The impact of omics research on our understanding of osteoarthritis and future treatments

Beier, Frank

doi:10.1097/bor.0000000000000919

Cited by 5 publications

(5 citation statements)

References 38 publications

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“…While an abundance of genetic variants associated with OA have been detected, research is limited by the fact that the majority of these variants are found within non-coding regions of the genome and have a small effect size [ 4 , 12 ]. This has led to the prevailing theory that the accumulation of multiple risk alleles contributes to the predisposition of OA later in life and that a threshold must exist that tips an individual into OA.…”

Section: Discussionmentioning

confidence: 99%

Genomic heterozygosity is associated with a lower risk of osteoarthritis

Gill,

Liu,

Sun

et al. 2024

BMC Genomics

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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.

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Section: Discussionmentioning

confidence: 99%

Genomic heterozygosity is associated with a lower risk of osteoarthritis

Gill,

Liu,

Sun

et al. 2024

BMC Genomics

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“…The identification of circulating miR biomarkers [ 203 ] using unbiased sequencing and other omics-based approaches (genome-wide association studies [ 204 ], proteomics [ 205 ], metabolomics [ 206 ]) may provide deeper insights into patient endotype. The use of AI algorithms and bioinformatics to cohesively knit large omics datasets [ 207 ] to systematically classify patient endotypes can further advance the field. Organ-on-chip technology, which can incorporate patient-specific blood, synovial fluid, urine and/or tissue biopsy samples, offers the dual potential of providing patient baseline disease endotype information and surrogate in vitro readouts of the efficacy of various drugs or test therapeutics [ 208 ].…”

Section: Roadmap For Successful Msc Oa Trialsmentioning

confidence: 99%

Culture-expanded mesenchymal stromal cell therapy: does it work in knee osteoarthritis? A pathway to clinical success

2023

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Osteoarthritis (OA) is a degenerative multifactorial disease with concomitant structural, inflammatory, and metabolic changes that fluctuate in a temporal and patient-specific manner. This complexity has contributed to refractory responses to various treatments. MSCs have shown promise as multimodal therapeutics in mitigating OA symptoms and disease progression. Here, we evaluated 15 randomized controlled clinical trials (RCTs) and 11 nonrandomized RCTs using culture-expanded MSCs in the treatment of knee OA, and we found net positive effects of MSCs on mitigating pain and symptoms (improving function in 12/15 RCTs relative to baseline and in 11/15 RCTs relative to control groups at study endpoints) and on cartilage protection and/or repair (18/21 clinical studies). We examined MSC dose, tissue of origin, and autologous vs. allogeneic origins as well as patient clinical phenotype, endotype, age, sex and level of OA severity as key parameters in parsing MSC clinical effectiveness. The relatively small sample size of 610 patients limited the drawing of definitive conclusions. Nonetheless, we noted trends toward moderate to higher doses of MSCs in select OA patient clinical phenotypes mitigating pain and leading to structural improvements or cartilage preservation. Evidence from preclinical studies is supportive of MSC anti-inflammatory and immunomodulatory effects, but additional investigations on immunomodulatory, chondroprotective and other clinical mechanisms of action are needed. We hypothesize that MSC basal immunomodulatory “fitness” correlates with OA treatment efficacy, but this hypothesis needs to be validated in future studies. We conclude with a roadmap articulating the need to match an OA patient subset defined by molecular endotype and clinical phenotype with basally immunomodulatory “fit” or engineered-to-be-fit-for-OA MSCs in well-designed, data-intensive clinical trials to advance the field.

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“…Recent advances in understanding complex disease have been greatly enhanced by the application of multi-omic approaches to disease relevant tissues [11, 18] . The strengths of these approaches are the focus on human disease cohorts at scale (hundreds to tens of thousands of participating individuals), the unbiased and systematic nature of molecular identification, the ability to map molecules to a shared pathway, and the ability to replicate results across independent cohorts.…”

Section: Introductionmentioning

confidence: 99%

Deconvoluting synovial fluid molecular endotypes in knee osteoarthritis: primary results from the STEpUP OA Consortium

Perry,

Deng,

Hulley

et al. 2024

Preprint

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BackgroundOsteoarthritis (OA) has a lifetime risk of over 40%, imposing a huge societal burden. Clinical variability suggests that it could be more than one disease.Synovial fluidTo detectEndotypes byUnbiasedProteomics in OA (STEpUP OA) was established to test the hypothesis that there are detectable distinct molecular endotypes in knee OA.MethodsOA knee synovial fluid (SF) samples (N=1361) were from pre-existing OA cohorts with cross-sectional clinical (radiographic and pain) data. Samples were divided into Discovery (N = 708) and Replication (N=653) datasets. Proteomic analysis was performed using SomaScan V4.1 assay (6596 proteins). Unsupervised clustering was performed using k-means, assessed using the f(k) metric, with and without adjustments for potential confounders. Regression analyses were used to assess protein associations with radiographic (Kellgren and Lawrence) and knee pain (WOMAC pain), with and without stratification by body mass index (BMI) or biological sex. Adjustments were made for cohort (random intercept) or intracellular protein, using an intracellular protein score (IPS). Analyses were carried out in R according to a pre-published plan.ResultsNo distinct SF molecular endotypes were identified in OA but two indistinct clusters were defined in non-IPS regressed data which were stable across subgroup analyses. Clustering was lost after IPS regression adjustment. Strong, replicable protein associations were observed with radiographic disease severity, which were retained after adjustment for cohort or IPS. Pathway analysis identified a strong “epithelial to mesenchymal transition (EMT)” pathway, and weaker associations with “angiogenesis”, “complement” and “coagulation”. The latter were variably lost after adjustment for BMI or biological sex. Associations with patient reported pain were weaker.ConclusionThese data support knee OA as a biologically continuous disease in which disease severity is associated with a strong, robust, tissue remodelling signature. Subtle differences were found in pathways after stratification by BMI or sex.

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The impact of omics research on our understanding of osteoarthritis and future treatments

Cited by 5 publications

References 38 publications

Genomic heterozygosity is associated with a lower risk of osteoarthritis

Genomic heterozygosity is associated with a lower risk of osteoarthritis

Culture-expanded mesenchymal stromal cell therapy: does it work in knee osteoarthritis? A pathway to clinical success

Deconvoluting synovial fluid molecular endotypes in knee osteoarthritis: primary results from the STEpUP OA Consortium

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