Characteristics of frequent geriatric users of an urban emergency department.

Parkinson’s disease (PD) presents both motor and non-motor symptoms (Dorsey et al., 2018). Constipation is one of the most common non-motor symptoms in PD (Knudsen et al., 2017). Importantly, constipation can occur over 10 years prior to a PD diagnosis, and might be a risk factor for PD development (Adams-Carr et al., 2016). Research has revealed the existence of pathological hallmarks of PD in colonic biopsies from patients with PD but not controls (Lebouvier et al., 2010). Additionally, α-synuclein accumulation has been detected in colonic biopsies performed nearly a decade prior to the emergence of motor symptoms (Shannon et al., 2012; Hilton et al., 2014). In a PD mouse model, gastrointestinal dysfunction reportedly precedes motor deficits, and increased α-synuclein protein expression appears in the colon before it occurs in the brain (Yang et al., 2018). This early gastrointestinal involvement supports the “ascending anatomical theory,” which suggests that PD pathology may progress from the gut to the brain (Braak et al., 2003). The gut microbiota is currently recognized as a key player for regulating physical health (Heintz-Buschart and Wilmes, 2018). In recent years, growing numbers of studies have explored how the gut microbiota affects brain function. Increasing evidence points to the gut microbiota as a risk factor for various neurological disorders (Cryan et al., 2020). Notably, accumulating evidence connects the gut microbiota to the symptomatology and pathophysiology of PD (dos Santos et al., 2023; Fang et al., 2024; Neufeld et al., 2024). To examine gut microbiota dysbiosis in patients with PD, 16S rRNA amplicon sequencing has been widely used (Scheperjans et al., 2015; Hill-Burns et al., 2017; Heintz-Buschart et al., 2018); however, this method has several limitations. It is prone to bias, has limited resolution, and lacks functional information. These drawbacks restrict the universality and significance of related studies, preventing the discovery of more PD-associated gut microbiome features. Additionally, it is challenging to assign abundance changes of different genes detected through 16S rRNA amplicon sequencing to specific microbial species or strains. Although high-resolution shotgun metagenomic sequencing has been gradually adopted to infer the biological functions of microbial communities (Bedarf et al., 2017; Qian et al., 2020; Wallen et al., 2022; Palacios et al., 2023), this method often generates misassemblies and chimeric contigs, introducing substantial biases into the analysis (Teeling and Glöckner, 2012; Howe and Chain, 2015). Assembly-free-based metagenomic approaches can profile low-abundance microorganisms that cannot be assembled because of low sequence coverage (Quince et al., 2017). Nevertheless, it remains challenging to identify the characteristics of these unrecognized microorganisms. There is therefore an urgent need to explore gut microbial functions at the genome level. Bacterial genomes have traditionally been obtained through conventional culturing methods; however, culturing gut microbiota in artificial culture media remains difficult. By contrast, metagenomic binning offers a powerful approach for reconstructing the genomes of rare community members (Wang et al., 2024). Metagenome-assembled genomes (MAGs), which are generated from metagenomic data as draft microbial genomes, have been extensively used to investigate microbiota characteristics in human diseases (Zhu et al., 2021; Hu et al., 2023; Yang et al., 2023). Nonetheless, the application of gut microbiota MAGs of patients with PD remains scarce.