Sarcopenia, unhealthy lifestyle, and vitamin D

Abstract

Observational studies have associated vitamin D deficiency with sarcopenia and lifestyle; however, the causal link between them remains unclear. This study aimed to evaluate the causal relationship between 25-hydroxyvitamin D (25(OH)D) and sarcopenia and unhealthy lifestyle using Mendelian randomization (MR). We extracted pooled data on 25(OH)D from a genome-wide association study conducted on individuals of European ancestry. Sarcopenia outcomes were assessed using appendicular lean mass, low handgrip strength, and usual walking pace. Unhealthy lifestyle outcomes were assessed using able to walk or cycle unaided for 10 minutes, moderate-to-vigorous intensity physical activity during leisure time, waist–hip ratio, alcohol consumption, and never smoked. A 2-sample MR approach was employed in this study, utilizing the inverse-variance weighted (IVW) method and the MR-Egger method as the primary research method. Heterogeneity and horizontal pleiotropy analyses were performed to ensure the stability of the candidate single-nucleotide polymorphisms as instrumental variables. The study found that a higher 25(OH)D level was associated with an increased appendicular lean mass (IVW: Beta 0.03, 95% confidence interval: 0.01–0.06, P = .011). However, this study did not provide evidence of a causal relationship between 25(OH)D levels and other muscle traits. For unhealthy lifestyle, MR-Egger analysis suggests that increased levels of 25(OH)D increase the probability of never smoked (odds ratio 1.08, 95% confidence interval: 1.03–1.11, P = .015). In addition, the study detected no pleiotropy (all P > .05), except for low hand grip strengthEuropean Working Group on Sarcopenia in Older People 2 (IVW: Q = 24.141, P = .019; MR-Egger: Q = 23.908, P = .013). This study confirms a causal relationship between 25(OH)D, sarcopenia, and smoking.

1. Introduction

Vitamin D plays a crucial role in regulating calcium balance and bone metabolism; Nevertheless, emerging research reveals that this vitamin exerts extensive functions in diverse tissues, skeletal muscle included.^[1] Vitamin D functions not only as a nutrient but also as a prohormone, mainly sourced from ultraviolet B rays in sunlight, and receptors for vitamin D are present in most principal organs and body tissues.^[2] Increasing evidence suggests that insufficient vitamin D levels may be a risk factor for multiple adverse health outcomes.^[3] For example, recent studies have found that low vitamin D levels are associated with an increased risk of mortality from multiple diseases.^[4] Decades of observational research have established a connection among vitamin D deficiency, compromised skeletal muscle health, and unhealthy lifestyles.^[5–7] Given the critical role vitamin D plays in human health and the numerous adverse effects of its deficiency, particularly the risk it poses to skeletal muscle health in the elderly, we urgently need to raise awareness of the importance of vitamin D.

Sarcopenia refers to a syndrome defined by age-associated loss of skeletal muscle mass, which is further accompanied by diminished muscle strength and impaired physical performance.^[8] The age-related decline in muscle strength and functional capacity gives rise to numerous negative health consequences, including a higher risk of falls, bone fractures, frailty, functional disability, and elevated mortality rates.^[9] Notably, sarcopenia is predictable and can be partially reversed or prevented through targeted measures. Therefore, identifying and implementing appropriate intervention strategies to relieve sarcopenia is of great significance. Observational studies have shown a complex relationship between lifestyle factors, sarcopenia, and vitamin D. It is important to emphasize that the findings of observational studies are often influenced by confounding variables and reverse causality – both of which may distort the accuracy of conclusions. For this reason, further research is required to clarify the causal relationships between muscle traits, lifestyle factors (e.g., tobacco use, alcohol intake, physical exercise, and sedentary behavior), and vitamin D. To address this research gap, researchers designed and conducted randomized controlled trials (RCTs) aimed at clarifying these causal relationships. However, clinical trial results regarding the effects of vitamin D supplementation on sarcopenia have been inconsistent.^[6] Furthermore, RCTs typically require substantial financial and human resources; in certain circumstances, specific interventions may be difficult to implement or may not obtain evaluation approval within the framework of a RCTs.

Additional evidence can be obtained by employing Mendelian randomization (MR) research methods. As an effective strategy, MR utilizes genetic variation as instrumental variables (IVs) to infer causality – this design can mitigate the confounding bias inherent in traditional studies to a certain extent.^[10] Unlike retrospective observational studies, MR studies do not need to worry about reverse causality issues when genetic tools are appropriately selected. The rationale lies in the fact that an individual’s germline genotype is determined before any potential outcome occurs. Essentially, MR mimics the design of RCTs, thereby providing stronger evidence to support causality. In contrast, traditional meta-analyses typically rely on pooled observational data, primarily identifying patterns of association rather than establishing definitive causation. MR also serves as an alternative approach to effectively leverage existing genome-wide association study (GWAS) findings: by treating genetic variation as an instrumental variable, it precisely pinpoints causal links between risk factors and disease, significantly reducing causal estimation bias and enhancing the validity of causal inference.^[11]

Therefore, this study aimed to investigate the causal relationship between genetically determined vitamin D levels and the risk of sarcopenia and unhealthy lifestyles using MR. This research promises to provide innovative strategies for the prevention and management of sarcopenia and unhealthy lifestyles. It helps improve public health, particularly enhancing the quality of life for the elderly.

2. Methods

2.1. Study design

This study employed a 2-sample MR design, as illustrated in Figure 1. The study comprised 5 key steps: identifying genetic variants that serve as instrumental variables for 25-hydroxyvitamin D (25(OH)D) levels; obtaining outcome summary data (SNPs) from genome-wide association studies of sarcopenia and unhealthy lifestyle; harmonizing exposure and outcome datasets; performing MR analysis; and evaluating the assumptions of the MR analysis and conducting sensitivity analyses.

Figure 1.

Overview of MR analyses process and major assumptions. Assumotion1: the assumption of association stipulates that the IV is significantly correlated with the exposure factors; Assumotion2: the assumption of independence requires that the IV is not associated with any known confounders; Assumotion3: the assumption of exclusivity asserts that the IV influences the outcome solely through the exposure factors. 25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, AWCU10 = able to walk or cycle unaided for 10 minutes, IVs = instrumental variables, IVW = inverse variance weighting, MR = Mendelian randomization, LD = linkage disequilibrium, MVPA = moderate-to-vigorous intensity physical activity during leisure time, SNPs = single nucleotide polymorphisms.

To make SNPs effective IV, 3 key assumptions must be satisfied: the association assumption requires a significant correlation between the IV and the exposure factor; the independence assumption requires the IV to be unrelated to any known confounding factors; the exclusivity assumption requires the IV to influence the outcome variable solely through the exposure factor. Additionally, we reported our findings in accordance with the MR-Strengthening the Reporting of Observational Studies in Epidemiology guidelines.^[12] All analyses were based on previous published studies, thus no ethical approval and patient consent are required.

2.2. Exposures

Serum 25(OH)D data were sourced from the publicly available dataset ebi-a-GCST90000621, which includes 318,851 samples from European pedigree samples and encompasses 6,098,063 SNPs.^[13] This extensive and heterogeneous dataset offers a valuable genetic background for evaluating the association of SNPs with 25(OH)D levels.

2.3. Outcomes

According to the definition of sarcopenia (ICD-10-CM: M62.84) proposed by the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), sarcopenia is diagnosed when an individual presents with low muscle mass (LMM) combined with low muscle strength and/or impaired physical performance. Notably, the presence of LMM is regarded as a prerequisite for confirming a sarcopenia diagnosis.^[14] Given that low muscle strength exhibits a stronger association with sarcopenia-related adverse outcomes than LMM, EWGSOP2 introduced the novel concept of “probable sarcopenia” and defined the isolated presence of low muscle strength as an indicator of probable sarcopenia.^[8] In contrast, severe sarcopenia is diagnosed when concurrent presence of low muscle strength, low muscle quantity/quality, and low physical performance is detected.^[8] In the present study, hand grip strength, recognized as a robust assessment metric, was employed as the parameter for evaluating muscle strength. appendicular lean mass (ALM; ebi-a-GCST90000025) was measured to assess muscle mass, while usual waking pace (ukb-b-4711) was used to evaluate physical performance. For the hand grip strength traits, 2 distinct definitions were applied to identify poor hand grip strength: the EWGSOP definition (males: <30 kg; females: <20 kg; ebi-a-GCST90007526) and the Foundation for the National Institutes of Health (FNIH) definition (males: <26 kg; females: <16 kg; ebi-a-GCST90007529).

In this study, lifestyle factors primarily encompass moderate-to-vigorous intensity physical activity during leisure time (MVPA), able to walk or cycle unaided for 10 minutes (AWCU10), never smoked, alcohol consumption, and Waist–hip ratio. Self-reported MVPA and AWCU10 data were obtained from the publicly available datasets ebi-a-GCST90104341 and ukb-b-14149, respectively. Following established methodologies, MVPA was calculated by combining moderate physical activity and vigorous physical activity^[15]; the corresponding dataset included 608,595 samples from individuals of European ancestry and encompassed 22,586,718 SNPs. The dataset for AWCU10 comprised 9851,867 SNPs, which were derived from 69,537 participants in the UK Biobank.^[16]

Data on never smoked, alcohol consumption, and waist–hip ratio were obtained from the publicly available datasets ukb-d-22506_114, ieu-a-1283, and ebi-a-GCST90029009, respectively. Specifically, these datasets included 91,353, 112,117, and 502,773 samples from individuals of European ancestry, and encompassed 13,567,196, 12,935,395, and 11,973,122 SNPs respectively. For the assessment of alcohol consumption, participants provided self-reported information via a questionnaire, including their current drinking status (never drank, ever drank, currently drinking, or declined to answer) and their weekly and monthly intake of different alcohol types (red wine, white wine, champagne, spirits, beer, beer/cream, and fortified wine). The average weekly alcohol intake (measured in standard units) was then calculated based on these self-reported responses.^[17] Detailed information on the databases included in this study, including GWAS ID, study population, and sample size is summarized in Table 1.

Table 1.

Characteristics of GWAS data in this study.

Trait	GWAS ID	Year	Population	Sample size	Number of SNPs
Exposure
25-hydroxyvitamin D level (25(OH)D)	ebi-a-GCST90000621	2020	European	318,851	6,098,063
Outcome
Appendicular lean mass (ALM)	ebi-a-GCST90000025	2020	European	450,243	18,071,518
Low hand grip strength (60 yr and older) (EWGSOP)	ebi-a-GCST90007526	2021	European	256,523	9336,415
Low hand grip strength (60 yr and older) (FNIH)	ebi-a-GCST90007529	2021	European	256,523	9354,214
Usual walking pace	ukb-b-4711	2018	European	459,915	9851,867
Able to walk or cycle unaided for 10 min (AWCU10)	ukb-b-14149	2018	European	69,537	9851,867
Moderate-to-vigorous intensity physical activity during leisure time (MVPA)	ebi-a-GCST90104341	2022	European	608,595	22,586,718
Waist–hip ratio	ebi-a-GCST90029009	2018	European	502,773	11,973,122
Alcohol consumption	ieu-a-1283	2017	European	112,117	12,935,395
Never smoked	ukb-d-22506_114	2018	European	91,353	13,567,196

EWGSOP = European Working Group on Sarcopenia in Older People 2, FNIH = Foundation for the National Institutes of Health, GWAS = genome-wide association study, SNPs = single nucleotide polymorphisms.

2.4. Selection of IV

To accurately investigate the causal relationship between 25(OH)D levels and sarcopenia-related traits as well as lifestyle factors, the selected IVs were required to satisfy the 3 aforementioned assumptions. When serum 25(OH)D was defined as the exposure variable and sarcopenia-related traits/lifestyle factors as the outcome variables, a genome-wide significance threshold of P < 5 × 10⁻⁸ was set. Additionally, the IVs were required to exhibit linkage disequilibrium with an r² < 0.001 and a genetic distance exceeding 10,000 kb. To reduce bias arising from weak IVs, an F statistic >10 was also mandated. This rigorous screening procedure is critical for minimizing false-positive results, thereby improving the reliability of the selected IVs. Prior to MR analysis, all selected SNPs were harmonized between the exposure and outcome datasets to ensure strand alignment and consistent effect direction.

2.5. MR analysis

In this 2-sample MR study, multiple analytical methods, including inverse-variance weighting (IVW), MR-Egger, weighted median, weighted mode, and simple mode, were employed to investigate whether a causal association exists between 25(OH)D and sarcopenia-related traits, as well as lifestyle factors. Among these methods, IVW was designated as the primary approach for MR analysis under the premise that no SNPs exhibited pleiotropy. The IVW method operates under the assumption that all genetic variants are valid IVs or that any violations of the exclusion restriction assumption are balanced. Specifically, it synthesizes the Wald ratio estimates for each individual SNP to derive a causal effect estimate for each risk factor and generates reliable estimates when no pleiotropy is present.

To evaluate the robustness of the study findings, heterogeneity tests and horizontal pleiotropy assessments were conducted. Specifically, Cochran Q test was used to detect heterogeneity among the IVs, with Q values and P values from both the IVW and MR-Egger methods serving as indicators of heterogeneity, with P < .05 signifying the presence of heterogeneity. Leave-one-out sensitivity analyses were also performed: individual IVs were excluded sequentially to determine whether any single SNP exerted a disproportionate influence on the results and whether substantial heterogeneity existed. In addition, funnel plots were employed as a supplementary measure to visually assess heterogeneity in this study. For significant MR effect estimates, the MR pleiotropy residual sum and outlier (MR-PRESSO) test was utilized to identify outliers and adjust for horizontal pleiotropy. If horizontal pleiotropy was detected among the IVs, outliers were removed, and the MR analysis was repeated. P < .05 was considered as statistically significant. All analyses, including heterogeneity and pleiotropy assessments, were performed using R software (version 4.4.2) and the TwoSampleMR package (R Foundation for Statistical Computing).

2.6. Software

MR analyses were conducted using the “TwoSampleMR” package version 0.6.8 in R software version 4.4.2. The MR analysis results were visualized using the R package “forestplot” version 3.1.6.

3. Results

3.1. MR analysis of 25(OH)D levels on traits of sarcopenia

In this study, we obtained 14 linkage disequilibrium-independent (r² < 0.001) IVs that reached genome-wide significance in 25(OH)D levels (P < 5 × 10⁻⁸), all 14 SNPs used as instruments for 25(OH)D had F statistics >10, with a mean F statistic of 172.43 (range: 32.96–1176.25) (Table S1, Supplemental Digital Content 1). A total of 13 SNPs were selected as IVs based on the predefined threshold criteria. Heterogeneity analysis using Cochran Q test showed no significant heterogeneity among IVs (P > .05, Table 2), except for low hand grip strength (EWGSOP) (IVW: Q = 24.141, P = .019; MR-Egger: Q = 23.908, P = .013, Table 2). MR-Egger regression intercept analysis showed no evidence of directional horizontal pleiotropy for all sarcopenia-related traits (all P > .05, Table 2). Consistent with these findings, the MR-PRESSO test also did not identify significant pleiotropy or outlier effects across these analyses (all P > .05, Table 2).

Table 2.

Heterogeneity tests and assessed horizontal pleiotropy in MR analysis.

Outcome	No SNP used in MR	MR-PRESSO P value	MR-Egger intercept P value	Cochran Q method	Q	P value
ALM	12	.678	.660	IVW	10.383	.410
				MR-Egger	10.349	.410
Low hand grip strength (EWGSOP)	13	.065	.749	IVW	24.141	.019
				MR-Egger	23.908	.013
Low hand grip strength (FNIH)	13	.504	.685	IVW	11.599	.478
				MR-Egger	11.419	.409
Usual walking pace	12	.178	.923	IVW	17.821	.086
				MR-Egger	17.803	.058
AWCU10	12	.779	.738	IVW	7.954	.717
				MR-Egger	7.836	.645
MVPA	13	.768	.424	IVW	6.694	.877
				MR-Egger	6.005	.873
Waist–hip ratio	9	.153	.436	IVW	14.056	.080
				MR-Egger	13.911	.053
Alcohol consumption	12	.701	.123	IVW	9.612	.566
				MR-Egger	6.780	.746
Never smoked	13	.182	.012	IVW	18.537	.100
				MR-Egger	9.488	.577

ALM = appendicular lean mass, AWCU10 = able to walk or cycle unaided for 10 minutes, EWGSOP = European Working Group on Sarcopenia in Older People 2, FDR = false discovery rate, FNIH = Foundation for the National Institutes of Health, IVW = inverse variance weighting, MR = Mendelian randomization, MR-PRESSO = MR pleiotropy residual sum and outlier MVPA = moderate-to-vigorous intensity physical activity during leisure time, SNPs = single nucleotide polymorphisms.

For the effect of 25(OH)D level on ALM, there was a statistically significant correlation between genetic susceptibility to 25(OH)D levels and ALM according to the IVW, weighted median methods and weighted mode (Beta 0.03, 95% confidence interval [CI]: 0.01–0.06, P = .011; Beta 0.06, 95% CI: 0.02–0.09, P = .003; Beta 0.06, 95% CI: 0.02–0.09, P = .009, Table 3, Fig. 2). The scatter plot showed that all MR analysis methods had the same direction of effect; the funnel plot was symmetrical, confirming that all outliers had been removed; and the leave-one-out plot indicated that the causal relationship between 25(OH)D level and ALM was robust and independent of a single SNP (Figs. 3–5).

Table 3.

Causal association between serum 25(OH)D levels with sarcopenia, and lifestyle in MR analysis.

Outcome	Outcome GWAS no SNP	No SNP used in MR	Method	Beta/OR	SE (95% CI)	P value	FDR_q
ALM	14	12	MR-Egger	0.0363	0.0224	.136	0.3294
			Weighted median	0.0560	0.0186	.003	0.0270
			Inverse-variance weighted	0.0330	0.0130	.011	0.0990
			Simple mode	0.0687	0.0319	.054	0.3420
			Weighted mode	0.0569	0.0180	.009	0.0810
Low hand grip strength (EWGSOP)	14	13	MR-Egger	0.1362	0.1324	.326	0.4890
			Weighted median	0.0752	0.0654	.250	0.3105
			Inverse-variance weighted	0.1011	0.0749	.177	0.2391
			Simple mode	−0.0602	0.1241	.636	0.6700
			Weighted mode	0.0636	0.0634	.335	0.4118
Low hand grip strength (FNIH)	14	13	MR-Egger	0.1887	0.1329	.183	0.3294
			Weighted median	0.1794	0.0963	.063	0.2520
			Inverse-variance weighted	0.1439	0.0766	.060	0.2391
			Simple mode	0.3261	0.1678	.076	0.3420
			Weighted mode	0.1986	0.0931	.054	0.2430
Usual walking pace	13	12	MR-Egger	0.0161	0.0250	.533	0.6086
			Weighted median	0.0221	0.0134	.099	0.2520
			Inverse-variance weighted	0.0181	0.0137	.186	0.2391
			Simple mode	−0.0126	0.0262	.640	0.6700
			Weighted mode	0.0200	0.0135	.167	0.3750
AWCU10	13	12	MR-Egger	−0.0196	0.0311	.541	0.6086
			Weighted median	−0.0301	0.0219	.168	0.2520
			Inverse-variance weighted	−0.0284	0.0179	.112	0.2391
			Simple mode	−0.0239	0.0480	.628	0.6700
			Weighted mode	−0.0307	0.0253	.250	0.3750
MVPA	14	13	MR-Egger	0.9327	0.8516–1.0215	.162	0.3294
			Weighted median	0.9517	0.8887–1.0193	.157	0.2520
			Inverse-variance weighted	0.9617	0.9103–1.0162	.165	0.2391
			Simple mode	0.9363	0.8370–1.0475	.273	0.6700
			Weighted mode	0.9467	0.8847–1.0130	.139	0.3750
Waist–hip ratio	13	9	MR-Egger	−0.0363	0.1062	.743	0.7430
			Weighted median	−0.0609	0.0398	.126	0.2520
			Inverse-variance weighted	−0.0628	0.0389	.107	0.2391
			Simple mode	−0.0371	0.0628	.571	0.6700
			Weighted mode	−0.0337	0.0498	.518	0.5180
Alcohol consumption	13	12	MR-Egger	0.0542	0.0327	.129	0.3294
			Weighted median	0.0187	0.0229	.411	0.4110
			Inverse-variance weighted	0.0083	0.0182	.648	0.6480
			Simple mode	0.0144	0.0329	.670	0.6700
			Weighted mode	0.0206	0.0218	.366	0.4118
Never smoked	14	13	MR-Egger	1.0796	1.0250–1.1372	.015	0.1350
			Weighted median	1.0234	0.9817–1.0669	.276	0.3105
			Inverse-variance weighted	1.0122	0.9745–1.0514	.530	0.5963
			Simple mode	1.0151	0.9557–1.0781	.636	0.6700
			Weighted mode	1.0248	0.9871–1.0639	.225	0.3750

Bold values represent statistically significant results (P < .05).

25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, AWCU10 = able to walk or cycle unaided for 10 minutes, CI = confidence interval, EWGSOP = European Working Group on Sarcopenia in Older People 2, FDR = false discovery rate, FNIH = Foundation for the National Institutes of Health, GWAS = genome-wide association study, MR = Mendelian randomization, MVPA = moderate-to-vigorous intensity physical activity during leisure time, OR = odds ratio, SE = standard error, SNPs = single nucleotide polymorphisms.

Figure 2.

The MR results between serum 25(OH)D levels with ALM, low hand grip strength (60 years and older) (EWGSOP), Low hand grip strength (60 years and older) (FNIH), Usual walking pace, MVPA, waist–hip ratio, and alcohol consumption. 25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, CI = confidence interval, EWGSOP = European Working Group on Sarcopenia in Older People 2, FNIH = Foundation for the National Institutes of Health, MR = Mendelian randomization, MVPA = moderate-to-vigorous intensity physical activity during leisure time, SNPs = single nucleotide polymorphisms.

Figure 3.

The MR analysis scatter plot for the assessment of the causal relationship between serum 25(OH) D levels and ALM. Five methods including inverse-variance weighting, MR-Egger, simple mode, weighted median and weighted mode were used in MR analyses. 25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, MR = Mendelian randomization, SNPs = single nucleotide polymorphisms.

Figure 5.

Funnel plot of the causal relationships between serum 25(OH)D levels and ALM. 25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, IV = instrumental variable, MR = Mendelian randomization, SE = standard error.

Figure 4.

Leave-one-out sensitivity analysis of the causal association between serum 25(OH)D levels and ALM (each row represents the IVW-derived causal effect estimate after sequentially excluding the corresponding SNP; “All” indicates the causal effect estimate using all included SNPs). 25(OH)D = 25-hydroxyvitamin D, ALM = appendicular lean mass, IVW = inverse variance weighting, MR = Mendelian randomization, SNPs = single nucleotide polymorphisms.

Regarding the effect of 25(OH)D levels on low hand grip strength and usual walking pace, the P values of all 5 methods were >0.05. The 95% CIs for the Beta included 0.000, indicating that there is no genetic association between serum 25(OH)D levels and low grip strength and usual walking speed (Fig. 2). Of note, the weighted mode estimate for low hand grip strength showed a borderline P value of .054. Although this value is close to the conventional threshold, the effect size was small and the 95% CI included the null value. Furthermore, all other MR methods (IVW, weighted median, MR-Egger, and simple mode) consistently yielded nonsignificant results, supporting the null causal conclusion. We acknowledge that limited statistical power may hinder detection of a weak causal effect rather than indicating a complete absence of association. The corroboration among the 5 methods strengthens the reliability and robustness of these findings.

3.2. MR analysis of 25(OH)D levels in unhealthy lifestyles

In terms of physical activity, this study found no evidence of a genetic association between 25(OH)D levels and physical activity, including AWCU10 and MVPA. Heterogeneity analysis using the Q test showed no significant heterogeneity for MR-Egger (Q = 7.836, P = .645; Q = 6.005, P = .873, Table 2) or IVW (Q = 7.954, P = .717; Q = 6.694, P = .877, Table 2). MR-Egger intercept analysis showed no significant directional pleiotropy, and MR-PRESSO tests similarly showed no evidence of pleiotropy or outlier effects (all P > .05, Table 2). These results suggest that there is no causal effect of genetic variation associated with 25(OH)D levels on physical activity.

The MR study found a statistically significant association between genetic susceptibility to 25(OH)D levels and never smoked based on the MR-Egger method (odds ratio = 1.08, 95% CI: 1.03–1.11, P = .015, Table 3, Fig. 6). It revealed that a 1-standard-deviation increase in quantile-normalized 25(OH)D level could elevate the probability of never smoked by 8%. Heterogeneity analysis using the Q test showed no significant heterogeneity for MR-Egger (Q = 9.488, P = .577, Table 2) or IVW (Q = 18.537, P = .100, Table 2). However, MR-Egger intercept analysis revealed evidence of directional horizontal pleiotropy (P = .012, Table 2). MR-PRESSO test did not identify significant pleiotropy or outlier effects for this outcome ((all P > .05, Table 2). This study found no evidence of a genetic association between 25(OH)D levels and waist–hip ratio and alcohol consumption.

Figure 6.

The MR results between serum 25(OH)D levels with AWCU10 and never smoked. 25(OH)D = 25-hydroxyvitamin D, AWCU10 = able to walk or cycle unaided for 10 minutes, CI = confidence interval, MR = Mendelian randomization, SNPs = single nucleotide polymorphisms.

4. Discussion

Vitamin D is a crucial component in the regulation of calcium homeostasis and bone metabolism; however, emerging research indicates that it plays diverse roles in other tissues,^[18–20] including skeletal muscle.^[1] In our study, the 2-sample MR analysis was used to investigate the causal association between 25(OH)D levels and sarcopenia-related traits, including ALM, usual walking pace, and grip strength diagnosed by the EWGSOP or FNIH criteria. We also examined the causal association between 25(OH)D levels and unhealthy lifestyle factors, including MVPA, AWCU10, never smoked, alcohol consumption, and waist–hip ratio. According to our analysis, we revealed significant causal links between 25(OH)D and sarcopenia and gene expression. Our primary MR analysis suggested a potential protective effect of 25(OH)D levels on ALM (IVW: Beta = 0.03, 95% CI: 0.01–0.06, P = .011). However, we found no causal association between 25(OH)D levels and usual walking pace or grip strength, regardless of whether the EWGSOP or FNIH diagnostic criteria were used. For unhealthy lifestyle factors, MR-Egger analysis indicated that higher 25(OH)D levels were associated with an increased likelihood of never smoked (odds ratio = 1.08, 95% CI: 1.03–1.11, P = .015). No causal evidence was found linking 25(OH)D levels to MVPA, AWCU10, alcohol consumption, or waist–hip ratio.

The positive association between 25(OH)D and ALM found in our study is consistent with most prior research.^[21–23] Muscle aging may be linked to a decrease in the rate of energy production in muscle cells. At the preclinical level, Bischoff-Ferrari et al reported that reduced expression of the vitamin D receptor (VDR) in muscle cells is directly associated with age-related loss of muscle mass and function.^[24] In vitro studies of muscle cells have identified the active form of vitamin D, 1,25-dihydroxyvitamin D (1,25(OH)₂D), as a key regulator of muscle mitochondrial activit, specifically, 1,25(OH)₂D signaling promotes mitochondrial biogenesis and enhances oxidative phosphorylation, which are critical for sustaining myofiber integrity and lean mass.^[25,26] However, Takafumi et al noted that vitamin D-VDR signaling has minimal impact on regulating muscle mass in mature myofibers but significantly influences muscle strength.^[27] This apparent discrepancy may explain why our study found a significant association between 25(OH)D and ALM, but not with grip strength or usual walking pace. The genetic architecture of muscle mass and strength may differ, with ALM being more directly modulated by VDR-mediated metabolic pathways. Future studies could investigate whether vitamin D supplementation preserves muscle mass by maintaining mitochondrial function in older adults, and whether such effects translate to improvements in muscle strength and physical performance.

Beyond its canonical role in bone formation, accumulating studies have highlighted the nontraditional roles of vitamin D in various pathological conditions, including infections, neurodegenerative diseases, and metabolic disorders.^[28–34] Therefore, we further explored associations between 25(OH)D and modifiable lifestyle factors, including smoking and physical activity. Most epidemiological studies to date have focused on how smoking affects vitamin D levels, with inconsistent findings, some reported an association between tobacco exposure and reduced vitamin D status,^[35–40] while others found no evidence of such a link.^[41] Unlike prior observational studies, which are limited by reverse causation and confounding, our MR analysis identified a potential causal association between higher 25(OH)D levels and never smoking status. However, this finding should be interpreted with caution, as statistical significance was only observed in the MR-Egger analysis, and not in the primary IVW or weighted median methods. MR-Egger is more sensitive to pleiotropy but has lower statistical power compared to other methods, which means this result may be influenced by residual pleiotropic effects or low power rather than a true causal relationship. The mechanisms underlying this potential association remain unclear, and the lack of consistency across MR methods limits strong conclusions. Future research should aim to replicate this finding in larger, multi-ancestry cohorts with well-powered analyses and explore potential biological pathways, such as whether vitamin D signaling influences smoking-related behaviors or metabolic responses to nicotine.

Observational studies have reported positive correlations between vitamin D levels and physical activity, including MVPA.^[42–44] This association can be partially explained by the storage of vitamin D in muscle tissue.^[45] However, our MR study failed to confirm a causal relationship between them. The different results from observational studies and MR analysis are mainly caused by various interfering factors in traditional population research. People who exercise more tend to spend more time outdoors, leading to greater sun exposure and higher vitamin D synthesis, while sedentary behavior is often linked to indoor lifestyles and lower vitamin D status. Additionally, vitamin D levels are influenced by age, sex, season, latitude, diet, sunscreen use, and lifestyle factors (e.g., exercise, smoking, and alcohol consumption), introducing multiple confounders in epidemiological studies and underscoring the need for research beyond observational designs.^[46–49] Therefore the correlation seen in observational studies is primarily driven by confounding factors rather than a direct causal effect. Similarly, prior MR studies have reported inverse causal relationships between waist circumference, body mass index, and 25 (OH) D levels.^[50,51] In contrast, our study found no significant causal association between 25(OH)D and waist–hip ratio. These results align with a recent meta-analysis of randomized controlled trials in postmenopausal women, which found no significant impact of vitamin D supplementation on body mass index, weight, or waist circumference.^[52] This discrepancy may reflect differences in study design, population characteristics, or instrument selection, highlighting the complex and multifactorial nature of the relationship between vitamin D and metabolic traits.

4.1. Strengths, limitations, and implications

A unique core strength of this study lies in its innovative application of the MR genetic analysis framework, which enables the safe investigation of the effects of increasing 25(OH)D levels in populations with very low baseline levels. Compared with RCTs, the MR design avoids active interventions, drastically reducing time/economic costs and ethical risks while ensuring high feasibility. Furthermore, the UK Biobank provides exclusive high-quality data, which includes measured serum 25(OH)D levels and genome-wide genotyping data from 318,851 participants, which provides a sufficient basis for analyzing both traits of sarcopenia and unhealthy lifestyle. While the extent to which the sarcopenia measurements used in this study serve as determinants for clinical diagnosis in the evaluated population remains unclear, the EWGSOP endorses the use of ALM thresholds as a clinical screening tool,^[8] and subsequent research has validated the relevance of these thresholds for public health.^[53]

Several critical limitations of this study must be fully acknowledged and objectively discussed. First, we tested multiple phenotypic outcomes in this study without formal multiple testing correction. All nominally significant results should be interpreted prudently to avoid overinterpretation of potential false positive findings. Second, several outcomes presented borderline statistical values near the conventional significance threshold. Specifically the weighted median result of grip strength yielded a P value of .054. This borderline non significant result cannot completely rule out potential type II errors caused by limited statistical power and insufficient sample size rather than a total absence of causal effect. Third, partial sample overlap exists between exposure and outcome GWAS datasets, which may introduce bias into the analyses. Specifically, such overlap can violate the independence assumption of 2-sample MR, leading to inflated type I error rates, especially in the presence of weak instruments. To mitigate this risk, we selected only genetic instruments with strong statistical power (all F statistics >10, with a mean of 172.43), which helps reduce the potential for weak instrument bias to be amplified by sample overlap. While we prioritized the largest publicly available GWAS datasets to maximize statistical power, the impact of sample overlap on causal estimates cannot be fully excluded. Fourth, all participants included in the original GWAS datasets were restricted to European ancestry populations. This single ethnic limitation greatly reduces the generalizability of our research conclusions and prevents direct extension to other ethnic groups. Additionally, the UK Biobank has a response rate of only 5%, meaning it does not fully represent the general population of the United Kingdom.^[54] Nevertheless, previous studies utilizing the UK Biobank have successfully replicated expected exposure-disease associations,^[54] a further, the MR approach is less susceptible to selection bias compared with other types of observational studies – these factors suggest that the limited representativeness of the UK Biobank had a minimal impact on our results.^[55] Consistent with all MR analyses, the genetic instruments employed in this study capture the average effect of exposure (i.e., serum 25(OH)D levels) over the entire life course. While muscle degeneration is a long-term, progressive process, this characteristic of MR analyses aligns with the temporal nature of muscle-related outcomes, thereby retaining the method’s inherent advantages.

This study has several implications for the prevention and intervention of sarcopenia in older adults. First, it is recommended that older adults be screened for vitamin D levels and assessed for ALM levels simultaneously. Second, vitamin D supplementation helps reduce the risk of sarcopenia in physically inactive or physically limited individuals, though optimal dosing requires further exploration. Third, The causal link between higher 25(OH)D and nonsmoking status suggests that vitamin D-deficient patients (particularly those with a smoking history) should undergo enhanced screening for smoking-related comorbidities, such as chronic obstructive pulmonary disease, coronary heart disease, and lung cancer.

5. Conclusion

In conclusion, our study supports a causal association between 25(OH)D and sarcopenia and smoking. The potential association between vitamin D and smoking status lacks statistical robustness due to method inconsistency and pleiotropic interference. Future research should conduct preclinical studies to clarify 25(OH)D’s mechanism in muscle (e.g., 25(OH)D-ALM vs grip strength discrepancy). Notably, the exclusive reliance on European ancestry GWAS data severely limits the generalizability of our findings, and future multi ethnic MR analyses are urgently required to validate these conclusions in diverse populations.

Acknowledgments

We acknowledge the participants and investigators of the IEU Open GWAS project, UK Biobank and GWAS Catalog.

Author contributions

Conceptualization: Xuan Zhou, Biao Li.

Data curation: Xuan Zhou, Biao Li, Xue Wang.

Formal analysis: Xuan Zhou, Bin Xu.

Investigation: Xuan Zhou, Zihui Han.

Methodology: Xuan Zhou, Zihui Han, Ruijuan Zhuang.

Supervision: Hengchao Ge, Ya Zhu, Ruijuan Zhuang.

Visualization: Quanpeng Wang, Chengxiu Zhu.

Writing – original draft: Xuan Zhou, Biao Li.

Writing – review & editing: Zhenyong Zhang, Ruijuan Zhuang.