A staged approach using machine learning and uncertainty quantification to predict the risk of hip fracture.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. The study cohort included 547 patients, with 94 experiencing hip fracture. To assess the risk of hip fracture, clinical variables and clinical variables combined with hip DXA imaging features were evaluated as predictors, followed by a novel staged approach. Hip DXA imaging features included those extracted by convolutional neural networks (CNNs), shape measurements, and texture features. Two ensemble machine learning models were evaluated: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and imaging features) using the logistic regression as the base classifier and bootstrapping for ensemble learning. The staged approach was developed using uncertainty quantification from Ensemble 1 which was used to decide if hip DXA imaging features were necessary to improve prediction for each subject. Ensemble 2 exhibited the highest performance, achieving an Area Under the Curve (AUC) of 0.95, an accuracy of 0.92, a sensitivity of 0.81, and a specificity of 0.94. The staged model also performed well, with an AUC of 0.85, an accuracy of 0.86, a sensitivity of 0.56, and a specificity of 0.92, outperforming Ensemble 1, which had an AUC of 0.55, an accuracy of 0.73, a sensitivity of 0.20, and a specificity of 0.83. Furthermore, the staged model suggested that 54.49 % of patients did not require DXA scanning, effectively balancing accuracy and specificity, while offering a robust solution when DXA data acquisition is not feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of advanced modeling strategies. Our staged approach offers a cost-effective holistic view of patient health. It can identify individuals at risk of hip fracture with a high accuracy while reducing unnecessary DXA scans. This approach has great promise to guide the need for interventions to prevent hip fracture while reducing diagnostic cost and exposure to radiation.

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convolutional neural network. Maximal fracture scores resulted in a performant model for subject-level fracture prediction. Combining individual deep learning vertebral body fracture scores and demographic covariates for subject-level classification of osteoporotic fracture achieved excellent performance (AUC-ROC of 0.968) on a large dataset of radiographs with basic demographic data. PURPOSE: Osteoporotic vertebral fractures are common and morbid. Automated opportunistic screening for incidental vertebral fractures from radiographs, the highest volume imaging modality, could improve osteoporosis detection and management. We consider how to form patient-level fracture predictions and summarization to guide management, using our previously developed vertebral fracture classifier on segmented radiographs from a prospective cohort study of US men (MrOS). We compare the performance of logistic regression (LR) and generalized additive models (GAM) with combinations of individual vertebral scores and basic demographic covariates. METHODS: Subject-level LR and GAM models were created retrospectively using all fracture predictions or summary variables such as order statistics, adjacent vertebral interactions, and demographic covariates (age, race/ethnicity). The classifier outputs for 8663 vertebrae from 1176 thoracic and lumbar radiographs in 669 subjects were divided by subject to perform stratified fivefold cross-validation. Models were assessed using multiple metrics, including receiver operating characteristic (ROC) and precision-recall (PR) curves. RESULTS: The best model (AUC-ROC = 0.968) was a GAM using the top three maximum vertebral fracture scores and age. Using top-ranked scores only, rather than all vertebral scores, improved performance for both model classes. Adding age, but not ethnicity, to the GAMs improved performance slightly. CONCLUSION: Maximal vertebral fracture scores resulted in the highest-performing models. While combining multiple vertebral body predictions risks decreasing specificity, our results demonstrate that subject-level models maintain good predictive performance. Thresholding strategies can be used to control sensitivity and specificity as clinically appropriate.

Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs.

BACKGROUND AND PURPOSE: Vertebral compression fractures may indicate osteoporosis but are underdiagnosed and underreported by radiologists. We have developed an ensemble of vertebral body (VB) segmentation models for lateral radiographs as a critical component of an automated, opportunistic screening tool. Our goal is to detect the approximate location of thoracic and lumbar VBs, including fractured vertebra, on lateral radiographs. MATERIALS AND METHODS: The Osteoporotic Fractures in Men Study (MrOS) data set includes spine radiographs of 5994 men aged ≥65 years from 6 clinical centers. Two segmentation models, U-Net and Mask-RCNN (Region-based Convolutional Neural Network), were independently trained on the MrOS data set retrospectively, and an ensemble was created by combining them. Primary performance metrics for VB detection success included precision, recall, and F1 score for object detection on a held-out test set. Intersection over union (IoU) and Dice coefficient were also calculated as secondary metrics of performance for the test set. A separate external data set from a quaternary health care enterprise was acquired to test generalizability, comprising diagnostic clinical radiographs from men and women aged ≥65 years. RESULTS: The trained models achieved F1 score of U-Net = 83.42%, Mask-RCNN = 86.30%, and ensemble = 88.34% in detecting all VBs, and F1 score of U-Net = 87.88%, Mask-RCNN = 92.31%, and ensemble = 97.14% in detecting severely fractured vertebrae. The trained models achieved an average IoU per VB of 0.759 for U-Net and 0.709 for Mask-RCNN. The trained models achieved F1 score of U-Net = 81.11%, Mask-RCNN = 79.24%, and ensemble = 87.72% in detecting all VBs in the external data set. CONCLUSIONS: An ensemble model combining predictions from U-Net and Mask-RCNN resulted in the best performance in detecting VBs on lateral radiographs and generalized well to an external data set. This model could be a key component of a pipeline to detect fractures on all vertebrae in a radiograph in an automated, opportunistic screening tool under development.

Chemokine CXCL9, a marker of inflammaging, is associated with changes of muscle strength and mortality in older men.

Our study examined associations of the CXC motif chemokine ligand 9 (CXCL9), a pro-inflammatory protein implicated in age-related inflammation, with musculoskeletal function in elderly men. We found in certain outcomes both cross-sectional and longitudinal significant associations of CXCL9 with poorer musculoskeletal function and increased mortality in older men. This requires further investigation. PURPOSE: We aim to determine the relationship of (CXCL9), a pro-inflammatory protein implicated in age-related inflammation, with both cross-sectional and longitudinal musculoskeletal outcomes and mortality in older men. METHODS: A random sample from the Osteoporotic Fractures in Men (MrOS) Study cohort (N = 300) was chosen for study subjects that had attended the third and fourth clinic visits, and data was available for major musculoskeletal outcomes (6 m walking speed, chair stands), hip bone mineral density (BMD), major osteoporotic fracture, mortality, and serum inflammatory markers. Serum levels of CXCL9 were measured by ELISA, and the associations with musculoskeletal outcomes were assessed by linear regression and fractures and mortality with Cox proportional hazards models. RESULTS: The mean CXCL9 level of study participants (79.1 ± 5.3 years) was 196.9 ± 135.2 pg/ml. There were significant differences for 6 m walking speed, chair stands, physical activity scores, and history of falls in the past year across the quartiles of CXCL9. However, higher CXCL9 was only significantly associated with changes in chair stands (ß = - 1.098, p < 0.001) even after adjustment for multiple covariates. No significant associations were observed between CXCL9 and major osteoporotic fracture or hip BMD changes. The risk of mortality increased with increasing CXCL9 (hazard ratio quartile (Q)4 vs Q1 1.98, 95% confidence interval 1.25-3.14; p for trend < 0.001). CONCLUSIONS: Greater serum levels of CXCL9 were significantly associated with a decline in chair stands and increased mortality. Additional studies with a larger sample size are needed to confirm our findings.

Skeletal Muscle Composition, Power, and Mitochondrial Energetics in Older Men and Women With Knee Osteoarthritis.

OBJECTIVE: Our objective was to investigate the overall and sex-specific relationships between the presence and severity of knee osteoarthritis (KOA) and muscle composition, power, and energetics in older adults. METHODS: Male and female patients (n = 655, mean ± SD age 76.1 ± 4.9 years; 57% female) enrolled in the Study of Muscle, Mobility, and Aging completed standing knee radiographs and knee pain assessments. Participants were divided into three groups using Kellgren-Lawrence grade (KLG) of KOA severity (0-1, 2, or 3-4). Outcome measures included whole-body muscle mass, thigh fat-free muscle (FFM) volume and muscle fat infiltration (MFI), leg power, specific power (power normalized to muscle volume), and muscle mitochondrial energetics. RESULTS: Overall, the presence and severity of KOA is associated with greater MFI, lower leg power and specific power, and reduced oxidative phosphorylation (P trend < 0.036). Sex-specific analysis revealed reduced energetics only in female patients with KOA (P trend < 0.007) compared to female patients without KOA. In models adjusted for age, sex, race, nonsteroidal anti-inflammatory drug administration, site or technician, physical activity, height, and participants with abdominal adiposity with KLG 3 to 4 had greater MFI (mean 0.008%, 95% confidence interval [CI] 0.004%-0.011%) and lower leg power (mean -51.56 W, 95% CI -74.03 to -29.10 W) and specific power (mean -5.38 W/L, 95% CI -7.31 to -3.45 W/L) than those with KLG 0 to 1. No interactions were found between pain and KLG status. Among those with KOA, MFI and oxidative phosphorylation were associated with thigh FFM volume, leg power, and specific power. CONCLUSION: Muscle health is associated with the presence and severity of KOA and differs by sex. Although muscle composition and power are lower in both male and female patients with KOA, regardless of pain status, mitochondrial energetics is reduced only in female patients.

A maternal brain hormone that builds bone.

In lactating mothers, the high calcium (Ca2+) demand for milk production triggers significant bone loss1. Although oestrogen normally counteracts excessive bone resorption by promoting bone formation, this sex steroid drops precipitously during this postpartum period. Here we report that brain-derived cellular communication network factor 3 (CCN3) secreted from KISS1 neurons of the arcuate nucleus (ARCKISS1) fills this void and functions as a potent osteoanabolic factor to build bone in lactating females. We began by showing that our previously reported female-specific, dense bone phenotype2 originates from a humoral factor that promotes bone mass and acts on skeletal stem cells to increase their frequency and osteochondrogenic potential. This circulatory factor was then identified as CCN3, a brain-derived hormone from ARCKISS1 neurons that is able to stimulate mouse and human skeletal stem cell activity, increase bone remodelling and accelerate fracture repair in young and old mice of both sexes. The role of CCN3 in normal female physiology was revealed after detecting a burst of CCN3 expression in ARCKISS1 neurons coincident with lactation. After reducing CCN3 in ARCKISS1 neurons, lactating mothers lost bone and failed to sustain their progeny when challenged with a low-calcium diet. Our findings establish CCN3 as a potentially new therapeutic osteoanabolic hormone for both sexes and define a new maternal brain hormone for ensuring species survival in mammals.

Infrapatellar fat pad size and subcutaneous fat in knee osteoarthritis radiographic progression: data from the osteoarthritis initiative.

OBJECTIVES: Adipose tissue has been associated with knee osteoarthritis (KOA) pathogenesis, but the longitudinal changes in adipose tissue with KOA progression have not been carefully evaluated. This study aimed to determine if longitudinal changes of systemic and local adipose tissue is associated with radiographic progression of KOA. METHODS: This case-control study used data from the Osteoarthritis Initiative (OAI) and included 315 cases (all the right knees with a minimum of Kellgren-Lawrence score (KL) of 0 and an increase of ≥ 1 KL from baseline to 48 months) and 315 controls matched by age, sex, race, and baseline KL. Cross sectional area of IPFP (IPFP CSA) and subcutaneous adipose tissue around the distal thigh (SCATthigh) were measured using MRI images at baseline and 24 months. Conditional logistic regression models were fitted to estimate associations of obesity markers, IPFP CSA, and SCATthigh with radiographic KOA progression. Mediation analysis was used to assess whether IPFP CSA or SCATthigh mediates the relationships between baseline BMI and radiographic KOA progression. RESULTS: 24-month changes of IPFP CSA (ΔIPFP CSA) and SCATthigh (ΔSCATthigh) were significantly greater in cases compared to controls, whereas Δ BMI and Δ abdominal circumference were similar in both groups during follow-up. Adjusted ORs for radiographic KOA progression were 9.299, 95% CI (5.357-16.141) per 1 SD increase of Δ IPFP CSA and 1.646, 95% CI (1.288-2.103) per 1 SD increase of Δ SCATthigh. ΔIPFP CSA mediated the association between baseline BMI and radiographic KOA progression (87%). CONCLUSIONS: Subjects with radiographic progression of KOA, had significant increases in IPFP CSA and subcutaneous adipose tissue while BMI and abdominal circumference remained stable. Additional studies are needed to confirm these associations.

Hip Fracture Risk Assessment Tools for Adults Aged 80 Years and Older.

Importance: While adults aged 80 years and older account for 70% of hip fractures in the US, performance of fracture risk assessment tools in this population is uncertain. Objective: To compare performance of the Fracture Risk Assessment Tool (FRAX), Garvan Fracture Risk Calculator, and femoral neck bone mineral density (FNBMD) alone in 5-year hip fracture prediction. Design, Setting and Participants: Prognostic analysis of 3 prospective cohort studies including participants attending an index examination (1997 to 2016) at age 80 years or older. Data were analyzed from March 2023 to April 2024. Main Outcomes and Measures: Participants contacted every 4 or 6 months after index examination to ascertain incident hip fractures and vital status. Predicted 5-year hip fracture probabilities calculated using FRAX and Garvan models incorporating FNBMD and FNBMD alone. Model discrimination assessed by area under receiver operating characteristic curve (AUC). Model calibration assessed by comparing observed vs predicted hip fracture probabilities within predicted risk quintiles. Results: A total of 8890 participants were included, with a mean (SD) age at index examination of 82.6 (2.7) years; 4906 participants (55.2%) were women, 866 (9.7%) were Black, 7836 (88.1%) were White, and 188 (2.1%) were other races and ethnicities. During 5-year follow-up, 321 women (6.5%) and 123 men (3.1%) experienced a hip fracture; 818 women (16.7%) and 921 men (23.1%) died before hip fracture. Among women, AUC was 0.69 (95% CI, 0.67-0.72) for FRAX, 0.69 (95% CI, 0.66-0.72) for Garvan, and 0.72 (95% CI, 0.69-0.75) for FNBMD alone (FNBMD superior to FRAX, P = .01; and Garvan, P = .01). Among men, AUC was 0.71 (95% CI, 0.66-0.75) for FRAX, 0.76 (95% CI, 0.72-0.81) for Garvan, and 0.77 (95% CI, 0.72-0.81) for FNBMD alone (P < .001 Garvan and FNBMD alone superior to FRAX). Among both sexes, Garvan greatly overestimated hip fracture risk among individuals in upper quintiles of predicted risk, while FRAX modestly underestimated risk among those in intermediate quintiles of predicted risk. Conclusions and Relevance: In this prognostic study of adults aged 80 years and older, FRAX and Garvan tools incorporating FNBMD compared with FNBMD alone did not improve 5-year hip fracture discrimination. FRAX modestly underpredicted observed hip fracture probability in intermediate-risk individuals. Garvan markedly overpredicted observed hip fracture probability in high-risk individuals. Until better prediction tools are available, clinicians should prioritize consideration of hip BMD, life expectancy, and patient preferences in decision-making regarding drug treatment initiation for hip fracture prevention in late-life adults.

Associations of empirically derived dietary patterns and cognitive performance in older men: Results of the Osteoporotic Fractures in Men (MrOS) study.

OBJECTIVE: The aim of this study was to examine associations between empirically derived dietary pattern scores and cognition, as well as risk of cognitive decline, over an average of 4.6 (± 0.3) years in older men. MATERIALS AND METHODS: This analysis was conducted as part of the Osteoporotic Fractures in Men (MrOS) prospective cohort study. Diet was assessed at Visit 1 (3/2000-4/2002) by food frequency questionnaire, and dietary patterns (Western and Prudent) were derived by factor analysis. The analytic cohort comprised 4231 community-dwelling American men who were aged 65 years or more. Cognitive function was assessed with the Modified Mini-Mental State exam (3MS) and the Trails B test at Visit 1 and at Visit 2 (3/2005-5/2006). Associations between dietary pattern score and cognition and risk of cognitive decline were estimated using mixed effects regression models. Model 1 was adjusted for age, clinic site and total energy intake (TEI). Model 2 was further adjusted for calcium and vitamin D supplement use, body mass index (BMI), physical activity, smoking, diabetes and hypertension (Western diet group) and education, calcium and vitamin D supplement use, depression, BMI, physical activity, smoking and stroke (Prudent diet group). RESULTS: Adherence to the Western dietary pattern was associated with higher 3MS scores and shorter Trails B test time at Visit 1 in Model 2. Adherence to the Prudent dietary pattern was associated with higher 3MS scores in Model 1 but not Model 2. There were no independent associations between dietary pattern scores and risk of cognitive decline 4.6 (± 0.3) years later at Visit 2. CONCLUSION: The results do not support a robust protective effect of the Prudent dietary pattern on cognition in the MrOS cohort. Associations between the Western dietary pattern and better cognitive scores should be interpreted with caution. Further research is needed to understand the complex interactions between dietary patterns and cognition in older men.

Clinical and imaging findings associated with preservation of knee joint health over 8 years in individuals aged 65 and over: data from the OAI.

OBJECTIVE: While risk factors for osteoarthritis (OA) are well known, it is not well understood why certain individuals maintain high mobility and joint health throughout their life while others demonstrate OA at older ages. The purpose of this study was to assess which demographic, clinical and MRI quantitative and semi-quantitative factors are associated with preserving healthy knees in older individuals. METHODS: This study analyzed data from the OA Initiative (OAI) cohort of individuals at the age of 65 years or above. Participants without OA at baseline (BL) (Kellgren-Lawrence (KL) ≤ 1) were followed and classified as incident cases (KL ≥ 2 during follow-up; n = 115) and as non-incident (KL ≤ 1 over 96-month; n = 391). Associations between the predictor-variables sex, age, BMI, race, clinical scoring systems, T2 relaxation times and Whole-Organ Magnetic Resonance Imaging-Score (WORMS) readings at BL and the preservation of healthy knees (KL ≤ 1) during a 96-month follow-up period were assessed using logistic regression models. RESULTS: Obesity and presence of pain showed a significant inverse association with maintaining radiographically normal joints in patients aged 65 and above. T2 relaxation times of the lateral femur and tibia as well as the medial femur were also significantly associated with maintaining radiographically normal knee joints. Additionally, absence of lesions of the lateral meniscus and absence of cartilage lesions in the medial and patellofemoral compartments were significantly associated with maintaining healthy knee joints. CONCLUSION: Overall, this study provides protective clinical parameters as well as quantitative and semi-quantitative MR-imaging parameters associated with maintaining radiographically normal knee joints in an older population over 8 years.

A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. We propose a novel staged model that combines advanced imaging and clinical data to improve predictive performance. By using convolutional neural networks (CNNs) to extract features from hip DXA images, along with clinical variables, shape measurements, and texture features, our method provides a comprehensive framework for assessing fracture risk. The study cohort included 547 patients, with 94 experiencing hip fracture. A staged machine learning-based model was developed using two ensemble models: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and DXA imaging features). This staged approach used uncertainty quantification from Ensemble 1 to decide if DXA features are necessary for further prediction. Ensemble 2 exhibited the highest performance, achieving an Area Under the Curve (AUC) of 0.9541, an accuracy of 0.9195, a sensitivity of 0.8078, and a specificity of 0.9427. The staged model also performed well, with an AUC of 0.8486, an accuracy of 0.8611, a sensitivity of 0.5578, and a specificity of 0.9249, outperforming Ensemble 1, which had an AUC of 0.5549, an accuracy of 0.7239, a sensitivity of 0.1956, and a specificity of 0.8343. Furthermore, the staged model suggested that 54.49% of patients did not require DXA scanning. It effectively balanced accuracy and specificity, offering a robust solution when DXA data acquisition is not always feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of the advanced modeling strategies. Our staged approach offers a cost-effective holistic view of patients' health. It could identify individuals at risk with a high accuracy but reduce the unnecessary DXA scanning. Our approach has great promise to guide interventions to prevent hip fractures with reduced cost and radiation.

Mechanical and structural properties of articular cartilage and subchondral bone in human osteoarthritic knees.

Knee osteoarthritis (OA), characterized by multiple joint tissue degenerations, remains a significant clinical challenge. Recent evidence suggests that crosstalk within the osteochondral unit may drive OA progression. Although structural-biomechanical properties of bone and cartilage have been studied, potential interaction within the osteochondral unit in the context of OA has yet to be investigated. We performed comprehensive structural and biomechanical quantification of the cartilage, subchondral bone plate (SBP), and subchondral trabecular bone (STB) using 101 osteochondral cores collected from tibial plateaus of 12 control human cadavers (CT, 5 male/7 female) and 19 patients undergoing total knee replacement (OA, 6 male/13 female). For each sample, we quantified SBP microstructure, plate-and-rod morphological properties of the STB using individual trabecula segmentation, and morphological and compositional properties of the articular cartilage. We also performed indentation testing on each compartment of the osteochondral unit to extract the respective structural-mechanical properties. Cartilage thickness was lower in moderate and severe OA regions, while Osteoarthritis Research Society International score was higher only in severe OA regions. GAG content did not change in any OA region. Aggregate and shear moduli were lower only in severe OA regions, while permeability was lower only in moderate OA regions. In the SBP, thickness and tissue mineral density were higher in moderate and severe OA regions. Tissue modulus of STB was lower in moderate OA regions despite a thicker and more mineralized SBP; this deterioration was not observed in severe OA regions. Regression analysis revealed strong correlations between cartilage and STB properties in CT; these correlations were also found in moderate OA regions but were not observed in severe OA regions. In summary, our findings comprehensively characterize the human OA osteochondral unit. Importantly, uncoupling cartilage and subchondral bone structural-mechanical properties may be a hallmark of OA.

Knee osteoarthritis (OA) is a complex condition involving the degradation of joint tissues. To better understand OA progression, we investigated the interplay between different components of the joint. Our study focused on how cartilage, subchondral bone plate (SBP), and subchondral trabecular bone (STB) interact in human knee OA samples. We observed distinct changes in these tissues in moderate and severe OA regions compared with healthy joints. In moderate to severe OA, we found that cartilage thickness decreased, while the SBP thickened. Interestingly, the strength of the STB decreased only in moderate OA regions, not in severe OA. Moreover, our analysis revealed strong correlations between cartilage and STB properties in healthy joints and moderate OA regions. However, these correlations were absent in severe OA regions, indicating a disruption in the usual relationship between these tissues. Overall, our findings shed light on the structural and biomechanical changes occurring within the knee joint in OA. Understanding these changes may offer insights into potential therapeutic strategies for managing OA.

Predictive value of sarcopenia components for all-cause mortality: findings from population-based cohorts.

BACKGROUND: Low grip strength and gait speed are associated with mortality. However, investigation of the additional mortality risk explained by these measures, over and above other factors, is limited. AIM: We examined whether grip strength and gait speed improve discriminative capacity for mortality over and above more readily obtainable clinical risk factors. METHODS: Participants from the Health, Aging and Body Composition Study, Osteoporotic Fractures in Men Study, and the Hertfordshire Cohort Study were analysed. Appendicular lean mass (ALM) was ascertained using DXA; muscle strength by grip dynamometry; and usual gait speed over 2.4-6 m. Verified deaths were recorded. Associations between sarcopenia components and mortality were examined using Cox regression with cohort as a random effect; discriminative capacity was assessed using Harrell's Concordance Index (C-index). RESULTS: Mean (SD) age of participants (n = 8362) was 73.8(5.1) years; 5231(62.6%) died during a median follow-up time of 13.3 years. Grip strength (hazard ratio (95% CI) per SD decrease: 1.14 (1.10,1.19)) and gait speed (1.21 (1.17,1.26)), but not ALM index (1.01 (0.95,1.06)), were associated with mortality in mutually-adjusted models after accounting for age, sex, BMI, smoking status, alcohol consumption, physical activity, ethnicity, education, history of fractures and falls, femoral neck bone mineral density (BMD), self-rated health, cognitive function and number of comorbidities. However, a model containing only age and sex as exposures gave a C-index (95% CI) of 0.65(0.64,0.66), which only increased to 0.67(0.67,0.68) after inclusion of grip strength and gait speed. CONCLUSIONS: Grip strength and gait speed may generate only modest adjunctive risk information for mortality compared with other more readily obtainable risk factors.

Higher expression of denervation-responsive genes is negatively associated with muscle volume and performance traits in the study of muscle, mobility, and aging (SOMMA).

With aging skeletal muscle fibers undergo repeating cycles of denervation and reinnervation. In approximately the 8th decade of life reinnervation no longer keeps pace, resulting in the accumulation of persistently denervated muscle fibers that in turn cause an acceleration of muscle dysfunction. The significance of denervation in important clinical outcomes with aging is poorly studied. The Study of Muscle, Mobility, and Aging (SOMMA) is a large cohort study with the primary objective to assess how aging muscle biology impacts clinically important traits. Using transcriptomics data from vastus lateralis muscle biopsies in 575 participants we have selected 49 denervation-responsive genes to provide insights to the burden of denervation in SOMMA, to test the hypothesis that greater expression of denervation-responsive genes negatively associates with SOMMA participant traits that included time to walk 400 meters, fitness (VO2peak), maximal mitochondrial respiration, muscle mass and volume, and leg muscle strength and power. Consistent with our hypothesis, increased transcript levels of: a calciumdependent intercellular adhesion glycoprotein (CDH15), acetylcholine receptor subunits (CHRNA1, CHRND, CHRNE), a glycoprotein promoting reinnervation (NCAM1), a transcription factor regulating aspects of muscle organization (RUNX1), and a sodium channel (SCN5A) were each negatively associated with at least 3 of these traits. VO2peak and maximal respiration had the strongest negative associations with 15 and 19 denervation-responsive genes, respectively. In conclusion, the abundance of denervationresponsive gene transcripts is a significant determinant of muscle and mobility outcomes in aging humans, supporting the imperative to identify new treatment strategies to restore innervation in advanced age.

The Mediating Role of Kynurenine Pathway Metabolites on the Relationship Between Inflammation and Muscle Mass in Oldest-Old Men.

Tryptophan (TRP) metabolites along the kynurenine (KYN) pathway (KP) have been found to influence muscle. Proinflammatory cytokines are known to stimulate the degradation of TRP down the KP. Given that both inflammation and KP metabolites have been connected with loss of muscle, we assessed the potential mediating role of KP metabolites on inflammation and muscle mass in older men. Five hundred and five men (85.0 ±â€…4.2 years) from the Osteoporotic Fractures in Men cohort study with measured D3-creatine dilution (D3Cr) muscle mass, KP metabolites, and inflammation markers (C-reactive protein [CRP], alpha-1-acid glycoprotein [AGP] and a subsample [n = 305] with interleukin [IL-6, IL-1ß, IL-17A] and tumor necrosis factor-α [TNF-α]) were included in the analysis. KP metabolites and inflammatory markers were measured using liquid chromatography-tandem mass spectrometry and immunoassays, respectively. 23%-92% of the inverse relationship between inflammatory markers and D3Cr muscle mass was mediated by KP metabolites (indirect effect p < .05). 3-hydroxyanthranilic acid (3-HAA), quinolinic acid (QA), TRP, xanthurenic acid (XA), KYN/TRP, 3-hydroxykynurenine (3-HK)/3-HAA, QA/3-HAA, and nicotinamide (NAM)/QA mediated the AGP relationship. 3-HAA, QA, KYN/TRP, 3-HK/XA, HKr ratio, 3-HK/3-HAA, QA/3-HAA, and NAM/QA mediated the CRP. KYN/TRP, 3-HK/XA, and NAM/QA explained the relationship for IL-6 and 3-HK/XA and QA/3-HAA for TNF-α. No mediation effect was observed for the other cytokines (indirect effect p > .05). KP metabolites, particularly higher ratios of KYN/TRP, 3-HK/XA, 3-HK/3-HAA, QA/3-HAA, and a lower ratio of NAM/QA, mediated the relationship between inflammation and low muscle mass. Our preliminary cross-sectional data suggest that interventions to alter D3Cr muscle mass may focus on KP metabolites rather than inflammation per se.

Isolation of Nuclei from Human Intermuscular Adipose Tissue and Downstream Single-Nuclei RNA Sequencing.

Intermuscular adipose tissue (IMAT) is a relatively understudied adipose depot located between muscle fibers. IMAT content increases with age and BMI and is associated with metabolic and muscle degenerative diseases; however, an understanding of the biological properties of IMAT and its interplay with the surrounding muscle fibers is severely lacking. In recent years, single-cell and nuclei RNA sequencing have provided us with cell type-specific atlases of several human tissues. However, the cellular composition of human IMAT remains largely unexplored due to the inherent challenges of its accessibility from biopsy collection in humans. In addition to the limited amount of tissue collected, the processing of human IMAT is complicated due to its proximity to skeletal muscle tissue and fascia. The lipid-laden nature of the adipocytes makes it incompatible with single-cell isolation. Hence, single nuclei RNA sequencing is optimal for obtaining high-dimensional transcriptomics at single-cell resolution and provides the potential to uncover the biology of this depot, including the exact cellular composition of IMAT. Here, we present a detailed protocol for nuclei isolation and library preparation of frozen human IMAT for single nuclei RNA sequencing. This protocol allows for the profiling of thousands of nuclei using a droplet-based approach, thus providing the capacity to detect rare and low-abundant cell types.

Effect of weight loss on knee joint synovitis over 48 months and mediation by subcutaneous fat around the knee: data from the Osteoarthritis Initiative.

BACKGROUND: Obesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression. METHODS: We included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m2) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (< ± 3% change, n = 117) over 48 months matched for age and sex. In magnetic resonance imaging (MRI) at baseline and 48 months, effusion-synovitis and Hoffa-synovitis using the MRI Osteoarthritis Knee Score (MOAKS) and average joint-adjacent SCF (ajSCF) were assessed. Odds-ratios (ORs) for synovitis progression over 48 months (≥ 1 score increase) were calculated in logistic regression models adjusting for age, sex, baseline BMI, Physical Activity Scale for the Elderly (PASE), and baseline SCF measurements. Mediation of the effect of weight loss on synovitis progression by local SCF change was assessed. RESULTS: Odds for effusion-synovitis progression decreased with weight loss and ajSCF decrease (odds ratio [OR] = 0.61 and 0.56 per standard deviation [SD] change, 95% confidence interval [CI] 0.44, 0.83 and 0.40, 0.79, p = 0.002 and 0.001, respectively), whereas odds for Hoffa-synovitis progression increased with weight loss and ajSCF decrease (OR = 1.47 and 1.48, CI 1.05, 2.04 and 1.02, 2.13, p = 0.024 and 0.038, respectively). AjSCF decrease mediated 39% of the effect of weight loss on effusion-synovitis progression. CONCLUSIONS: Effusion-synovitis progression was slowed by weight loss and decrease in local subcutaneous fat. Hoffa-synovitis characterized by fluid in the infrapatellar fat pad increased at the same time, suggesting a decreasing fat pad rather than active synovitis. Decrease in local subcutaneous fat partially mediated the systemic effect of weight loss on synovitis.

Cohort profile: Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) - an international consortium of prospective cohort studies with individual participant data on hip osteoarthritis.

PURPOSE: Hip osteoarthritis (OA) is a major cause of pain and disability worldwide. Lack of effective therapies may reflect poor knowledge on its aetiology and risk factors, and result in the management of end-stage hip OA with costly joint replacement. The Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) consortium was established to pool and harmonise individual participant data from prospective cohort studies. The consortium aims to better understand determinants and risk factors for the development and progression of hip OA, to optimise and automate methods for (imaging) analysis, and to develop a personalised prediction model for hip OA. PARTICIPANTS: World COACH aimed to include participants of prospective cohort studies with ≥200 participants, that have hip imaging data available from at least 2 time points at least 4 years apart. All individual participant data, including clinical data, imaging (data), biochemical markers, questionnaires and genetic data, were collected and pooled into a single, individual-level database. FINDINGS TO DATE: World COACH currently consists of 9 cohorts, with 38 021 participants aged 18-80 years at baseline. Overall, 71% of the participants were women and mean baseline age was 65.3±8.6 years. Over 34 000 participants had baseline pelvic radiographs available, and over 22 000 had an additional pelvic radiograph after 8-12 years of follow-up. Even longer radiographic follow-up (15-25 years) is available for over 6000 of these participants. FUTURE PLANS: The World COACH consortium offers unique opportunities for studies on the relationship between determinants/risk factors and the development or progression of hip OA, by using harmonised data on clinical findings, imaging, biomarkers, genetics and lifestyle. This provides a unique opportunity to develop a personalised hip OA risk prediction model and to optimise methods for imaging analysis of the hip.

Age Is Associated With Dampened Circadian Patterns of Rest and Activity: The Study of Muscle, Mobility, and Aging (SOMMA).

BACKGROUND: The effects of aging on circadian patterns of behavior are insufficiently described. To address this, we characterized age-specific features of rest-activity rhythms (RAR) in community-dwelling older adults both overall, and in relation, to sociodemographic characteristics. METHODS: We examined cross-sectional associations between RAR and age, sex, race, education, multimorbidity burden, financial, work, martial, health, and smoking status using assessments of older adults with wrist-worn free-living actigraphy data (N = 820, age = 76.4 years, 58.2% women) participating in the Study of Muscle, Mobility, and Aging (SOMMA). RAR parameters were determined by mapping an extension to the traditional cosine curve to activity data. Functional principal component analysis determined variables accounting for variance. RESULTS: Age was associated with several metrics of dampened RAR; women had stronger and more robust RAR versus men (all p < .05). Total activity (56%) and time of activity (20%) accounted for most of the RAR variance. Compared to the latest decile of acrophase, those in the earliest decile had higher average amplitude (p < .001). Compared to the latest decile of acrophase, those in the earliest and midrange categories had more total activity (p = .02). Being in a married-like relationship and a more stable financial situation were associated with stronger rhythms; higher education was associated with less rhythm strength (all p < .05). CONCLUSIONS: Older age was associated with dampened circadian behavior; behaviors were sexually dimorphic. Some sociodemographic characteristics were associated with circadian behavior. We identified a behavioral phenotype characterized by early time of day of peak activity, high rhythmic amplitude, and more total activity.

Impact of Upadacitinib on Laboratory Parameters and Related Adverse Events in Patients with RA: Integrated Data Up to 6.5 Years.

INTRODUCTION: Upadacitinib (UPA) is a Janus kinase inhibitor that has demonstrated efficacy in moderate-to-severe rheumatoid arthritis (RA) with an acceptable safety profile. We investigated laboratory parameter changes in UPA RA clinical trials. METHODS: Pooled data from six randomized trials in the SELECT phase 3 program were included. Key laboratory parameters and safety data were measured for UPA 15 and 30 mg once daily (QD), adalimumab (ADA) 40 mg every other week + methotrexate (MTX), and MTX monotherapy. Exposure-adjusted event rates (EAERs) of adverse events were calculated. RESULTS: A total of 3209 patients receiving UPA 15 mg QD (10 782.7 patient-years [PY]), 1204 patients receiving UPA 30 mg QD (3162.5 PY), 579 patients receiving ADA + MTX (1573.2 PY), and 314 patients receiving MTX monotherapy (865.1 PY) were included, representing up to 6.5 years of total exposure. Decreases in mean levels of hemoglobin, neutrophils, and lymphocytes, and increases in mean levels of liver enzymes and creatinine phosphokinase were observed with UPA, with grade 3 or 4 changes observed in some patients. Mean low- and high-density lipoprotein cholesterol ratios remained stable for patients receiving UPA 15 mg QD. EAERs of anemia and neutropenia occurred at generally consistent rates between UPA and active comparators (3.1-4.3 and 1.7-5.0 events [E]/100 PY across treatment groups, respectively). Rates of hepatic disorder were higher with MTX monotherapy, UPA 15 mg and UPA 30 mg (10.8, 9.7, and 11.0 E/100 PY, respectively) versus ADA + MTX (6.4 E/100 PY). Rates of lymphopenia were highest with MTX monotherapy (3.2 E/100 PY). Treatment discontinuations due to laboratory-related events were rare, occurring in 1.1% and 2.2% of patients treated with UPA 15 and 30 mg QD, respectively. CONCLUSIONS: The results of this integrated long-term analysis of laboratory parameters continue to support an acceptable safety profile of UPA 15 mg QD for moderate-to-severe RA.