Sex related differences in muscle health and metabolism in chronic obstructive pulmonary disease.

BACKGROUND & AIMS: Sex differences in muscle function and mass, dyspnea, and clinical outcomes have been observed in patients with Chronic Obstructive Pulmonary Disease (COPD) despite a similar level of airflow obstruction. Protein and amino acid metabolism is altered in COPD, however, it remains unclear whether a difference in metabolic signature exists between males and females with COPD that may explain the observed differences in muscle health and clinical outcomes. METHODS: In 234 moderate to severe COPD patients (males/females: 113/121) and 182 healthy controls (males/females: 77/105), we assessed, besides presence of comorbidities and clinical features, muscle function by handgrip and leg dynamometry, and body composition by dual-energy x-ray absorptiometry. In the postabsorptive state, a mixture of 18 stable isotopes of amino acids was administered by pulse and arterialized blood was sampled for 2 h. Amino acid concentrations and enrichments were analyzed by LC-MS/MS to calculate whole body (net) protein breakdown (WBnetPB) and whole body production (WBP) rates (µmol/hour) of the amino acids playing a known role in muscle health. Statistics was done by ANCOVA to examine the effects of sex, COPD, and sex-by-COPD interaction with as covariates age and lean mass. Significance was set as p < 0.05. RESULTS: Lung function was comparable between males and females with COPD. Being a female and presence of COPD were independently associated with lower appendicular lean mass, muscle strength, and WBnetPB (p < 0.05). Being a male was associated with higher visceral adipose tissue, C-reactive protein (CRP) (p < 0.05), and higher prevalence of heart failure and obstructive sleep apnea. Sex-by-COPD interactions were found indicating lower fat mass (p = 0.0005) and WBPs of phenylalanine (measure of whole body protein turnover) and essential amino acids (p < 0.05), particularly in COPD females. Higher visceral adipose tissue (p = 0.025), CRP (p < 0.0001), and WBP of tau-methylhistidine (p = 0.010) (reflecting enhanced myofibrillar protein breakdown) were observed in COPD males. CONCLUSIONS: Presence of sex specific changes in protein and amino acid metabolism and cardiometabolic health in COPD need to be considered when designing treatment regimens to restore muscle health in males and females with COPD. CLINICAL TRIAL REGISTRY: www. CLINICALTRIALS: gov, NCT01787682, NCT01624792, NCT02157844, NCT02065141, NCT02770092, NCT02780219, NCT03327181, NCT03796455, NCT01173354, NCT01154400.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.