Genetic Association Between Attention-Deficit/Hyperactivity Disorder and Sarcopenia: A Bidirectional Two-Sample, Two-Step Mendelian Randomized Study

Article information

Psychiatry Investig. 2025;22(3):304-310

Publication date (electronic) : 2025 March 18

doi : https://doi.org/10.30773/pi.2024.0290

Xiaoyan Zhao ^,^*

, Yueqin Jin ^,^*

, Leping Ma

, Xiaole Zhao

, Xiaoqing Fang

, Fenfang Yuan

Shaoxing Keqiao Women and Children’s Hospital, Shaoxing, China

Correspondence: Xiaoyan Zhao, MM Shaoxing Keqiao Women and Children’s Hospital, Shaoxing 312030, China Tel: +86-0575-85028696, E-mail: zhaoxiaoyan1011@163.com

*These authors contributed equally to this work.

Received 2024 September 27; Revised 2024 December 14; Accepted 2025 January 27.

Abstract

Objective

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children and adolescents, often accompanied by motor function disorders. Sarcopenia not only has skeletal muscle dysfunction but also has neurocognitive dysfunction. At present, there is no research to explore the relationship between ADHD and skeletal muscle function. The purpose of this study is to explore whether there is a causal effect between ADHD and sarcopenia.

Methods

In this study, genome-wide association study data of ADHD, appendicular lean mass (ALM), hand grip strength, and walking pace (WP) were extracted from public databases. The bidirectional two-sample Mendelian randomization (MR) method was employed to investigate the correlation between ADHD and sarcopenia-related indicators, and the inverse-variance weighted analysis as the primary analysis method.

Results

Based on the forward MR analysis, a potential causal relationship exists between ADHD and ALM (odds ratio [OR]=1.020, 95% confidence interval [CI]: 1.012–1.029, p<0.001). The reverse MR analysis indicates a link between WP and the risk of ADHD (OR=2.712, 95% CI: 1.609–4.571, p<0.001), with an accelerated WP increasing the likelihood of ADHD. Nevertheless, other MR analysis results did not show significant differences.

Conclusion

The findings of this study indicate an intricate causal relationship between ADHD and sarcopenia, suggesting the absence of a clear link. WP may be used as one of the indicators to evaluate the risk of ADHD. At the same time, we should pay more attention to the ALM of ADHD patients.

Keywords: Mendelian randomization analysis; Attention deficit hyperactivity disorder; Sarcopenia; Skeletal muscle

INTRODUCTION

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, predominantly affecting males. Its main clinical features include frequent attention deficit and/or hyperactivity and impulsivity [1,2]. Increasing evidence suggests a link between ADHD and various physical health issues [3-6]. Some studies have pointed out that ADHD patients have certain motor function problems, which are often manifested as uncoordinated gait of lower limbs and motor function defects of upper limbs [7,8]. Skeletal muscle is an important endocrine organ, which can secrete interleukins, brain-derived neurotrophic factors, and so on, and has a close connection with the neural development of the brain and cognitive functions [9]. Therefore, it is crucial to monitor the condition of skeletal muscle in ADHD patients.

Sarcopenia is a progressive, systemic skeletal muscle disease, accompanied by a decrease in muscle mass and strength, often co-existing with several chronic diseases and indicating poor prognosis outcomes [10]. The exact pathogenesis of sarcopenia remains unclear. However, several studies have indicated potential links to dopaminergic dysfunction, reduced neural excitability, and the degradation of brain connectivity [11]. Furthermore, sarcopenia is also associated with cognitive impairments, including conditions such as Parkinson’s disease, depression, and various other neuropsychiatric disorders [12]. However, there is still uncertainty about the causal effect of sarcopenia on health status, which limits attempts to translate current knowledge about the pathophysiology of sarcopenia into clinical practice [13]. Currently, there is no research exploring whether there is a correlation or potential causal relationship between ADHD and sarcopenia, but based on the possible connection between these two diseases on the neural regulatory pathway, we attempt to explore the relationship between them.

Mendelian randomization (MR) is a reliable epidemiological analysis method that uses genetic variation as a risk factor to assess the causal relationship between two diseases. It identifies mutated genes from genome-wide association study (GWAS) that may lead to disease occurrence, serving as a causal tool for the occurrence of another disease [14]. According to Mendelian inheritance laws, genetic variations are randomly distributed and less influenced by confounding factors. This study employs a bidirectional two-sample MR method to investigate whether there is a causal relationship between ADHD and indicators of sarcopenia. The findings aim to provide a theoretical basis for the prediction and assessment of ADHD in clinical practice.

METHODS

Study design

MR is a specialized analysis based on genetic instrumental variables (IVs), which assesses the influence of risk factors on various outcomes by using single nucleotide polymorphisms (SNPs) as IVs [15]. In GWAS, SNPs associated with certain risk factors can be used as IVs to detect their causal effects on different outcomes. The selection of IVs involves three key assumptions: 1) the IV must be significantly associated with the exposure; 2) the IV cannot be associated with any known confounders that may alter the association between exposure and outcome; 3) the IV must be unrelated to the outcome, possibly only affecting it through its influence on the exposure.

This study employed pooled data from the GWAS Consortium to identify traits associated with sarcopenia [16], specifically appendicular lean mass (ALM), hand grip strength (HGS), and walking pace (WP), which were used as indicators for muscle mass, muscle strength, and physical performance, respectively. We conducted a bidirectional two-sample, two-step MR analysis to investigate the causal relationship and direction between ADHD and sarcopenia-related traits. This study was structured in two stages. First, we examined whether ADHD is causally linked to sarcopenia-related traits. In the second stage, we evaluated whether the characteristics related to sarcopenia are related to ADHD. Figure 1 provides a schematic illustration of our MR study. The study protocol was approved by the medical ethics committee of the Shaoxing Keqiao Women and Children’s Hospital (approval number: KFBCP NO.002 [2024]).

Figure 1.

Schematic diagram of Mendelian randomization study on ADHD and sarcopenia. ADHD, attention-deficit/hyperactivity disorder.

Data sources

We gathered the summary statistics of GWAS for ADHD from a large-scale study, which included 225,534 European participants (38,691 cases and 186,843 controls) [17], and identified 27 independent SNPs. We also obtained the GWAS summary statistics for ALM (n=450,243), HGS (left, n=461,089; right, n=461,026), and WP (n=459,915) from UKBiobank. Table 1 provides an overview of the data involved in this study. Our research constitutes a secondary analysis of publicly available data, seeking informed consent from all participants in accordance with the original GWAS protocol, and all ethical approvals for the GWAS were obtained by the original GWAS authors.

Table 1.

GWAS summarizes statistical data

Genetic instrument selection

The genetic tools are selected based on the following principles: 1) Setting p<5×10^-8 as the threshold for SNPs to achieve genome-wide significance, and linkage disequilibrium (LD) r2<0.001 (distance of aggregation=10,000 kb) as the cutoff value to determine whether SNPs are in LD [18]. 2) Excluding SNPs with significant relationships (p<5×10^-8) from the resulting database to avoid violating the third assumption above [19]. 3) Calculating the F statistic to evaluate the effectiveness of each SNP using the following formula: F=R²(N-K-1)/K(1-R²), where R² represents the exposure variance caused by genetic variance, K represents the number of SNPs, and N represents the sample size. The selection of SNPs is based on the commonly cited principle that the F statistic should be greater than 10 to prevent weak instrumental bias in MR analysis [20]. 4) Using the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) method to eliminate potential outliers [18]. 5) Eliminating palindromic SNPs by coordinating exposure data sets and result data sets [21,22]. After thorough screening, the remaining SNPs are used for subsequent analysis.

Statistical analysis

In this study, we used the Two Sample MR and MR-PRESSO packages in R software (version 4.2.3; R Foundation for Statistical Computing) to execute all MR and sensitivity analyses. A bidirectional two-sample MR analysis was employed to investigate the correlation between ADHD and sarcopenia-related traits. For binary outcomes, we estimated the MR as the odds ratio (OR) with 95% confidence intervals (CIs), while for continuous outcomes, we used the β coefficient of standard errors (SEs) as the OR of SEs.

We employed the MR-PRESSO test (10,000 repeated settings) to identify outliers and eliminate them, enabling a reassessment of the data [23]. We primarily utilized the random inverse-variance weighted (IVW) method for our analysis. To ensure consistent results, we employed MR Egger and the weighted median [19,24], conducted a range of sensitivity analyses—including Cochran’s Q test, MR-Egger intercept test, and leave-one-out analysis—to assess the reliability of our findings [19,24]. Cochran’s Q test was used to identify heterogeneity, while MR-Egger intercept test and leave-one-out analysis evaluated pleiotropy [19,24]. The delta method [25] was employed to calculate the SE and 95% CIs per standard deviation. The analysis flow is depicted in Supplementary Figure 1.

RESULTS

Using IVs for screening, we identified SNPs that are significantly associated with the exposure, and obtained their beta values, SEs, and p-values. We also found the corresponding values for these SNPs in the results database. The results of this MR study primarily rely on IVW analysis.

Causal effects of ADHD on sarcopenia-related traits

In the MR-PRESSO analysis, we adjusted for potential confounding factors and excluded outliers (Supplementary Table 1). In the IVW analysis, we observed a potential causal relationship between ADHD and ALM (OR=1.020, 95% CI: 1.012–1.029, p<0.001), with results that were consistent using the MR-Egger and weighted median methods. The Cochran’s Q test, MR-Egger intercept test, and leave-one-out analysis were used to assess the robustness and reliability of these findings. The MR-Egger intercept test indicated the absence of horizontal pleiotropy (p>0.05). The Cochran’s Q test p-value<0.05 suggested the detection of heterogeneity, which was considered acceptable considering we employed the random-effect IVW as our primary outcome [19]. The leave-one-out analysis confirmed that deleting a single SNP did not significantly affect the results. Furthermore, no significant positive causal relationship was identified between ADHD and either left or right HGS or WP (refer to Figure 2 for detailed MR analysis results).

Figure 2.

Positive MR analysis of ADHD and sarcopenia indicators. MR, Mendelian randomization; ADHD, attention-deficit/hyperactivity disorder; SNP, single nucleotide polymorphism; ALM, appendicular lean mass; IVW, inverse-variance weighted; HGS, hand grip strength; WP, walking pace; OR, odds ratio; CI, confidence interval.

Causal effects of sarcopenia-related traits on ADHD

We used MR-PRESSO analysis to correct for potential confounding factors and removed outliers (Supplementary Table 1). IVW analysis showed a potential causal relationship between the increase in WP and the heightened risk of ADHD onset (OR=2.712, 95% CI: 1.609–4.571, p<0.001). Every 1 m/s increase in WP increased the risk of ADHD by 271.2%. The results obtained using the weighted median method are similar, with MR Egger showing consistent and significant directions. Similarly, we conducted Cochran’s Q test, MR-Egger intercept test, and leave-one-out analysis to verify the reliability of the reverse MR analysis results. The p-value of Cochran’s Q test is less than 0.001, indicating the presence of certain heterogeneity. Due to the use of random effects IVW as the primary outcome, heterogeneity is acceptable [19]. The results of the MR-Egger intercept test were all p>0.05, indicating that no horizontal pleiotropy was detected. According to the leave-one-out analysis, excluding one SNP does not change the directionality of the results, in other words, removing any SNP will not have a significant impact on the results. There is no significant reverse causal relationship between ALM, left and right HGS, and ADHD (detailed results of MR analysis are shown in Figure 3).

Figure 3.

Reverse MR analysis of ADHD and sarcopenia indicators. MR, Mendelian randomization; ADHD, attention-deficit/hyperactivity disorder; SNP, single nucleotide polymorphism; ALM, appendicular lean mass; IVW, inverse-variance weighted; HGS, hand grip strength; WP, walking pace; OR, odds ratio; CI, confidence interval.

DISCUSSION

In this study, we attempted to establish the link between ADHD and sarcopenia. According to our positive MR analysis, there is a potential causal relationship between ADHD and ALM (OR=1.020, 95% CI: 1.012–1.029, p<0.001); the reverse MR analysis showed that the acceleration of WP significantly increased the risk of ADHD (OR=2.712, 95% CI: 1.609–4.571, p<0.001). However, the diagnosis of sarcopenia requires consideration of three evaluation indicators [16], and a single positive indicator cannot diagnose the patient. Therefore, based on the above, we believe that there is no significant causal relationship between sarcopenia and ADHD, but ALM and WP may be used as new indicators for screening and evaluating ADHD patients.

Our findings indicate that the onset of ADHD may lead to an increase in ALM, although some observational studies seem to contradict our results. Martins-Silva et al. [26] conducted a cohort study in a Brazilian population, selecting 5,249 newborns born in 1993 to assess ADHD symptoms and physical composition at the ages of 11, 15, 18, and 22 years old. The results showed that children with higher ADHD symptom scores at the age of 11 had lower percentages of fat-free mass (FFM) and higher percentages of fat mass (FM) at the ages of 18 and 22 years old. And this study conducted at the age of 22 found that the presence of ADHD symptoms at the age of 22 was associated with lower percentages of FFM. Percentages of FFM can reflect the percentage of muscle to some extent, and many studies currently use FFM indicators to replace it to assess muscle mass [27,28]. However, FFM, which equals body weight minus body FM, encompasses not only ALM but also the combined mass of other regions such as internal organs, bones, muscles in other parts, water, and connective tissue. Therefore, we believe that the decrease in FFM% in ADHD patients in previous studies may be affected by other confounding factors, and there is a certain bias in the evaluation of muscle quality. In this study, we have addressed the limitations of observational studies and established a causal relationship between ADHD and ALM using MR analysis. However, there is currently no relevant research that fully explores the connection mechanism between ADHD and ALM.

The results of this study suggest that increasing WP may lead to the onset of ADHD. Simmons et al. [29] reported in a study on gait control in children with ADHD that the ADHD group had faster WP when walking backward than the normal group, and the WP variability and step width of the ADHD group were significantly greater than those of the normal group. Papadopoulos et al. [30] tested the gait patterns of 14 children with ADHD and 13 children with normal development in a study, and the results showed that ADHD children had a tendency to increase WP. Our research findings seem to confirm this as well. In the study, it was also observed that children with ADHD have gait abnormalities, often using the “toe out” foot angle posture for walking [29]. This gait deformity is often caused by impaired posture control, which increases the support base to compensate for it. In order to maintain dynamic balance, the brain regulates it by connecting the neuromuscular system and related sensory systems, namely the somatosensory, vestibular, and visual systems [31]. Research has shown that ADHD patients often experience decreased sensory integration and impaired control abilities, which may be related to abnormalities in the posterior parietal cortex, temporal occipital cortex, and other areas of the brain [32]. We believe that an increase in WP, abnormal gait, and poor balance may indicate damage to the body’s sensory and neuromuscular systems, leading to an increased risk of ADHD. For the diagnosis and treatment of clinical ADHD patients, this may be a new signal that requires consideration of walking speed, stride, gait, etc., which may indirectly provide us with new clues about balance and sensory systems.

In addition, we believe that thyroid hormone may mediate the relationship between WP and ADHD through other pathways. Thyroid hormone has multiple physiological effects and is crucial for maintaining metabolism, adaptive thermogenesis, fat metabolism, growth and appetite, and neurological development [33]. Chen et al. [34] found a significant positive correlation between total triiodothyronine (TT3) and WP; the study by Albrecht et al. [35] reported a significant positive correlation between free triiodothyronine (FT3) levels and the severity of ADHD symptoms under continuous assessment. Although these are observational studies and the causal relationship is not yet clear, this may also suggest that increasing walking speed may induce the occurrence of ADHD at hormone levels, which is a new direction for our future efforts.

Our study has several advantages. First, MR analysis can effectively mitigate the impact of potential confounding factors, and MR studies are considered to be natural randomized controlled trial studies, which are more reliable than observational studies [22]; second, this study is limited to European populations, avoiding bias in population selection; third, our study conducted a two-way analysis, and the data sample was large enough to ensure the accuracy and reliability of the results, and this study is consistent with the current consensus on the diagnosis of sarcopenia in Europe and Asia [16,36].

Our research also has some limitations. Firstly, our study included all European populations, which may have overlooked the influence of bloodline, cultural background, and other factors on the results. Secondly, GWAS data lacks age and gender stratification, and our study cannot analyze the association between ADHD and sarcopenia in different subgroups in more detail, which may lead to bias. Third, due to the lack of research on the relationship between myopenia related indicators and ADHD, the mechanism of WP affecting the incidence rate of ADHD needs further research.

Conclusion

In summary, bidirectional dual sample MR studies have shown that the causal relationship between ADHD and sarcopenia is relatively complex, and there may be no potential causal relationship. WP might be used as one of the indicators to evaluate the risk of ADHD. At the same time, we should pay more attention to the ALM of ADHD patients. Future research based on larger GWAS or age stratified MR studies is needed to validate these findings.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0290.

Supplementary Table 1.

The results of MR-PRESSO test in this study

pi-2024-0290-Supplementary-Table-1.pdf

Supplementary Figure 1.

MR analysis flowchart. ADHD, attention-deficit/hyperactivity disorder; SNP, single nucleotide polymorphism; GWAS, genome-wide association study; MR-PRESSO, Mendelian Randomization Pleiotropy RESidual Sum and Outlier; MR, Mendelian randomization.

pi-2024-0290-Supplementary-Fig-1.pdf

Notes

Availability of Data and Material

The data that support the findings of this study are openly available in https://gwas.mrcieu.ac.uk/.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Xiaoyan Zhao, Yueqin Jin, Leping Ma, Xiaoqing Fang. Data curation: Yueqin Jin. Formal analysis: Xiaoyan Zhao, Leping Ma. Investigation: Yueqin Jin, Leping Ma. Methodology: Xiaoyan Zhao. Project administration: Fenfang Yuan. Resources: Xiaole Zhao. Supervision: Yueqin Jin, Xiaoqing Fang. Validation: Xiaole Zhao. Visualization: Leping Ma. Writing—original draft: Xiaoyan Zhao, Yueqin Jin. Writing—review & editing: Xiaoyan Zhao, Yueqin Jin.

Funding Statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Acknowledgements

None

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Phenotype	Races	Sizes of sample	Year	Consortium	GWAS ID/PMID
ADHD	European	38,691	2022	iPSYCH+deCODE+PGC data	36702997
Appendicular lean mass	European	450,243	2020	UK Biobank	ebi-a-GCST90000025
Hand grip strength (left)	European	461,089	2018	UK Biobank	ukb-b-10215
Hand grip strength (right)	European	461,026	2018	UK Biobank	ukb-b-7478
Walking pace	European	459,915	2018	UK Biobank	ukb-b-4711