Comparative analysis of the association between various serum vitamin D biomarkers and sarcopenia

Abstract Background Vitamin D status is associated with muscle strength and maintenance of muscle fibers. However, which serum vitamin D biomarker better reflects sarcopenia remains unclear. The aim of this study was to investigate associations between various serum vitamin D biomarkers (total 25‐hydroxy vitamin D [25(OH)D], bioavailable 25(OH)D, 24,25‐dihydroxyvitamin D [24,25(OH)2D], and vitamin D metabolite ratio [VMR]) and sarcopenia. Methods The data for 83 hip fracture patients were finally included in the analysis. Sarcopenia was defined according to the Asia Working Group for Sarcopenia (AWGS) criteria. Measurements of 24,25(OH)2D and 25(OH)D were made using solid‐phase extraction (SPE) and subsequent liquid chromatography‐tandem mass spectrometry (LC‐MS/MS). Vitamin D binding protein (VDBP) concentration was measured using an enzyme‐linked immunosorbent assay. The VMR was calculated by dividing serum 24,25(OH)2D by serum 25(OH)D and then multiplying by 100. Based on total 25(OH)D, VDBP, and albumin concentrations, bioavailable 25(OH)D concentrations were calculated using the equations from the other previous studies. Results Bioavailable 25(OH)D levels were significantly (p = 0.030) decreased in the sarcopenia group compared with the non‐sarcopenia group. Results of ROC analysis for the diagnosis of sarcopenia using serum level of bioavailable of 25(OH)D revealed that the cutoff point for bioavailable 25(OH)D was 1.70 ng/ml (AUC = 0.649, p < 0.001). In the group with a bioavailable 25(OH)D less than 1.70 ng/ml, the incidence of sarcopenia increased by 3.3 times (odds ratio: 3.33, p = 0.013). Conclusion We demonstrated that bioavailable 25(OH)D was associated with sarcopenia among the various serum vitamin D biomarkers. Bioavailable vitamin D might be helpful for assessing the risk of sarcopenia.


| INTRODUC TI ON
Vitamin D is mainly synthesized in the skin of people exposed to sunlight, and some can also be obtained from the diet. Vitamin D needs a two-step hydroxylation (25-hydroxylation and 1αhydroxylation) to be in its biologically active form. The first hydroxylation, 25- It is well known that vitamin D primarily plays a critical role in the regulation of calcium homeostasis. Skeletal muscles may require vitamin D and calcium for normal development and maintenance of function. It was previously reported that vitamin D deficiency and inactivating mutations in vitamin D receptor (VDR) are associated with muscle weakness in humans and mouse models. [3][4][5] Sarcopenia is an age-related clinical condition characterized by a gradual and generalized loss of skeletal muscle mass with a decrease in strength and physical capacity. 6 It is considered to be one of the risk factors for adverse events in older people, including delirium, disability, institutionalization, and even death. 78 Nowadays, there is an increasing trend in the prevalence of sarcopenia, which is probably related to an increase in human life expectancy. 9 Vitamin D deficiency is common among older people around the world. Older people are particularly prone to the development of vitamin D insufficiency or deficiency for following reasons: a reduced cutaneous synthesis in the skin, decreased daily sun exposure, and chronic diseases of organs related to vitamin D metabolism. [9][10][11] Many prospective studies have examined the role of vitamin D in muscle strength and physical performance of older adults. [12][13][14] Roles of vitamin D and VDR in muscles have been well described in numerous studies and reviews. 4,15,16 Several vitamin D biomarkers have been suggested for evaluating vitamin D status in the body. Commonly, vitamin D status is assessed by one measurement of serum 25(OH)D concentration.
Generally used criteria for the evaluation of vitamin D status are as follows: vitamin D deficiency, <20 ng/ml; vitamin D insufficiency, 20-30 ng/ml; and vitamin D sufficiency, >30 ng/ml. 2, 17,18 However, some recent studies have suggested that 25(OH)D alone may not reflect accurate vitamin D status. 19 conditions. VDBP is increased under hyper-estrogen state such as pregnancy, whereas it is decreased in certain disease states including severe hepatic disease. [23][24][25][26] The GC gene encodes VDBP and two single nucleotide polymorphisms (SNPs), rs7041 and rs4588, generating three major polymorphic isoforms of VDBP: Gc1f, Gc1s, and Gc2. 27,28 Since the affinity of VDBP for vitamin D is isoformdependent, the GC genotype plays an important role in determining serum bioavailable 25(OH)D levels. 25,26,28 24,25(OH) 2 D is the major product of catabolism of 25(OH) D. Because enzymatic synthesis of 24,25(OH) 2 D is directly proportional to the concentration of 25(OH)D substrate, concentrations of both metabolites in circulation are strongly correlated. 29 Furthermore, expression of 24-hydroxylase enzyme (CYP24A1) that converts 25(OH)D to 24,25(OH) 2 D is regulated in part by vitamin D receptor activity. 30,31 Since the production of 24,25(OH) 2 D is reg- have also suggested that the adequacy of vitamin D may be reflected by VMR. 22,33 This ratio also depend primarily on CYP24A1 expression, which is downregulated in vitamin D deficiency. Therefore, VMR could also be an alternative indicator that accurately reflects vitamin D status.
It is well known that vitamin D status is associated with muscle strength and maintenance of muscle fibers. However, which serum vitamin D biomarker better reflects sarcopenia remains unclear.
Therefore, the objective of the present study was to investigate the relationship between various vitamin D biomarkers including 25(OH)D, bioavailable vitamin D, 24,25(OH) 2 D, and VMR through patients with sarcopenia control study in order to elucidate which biomarkers may better reflect sarcopenia.

| Diagnosis of sarcopenia
Body composition was measured using a whole-body dual X-ray absorptiometry (DEXA), for which a QDR 4500A apparatus (Hologic) was employed. Bone mineral content, fat mass, and lean soft tissue mass were measured separately for each part of the body, including arms and legs. Lean soft tissue masses of arms and legs were almost equal to skeletal muscle mass. Absolute muscle mass is known to correlate with height. Thus, skeletal muscle mass index (SMI) was calculated with the following formula: lean mass (kg)/ height 2 (m 2 ), which was directly analogous to body mass index (BMI:

| VDBP assay and GC genotyping
Vitamin D binding protein concentration was measured using an enzyme-linked immunosorbent assay (ELISA) kit (R&D Systems) according to the manufacturer's protocol.
For GC gene genotyping, genomic DNA was isolated from peripheral blood leukocytes using a DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer's instructions. GC genotyping for rs7041 (c.1296T > G; p. Asp432Glu) and rs4588 (c.1307C > A; p. Thr436Lys) was performed using a TaqMan SNP Genotyping Assay (Thermo Fisher Scientific) and an ABI ViiA 7 Real-Time PCR System (Applied Biosystems) according to each manufacturer's instructions and described in the previous study. 35

| Calculation of VMR and bioavailable 25(OH)D concentration
Vitamin D metabolite ratio was calculated by dividing serum

| Statistical analysis
The sample size was calculated to be 66 considering an expected sensitivity of 90%, an expected specificity of 50%, a disease prevalence of 35%, an acceptable precision of 15%, and a significance F I G U R E 1 Flow diagram of patients involved in the study level of 0.05. Finally, we decided to recruit more than 83 subjects, considering a dropout rate of 20%. 37 To compare means and proportions of each group, Student's t test and chi-squared (χ2) test were employed. The Pearson correlation test was used for correlation analysis. A receiver operating characteristic (ROC) curve analysis was also performed to identify the cutoff value for diagnosis of sarcopenia using bioavailable 25(OH) D. All statistical tests were two-tailed. Statistical significance was defined at p < 0.05. All statistical calculations were performed using SPSS Statistics V.22 (SPSS Inc.) and software R (v 3.1.0; The R 100 Foundation). However, parathyroid hormone (PTH) was significantly higher in the non-sarcopenia group than in the sarcopenia group (p = 0.015).

| Demographic characteristics and laboratory test results
Demographic characteristics and laboratory test results of patients are shown in Table 1.

| Comparison of serum vitamin D biomarkers by the presence of sarcopenia
Bioavailable 25(OH)D levels were significantly (p = 0.030) decreased in the sarcopenia group than in the non-sarcopenia group ( Table 2). Levels of 24,25(OH) 2 D were decreased with marginally significance (p = 0.087) in the sarcopenia group than in the non-sarcopenia group.

| Correlation analysis of variables associated with sarcopenia
Correlation analysis was performed with indicators related to sarcopenia and various vitamin D biomarkers. Results are shown in

| DISCUSS ION
In  Note: Data were presented as mean ± standard deviation. Therefore, bioavailable 25(OH)D alone has limitations in diagnosing sarcopenia. However, it implies that it could be used as an auxiliary criterion to predict the risk of sarcopenia. However, it is difficult to draw a conclusive conclusion that is clinically useful based on findings of this study alone. More well-designed and large-scale studies will be required.
In the present study, VDBP concentration was 271.74 ± 88.52 µg/ ml (mean ± SD) for all subjects enrolled, which was significantly (p < 0.0001) higher than that in a previously reported VDBP concentration of 166.47 ± 36.36 µg/ml in healthy people. 35 VDBP is an acute-phase reactant. Its concentration is known to increase after trauma due to increases in cytokine and glucocorticoid. 45

ACK N OWLED G M ENTS
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

CO N FLI C T O F I NTE R E S T
The authors declare that this research is not related to any commercial or financial interests.

AUTH O R CO NTR I B UTI O N S
JIY and MCC contributed to the study planning. HJC, BGK, and YKJ performed the experiments. JIY, KWB, and MGS contributed to the inclusion of patients. JIY and MCC contributed to analysis and interpretation of the data. All authors contributed to writing the paper and approved the final version for publication.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable request.  TA B L E 3 GC genotype and allele frequencies