Genome-wide association study of knee pain identifies associations with GDF5 and COL27A1 in UK Biobank

Clinical Assessment of Osteoarthritis Pain: Contemporary Scenario, Challenges, and Future Perspectives

The multifaceted nature of osteoarthritis (OA) pain presents a challenge in understanding and managing the condition. The diverse pain experiences, progression rates, individual responses to treatments, and complex disease mechanisms contribute to heterogeneity in the clinical studies outcomes. The lack of a standardized methodology for assessing and classifying OA pain challenges healthcare practitioners. This complicates the establishment of universally applicable protocols or standardized guidelines for treatment. This article explores the heterogeneity observed in clinical studies evaluating OA pain treatments, highlighting the necessity for refined methodologies, personalized patient categorization, and consistent outcome measures. It discusses the role of the multidimensional nature of OA pain, underlying pain mechanisms, and other contributing factors to the heterogeneity in outcome measures. Addressing these variations is crucial to establishing a more consistent framework for evidence-based treatments and advancing care of the patient with OA pain.

The Genetic Markers of Knee Osteoarthritis in Women from Russia

Osteoarthritis is a chronic progressive joint disease that clinically debuts at the stage of pronounced morphologic changes, which makes treatment difficult. In this regard, an important task is the study of genetic markers of the disease, which have not been definitively established, due to the clinical and ethnic heterogeneity of the studied populations. To find the genetic markers for the development of knee osteoarthritis (OA) in women from the Volga-Ural region of Russia, we conducted research in two stages using different genotyping methods, such as the restriction fragment length polymorphism (RFLP) measurement, TaqMan technology and competitive allele-specific PCR-KASPTM. In the first stage, we studied polymorphic variants of candidate genes (ACAN, ADAMTS5, CHST11, SOX9, COL1A1) for OA development. The association of the *27 allele of the VNTR locus of the ACAN gene was identified (OR = 1.6). In the second stage, we replicated the GWAS results (ASTN2, ALDH1A2, DVWA, CHST11, GNL3, NCOA3, FILIP/SENP1, MCF2L, GLT8D, DOT1L) for knee OA studies. The association of the *T allele of the rs7639618 locus of the DVWA gene was detected (OR = 1.54). Thus, the VNTR locus of ACAN and the rs7639618 locus of DVWA are risk factors for knee OA in women from the Volga-Ural region of Russia.

A multi-ancestry genetic study of pain intensity in 598,339 veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Looking back on 30+ years of the Johnston County Osteoarthritis Project while looking forward with the Johnston County Health Study: A narrative review

Over the last 30 years, knowledge of the epidemiology of osteoarthritis (OA) has dramatically advanced, and Osteoarthritis and Cartilage has been on the forefront of disseminating research findings from large OA cohort studies, including the Johnston County OA Project (JoCoOA). The JoCoOA is a population-based, prospective longitudinal cohort that began roughly 30 years ago with a key focus on understanding prevalence, incidence, and progression of OA, as well as its risk factors, in a predominantly rural population of Black and White adults 45+ years old in a county in the southeastern United States. Selected OA results that will be discussed in this review include racial differences, lifetime risk, biomarkers, mortality, and OA risk factors. The new Johnston County Health Study will also be introduced. This new cohort study of OA and comorbid conditions builds upon current OA knowledge and JoCoOA infrastructure and is designed to reflect changes in demographics and urbanization in the county and the region.

Can we achieve pain stratification in musculoskeletal conditions? Implications for clinical practice

In the last few years there has been an increased appreciation that pain perception in rheumatic and musculoskeletal diseases (RMDs) has several mechanisms which include nociceptive, inflammatory, nociplastic and neuropathic components. Studies in specific patient groups have also demonstrated that the pain experienced by people with specific diagnoses can present with distinctive components over time. For example, the pain observed in rheumatoid arthritis has been widely accepted to be caused by the activation of nociceptors, potentiated by the release of inflammatory mediators, including prostaglandins, leukotrienes and cytokine networks in the joint environment. However, people with RA may also experience nociplastic and neuropathic pain components, particularly when treatments with disease modifying anti-rheumatic drugs (DMARDs) have been implemented and are insufficient to control pain symptoms. In other RMDs, the concept of pain sensitisation or nociplastic pain in driving ongoing pain symptoms e.g. osteoarthritis and fibromyalgia, is becoming increasingly recognised. In this review, we explore the hypothesis that pain has distinct modalities based on clinical, pathophysiological, imaging and genetic factors. The concept of pain stratification in RMD is explored and implications for future management are also discussed.

Polymorphism rs143384 GDF5 reduces the risk of knee osteoarthritis development in obese individuals and increases the disease risk in non-obese population

BACKGROUND

We investigated the effect of obesity on the association of genome-wide associative studies (GWAS)-significant genes with the risk of knee osteoarthritis (KOA).

METHODS

All study participants (n = 1,100) were divided into 2 groups in terms of body mass index (BMI): BMI ≥ 30 (255 KOA patients and 167 controls) and BMI < 30 (245 KOA and 433 controls). The eight GWAS-significant KOA single nucleotide polymorphisms (SNP) of six candidate genes, such as LYPLAL1 (rs2820436, rs2820443), SBNO1 (rs1060105, rs56116847), WWP2 (rs34195470), NFAT5 (rs6499244), TGFA (rs3771501), GDF5 (rs143384), were genotyped. Logistic regression analysis (gPLINK online program) was used for SNPs associations study with the risk of developing KOA into 2 groups (BMI ≥ 30 and BMI < 30) separately. The functional effects of KOA risk loci were evaluated using in silico bioinformatic analysis.

RESULTS

Multidirectional relationships of the rs143384 GDF5 with KOA in BMI-different groups were found: This SNP was KOA protective locus among individuals with BMI ≥ 30 (OR 0.41 [95%CI 0.20-0.94] recessive model) and was disorder risk locus among individuals with BMI < 30 (OR 1.32 [95%CI 1.05-1.65] allele model, OR 1.44 [95%CI 1.10-1.86] additive model, OR 1.67 [95%CI 1.10-2.52] dominant model). Polymorphism rs143384 GDF5 manifested its regulatory effects in relation to nine genes (GDF5, CPNE1, EDEM2, ERGIC3, GDF5OS, PROCR, RBM39, RPL36P4, UQCC1) in adipose tissue, which were involved in the regulation of pathways of apoptosis of striated muscle cells.

CONCLUSIONS

In summary, the effect of obesity on the association of the rs143384 GDF5 with KOA was shown: the "protective" value of this polymorphism in the BMI ≥ 30 group and the "risk" meaning in BMI < 30 cohort.

Influence of Different Evolutive Forces on GDF5 Gene Variability

The GDF5 gene is involved in the development of skeletal elements, synovial joint formation, tendons, ligaments, and cartilage. Several polymorphisms are present within the gene, and two of them, rs143384 and 143383, were reported to be correlated with osteoarticular disease or muscle flexibility. The aim of this research is to verify if the worldwide distribution of the rs143384 polymorphism among human populations was shaped by selective pressure, or if it was the result of random genetic drift events. Ninety-four individuals of both the male and female sexes, 18-28 years old, from Sardinia were analyzed. We observed the following genotype frequencies: 28.72% of AA homozygotes, 13.83% of GG homozygotes, and 57.45% of AG heterozygotes. The allele frequencies were 0.574 for allele A and 0.426 for allele G. The relationships between the populations were verified via Multidimensional Scaling (MDS). Our data show (i) a clear heterogeneity within the African populations; (ii) a strong differentiation between the African populations and the other populations; and that (iii) the Sardinian population is placed within the European cluster. To reveal possible traces of selective pressure, the Population Branch Statistic (PBS) was calculated; both the rs143384 and 143383 SNPs have low PBS values, suggesting that there are no signals of selective pressure in those areas of the gene.

A systematic review of genome-wide association studies for pain, nociception, neuropathy, and pain treatment responses

ABSTRACT

Pain is the leading cause of disability worldwide, imposing an enormous burden on personal health and society. Pain is a multifactorial and multidimensional problem. Currently, there is (some) evidence that genetic factors could partially explain individual susceptibility to pain and interpersonal differences in pain treatment response. To better understand the underlying genetic mechanisms of pain, we systematically reviewed and summarized genome-wide association studies (GWASes) investigating the associations between genetic variants and pain/pain-related phenotypes in humans. We reviewed 57 full-text articles and identified 30 loci reported in more than 1 study. To check whether genes described in this review are associated with (other) pain phenotypes, we searched 2 pain genetic databases, Human Pain Genetics Database and Mouse Pain Genetics Database. Six GWAS-identified genes/loci were also reported in those databases, mainly involved in neurological functions and inflammation. These findings demonstrate an important contribution of genetic factors to the risk of pain and pain-related phenotypes. However, replication studies with consistent phenotype definitions and sufficient statistical power are required to validate these pain-associated genes further. Our review also highlights the need for bioinformatic tools to elucidate the function of identified genes/loci. We believe that a better understanding of the genetic background of pain will shed light on the underlying biological mechanisms of pain and benefit patients by improving the clinical management of pain.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

ABSTRACT

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

Big data, big consortia, and pain: UK Biobank, PAINSTORM, and DOLORisk

Chronic pain (CP) is a common and often debilitating disorder that has major social and economic impacts. A subset of patients develop CP that significantly interferes with their activities of daily living and requires a high level of healthcare support. The challenge for treating physicians is in preventing the onset of refractory CP or effectively managing existing pain. To be able to do this, it is necessary to understand the risk factors, both genetic and environmental, for the onset of CP and response to treatment, as well as the pathogenesis of the disorder, which is highly heterogenous. However, studies of CP, particularly pain with neuropathic characteristics, have been hindered by a lack of consensus on phenotyping and data collection, making comparisons difficult. Furthermore, existing cohorts have suffered from small sample sizes meaning that analyses, especially genome-wide association studies, are insufficiently powered. The key to overcoming these issues is through the creation of large consortia such as DOLORisk and PAINSTORM and biorepositories, such as UK Biobank, where a common approach can be taken to CP phenotyping, which allows harmonisation across different cohorts and in turn increased study power. This review describes the approach that was used for studying neuropathic pain in DOLORisk and how this has informed current projects such as PAINSTORM, the rephenotyping of UK Biobank, and other endeavours. Moreover, an overview is provided of the outputs from these studies and the lessons learnt for future projects.

Improved genetic prediction of the risk of knee osteoarthritis using the risk factor-based polygenic score

BACKGROUND

Polygenic risk score (PRS) analysis is used to predict disease risk. Although PRS has been shown to have great potential in improving clinical care, PRS accuracy assessment has been mainly focused on European ancestry. This study aimed to develop an accurate genetic risk score for knee osteoarthritis (OA) using a multi-population PRS and leveraging a multi-trait PRS in the Japanese population.

METHODS

We calculated PRS using PRS-CS-auto, derived from genome-wide association study (GWAS) summary statistics for knee OA in the Japanese population (same ancestry) and multi-population. We further identified risk factor traits for which PRS could predict knee OA and subsequently developed an integrated PRS based on multi-trait analysis of GWAS (MTAG), including genetically correlated risk traits. PRS performance was evaluated in participants of the Nagahama cohort study who underwent radiographic evaluation of the knees (n = 3,279). PRSs were incorporated into knee OA integrated risk models along with clinical risk factors.

RESULTS

A total of 2,852 genotyped individuals were included in the PRS analysis. The PRS based on Japanese knee OA GWAS was not associated with knee OA (p = 0.228). In contrast, PRS based on multi-population knee OA GWAS showed a significant association with knee OA (p = 6.7 × 10^-5, odds ratio (OR) per standard deviation = 1.19), whereas PRS based on MTAG of multi-population knee OA, along with risk factor traits such as body mass index GWAS, displayed an even stronger association with knee OA (p = 5.4 × 10^-7, OR = 1.24). Incorporating this PRS into traditional risk factors improved the predictive ability of knee OA (area under the curve, 74.4% to 74.7%; p = 0.029).

CONCLUSIONS

This study showed that multi-trait PRS based on MTAG, combined with traditional risk factors, and using large sample size multi-population GWAS, significantly improved predictive accuracy for knee OA in the Japanese population, even when the sample size of GWAS of the same ancestry was small. To the best of our knowledge, this is the first study to show a statistically significant association between the PRS and knee OA in a non-European population.

TRIAL REGISTRATION

No. C278.

General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology.

METHODS

The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS.

RESULTS

Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062).

CONCLUSIONS

PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Investigating the shared genetic architecture and causal relationship between pain and neuropsychiatric disorders

Pain often occurs in parallel with neuropsychiatric disorders. However, the underlying mechanisms and potential causality have not been well studied. We collected the genome-wide association study (GWAS) summary statistics of 26 common pain and neuropsychiatric disorders with sample size ranging from 17,310 to 482,730 in European population. The genetic correlation between pair of pain and neuropsychiatric disorders, as well as the relevant cell types were investigated by linkage disequilibrium (LD) score regression analyses. Then, transcriptome-wide association study (TWAS) was applied to identify the potential shared genes by integrating the gene expression information and GWAS. In addition, Mendelian randomization (MR) analyses were conducted to infer the potential causality between pain and neuropsychiatric disorders. Among the 169 pairwise pain and neuropsychiatric disorders, 55 pairs showed positive correlations (median r_g = 0.43) and 9 pairs showed negative correlations (median r_g =  -0.31). Using MR analyses, 26 likely causal associations were identified, including that neuroticism and insomnia were risk factors for most of short-term pain, and multisite chronic pain was risk factor for neuroticism, insomnia, major depressive disorder and attention deficit/hyperactivity disorder, and vice versa. The signals of pain and neuropsychiatric disorders tended to be enriched in the functional regions of cell types from central nervous system (CNS). A total of 19 genes shared in at least one pain and neuropsychiatric disorder pair were identified by TWAS, including AMT, NCOA6, and UNC45A, which involved in glycine degradation, insulin secretion, and cell proliferation, respectively. Our findings provided the evidence of shared genetic structure, causality and potential shared pathogenic mechanisms between pain and neuropsychiatric disorders, and enhanced our understanding of the comorbidities of pain and neuropsychiatric disorders.

A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits

The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.

R399E, A Mutated Form of Growth and Differentiation Factor 5, for Disease Modification of Osteoarthritis

OBJECTIVE

To preclinically characterize a mutant form of growth and differentiation factor 5, R399E, with reduced osteogenic properties as a potential disease-modifying osteoarthritis (OA) drug.

METHODS

Cartilage, synovium, and meniscus samples from patients with OA were used to evaluate anabolic and antiinflammatory properties of R399E. In the rabbit joint instability model, 65 rabbits underwent transection of the anterior cruciate ligament plus partial meniscectomy. Three intraarticular (IA) R399E doses were administered biweekly 6 times, and static incapacitance was determined to assess joint pain. OA was evaluated 13 weeks after surgery. In sheep, medial meniscus transection was performed to induce OA, dynamic weight bearing was measured in-life, and OA was assessed after 13 weeks.

RESULTS

Intermittent exposure to R399E (1 week per month) was sufficient to induce cell proliferation and release of anabolic markers in 3-dimensional chondrocyte cultures. R399E also inhibited the release of interleukin-1β (IL-1β), IL-6, and prostaglandin E₂ from cartilage with synovium, meniscal cell, and synoviocyte cultures. In rabbits, the mean difference (95% confidence interval [95% CI]) in weight bearing for R399E compared to vehicle was -5.8 (95% confidence interval [95% CI] -9.54, -2.15), -7.2 (95% CI -10.93, -3.54), and -7.7 (95% CI -11.49, -3.84) for the 0.6, 6, and 60 μg doses, respectively, 6 hours after the first IA injection, and was statistically significant through the entire study for all doses. Cartilage surface structure improved with the 6-μg dose. Structural and symptomatic improvement with the same dose was confirmed in the sheep model of OA.

CONCLUSION

R399E influences several pathologic processes contributing to OA, highlighting its potential as a disease-modifying therapy.

Multisite chronic pain as a causal risk factor for coronary artery disease: findings from Mendelian randomization

ABSTRACT

The potential consequences of the number of chronic pain sites (referred to multisite chronic pain) on the risk of cardiovascular diseases (CVDs) remain unclear. We attempted to investigate the causality of multisite chronic pain with CVDs and its possible causal mediators. Using summary genome-wide association statistics, two-sample Mendelian randomization (MR) analyses were performed to assess whether multisite chronic pain has a causal effect on the 3 CVDs including coronary artery disease, atrial fibrillation, and stroke. We then conducted MR mediation analyses to establish whether body mass index (BMI), smoking, and depression causally mediate any association. Genetic liability to multisite chronic pain was associated with increased risk of coronary artery disease (odds ratio [OR] 1.52, 95% confidence interval [CI] 1.19-1.95 per one increase in the number of pain locations) but not with atrial fibrillation or stroke. We also found positive causal effects of multisite chronic pain on BMI, smoking, and depression and causal effects of BMI, smoking, and depression on coronary artery disease. In multivariable MR analyses, the excess risk of coronary artery disease was attenuated after adjusting for BMI (OR 1.43, 95% CI 1.05-1.93), smoking (OR 1.49, 95% CI 1.11-2.00), depression (OR 1.44, 95% CI 1.03-2.01), and 3 risk factors combined (OR 1.34, 95% CI 0.88-2.05). Our findings demonstrated that multisite chronic pain led to higher risk of coronary artery disease, which is partly mediated through BMI, smoking, and depression.

Extracellular vesicles in osteoarthritis of peripheral joint and temporomandibular joint

Osteoarthritis (OA) is a disabling disease with significant morbidity worldwide. OA attacks the large synovial joint, including the peripheral joints and temporomandibular joint (TMJ). As a representative of peripheral joint OA, knee OA shares similar symptoms with TMJ OA. However, these two joints also display differences based on their distinct development, anatomy, and physiology. Extracellular vesicles (EVs) are phospholipid bilayer nanoparticles, including exosomes, microvesicles, and apoptotic bodies. EVs contain proteins, lipids, DNA, micro-RNA, and mRNA that regulate tissue homeostasis and cell-to-cell communication, which play an essential role in the progression and treatment of OA. They are likely to partake in mechanical response, extracellular matrix degradation, and inflammatory regulation during OA. More evidence has shown that synovial fluid and synovium-derived EVs may serve as OA biomarkers. More importantly, mesenchymal stem cell-derived EV shows a therapeutic effect on OA. However, the different function of EVs in these two joints is largely unknown based on their distinct biological characteristic. Here, we reviewed the effects of EVs in OA progression and compared the difference between the knee joint and TMJ, and summarized their potential therapeutic role in the treatment of OA.

Characterization of Genetic Risk of End-Stage Knee Osteoarthritis Treated with Total Knee Arthroplasty: A Genome-Wide Association Study

BACKGROUND

End-stage knee osteoarthritis (OA) is a highly debilitating disease for which total knee arthroplasty (TKA) serves as an effective treatment option. Although a genetic component to OA in general has been described, evaluation of the genetic contribution to end-stage OA of the knee is limited. To this end, we present a genome-wide association study involving patients undergoing TKA for primary knee OA to characterize the genetic features of severe disease on a population level.

METHODS

Individuals with the diagnosis of knee OA who underwent primary TKA were identified in the U.K. Biobank using administrative codes. The U.K. Biobank is a data repository containing prospectively collected clinical and genomic data for >500,000 patients. A genome-wide association analysis was performed using the REGENIE software package. Logistic regression was also used to compare the total genetic risk between subgroups stratified by age and body mass index (BMI).

RESULTS

A total of 16,032 patients with end-stage knee OA who underwent primary TKA were identified. Seven genetic loci were found to be significantly associated with end-stage knee OA. The odds ratio (OR) for developing end-stage knee OA attributable to genetics was 1.12 (95% confidence interval [CI], 1.10 to 1.14), which was lower than the OR associated with BMI (OR = 1.81; 95% CI, 1.78 to 1.83) and age (OR = 2.38; 95% CI, 2.32 to 2.45). The magnitude of the OR for developing end-stage knee OA attributable to genetics was greater in patients <60 years old than in patients ≥60 years old (p = 0.002).

CONCLUSIONS

This population-level genome-wide association study of end-stage knee OA treated with primary TKA was notable for identifying multiple significant genetic variants. These loci involve genes responsible for cartilage development, cartilage homeostasis, cell signaling, and metabolism. Age and BMI appear to have a greater impact on the risk of developing end-stage disease compared with genetic factors. The genetic contribution to the development of severe disease is greater in younger patients.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Genome-wide association study of pain sensitivity assessed by questionnaire and the cold pressor test

ABSTRACT

We deployed an online pain sensitivity questionnaire (PSQ) and an at-home version of the cold pressor test (CPT) in a large genotyped cohort. We performed genome-wide association studies on the PSQ score (25,321 participants) and CPT duration (6853). We identified one new genome-wide significant locus associated with the PSQ score, which was located in the TSSC1 (also known as EIPR1 ) gene (rs58194899, OR = 0.950 [0.933-0.967], P -value = 1.9 × 10 -8 ). Although high pain sensitivity measured by both PSQ and CPT was associated with individual history of chronic and acute pains, genetic correlation analyses surprisingly suggested an opposite direction: PSQ score was inversely genetically correlated with neck and shoulder pain ( rg = -0.71), rheumatoid arthritis (-0.68), and osteoarthritis (-0.38), and with known risk factors, such as the length of working week (-0.65), smoking (-0.36), or extreme BMI (-0.23). Gene-based analysis followed by pathway analysis showed that genome-wide association studies results were enriched for genes expressed in the brain and involved in neuronal development and glutamatergic synapse signaling pathways. Finally, we confirmed that females with red hair were more sensitive to pain and found that genetic variation in the MC1R gene was associated with an increase in self-perceived pain sensitivity as assessed by the PSQ.

Bioinformatics Analysis and Experimental Verification Identify Downregulation of COL27A1 in Poor Segmental Congenital Scoliosis

BACKGROUND

Congenital scoliosis (CS) represents the congenital defect disease, and poor segmental congenital scoliosis (PSCS) represents one of its types. Delayed intervention can result in disability and paralysis. In this study, we would identify the core biomarkers for PSCS progression through bioinformatics analysis combined with experimental verification.

METHODS

This work obtained the GSE11854 expression dataset associated with somite formation in the GEO database, which covers data of 13 samples. Thereafter, we utilized the edgeR of the R package to obtain DEGs in this dataset. Then, GO annotation, KEGG analyses, and DO annotation of DEGs were performed by "clusterProfiler" of the R package. This study performed LASSO regression for screening the optimal predicting factors for somite formation. Through RNA sequencing based on peripheral blood samples from healthy donors and PSCS cases, we obtained the RNA expression patterns and screen out DEGs using the R package DESeq2. The present work analyzed COL27A1 expression in PSCS patients by the RT-PCR assay.

RESULTS

A total of 443 genes from the GSE11854 dataset were identified as DEGs, which were involved in BP associated with DNA replication, CC associated with chromosomal region, and MF associated with ATPase activity. These DEGs were primarily enriched in the TGF-β signaling pathway and spinal deformity. Further, LASSO regression suggested that 9 DEGs acted as the signature markers for somite formation. We discovered altogether 162 DEGs in PSCS patients, which were involved in BP associated with cardiac myofibril assembly and MF associated with structural constituent of muscle. However, these 162 DEGs were not significantly correlated with any pathways. Finally, COL27A1 was identified as the only intersected gene between the best predictors for somite formation and PSCS-related DEGs, which was significantly downregulated in PSCS patients.

CONCLUSION

This work sheds novel lights on DEGs related to the PSCS pathogenic mechanism, and COL27A1 is the possible therapeutic target for PSCS. Findings in this work may contribute to developing therapeutic strategies for PSCS.

Reciprocal interaction between depression and pain: results from a comprehensive bidirectional Mendelian randomization study and functional annotation analysis

ABSTRACT

To understand a putative causal link for depression and pain, we retrieved summary statistics from genome-wide association studies conducted for pain at 7 different body sites (N = 151,922-226,683) and major depression disorder (MDD, Ncase/control = 246,363/561,190). We conducted a bidirectional Mendelian randomization analysis using distinct genome-wide association studies-identified single nucleotide polymorphisms for each trait as instrumental variables and performed several sensitivity analyses to verify Mendelian randomization assumptions. We also conducted functional annotation analysis using 396 tissue-specific annotations from the roadmap project. Across 7 different body sites, genetic predisposition to depression was associated with pain at the neck/shoulder (odds ratio [OR] = 1.08 per one log-unit increase in depression risk, 95% confidence interval [CI]: 1.06-1.10), back (OR = 1.05, 95% CI: 1.04-1.07), abdominal/stomach (OR = 1.03, 95% CI: 1.02-1.04), as well as headache (OR = 1.10, 95% CI: 1.07-1.12), but not with pain on the face, hip, and knee. In the reverse direction, genetically instrumented multisite chronic pain (OR = 1.78 per one increment in the number of pain site, 95% CI: 1.51-2.11) and headache (OR = 1.55 per one log-unit increase in headache risk, 95% CI = 1.13-2.10) were associated with MDD. Functional annotation analysis showed differential clustering patterns where depression clustered closely with headache and neck/shoulder pain, exhibiting substantial brain tissue enrichment. Our study indicates that depression is a causal risk factor for headache and pain localized at neck/shoulder, back, and abdominal/stomach, rather than pain at face, hip, and knee, and suggests common neurological pathologies underlying the development of depression, headache, and neck/shoulder pain.

Genetic basis to structural grey matter associations with chronic pain

Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.

Developing nociceptor-selective treatments for acute and chronic pain

Despite substantial efforts dedicated to the development of new, nonaddictive analgesics, success in treating pain has been limited. Clinically available analgesic agents generally lack efficacy and may have undesirable side effects. Traditional target-based drug discovery efforts that generate compounds with selectivity for single targets have a high rate of attrition because of their poor clinical efficacy. Here, we examine the challenges associated with the current analgesic drug discovery model and review evidence in favor of stem cell–derived neuronal-based screening approaches for the identification of analgesic targets and compounds for treating diverse forms of acute and chronic pain.

"Lessons from Rare Forms of Osteoarthritis"

Osteoarthritis (OA) is one of the most prevalent conditions in the world, particularly in the developed world with a significant increase in cases and their predicted impact as we move through the twenty-first century and this will be exacerbated by the covid pandemic. The degeneration of cartilage and bone as part of this condition is becoming better understood but there are still significant challenges in painting a complete picture to recognise all aspects of the condition and what treatment(s) are most appropriate in individual causes. OA encompasses many different types and this causes some of the challenges in fully understanding the condition. There have been examples through history where much has been learnt about common disease(s) from the study of rare or extreme phenotypes, particularly where Mendelian disorders are involved. The often early onset of symptoms combined with the rapid and aggressive pathogenesis of these diseases and their predictable outcomes give an often-under-explored resource. It is these "rarer forms of disease" that William Harvey referred to that offer novel insights into more common conditions through their more extreme presentations. In the case of OA, GWAS analyses demonstrate the multiple genes that are implicated in OA in the general population. In some of these rarer forms, single defective genes are responsible. The extreme phenotypes seen in conditions such as Camptodactyly Arthropathy-Coxa Vara-pericarditis Syndrome, Chondrodysplasias and Alkaptonuria all present potential opportunities for greater understanding of disease pathogenesis, novel therapeutic interventions and diagnostic imaging. This review examines some of the rarer presenting forms of OA and linked conditions, some of the novel discoveries made whilst studying them, and findings on imaging and treatment strategies.

A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank

Background

Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK.

Methods

A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication.

Results

We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10⁻¹¹. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10⁻¹⁰ for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10⁻⁸ for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively).

Conclusions

We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

Sources of Individual Differences in Pain

Pain is an immense clinical and societal challenge, and the key to understanding and treating it is variability. Robust interindividual differences are consistently observed in pain sensitivity, susceptibility to developing painful disorders, and response to analgesic manipulations. This review examines the causes of this variability, including both organismic and environmental sources. Chronic pain development is a textbook example of a gene-environment interaction, requiring both chance initiating events (e.g., trauma, infection) and more immutable risk factors. The focus is on genetic factors, since twin studies have determined that a plurality of the variance likely derives from inherited genetic variants, but sex, age, ethnicity, personality variables, and environmental factors are also considered.

Joint disease-specificity at the regulatory base-pair level

Given the pleiotropic nature of coding sequences and that many loci exhibit multiple disease associations, it is within non-coding sequence that disease-specificity likely exists. Here, we focus on joint disorders, finding among replicated loci, that GDF5 exhibits over twenty distinct associations, and we identify causal variants for two of its strongest associations, hip dysplasia and knee osteoarthritis. By mapping regulatory regions in joint chondrocytes, we pinpoint two variants (rs4911178; rs6060369), on the same risk haplotype, which reside in anatomical site-specific enhancers. We show that both variants have clinical relevance, impacting disease by altering morphology. By modeling each variant in humanized mice, we observe joint-specific response, correlating with GDF5 expression. Thus, we uncouple separate regulatory variants on a common risk haplotype that cause joint-specific disease. By broadening our perspective, we finally find that patterns of modularity at GDF5 are also found at over three-quarters of loci with multiple GWAS disease associations.

The effect of common variants in GDF5 gene on the susceptibility to chronic postsurgical pain

Background

The growth differentiation factor 5 (GDF5) gene regulates the growth of neuronal axons and dendrites and plays a role in the inflammatory response and tissue damage. The gene may also be associated with chronic postsurgical pain. This study aimed to reveal the relationship between SNPs in the GDF5 gene and orthopedic chronic postsurgical pain in Han Chinese population based on a case-control study.

Methods

We genotyped 8 SNPs within GDF5 gene in 1048 surgical patients with chronic postsurgical pain as the case group and 2062 surgical patients who were pain free as the control group. SNP and haplotypic analyses were performed, and stratified analyses were conducted to determine the correlations between significant SNPs and clinical characteristics.

Results

Only rs143384 in the 5′UTR of GDF5 was identified as significantly associated with increased susceptibility to chronic postsurgical pain, and the risk of A allele carriers was increased approximately 1.35-fold compared with that of G allele carriers. Haplotypes AGG and GGG in the LD block rs143384-rs224335-rs739329 also showed similar association patterns. Furthermore, we found that rs143384 was significantly correlated with chronic postsurgical pain in the subgroup aged ≤ 61 years, subgroup with a BMI ≤ 26, subgroup with no-smoking or no pain history, and subgroup with a drinking history.

Conclusion

Our study provided supportive evidence that genetic variations in the GDF5 gene are potential genetic factors that can increase the risk of chronic postsurgical pain in the Han Chinese population, but further research is necessary to elucidate the underlying mechanism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02549-5.

Transcriptome-wide association study uncovers the role of essential genes in anthracycline-induced cardiotoxicity

Anthracyclines are highly effective chemotherapeutic agents; however, their clinical utility is limited by severe anthracycline-induced cardiotoxicity (ACT). Genome-wide association studies (GWAS) have uncovered several genetic variants associated with ACT, but the impact of these findings requires further elucidation. We conducted a transcriptome-wide association study (TWAS) using our previous GWAS summary statistics (n = 280 patients) to identify gene expression-related associations with ACT. We identified a genetic association between decreased expression of GDF5 and ACT (Z-score = -4.30, P = 1.70 × 10^-5), which was replicated in an independent cohort (n = 845 patients, P = 3.54 × 10^-3). Additionally, cell viability of GDF5-silenced human cardiac myocytes was significantly decreased in response to anthracycline treatment. Subsequent gene set enrichment and pathway analyses of the TWAS data revealed that genes essential for survival, cardioprotection and response to anthracyclines, as well as genes involved in ribosomal, spliceosomal and cardiomyopathy pathways are important for the development of ACT.

Genome-wide association study identifies RNF123 locus as associated with chronic widespread musculoskeletal pain

Background and objectives

Chronic widespread musculoskeletal pain (CWP) is a symptom of fibromyalgia and a complex trait with poorly understood pathogenesis. CWP is heritable (48%–54%), but its genetic architecture is unknown and candidate gene studies have produced inconsistent results. We conducted a genome-wide association study to get insight into the genetic background of CWP.

Methods

Northern Europeans from UK Biobank comprising 6914 cases reporting pain all over the body lasting >3 months and 242 929 controls were studied. Replication of three independent genome-wide significant single nucleotide polymorphisms was attempted in six independent European cohorts (n=43 080; cases=14 177). Genetic correlations with risk factors, tissue specificity and colocalisation were examined.

Results

Three genome-wide significant loci were identified (rs1491985, rs10490825, rs165599) residing within the genes Ring Finger Protein 123 (RNF123), ATPase secretory pathway Ca²⁺transporting 1 (ATP2C1) and catechol-O-methyltransferase (COMT). The RNF123 locus was replicated (meta-analysis p=0.0002), the ATP2C1 locus showed suggestive association (p=0.0227) and the COMT locus was not replicated. Partial genetic correlation between CWP and depressive symptoms, body mass index, age of first birth and years of schooling were identified. Tissue specificity and colocalisation analysis highlight the relevance of skeletal muscle in CWP.

Conclusions

We report a novel association of RNF123 locus and a suggestive association of ATP2C1 locus with CWP. Both loci are consistent with a role of calcium regulation in CWP. The association with COMT, one of the most studied genes in chronic pain field, was not confirmed in the replication analysis.

Osteoarthritis year in review: genetics, genomics, epigenetics

OBJECTIVE

In this review, we have highlighted advances in genetics, genomics and epigenetics in the field of osteoarthritis (OA) over the past year.

METHODS

A literature search was performed using PubMed and the criteria: "osteoarthritis" and one of the following terms "genetic(s), genomic(s), epigenetic(s), epigenomic(s), noncoding RNA, microRNA, long noncoding RNA, lncRNA, circular RNA, RNA sequencing, single cell sequencing, or DNA methylation between April 1, 2019 and April 30, 2020.

RESULTS

We identified 653 unique publications, many studies spanned multiple search terms. We summarized advances relating to evolutionary genetics, pain, ethnicity specific risk factors, functional studies of gene variants, and interactions between coding and non-coding RNAs in OA pathogenesis.

CONCLUSIONS

Studies have identified variants contributing to OA susceptibility, candidate biomarkers for diagnosis and prognosis, as well as promising therapeutic candidates. Validation in multiple cohorts, multi-omics strategies, and machine learning aided computational analyses have all contributed to the strength of published literature. Open access data-sets, greater sample sizes to capture broader populations and understanding disease mechanisms by investigating the interactions between multiple tissue types will further aid in progress towards understanding and curing OA.

Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium

OBJECTIVE

To determine the optimal combination of imaging and biochemical biomarkers to predict knee osteoarthritis (OA) progression.

METHODS

Nested case-control study from the FNIH OA Biomarkers Consortium of participants with Kellgren-Lawrence grade 1-3 and complete biomarker data (n=539 to 550). Cases were knees with radiographic and pain progression between 24-48 months from baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) with p<0.10 in univariate analysis were selected, including MRI (quantitative (Q) cartilage thickness and volume; semi-quantitative (SQ) MRI markers; bone shape and area; Q meniscal volume), radiographic (trabecular bone texture (TBT)), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using three different step-wise selection methods (complex vs. parsimonious models).

RESULTS

Among baseline biomarkers, the number of locations affected by osteophytes (SQ), Q central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and SQ Hoffa-synovitis predicted progression in most models (C-statistics 0.641-0.671). 24-month changes in SQ MRI markers (effusion-synovitis, meniscal morphology, and cartilage damage), Q central medial femoral cartilage thickness, Q medial tibial cartilage volume, Q lateral patellofemoral bone area, horizontal TBT (intercept term), and urine NTX-I predicted progression in most models (C-statistics 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, with higher C-statistics (0.716-0.832).

CONCLUSION

This study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to progress.

Genetics of pain: From rare Mendelian disorders to genetic predisposition to pain

Background and aim of the work:

Pain is defined by the International Association for the Study of Pain as “an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage”. In this mini-review, we focused on the Mendelian disorders with chronic pain as the main characteristic or where pain perception is disrupted, and on the polymorphisms that can impart susceptibility to chronic pain.

Methods:

We searched PubMed and Online Mendelian Inheritance in Man (OMIM) databases and selected only syndromes in which pain or insensitivity to pain were among the main characteristics. Polymorphisms were selected from the database GWAS catalog (https://www.ebi.ac.uk/gwas/home).

Results:

We retrieved a total of 28 genes associated with Mendelian inheritance in which pain or insensitivity to pain were the main characteristics and 70 polymorphisms associated with modulation of pain perception.

Conclusions:

This mini-review highlights the importance of genetics in phenotypes characterized by chronic pain or pain insensitivity. We think that an effective genetic test should analyze all genes associated with Mendelian pain disorders and all SNPs that can increase the risk of pain. (www.actabiomedica.it)

Identification of TGFβ signatures in six murine models mimicking different osteoarthritis clinical phenotypes

OBJECTIVE

TGFβ is a key player in cartilage homeostasis and OA pathology. However, few data are available on the role of TGFβ signalling in the different OA phenotypes. Here, we analysed the TGFβ pathway by transcriptomic analysis in six mouse models of OA.

METHOD

We have brought together seven expert laboratories in OA pathophysiology and, used inter-laboratories standard operating procedures and quality controls to increase experimental reproducibility and decrease bias. As none of the available OA models covers the complexity and heterogeneity of the human disease, we used six different murine models of knee OA: from post-traumatic/mechanical models (meniscectomy (MNX), MNX and hypergravity (HG-MNX), MNX and high fat diet (HF-MNX), MNX and seipin knock-out (SP-MNX)) to aging-related OA and inflammatory OA (collagenase-induced OA (CIOA)). Four controls (MNX-sham, young, SP-sham, CIOA-sham) were added. OsteoArthritis Research Society International (OARSI)-based scoring of femoral condyles and ribonucleic acid (RNA) extraction from tibial plateau samples were done by single operators as well as the transcriptomic analysis of the TGFβ family pathway by Custom TaqMan® Array Microfluidic Cards.

RESULTS

The transcriptomic analysis revealed specific gene signatures in each of the six models; however, no gene was deregulated in all six OA models. Of interest, we found that the combinatorial Gdf5-Cd36-Ltbp4 signature might discriminate distinct subgroups of OA: Cd36 upregulation is a hallmark of MNX-related OA while Gdf5 and Ltbp4 upregulation is related to MNX-induced OA and CIOA.

CONCLUSION

These findings stress the OA animal model heterogeneity and the need of caution when extrapolating results from one model to another.

Genetics of early growth traits

In recent years, genome-wide association studies have shed light on the genetics of early growth and its links with later-life health outcomes. Large-scale datasets and meta-analyses, combined with recently developed analytical methods, have enabled dissection of the maternal and fetal genetic contributions to variation in birth weight. Additionally, longitudinal approaches have shown differences between the genetic contributions to infant, childhood and adult adiposity. In contrast, studies of adult height loci have shown strong associations with early body length and childhood height. Early growth-associated loci provide useful tools for causal analyses: Mendelian randomization (MR) studies have provided evidence that early BMI and height are causally related to a number of adult health outcomes. We advise caution in the design and interpretation of MR studies of birth weight investigating effects of fetal growth on later-life cardiometabolic disease because birth weight is only a crude indicator of fetal growth, and the choice of genetic instrument (maternal or fetal) will greatly influence the interpretation of the results. Most genetic studies of early growth have to date centered on European-ancestry participants and outcomes measured at a single time-point, so key priorities for future studies of early growth genetics are aggregation of large samples of diverse ancestries and longitudinal studies of growth trajectories.

Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions

Chronic musculoskeletal pain affects all aspects of human life. However, mechanisms of its genetic control remain poorly understood. Genetic studies of pain are complicated by the high complexity and heterogeneity of pain phenotypes. Here, we apply principal component analysis to reduce phenotype heterogeneity of chronic musculoskeletal pain at four locations: the back, neck/shoulder, hip, and knee. Using matrices of genetic covariances, we constructed four genetically independent phenotypes (GIPs) with the leading GIP (GIP1) explaining 78.4% of the genetic variance of the analyzed conditions, and GIP2–4 explain progressively less. We identified and replicated five GIP1-associated loci and one GIP2-associated locus and prioritized the most likely causal genes. For GIP1, we showed enrichment with multiple nervous system-related terms and genetic correlations with anthropometric, sociodemographic, psychiatric/personality traits and osteoarthritis. We suggest that GIP1 represents a biopsychological component of chronic musculoskeletal pain, related to physiological and psychological aspects and reflecting pain perception and processing.

Yakov Tsepilov, Maxim Freidin et al. find that chronic musculoskeletal pain conditions at four distinct anatomical sites share a common genetic background. The authors constructed genetically independent phenotypes (GIP) from principal components analysis of the different pain phenotypes and used the GIPs to perform genome-wide association studies to identify underlying genetic factors.