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Current methods for comparing single-cell RNA sequencing datasets collected in multiple conditions focus on discrete regions of the transcriptional state space, such as clusters of cells. Here we quantify the effects of perturbations at the single-cell level using a continuous measure of the effect of a perturbation across the transcriptomic space. We describe this space as a manifold and develop a relative likelihood estimate of observing each cell in each of the experimental conditions using graph signal processing. This likelihood estimate can be used to identify cell populations specifically affected by a perturbation. We also develop vertex frequency clustering to extract populations of affected cells at the level of granularity that matches the perturbation response. The accuracy of our algorithm at identifying clusters of cells that are enriched or depleted in each condition is, on average, 57% higher than the next-best-performing algorithm tested. Gene signatures derived from these clusters are more accurate than those of six alternative algorithms in ground truth comparisons. Matched treatment and control single-cell RNA sequencing samples are more accurately compared at the single-cell level.

Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data for novel discoveries. We developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis. We demonstrate that scNAT is capable of removing batch effects, and identifying cell clusters and a T cell migration trajectory from blood to cerebrospinal fluid in multiple sclerosis.

Background Malnutrition, weight loss, and muscle wasting (sarcopenia) are common among women with advanced ovarian cancer and have been associated with adverse clinical outcomes and survival. Our objective is to investigate overall survival (OS) related to changes in skeletal muscle (SM) for patients with advanced ovarian cancer treated with neoadjuvant chemotherapy and interval debulking. Methods Ovarian cancer patients (n = 123) treated with neoadjuvant chemotherapy and interval debulking in the area of Maastricht (the Netherlands) between 2000 and 2014 were included retrospectively. Surface areas of SM and adipose tissue were defined on computed tomography at the level of the third lumbar vertebra. Low SM at baseline and SM changes during chemotherapy were compared with Kaplan Meier curves, and Cox‐regression models were applied to test predictors of OS. Results Median OS for patients who lost SM (n = 83) was 916 ± 99 days, which was significantly different from median OS for patients who maintained or gained SM (n = 40), which was 1431 ± 470 days (P = 0.004). Loss of SM was also a significant predictor of OS in multivariable Cox‐regression analysis (hazard ratio 1.773 (95%CI: 1.018–3.088), P = 0.043). Low baseline SM did not influence survival. Conclusions Patients with ovarian cancer have a worse survival when they lose SM during neoadjuvant chemotherapy. Evaluation of low SM at a specific time point is not prognostic for OS. External and prospective validation of these findings is imperative. Nutritional, pharmacological, and/or physical intervention studies are necessary to establish whether SM impairment can be prevented to prolong ovarian cancer survival.

Background Cancer cachexia and skeletal muscle wasting are related to poor survival. In this study, quantitative body composition measurements using computed tomography (CT) were investigated in relation to survival, post‐operative complications, and surgical site infections in surgical patients with cancer of the head of the pancreas. Methods A prospective cohort of 199 patients with cancer of the head of the pancreas was analysed by CT imaging at the L3 level to determine (i) muscle radiation attenuation (average Hounsfield units of total L3 skeletal muscle); (ii) visceral adipose tissue area; (iii) subcutaneous adipose tissue area; (iv) intermuscular adipose tissue area; and (v) skeletal muscle area. Sex‐specific cut‐offs were determined at the lower tertile for muscle radiation attenuation and skeletal muscle area and the higher tertile for adipose tissues. These variables of body composition were related to overall survival, severe post‐operative complications (Dindo–Clavien ≥ 3), and surgical site infections (wounds inspected daily by an independent trial nurse) using Cox‐regression analysis and multivariable logistic regression analysis, respectively. Results Low muscle radiation attenuation was associated with shorter survival in comparison with moderate and high muscle radiation attenuation [median survival 10.8 (95% CI: 8.8–12.8) vs. 17.4 (95% CI: 14.7–20.1), and 18.5 (95% CI: 9.2–27.8) months, respectively; P < 0.008]. Patient subgroups with high muscle radiation attenuation combined with either low visceral adipose tissue or age <70 years had longer survival than other subgroups (P = 0.011 and P = 0.001, respectively). Muscle radiation attenuation was inversely correlated with intermuscular adipose tissue (rp = −0.697, P < 0.001). High visceral adipose tissue was associated with an increased surgical site infection rate, OR: 2.4 (95% CI: 1.1–5.3; P = 0.027). Conclusions Low muscle radiation attenuation was associated with reduced survival, and high visceral adiposity was associated with an increase in surgical site infections. The strong correlation between muscle radiation attenuation and intermuscular adipose tissue suggests the presence of ectopic fat in muscle, warranting further investigation. CT image analysis could be implemented in pre‐operative risk assessment to assist in treatment decision‐making.

Background Cancer cachexia is characterized by a negative energy balance, muscle and adipose tissue wasting, insulin resistance, and systemic inflammation. Because of its strong negative impact on prognosis and its multifactorial nature that is still not fully understood, cachexia remains an important challenge in the field of cancer treatment. Recent animal studies indicate that the gut microbiota is involved in the pathogenesis and manifestation of cancer cachexia, but human data are lacking. The present study investigates gut microbiota composition, short‐chain fatty acids (SCFA), and inflammatory parameters in human cancer cachexia. Methods Faecal samples were prospectively collected in patients (N = 107) with pancreatic cancer, lung cancer, breast cancer, or ovarian cancer. Household partners (N = 76) of the patients were included as healthy controls with similar diet and environmental conditions. Patients were classified as cachectic if they lost >5% body weight in the last 6 months. Gut microbiota composition was analysed by sequencing of the 16S rRNA V4 gene region. Faecal SCFA levels were quantified by gas chromatography. Faecal calprotectin was assessed with enzyme‐linked immunosorbent assay. Serum C‐reactive protein and leucocyte counts were retrieved from medical records. Results Cachexia prevalence was highest in pancreatic cancer (66.7%), followed by ovarian cancer (25%), lung cancer (20.8%), and breast cancer (17.3%). Microbial α‐diversity was not significantly different between cachectic cancer patients (N = 33), non‐cachectic cancer patients (N = 74), or healthy controls (N = 76) (species richness P = 0.31; Shannon effective index P = 0.46). Community structure (β‐diversity) tended to differ between these groups (P = 0.053), although overall differences were subtle and no clear clustering of samples was observed. Proteobacteria (P < 0.001), an unknown genus from the Enterobacteriaceae family (P < 0.01), and Veillonella (P < 0.001) were more abundant among cachectic cancer patients. Megamonas (P < 0.05) and Peptococcus (P < 0.001) also showed differential abundance. Faecal levels of all SCFA tended to be lower in cachectic cancer patients, but only acetate concentrations were significantly reduced (P < 0.05). Faecal calprotectin levels were positively correlated with the abundance of Peptococcus, unknown Enterobacteriaceae, and Veillonella. We also identified several correlations and interactions between clinical and microbial parameters. Conclusions This clinical study provided the first insights into the alterations of gut microbiota composition and SCFA levels that occur in cachectic cancer patients and how they are related to inflammatory parameters. These results pave the way for further research examining the role of the gut microbiota in cancer cachexia and its potential use as therapeutic target.

Low skeletal muscle mass on intensive care unit admission is related to increased mortality. It is however unknown whether this association is influenced by co-morbidities that are associated with skeletal muscle loss. The aim of this study was to investigate whether sarcopenia is an independent risk factor for hospital mortality in critical illness in the presence of co-morbidities associated with muscle wasting. Data of 155 patients with abdominal sepsis were retrospectively analyzed. Skeletal muscle area was assessed using CT-scans at the level of vertebra L3. Demographic and clinical data were retrieved from electronic patient files. Sarcopenia was defined as a muscle area index below the 5th percentile of the general population. Uni- and multivariable analyses were performed to assess the association between sarcopenia and hospital mortality, correcting for age and comorbidities. The prevalence of sarcopenia was higher in patients that did not survive until hospital discharge. However, it appeared that this relation was confounded by the presence of chronic renal insufficiency and cancer. These were independent risk factors for hospital mortality, whereas sarcopenia was not. In critically ill patients with abdominal sepsis, muscle wasting associated co-morbidities rather than sarcopenia were risk factors for hospital mortality. •The prevalence of sarcopenia is higher in non-surviving critically ill patients.•Sarcopenia is not an independent risk factor for mortality in critical illness.•The association between sarcopenia and increased mortality in critically ill is mediated by chronic co-morbidities.

•The assessment of muscle loss during critical illness using computed tomography scans is hampered by the formation of edema.•Edema in critical illness leads to overestimation of muscle area measurements.•Edema formation and decreased muscle quality were associated with a higher disease severity.•Muscle radiation attenuation cannot be used as an indicator for formation of edema.•In critical illness, researchers must be careful with the interpretation of muscle area measurements. Changes in muscle mass and quality are important targets for nutritional intervention in critical illness. Effects of such interventions may be assessed using sequential computed tomography (CT) scans. However, fluid and lipid infiltration potentially affects muscle area measurements. The aim of this study was to evaluate changes in muscle mass and quality in critical illness with special emphasis on the influence of edema on this assessment. Changes in skeletal muscle area index (SMI) and radiation attenuation (RA) at the level of vertebra L3 were analyzed using sequential CT scans of 77 patients with abdominal sepsis. Additionally, the relation between these changes and disease severity using the maximum Sequential Organ Failure Assessment (SOFA) score and change in edema were studied. SMI declined on average 0.35%/d (±1.22%; P = 0.013). However, SMI increased in 41.6% of the study population. Increasing edema formation was significantly associated with increased SMI and with a higher SOFA score. Muscle RA decreased during critical illness, but was not significantly associated with changes in SMI or changes in edema. In critically ill patients, edema affects skeletal muscle area measurements, which leads to an overestimation of skeletal muscle area. A higher SOFA score was associated with edema formation. Because both edema and fat infiltration may affect muscle RA, the separate effects of these on muscle quality are difficult to distinguish. When using abdominal CT scans to changes in muscle mass and quality in critically ill patients, researchers must be aware and careful with the interpretation of the results.

Background Polytrauma patients with an Injury Severity Score (ISS) ≥ 16 have a high mortality rate. Early identification of patients at risk of mortality is key. Different risk stratification models are available; however, body composition on third lumbar computed tomography (L3 CT) is not routinely used. The aim of this study is to determine the effect of CT body composition on 1‐year mortality in adult polytrauma patients. Methods Body composition analysis (L3 CT) was performed on 593 adult polytrauma patients. The associations with 1‐year mortality were assessed using uni‐ and multivariable logistic regression analysis. As a sensitivity analysis, 1‐year mortality was analysed using Kaplan–Meier survival curves, log‐rank tests and Cox regression. Results The study population was predominantly male (69.5%), with a mean age of 55 (±20) years and an average BMI of 25.34 kg/m2 (±4.07). Comorbidities were present in 327 (55.4%) patients, with an average Charlson Comorbidity Index (CCI) of 2.07 points (±2.1). The mean ISS score was 27.59 (±11.06); 323 (54.5%) patients had an ISS ≥ 25 points. Age, CCI, ISS, skeletal muscle index and skeletal muscle radiation attenuation (OR 1.053, 5.713, 3.711, 0. 563 and 0.533, respectively; p < 0.001), subcutaneous adipose tissue radiation attenuation (SATRA OR 1.253, p = 0.028) and visceral adipose tissue index (OR 1.242, p = 0.038) were significantly associated with 1‐year mortality. In multivariable logistic regression, age, ISS and SATRA remained statistically significantly associated with 1‐year mortality (OR 1.062, p < 0.001; OR 4.761, p < 0.001; OR 1.396, p = 0.009). Conclusions This study demonstrated that subcutaneous adipose tissue radiation attenuation on emergency trauma CT scans is significantly associated with 1‐year mortality in adult polytrauma patients. Additionally, we found a significant effect of age and ISS on 1‐year mortality. Incorporating body composition analysis could lead to a better selection of patients at risk for 1‐year mortality and aid in treatment decision‐making.

Background Body composition alterations such as skeletal muscle (SM) loss in cancer patients are associated with poor survival. In turn, immune cell‐driven pathways have been linked to muscle wasting. We aimed to investigate the relationship between body composition, tumour‐infiltrating lymphocytes and survival in patients with advanced lung cancer. Methods We studied 200 patients with advanced lung cancer receiving immunotherapy (n = 81) or non‐immunotherapy regimens (n = 119). Body composition including SM index (SMI) at baseline and longitudinal changes were assessed using computed tomography (CT) scans at the third lumbar vertebra. Associations between body composition parameters and overall survival (OS) were evaluated using Cox regression analysis. The median value of SMI, stratified by sex, was used as the cut‐off to define groups with high and low baseline SMI. Stable SMI was defined by any increase or < 2% decrease per 100 days; loss of SMI was defined by ≥ 2% decrease per 100 days. Logistic regression analysis was applied to investigate the association between SMI and peripheral circulating immune cells. Tumour‐infiltrating lymphocytes were identified by immunohistochemistry, and their relationship with SMI was evaluated. Results SMI loss was associated with shorter OS (whole cohort: HR = 2.314, 95% CI = 1.388–3.858, p = 0.001; immunotherapy cohort: HR = 3.028, 95% CI = 1.113–8.236, p = 0.03; non‐immunotherapy cohort: HR = 2.298, 95% CI = 1.191–4.435, p = 0.013). Low baseline SMI was associated with higher CD3+ T cell abundance (OR = 1.240, 95% CI = 1.080–1.424, p = 0.002) but lower CD3+ CD8+ T cell abundance (OR = 0.862, 95% CI = 0.762–0.974, p = 0.018) in peripheral blood. Subsequent SMI loss during treatment was also significantly associated with higher CD3+ T cell counts (OR = 3.414, 95% CI = 1.301–8.961, p = 0.013) and lower CD3+ CD8+ T cell abundance (OR = 0.666, 95% CI = 0.459–0.968, p = 0.033). Patients with stable SMI had a higher number of CD8+ tumour‐infiltrating lymphocytes than patients with SMI loss (15.4% vs. 7.9%, p = 0.036). Conclusion SM loss is an independent predictor for survival in patients with advanced lung cancer and is associated with reduced peripheral and tumour‐infiltrating cytotoxic T cell abundance. An inadequate antitumour immune response may contribute to metabolic tissue wasting in cancer.

Background Body composition assessment, measured using single‐slice computed tomography (CT) image at L3 level, and aerobic physical fitness, objectively measured using cardiopulmonary exercise testing (CPET), are each independently used for perioperative risk assessment. Sarcopenia (i.e. low skeletal muscle mass), myosteatosis [i.e. low skeletal muscle radiation attenuation (SM‐RA)], and impaired objectively measured aerobic fitness (reduced oxygen uptake) have been associated with poor post‐operative outcomes and survival in various cancer types. However, the association between CT body composition and physical fitness has not been explored. In this study, we assessed the association of CT body composition with selected CPET variables in patients undergoing hepatobiliary and pancreatic surgery. Methods A pragmatic prospective cohort of 123 patients undergoing hepatobiliary and pancreatic surgery were recruited. All patients underwent preoperative CPET. Preoperative CT scans were analysed using a single‐slice CT image at L3 level to assess skeletal muscle mass, adipose tissue mass, and muscle radiation attenuation. Multivariate linear regression was used to test the association between CPET variables and body composition. Main outcomes were oxygen uptake at anaerobic threshold ( V̇O2 at AT), oxygen uptake at peak exercise ( V̇O2 peak), skeletal muscle mass, and SM‐RA. Results Of 123 patients recruited [77 men (63%), median age 66.9 ± 11.7, median body mass index 27.3 ± 5.2], 113 patients had good‐quality abdominal CT scans available and were included. Of the CT body composition variables, SM‐RA had the strongest correlation with V̇O2 peak (r = 0.57, P < 0.001) and V̇O2 at AT (r = 0.45, P < 0.001) while skeletal muscle mass was only weakly associated with V̇O2 peak (r = 0.24, P < 0.010). In the multivariate analysis, only SM‐RA was associated with V̇O2 peak (B = 0.25, 95% CI 0.15–0.34, P < 0.001, R2 = 0.42) and V̇O2 at AT (B = 0.13, 95% CI 0.06–0.18, P < 0.001, R2 = 0.26). Conclusions There is a positive association between preoperative CT SM‐RA and preoperative physical fitness ( V̇O2 at AT and at peak). This study demonstrates that myosteatosis, and not sarcopenia, is associated with reduced aerobic physical fitness. Combining both myosteatosis and physical fitness variables may provide additive risk stratification accuracy and guide interventions during the perioperative period.