The present study demonstrates the feasibility of this MRI technique for assessment of muscle composition in HD patients and that combined assessment of muscle volume and muscle fat seems to predict mortality. Furthermore, the combination of these biomarkers, the combined variable Musclecomb, provides a more complete and muscle specific description.
The current consensus for evaluating sarcopenia recommends assessing muscle quantity as well as muscle function (strength or performance)(2). Due to the high correlation between muscle quantity and body size, the patient’s body size needs to be considered when assessing if they have a proper amount of muscle quantity or no. This is commonly done by creating a skeletal muscle index – muscle quantity divided by height2, weight or BMI. However, the most appropriate method of indexing muscle quantity remains still uncertain(8, 16). Recently, Linge et al. used MRI in a study of sarcopenic obesity and reported that common ways to adjust muscle quantity for body size (division by height2, weight or BMI) does not effectively normalize this relationship and confounds studies on sarcopenia. They suggested a body size adjustment for muscle volume using personalized virtual control groups, that ultimately enabled BMI-independent sarcopenia assessment(8). The same method was applied in this study.
The etiology of sarcopenia in CKD patients is still unclear but multiple factors are involved. Conditions that are directly related to CKD pathogenesis, such as cardiovascular diseases and diabetes mellitus (DM), are also independently associated with sarcopenia(17-19). Therefore, we analyzed the relationship between muscle composition and comorbidity index (nCI) in our patient cohort. We observed that the combined muscle score achieved by muscle volume z-score and MFI was significantly associated with the comorbidity index, but the association with the separate measurements did not reach significant level.
Our results suggest that the comorbidity score may identify patients who are more likely to have sarcopenia. Other studies have also found an association between nCI and sarcopenia supporting the idea that nCI could be used as a predictor to identify sarcopenia (20, 21).
As mentioned above, sarcopenia often co-exists with DM in HD patients and there is evidence that DM is an independent risk factor for the development of sarcopenia (17, 22). Interestingly, in our study, all patients with DM belonged to the non-survivor group where adverse MC with low muscle volume z-score and high MFI were dominant.
Sarcopenia in CKD is associated with important clinical outcomes such as poor quality of life, cognitive impairment, depression, functional decline, frailty and hospitalization (5). Several studies have also reported that sarcopenia is an independent predictor of mortality in CKD patients (23). A new study on 9 000 individuals with CKD on UK Biobank reported that the presence of sarcopenia in CKD increased the mortality risk by 33%(24). In our study, we found that both muscle volume and MFI were significantly and independently associated with mortality and this association was even stronger when the combined score was assessed.
In line with our results, a study with patients undergoing hemodialysis reported that both low muscle mass and reduced muscle strength was associated with mortality (6). Interestingly, analysis of muscle composition data showed that adverse MC (low muscle volume z-score coupled to high MFI) seems to be associated with mortality in our patient group (fig 1). Recently published preliminary data on 40 000 participants in UK Biobank further showed that adverse MC, identified using the same method as in this study, is associated with four times higher mortality in general population(13) .These results, in combination with the results on the CKD patients in the present study, highlight that identification of adverse MC can be used to understand mortality risk related to sarcopenia across disease stages, not only in end stage disease (fig 2).
Hypoalbuminemia is a well-known predictor of mortality in patients with CKD (25) and it has been reported that there is an association between sarcopenia and hypoalbuminemia (24, 26). In our study, we observed that patients in the non-survivor group (with a dominant adverse MC) had significantly lower serum albumin levels.
The strengths of this study include the detailed assessment of muscle composition (muscle volume and fat infiltration) with MRI and the use of quantitative muscle biomarkers with strong associations to functional performance and outcomes. The use of a highly standardized image acquisition protocol and systematic quality control procedures for muscle composition quantification enabled comparison between the study participants and virtual controls assessed in UK Biobank thus increasing the study size and enabling body size-independent sarcopenia assessment. The study has some limitations, including relatively low sample size and gender bias (only 2/11 of participants were women). A larger-scale study is needed to confirm our results.