Longevity and muscle strength are heritable traits, and age-related muscle weakness is a major contributor to disability in older adults. However, the susceptibility genes and shared genetic mechanisms underlying lifespan and sarcopenia remain unclear. This study aimed to identify genes associated with longevity and muscle weakness and to characterize their shared genetic architecture.
{"title":"Identifying Susceptibility Genes and Shared Genetic Architecture for Longevity and Muscle Weakness","authors":"Yilong Lin, Yun Zhang, Shengjie Lin, Songsong Wang, Zhiqiang Que, Yue Zhang, Jing She, Ruidan Zhao, Jiawei Chen, Anqi Qiu, Shinan Wu, Ruiqin Yang, Liyi Zhang, Qingmo Yang","doi":"10.1002/jcsm.70197","DOIUrl":"https://doi.org/10.1002/jcsm.70197","url":null,"abstract":"Longevity and muscle strength are heritable traits, and age-related muscle weakness is a major contributor to disability in older adults. However, the susceptibility genes and shared genetic mechanisms underlying lifespan and sarcopenia remain unclear. This study aimed to identify genes associated with longevity and muscle weakness and to characterize their shared genetic architecture.","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"397 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kenney Ki Lee Lau, Abbey Ssu Chi Chen, Christine Hoi Yan Fu, Jonathan Patrick Ng, Michael Tim Yun Ong, Patrick Shu Hang Yung, Pauline Po Yee Lui
Current treatments for knee osteoarthritis (OA) offer limited functional and structural improvements. Compared to age- and gender-matched controls, patients with knee OA show a higher prevalence of muscle weakness, which negatively affects their ability to exercise—a key factor in enhancing physical mobility and delaying disease progression. Pulsed electromagnetic field (PEMF) therapy shows promise in promoting myogenesis and chondrogenesis in pre-clinical studies. However, its effects on muscle strength and size, cartilage deterioration and overall physical function in knee OA patients remain unclear. This randomized placebo-controlled trial aimed to evaluate the impact of PEMF therapy on knee muscle power, lean muscle mass, femoral cartilage thickness, minimum joint space width (mJSW), lower limb physical functions and knee-specific patient-reported outcome (PRO) in patients with refractory mild-to-moderate knee OA.
{"title":"Pulsed Electromagnetic Field Therapy for Mild-to-Moderate Knee Osteoarthritis: A Double-Blind, Randomized, Placebo-Controlled Clinical Trial","authors":"Kenney Ki Lee Lau, Abbey Ssu Chi Chen, Christine Hoi Yan Fu, Jonathan Patrick Ng, Michael Tim Yun Ong, Patrick Shu Hang Yung, Pauline Po Yee Lui","doi":"10.1002/jcsm.70199","DOIUrl":"https://doi.org/10.1002/jcsm.70199","url":null,"abstract":"Current treatments for knee osteoarthritis (OA) offer limited functional and structural improvements. Compared to age- and gender-matched controls, patients with knee OA show a higher prevalence of muscle weakness, which negatively affects their ability to exercise—a key factor in enhancing physical mobility and delaying disease progression. Pulsed electromagnetic field (PEMF) therapy shows promise in promoting myogenesis and chondrogenesis in pre-clinical studies. However, its effects on muscle strength and size, cartilage deterioration and overall physical function in knee OA patients remain unclear. This randomized placebo-controlled trial aimed to evaluate the impact of PEMF therapy on knee muscle power, lean muscle mass, femoral cartilage thickness, minimum joint space width (mJSW), lower limb physical functions and knee-specific patient-reported outcome (PRO) in patients with refractory mild-to-moderate knee OA.","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xi Xiong, David T W Lui, Chengsheng Ju, Xiaodong Liu, Li Wei, Manju Chandran, Carlos K H Wong
Background: Type 2 diabetes is associated with an increased risk of fragility fractures. While obesity may protect against fractures, individuals with type 2 diabetes often exhibit other metabolic syndrome (MetS) traits and albuminuria. We evaluated their roles and synergistic implications on incident fractures, stratified by obesity status.
Methods: Patients with type 2 diabetes were identified from territory-wide electronic health records in Hong Kong (2000-2018). MetS-related traits included albuminuria and individual MetS traits (obesity, hypertension, low HDL-cholesterol and hypertriglyceridemia). Outcomes were hip and major osteoporotic fractures (MOF). Patients were followed until fracture, death or 31 December 2020. Adjusted hazard ratios (aHRs) were estimated using multivariable Cox models.
Results: Among 165 289 patients with type 2 diabetes (median age: 60.0 years; 54.2% men), 1583 (0.96%) experienced hip fractures, and 3393 (2.05%) had MOF over a median follow-up of 5.3 years. Albuminuria was the strongest risk factor for hip fractures (obese: aHR 1.33, 95% CI 1.11-1.60; non-obese: 1.54, 1.33-1.78) and MOF (obese: 1.13, 1.01-1.26; non-obese: 1.28, 1.15-1.43). Hypertension was a significant risk factor only in non-obese patients. In the non-obese group, each additional MetS-related trait was associated with an increased risk of hip fracture and MOF. When stratified by diabetes duration, albuminuria remained a significant risk factor across different diabetes durations, while suboptimal glycaemic control became a significant risk factor particularly when diabetes duration ≥ 5 years.
Conclusions: In this large population-based cohort of patients with type 2 diabetes predominantly of Asian descent from Hong Kong, albuminuria emerged as an important predictor of fracture risk. MetS traits compound this risk, especially in non-obese individuals. These findings could be instrumental in shaping screening initiatives for fracture risk optimization in type 2 diabetes.
背景:2型糖尿病与脆性骨折的风险增加有关。虽然肥胖可以预防骨折,但2型糖尿病患者经常表现出其他代谢综合征(MetS)特征和蛋白尿。我们评估了它们在偶发性骨折中的作用和协同作用,并按肥胖状况分层。方法:从香港地区(2000-2018年)的电子健康记录中确定2型糖尿病患者。代谢相关特征包括蛋白尿和个体代谢相关特征(肥胖、高血压、低高密度脂蛋白胆固醇和高甘油三酯血症)。结果为髋部和主要骨质疏松性骨折(MOF)。对患者进行随访,直至骨折、死亡或2020年12月31日。校正风险比(aHRs)采用多变量Cox模型估计。结果:165 289例2型糖尿病患者(中位年龄:60.0岁,男性54.2%)中位随访5.3年,1583例(0.96%)髋部骨折,3393例(2.05%)发生MOF。蛋白尿是髋部骨折(肥胖:aHR 1.33, 95% CI 1.11-1.60;非肥胖:1.54,1.33-1.78)和MOF(肥胖:1.13,1.01-1.26;非肥胖:1.28,1.15-1.43)的最强危险因素。高血压仅在非肥胖患者中是显著的危险因素。在非肥胖组中,每增加一个met相关特征都与髋部骨折和MOF的风险增加有关。当按糖尿病病程分层时,蛋白尿在不同的糖尿病病程中仍然是一个重要的危险因素,而血糖控制不佳成为一个重要的危险因素,特别是当糖尿病病程≥5年时。结论:在以香港亚裔为主的2型糖尿病患者为研究对象的大型人群队列中,蛋白尿成为骨折风险的重要预测因子。代谢代谢特征使这种风险更加复杂,尤其是在非肥胖者中。这些发现可能有助于制定2型糖尿病患者骨折风险优化筛查计划。
{"title":"Associations of Albuminuria and Metabolic Syndrome Traits With Fracture Risk in Patients With Type 2 Diabetes: A Population-Based Cohort Study.","authors":"Xi Xiong, David T W Lui, Chengsheng Ju, Xiaodong Liu, Li Wei, Manju Chandran, Carlos K H Wong","doi":"10.1002/jcsm.70215","DOIUrl":"10.1002/jcsm.70215","url":null,"abstract":"<p><strong>Background: </strong>Type 2 diabetes is associated with an increased risk of fragility fractures. While obesity may protect against fractures, individuals with type 2 diabetes often exhibit other metabolic syndrome (MetS) traits and albuminuria. We evaluated their roles and synergistic implications on incident fractures, stratified by obesity status.</p><p><strong>Methods: </strong>Patients with type 2 diabetes were identified from territory-wide electronic health records in Hong Kong (2000-2018). MetS-related traits included albuminuria and individual MetS traits (obesity, hypertension, low HDL-cholesterol and hypertriglyceridemia). Outcomes were hip and major osteoporotic fractures (MOF). Patients were followed until fracture, death or 31 December 2020. Adjusted hazard ratios (aHRs) were estimated using multivariable Cox models.</p><p><strong>Results: </strong>Among 165 289 patients with type 2 diabetes (median age: 60.0 years; 54.2% men), 1583 (0.96%) experienced hip fractures, and 3393 (2.05%) had MOF over a median follow-up of 5.3 years. Albuminuria was the strongest risk factor for hip fractures (obese: aHR 1.33, 95% CI 1.11-1.60; non-obese: 1.54, 1.33-1.78) and MOF (obese: 1.13, 1.01-1.26; non-obese: 1.28, 1.15-1.43). Hypertension was a significant risk factor only in non-obese patients. In the non-obese group, each additional MetS-related trait was associated with an increased risk of hip fracture and MOF. When stratified by diabetes duration, albuminuria remained a significant risk factor across different diabetes durations, while suboptimal glycaemic control became a significant risk factor particularly when diabetes duration ≥ 5 years.</p><p><strong>Conclusions: </strong>In this large population-based cohort of patients with type 2 diabetes predominantly of Asian descent from Hong Kong, albuminuria emerged as an important predictor of fracture risk. MetS traits compound this risk, especially in non-obese individuals. These findings could be instrumental in shaping screening initiatives for fracture risk optimization in type 2 diabetes.</p>","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"17 1","pages":"e70215"},"PeriodicalIF":9.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12864539/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146103297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDAI-driven automated body composition analysis (BCA) may provide quantitative prognostic biomarkers derived from routine staging CTs. This two-centre study evaluates the prognostic value of these volumetric markers for overall survival in lung cancer patients.METHODSLung cancer cohorts from Hospital A (n = 3345, median age 65, 86% NSCLC, 40% M1, 40% female) and B (n = 1364, median age 66, 87% NSCLC, 37% M1, 38% female) underwent automated BCA of abdominal CTs ±60 days of primary diagnosis. A deep learning network segmented muscle, bone and adipose tissues (visceral = VAT, subcutaneous = SAT, intra-/intermuscular = IMAT and total = TAT) to derive three markers: Sarcopenia Index (SI = Muscle/Bone), Myosteatotic Fat Index (MFI = IMAT/TAT) and Abdominal Fat Index (AFI = VAT/SAT). Kaplan-Meier survival analysis, Cox proportional hazards modelling and machine learning-based survival prediction were performed. A survival model including clinical data (BMI, ECOG, L3-SMI, -SATI, -VATI and -IMATI) was fitted on Hospital A data and validated on Hospital B data.RESULTSIn nonmetastatic NSCLC, high SI predicted longer survival across centres for males (Hospital A: 24.6 vs. 46.0 months; Hospital B: 13.3 vs. 28.9 months; both p < 0.001) and females (Hospital A: 37.9 vs. 53.6 months, p = 0.008; Hospital B: 23.0 vs. 28.6 months, p = 0.018). High MFI indicated reduced survival in males at both hospitals (Hospital A: 43.7 vs. 28.2 months; Hospital B: 28.8 vs. 14.3 months; both p ≤ 0.001) but showed center-dependent effects in females (significant only in Hospital A, p < 0.01). In metastatic disease, SI remained prognostic for males at both centres (p < 0.05), while MFI was significant only in Hospital A (p ≤ 0.001) and AFI only in Hospital B (p = 0.042). Multivariate Cox regression confirmed that higher SI was protective (A: HR 0.53, B: 0.59, p ≤ 0.001), while MFI was associated with shorter survival (A: HR 1.31, B: 1.12, p < 0.01). The multivariate survival model trained on Hospital A's data demonstrated prognostic differentiation of groups in internal (n = 209, p ≤ 0.001) and external (Hospital B, n = 361, p = 0.044) validation, with SI feature importance (0.037) ranking below ECOG (0.082) and M-status (0.078), outperforming all other features including conventional L3-single-slice measurements.CONCLUSIONCT-based volumetric BCA provides prognostic biomarkers in lung cancer with varying significance by sex, disease stage and centre. SI was the strongest prognostic marker, outperforming conventional L3-based measurements, while fat-related markers showed varying associations. Our multivariate model suggests that BCA markers, particularly SI, may enhance risk stratification in lung cancer, pending centre-specific and sex-specific validation. Integration of these markers into clinical workflows could enable personalized care and targeted interventions for high-risk patients.
{"title":"Exploration of Fully-Automated Body Composition Analysis Using Routine CT-Staging of Lung Cancer Patients for Survival Prognosis.","authors":"Marc-David Künnemann,Christian Römer,Anne Helfen,Annalen Bleckmann,Marcel Kemper,Walter Heindel,Tobias J Brix,Michael Forsting,Johannes Haubold,Marcel Opitz,Martin Schuler,Felix Nensa,Katarzyna Borys,René Hosch","doi":"10.1002/jcsm.70021","DOIUrl":"https://doi.org/10.1002/jcsm.70021","url":null,"abstract":"BACKGROUNDAI-driven automated body composition analysis (BCA) may provide quantitative prognostic biomarkers derived from routine staging CTs. This two-centre study evaluates the prognostic value of these volumetric markers for overall survival in lung cancer patients.METHODSLung cancer cohorts from Hospital A (n = 3345, median age 65, 86% NSCLC, 40% M1, 40% female) and B (n = 1364, median age 66, 87% NSCLC, 37% M1, 38% female) underwent automated BCA of abdominal CTs ±60 days of primary diagnosis. A deep learning network segmented muscle, bone and adipose tissues (visceral = VAT, subcutaneous = SAT, intra-/intermuscular = IMAT and total = TAT) to derive three markers: Sarcopenia Index (SI = Muscle/Bone), Myosteatotic Fat Index (MFI = IMAT/TAT) and Abdominal Fat Index (AFI = VAT/SAT). Kaplan-Meier survival analysis, Cox proportional hazards modelling and machine learning-based survival prediction were performed. A survival model including clinical data (BMI, ECOG, L3-SMI, -SATI, -VATI and -IMATI) was fitted on Hospital A data and validated on Hospital B data.RESULTSIn nonmetastatic NSCLC, high SI predicted longer survival across centres for males (Hospital A: 24.6 vs. 46.0 months; Hospital B: 13.3 vs. 28.9 months; both p < 0.001) and females (Hospital A: 37.9 vs. 53.6 months, p = 0.008; Hospital B: 23.0 vs. 28.6 months, p = 0.018). High MFI indicated reduced survival in males at both hospitals (Hospital A: 43.7 vs. 28.2 months; Hospital B: 28.8 vs. 14.3 months; both p ≤ 0.001) but showed center-dependent effects in females (significant only in Hospital A, p < 0.01). In metastatic disease, SI remained prognostic for males at both centres (p < 0.05), while MFI was significant only in Hospital A (p ≤ 0.001) and AFI only in Hospital B (p = 0.042). Multivariate Cox regression confirmed that higher SI was protective (A: HR 0.53, B: 0.59, p ≤ 0.001), while MFI was associated with shorter survival (A: HR 1.31, B: 1.12, p < 0.01). The multivariate survival model trained on Hospital A's data demonstrated prognostic differentiation of groups in internal (n = 209, p ≤ 0.001) and external (Hospital B, n = 361, p = 0.044) validation, with SI feature importance (0.037) ranking below ECOG (0.082) and M-status (0.078), outperforming all other features including conventional L3-single-slice measurements.CONCLUSIONCT-based volumetric BCA provides prognostic biomarkers in lung cancer with varying significance by sex, disease stage and centre. SI was the strongest prognostic marker, outperforming conventional L3-based measurements, while fat-related markers showed varying associations. Our multivariate model suggests that BCA markers, particularly SI, may enhance risk stratification in lung cancer, pending centre-specific and sex-specific validation. Integration of these markers into clinical workflows could enable personalized care and targeted interventions for high-risk patients.","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"27 1","pages":"e70021"},"PeriodicalIF":8.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144787090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pamela N. Klassen, Vera C. Mazurak, Jessica Thorlakson, Stephane Servais
Investigators are increasingly measuring skeletal muscle (SM) and adipose tissue (AT) change during cancer treatment to understand impact on patient outcomes. Recent meta‐analyses have reported high heterogeneity in this literature, representing uncertainty in the resulting estimates. Using the setting of palliative‐intent chemotherapy as an exemplar, we aimed to systematically summarize the sources of variability among studies evaluating SM and AT change during cancer treatment and propose standards for future studies to enable reliable meta‐analysis. Studies that measured computed tomography‐defined SM and/or AT change in adult patients during palliative‐intent chemotherapy for solid tumours were included, with no date or geographical limiters. Of 2496 publications screened by abstract/title, 83 were reviewed in full text and 38 included for extraction, representing 34 unique cohorts across 8 tumour sites. The timing of baseline measurement was frequently defined as prior to treatment, while endpoint timing ranged from 6 weeks after treatment start to time of progression. Fewer than 50% specified the actual time interval between measurements. Measurement error was infrequently discussed (8/34). A single metric (cm2/m2, cm2 or %) was used to describe SM change in 18/34 cohorts, while multiple metrics were presented for 10/34 and no descriptive metrics for 6/34. AT change metrics and sex‐specific reporting were available for 10/34 cohorts. Associations between SM loss and overall survival were evaluated in 24 publications, with classification of SM loss ranging from any loss to >14% loss over variable time intervals. Age and sex were the most common covariates, with disease response in 50% of models. Despite a wealth of data and effort, heterogeneity in study design, reporting and statistical analysis hinders evidence synthesis regarding the severity and outcomes of SM and AT change during cancer treatment. Proposed standards for study design include selection of homogenous cohorts, clear definition of baseline/endpoint timing and attention to measurement error. Standard reporting should include baseline SM and AT by sex, actual scan interval, SM and AT change using multiple metrics and visualization of the range of change observed. Reporting by sex would advance understanding of sexual dimorphism in SM and AT change. Evaluating the impact of tissue change on outcomes requires adjustment for relevant covariates and concurrent disease response. Adoption of these standards by researchers and publishers would alter the current paradigm to enable meta‐analysis of future studies and move the field towards meaningful application of SM and AT change to clinical care.
{"title":"Call for standardization in assessment and reporting of muscle and adipose change using computed tomography analysis in oncology: A scoping review","authors":"Pamela N. Klassen, Vera C. Mazurak, Jessica Thorlakson, Stephane Servais","doi":"10.1002/jcsm.13318","DOIUrl":"10.1002/jcsm.13318","url":null,"abstract":"Investigators are increasingly measuring skeletal muscle (SM) and adipose tissue (AT) change during cancer treatment to understand impact on patient outcomes. Recent meta‐analyses have reported high heterogeneity in this literature, representing uncertainty in the resulting estimates. Using the setting of palliative‐intent chemotherapy as an exemplar, we aimed to systematically summarize the sources of variability among studies evaluating SM and AT change during cancer treatment and propose standards for future studies to enable reliable meta‐analysis. Studies that measured computed tomography‐defined SM and/or AT change in adult patients during palliative‐intent chemotherapy for solid tumours were included, with no date or geographical limiters. Of 2496 publications screened by abstract/title, 83 were reviewed in full text and 38 included for extraction, representing 34 unique cohorts across 8 tumour sites. The timing of baseline measurement was frequently defined as prior to treatment, while endpoint timing ranged from 6 weeks after treatment start to time of progression. Fewer than 50% specified the actual time interval between measurements. Measurement error was infrequently discussed (8/34). A single metric (cm2/m2, cm2 or %) was used to describe SM change in 18/34 cohorts, while multiple metrics were presented for 10/34 and no descriptive metrics for 6/34. AT change metrics and sex‐specific reporting were available for 10/34 cohorts. Associations between SM loss and overall survival were evaluated in 24 publications, with classification of SM loss ranging from any loss to >14% loss over variable time intervals. Age and sex were the most common covariates, with disease response in 50% of models. Despite a wealth of data and effort, heterogeneity in study design, reporting and statistical analysis hinders evidence synthesis regarding the severity and outcomes of SM and AT change during cancer treatment. Proposed standards for study design include selection of homogenous cohorts, clear definition of baseline/endpoint timing and attention to measurement error. Standard reporting should include baseline SM and AT by sex, actual scan interval, SM and AT change using multiple metrics and visualization of the range of change observed. Reporting by sex would advance understanding of sexual dimorphism in SM and AT change. Evaluating the impact of tissue change on outcomes requires adjustment for relevant covariates and concurrent disease response. Adoption of these standards by researchers and publishers would alter the current paradigm to enable meta‐analysis of future studies and move the field towards meaningful application of SM and AT change to clinical care.","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"14 5","pages":"1918-1931"},"PeriodicalIF":8.9,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcsm.13318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10524503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicolas Collao, Donna D'Souza, Laura Messeiller, Evan Pilon, Jessica Lloyd, Jillian Larkin, Matthew Ngu, Alexanne Cuillerier, Alexander E. Green, Keir J. Menzies, Yan Burelle, Michael De Lisio