Dementia is a syndrome that leads to a severe decline in cognitive function. As a neurodegenerative disease, it seriously affects the normal life and work of patients (Gale et al., 2018). The prevalence of dementia is 697 per 10,000 people, and the number of people with dementia doubles approximately every 5 years (Cao et al., 2020). This disease undoubtedly places a heavy burden on families and governments, with studies showing that the total cost of dementia is expected to reach US $507.49 billion by 2030 and US $1.89 trillion by 2050 (Jia et al., 2018). The most common dementia subtypes, according to clinicopathology, include Alzheimer’s dementia (ADD), vascular dementia (VaD), frontotemporal dementia (FTD), dementia with Lewy bodies (DLB), and unspecified dementia (Elahi and Miller, 2017). Although the etiologies of the various dementia types remain unclear, the risk factors for dementia mainly include advanced age, metabolic disorders, inflammation, cerebrovascular diseases, and genetic factors (Raz et al., 2016; Forloni and Balducci, 2018).

Musculoskeletal disorders (MSDs) are a serious public health problem and the most common cause of sick absence, chronic incapacity, and retirement due to ill health (Weerasekara and Hiller, 2017). An 11-year follow-up study from Norway showed that 48% of adults had at least one chronic MSDs and 20% had chronic extensive MSDs (Hagen et al., 2011). MSDs are a leading cause of pain and disability in patients, and all MSDs accounted for 6.7% of the total global disease burden in 2010 (March et al., 2014). OA was the most common MSD in 2019, reported in 527.81 million people, and the prevalence of OA is increasing annually (Hamood et al., 2021; Long et al., 2022). Similar to dementia, advanced age, genetic factors, and metabolic disorders also play an important role in MSDs, including OA, rheumatoid arthritis (RA), ankylosing spondylitis (AS), and osteoporosis (OP) (Gallo et al., 2017; Baar et al., 2018; Magnusson et al., 2023).

Both MSDs and dementia are heavy health burdens in older adults. Numerous previous studies have investigated the causal association between MSDs and dementia. According to a study by Guo et al. (2022), OA patients are at an increased risk for various cognitive impairments (Guo et al., 2022), but a retrospective cross-sectional study showed that pain interference is positively associated with dementia regardless of whether OA is present (Ikram et al., 2019). Kronzer et al. (2021) reported that the risk of ADD appears to decline over time in patients with RA (Kronzer et al., 2021). Jang et al. (2019) found that patients with AS had a higher prevalence of all-cause dementia and ADD (Jang et al., 2019). Simultaneously, some reported that sarcopenia was associated with the risk of DLB and ADD (Dost et al., 2022, 2023). However, most of these studies were retrospective, and the potential bias of residual confounding and reverse causality were unavoidable in these studies. The causality of MSDs and dementia needs to be supported by genetic evidence.

Mendelian randomization (MR) is a genetic method used to assess causal associations between an exposure or risk factor and a clinically relevant outcome (Sekula et al., 2016). MR regards a single-nucleotide polymorphism (SNP) as an instrumental variable (IV) for testing exposure because the alleles of genetic variation during meiosis are randomly assigned, and fixation of offspring genotypes occurs before exposure occurs. MR can minimize the problems of reverse causation and confounding factors (Bell et al., 2021). Because of these advantages, MR has been widely used for studying dementia and its related traits in recent years; for example, a previous MR study found that there was no genetic association between dementia and systemic lupus erythematosus and that high blood pressure was associated with a lower risk of dementia (Sproviero et al., 2021; Jin et al., 2022). In this study, we utilized publicly available gene-wide association study (GWAS) summary data for two-sample MR analysis. To our knowledge, this is the first MR study to explore the causal associations among common MSDs and various types of dementia.

This study found broad genetic causal associations between MSDs and various types of dementia using the MR method. In our study, we found that AS was identified as an independent risk factor for dementia, DLB, and ADD. Autoimmune arthritis, including JIA, RA and SNRA, was associated with a reduced risk of FTD; furthermore, RA was inversely associated with unspecified dementia. Meanwhile, we found that OA is associated with a lower risk of different dementia subtypes. It can be concluded that some MSDs were associated with the risk factors for different subtypes of dementia.

Since the two major public health problems in middle-aged and older people are MSDs and dementia, their relationship has been widely studied. A retrospective study from South Korea showed that after adjusting for confounding factors such as sex, age, and income, patients with AS showed a higher prevalence of overall dementia and ADD than healthy controls (Jang et al., 2019). A 40-year cohort study showed that the incidence of dementia in patients with new-onset RA decreased over time (Kronzer et al., 2021). A nationwide cohort study in Taiwan showed that OA is an independent risk factor for dementia (Huang et al., 2015). There are many other studies similar to the above; however, most of these studies are based on observational evidence, which is easily affected by various confounding factors. For example, Huang et al. (2015) explained the positive causal associations between OA and dementia due to the pain and depression status of OA patients (Huang et al., 2015). Jang et al. (2019) explained the positive causal associations between AS and dementia as being caused by common risk factors such as hypertension, diabetes, and dyslipidemia (Jang et al., 2019). Furthermore, the drug treatment of MSDs also affects the causal associations between MSDs and dementia. For example, a study showed that aspirin was associated with improvements in cognitive impairment, whereas prednisone was associated with cognitive decline (Mclaurin et al., 2005). Simultaneously, a study showed that disease-modifying antirheumatic drugs (DMARDs) such as hydroxychloroquine, methotrexate and sulfasalazine have a significantly increased risk of dementia (Chou et al., 2017). To minimize the influence of the abovementioned confounding factors, this study provides new evidence for a causal association between MSDs and dementia from a genetic perspective using two-sample MR.

Our results are consistent with those of previous studies showing that AS is an independent risk factor for dementia, FTD, and ADD. AS is a chronic inflammatory rheumatic autoimmune disease. A functional magnetic resonance imaging study showed that long-term chronic inflammation caused by AS causes widespreasud changes in brain connectivity and leads to deficits in brain function (Li et al., 2017). Long-term chronic inflammation is an important feature of AS, and the activation of the NLR family pyrin domain containing 3 inflammasome (NLRP3) is an important component of the pathogenesis of AS (Kim et al., 2018). A study showed that systemic inflammation downregulates amyloid-β clearance and affects microglial morphology in an NLRP3-dependent manner, ultimately leading to cognitive impairment (Tejera et al., 2019). DLB is the second most common type of dementia after ADD and is characterized by the formation of Lewy bodies in the nerve cells of the brain, and α-synuclein is the major component of Lewy bodies (McKeith et al., 2017). Previous studies showed that the activation of the NLRP3 inflammasome is associated with the accumulation of α-synuclein aggregates, and these studies further confirmed the role of NLRP3 in amyloid β and tau driving in Alzheimer’s disease (Gordon et al., 2018; Anderson et al., 2023). Therefore, inflammation caused by AS may explain the causal relationship between AS and dementia.

In this MR analysis, no genetic association was found between RA and dementia, ADD, VAD. Previous studies on the causation between RA and dementia were complex. Some studies have shown that RA is associated with a decreased risk of dementia, whereas others have shown the opposite (Lin et al., 2018; Kronzer et al., 2021). We speculate that these contradictions may be caused by the use of DMARDs, which have been the main treatment for RA for decades. Studies have shown that all patients with RA should receive DMARD treatment as soon as possible to control symptoms and slow disease progression (Rindfleisch and Muller, 2005). A case–control study showed that patients with RA who used conventional synthetic DMARDs had a 1.63-fold higher risk of dementia than patients who did not use conventional synthetic DMARDs (Chou et al., 2017). In our study, we also found that JIA, RA, and SNRA were significantly associated with a reduced risk of FDT. FDT is a neurodegenerative disorder characterized by progressive deficits in behavior, executive function, or language that asymmetrically affect the frontotemporal lobes of the brain. Shared genetic risk factors for FDT and autoimmune diseases, including RA, have been documented (Broce et al., 2018). C9orf72 is the most common genetic background of FTD, and its causal relationship with autoimmune diseases remains uncertain. Some studies have shown that in the Finnish population, carriers of FTD C9orf72 expansion are less likely to develop autoimmune diseases than noncarriers (Katisko et al., 2018), which provides some suggestive evidence for the associations between autoimmune disease and FTD. Simultaneously, a study showed that change in the systemic inflammatory state affect the pathogenesis of FTD (Mccauley and Baloh, 2019). This MR study provides new evidence and direction for the causal associations among RA, JIA, and other autoimmune diseases and FTD through genetic methods.

This MR study also showed that OA may be related to a decreased risk of dementia. A previous study showed that OA is an independent risk factor for dementia and cognitive impairment (Guo et al., 2022), which is inconsistent with our findings. We considered several possible reasons for this difference. First, glucosamine is an important nonsurgical treatment for OA (Fransen et al., 2015), and longitudinal cohort and MR studies have shown a significant causal relationship between glucosamine and a reduced risk of dementia (Zheng et al., 2023). Meanwhile, animal experiments have shown that glucosamine can reduce inflammation in the central nervous system and protect cognitive function from damage caused by hypoxia (Lee et al., 2018). Due to the high overlap between patients with OA and glucosamine-using populations, a considerable fraction of SNPs for these two traits were concordant, which may explain the protective effect of OA on dementia observed in this study. Second, the role of inflammation in the development of dementia is complex. Although many studies suggest that inflammation has widespread neurodestructive and dementia-promoting effects (Li et al., 2017; Tejera et al., 2019), current studies have shown that microglia have both protective and destructive effects on nerves in an inflammatory environment (Enciu and Popescu, 2013). Meanwhile, apoptotic chondrocytes release RNA and activate TLR3 signaling, which is one of the important mechanisms of OA progression (Stolberg-Stolberg et al., 2022), while Bsibsi et al. (2006) showed that TLR3 is induced and activated during astrocyte inflammation, leading to the production of anti-inflammatory cytokines and ultimately mediating a comprehensive neuroprotective response (Bsibsi et al., 2006), which seems to explain the potential protective effect of OA against various subtypes of dementia. Simultaneously, our study found that there were no genetic associations between other MSDs and dementia, which is inconsistent with some previous studies. For example, a previous study reported that muscle strength was associated with the severity of dementia, and some found that sarcopenia may be more common in patients with ADD and DLB (Dost et al., 2022, 2023). We speculate that individual background factors related to sarcopenia, rather than sarcopenia itself, also contribute to the development of dementia. The studies showed that decreased muscle strength will lead to a significant increase in the incidence of mental illnesses, including anxiety and depression, and these disorders may play an indispensable role in the development of dementia (Mirza et al., 2016; Kandola et al., 2020).

To the best of our knowledge, this is the first MR study of common MSDs and dementia and has several strengths. First, the MR analysis minimized errors caused by reverse causality and confounders in the causal estimates of MSD and dementia. Second, this study used the most recent GWAS summary data, including a large sample size, and all SNPs were strictly screened to ensure the independence of the IVs and strong correlations with the exposure. Meanwhile, the lowest F value of the IVs was 10.986, indicating that the genetic instruments we used have strong statistical power. Finally, the use of various sensitivity tests ensured the stability of the causal estimates. Furthermore, we explained the relationship between MSDs and dementia by reviewing many previous studies. However, our study also has the following limitations. First, since all the relevant SNP data were only from studies on European populations, the results of our study should be applied to other races with caution. Second, in two-sample MR studies, sample overlap may lead to biased effect estimates, and we can only control this error by choosing other GWAS summary data. In our study, outcome data for dementia were from the FinnGen consortium, and most of the exposure data were from the Genetics of Osteoarthritis consortium and GWAS catalog. However, we were unable to find satisfactory GWAS data for SNRA, SPRA, JIA meniscus derangement, muscle wasting and atrophy, lateral epicondylitis and cervical disc disorders outside of the FinnGen consortium. We examined sample overlap of these traits with dementia, and the highest rate was 2.26% (meniscus derangement and dementia). Although this ratio is acceptable with reference to published research (Burgess et al., 2016), we still treated these results with caution. Third, we were unable to perform further subgroup analyses because of our inability to obtain detailed information and clinical stages of the participants in the GWAS. Fourth, the impact of horizontal pleiotropy on MR research is unavoidable, although we conducted a rigorous screening of the IVs used and used methods such as MR-PRESSO and MR–Egger to monitor them. Last, epigenetic problems, including DNA methylation and pathway inactivation, also affect the accuracy of MR research results to varying degrees.

In this study, our aim was to identify causal associations among MSDs and different types of dementia. After eliminating the outliers detected in the MR-PRESSO analysis, we found that hip OA was genetically associated with a lower risk of dementia, unspecified dementia, ADD and VaD. Kneehip OA was inversely associated with unspecified dementia and VaD; RA, JIA, and SNRA were inversely associated with FTD, and RA was inversely associated with unspecified dementia. Simultaneously, AS was an independent risk factor for dementia, ADD and DLB. This study provides new genetic evidence for the associations between MSDs and dementia and may aid in the early detection of dementia in patients with MSDs.

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants' legal guardians/next of kin in accordance with the national legislation and the institutional requirements.

JiW: Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing. MY: Formal analysis, Writing – review & editing. YT: Investigation, Writing – review & editing. RF: Software, Writing – review & editing. KX: Software, Writing – review & editing. MT: Investigation, Writing – review & editing. JuW: Validation, Writing – review & editing. QW: Validation, Writing – review & editing. PX: Conceptualization, Project administration, Writing – review & editing.