Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis.

The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.

GlycA and CRP Are Genetically Correlated: Insight into the Genetic Architecture of Inflammageing.

Inflammageing is a condition of perpetual low-grade inflammation induced by ageing. Inflammageing may be predicted by the C-reactive protein (CRP) or by a recently described biomarker which measures N-glycosylated side chains of the carbohydrate component of several acute-phase proteins known as GlycA. The objective of this study was to examine in depth the genetic relationships between CRP and GlycA as well as between each of them and other selected cytokines, which may shed light on the mechanisms of inflammageing. Using the Olink 96 Inflammation panel, data on inflammatory mediators for 1518 twins from the TwinsUK dataset were acquired. Summary statistics for genome-wide association studies for several cytokines as well as CRP and GlycA were collected from public sources. Extensive genetic correlation analyses, colocalization and genetic enrichment analyses were carried out to detect the shared genetic architecture between GlycA and CRP. Mendelian randomization was carried out to assess potential causal relationships. GlycA predicted examined cytokines with a magnitude twice as great as that of CRP. GlycA and CRP were significantly genetically correlated (Rg = 0.4397 ± 0.0854, p-value = 2.60 × 10-7). No evidence of a causal relationship between GlycA and CRP, or between these two biomarkers and the cytokines assessed was obtained. However, the aforementioned relationships were explained well by horizontal pleiotropy. Five exonic genetic variants annotated to five genes explain the shared genetic architecture observed between GlycA and CRP: IL6R, GCKR, MLXIPL, SERPINA1, and MAP1A. GlycA and CRP possess a shared genetic architecture, but the relationship between them appears to be modest, which may imply the promotion of differing inflammatory pathways. GlycA appears to be a more robust predictor of cytokines compared to CRP.

Discovery of circulating blood biomarkers in patients with and without Modic changes of the lumbar spine: a preliminary analysis.

PURPOSE: The following study aimed to determine the existence of blood biomarkers in symptomatic patients with or without lumbar Modic changes (MC). METHODS: A cross-sectional sub-analyses of a prospective cohort was performed. Fasting blood samples were collected from patients with and without lumbar MC who had undergone spinal fusion or microdiscectomy. An 80-plex panel and CCL5/RANTES were used to assess preoperative plasma cytokine concentrations. Patient demographics and imaging phenotypes were also assessed. RESULTS: Thirty-one subjects were analysed (n = 18 no MC; n = 13 MC). No significant differences were found in age, sex, body mass index, smoking and alcohol history, and surgical procedure (i.e. fusion, decompression) between the two groups (p > 0.05). Several statistically significant blood biomarkers in MC patients were identified, including elevated levels of C-C Motif Chemokine Ligand 5 (CCL5, p = 0.0006), while Macrophage Migration Inhibitory Factor (MIF) was significantly lower (p = 0.009). Additionally, C-X-C Motif Chemokine Ligand 5 (CXCL5, p = 0.052), Pentraxin 3 (PTX3, p = 0.06) and Galectin-3 (Gal-3, p = 0.07) showed potential relevance. Moreover, MC patients exhibited significantly higher levels of disc degeneration (p = 0.0001) and displacement severity (p = 0.020). Based on multivariate analyses and controlling for disc degeneration/displacement, CCL5 (OR 1.02; 95% CI 1.002-1.033; p = 0.028) and MIF (OR 0.60; 95% CI 0.382-0.951; p = 0.030) were independently associated with MC patients. CONCLUSION: This "proof-of-concept" study is the first to identify specific and significantly circulating blood biomarkers associated with symptomatic patients with lumbar MC, independent of disc alterations of degeneration and/or bulges/herniations. Specifically, differences in CCL5 and MIF protein levels were significantly noted in MC patients compared to those without MC.

No evidence of association between either Modic change or disc degeneration and five circulating inflammatory proteins.

Introduction: Intervertebral disc degeneration and Modic change are the main spinal structural changes associated with chronic low back pain (LBP). Both conditions are thought to manifest local inflammation and if inflammatory proteins translocate to the blood circulation could be detected systemically. The work here assesses whether the presence of disc degeneration is associated with detectable blood level changes of five inflammatory markers and whether chronic LBP is associated with these changes. Materials and Methods: Two hundred and forty TwinsUK cohort participants with both MRI disc degeneration grade and Modic change extent, and IL-6, IL-8, IL-8 TNF, and CX3CL1 protein blood concentration measurements were included in this work. Linear mixed effects models were used to test the association of blood cytokine concentration with disc degeneration score and Modic change volumetric score. Association of chronic LBP status from questionnaires with disc degeneration, Modic change, and cytokine blood concentration was also tested. Results: No statistically significant association between disc degeneration or Modic change with cytokine blood concentration was found. Instead, regression analysis pointed strong association between cytokine blood concentration with body mass index for IL-6 and with age for IL-6 and TNF. Mild association was found between IL-8 blood concentration and body mass index. Additionally, LBP status was associated with Modic change volumetric score but not associated with any cytokine concentration. Conclusions: We found no evidence that Modic change and disc degeneration are able to produce changes in tested blood cytokine concentration. However, age and body mass index have strong influence on cytokine concentration and both are associated with the conditions studied which may confound associations found in the literature. It is then unlikely that cytokines produced in the disc or vertebral bone marrow induce chronic LBP.

Treatment response in rheumatoid arthritis is predicted by the microbiome: a large observational study in UK DMARD-naïve patients.

OBJECTIVES: Disease-modifying antirheumatic drugs (DMARDs) are first line treatment in rheumatoid arthritis (RA). Treatment response to DMARDs is patient-specific, dose efficacy is difficult to predict and long-term results variable. The gut microbiota are known to play a pivotal role in prodromal and early-disease RA, manifested by Prevotella spp. enrichment. The clinical response to therapy may be mediated by microbiota, and large-scale studies assessing the microbiome are few. This study assessed whether microbiome signals were associated with, and predictive of, patient response to DMARD-treatment. Accurate early identification of those who will respond poorly to DMARD therapy would allow selection of alternative treatment (e.g. biologic therapy), and potentially improve patient outcome. METHODS: A multicentre, longitudinal, observational study of stool- and saliva microbiome was performed in DMARD-naïve, newly diagnosed RA patients during introduction of DMARD treatment. Clinical data and samples were collected at baseline (n = 144) in DMARD-naïve patients and at six weeks (n = 117) and 12 weeks (n = 95) into DMARD-therapy. Samples collected (n = 365 stool, n = 365 saliva) underwent shotgun sequencing. Disease activity measures were collected at each timepoint and minimal clinically important improvement determined. RESULTS: In total, 26 stool microbes were found to decrease in those manifesting a minimal clinically important improvement. Prevotella spp. and Streptococcus spp. were the predominant taxa to decline following six weeks and 12 weeks of DMARDs, respectively. Furthermore, baseline microbiota of DMARD-naïve patients were indicative of future response. CONCLUSION: DMARDs appear to restore a perturbed microbiome to a eubiotic state. Moreover, microbiome status can be used to predict likelihood of patient response to DMARD.

Screening for Circulating Inflammatory Proteins Does Not Reveal Plasma Biomarkers of Constant Tinnitus.

BACKGROUND AND OBJECTIVE: Tinnitus would benefit from an objective biomarker. The goal of this study is to identify plasma biomarkers of constant and chronic tinnitus among selected circulating inflammatory proteins. METHODS: A case-control retrospective study on 548 cases with constant tinnitus and 548 matched controls from the Swedish Tinnitus Outreach Project (STOP), whose plasma samples were examined using Olink's Inflammatory panel. Replication and meta-analysis were performed using the same method on samples from the TwinsUK cohort. Participants from LifeGene, whose blood was collected in Stockholm and Umeå, were recruited to STOP for a tinnitus subtyping study. An age and sex matching was performed at the individual level. TwinsUK participants (n = 928) were selected based on self-reported tinnitus status over 2 to 10 years. Primary outcomes include normalized levels for 96 circulating proteins, which were used as an index test. No reference standard was available in this study. RESULTS: After adjustment for age, sex, BMI, smoking, hearing loss, and laboratory site, the top proteins identified were FGF-21, MCP4, GDNF, CXCL9, and MCP-1; however, these were no longer statistically significant after correction for multiple testing. Stratification by sex did not yield any significant associations. Similarly, associations with hearing loss or other tinnitus-related comorbidities such as stress, anxiety, depression, hyperacusis, temporomandibular joint disorders, and headache did not yield any significant associations. Analysis in the TwinsUK failed in replicating the top candidates. Meta-analysis of STOP and TwinsUK did not reveal any significant association. Using elastic net regularization, models exhibited poor predictive capacity tinnitus based on inflammatory markers [sensitivity = 0.52 (95% CI 0.47-0.57), specificity = 0.53 (0.48-0.58), positive predictive value = 0.52 (0.47-0.56), negative predictive values = 0.53 (0.49-0.58), and AUC = 0.53 (0.49-0.56)]. DISCUSSION: Our results did not identify significant associations of the selected inflammatory proteins with constant tinnitus. Future studies examining longitudinal relations among those with more severe tinnitus and using more recent expanded proteomics platforms and sampling of cerebrospinal fluid could increase the likelihood of identifying relevant molecular biomarkers.

Accurate phenotypic classification and exome sequencing allow identification of novel genes and variants associated with adult-onset hearing loss.

Adult-onset progressive hearing loss is a common, complex disease with a strong genetic component. Although to date over 150 genes have been identified as contributing to human hearing loss, many more remain to be discovered, as does most of the underlying genetic diversity. Many different variants have been found to underlie adult-onset hearing loss, but they tend to be rare variants with a high impact upon the gene product. It is likely that combinations of more common, lower impact variants also play a role in the prevalence of the disease. Here we present our exome study of hearing loss in a cohort of 532 older adult volunteers with extensive phenotypic data, including 99 older adults with normal hearing, an important control set. Firstly, we carried out an outlier analysis to identify genes with a high variant load in older adults with hearing loss compared to those with normal hearing. Secondly, we used audiometric threshold data to identify individual variants which appear to contribute to different threshold values. We followed up these analyses in a second cohort. Using these approaches, we identified genes and variants linked to better hearing as well as those linked to worse hearing. These analyses identified some known deafness genes, demonstrating proof of principle of our approach. However, most of the candidate genes are novel associations with hearing loss. While the results support the suggestion that genes responsible for severe deafness may also be involved in milder hearing loss, they also suggest that there are many more genes involved in hearing which remain to be identified. Our candidate gene lists may provide useful starting points for improved diagnosis and drug development.

The Human Microbiome and Its Role in Musculoskeletal Disorders.

Musculoskeletal diseases (MSDs) are characterized as injuries and illnesses that affect the musculoskeletal system. MSDs affect every population worldwide and are associated with substantial global burden. Variations in the makeup of the gut microbiota may be related to chronic MSDs. There is growing interest in exploring potential connections between chronic MSDs and variations in the composition of gut microbiota. The human microbiota is a complex community consisting of viruses, archaea, bacteria, and eukaryotes, both inside and outside of the human body. These microorganisms play crucial roles in influencing human physiology, impacting metabolic and immunological systems in health and disease. Different body areas host specific types of microorganisms, with facultative anaerobes dominating the gastrointestinal tract (able to thrive with or without oxygen), while strict aerobes prevail in the nasal cavity, respiratory tract, and skin surfaces (requiring oxygen for development). Together with the immune system, these bacteria have coevolved throughout time, forming complex biological relationships. Changes in the microbial ecology of the gut may have a big impact on health and can help illnesses develop. These changes are frequently impacted by lifestyle choices and underlying medical disorders. The potential for safety, expenses, and efficacy of microbiota-based medicines, even with occasional delivery, has attracted interest. They are, therefore, a desirable candidate for treating MSDs that are chronic and that may have variable progression patterns. As such, the following is a narrative review to address the role of the human microbiome as it relates to MSDs.

Multi-Trait Exome-Wide Association Study of Back Pain-Related Phenotypes.

Back pain (BP) is a major contributor to disability worldwide, with heritability estimated at 40-60%. However, less than half of the heritability is explained by common genetic variants identified by genome-wide association studies. More powerful methods and rare and ultra-rare variant analysis may offer additional insight. This study utilized exome sequencing data from the UK Biobank to perform a multi-trait gene-based association analysis of three BP-related phenotypes: chronic back pain, dorsalgia, and intervertebral disc disorder. We identified the SLC13A1 gene as a contributor to chronic back pain via loss-of-function (LoF) and missense variants. This gene has been previously detected in two studies. A multi-trait approach uncovered the novel FSCN3 gene and its impact on back pain through LoF variants. This gene deserves attention because it is only the second gene shown to have an effect on back pain due to LoF variants and represents a promising drug target for back pain therapy.

Repurposing Antihypertensive and Statin Medications for Spinal Pain: A Mendelian Randomization Study.

STUDY DESIGN: Mendelian randomization (MR) study. OBJECTIVE: To examine whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal pain (back or neck pain). SUMMARY OF BACKGROUND DATA: Observational studies and a recent MR study have found associations between elevated blood pressure and a greater risk of back pain. Observational studies have found associations between hyperlipidemia and statin use and greater risk of back pain. No prior MR studies have examined the effects of antihypertensives or statins on spinal pain. MATERIALS AND METHODS: This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies (GWAS). Sample sizes in exposure GWASs were n=757,601 (systolic blood pressure) and n=173,082 (low-density lipoprotein cholesterol), and n=1,028,947 for the outcome GWAS of spinal pain defined as health care seeking for any spinal pain-related diagnosis. Genes and cis-acting variants were identified as proxies for the drug targets of interest. MR analyses used inverse-variance weighted meta-analysis. The threshold for statistical significance after correction for multiple testing was P <0.0125. RESULTS: No statistically significant associations of these medications with spinal pain were found. However, findings were suggestive of a protective effect of beta-blockers on spinal pain risk (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72-0.98; P =0.03), and calcium channel blockers on greater spinal pain risk (OR 1.12, 95% CI 1.02-1.24; P =0.02). CONCLUSIONS: A protective effect of beta-blockers on spinal pain was suggested in the current study, consistent with findings from observational studies of various other pain phenotypes. The detrimental effect of calcium channel blockers on spinal pain suggested in the current study must be interpreted in the context of conflicting directions of effect on nonspinal pain phenotypes in other observational studies.This Mendelian randomization study examined whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal.This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies ranging size from 173,082 to 1,028,947 adults.While no statistically significant associations were found, a protective effect of beta-blockers on spinal pain was suggested (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72 to 0.98; p= 0.03), as was a detrimental effect of calcium channel blockers on spinal pain (OR 1.12, 95% CI 1.02 to 1.24; p= 0.02).

Modic change is associated with increased BMI but not autoimmune diseases in TwinsUK.

PURPOSE: Low back pain (LBP) is one of the largest causes of morbidity worldwide. The aetiology of LBP is complex, and many factors contribute to the onset. Bone marrow lesions within the vertebra adjacent to an intervertebral degenerate disc named Modic change (MC) have been suggested as a diagnostic subgroup of LBP. Autoimmune response has been proposed to be one of the causes that promote the development of MC. The aim of the current investigation is to assess prevalence and severity of MC and LBP in participants with an autoimmune disease diagnosis in a well-documented cohort of adult twin volunteers. METHODS: Multivariate generalized mixed linear models (GLMM) were implemented in order to calculate the association between having an autoimmune disorder and MC prevalence, width and severe and disabling LBP. The model was corrected for family structure as well as for covariates such as age, BMI and smoking. RESULTS: No association was found between diagnosis of autoimmune disorder and MC. Interestingly, BMI was independently associated with MC width but not to MC prevalence. These results help to shed light on the relationship between MC and autoimmunity as well as the role of BMI in the development of the lesions. CONCLUSION: This study is the first to examine autoimmune disorders and MC prevalence in a large, population-based female cohort. The study was well powered to detect a small effect. No association was found between having a diagnosis of one or more autoimmune conditions and MC prevalence, width or LBP.

Assessment of the socio-economic impacts associated with the arrival of apple snail (Pomacea canaliculata) in Mwea irrigation scheme, Kenya.

BACKGROUND: In Kenya, rice (Oryza sativa L.) is mainly produced under irrigation by small-scale farmers. Mwea irrigation scheme (MIS) in Kirinyaga County accounts for 80-88% of rice production. Here, rice is the main source of livelihood and a source of revenue generation for the county. However, a recently established invasive freshwater snail, Pomacea canaliculata (Lamarck) (family: Ampullariidae), a species of apple snail, presents a serious threat to rice production. RESULTS: Household surveys, focus group discussions and key informant interviews highlight apple snail as a serious problem in MIS. Households that observed at least a moderate level of infestation (>20% of cultivated area) experienced significant reductions in rice yield (~14%) and net rice income (~60%). Farmers reported increased use of chemical pesticides for management of apple snail. In addition, the cost of hired labor for physical removal of egg masses and snails is resulting in substantial negative effects on net income. Farmer age, area of land owned, responsibility for decision-making, receipt of extension advice, training, and membership of a farmer organization, were all statistically significant variables to explain farmers awareness of the need for area-wide apple snail management. CONCLUSION: Strategies to limit the spread of apple snail are urgently needed. A Multi-Institutional Technical Team (MITT) has been established to spearhead management efforts and consolidate advice to farmers on how to manage apple snail. However, without action to mitigate spread, the consequences could be disastrous for rice production and food security in Kenya, and for other rice growing regions across Africa. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

African agri-entrepreneurship in the face of the COVID-19 pandemic.

Background: The African continent is known for high entrepreneurial activity, especially in the agricultural sector. Despite this, the continent's economic development is below expectations, due to numerous factors constraining the growth and sustainability of agricultural SMEs. These constraints have been exacerbated by the COVID-19 pandemic. The purpose of this study was to understand the pathways through which the pandemic affected agri-SMEs, with specific focus on assessing the differentiated effects arising from the size of the agri-SME and the gender of the owner-manager. Methods: Data was collected from over 100 agri-SMEs, ranging in size from sole proprietorships with one employee to agri-SMEs employing up to 100 people, in six African countries. Mixed methods were used to analyse the data with changes in business operations arising from changing market access, regimented health and safety guidelines and constrained labour supply assessed using visualisations and descriptive statistics. Logistic regression modelling was employed to determine the set of variables contributing to agri-SME business downturn during the COVID-19 pandemic. Results: All surveyed agri-SMEs were negatively affected by COVID-19-associated restrictions with the size of the firm and gender of the owner-managers resulting in differentiated impacts. The smallest agri-SMEs, mainly owner-managed by women, were more likely to experience disruptions in marketing their goods and maintaining their labour supply. Larger agri-SMEs made changes to their business operations to comply with government guidelines during the pandemic and made investments to manage their labour supply, thus sustaining their business operations. In addition, logistic regression modelling results show that financing prior to the pandemic, engaging in primary agricultural production, and being further from urban centres significantly influenced the likelihood of a firm incurring business losses. Conclusions: These findings necessitate engendered multi-faceted agri-SME support packages that are tailored for smaller-sized agri-SMEs. Any such support package should include support for agri-SMEs to develop sustainable marketing strategies and help them secure flexible financing that considers payment deferrals and debt moratorium during bona fide market shocks such as the COVID-19 pandemic.

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain.

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain.

Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.

Accurate phenotypic classification and exome sequencing allow identification of novel genes and variants associated with adult-onset hearing loss.

Adult-onset progressive hearing loss is a common, complex disease with a strong genetic component. Although to date over 150 genes have been identified as contributing to human hearing loss, many more remain to be discovered, as does most of the underlying genetic diversity. Many different variants have been found to underlie adult-onset hearing loss, but they tend to be rare variants with a high impact upon the gene product. It is likely that combinations of more common, lower impact variants also play a role in the prevalence of the disease. Here we present our exome study of hearing loss in a cohort of 532 older adult volunteers with extensive phenotypic data, including 99 older adults with normal hearing, an important control set. Firstly, we carried out an outlier analysis to identify genes with a high variant load in older adults with hearing loss compared to those with normal hearing. Secondly, we used audiometric threshold data to identify individual variants which appear to contribute to different threshold values. We followed up these analyses in a second cohort. Using these approaches, we identified genes and variants linked to better hearing as well as those linked to worse hearing. These analyses identified some known deafness genes, demonstrating proof of principle of our approach. However, most of the candidate genes are novel associations with hearing loss. While the results support the suggestion that genes responsible for severe deafness may also be involved in milder hearing loss, they also suggest that there are many more genes involved in hearing which remain to be identified. Our candidate gene lists may provide useful starting points for improved diagnosis and drug development.

Are current machine learning applications comparable to radiologist classification of degenerate and herniated discs and Modic change? A systematic review and meta-analysis.

INTRODUCTION: Low back pain is the leading contributor to disability burden globally. It is commonly due to degeneration of the lumbar intervertebral discs (LDD). Magnetic resonance imaging (MRI) is the current best tool to visualize and diagnose LDD, but places high time demands on clinical radiologists. Automated reading of spine MRIs could improve speed, accuracy, reliability and cost effectiveness in radiology departments. The aim of this review and meta-analysis was to determine if current machine learning algorithms perform well identifying disc degeneration, herniation, bulge and Modic change compared to radiologists. METHODS: A PRISMA systematic review protocol was developed and four electronic databases and reference lists were searched. Strict inclusion and exclusion criteria were defined. A PROBAST risk of bias and applicability analysis was performed. RESULTS: 1350 articles were extracted. Duplicates were removed and title and abstract searching identified original research articles that used machine learning (ML) algorithms to identify disc degeneration, herniation, bulge and Modic change from MRIs. 27 studies were included in the review; 25 and 14 studies were included multi-variate and bivariate meta-analysis, respectively. Studies used machine learning algorithms to assess LDD, disc herniation, bulge and Modic change. Models using deep learning, support vector machine, k-nearest neighbors, random forest and naïve Bayes algorithms were included. Meta-analyses found no differences in algorithm or classification performance. When algorithms were tested in replication or external validation studies, they did not perform as well as when assessed in developmental studies. Data augmentation improved algorithm performance when compared to models used with smaller datasets, there were no performance differences between augmented data and large datasets. DISCUSSION: This review highlights several shortcomings of current approaches, including few validation attempts or use of large sample sizes. To the best of the authors' knowledge, this is the first systematic review to explore this topic. We suggest the utilization of deep learning coupled with semi- or unsupervised learning approaches. Use of all information contained in MRI data will improve accuracy. Clear and complete reporting of study design, statistics and results will improve the reliability and quality of published literature.

Genotype-by-environment interactions in chronic back pain.

BACKGROUND CONTEXT: Chronic back pain (CBP) is a common debilitating condition with substantial societal impact. While understanding genotype-by-environment (GxE) interactions may be crucial to achieving the goals of personalized medicine, there are few large-scale studies investigating this topic for CBP. None of them systematically explore multiple CBP risk factors. PURPOSE: To estimate the extent to which genetic effects on CBP are modified by known demographic and clinical risk factors. RESEARCH DESIGN: Case-control study, genome-wide GxE interaction study. PATIENT SAMPLE: Data on up to 331,610 unrelated participants (57,881 CBP cases and 273,729 controls) from the UK Biobank cohort were used. UK Biobank is a prospective cohort with collected deep genetic and phenotypic data on approximately 500,000 individuals across the UK. OUTCOME MEASURES: Self-reported chronic back pain. METHODS: We applied a whole-genome approach to estimate the proportion of phenotypic variance explained by interactions between genotype and 12 known risk factors. We also analyzed if effects of common single-nucleotide polymorphisms on CBP are changed in presence of known risk factors. RESULTS: The results indicate a modest, if any, modification of genetic effects by examined risk factors in CBP. Our estimates suggest that detecting such weak effects would require a sample size of millions of individuals. CONCLUSIONS: The GxE interactions with examined common risk factors for CBP are either weak or absent. Interactions of such magnitude are unlikely to have the potential to inform and influence treatment strategies. Risk estimation models may use common genetic variation and the considered risk factors as independent predictors, without accounting for GxE.

Evidence of causal effects of blood pressure on back pain and back pain on type II diabetes provided by a bidirectional Mendelian randomization study.

BACKGROUND CONTEXT: Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation. PURPOSE: To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa. STUDY DESIGN: Bidirectional Mendelian randomization (MR) study. PATIENT SAMPLES: Genome-wide association studies (GWAS) with sample sizes between 173,082 and 1,028,947 participants. OUTCOME MEASURES: Outcomes included (1) back pain associated with health care use (BP-HC) in the forward MR; and (2) seven cardiovascular phenotypes in the reverse MR, including 2 measurements used for the evaluation of hypertension (diastolic blood pressure and systolic blood pressure), 4 phenotypes related to dyslipidemia (LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides), and type II diabetes. METHODS: We used summary statistics from large, publicly available GWAS for BP-HC and the 7 cardiovascular phenotypes to obtain genetic instrumental variables. We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis, Causal Analysis Using Summary Effect (CAUSE), and sensitivity analyses. RESULTS: In forward MR analyses of seven cardiovascular phenotypes, diastolic blood pressure was associated with BP-HC across all analyses (IVW estimate: OR = 1.10 per 10.5 mm Hg increase [1.04-1.17], p-value = .001), and significant associations of systolic blood pressure with BP-HC were also found (IVW estimate: OR = 1.09 per 19.3 mm Hg increase [1.04-1.15], p-value = .0006). In reverse MR analyses, only type II diabetes was associated with BP-HC across all analyses (IVW estimate: OR = 1.40 [1.13-1.73], p-value = .002). CONCLUSIONS: These findings from analyses of large, population-based samples indicate that higher blood pressure increases the risk of BP-HC, and BP-HC itself increases the risk of type II diabetes.

Long-COVID fatigue is not predicted by pre-pandemic plasma IL-6 levels in mild COVID-19.

OBJECTIVE AND DESIGN: Fatigue is a prominent symptom in the general population and may follow viral infection, including SARS-CoV2 infection which causes COVID-19. Chronic fatigue lasting more than three months is the major symptom of the post-COVID syndrome (known colloquially as long-COVID). The mechanisms underlying long-COVID fatigue are unknown. We hypothesized that the development of long-COVID chronic fatigue is driven by the pro-inflammatory immune status of an individual prior to COVID-19. SUBJECTS AND METHODS: We analyzed pre-pandemic plasma levels of IL-6, which plays a key role in persistent fatigue, in N = 1274 community dwelling adults from TwinsUK. Subsequent COVID-19-positive and -negative participants were categorized based on SARS-CoV-2 antigen and antibody testing. Chronic fatigue was assessed using the Chalder Fatigue Scale. RESULTS: COVID-19-positive participants exhibited mild disease. Chronic fatigue was a prevalent symptom among this population and significantly higher in positive vs. negative participants (17% vs 11%, respectively; p = 0.001). The qualitative nature of chronic fatigue as determined by individual questionnaire responses was similar in positive and negative participants. Pre-pandemic plasma IL-6 levels were positively associated with chronic fatigue in negative, but not positive individuals. Raised BMI was associated with chronic fatigue in positive participants. CONCLUSIONS: Pre-existing increased IL-6 levels may contribute to chronic fatigue symptoms, but there was no increased risk in individuals with mild COVID-19 compared with uninfected individuals. Elevated BMI also increased the risk of chronic fatigue in mild COVID-19, consistent with previous reports.