Johnston County Research Articles

Prevalence and Factors Associated With High-Impact Chronic Pain in Knee Osteoarthritis: The Johnston County Health Study

Pain is a hallmark symptom of knee osteoarthritis (KOA), yet intensity and severity vary widely among individuals. There is a knowledge gap in understanding key characteristics of high-impact chronic pain (HICP) within the context of KOA. Therefore, our first purpose was to examine the prevalence of HICP in a cohort of individuals with radiographic evidence of KOA, and our second purpose was to assess patient-level factors associated with HICP. Data from the Johnston County Health Study were used to compare those with and without HICP. Variables included sociodemographic factors, clinical factors, health care use, and psychosocial distress. HICP status was classified with Patient-Reported Outcomes Measurement Information System (PROMIS) Pain Interference and Physical Function measures. The results indicated that 15.5% (48/310) of participants were classified as having HICP when the PROMIS-Pain Interference cutoff score was used, while 21.2% (66/310) were classified as having HICP with a PROMIS-Physical Function cutoff score. Multivariable analyses indicated that HICP was consistently characterized by increased kinesiophobia and somatization, regardless of PROMIS measure used for HICP status. A secondary insight was that HICP was not consistently characterized by sociodemographic and clinical variables, as these findings were dependent on PROMIS measure used. These findings could be used to develop intervention approaches specific to individuals with KOA and to inform future investigations of sociodemographic and clinical factors associated with HICP. PerspectiveThese findings provide additional information on the characterization of HICP for individuals with KOA. There was consistency in psychosocial factors associated with HICP, while sociodemographic and clinical factors varied based on how HICP status was defined.

Diminished vibration perception and greater pressure pain sensitivity are associated with worse knee osteoarthritis outcomes across sex and race

ObjectiveTo examine associations of vibration sensitivity and pressure pain sensitivity with knee osteoarthritis (OA) outcomes across sex and race, which may relate to known sex and race disparities in clinical outcomes. DesignData were from the 2013-2015 visit of the Johnston County Osteoarthritis Project. Exposures were vibration perception threshold (VPT) measured at the bilateral medial femoral condyle (MFC) and first metatarsophalangeal joint (MTP), and pressure pain threshold (PPT) measured at the bilateral upper trapezius. Outcomes were knee pain severity and presence of knee symptoms, radiographic knee OA, and symptomatic knee OA in each knee. Cross-sectional associations of the exposures with the outcomes were examined using logistic regression models, overall and separately by sex and race. ResultsIn the VPT and PPT analyses, 851 and 862 participants (mean age 71 years, 68% female, 33% Black, body mass index 31 kg/m2) and 1585 and 1660 knees were included, respectively. Higher VPT (lower vibration sensitivity) at the MFC and first MTP joint was associated with all outcomes. Lower PPT (greater pressure pain sensitivity) was associated with greater knee pain severity. Associations of VPT and PPT with all outcomes were similar among females and males and Black and White individuals. ConclusionsDiminished vibration perception and greater pressure pain sensitivity were cross-sectionally associated with worse knee OA outcomes. Despite differences in VPT and PPT among females and males and Black and White adults, associations with knee OA outcomes did not differ by sex or race, suggesting neurophysiological differences do not relate to established disparities.

Occurrence and Distribution of Meloidogyne spp. in Fields Rotated with Sweetpotato and Host Range of a North Carolina Population of Meloidogyne enterolobii.

Root-knot nematodes (RKNs, Meloidogyne spp.) are some of the most economically important and common plant parasitic nematodes in North Carolina (NC) cropping systems. Soil samples collected from fields planted with crops rotated with sweetpotato (Ipomoea batatas [L.] Lam.) in 39 NC counties in 2015 to 2018 were processed at the NC Nematode Assay Laboratory. The occurrence of second-stage juvenile (J2) RKN populations was examined based on collection year, month, county, and previous planted crop. The highest number of RKN-positive samples originated from Cumberland (53%), Sampson (48%), and Johnston (48%) counties. The highest average RKN population density was detected in Sampson (147 J2/500 cm3 of soil) and Nash (135 J2/500 cm3 of soil) counties, while Wayne (7 J2/500 cm3 of soil) and Greene (11 J2/500 cm3 of soil) counties had the lowest average RKN population density. Meloidogyne enterolobii is a new invasive species that is impacting sweetpotato growers of NC. The host status of an NC population of M. enterolobii, the guava RKN, was determined by examining eggs per gram of fresh root (ER) and the final nematode egg population divided by the initial population egg count (reproductive factor, RF) in greenhouse experiments. This included 18 vegetable, field, and cover crops and weed species. The tomato 'Rutgers' was used as a susceptible control. Cabbage 'Stonehead', pepper 'Red Bull', and watermelon 'Charleston Gray' and 'Fascination' were hosts and had similar mean ER values to the positive control, ranging from 64 to 18,717. Among field crops, cotton, soybean 'P5018RX', and tobacco were hosts with ER values that ranged from 185 to 706. Members of the Poaceae family such as sweet corn (Zea mays) and sudangrass (Sorghum × drummondii) were nonhosts to M. enterolobii, and the mean ER values ranged from 1.85 to 7. The peanut 'Tifguard' and winter wheat (Triticum aestivum) also had lower ER values than the vegetable hosts. Growers should consider planting less susceptible hosts or nonhosts such as peanut, sudangrass, sweet corn, and winter wheat in 2- to 3-year crop rotations to lower populations of this invasive nematode.

Occupational tasks associated with shoulder pain and upper extremity disability: a cross-sectional study in the Johnston County Osteoarthritis Project

BackgroundShoulder pain is a leading cause of disability. Occupations requiring high upper extremity demands may put workers at greater risk of shoulder injury and resulting pain. We examined associations of occupation with shoulder pain and upper extremity disability in the Johnston County Osteoarthritis Project.MethodsWork industry and occupational tasks for the longest job held were collected from participants. At follow-up ranging from 4–10 years later, participants were asked about shoulder symptoms (pain, aching, or stiffness occurring most days of 1 month in the last year) and given a 9-item, modified Disabilities Arm Shoulder and Hand (DASH) questionnaire to categorize disability from 0–4 (none-worst). Logistic regression and cumulative logit regression models were used to estimate associations with prevalent shoulder symptoms and with worse disability category, respectively. Models were adjusted for cohort, age, sex, race, education and time to follow-up. Sex- and race-stratified associations were evaluated.ResultsAmong 1560 included participants, mean age was 62 years (standard deviation ± 9 years); 32% were men, and 31% were Black. Compared to the managerial/professional industry, higher odds of both shoulder symptoms and worse upper extremity disability were seen for most industrial groups with physically demanding jobs, particularly the service industry. Work that often or always required lifting/moving > 10 lbs. was associated with higher odds of shoulder symptoms. Work that sometimes or always required heavy work while standing was associated with higher odds of shoulder symptoms, and this association was stronger among men and White workers.ConclusionPhysically demanding occupations were associated with increased occurrence of shoulder pain and disability. Mitigating specific physical work demands may reduce shoulder-related disability.

Tick-Borne Disease Infections and Chronic Musculoskeletal Pain

Tick-borne diseases (TBDs) other than Lyme disease, such as spotted fever group rickettsiosis, ehrlichiosis, and galactose-α-1,3-galactose (α-gal) syndrome, are an emerging public health issue. Long-term sequelae secondary to Ehrlichia or Rickettsia infection are uncommon; however, musculoskeletal symptoms are often attributed to prior tick exposure. To evaluate the potential associations between prior exposure to TBDs and musculoskeletal symptoms, including radiographic osteoarthritis. This cross-sectional study analyzed serum samples from the fourth visit (2017-2018) of the Johnston County Osteoarthritis (JoCo OA) project, an ongoing longitudinal, population-based study in Johnston County, North Carolina. Biospecimen testing and analysis were performed between May 2022 and November 2023. Participants in the JoCo OA project are noninstitutionalized White and Black Johnston County residents 45 years or older. The primary outcome was seropositivity with Ehrlichia IgG, Rickettsia IgG, and/or α-gal IgE and musculoskeletal symptoms. Secondary outcomes included risk factors associated with elevated α-gal IgE and weighted population point prevalence rates. Participants completed questionnaires, underwent physical assessments, and provided biospecimens for serological testing. Multivariable models were used to estimate associations of interest. Of the 605 participants who completed the fourth visit of the JoCo OA project, 488 (80.7%) had serum samples available for testing. The 488 participants had a median (IQR) age of 72 (68-78) years and included 336 females (68.9%) and 161 Black (33.0%) and 327 White (67.0%) individuals. The overall weighted point prevalence was 8.6% (95% CI, 5.9%-11.3%) for Ehrlichia IgG, 17.1% (95% CI, 12.6%-21.5%) for Rickettsia IgG, and 19.6% (95% CI, 15.3%-23.8%) for α-gal IgE level greater than 0.1 IU/mL. Only α-gal IgE was associated with knee pain, aching or stiffness (mean ratio, 1.30; 95% CI, 1.09-1.56). Antibodies to Rickettsia, Ehrlichia, and α-gal were not associated with symptomatic radiographic knee osteoarthritis. Male sex (odds ratio [OR], 2.63; 95% CI, 1.55-4.47), current smoker status (OR, 3.55; 95% CI, 1.38-9.18), and an attached tick bite in the past 5 years (OR, 3.99; 95% CI, 2.22-7.15) were all risk factors that were associated with α-gal IgE level greater than 0.1 IU/mL. Despite only 84 individuals (17.2%) recalling a tick bite in the past 5 years, 178 (36.5%) had evidence of prior tick-borne exposure, suggesting frequent human-tick interactions. Results of this cross-sectional study indicate no association between Ehrlichia or Rickettsia seropositivity and chronic musculoskeletal symptoms or osteoarthritis. Further investigation is needed into the pathogenesis of α-gal syndrome and interventions to reduce human-tick interactions.

Association of Foot Symptoms With Decreased Time to All-Cause Mortality: The Johnston County Osteoarthritis Project.

Adults with foot symptoms (ie, pain, aching, or stiffness) may be at increased risk of reduced time to all-cause mortality. The purpose of this study was to evaluate whether foot symptoms are independently associated with all-cause mortality in older adults. We analyzed longitudinal data from 2613 participants from the Johnston County Osteoarthritis Project, a longitudinal population-based cohort of adults 45 years of age and older. Participants completed questionnaires at baseline to determine presence of foot symptoms and covariable status. Baseline walking speed was measured via an 8-foot walk test. To examine the association of foot symptoms with time to mortality, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox regression models, adjusted for potential confounders. We observed 813 deaths over 4 to 14.5 years of follow-up. At baseline, 37% of participants had foot symptoms, mean age was 63 years, mean body mass index was approximately 31 kg/m2 , 65% were women, and 33% were Black. Moderate to severe foot symptoms were associated with reduced time to mortality after adjustment for demographics, comorbidities, physical activity, and knee and hip symptoms (HR=1.30, 95% CI 1.09-1.54). Importantly, this association was not modified by walking speed or diabetes. Individuals with foot symptoms had an increased hazard of all-cause mortality compared with those with no foot symptoms. These effects were independent of key confounders and were not moderated by walking speed. Effective interventions to identify and manage at least moderate foot symptoms may reduce the risk of decreased time to mortality.

Serum proteomic biomarkers diagnostic of knee osteoarthritis

To better understand the pathogenesis of knee osteoarthritis (OA) through identification of serum diagnostics. We conducted multiple reaction monitoring mass spectrometry analysis of 107 peptides in baseline sera of two cohorts: the Foundation for National Institutes of Health (NIH) (n=596 Kellgren-Lawrence (KL) grade 1-3 knee OA participants); and the Johnston County Osteoarthritis Project (n=127 multi-joint controls free of radiographic OA of the hands, hips, knees (bilateral KL=0), and spine). Data were split into (70%) training and (30%) testing sets. Diagnostic peptide and clinical data predictors were selected by random forest (RF); selection was based on association (p<0.05) with OA status in multivariable logistic regression models. Model performance was based on area under the curve (AUC) of receiver operating characteristic (ROC) and precision-recall (PR) curves. RF selected 23 peptides (19 proteins) and body mass index (BMI) as diagnostic of OA. BMI weakly diagnosed OA (ROC-AUC 0.57, PR-AUC 0.812) and only symptomatic OA cases. ACTG was the strongest univariable predictor (ROC-AUC 0.705, PR-AUC 0.897). The final model (8 serum peptides) was highly diagnostic (ROC-AUC 0.833, 95% confidence interval [CI] 0.751, 0.905; PR-AUC 0.929, 95% CI 0.876, 0.973) in the testing set and equally diagnostic of non-symptomatic and symptomatic cases (AUCs 0.830-0.835), and not significantly improved with addition of BMI. The STRING database predicted multiple high confidence interactions of the 19 diagnostic OA proteins. No more than 8 serum protein biomarkers were required to discriminate knee OA from non-OA. These biomarkers lend strong support to the involvement and cross-talk of complement and coagulation pathways in the development of OA.

Features of Knee and Multijoint Osteoarthritis by Sex and Race and Ethnicity: A Preliminary Analysis in the Johnston County Health Study.

To evaluate knee osteoarthritis (KOA) and multijoint osteoarthritis (MJOA), and to compare features by sex and race and ethnicity in a population-based cohort. Participants (n = 544) enrolled in the Johnston County Health Study (JoCoHS) as of January 2023 were categorized by radiographic and symptomatic KOA and MJOA phenotypes, and frequencies were compared by sex and race and ethnicity. Symptoms were assessed according to the Knee Injury and Osteoarthritis Outcome Score (KOOS) and pain, aching, and stiffness (PAS) scores at various joints. Models produced estimates (odds ratio [OR] or mean ratios [MR] and 95% CI) adjusted for age, BMI (kg/m2), and education. Men had twice the odds of having MJOA-6 (≥ 3 lower extremity joints affected); there were no significant differences in MJOA phenotypes by race and ethnicity. Women had 50% higher odds of having KOA or having various features of KOA. Women reported significantly worse KOOS Symptoms scores (MR 1.25). Black participants had higher odds of more severe KOA (OR 1.47), subchondral sclerosis (OR 2.06), and medial tibial osteophytes (OR 1.50). Black participants reported worse KOOS Symptoms than White participants (MR 1.18). Although not statistically significant, Hispanic participants (vs non-Hispanic participants) appeared to have lower odds of radiographic changes but reported worse symptoms. Preliminary findings in the diverse JoCoHS cohort suggest more lower extremity- predominant MJOA in men compared to women. Women and Black participants had more KOA features and more severe symptoms. Hispanic participants appear to have higher pain and symptoms scores despite having fewer structural changes. Studies in diverse populations are needed to understand the burden of OA.

Epidemiology of Hip Osteoarthritis: The Johnston County Osteoarthritis Project.

Hip osteoarthritis (OA) is common but understudied compared with knee OA, and insights into the impact of this condition on the general population are needed. This review article summarizes findings from the 30-year, longitudinal, population-based Johnston County Osteoarthritis Project cohort to address the prevalence, incidence, and progression of hip OA and differences by sex and race; similarities and differences related to other joints; and impact on morbidity and mortality.

Cross-Sectional Associations Of Ultrasound Features At The Knee With Sex, Race, Ethnicity, And Radiographic OA: The Johnston County Health Study

Cross-Sectional Associations Of Ultrasound Features At The Knee With Sex, Race, Ethnicity, And Radiographic OA: The Johnston County Health Study

Poor Physical Function Is Associated With Mortality Among Individuals With Knee And/Or Hip OA: The Johnston County Osteoarthritis Project

Poor Physical Function Is Associated With Mortality Among Individuals With Knee And/Or Hip OA: The Johnston County Osteoarthritis Project

An Exploratory Case-Control Study on the Associations of Bacterially-Derived Vitamin K Forms with the Intestinal Microbiome and Obesity-Related Osteoarthritis

BackgroundEvidence suggests that natural metabolites produced by intestinal microorganisms may have beneficial or harmful effects on osteoarthritis (OA). This could include menaquinones, which are bacterially-synthesized, biologically-active vitamin K forms abundant in the intestinal microbiome. ObjectivesThe overall goal of this study was to evaluate the association of intestinally-derived menaquinones with obesity-related OA. MethodsThis case-control study used data and biospecimens derived from a subgroup of Johnston County Osteoarthritis Study participants. Fecal menaquinone concentrations and microbial composition were determined in 52 obese participants with hand and knee OA and 42 age- and sex-matched obese participants without OA. The inter-relationships among fecal menaquinones were evaluated using principal component analysis. The differences in alpha and beta diversities and microbial composition across menaquinone clusters were evaluated using ANOVA. ResultsThe samples were clustered into the following 3 groups: cluster 1 characterized by higher fecal menaquinone-9 and -10 concentrations, cluster 2 characterized by lower overall menaquinone concentrations, and cluster 3 characterized by higher menaquinone-12 and -13 concentrations. Overall, fecal menaquinone clusters did not differ between participants with or without OA (P = 0.707). Microbial diversity did not differ across the fecal menaquinone clusters (all F-test P > 0.12). However, the relative abundance of bacterial taxa differed among clusters, with higher abundance of Coprococcus, Prevotella, and Eggerthella in cluster 2 than in cluster 1; higher abundance of Oscillospira, Dorea, Eubacterium, and Bacteroides in cluster 3 than in cluster 1; and higher abundance of Prevotella, Sutterella, and Dorea in cluster 3 than in cluster 2 (all P < 0.001). ConclusionMenaquinones were variable and abundant in the human gut, but the fecal menaquinone clusters did not differ with OA status. Although the relative abundance of specific bacterial taxa differed among fecal menaquinone clusters, the relevance of these differences with respect to vitamin K status and human health is uncertain.

Biomarkers and longitudinal changes in lumbar spine degeneration and low back pain: the Johnston County Osteoarthritis Project

To determine if baseline biomarkers are associated with longitudinal changes in the worsening of disc space narrowing (DSN), vertebral osteophytes (OST), and low back pain (LBP). Paired baseline (2003-2004) and follow-up (2006-2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for severity of DSN and OST. LBP severity was self-reported. Concentrations of analytes (cytokines, proteoglycans, and neuropeptides) were quantified by immunoassay. Pressure-pain threshold (PPT), a marker of sensitivity to pressure pain, was measured with a standard dolorimeter. Binary logistic regression models were used to estimate odd ratios (OR) and 95% confidence intervals (CI) of biomarker levels with DSN, OST, or LBP. Interactions were tested between biomarker levels and the number of affected lumbar spine levels or LBP. We included participants (n=723) with biospecimens, PPT, and paired lumbar spine radiographic data. Baseline Lumican, a proteoglycan reflective of extracellular matrix changes, was associated with longitudinal changes in DSN worsening (OR=3.19 [95% CI 1.22, 8.01]). Baseline brain-derived neuropathic factor, a neuropeptide, (OR=1.80 [95% CI 1.03, 3.16]) was associated with longitudinal changes in OST worsening, which may reflect osteoclast genesis. Baseline hyaluronic acid (OR=1.31 [95% CI 1.01, 1.71]), indicative of systemic inflammation, and PPT (OR=1.56 [95% CI 1.02, 2.31]) were associated with longitudinal increases in LBP severity. These findings suggest that baseline biomarkers are associated with longitudinal changes occurring in structures of the lumbar spine (DSN vs OST). Markers of inflammation and perceived pressure pain sensitivity were associated with longitudinal worsening of LBP.

Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project.

The lack of accurate biomarkers to predict knee osteoarthritis (OA) progression is a key unmet need in OA clinical research. The objective of this study was to develop baseline peripheral blood epigenetic biomarker models to predict knee OA progression. Genome-wide buffy coat DNA methylation patterns from 554 individuals from the Osteoarthritis Biomarkers Consortium (OABC) were determined using Illumina Infinium MethylationEPIC 850K arrays. Data were divided into model development and validation sets, and machine learning models were trained to classify future OA progression by knee pain, radiographic imaging, knee pain plus radiographic imaging, and any progression (pain, radiographic, or both). Parsimonious models using the top 13 CpG sites most frequently selected during development were tested on independent samples from participants in the Johnston County Osteoarthritis (JoCo OA) Project (n=128) and a previously published Osteoarthritis Initiative (OAI) data set (n=55). Full models accurately classified future radiographic-only progression (mean ± SEM accuracy 87 ± 0.8%, area under the curve [AUC] 0.94 ± 0.004), pain-only progression (accuracy 89 ± 0.9%, AUC 0.97 ± 0.004), pain plus radiographic progression (accuracy 72 ± 0.7%, AUC 0.79 ± 0.006), and any progression (accuracy 78 ± 0.4%, AUC 0.86 ± 0.004). Pain-only and radiographic-only progressors were not distinguishable (mean ± SEM accuracy 58 ± 1%, AUC 0.62 ± 0.001). Parsimonious models showed similar performance and accurately classified future radiographic progressors in the OABC cohort and in both validation cohorts (mean ± SEM accuracy 80 ± 0.3%, AUC 0.88 ± 0.003 [using JoCo OA Project data], accuracy 80 ± 0.8%, AUC 0.89 ± 0.002 [using previous OAI data]). Our data suggest that pain and structural progression share similar early systemic immune epigenotypes. Further studies should focus on evaluating the pathophysiologic consequences of differential DNA methylation and peripheral blood cell epigenotypes in individuals with knee OA.

Associations Between Baseline and Longitudinal Semiautomated Quantitative Joint Space Width at the Hip and Incident Hip Osteoarthritis: Data From a Community-Based Cohort.

To evaluate quantitative joint space width (JSW) at 10-, 30-, and 50-degree locations in relation to incident radiographic and symptomatic hip osteoarthritis (HOA) in a community-based cohort. Data were from Johnston County OA Project participants with supine hip radiographs at each of 4 time points; all had Kellgren/Lawrence (K/L) grades and quantitative JSW. We assessed covariates (age, race, height, weight, body mass index [BMI]) associated with quantitative JSW and hip-level associations between quantitative JSW and HOA over time using sex-stratified and multivariable-adjusted linear mixed models. A cluster analysis with logistic regression estimated associations between quantitative JSW trajectory groups and incident radiographic HOA and symptomatic HOA. At baseline, 397 participants (784 hips, 41% men, 24% Black, mean age 57 years) had a mean BMI of 29 kg/m2 . Over a mean of 18 years, 20% and 12% developed incident K/L grade-defined radiographic HOA or symptomatic HOA, respectively. Quantitative JSW was more sensitive to changes over time at 50 degrees. Values were stable among men but declined over time in women. Heavier women lost more quantitative JSW; changes in quantitative JSW were not significantly associated with race, education, or injury in women or men. In women only, loss of quantitative JSW over time was associated with 2-3 times higher odds of radiographic HOA and symptomatic HOA; among women and men, narrower baseline quantitative JSW was associated with these outcomes. Hip quantitative JSW demonstrates marked differences in respect to sex, with significant loss over time only in women. Loss of quantitative JSW over time in women and narrower baseline quantitative JSW in men and women were associated with incident radiographic HOA and symptomatic HOA.

Association of Biomarkers with Individual and Multiple Body Sites of Pain: The Johnston County Osteoarthritis Project.

IntroductionBiochemical biomarkers may provide insight into musculoskeletal pain reported at individual or multiple body sites. The purpose of this study was to determine if biomarkers or pressure-pain threshold (PPT) were associated with individual or multiple sites of pain.MethodsThis cross-sectional analysis included 689 community-based participants. Self-reported symptoms (ie, pain, aching, or stiffness) were ascertained about the neck, upper back/thoracic, low back, shoulders, elbows, wrist, hands, hips, knees, ankles, and feet. Measured analytes included CXCL-6, RANTES, HA, IL-6, BDNF, OPG and NPY. A standard dolorimeter measured PPT. Logistic regression was used determine the association between biomarkers and PPT with individual and summed sites of pain.ResultsIncreased IL-6 and HA were associated with knee pain (OR=1.30, 95% CI 1.03, 1.64) and (OR=1.32, 95% CI 1.01, 1.73) respectively; HA was also associated with elbow/wrist/hand pain (OR=1.60, 95% CI 1.22, 2.09). Those with increased NPY levels were less likely to have shoulder pain (OR=0.56, 95% CI 0.33, 0.93). Biomarkers HA (OR=1.50, 95% CI 1.07, 2.10), OPG (OR=1.74, 95% CI 1.00, 3.03), CXCL-6 (OR=1.75, 95% CI 1.02, 3.01) and decreased PPT (OR=3.97, 95% CI 2.22, 7.12) were associated with multiple compared to no sites of pain. Biomarker HA (OR=1.57, 95% CI 1.06, 2.32) and decreased PPT (OR=3.53, 95% CI 1.81, 6.88) were associated with multiple compared to a single site of pain.ConclusionBiomarkers of inflammation (HA, OPG, IL-6 and CXCL-6), pain (NPY) and PPT may help to understand the etiology of single and multiple pain sites.

Predictors of Lumbar Spine Degeneration and Low Back Pain in the Community: The Johnston County Osteoarthritis Project.

To determine the incidence and worsening of lumbar spine structure and low back pain (LBP) and whether they are predicted by demographic characteristics or clinical characteristics or appendicular joint osteoarthritis (OA). Paired baseline (2003-2004) and follow-up (2006-2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for osteophytes (OST), disc space narrowing (DSN), spondylolisthesis, and presence of facet joint OA (FOA). Spine OA was defined as at least mild OST and mild DSN at the same level for any level of the lumbar spine. LBP, comorbidities, and back injury were self-reported. Weibull models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of spine phenotypes accounting for potential predictors including demographic characteristics, clinical characteristics, comorbidities, obesity, and appendicular OA. Obesity was a consistent and strong predictor of incidence of DSN (HR 1.80 [95% CI 1.09-2.98]), spine OA (HR 1.56 [95% CI 1.01-2.41]), FOA (HR 4.99 [95% CI 1.46-17.10]), spondylolisthesis (HR 1.87 [95% CI 1.02-3.43]), and LBP (HR 1.75 [95% CI 1.19-2.56]), and worsening of DSN (HR 1.51 [95% CI 1.09-2.09]) and LBP (HR 1.51 [95% CI 1.12-2.06]). Knee OA was a predictor of incident FOA (HR 4.18 [95% CI 1.44-12.2]). Spine OA (HR 1.80 [95% CI 1.24-2.63]) and OST (HR 1.85 [95% CI 1.02-3.36]) were predictors of incidence of LBP. Hip OA (HR 1.39 [95% CI 1.04-1.85]) and OST (HR 1.58 [95% CI 1.00-2.49]) were predictors of LBP worsening. Among the multiple predictors of spine phenotypes, obesity was a common predictor for both incidence and worsening of lumbar spine degeneration and LBP.

Particulate Matter and Ammonia Pollution in the Animal Agricultural-Producing Regions of North Carolina: Integrated Ground-Based Measurements and Satellite Analysis

Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM2.5 chemical composition analysis suggests that ammonium is a major component of the PM2.5 aerosol.

Biomarker clusters differentiate phenotypes of lumbar spine degeneration and low back pain: The Johnston County Osteoarthritis Project

ObjectiveDescribe the association between biomarkers and lumbar spine degeneration (vertebral osteophytes [OST], facet joint osteoarthritis [FOA], and disc space narrowing [DSN]), for persons with and without low back pain (LBP) and determine whether clusters based on biomarkers differentiate lumbar spine structure with and without LBP. MethodsUsing data from the Johnston County Osteoarthritis Project (2006–2010), we measured serum N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, HA, IL-6, BDNF, OPG, and NPY, and urinary CTX-II. Biomarkers were used to group participants using k-means cluster analysis. Logistic regression models were used to compare biomarker clusters. ResultsThe sample consisted of 731 participants with biospecimens and lumbar spine radiographic data. Three biomarker subgroups were identified: one characterized by structural degenerative changes; another characterized by structural degenerative changes and inflammation, with pain; and a referent cluster with lower levels of biomarkers, pain, and structural degenerative changes. Compared to the referent subgroup, the structural change subgroup was associated with DSN (OR ​= ​1.94, 95% CI 1.30–2.90) and FOA (OR ​= ​1.72, 95% CI 1.12–2.62), and the subgroup with structural degenerative change, inflammation, and pain was associated with OST with LBP (OR ​= ​1.60, 95% CI 1.04–2.46), FOA with LBP (OR ​= ​1.59, 95% CI 1.04–2.45), and LBP (OR ​= ​1.63, 95% CI 1.11–2.41). The subgroup with structural degenerative changes was more likely to have OST (OR ​= ​1.82, 95% CI 1.06–3.13) and less likely to have FOA with LBP (OR ​= ​0.62, 95% CI 0.40–0.96) compared to the group with inflammation and pain. ConclusionClustering by biomarkers may assist in differentiating patients for specific clinical interventions aimed at decreasing LBP.

PERIPHERAL BLOOD DNA METHYLATION-BASED MACHINE LEARNING MODELS ARE PREDICTIVE OF FUTURE KNEE OA PROGRESSION: BIOSPECIMENS AND DATA FROM THE OSTEOARTHRITIS INITIATIVE AND JOHNSTON COUNTY OSTEOARTHRITIS PROJECT

Purpose: Knee osteoarthritis (OA) is a heterogeneous disease characterized by a variety of clinical and molecular phenotypes, for which there exist no widely-available biomarkers. We have previously published a pilot analysis of baseline peripheral blood cell DNA methylation patterns from a small group of patients from the Osteoarthritis Initiative (OAI), demonstrating that methylation-based models could distinguish future radiographic progressors from nonprogressors. In the current study, we apply this method to the FNIH OsteoArthritis Biomarkers Consortium (OABC) subcohort of the OAI that included pain-, radiographic-, and dual- (both pain and radiographic) progressors compared to nonprogressors and to similarly constructed groups in the Johnston County Osteoarthritis Project (JoCoOA) and an independent OAI cohort from our prior work.