Objective: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progression phenotypes that are potentially more responsive to interventions. Design: We used publicly available data from the Foundation for the National Institutes of Health (FNIH) osteoarthritis (OA) Biomarkers Consortium, where radiographic (medial joint space narrowing of 0.7 mm), and pain progression (increase of 9 Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] points) were defined at 48 months, as four mutually exclusive outcome groups (none, both, pain only, radiographic only), along with an extensive set of covariates. We applied distance weighted discrimination (DWD), direction-projection-permutation (DiProPerm) testing, and clustering methods to focus on the contrast (z-scores) between those progressing by both criteria ("progressors") and those progressing by neither ("non-progressors"). Results: Using all observations (597 individuals, 59% women, mean age 62 years and BMI 31 kg/m 2) and all 73 baseline variables available in the dataset, there was a clear separation among progressors and non-progressors (z ¼ 10.1). Higher z-scores were seen for the magnetic resonance imaging (MRI)-based variables than for demographic/clinical variables or biochemical markers. Baseline variables with the greatest contribution to non-progression at 48 months included WOMAC pain, lateral meniscal extrusion, and serum N-terminal pro-peptide of collagen IIA (PIIANP), while those contributing to progression included bone marrow lesions, osteophytes, medial meniscal extrusion, and urine C-terminal crosslinked telopeptide type II collagen (CTX-II). Conclusions: Using methods that provide a way to assess numerous variables of different types and scalings simultaneously in relation to an outcome of interest enabled a data-driven approach that identified key variables associated with a progression phenotype.

These results suggest factors related to the gut microbiota promote the development of OA after joint injury.

Purpose: Quadriceps muscle weakness is associated with knee joint pain and may be an important yet modifiable risk factor for radiographic knee osteoarthritis (OA). The purpose of this study was to evaluate the association between quadriceps strength to incident radiographic knee OA. Methods: The study sample included 389 participants from the Michigan Bone Health and Metabolism Study (MBHMS) that were free of radiographic knee OA at the 2002 study visit. Participants underwent annual quadriceps testing from 2001-2007 using a portable isometric strength chair and were radiographed in 2007 to determine incident knee OA status. Linear mixed models were used to determine whether level or rate of change in quadriceps strength differed among women with and without incident radiographic knee OA. Models were adjusted for age, body mass index (BMI), knee joint pain, and menopause status. Results: At the 2002 follow-up visit, the average age of participants was 46.5 years and the average BMI was 28.2 kg/m 2. Of the 389 women without radiographic knee OA in 2002, 29 women developed knee OA by 2007 (5-year incidence of 7.5%). Women with incident radiographic knee OA had slightly higher quadriceps strength levels in in midadulthood but this difference was not statistically significant (p ¼ 0.10). While quadriceps strength levels decreased with age in women with and without incident radiographic OA, there was a more rapid rate of strength decline among women with incident OA as compared to women who remained OA-free (p ¼ 0.03). Conclusions: Women with incident radiographic knee OA had more rapid declines in quadriceps strength through the mid-life. Maintenance of quadriceps muscle strength through resistance training may be an appropriate intervention to prevent the onset of knee OA and forestall associated functional limitations and disability.

BackgroundLow back pain (LBP) and osteoarthritis (OA) of the lumbar spine are common causes of disability. The contribution of joint hypermobility (range of motion greater than normal at most joints) to LBP and lumbar spine OA is not well known.ObjectivesThis cross-sectional study examined the relationship of joint hypermobility with LBP and lumbar spine OA in a large cohort in the United States.MethodsOf the 2146 participants with Beighton (hypermobility) data collected from 2003 to 2010, 1864 had complete LBP and lumbar spine radiographic data available for analyses. For the Beighton criteria, one point was given for each completed maneuver: passive dorsiflexion right/left fifth finger 90+ degrees, passive apposition right/left thumbs to forearm, right/left elbow hyperextension 10+ degrees, right/left knee hyperextension 10+ degrees, and palms on floor during forward trunk flexion with knees extended. The total score ranged from 0 (unable) to 9 (performed all maneuvers). A Beighton score ≥4 was defined as hypermobility. Presence of LBP was based on pain, aching or stiffness of the low back on most days. Each lumbar spine radiographic level was graded for disc space narrowing (DSN) and osteophytes (OST) in a semi-quantitative fashion (0–3) according to the Burnett Atlas. Radiographic lumbar spine OA (rOA) was defined as the presence of DSN and OST grade 1+ at the same lumbar level. Symptomatic lumbar spine OA (sxOA) was defined as presence of rOA with LBP. Associations of LBP and lumbar spine OA with hypermobility (Beighton ≥4) and each individual Beighton maneuver were estimated using separate logistic regression models, controlling for gender, race, age, body mass index (BMI), and history of low back injury. Interactions were examined between hypermobility and each covariate (p<0.10 considered statistically significant).ResultsParticipant characteristics were: mean age 66 years (standard deviation [SD]±10), mean BMI 31 (SD±7) kg/m2, 65% women, 33% African American, 2% low back injury, 6% hypermobility, 40% LBP, 59% rOA, and 25% sxOA. Adjusted results are summarized in the Table. Although not statistically significant, the adjusted odds of rOA were 18% lower among participants with vs. without hypermobility, while the odds of LBP and sxOA were 30% and 20% higher, respectively. Fifth finger dorsiflexion was inversely associated with LBP (35% lower odds) and sxOA (21% lower odds). The elbow maneuver was positively associated with LBP (41% higher odds), but inversely associated with rOA (28%); a similar, but not statistically significant, pattern was seen for the knee maneuver. The trunk flexion maneuver was inversely associated with LBP, rOA, and sxOA. No interactions of hypermobility and covariates were noted.ConclusionsJoint hypermobility (specifically elbow and knee maneuvers) appears to be positively associated with LBP but inversely related to lumbar spine rOA. The trunk maneuver may reflect the musculotendinous (hamstring) flexibility more than ligamentous laxity, suggesting that greater hamstring flexibilit...

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