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        Early diagnosis of essential tremor (ET) can be challenging, especially when distinguished from healthy controls (HC) and Parkinson’s disease (PD). Recently, the analysis of stool samples for gut microbiota and its metabolites has provided new methods for the discovery of new biomarkers of neurodegenerative diseases. Short-chain fatty acids (SCFA), as the main metabolite of intestinal flora, are reduced in feces in PD. However, fecal SCFA have never been studied in ET. We aimed to investigate fecal levels of SCFAs in ET, assess their relationship with clinical symptoms and gut microbiota, and determine their potential diagnostic ability. Fecal SCFA and gut microbiota were measured in 37 ETs, 37 new PDs, and 35 HCs. Constipation, autonomic dysfunction, and tremor severity were assessed using scales. Fecal levels of propionate, butyrate, and isobutyrate were lower in ET than in HC. A combination of propionic, butyric and isobutyric acids distinguished ET from HC with an AUC of 0.751 (95% CI: 0.634–0.867). Fecal isovaleric acid and isobutyric acid levels were lower in ET than in PD. Isovaleric acid and isobutyric acid discriminate between ET and PD with an AUC of 0.743 (95% CI: 0.629–0.857). Fecal propionate is inversely associated with constipation and autonomic dysfunction. Isobutyric acid and isovaleric acid are inversely related to tremor severity. The decrease in fecal SCFA content was associated with a decrease in the abundance of Faecalibacterium and Streptobacterium in the ET. Thus, the content of SCFA in feces decreases in ET and is associated with the severity of the clinical picture and changes in the intestinal microbiota. Propionic acid, butyric acid, isobutyric acid, and isovaleric acid in feces may be potential diagnostic and differential diagnostic biomarkers for ET.
        Essential tremor (ET) is a progressive, chronic neurodegenerative disorder characterized primarily by tremor of the upper extremities, which can also affect other parts of the body such as the head, vocal cords, and lower extremities 1 . Clinical features of ET include not only motor symptoms but also some non-motor signs, including gastrointestinal disease 2 . Numerous studies have been conducted to examine the pathological and physiological characteristics of essential tremor, but clear pathophysiological mechanisms have not been identified3,4. Recent studies suggest that dysfunction of the microbiota-gut-brain axis may contribute to neurodegenerative diseases, and there is growing evidence for a potential bidirectional link between the gut microbiota and neurodegenerative diseases5,6. Notably, in one case report, fecal microbiota transplantation improved both essential tremor and irritable bowel syndrome in a patient, which may indicate a close relationship between gut microbiota and essential tremor. In addition, we also found specific changes in the gut microbiota in patients with ET, which strongly supports the important role of gut dysbiosis in ET8.
        Regarding gut dysbiosis in neurodegenerative diseases, PD is the most widely studied5. An unbalanced microbiota can increase intestinal permeability and activate intestinal glia, leading to alpha-synucleinopathies9,10,11. PD and ET have certain overlapping characteristics, such as similar frequency of tremor in ET and PD patients, overlapping resting tremor (typical tremor in PD), and postural tremor (mostly found in ET patients), making it difficult to distinguish between them. early stages 12. Therefore, we urgently need to open a useful window to differentiate between ET and PD. In this context, studying the specific intestinal dysbiosis and associated metabolite changes in ET and identifying their differences from PD may become potential biomarkers for the diagnosis and differential diagnosis of ET.
        Short-chain fatty acids (SCFAs) are the major metabolites produced by intestinal bacterial fermentation of dietary fiber and are thought to play a critical role in gut-brain interactions13,14. SCFAs are taken up by colon cells and transported to the liver through the portal venous system, and some SCFAs enter the systemic circulation. SCFAs have local effects on maintaining the integrity of the intestinal barrier and promoting innate immunity in the intestinal mucosa15. They also have long-term effects on the blood-brain barrier (BBB) ​​by stimulating tight junction proteins and activating neurons by stimulating G protein-coupled receptors (GPCRs) to cross the BBB16. Acetate, propionate, and butyrate are the most abundant SCFAs in the colon. Previous studies have shown decreased fecal levels of acetic, propionic and butyric acids in patients with Parkinson’s disease17. However, fecal SCFA levels have never been studied in patients with ET.
        Thus, our study was aimed at identifying specific changes in fecal SCFA in patients with ET and their differences from patients with PD, assessing the relationship of fecal SCFA with clinical symptoms of SCFA and intestinal microbiota, as well as identifying the potential diagnostic and differential diagnostic capabilities of fecal samples. KZHK. To address confounding factors associated with anti-PD drugs, we selected patients with new-onset Parkinson’s disease as disease controls.
        The demographic and clinical characteristics of the 37 ETs, 37 PDs, and 35 HCs are summarized in Table 1. ETs, PDs, and HCs were matched by age, sex, and BMI. The three groups also had similar proportions of smoking, drinking alcohol and drinking coffee and tea. The Wexner score (P = 0.004) and HAMD-17 score (P = 0.001) of the PD group were higher than those of the HC group, and the HAMA score (P = 0.011) and HAMD-17 score (P = 0.011) of the ET group were higher than that of the HC group. The course of the disease in the ET group was significantly longer than in the PD group (P<0.001).
        There were significant differences in fecal levels of fecal propionic acid (P = 0.023), acetic acid (P = 0.039), butyric acid (P = 0.020), isovaleric acid (P = 0.045), and isobutyric acid (P = 0.015). . In further post hoc analysis, the levels of propionic acid (P = 0.023), butyric acid (P = 0.007), and isobutyric acid (P = 0.040) in the ET group were significantly lower than those in the HC group. Patients with ET had lower levels of isovalerate (P = 0.014) and isobutyrate (P = 0.005) than patients with PD. In addition, levels of fecal propionic acid (P = 0.013), acetic acid (P = 0.016), and butyric acid (P = 0.041) were lower in patients with PD than in patients with CC (Fig. 1 and Supplementary Table 1) .
        ag represents a group comparison of propionic acid, acetic acid, butyric acid, isovaleric acid, valeric acid, caproic acid and isobutyric acid, respectively. There were significant differences in the levels of fecal propionic acid, acetic acid, butyric acid, isovaleric acid and isobutyric acid between the three groups. ET essential tremor, Parkinson’s disease, healthy HC control, SCFA. Significant differences are indicated by *P < 0.05 and **P < 0.01.
        Considering the difference in disease course between the ET group and the PD group, we tested 33 patients with early PD and 16 patients with ET (disease course ≤3 years) for further comparison (Supplementary Table 2). The results showed that fecal propionic acid content of ET was significantly lower than that of HA (P=0.015). The difference between ET and HC for butyric acid and isobutyric acid was not significant, but a trend was still observed (P = 0.082). Fecal isobutyrate levels were significantly lower in patients with ET compared with patients with PD (P = 0.030). The difference between ET and PD of isovaleric acid was not significant, but there was still a trend (P = 0.084). Propionic acid (P = 0.023), acetic acid (P = 0.020), and butyric acid (P = 0.044) were significantly lower in PD patients than in HC patients. These results (Supplementary Figure 1) are generally consistent with the main results. The difference in results between the overall sample and the early patient subgroup may be due to the smaller sample size in the subgroup, resulting in lower statistical power of the data.
        We next examined whether fecal SCFA levels could distinguish patients with ET from patients with CU or PD. According to ROC analysis, the difference in AUC of propionate levels was 0.668 (95% CI: 0.538-0.797), which made it possible to distinguish patients with ET from HC. Patients with ET and GC could be distinguished by butyrate levels with an AUC of 0.685 (95% CI: 0.556–0.814). Differences in isobutyric acid levels may distinguish patients with ET from HC with an AUC of 0.655 (95% CI: 0.525–0.786). When combining propionate, butyrate and isobutyrate levels, a higher AUC of 0.751 (95% CI: 0.634–0.867) was obtained with a sensitivity of 74.3% and specificity of 72.9% (Fig. 2a). To differentiate between ET and PD patients, the AUC for isovaleric acid levels was 0.700 (95% CI: 0.579–0.822) and for isobutyric acid levels was 0.718 (95% CI: 0.599–0.836). The combination of isovaleric acid and isobutyric acid levels had a higher AUC of 0.743 (95% CI: 0.629–0.857), sensitivity of 74.3% and specificity of 62.9% (Fig. 2b). In addition, we examined whether SCFA levels in feces of patients with Parkinson’s disease differed from controls. According to ROC analysis, the AUC for identifying patients with PD based on differences in propionic acid levels was 0.687 (95% CI: 0.559-0.814), with a sensitivity of 68.6% and specificity of 68.7%. Differences in acetate levels may distinguish PD patients from HCs with an AUC of 0.674 (95% CI: 0.542–0.805). Patients with PD can be differentiated from CU only by butyrate levels with an AUC of 0.651 (95% CI: 0.515–0.787). When combining propionate, acetate and butyrate levels, an AUC of 0.682 (95% CI: 0.553–0.811) was obtained (Fig. 2c).
        Discrimination of the Russian Orthodox Church against ET and HC; b discrimination of the Russian Orthodox Church against ET and PD; c ROC discrimination against PD and HC. ET essential tremor, Parkinson’s disease, healthy HC control, SCFA.
        In patients with ET, fecal isobutyric acid levels were negatively correlated with FTM score (r = -0.349, P = 0.034), and fecal isovaleric acid levels were negatively correlated with FTM score (r = -0.421, P = 0.001) and TETRAS score. (r = -0.382, P = 0.020). In patients with ET and PD, fecal propionate levels were negatively correlated with SCOPA-AUT scores (r = −0.236, P = 0.043) (Fig. 3 and Supplementary Table 3). There was no significant correlation between disease course and SCFA in either the ET group (P ≥ 0.161) or the PD group (P ≥ 0.246) (Supplementary Table 4). In patients with PD, fecal caproic acid levels were positively correlated with MDS-UPDRS scores (r = 0.335, P = 0.042). Across all participants, fecal propionate (r = −0.230, P = 0.016) and acetate (r = −0.210, P = 0.029) levels were negatively correlated with Wexner scores (Fig. 3 and Supplementary Table 3).
        Fecal isobutyric acid levels were negatively correlated with FTM scores, isovaleric acid was negatively correlated with FTM and TETRAS scores, propionic acid was negatively correlated with SCOPA-AUT scores, caproic acid was positively correlated with MDS-UPDRS scores, and propionic acid was negatively correlated with FTM and TETRAS scores. TETRAS and acetic acid were negatively correlated with the Wexner score. MDS-UPDRS Association sponsored version of the Unified Parkinson’s Disease Rating Scale, Mini-Mental State Examination MMSE, Hamilton Depression Rating Scale HAMD-17, 17 items, Hamilton Anxiety Rating Scale HAMA, HY Hoehn and Yahr stages, SCFA, SCOPA – AUT Parkinson’s Disease Autonomic Symptom Outcome Scale, FTM Fana-Tolosa-Marin Clinical Tremor Rating Scale, TETRAS Research Group (TRG) Essential Tremor Rating Scale. Significant differences are indicated by *P < 0.05 and **P < 0.01.
        We further explored the discriminatory nature of gut microbiota using LEfSE analysis and selected the genus relative abundance data level for further analysis. Comparisons were made between ET and HC and between ET and PD. Spearman correlation analysis was then performed on the relative abundance of gut microbiota and fecal SCFA levels in the two comparison groups.
        Faecalibacterium (correlated with butyric acid, r = 0.408, P < 0.001), Lactobacillus (correlated with butyric acid, r = 0.283, P = 0.016), Streptobacterium (correlated with propionic acid, r = 0.327) were present in the analysis of ET and CA. , P = 0.005; correlated with butyric acid, r = 0.374, P = 0.001; correlates with isobutyric acid, r = 0.329, P = 0.005), Howardella (correlates with propionic acid, r = 0.242, P = 0.041), Raoultella (correlates with propionate, r = 0.249, P = 0.035), and Candidatus Arthromitus (correlates with isobutyric acid, r = 0.302, P = 0.010) was found to be decreased in ET and positively correlated with fecal SCFA levels. However, Stenotropomonas abundance increased in ET and was negatively correlated with fecal isobutyrate levels (r = -0.250, P = 0.034). After FDR adjustment, only the correlations between Faecalibacterium, Catenibacter, and SCFA remained significant (P ≤ 0.045) (Fig. 4 and Supplementary Table 5).
        Correlation analysis of ET and HC. After FDR adjustment, the abundance of Faecalibacterium (positively associated with butyrate) and Streptobacterium (positively associated with propionate, butyrate, and isobutyrate) was found to be reduced in ET and positively associated with fecal SCFA levels. b Correlation analysis of ET and PD. After FDR adjustment, no significant associations were found. ET essential tremor, Parkinson’s disease, healthy HC control, SCFA. Significant differences are indicated by *P < 0.05 and **P < 0.01.
        When analyzing ET versus PD, Clostridium trichophyton was found to be increased in ET and correlated with fecal isovaleric acid (r = -0.238, P = 0.041) and isobutyric acid (r = -0.257, P = 0.027). ). After FDR adjustment, either remained significant (P≥0.295) (Figure 4 and Supplementary Table 5).
        This study is a comprehensive study that examines fecal SCFA levels and correlates them with changes in gut microbiota and symptom severity in patients with ET compared with patients with CU and PD. We found that fecal SCFA levels were reduced in patients with ET and were associated with clinical severity and specific changes in the gut microbiota. Cumulative levels of short-chain fatty acids (SCFAs) in feces differentiate ET from GC and PD.
        Compared with GC patients, ET patients have lower fecal levels of propionic, butyric, and isobutyric acids. The combination of propionic, butyric and isobutyric acids can differentiate between ET and HC with an AUC of 0.751 (95% CI: 0.634–0.867), sensitivity of 74.3% and specificity of 72.9%, indicating their use as a potential role as diagnostic biomarkers for ET. Further analysis showed that fecal propionic acid levels were negatively correlated with the Wexner score and the SCOPA-AUT score. Fecal isobutyric acid levels were inversely correlated with FTM scores. On the other hand, a decrease in butyrate levels in ET was associated with a decrease in the abundance of SCFA-producing microbiota, Faecalibacterium, and Categorybacter. In addition, reductions in Catenibacter abundance in ET were also associated with reductions in fecal propionic and isobutyric acid levels.
        Most SCFAs produced in the colon are taken up by colonocytes primarily through H+-dependent or sodium-dependent monocarboxylate transporters. Absorbed short-chain fatty acids are used as an energy source for colonocytes, whereas those that are not metabolized in colonocytes are transported into the portal circulation 18 . SCFAs can influence intestinal motility, enhance intestinal barrier function, and influence host metabolism and immunity19. It was previously found that fecal concentrations of butyrate, acetate, and propionate were reduced in PD patients compared with HCs17, which is consistent with our results. Our study found decreased SCFA in patients with ET, but little is known about the role of SCFA in the pathology of ET. Butyrate and propionate can bind to GPCRs and influence GPCR-dependent signaling such as MAPK and NF-κB20 signaling. The basic concept of the gut-brain axis is that SCFAs secreted by gut microbes can influence host signaling, thereby influencing gut and brain function. Because butyrate and propionate have potent inhibitory effects on histone deacetylase (HDAC) activity21 and butyrate can also act as a ligand for transcription factors, they have widespread effects on host metabolism, differentiation and proliferation, primarily due to their influence on gene regulation22 . Based on evidence from SCFA and neurodegenerative diseases, butyrate is considered a therapeutic candidate due to its ability to correct impaired HDAC activity, which may mediate dopaminergic neuron death in PD23,24,25. Animal studies have also demonstrated the ability of butyric acid to prevent dopaminergic neuron degeneration and improve movement disorders in PD models26,27. Propionic acid has been found to limit inflammatory responses and protect the integrity of the BBB28,29. Studies have shown that propionic acid promotes the survival of dopaminergic neurons in response to rotenone toxicity in PD models 30 and that oral administration of propionic acid rescues dopaminergic neuron loss and motor deficits in mice with PD 31 . Little is known about the function of isobutyric acid. However, a recent study found that colonization of mice with B. ovale increased intestinal SCFA content (including acetate, propionate, isobutyrate, and isovalerate) and intestinal GABA concentration, highlighting that a link has been established between gut microbiota and intestinal SCFA. concentrations of neurotransmitters32. For ET, abnormal pathological changes in the cerebellum include changes in Purkinje cell axons and dendrites, displacement and loss of Purkinje cells, changes in basket cell axons, and abnormalities in ascending fiber connections to Purkinje cells. nuclei, which leads to a decrease in GABAergic output from the cerebellum3,4,33. It remains unclear whether SCFAs are associated with Purkinje cell neurodegeneration and decreased cerebellar GABA production. Our results suggest a close relationship between SCFA and ET; however, the cross-sectional study design does not allow any conclusions about the causal relationship between SCFA and the ET disease process. Further longitudinal follow-up studies are needed, including serial measurements of fecal SCFAs, as well as animal studies examining mechanisms.
        SCFAs are thought to stimulate colonic smooth muscle contractility34. A lack of SCFA will worsen the symptoms of constipation, and supplementation with SCFA may improve the symptoms of constipation PD35. Our results also indicate a significant association between decreased fecal SCFA content and increased constipation and autonomic dysfunction in patients with ET. One case report found that microbiota transplantation improved both essential tremor and irritable bowel syndrome in patient 7, further suggesting a close relationship between gut microbiota and ET. Therefore, we believe that fecal SCFA/microbiota may influence host intestinal motility and autonomic nervous system function.
        The study found that decreased levels of fecal SCFAs in ET were associated with decreased abundance of Faecalibacterium (associated with butyrate) and Streptobacterium (associated with propionate, butyrate, and isobutyrate). After FDR correction, this relationship remains significant. Faecalibacterium and Streptobacterium are SCFA-producing microorganisms. Faecalibacterium is known to be a butyrate-producing microorganism36, while the main products of Catenibacter fermentation are acetate, butyrate and lactic acid37. Faecalibacterium was detected in 100% of both the ET and HC groups; The median relative abundance of the ET group was 2.06% and that of the HC group was 3.28% (LDA 3.870). The category bacterium was detected in 21.6% (8/37) of the HC group and only in 1 sample of the ET group (1/35). The decrease and undetectability of streptobacteria in ET may also indicate a correlation with the pathogenicity of the disease. The median relative abundance of Catenibacter species in the HC group was 0.07% (LDA 2.129). In addition, lactic acid bacteria were associated with changes in fecal butyrate (P=0.016, P=0.096 after FDR adjustment), and arthritis candidate was associated with changes in isobutyrate (P=0.016, P=0.072 after FDR adjustment). After FDR correction, only the correlation trend remains, which is not statistically significant. Lactobacilli are also known to be SCFA (acetic acid, propionic acid, isobutyric acid, butyric acid) producers 38 and Candidatus Arthromitus is a specific inducer of T helper 17 (Th17) cell differentiation, with Th1/2 and Tregs associated with immune balance /Th1739. . A recent study suggests that elevated levels of fecal pseudoarthritis may contribute to colonic inflammation, intestinal barrier dysfunction, and systemic inflammation 40 . Clostridium trichophyton was increased in ET compared to PD. Clostridium trichoides abundance was found to be negatively correlated with isovaleric acid and isobutyric acid. After FDR adjustment, both remained significant (P≥0.295). Clostridium pilosum is a bacterium known to be associated with inflammation and may contribute to intestinal barrier dysfunction41. Our previous study reported changes in the gut microbiota of patients with ET8. Here we also report changes in SCFAs in ET and identify an association between gut dysbiosis and changes in SCFAs. Decreased SCFA levels are closely associated with intestinal dysbiosis and tremor severity in ET. Our results suggest that the gut-brain axis may play an important role in the pathogenesis of ET, but further studies in animal models are needed.
        Compared with patients with PD, patients with ET have lower levels of isovaleric and isobutyric acids in their feces. The combination of isovaleric acid and isobutyric acid identified ET in PD with an AUC of 0.743 (95% CI: 0.629–0.857), sensitivity of 74.3% and specificity of 62.9%, suggesting their potential role as biomarkers in the differential diagnosis of ET. . Fecal isovaleric acid levels were inversely correlated with FTM and TETRAS scores. Fecal isobutyric acid levels were inversely correlated with FTM scores. The decrease in isobutyric acid levels was associated with a decrease in the abundance of catobacteria. Little is known about the functions of isovaleric acid and isobutyric acid. A previous study showed that colonization of mice with Bacteroides ovale increased intestinal SCFA content (including acetate, propionate, isobutyrate, and isovalerate) and intestinal GABA concentrations, highlighting the intestinal link between microbiota and intestinal SCFA/neurotransmitter concentrations32. Interestingly, observed isobutyric acid levels were similar between the PD and HC groups, but differed between the ET and PD (or HC) groups. Isobutyric acid could distinguish between ET and PD with an AUC of 0.718 (95% CI: 0.599–0.836) and identify ET and NC with an AUC of 0.655 (95% CI: 0.525–0.786). In addition, isobutyric acid levels correlate with tremor severity, further strengthening its association with ET. The question of whether oral isobutyric acid can reduce the severity of tremor in patients with ET deserves further study.
        Thus, fecal SCFA content is reduced in patients with ET and is associated with the clinical severity of ET and specific changes in the intestinal microbiota. Fecal propionate, butyrate, and isobutyrate may be diagnostic biomarkers for ET, whereas isobutyrate and isovalerate may be differential diagnostic biomarkers for ET. Changes in fecal isobutyrate may be more specific for ET than changes in other SCFAs.
        Our study has several limitations. First, dietary patterns and food preferences may influence microbiota expression, larger study samples in different populations are needed, and future studies should introduce comprehensive and systematic dietary surveys such as food frequency questionnaires. Second, the cross-sectional study design precludes any conclusions about a causal relationship between SCFAs and the development of ET. Further long-term follow-up studies with serial measurements of fecal SCFAs are needed. Third, the diagnostic and differential diagnostic capabilities of fecal SCFA levels should be validated using independent samples from ET, HC, and PD. More independent fecal samples should be tested in the future. Finally, patients with PD in our cohort had significantly shorter disease duration than patients with ET. We mainly matched ET, PD and HC by age, sex and BMI. Given the difference in disease course between the ET group and the PD group, we also studied 33 patients with early PD and 16 patients with ET (disease duration ≤3 years) for further comparison. Between-group differences in SCFA were generally consistent with our primary data. In addition, we found no correlation between disease duration and changes in SCFA. However, in the future, it would be best to recruit patients with PD and ET at an early stage with a shorter disease duration to complete the validation in a larger sample.
        The study protocol was approved by the ethics committee of Ruijin Hospital, affiliated to Shanghai Jiao Tong University School of Medicine (RHEC2018-243). Written informed consent was obtained from all participants.
        Between January 2019 and December 2022, 109 subjects (37 ET, 37 PD, and 35 HC) from the Movement Disorder Center Clinic of Ruijin Hospital, affiliated to Shanghai Jiao Tong University School of Medicine, were included in this study. The criteria were: (1) age 25–85 years, (2) patients with ET were diagnosed according to the MDS Working Group criteria 42 and PD were diagnosed according to the MDS criteria 43, (3) all patients were not taking anti-PD drugs before chair. collection of samples. (4) The ET group took only β-blockers or no related drugs before collecting stool samples. HCs matched to age, gender, and body mass index (BMI) were also selected. Exclusion criteria were: (1) vegetarians, (2) poor nutrition, (3) chronic diseases of the gastrointestinal tract (including inflammatory bowel disease, gastric or duodenal ulcers), (4) severe chronic diseases (including malignant tumors), heart failure, renal failure, hematological diseases) (5) History of major gastrointestinal surgery, (6) Chronic or regular consumption of yogurt, (7) Use of any probiotics or antibiotics for 1 month, (8 ) Chronic use of corticosteroids, proton pump inhibitors, statins, metformin, immunosuppressants or anticancer drugs and (9) severe cognitive impairment that interferes with clinical trials.
        All subjects provided medical history, weight and height information to calculate BMI, and underwent a neurological examination and clinical assessment such as the Hamilton Anxiety Rating Scale (HAMA) 44 anxiety score, the Hamilton Depression Rating Scale-17 score (HAMD-17) 45. depression, severity of constipation using the Wexner Constipation Scale 46 and the Bristol Stool Scale 47 and cognitive performance using the Mini-Mental State Examination (MMSE) 48 . The Scale for the Assessment of Autonomic Symptoms of Parkinson’s Disease (SCOPA-AUT) 49 examined autonomic dysfunction in patients with ET and PD. The Fan-Tolos-Marin Clinical Tremor Rating Scale (FTM) and the Essential Tremor Rating Scale (TETRAS) 50 The Tremor Study Group (TRG) 50 were examined in patients with ET; the United Parkinson’s Disease Association-sponsored Kinson’s disease rating scale (MDS- UPDRS) version 51 and Hoehn and Yahr (HY) grade 52 were examined.
        Each participant was asked to collect a stool sample in the morning using a stool collection container. Transfer containers to ice and store at -80°C before processing. SCFA analysis was performed according to routine operations of Tiangene Biotechnology (Shanghai) Co., Ltd. 400 mg of fresh fecal samples were collected from each subject and analyzed using SCFAs after grinding and pre-sonication. Selected SCFAs in feces were analyzed using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem MS (LC-MS/MS).
        DNA was extracted from 200 mg samples using the QIAamp® Fast DNA Stool Mini Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. Microbial composition was determined by sequencing the 16 S rRNA gene on DNA isolated from feces by amplifying the V3-V4 region. Test the DNA by running the sample on a 1.2% agarose gel. Polymerase chain reaction (PCR) amplification of the 16S rRNA gene was performed using universal bacterial primers (357 F and 806 R) and a two-step amplicon library constructed on the Novaseq platform.
        Continuous variables are expressed as mean ± standard deviation, and categorical variables are expressed as numbers and percentages. We used Levene’s test to test the homogeneity of variances. Comparisons were made using two-tailed t tests or analysis of variance (ANOVA) if variables were normally distributed and nonparametric Mann-Whitney U tests if normality or homoscedasticity assumptions were violated. We used the area under the receiver operating characteristic (ROC) curve (AUC) to quantify the diagnostic performance of the model and examine the ability of SCFA to distinguish patients with ET from those with HC or PD. To examine the relationship between SCFA and clinical severity, we used Spearman correlation analysis. Statistical analysis was performed using SPSS software (version 22.0; SPSS Inc., Chicago, IL) with the significance level (including P value and FDR-P) set at 0.05 (two-sided).
        The 16 S sequences were analyzed using a combination of Trimmomatic (version 0.35), Flash (version 1.2.11), UPARSE (version v8.1.1756), mothur (version 1.33.3) and R (version 3.6.3) software. Raw 16S rRNA gene data were processed using UPARSE to generate operational taxonomic units (OTUs) with 97% identity. Taxonomies were specified using Silva 128 as the reference database. The generic level of relative abundance data was selected for further analysis. Linear discriminant analysis (LDA) effect size analysis (LEfSE) was used for comparisons between groups (ET vs. HC, ET vs. PD) with an α threshold of 0.05 and an effect size threshold of 2.0. Discriminant genera identified by LEfSE analysis were further used for Spearman correlation analysis of SCFA.
       For more information about the study design, see the Natural Research Report Abstract associated with this article.
        Raw 16S sequencing data are stored in the National Center for Biotechnology Information (NCBI) BioProject database (SRP438900: PRJNA974928), URL: https://www.ncbi.nlm.nih.gov/Traces/study/?acc= SRP438900&o. =acc_s% 3Aa. Other relevant data are available to the corresponding author on reasonable request, such as scientific collaborations and academic exchanges with full research projects. No transfer of data to third parties without our consent is permitted.
        Open source code only with a combination of Trimmomatic (version 0.35), Flash (version 1.2.11), UPARSE (version v8.1.1756), mothur (version 1.33.3) and R (version 3.6.3), using default settings or section “Method”. Additional clarifying information can be provided to the corresponding author upon reasonable request.
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