoarthritis (OA) by a metabolomics analysis. METHODS: Study participants included hip/knee OA patients and controls. Fasting plasma samples were metabolomically profiled. Common factor analysis and K-means clustering were applied to the metabolomics data to identify the endotypes of OA patients. Logistic regression was utilized to identify the most significant metabolites contributing to the endotypes. Clinical and epidemiological factors were examined in relation to the identified OA endotypes. RESULTS: Six hundred and fifteen primary OA patients and 237 controls were included. Among the 186 metabolites measured, 162 passed the quality control analysis. The 615 OA patients were classified in three clusters (A, 66; B, 200; and C, 349). Patients in cluster A had a significantly higher concentration of butyrylcarnitine (C4) than other clusters and controls (all P < 0.0002). Elevated C4 is thought to be related to muscle weakness and wasting. Patients in cluster B had a significantly lower arginine concentration than other clusters and controls (all P < 7.98 × 10-11). Cluster C patients had a significantly lower concentration of lysophosphatidylcholine (with palmitic acid), which is a pro-inflammatory bioactive compound, than other clusters and controls (P < 3.79 × 10-6). Further, cluster A had a higher BMI and prevalence of diabetes than other clusters (all P ≤ 0.0009), and also a higher prevalence of coronary heart disease than cluster C (P = 0.04). Cluster B had a higher prevalence of coronary heart disease than cluster C (P = 0.003) whereas cluster C had a higher prevalence of osteoporosis (P = 0.009). CONCLUSION: Our data suggest three possible clinically actionable endotypes in primary OA: muscle weakness, arginine deficit and low inflammatory OA.

Association Between Epidemiological Factors and Nonresponders to Total Joint Replacement Surgery in Primary Osteoarthritis Patients.

BACKGROUND: While total joint replacement (TJR) is the most effective treatment for end-stage osteoarthritis (OA), one-third of patients do not experience clinically important improvement in pain or function following the surgery. Thus, it is important to identify factors for nonresponders and develop strategies to improve TJR outcomes. METHODS: Study participants were patients who underwent TJR (hip/knee) due to OA and completed the WOMAC before and on average 4 years after surgery. Nonresponders (pain nonresponders, function nonresponders, pain and function nonresponders) were determined using the WOMAC change score from baseline to follow-up under two previously reported criteria. Eighty-eight self-reported factors collected by a general health questionnaire were examined for associations with nonresponders. RESULTS: A total of 601 patients (30.8% hip and 69.2% knee replacement) were included; 18% of them were found to be either pain or function nonresponders. Nine factors were identified in the univariable analyses to be associated with nonresponders, and 5 of them (clinical depression, multisite musculoskeletal pain [MSMP], younger age, golfer's elbow, and driving more than 4 hours on average per working day) remained significant in the multivariable analyses in at least one of six categories. Clinical depression, having MSMP, and younger age were the major factors to be independently associated with nonresponders across five categories. In addition, two factors (age at menopause and age at hysterectomy) were significantly associated with female nonresponders. CONCLUSION: Our data suggested potential roles of pain perception, widespread pain sensitization, patient expectations, and early menopause in females in TJR outcomes, warranting further investigation.

Differential correlation network analysis identified novel metabolomics signatures for non-responders to total joint replacement in primary osteoarthritis patients.

INTRODUCTION: Up to one third of total joint replacement patients (TJR) experience poor surgical outcome. OBJECTIVES: To identify metabolomic signatures for non-responders to TJR in primary osteoarthritis (OA) patients. METHODS: A newly developed differential correlation network analysis method was applied to our previously published metabolomic dataset to identify metabolomic network signatures for non-responders to TJR. RESULTS: Differential correlation networks involving 12 metabolites and 23 metabolites were identified for pain non-responders and function non-responders, respectively. CONCLUSION: The differential networks suggest that inflammation, muscle breakdown, wound healing, and metabolic syndrome may all play roles in TJR response, warranting further investigation.

An evolutionary learning and network approach to identifying key metabolites for osteoarthritis.

Metabolomics studies use quantitative analyses of metabolites from body fluids or tissues in order to investigate a sequence of cellular processes and biological systems in response to genetic and environmental influences. This promises an immense potential for a better understanding of the pathogenesis of complex diseases. Most conventional metabolomics analysis methods exam one metabolite at a time and may overlook the synergistic effect of combining multiple metabolites. In this article, we proposed a new bioinformatics framework that infers the non-linear synergy among multiple metabolites using a symbolic model and subsequently, identify key metabolites using network analysis. Such a symbolic model is able to represent a complex non-linear relationship among a set of metabolites associated with osteoarthritis (OA) and is automatically learned using an evolutionary algorithm. Applied to the Newfoundland Osteoarthritis Study (NFOAS) dataset, our methodology was able to identify nine key metabolites including some known osteoarthritis-associated metabolites and some novel metabolic markers that have never been reported before. The results demonstrate the effectiveness of our methodology and more importantly, with further investigations, propose new hypotheses that can help better understand the OA disease.

Metabolomics of osteoarthritis: emerging novel markers and their potential clinical utility.

OA is a multifactorial and progressive disease with no cure yet. Substantial efforts have been made and several biochemical and genetic markers have been reported, but neither alone nor in combination is adequate to identify early OA changes or determine disease progression with sufficient predictive values. Recent advances in metabolomics and its application to the study of OA have led to elucidation of involvement of several metabolic pathways and new specific metabolic markers for OA. Some of these metabolic pathways affect amino acid metabolism, including branched chain amino acids and arginine, and phospholipid metabolism involving conversion of phosphatidylcholine to lysophosphatidylcholine. These metabolic markers appear to be clinically actionable and may potentially improve the clinical management of OA patients. In this article, we review the recent studies of metabolomics of OA, discuss those novel metabolic markers and their potential clinical utility, and indicate future research directions in the field.

Association of rs2282679 A>C polymorphism in vitamin D binding protein gene with colorectal cancer risk and survival: effect modification by dietary vitamin D intake.

BACKGROUND: The rs2282679 A>C polymorphism in the vitamin D binding protein gene is associated with lower circulating levels of vitamin D. We investigated associations of this SNP with colorectal cancer (CRC) risk and survival and whether the associations vary by dietary vitamin D intake and tumor molecular phenotype. METHODS: A population-based case-control study identified 637 incident CRC cases (including 489 participants with follow-up data on mortality end-points) and 489 matched controls. Germline DNA samples were genotyped with the Illumina Omni-Quad 1 Million chip in cases and the Affymetrix Axiom® myDesign™ Array in controls. Logistic regression examined the association between the rs2282679 polymorphism and CRC risk with inclusion of potential confounders. Kaplan-Meier curves and multivariable Cox models assessed the polymorphism relative to overall survival (OS) and disease-free survival (DFS). RESULTS: The rs2282679 polymorphism was not associated with overall CRC risk; there was evidence, however, of effect modification by total vitamin D intake (Pinteraction = 0.019). Survival analyses showed that the C allele was correlated with poor DFS (per-allele HR, 1.36; 95%CI, 1.05-1.77). The association of rs2282679 on DFS was limited to BRAF wild-type tumors (HR, 1.58; 95%CI, 1.12-2.23). For OS, the C allele was associated with higher all-cause mortality among patients with higher levels of dietary vitamin D (HR, 2.11; 95%CI, 1.29-3.74), calcium (HR, 1.93; 95%CI, 1.08-3.46), milk (HR, 2.36; 95%CI, 1.26-4.44), and total dairy product intakes (HR, 2.03; 95%CI, 1.11-3.72). CONCLUSION: The rs2282679 SNP was not associated with overall CRC risk, but may be associated with survival after cancer diagnosis. The association of this SNP on survival among CRC patients may differ according to dietary vitamin D and calcium intakes and according to tumor BRAF mutation status.

Expression and Metabolomic Profiling in Axial Spondyloarthritis.

PURPOSE OF REVIEW: The purpose of this review is to highlight recent evidence with respect to expression and metabolomic profiling in axial spondyloarthritis (axSpA) that included ankylosing spondylitis (AS). RECENT FINDINGS: AxSpA is not only characterized by the strongest genetic contribution for any complex rheumatic disease but is also influenced by environmental and immunological factors. Large-scale association-based studies have identified over 100 genetic variants contributing to 30% of the genetic risk of ankylosing spondylitis. Recent studies in global expression and metabolomic profiling appear to highlight common themes despite differences in tissues, populations, techniques, and relative paucity of patients in many of these studies. Expression studies support a role for immunomodulation and bone remodeling in the pathogenesis and progression of axSpA/AS, while metabolomic studies implicate the importance of the intestinal microbial metabolism as well as fat and choline metabolic pathways in AS.

Vitamin D receptor and calcium-sensing receptor polymorphisms and colorectal cancer survival in the Newfoundland population.

BACKGROUND: Increased serum levels of vitamin D and calcium have been associated with lower risks of colorectal cancer (CRC) incidence and mortality. These inverse associations may be mediated by the vitamin D receptor (VDR) and the calcium-sensing receptor (CASR). We investigated genetic variants in VDR and CASR for their relevance to CRC prognosis. METHODS: A population-based cohort of 531 CRC patients diagnosed from 1999 to 2003 in Newfoundland and Labrador, Canada, was followed for mortality and cancer recurrence until April 2010. Germline DNA samples were genotyped with the Illumina Omni-Quad 1 Million chip. Multivariate Cox models assessed 41 tag single-nucleotide polymorphisms and relative haplotypes on VDR and CASR in relation to all-cause mortality (overall survival, OS) and disease-free survival (DFS). RESULTS: Gene-level associations were observed between VDR and the DFS of rectal cancer patients (P=0.037) as well as between CASR and the OS of colon cancer patients (P=0.014). Haplotype analysis within linkage blocks of CASR revealed the G-G-G-G-G-A-C haplotype (rs10222633-rs10934578-rs3804592-rs17250717-A986S-R990G-rs1802757) to be associated with a decreased OS of colon cancer (HR, 3.15; 95% CI, 1.66-5.96). Potential interactions were seen among prediagnostic dietary calcium intake with the CASR R990G (Pint=0.040) and the CASR G-T-G-G-G-G-C haplotype for rs10222633-rs10934578-rs3804592-rs17250717-A986S-R990G-rs1802757 (Pint=0.017), with decreased OS time associated with these variants limited to patients consuming dietary calcium below the median, although the stratified results were not statistically significant after correction for multiple testing. CONCLUSIONS: Polymorphic variations in VDR and CASR may be associated with survival after a diagnosis of CRC.

Human metabolic individuality in biomedical and pharmaceutical research.

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

Two novel candidate genes identified in adults from the Newfoundland population with addictive tendencies towards food.

Food addiction (FA) is a distinguished clinical feature affecting about 5% adults of the general population in Canada. FA contributes to obesity, however, the underlying genes in FA are largely unknown. The aim of the current study was to search for FA candidate genes using an exome sequencing followed by a verification study using the most significantly associated identified genes. From a total of 752 adults, 24 subjects were selected including 8 obese with high and 8 obese with low/zero FA clinical symptom score (FAO, NFO), and 8 healthy controls with normal BMI and low/zero FA symptom score (Ctrl). Exome sequencing was completed in all three groups. The top 100 SNPs identified were categorized into 5 subgroups based on gene functions: addiction (Ad), psychological disorders, energy metabolism and obesity, and cancer, unknown function or with other diseases. In the verification study, the top 19 SNPs in the Addiction subgroup were genotyped in the entire 752 subjects using Sequenom iPLEX Gold genotyping technology. Comparison of NFO with Ctrl, and FAO with NFO, Ctrl and the combined group of NFO + Ctrl revealed 19 SNPs associated with Ad genes including, TIRAP, MMADHC, ERAP1, NTM, MYPN, GRID1, ITPR2, GPSM1, ZCCHC14, TNN, PPARD, CACNA1C, SIM1, and DRD2. Genetic association analysis was performed. The major allele A of rs2511521 located in DRD2 (OR = 3.1(95% CI 1.1-8.2)) and the minor allele T of rs625413 located in TIRAP (OR = 2.5(95% CI 1.1-5.8)) in NFO subjects significantly associated with increased risk of food addiction. Using a combination of exome sequencing method and a candidate gene association approach two new FA candidate genes are identified. Further study on the rest of the genes in the other four categories will be warranted.

Lysophosphatidylcholines to phosphatidylcholines ratio predicts advanced knee osteoarthritis.

OBJECTIVE: To identify novel biomarker(s) for predicting advanced knee OA. METHODS: Study participants were derived from the Newfoundland Osteoarthritis Study and the Tasmania Older Adult Cohort Study. All knee OA cases were patients who underwent total knee replacement (TKR) due to primary OA. Metabolic profiling was performed on fasting plasma. Four thousand and eighteen plasma metabolite ratios that were highly correlated with that in SF in our previous study were generated as surrogates for joint metabolism. RESULTS: The discovery cohort included 64 TKR cases and 45 controls and the replication cohorts included a cross-sectional cohort of 72 TKR cases and 76 controls and a longitudinal cohort of 158 subjects, of whom 36 underwent TKR during the 10-year follow-up period. We confirmed the previously reported association of the branched chain amino acids to histidine ratio with advanced knee OA (P = 9.3 × 10(-7)) and identified a novel metabolic marker-the lysophosphatidylcholines (lysoPCs) to phosphatidylcholines (PCs) ratio-that was associated with advanced knee OA (P = 1.5 × 10(-7)) after adjustment for age, sex and BMI. When the subjects of the longitudinal cohort were categorized into two groups based on the optimal cut-off of the ratio of 0.09, we found the subjects with the ratio ⩾0.09 were 2.3 times more likely to undergo TKR than those with the ratio <0.09 during the 10-year follow-up (95% CI: 1.2, 4.3, P = 0.02). CONCLUSION: We identified the ratio of lysoPCs to PCs as a novel metabolic marker for predicting advanced knee OA. Further studies are required to examine whether this ratio can predict early OA change.

TGF-ß signal transduction pathways and osteoarthritis.

Osteoarthritis (OA) is the most common form of arthritis, resulting in substantial disability and economic burden worldwide. While its exact pathogenesis remains elusive, both in vitro and human population-based studies have merged to support the hypothesis that TGF-ß/BMP-mediated signalling pathways play a role in the development of OA. Unraveling the TGF-ß/BMP-mediated mechanism(s) in OA has great potential in identifying novel targets and developing new drugs for OA treatment. This review summarizes both in vitro and in vivo evidence of TGF-ß/BMP-mediated signal transduction pathways in OA and discusses the future research direction in this regard.

Genome-wide DNA methylation study of hip and knee cartilage reveals embryonic organ and skeletal system morphogenesis as major pathways involved in osteoarthritis.

BACKGROUND: Evidence suggests that epigenetics plays a role in osteoarthrits (OA). The aim of the study was to describe the genome wide DNA methylation changes in hip and knee OA and identify novel genes and pathways involved in OA by comparing the DNA methylome of the hip and knee osteoarthritic cartilage tissues with those of OA-free individuals. METHODS: Cartilage samples were collected from hip or knee joint replacement patients either due to primary OA or hip fractures as controls. DNA was extracted from the collected cartilage and assayed by Illumina Infinium HumanMethylation450 BeadChip array, which allows for the analysis of >480,000 CpG sites. Student T-test was conducted for each CpG site and those sites with at least 10 % methylation difference and a p value <0.0005 were defined as differentially methylated regions (DMRs) for OA. A sub-analysis was also done for hip and knee OA separately. DAVID v6.7 was used for the functional annotation clustering of the DMR genes. Clustering analysis was done using multiple dimensional scaling and hierarchical clustering methods. RESULTS: The study included 5 patients with hip OA, 6 patients with knee OA and 7 hip cartilage samples from OA-free individuals. The comparisons of hip, knee and combined hip/knee OA patients with controls resulted in 26, 72, and 103 DMRs, respectively. The comparison between hip and knee OA revealed 67 DMRs. The overall number of the sites after considering the overlaps was 239, among which 151 sites were annotated to 145 genes. One-fifth of these genes were reported in previous studies. The functional annotation clustering of the identified genes revealed clusters significantly enriched in skeletal system morphogenesis and development. The analysis revealed significant difference among OA and OA-free cartilage, but less different between hip OA and knee OA. CONCLUSIONS: We found that a number of CpG sites and genes across the genome were differentially methylated in OA patients, a remarkable portion of which seem to be involved in potential etiologic mechanisms of OA. Genes involved in skeletal developmental pathways and embryonic organ morphogenesis may be a potential area for further OA studies.

Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population.

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype-phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.

Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function.

Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.