Trajectories of Short-Chain Fatty Acids and Risk of Adverse Kidney Outcomes in Type 2 Diabetes: A Prospective Cohort Study

Trajectories of Short-Chain Fatty Acids and Risk of Adverse Kidney Outcomes in Type 2 Diabetes: A Prospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trajectories of Short-Chain Fatty Acids and Risk of Adverse Kidney Outcomes in Type 2 Diabetes: A Prospective Cohort Study Hui-Ju Tsai, Ping-Shaou Yu, Wei-Wen Hung, Ping-Hsun Wu, Wei-Chun Hung, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7791885/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The impact of short-chain fatty acids (SCFAs) on kidney outcomes in individuals with Type 2 diabetes (T2D) is not clearly understood. This study aimed to investigate the relationship between serum SCFA levels and adverse kidney outcomes in T2D patients. T2D patients were recruited between October 2016 and June 2020 and followed until December 2021. The serum levels of nine SCFAs were assessed using liquid chromatography-mass spectrometry. The primary kidney outcomes were defined as a doubling of serum creatinine levels or progression to end-stage kidney disease (ESKD). Secondary outcomes included an annual decline in estimated glomerular filtration rate (eGFR) of more than 5 ml/min/1.73 m² or a rapid 25% reduction in eGFR during the follow-up period. The mean age of the 480 T2D participants was 62.0 years. The individuals in tertile 3 of serum propionate, butyrate, and formate levels showed an 86%, 79%, and 75% reduction, respectively, in the adjusted risk of experiencing a doubling of serum creatinine or progression to ESKD, compared to those in tertiles 1 and 2 of serum propionate, butyrate and formate levels. Adjusted logistical analysis showed that the individuals in tertile 3 of serum propionate, butyrate, formate and valerate levels had a reduced risk of rapid eGFR decline by 62%, 59%, 54%, and 58%, respectively. In conclusion, T2D patients who have higher circulating levels of SCFAs, particularly propionate, butyrate, and formate, are at a reduced risk of unfavorable kidney outcomes. These SCFAs may serve as indicative biomarkers for kidney function deterioration in T2D individuals. Type 2 diabetes short-chain fatty acids end-stage kidney disease estimated glomerular filtration rate Figures Figure 1 Figure 2 Figure 3 Introduction Diabetes presents a major global health challenge and imposes a substantial economic burden on healthcare systems. Type 2 diabetes (T2D) is the main cause of chronic kidney disease (CKD) and end-stage kidney disease (ESKD). 1 The prevalence of chronic kidney disease (CKD) related to Type 2 diabetes (T2D) rose from 1.39% in 1999 to 1.74% in 2019, marking a significant increase in the number of affected individuals over the two-decade period. 2 Identifying novel biomarkers for kidney failure in T2D patients could allow for the early detection of individuals at risk and the development of tailored treatment strategies, ultimately enhancing patient outcomes and alleviating the burden on healthcare systems. Short-chain fatty acids (SCFAs) are volatile fatty acids generated by gut bacteria through the fermentation of dietary fiber. Carbohydrates are the primary source of short-chain fatty acids (SCFAs); however, amino acids such as valine, leucine, and isoleucine—derived from protein breakdown—can be converted into branched-chain SCFAs, including isobutyrate, isovalerate, and 2-methyl butyrate, which account for approximately 5% of total SCFA production. 3 , 4 SCFAs influence glucose metabolism, insulin sensitivity, and lipogenesis through multiple pathways, thereby playing a role in the development of obesity, diabetes, and other metabolic disorders. 5 , 6 Previous studies have suggested that the gut microbiota and kidneys interact via a gut-kidney axis, and that this axis also participates in the kidney injury process. 7 SCFAs, key metabolites produced through gut microbiota-mediated fermentation of dietary fiber, have garnered significant attention for their biological effects. Despite growing interest, the potential of circulating SCFA levels as biomarkers for kidney disease progression in clinical T2D population remains insufficiently studied. This study, therefore, aimed to examine the associations between circulating SCFA levels and adverse kidney outcomes in individuals with T2D. Materials and Methods Study Subjects Participants with T2D attending the outpatient departments of Kaohsiung Medical University Hospital (KMUH) were invited to participate in this prospective study from October 2016 to June 2020. This study has been described in detail previously. 8 In brief, T2D was diagnosed based on medical history, American Diabetes Association-defined blood glucose levels, or prescriptions for anti-diabetic medications. All of the enrolled patients received a diabetes education program and adhered to the recommended dietary guidelines for individuals with diabetes. Estimated glomerular filtration rate (eGFR) was determined using the 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. 9 The exclusion criteria were eGFR below 30 ml/min/1.73 m², acute illness, and the use of antimicrobial or probiotic agents in the month prior to enrollment. Approval for this study was granted by the Institutional Review Board of KMUH (KMUHIRB-G(II)-20160021, KMUHIRB-G(II)-20150044, KMUHIRB-G(II)-20190036). All of the enrolled patients provided written informed consent, and the study was conducted following the principles of the Declaration of Helsinki. Data Collection The following information was obtained through patient interviews and review of medical records at the time of enrollment: demographics, smoking and alcohol history, brief dietary recall about the preference for a plant-based diet or animal-based diet, and clinical information. Hypertension was diagnosed based on medical history or prescriptions for antihypertensive medications. Patients with a history of acute/chronic ischemic heart disease, myocardial infarction, or heart failure were classified as having heart disease. Body mass index was calculated as body weight/height 2 . Data on medication usage were recorded from medical records before and after enrollment, including anti-diabetic drugs, insulin, anti-hypertensive drugs, and statins. Twelve-hour fasting blood and urine samples were obtained for biochemical analysis. Serum creatinine was measured using the compensated Jaffé method (kinetic alkaline picrate) with an autoanalyzer (Roche/Integra 400, Roche Diagnostics), calibrated against an isotope-dilution mass spectrometry standard (Vickery, Stevens, Dalton, van Lente, & Lamb, 2006). The urinary albumin/creatinine ratio (UACR) was used to express the amount of protein in urine. Measurement of Serum SCFA Levels The detailed method for measurement of circulating SCFAs was described in previous study. 8 In brief, serum levels of the following SCFAs: methylvalerate, isovalerate, valerate, formate, methylbutyrate, isobutyrate, butyrate, propionate, and acetate, were quantified using liquid chromatography–mass spectrometry (LC-MS). Briefly, 50 µL of serum was mixed with 20 µL of 200 mM 3-nitrophenylhydrazine hydrochloride and 20 µL of 120 mM N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide hydrochloride in 6% pyridine, both prepared in 100% aqueous methanol. The mixture was incubated at 40°C for 30 minutes. After the reaction, the volume was adjusted to 210 µL with 10% aqueous methanol. Then, 25 µL of internal standard solution was added to 75 µL of the prepared sample, and a 10 µL aliquot was analyzed by LC-MS/MS. All detection and quantification were performed using a Waters ACQUITY UPLC system (Waters Corporation, Milford, MA) coupled with a tandem mass spectrometer (Finnigan TSQ Quantum Ultra, Thermo Scientific, San Jose, CA) operated with Xcalibur software (Thermo Scientific, San Jose, CA). The system employed an electrospray ionization source in positive mode. A 10 µL sample was filtered and injected into an ACQUITY UPLC BEH C18 column (130 Å, 1.7 µm, 2.1 × 100 mm; Waters Corporation, Milford, MA) with a flow rate of 300 µL/min at a column temperature of 40°C. Clinical Outcomes of the Patients Patients were followed until they reached a primary or secondary kidney outcome, died, were lost to follow-up, or until the end of the study period (December 2021). Outpatient clinic visits occurred every three months, during which clinical status and eGFR were evaluated. Only outpatient data were included in the analysis; information from hospitalizations or acute kidney injury events was excluded. The primary kidney outcomes were defined as either a doubling of serum creatinine or progression to ESKD. Secondary outcomes included a decline in eGFR of more than 5 mL/min/1.73 m² per year or a 25% reduction from baseline during the follow-up period. 10 The annual eGFR change, referred to as the eGFR slope, was calculated using the regression coefficient of eGFR over time and expressed in mL/min/1.73 m² per year. All available eGFR measurements from enrollment through the end of follow-up were used to calculate these outcomes. Percentage change in eGFR was determined by comparing the first and last recorded values. 11 Statistical Analysis Differences in continuous variables between groups were evaluated using independent t-tests or Mann-Whitney U tests, while categorical variables were compared using chi-square tests. Continuous variables with non-normal distributions were log10-transformed to approximate normality. Person-time was calculated from enrollment to the occurrence of a primary kidney outcome or the end of follow-up. Kaplan-Meier survival analysis was used to assess the relationship between serum SCFA levels and the cumulative risk of kidney outcomes, while Cox proportional hazards models evaluated the relationships between SCFA levels and primary kidney outcomes. Model fit was assessed using the Hosmer-Lemeshow test for models including SCFAs, eGFR, and UACR in predicting primary kidney outcome. 12 Logistic regression analyses were performed to examine the associations between serum SCFA levels and rapid kidney function decline, defined as an annual eGFR loss of more than 5 mL/min/1.73 m² or a 25% reduction in eGFR during follow-up. Multivariable models adjusted for traditional risk factors, including age, sex, use of angiotensin-converting enzyme inhibitors (ACEIs), use of angiotensin II receptor blockers (ARBs), baseline serum creatinine, log-transformed UACR, and glycated hemoglobin (HbA1c). Subgroup analyses explored potential effect modifiers in the association between SCFA tertiles and rapid kidney function decline, stratified by age (≥ 65 or < 65 years), sex (male or female), eGFR ( 7%), and UACR (< 30 mg/g or ≥ 30 mg/g). All statistical analyses were conducted using SPSS version 22 (IBM Inc., Armonk, NY) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed p-value of less than 0.05 was regarded as statistically significant. Results Characteristics of the Patients The study included 480 patients with T2D, with a mean age of 62.0 ± 11.1 years, and 54.6% of them were male (Table 1 ). The average duration of T2D was 10.2 years. Hyperlipidemia and hypertension and hyperlipidemia were present in 80.7 and 59.6% of the participants, respectively (Table 1 ). The mean eGFR was 82.2 mL/min/1.73 m², while the median UACR and HbA1c were 16.2 mg/g and 7.0%, respectively (Table 1 ). Table 1 The characteristics of study type 2 diabetes patients Entire Cohort (n = 480) Age, year 62.0 ± 11.1 Sex (male), % 54.6 Smoke, % 24.0 Alcohol, % 20.7 Hypertension, % 59.6 Gout, % 6.9 Hyperlipidemia, % 80.7 T2D duration, year 10.2 ± 8.5 Body mass index, kg/m 2 26.5 ± 4.4 Diet habit, % Protein more than fiber 15.8 Fiber more than protein 34.3 Fiber equal to protein 49.9 Medication Sulfonylurea (yes v.s. no) 42.1 DPP4 inhibitor (yes v.s. no) 63.1 Glucophage (yes v.s. no) 84.4 SGLT2 inhibitor (yes v.s. no) 2.8 Actos (yes v.s. no) 27.3 Insulin (yes v.s. no) 15.6 Statin (yes v.s. no) 43.5 Calcium channel blocker (yes v.s. no) 22.9 Beta blocker (yes v.s. no) 19.2 ACEI/ARB (yes v.s. no) 38.3 Short chain fatty acid Formate, µM 125.0(89.9,213.9) Acetate, µM 97.8(75.1,134.0) Propionate, µM 15.4(11.8,21.4) Butyrate, µM 8.1(6.1,9.6) Isobutyrate, µM 7.7(5.4,12.5) Methylbutyrate, µM 6.2(4.5,13.7) Valerate, µM 2.7(1.7,4.8) Isovalerate, µM 17.7(4.0,24.8) Methylvalerate, µM 1.4(0.7,3.1) Laboratory parameters Albumin, g/dl 4.6 ± 3.1 Hemoglobin, g/dl 13.8 ± 1.6 Uric acid, mg/dl 5.8 ± 1.5 GOT, IU/dl 30.4 ± 15.0 GPT, IU/dl 33.8 ± 25.3 Creatinine, mg/dl 0.9 ± 0.4 eGFR, ml/1.73m 2 /yr 82.2 ± 28.3 Cholesterol, mg/dl 168.8 ± 37.4 Triglyceride, mg/dl 120.5(86.0,177.7) HbA1c, % 7.0(6.5,7.9) Urinary ACR, mg/g 16.2(6.4,66.6) Data are expressed as numbers (percentages) for categorical variables and means ± SDs or medians (25th, 75th percentiles) for continuous variables as appropriate. Abbreviations: ACEI, angiotensin converting enzyme inhibitors; ACR, albumin-creatinine ratio; ARB, angiotensin II receptor blockers; DM, diabetes mellitus; DPP-4, dipeptidyl peptidase 4; eGFR, estimated glomerular filtration rate; GOT, glutamate oxaloactate transminase; GPT, glutamate pyruvate transaminase;HbA1c, glycated hemoglobin; SGLT2, sodium–glucose cotransporter 2; T2D, type 2 diabetes mellitus Serum SCFA Levels and Doubling of Serum Creatinine Levels or ESKD Over a mean follow-up period of 3.9 years, 20 patients (4.2%) experienced either a doubling of serum creatinine or progression to ESKD, with 18 patients (3.8%) reaching creatinine doubling, 3 patients (0.6%) progressing to ESKD, or 13 patients (2.7%) dying (Table 2 ). Table 2 The Association Between Serum SCFA and Primary Kidney Outcome in Type 2 Diabetes Patients Event N (%) Follow-up period (years) Event per 1000 patient-year Crude HR (95% CI) P Adjusted HR 1 (95%CI) P ESKD or doubling of serum creatinine 20/480(4.2) Serum propionate level propionate tertile 1 and 2 (≤ 18.91 µM) 18/320(5.6) 3.95 ± 0.85 14.25 1.00(Reference) 0.035 1.00(Reference) 0.014 propionate tertile 3 (> 18.91 µM) 2/160(1.3) 3.87 ± 1.04 3.23 0.21(0.05–0.89) 0.14(0.03–0.66) Serum butyrate level butyrate tertile 1 and 2 (≤ 8.90 µM) 17/320(5.3) 3.94 ± 0.84 13.10 1.00(Reference) 0.076 1.00(Reference) 0.023 butyrate tertile 3 (> 8.90 µM) 3/160 (1.9) 3.88 ± 1.05 5.13 0.33(0.10–1.12) 0.21(0.05–0.80) Serum formate level formate tertile 1 and 2 (≤ 163.34 µM) 15/321(4.0) 3.60 ± 0.88 11.80 1.00(Reference) 0.166 1.00(Reference) 0.012 formate tertile 3 (> 163.34 µM) 5/159(4.4) 4.56 ± 0.61 8.18 0.51(0.20–1.32) 0.25(0.09–0.74) Abbreviations: ESKD, end stage kidney disease; eGFR, estimated glomerular filtration rate; HR, hazard ratio; CI, Confidence interval. 1 The multivariable model was adjusted for age, sex, ACEI/ARB usage, HbA1C, baseline serum creatinine, log form urinary albumin/creatinine ratio Univariate Cox regression analysis assessed the relationship between serum SCFA tertiles and the primary kidney outcomes (creatinine doubling or ESKD). Among the nine SCFAs measured, only tertile 3 of serum propionate showed a significant inverse association with the primary kidney outcomes compared to tertiles 1 and 2 (HR: 0.21, 95% CI: 0.05–0.89, p = 0.035; Table 2 ). No significant associations were observed for the other eight SCFAs (Tables S1 and S2). After controlling for traditional risk factors such as sex, age, ACEI/ARB use, baseline creatinine, UACR, and HbA1c, patients in tertile 3 of serum propionate, butyrate, and formate showed significantly lower risks of reaching a primary outcome. Specifically, risk reductions were 86% for propionate (HR = 0.14, 95% CI = 0.03–0.66, p = 0.014), 79% for butyrate (HR = 0.21, 95% CI = 0.05–0.80, p = 0.023), and 75% for formate (HR = 0.25, 95% CI = 0.09–0.74, p = 0.012) compared to those in tertiles 1 and 2 (Table 2 ). Kaplan-Meier survival curves further demonstrated a significantly lower cumulative incidence of primary outcomes among patients in tertile 3 of propionate, butyrate, and formate compared to those in lower tertiles (p for trend = 0.014, 0.025, and 0.012, respectively; Fig. 1 A–C). Specifically, patients in tertile 3 of propionate had the lowest risk of experiencing a primary kidney outcome. Model performance for predicting primary outcomes based on serum formate, propionate, butyrate, UACR, and eGFR is illustrated in scatter plots (Fig. 2 A–E), showing observed versus predicted events. Predictions based on formate, propionate, and butyrate closely aligned with observed outcomes, as indicated by data clustering along the identity line (Fig. 2 A–C). The nonsignificant Hosmer-Lemeshow tests further confirmed good model calibration for these SCFAs (p = 0.35 for formate, p = 0.49 for propionate, and p = 0.54 for butyrate). In contrast, UACR (Fig. 2 D) and eGFR (Fig. 2 E) models showed significant miscalibration (p = 0.019 for UACR and p = 0.004 for eGFR), with observed outcomes deviating from predictions. Serum SCFA Levels and Rapid Decline in Kidney Function During the follow-up period, 71 (14.8%) patients had a decline in eGFR decline > 5 ml/min/1.73 m 2 per year and 66 (13.8%) had a decline in eGFR of 25% or more. Among the nine SCFAs, compared to tertile 1 and 2, tertile 3 of serum propionate (odds ratio (OR) = 0.44, 95% CI = 0.24–0.82, p = 0.01), butyrate (OR = 0.49, 95% CI = 0.27–0.90, p = 0.02), formate (OR = 0.54, 95% CI = 0.29–0.98, p = 0.042), and valerate (OR = 0.49, 95% CI = 0.27–0.90, p = 0.022) levels were significantly and negatively associated with eGFR decline > 5 ml/min/1.73 m 2 per year in univariate logistic regression (Table 3 ). The other five SCFAs were not correlated with eGFR decline > 5 ml/min/1.73 m 2 per year (Table S3). Adjusted logistic analysis showed that the patients in tertile 3 of serum propionate (OR = 0.38, 95% CI = 0.20–0.74, p = 0.004), butyrate (OR = 0.41, 95% CI = 0.21–0.77, p = 0.006), formate (OR = 0.46, 95% CI = 0.24–0.89, p = 0.022) and valerate (OR = 0.42, 95% CI = 0.22–0.80, p = 0.008) had reductions of 62%, 59%, 54%, and 58%, respectively, in the risk of eGFR decline > 5 ml/min/1.73 m 2 per year (Table 3 ). In addition, tertile 3 of serum propionate (OR = 0.48, 95% CI = 0.25–0.94, p = 0.032) and butyrate (OR = 0.50, 95% CI = 0.26–0.96, p = 0.038) in adjusted logistic analysis were negatively associated with a decline in eGFR of 25% or more during the follow-up period (Table 3 ). However, the other SCFAs were not related to a decline in eGFR of 25% or more during the follow-up period. Table 3 The Association Between Serum SCFA and Secondary Kidney Outcome in Type 2 Diabetes Patients Event N(%) Crude OR(95% CI) P Adjusted OR 1 (95%CI) P eGFR decline > 5ml/min/1.73m2/year 71/480(14.8) Serum propionate level propionate tertile 1 and 2 (≤ 18.91 µM) 57/320(17.8) 1.00(Reference) 0.010 1.00(Reference) 0.004 propionate tertile 3 (> 18.91 µM) 14/160(8.8) 0.44(0.24–0.82) 0.38(0.20–0.74) Serum butyrate level butyrate tertile 1 and 2 (≤ 8.90 µM) 56/320(17.5) 1.00(Reference) 0.020 1.00(Reference) 0.006 butyrate tertile 3 (> 8.90 µM) 15/160(9.4) 0.49(0.27–0.90) 0.41(0.21–0.77) Serum formate level formate tertile 1 and 2 (≤ 163.34 µM) 55/320(17.2) 1.00(Reference) 0.042 1.00(Reference) 0.022 formate tertile 3 (> 163.34 µM) 16/160(10.0) 0.54(0.29–0.98) 0.46(0.24–0.89) Serum valerate level valerate tertile 1 and 2 (≤ 3.93µM) 56/320(17.5) 1.00(Reference) 0.022 1.00(Reference) 0.008 valerate tertile 3 (> 3.93µM) 15/160(9.4) 0.49(0.27–0.90) 0.42(0.22–0.80) 25% eGFR decline 66 (13.8%) Serum propionate level propionate tertile 1 and 2 (≤ 18.91 µM) 57/320 (17.8) 1.00(Reference) 0.052 1.00(Reference) 0.032 propionate tertile 3 (> 18.91 µM) 14/160 (8.8) 0.55(0.30-1.00) 0.48(0.25–0.94) Serum butyrate level butyrate tertile 1 and 2 (≤ 8.90 µM) 56/320 (17.5) 1.00(Reference) 0.094 1.00(Reference) 0.038 butyrate tertile 3 (> 8.90 µM) 15/160 (9.4) 0.60(0.33–1.09) 0.50(0.26–0.96) Serum formate level formate tertile 1 and 2 (≤ 163.34 µM) 55/320(17.2) 1.00(Reference) 0.278 1.00(Reference) 0.106 formate tertile 3 (> 163.34 µM) 16/160 (10.1) 0.73(0.41–1.30) 0.57(0.29–1.13) Serum valerate level valerate tertile 1 and 2 (≤ 3.93µM) 56/320 (17.4) 1.00(Reference) 0.278 1.00(Reference) 0.111 valerate tertile 3 (> 3.93µM) 15/160 (9.4) 0.73(0.41–1.30) 0.59(0.31–1.13) Abbreviations: eGFR, estimated glomerular filtration rate; OR, odds ratio; CI, Confidence interval. 1 The multivariable model was adjusted for age, sex, ACEI/ARB usage, HbA1C, baseline serum creatinine, log form urinary albumin/creatinine ratio Subgroup Analysis of Serum SCFA Levels and Rapid Decline in Kidney Function To explore whether age, sex, baseline kidney function, and glycemic control influenced the associations between circulating propionate, butyrate, formate, and valerate levels and rapid kidney function decline, subgroup analyses were performed by stratifying patients by age (< 65 years vs. ≥65), sex (female vs. male), baseline eGFR (7%) (Fig. 3 A–D). Compared to tertiles 1 and 2, significant negative associations were found between tertile 3 of serum propionate and valerate levels and eGFR decline > 5 ml/min/1.73 m 2 per year in the female, age 5 ml/min/1.73 m 2 per year in the male, age 5 ml/min/1.73 m 2 per year were found in the eGFR ≥ 60 ml/min/1.73 m 2 and HbA1c > 7% subgroups. Discussion This prospective longitudinal study was to explore associations between serum levels of SCFAs and adverse kidney outcomes in patients with T2D, including progression to ESKD, doubling of serum creatinine level, and rapid kidney function decline. After adjusting for risk factors known to be associated with adverse kidney outcomes, the patients with high circulating SCFA levels, and especially propionate, butyrate, formate and valerate, had lower risks of adverse renal outcomes compared to those with low circulating SCFA levels. This inverse association between circulating SCFA levels and adverse kidney outcomes was also found in subgroup analysis in the patients aged < 65 years, those with preserved baseline kidney function, and those with well-controlled glucose levels. Furthermore, reclassification ability and calibration analysis showed that levels of SCFAs, mainly propionate, butyrate, and formate, could potentially be reliable biomarkers along with UACR and eGFR to predict adverse kidney outcomes. The primary finding of this prospective study is that serum SCFA levels were negatively correlated with a rapid decline in kidney function in T2D patients. Previous reports exploring the association between SCFAs and kidney function have been limited to cross-sectional studies. 13 , 14 Wang et al. reported that butyrate levels were lower in patients with CKD stage 5 than in normal individuals, and that butyrate supplements may have delayed kidney progression in a CKD rat model. 13 In addition, Li et al identified associations between significant decreases in propionic acid and butyric acid levels and progression of diabetic kidney disease (DKD) in an in-vivo model. 14 In another study, DKD patients were found to have lower fecal propionate, butyrate and acetate levels compared to normal individuals, and fecal and serum acetate levels were correlated with eGFR. 7 However, the prognostic impact of SCFAs on kidney outcomes in T2D patients has not been well-explored in longitudinal studies. Our findings showed that circulating SCFA levels, mainly propionate, butyrate, formate and valerate, had inverse correlations with adverse kidney outcomes including rapid decline in kidney function, doubling of serum creatinine levels or progression to ESKD, and that they could decrease the risk of poor kidney progression in T2D patients. Interestingly, this inverse association was also consistent in those aged < 65 years, with an eGFR ≥ 60 ml/min/1.73 m 2 , or HbA1c ≤ 7.0% in subgroup analysis, but not in those aged ≥ 65 years, with an eGFR 7.0%. This suggests that SCFAs may have a protective impact against a rapid decline in kidney function in T2D patients who are younger, with good baseline kidney function, or well-controlled glucose level. A previous study reported decreases in the abundance of SCFA-producing genera and SCFAs with increasing age. 15 Therefore, SCFA supplements may be given greater consideration in older people. Aging itself is known to be play an important role in the decline in kidney function. Our findings demonstrated an inverse association between SCFA levels and adverse kidney outcomes in younger T2D patients, suggesting that in older patients with impaired baseline kidney function, the impact of aging on kidney disease progression may outweigh the protective effects of SCFAs. Strict glycemic control is known to help prevent the onset and progression of both macrovascular and microvascular complications in patients with T2D. 16 Conversely, some studies have indicated that intensive glycemic control alone may not be sufficient to prevent adverse kidney outcomes. 17 Our results show the potential of SCFAs to prevent adverse kidney outcomes in various subgroups of T2D individuals, and we could precisely understand the role of SCFAs in personalized DKD progression. Growing body of evidence has revealed the therapeutic potential of SCFAs, including propionate and butyrate, to protect against CKD in in vivo and in vitro models. 18–22 Propionate and butyrate supplements were shown to significantly mitigate impaired kidney function in a CKD animal model, 19, 21 and they were shown to suppress the expressions of pro-inflammatory factors (such as TNF-α, IL-1β, MCP-1, and IL-6) and fibrosis-related genes (such as TGF-β, Col-1a, and Col-3), and enhance intestinal barrier function and mucosal immunity in mouse kidneys. 19 , 23 – 25 In addition, butyrate was shown to alleviate kidney failure in a CKD animal model by improving 5'adenosine monophosphate-activated protein kinase phosphorylation, promoting colonic mucin and tight junction proteins, and increasing glucagon-like peptide-1 secretion. 26 In another DKD animal model, butyrate was shown to inhibit oxidative stress and inflammatory gene expressions, and then ameliorate kidney fibrosis and pathological changes by inhibiting HDAC. 18 Moreover, butyrate has been reported to partially alleviate T2D-related kidney injury by inhibiting oxidative stress and nuclear factor kappa B signaling via GPR43 activation in DKD mice. 20 Taken together, the data from these animal studies suggests that SCFAs, especially propionate and butyrate, may reduce the risk of a decline in kidney function in patients with CKD or DKD. However, the impact of SCFAs on kidney outcomes in humans, particularly those with T2D, remains largely unclear. Our findings demonstrated the protective effects of propionate and butyrate against kidney function decline in our T2D cohort, highlighting their potential as both therapeutic agents and predictive biomarkers for kidney injury in T2D patients. In addition to propionate and butyrate, we also found that circulating formate level was negatively associated with ESKD or doubling of serum creatinine, and that circulating formate and valerate levels were inversely related with a rapid decline in kidney function. Formate and valerate have not traditionally been considered to be of particular clinical significance among clinical physicians, and few reports have discussed their physiological effects on kidney disease. Formate, a single-carbon molecule, serves as a mediator of metabolic interactions between the host and the gut microbiome. 27 It is believed to be an endogenous byproduct of amino acids in mitochondria 27 , and reduced formate levels may induce oxidative stress response and aggravate mitochondrial dysfunction. 28 Valerate, a five-carbon molecule, is the salt of a straight-chain alkyl carboxylic acid, and it is considered to be an important modulator of immune response, oxidative stress, and inflammation pathways. 29 , 30 We found that high circulating valerate levels may lower the risk of accelerated kidney function loss, which is consistent with the findings of Zhong et al. 31 Taken together, we speculate that propionate, butyrate, formate, and valerate may exert a therapeutic effect on DKD. Additional translational studies are required to evaluate the potential of SCFAs, particularly propionate, butyrate, formate, and valerate, as prognostic biomarkers and therapeutic targets for the prevention and management of kidney complications in T2D individuals. This study has some limitations that should be considered. First, the biological samples and clinical data were derived from a single medical center, which may limit the generalizability of the findings. Second, only single baseline serum SCFA level and covariate data were measured, and thus their time-variant effects on kidney outcomes may be underestimated. In addition, the observational design of our study means that we cannot draw conclusions regarding causality, and further studies are needed to clarify this issue. Although general dietary patterns were documented, the lack of detailed data on energy intake and specific food components may have underestimated the influence of diet on host SCFA production. Furthermore, this study follow-up was conducted up to 2021, which is another limitation as it does not account for the impact of more recent therapies. Conclusively, our results indicate that elevated circulating SCFA levels, and mainly propionate, butyrate, formate, and valerate, were associated with a decreased risk of adverse kidney outcomes in T2D patients, especially in those who were younger, with proper glycemic control, and preserved baseline kidney function. Our results suggest that SCFAs, together with eGFR and UACR, may serve as dependable indicators for predicting adverse kidney outcomes in patients with T2D. Further studies are needed to clarify our findings and the role of SCFAs in adverse kidney outcomes, which could contribute to the development of new therapeutic approaches for preventing and managing adverse kidney outcomes in T2D patients. Declarations Authors’ contributions Conception or design: Yi-Chun Tsai, Wei-Wen Hung, Wei-Chun Hung, Shang-Jyh Hwang, Ping-Hsun Wu, Mei-Chuan Kuo Acquisition, analysis, or interpretation of data: Ping-Shaou Yu, Yi-Chun Tsai, Hui-Ju Tsai Drafting the work or revising: Hui-Ju Tsai Final approval of the manuscript: Hui-Ju Tsai, Yi-Chun Tsai Funding This study was funded by grants from Kaohsiung Medical University Hospital, Kaohsiung, Taiwan (KMUH-112-2R30, KMUH-113-3R26, KMUH-113-R010), and from National Science and Technology Council (NSTC 113-2314-B-037-071). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper References Deng Y, Li N, Wu Y, et al. 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Dong W, Jia Y, Liu X, et al. Sodium butyrate activates NRF2 to ameliorate diabetic nephropathy possibly via inhibition of HDAC. J Endocrinol Jan. 2017;232(1):71–83. Ma X, Fan PX, Li LS, Qiao SY, Zhang GL, Li DF. Butyrate promotes the recovering of intestinal wound healing through its positive effect on the tight junctions. J Anim Sci Dec. 2012;90(Suppl 4):266–8. Marzocco S, Fazeli G, Di Micco L et al. Supplementation of Short-Chain Fatty Acid, Sodium Propionate, in Patients on Maintenance Hemodialysis: Beneficial Effects on Inflammatory Parameters and Gut-Derived Uremic Toxins, A Pilot Study (PLAN Study). J Clin Med Sep 30 2018;7(10). Magliocca G, Mone P, Di Iorio BR, Heidland A, Marzocco S. Short-Chain Fatty Acids in Chronic Kidney Disease: Focus on Inflammation and Oxidative Stress Regulation. Int J Mol Sci May 11 2022;23(10). Gonzalez A, Krieg R, Massey HD, et al. Sodium butyrate ameliorates insulin resistance and renal failure in CKD rats by modulating intestinal permeability and mucin expression. Nephrol Dial Transpl May. 2019;1(5):783–94. Hughes ER, Winter MG, Duerkop BA, et al. Microbial Respiration and Formate Oxidation as Metabolic Signatures of Inflammation-Associated Dysbiosis. Cell Host Microbe Feb. 2017;8(2):208–19. Xu W, Xue W, Zhou Z, et al. Formate Might Be a Novel Potential Serum Metabolic Biomarker for Type 2 Diabetic Peripheral Neuropathy. Diabetes Metab Syndr Obes. 2023;16:3147–60. Jayaraj RL, Beiram R, Azimullah S et al. Valeric Acid Protects Dopaminergic Neurons by Suppressing Oxidative Stress, Neuroinflammation and Modulating Autophagy Pathways. Int J Mol Sci Oct 16 2020;21(20). Luu M, Pautz S, Kohl V, et al. The short-chain fatty acid pentanoate suppresses autoimmunity by modulating the metabolic-epigenetic crosstalk in lymphocytes. Nat Commun Feb. 2019;15(1):760. Zhong C, Bai X, Chen Q, et al. Gut microbial products valerate and caproate predict renal outcome among the patients with biopsy-confirmed diabetic nephropathy. Acta Diabetol Nov. 2022;59(11):1469–77. Supplementary Files SupplementaryTable.docx graphicfigure.jpg Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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15:58:02","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":119140,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/ae717a74f23da286f79be8d2.html"},{"id":94213117,"identity":"37eff67e-3199-49ed-ba48-2f95ab9de60a","added_by":"auto","created_at":"2025-10-23 15:58:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":322202,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier curves of primary kidney outcome (doubling of serum creatinine or dialysis) by baseline serum short-chain fatty acids (A) propionate (B) butyrate (C) formate) level (tertile 3 v.s. tertile 1+2) in type 2 diabetes patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/e432c2c2979502048b798a76.jpeg"},{"id":94211936,"identity":"f05fe4ba-1e90-43d2-adff-02fbdf4fd054","added_by":"auto","created_at":"2025-10-23 15:50:01","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":406803,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCalibration plots for serum short-chain fatty acids (A) formate, (B) propionate, (C) butyrate, (D) UACR, and (E) eGFR in predicting primary kidney outcome (doubling of serum creatinine or dialysis) in type 2 diabetes patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: eGFR, estimated glomerular filtration rate; urinary albumin/creatinine ratio (UACR)\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/dabf8424faa6a14aa30d542e.jpeg"},{"id":94213456,"identity":"ee770780-3cdf-4ebc-9ff8-815a4c94bc20","added_by":"auto","created_at":"2025-10-23 16:06:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":280175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubgroup analysis of association between serum short-chain fatty acids (A) propionate, (B) butyrate, (C) formate, (D) valerate level (tertile 3 v.s. tertile 1+2) and eGFR decline \u0026gt; 5ml/min/1.73m2/year in type 2 diabetes patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: T2D, type 2 diabetes; AOR, adjusted odds ratio; angiotensin-converting enzyme inhibitors (ACEIs); angiotensin II receptor blockers (ARBs); CI, Confidence interval; eGFR, estimated glomerular filtration rate; HbA1c, Glycated hemoglobin; urinary albumin/creatinine ratio (UACR)\u003c/p\u003e\n\u003cp\u003eadjusted odds ratio was adjusted for for age, sex, ACEI/ARB usage, HbA1C, baseline serum creatinine, log form UACR\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/1dda689b1d6cdb2703137639.png"},{"id":94612589,"identity":"e1566bbd-4c2f-4c70-91b1-4631fce68e42","added_by":"auto","created_at":"2025-10-29 02:11:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2283417,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/44e14746-72af-4878-aab4-805b3fe75aa2.pdf"},{"id":94211940,"identity":"ddf58a9d-320e-45a8-a4e9-2fa955a32bf6","added_by":"auto","created_at":"2025-10-23 15:50:01","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":25001,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/9a9961600e43ed47f566e2e0.docx"},{"id":94211949,"identity":"b7e328d7-7fe1-4cc5-9967-51cd2805c259","added_by":"auto","created_at":"2025-10-23 15:50:02","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":278262,"visible":true,"origin":"","legend":"","description":"","filename":"graphicfigure.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7791885/v1/132c2902144a069d7ecbc533.jpg"}],"financialInterests":"","formattedTitle":"Trajectories of Short-Chain Fatty Acids and Risk of Adverse Kidney Outcomes in Type 2 Diabetes: A Prospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes presents a major global health challenge and imposes a substantial economic burden on healthcare systems. Type 2 diabetes (T2D) is the main cause of chronic kidney disease (CKD) and end-stage kidney disease (ESKD).\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The prevalence of chronic kidney disease (CKD) related to Type 2 diabetes (T2D) rose from 1.39% in 1999 to 1.74% in 2019, marking a significant increase in the number of affected individuals over the two-decade period.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Identifying novel biomarkers for kidney failure in T2D patients could allow for the early detection of individuals at risk and the development of tailored treatment strategies, ultimately enhancing patient outcomes and alleviating the burden on healthcare systems.\u003c/p\u003e\u003cp\u003eShort-chain fatty acids (SCFAs) are volatile fatty acids generated by gut bacteria through the fermentation of dietary fiber. Carbohydrates are the primary source of short-chain fatty acids (SCFAs); however, amino acids such as valine, leucine, and isoleucine\u0026mdash;derived from protein breakdown\u0026mdash;can be converted into branched-chain SCFAs, including isobutyrate, isovalerate, and 2-methyl butyrate, which account for approximately 5% of total SCFA production.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e SCFAs influence glucose metabolism, insulin sensitivity, and lipogenesis through multiple pathways, thereby playing a role in the development of obesity, diabetes, and other metabolic disorders.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Previous studies have suggested that the gut microbiota and kidneys interact via a gut-kidney axis, and that this axis also participates in the kidney injury process.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e SCFAs, key metabolites produced through gut microbiota-mediated fermentation of dietary fiber, have garnered significant attention for their biological effects. Despite growing interest, the potential of circulating SCFA levels as biomarkers for kidney disease progression in clinical T2D population remains insufficiently studied. This study, therefore, aimed to examine the associations between circulating SCFA levels and adverse kidney outcomes in individuals with T2D.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Subjects\u003c/h2\u003e\u003cp\u003e Participants with T2D attending the outpatient departments of Kaohsiung Medical University Hospital (KMUH) were invited to participate in this prospective study from October 2016 to June 2020. This study has been described in detail previously.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In brief, T2D was diagnosed based on medical history, American Diabetes Association-defined blood glucose levels, or prescriptions for anti-diabetic medications. All of the enrolled patients received a diabetes education program and adhered to the recommended dietary guidelines for individuals with diabetes. Estimated glomerular filtration rate (eGFR) was determined using the 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e The exclusion criteria were eGFR below 30 ml/min/1.73 m\u0026sup2;, acute illness, and the use of antimicrobial or probiotic agents in the month prior to enrollment. Approval for this study was granted by the Institutional Review Board of KMUH (KMUHIRB-G(II)-20160021, KMUHIRB-G(II)-20150044, KMUHIRB-G(II)-20190036). All of the enrolled patients provided written informed consent, and the study was conducted following the principles of the Declaration of Helsinki.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eThe following information was obtained through patient interviews and review of medical records at the time of enrollment: demographics, smoking and alcohol history, brief dietary recall about the preference for a plant-based diet or animal-based diet, and clinical information. Hypertension was diagnosed based on medical history or prescriptions for antihypertensive medications. Patients with a history of acute/chronic ischemic heart disease, myocardial infarction, or heart failure were classified as having heart disease. Body mass index was calculated as body weight/height\u003csup\u003e2\u003c/sup\u003e. Data on medication usage were recorded from medical records before and after enrollment, including anti-diabetic drugs, insulin, anti-hypertensive drugs, and statins.\u003c/p\u003e\u003cp\u003eTwelve-hour fasting blood and urine samples were obtained for biochemical analysis. Serum creatinine was measured using the compensated Jaff\u0026eacute; method (kinetic alkaline picrate) with an autoanalyzer (Roche/Integra 400, Roche Diagnostics), calibrated against an isotope-dilution mass spectrometry standard (Vickery, Stevens, Dalton, van Lente, \u0026amp; Lamb, 2006). The urinary albumin/creatinine ratio (UACR) was used to express the amount of protein in urine.\u003c/p\u003e\n\u003ch3\u003eMeasurement of Serum SCFA Levels\u003c/h3\u003e\n\u003cp\u003eThe detailed method for measurement of circulating SCFAs was described in previous study.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In brief, serum levels of the following SCFAs: methylvalerate, isovalerate, valerate, formate, methylbutyrate, isobutyrate, butyrate, propionate, and acetate, were quantified using liquid chromatography\u0026ndash;mass spectrometry (LC-MS). Briefly, 50 \u0026micro;L of serum was mixed with 20 \u0026micro;L of 200 mM 3-nitrophenylhydrazine hydrochloride and 20 \u0026micro;L of 120 mM N-(3-dimethylaminopropyl)-N\u0026prime;-ethylcarbodiimide hydrochloride in 6% pyridine, both prepared in 100% aqueous methanol. The mixture was incubated at 40\u0026deg;C for 30 minutes. After the reaction, the volume was adjusted to 210 \u0026micro;L with 10% aqueous methanol. Then, 25 \u0026micro;L of internal standard solution was added to 75 \u0026micro;L of the prepared sample, and a 10 \u0026micro;L aliquot was analyzed by LC-MS/MS.\u003c/p\u003e\u003cp\u003eAll detection and quantification were performed using a Waters ACQUITY UPLC system (Waters Corporation, Milford, MA) coupled with a tandem mass spectrometer (Finnigan TSQ Quantum Ultra, Thermo Scientific, San Jose, CA) operated with Xcalibur software (Thermo Scientific, San Jose, CA). The system employed an electrospray ionization source in positive mode. A 10 \u0026micro;L sample was filtered and injected into an ACQUITY UPLC BEH C18 column (130 \u0026Aring;, 1.7 \u0026micro;m, 2.1 \u0026times; 100 mm; Waters Corporation, Milford, MA) with a flow rate of 300 \u0026micro;L/min at a column temperature of 40\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eClinical Outcomes of the Patients\u003c/h3\u003e\n\u003cp\u003ePatients were followed until they reached a primary or secondary kidney outcome, died, were lost to follow-up, or until the end of the study period (December 2021). Outpatient clinic visits occurred every three months, during which clinical status and eGFR were evaluated. Only outpatient data were included in the analysis; information from hospitalizations or acute kidney injury events was excluded. The primary kidney outcomes were defined as either a doubling of serum creatinine or progression to ESKD. Secondary outcomes included a decline in eGFR of more than 5 mL/min/1.73 m\u0026sup2; per year or a 25% reduction from baseline during the follow-up period. \u003csup\u003e10\u003c/sup\u003e The annual eGFR change, referred to as the eGFR slope, was calculated using the regression coefficient of eGFR over time and expressed in mL/min/1.73 m\u0026sup2; per year. All available eGFR measurements from enrollment through the end of follow-up were used to calculate these outcomes. Percentage change in eGFR was determined by comparing the first and last recorded values.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDifferences in continuous variables between groups were evaluated using independent t-tests or Mann-Whitney U tests, while categorical variables were compared using chi-square tests. Continuous variables with non-normal distributions were log10-transformed to approximate normality. Person-time was calculated from enrollment to the occurrence of a primary kidney outcome or the end of follow-up. Kaplan-Meier survival analysis was used to assess the relationship between serum SCFA levels and the cumulative risk of kidney outcomes, while Cox proportional hazards models evaluated the relationships between SCFA levels and primary kidney outcomes. Model fit was assessed using the Hosmer-Lemeshow test for models including SCFAs, eGFR, and UACR in predicting primary kidney outcome.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Logistic regression analyses were performed to examine the associations between serum SCFA levels and rapid kidney function decline, defined as an annual eGFR loss of more than 5 mL/min/1.73 m\u0026sup2; or a 25% reduction in eGFR during follow-up. Multivariable models adjusted for traditional risk factors, including age, sex, use of angiotensin-converting enzyme inhibitors (ACEIs), use of angiotensin II receptor blockers (ARBs), baseline serum creatinine, log-transformed UACR, and glycated hemoglobin (HbA1c). Subgroup analyses explored potential effect modifiers in the association between SCFA tertiles and rapid kidney function decline, stratified by age (\u0026ge;\u0026thinsp;65 or \u0026lt;\u0026thinsp;65 years), sex (male or female), eGFR (\u0026lt;\u0026thinsp;60 or \u0026ge;\u0026thinsp;60 mL/min/1.73 m\u0026sup2;), HbA1c (\u0026le;\u0026thinsp;7% or \u0026gt;\u0026thinsp;7%), and UACR (\u0026lt;\u0026thinsp;30 mg/g or \u0026ge;\u0026thinsp;30 mg/g). All statistical analyses were conducted using SPSS version 22 (IBM Inc., Armonk, NY) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed p-value of less than 0.05 was regarded as statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eCharacteristics of the Patients\u003c/h2\u003e\u003cp\u003eThe study included 480 patients with T2D, with a mean age of 62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1 years, and 54.6% of them were male (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The average duration of T2D was 10.2 years. Hyperlipidemia and hypertension and hyperlipidemia were present in 80.7 and 59.6% of the participants, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean eGFR was 82.2 mL/min/1.73 m\u0026sup2;, while the median UACR and HbA1c were 16.2 mg/g and 7.0%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe characteristics of study type 2 diabetes patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEntire Cohort (n\u0026thinsp;=\u0026thinsp;480)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (male), %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoke, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGout, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT2D duration, year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiet habit, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein more than fiber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFiber more than protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFiber equal to protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMedication\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSulfonylurea (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDPP4 inhibitor (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlucophage (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSGLT2 inhibitor (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActos (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStatin (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium channel blocker (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeta blocker (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEI/ARB (yes v.s. no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShort chain fatty acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125.0(89.9,213.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97.8(75.1,134.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePropionate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.4(11.8,21.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eButyrate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.1(6.1,9.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIsobutyrate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.7(5.4,12.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethylbutyrate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.2(4.5,13.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eValerate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.7(1.7,4.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIsovalerate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.7(4.0,24.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethylvalerate, \u0026micro;M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.4(0.7,3.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLaboratory parameters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlbumin, g/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin, g/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid, mg/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGOT, IU/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGPT, IU/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreatinine, mg/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eeGFR, ml/1.73m\u003csup\u003e2\u003c/sup\u003e/yr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.2\u0026thinsp;\u0026plusmn;\u0026thinsp;28.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol, mg/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e168.8\u0026thinsp;\u0026plusmn;\u0026thinsp;37.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglyceride, mg/dl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120.5(86.0,177.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHbA1c, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.0(6.5,7.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrinary ACR, mg/g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.2(6.4,66.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eData are expressed as numbers (percentages) for categorical variables and means\u0026thinsp;\u0026plusmn;\u0026thinsp;SDs or medians (25th, 75th percentiles) for continuous variables as appropriate.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eAbbreviations: ACEI, angiotensin converting enzyme inhibitors; ACR, albumin-creatinine ratio; ARB, angiotensin II receptor blockers; DM, diabetes mellitus; DPP-4, dipeptidyl peptidase 4; eGFR, estimated glomerular filtration rate; GOT, glutamate oxaloactate transminase; GPT, glutamate pyruvate transaminase;HbA1c, glycated hemoglobin; SGLT2, sodium\u0026ndash;glucose cotransporter 2; T2D, type 2 diabetes mellitus\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSerum SCFA Levels and Doubling of Serum Creatinine Levels or ESKD\u003c/h3\u003e\n\u003cp\u003eOver a mean follow-up period of 3.9 years, 20 patients (4.2%) experienced either a doubling of serum creatinine or progression to ESKD, with 18 patients (3.8%) reaching creatinine doubling, 3 patients (0.6%) progressing to ESKD, or 13 patients (2.7%) dying (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eThe Association Between Serum SCFA and Primary Kidney Outcome in Type 2 Diabetes Patients\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvent\u003c/p\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFollow-up period (years)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEvent per 1000 patient-year\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCrude HR\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAdjusted HR\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eESKD or doubling of serum creatinine\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20/480(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum propionate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18/320(5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2/160(1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21(0.05\u0026ndash;0.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.14(0.03\u0026ndash;0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum butyrate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17/320(5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3/160 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33(0.10\u0026ndash;1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.21(0.05\u0026ndash;0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum formate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15/321(4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5/159(4.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.51(0.20\u0026ndash;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.25(0.09\u0026ndash;0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eAbbreviations: ESKD, end stage kidney disease; eGFR, estimated glomerular filtration rate; HR, hazard ratio; CI, Confidence interval.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e1\u003c/sup\u003eThe multivariable model was adjusted for age, sex, ACEI/ARB usage, HbA1C, baseline serum creatinine, log form urinary albumin/creatinine ratio\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eUnivariate Cox regression analysis assessed the relationship between serum SCFA tertiles and the primary kidney outcomes (creatinine doubling or ESKD). Among the nine SCFAs measured, only tertile 3 of serum propionate showed a significant inverse association with the primary kidney outcomes compared to tertiles 1 and 2 (HR: 0.21, 95% CI: 0.05\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;0.035; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No significant associations were observed for the other eight SCFAs (Tables S1 and S2).\u003c/p\u003e\u003cp\u003eAfter controlling for traditional risk factors such as sex, age, ACEI/ARB use, baseline creatinine, UACR, and HbA1c, patients in tertile 3 of serum propionate, butyrate, and formate showed significantly lower risks of reaching a primary outcome. Specifically, risk reductions were 86% for propionate (HR\u0026thinsp;=\u0026thinsp;0.14, 95% CI\u0026thinsp;=\u0026thinsp;0.03\u0026ndash;0.66, p\u0026thinsp;=\u0026thinsp;0.014), 79% for butyrate (HR\u0026thinsp;=\u0026thinsp;0.21, 95% CI\u0026thinsp;=\u0026thinsp;0.05\u0026ndash;0.80, p\u0026thinsp;=\u0026thinsp;0.023), and 75% for formate (HR\u0026thinsp;=\u0026thinsp;0.25, 95% CI\u0026thinsp;=\u0026thinsp;0.09\u0026ndash;0.74, p\u0026thinsp;=\u0026thinsp;0.012) compared to those in tertiles 1 and 2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eKaplan-Meier survival curves further demonstrated a significantly lower cumulative incidence of primary outcomes among patients in tertile 3 of propionate, butyrate, and formate compared to those in lower tertiles (p for trend\u0026thinsp;=\u0026thinsp;0.014, 0.025, and 0.012, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;C). Specifically, patients in tertile 3 of propionate had the lowest risk of experiencing a primary kidney outcome.\u003c/p\u003e\u003cp\u003eModel performance for predicting primary outcomes based on serum formate, propionate, butyrate, UACR, and eGFR is illustrated in scatter plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;E), showing observed versus predicted events. Predictions based on formate, propionate, and butyrate closely aligned with observed outcomes, as indicated by data clustering along the identity line (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;C). The nonsignificant Hosmer-Lemeshow tests further confirmed good model calibration for these SCFAs (p\u0026thinsp;=\u0026thinsp;0.35 for formate, p\u0026thinsp;=\u0026thinsp;0.49 for propionate, and p\u0026thinsp;=\u0026thinsp;0.54 for butyrate). In contrast, UACR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) and eGFR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE) models showed significant miscalibration (p\u0026thinsp;=\u0026thinsp;0.019 for UACR and p\u0026thinsp;=\u0026thinsp;0.004 for eGFR), with observed outcomes deviating from predictions.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSerum SCFA Levels and Rapid Decline in Kidney Function\u003c/h2\u003e\u003cp\u003eDuring the follow-up period, 71 (14.8%) patients had a decline in eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year and 66 (13.8%) had a decline in eGFR of 25% or more. Among the nine SCFAs, compared to tertile 1 and 2, tertile 3 of serum propionate (odds ratio (OR)\u0026thinsp;=\u0026thinsp;0.44, 95% CI\u0026thinsp;=\u0026thinsp;0.24\u0026ndash;0.82, p\u0026thinsp;=\u0026thinsp;0.01), butyrate (OR\u0026thinsp;=\u0026thinsp;0.49, 95% CI\u0026thinsp;=\u0026thinsp;0.27\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;0.02), formate (OR\u0026thinsp;=\u0026thinsp;0.54, 95% CI\u0026thinsp;=\u0026thinsp;0.29\u0026ndash;0.98, p\u0026thinsp;=\u0026thinsp;0.042), and valerate (OR\u0026thinsp;=\u0026thinsp;0.49, 95% CI\u0026thinsp;=\u0026thinsp;0.27\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;0.022) levels were significantly and negatively associated with eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year in univariate logistic regression (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The other five SCFAs were not correlated with eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year (Table S3). Adjusted logistic analysis showed that the patients in tertile 3 of serum propionate (OR\u0026thinsp;=\u0026thinsp;0.38, 95% CI\u0026thinsp;=\u0026thinsp;0.20\u0026ndash;0.74, p\u0026thinsp;=\u0026thinsp;0.004), butyrate (OR\u0026thinsp;=\u0026thinsp;0.41, 95% CI\u0026thinsp;=\u0026thinsp;0.21\u0026ndash;0.77, p\u0026thinsp;=\u0026thinsp;0.006), formate (OR\u0026thinsp;=\u0026thinsp;0.46, 95% CI\u0026thinsp;=\u0026thinsp;0.24\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;0.022) and valerate (OR\u0026thinsp;=\u0026thinsp;0.42, 95% CI\u0026thinsp;=\u0026thinsp;0.22\u0026ndash;0.80, p\u0026thinsp;=\u0026thinsp;0.008) had reductions of 62%, 59%, 54%, and 58%, respectively, in the risk of eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In addition, tertile 3 of serum propionate (OR\u0026thinsp;=\u0026thinsp;0.48, 95% CI\u0026thinsp;=\u0026thinsp;0.25\u0026ndash;0.94, p\u0026thinsp;=\u0026thinsp;0.032) and butyrate (OR\u0026thinsp;=\u0026thinsp;0.50, 95% CI\u0026thinsp;=\u0026thinsp;0.26\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;0.038) in adjusted logistic analysis were negatively associated with a decline in eGFR of 25% or more during the follow-up period (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, the other SCFAs were not related to a decline in eGFR of 25% or more during the follow-up period.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe Association Between Serum SCFA and Secondary Kidney Outcome in Type 2 Diabetes Patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvent N(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCrude OR(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdjusted OR\u003csup\u003e1\u003c/sup\u003e (95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eeGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5ml/min/1.73m2/year\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71/480(14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum propionate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 1 and 2 (\u0026le;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57/320(17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14/160(8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.44(0.24\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.38(0.20\u0026ndash;0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum butyrate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56/320(17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15/160(9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49(0.27\u0026ndash;0.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.41(0.21\u0026ndash;0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum formate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55/320(17.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16/160(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.54(0.29\u0026ndash;0.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.46(0.24\u0026ndash;0.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum valerate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003evalerate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;3.93\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56/320(17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003evalerate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;3.93\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15/160(9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49(0.27\u0026ndash;0.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.42(0.22\u0026ndash;0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e25% eGFR decline\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66 (13.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum propionate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 1 and 2 (\u0026le;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57/320 (17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epropionate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;18.91 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14/160 (8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.55(0.30-1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.48(0.25\u0026ndash;0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum butyrate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56/320 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebutyrate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;8.90 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15/160 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.60(0.33\u0026ndash;1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.50(0.26\u0026ndash;0.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum formate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55/320(17.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eformate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;163.34 \u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16/160 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.73(0.41\u0026ndash;1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.57(0.29\u0026ndash;1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum valerate level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003evalerate tertile 1 and 2\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;3.93\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56/320 (17.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00(Reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003evalerate tertile 3\u003c/p\u003e\u003cp\u003e(\u0026gt;\u0026thinsp;3.93\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15/160 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.73(0.41\u0026ndash;1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.59(0.31\u0026ndash;1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviations: eGFR, estimated glomerular filtration rate; OR, odds ratio; CI, Confidence interval.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003eThe multivariable model was adjusted for age, sex, ACEI/ARB usage, HbA1C, baseline serum creatinine, log form urinary albumin/creatinine ratio\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup Analysis of Serum SCFA Levels and Rapid Decline in Kidney Function\u003c/h2\u003e\u003cp\u003eTo explore whether age, sex, baseline kidney function, and glycemic control influenced the associations between circulating propionate, butyrate, formate, and valerate levels and rapid kidney function decline, subgroup analyses were performed by stratifying patients by age (\u0026lt;\u0026thinsp;65 years vs. \u0026ge;65), sex (female vs. male), baseline eGFR (\u0026lt;\u0026thinsp;60 mL/min/1.73 m\u0026sup2; vs. \u0026ge;60), and HbA1c (\u0026le;\u0026thinsp;7% vs. \u0026gt;7%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;D). Compared to tertiles 1 and 2, significant negative associations were found between tertile 3 of serum propionate and valerate levels and eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year in the female, age\u0026thinsp;\u0026lt;\u0026thinsp;65 years, eGFR\u0026thinsp;\u0026ge;\u0026thinsp;60 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e, and HbA1c\u0026thinsp;\u0026le;\u0026thinsp;7% subgroups. In addition, significant negative associations were found between tertile 3 of serum butyrate level with eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year in the male, age\u0026thinsp;\u0026lt;\u0026thinsp;65 years, and eGFR\u0026thinsp;\u0026ge;\u0026thinsp;60 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e subgroups. Moreover, inverse relationship between tertile 3 of serum formate level and eGFR decline\u0026thinsp;\u0026gt;\u0026thinsp;5 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e per year were found in the eGFR\u0026thinsp;\u0026ge;\u0026thinsp;60 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e and HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7% subgroups.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective longitudinal study was to explore associations between serum levels of SCFAs and adverse kidney outcomes in patients with T2D, including progression to ESKD, doubling of serum creatinine level, and rapid kidney function decline. After adjusting for risk factors known to be associated with adverse kidney outcomes, the patients with high circulating SCFA levels, and especially propionate, butyrate, formate and valerate, had lower risks of adverse renal outcomes compared to those with low circulating SCFA levels. This inverse association between circulating SCFA levels and adverse kidney outcomes was also found in subgroup analysis in the patients aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years, those with preserved baseline kidney function, and those with well-controlled glucose levels. Furthermore, reclassification ability and calibration analysis showed that levels of SCFAs, mainly propionate, butyrate, and formate, could potentially be reliable biomarkers along with UACR and eGFR to predict adverse kidney outcomes.\u003c/p\u003e\u003cp\u003eThe primary finding of this prospective study is that serum SCFA levels were negatively correlated with a rapid decline in kidney function in T2D patients. Previous reports exploring the association between SCFAs and kidney function have been limited to cross-sectional studies.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Wang et al. reported that butyrate levels were lower in patients with CKD stage 5 than in normal individuals, and that butyrate supplements may have delayed kidney progression in a CKD rat model.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e In addition, Li et al identified associations between significant decreases in propionic acid and butyric acid levels and progression of diabetic kidney disease (DKD) in an in-vivo model.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e In another study, DKD patients were found to have lower fecal propionate, butyrate and acetate levels compared to normal individuals, and fecal and serum acetate levels were correlated with eGFR.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, the prognostic impact of SCFAs on kidney outcomes in T2D patients has not been well-explored in longitudinal studies. Our findings showed that circulating SCFA levels, mainly propionate, butyrate, formate and valerate, had inverse correlations with adverse kidney outcomes including rapid decline in kidney function, doubling of serum creatinine levels or progression to ESKD, and that they could decrease the risk of poor kidney progression in T2D patients.\u003c/p\u003e\u003cp\u003eInterestingly, this inverse association was also consistent in those aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years, with an eGFR\u0026thinsp;\u0026ge;\u0026thinsp;60 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e, or HbA1c\u0026thinsp;\u0026le;\u0026thinsp;7.0% in subgroup analysis, but not in those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years, with an eGFR\u0026thinsp;\u0026lt;\u0026thinsp;60 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e or HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7.0%. This suggests that SCFAs may have a protective impact against a rapid decline in kidney function in T2D patients who are younger, with good baseline kidney function, or well-controlled glucose level. A previous study reported decreases in the abundance of SCFA-producing genera and SCFAs with increasing age.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Therefore, SCFA supplements may be given greater consideration in older people. Aging itself is known to be play an important role in the decline in kidney function. Our findings demonstrated an inverse association between SCFA levels and adverse kidney outcomes in younger T2D patients, suggesting that in older patients with impaired baseline kidney function, the impact of aging on kidney disease progression may outweigh the protective effects of SCFAs. Strict glycemic control is known to help prevent the onset and progression of both macrovascular and microvascular complications in patients with T2D.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Conversely, some studies have indicated that intensive glycemic control alone may not be sufficient to prevent adverse kidney outcomes.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Our results show the potential of SCFAs to prevent adverse kidney outcomes in various subgroups of T2D individuals, and we could precisely understand the role of SCFAs in personalized DKD progression.\u003c/p\u003e\u003cp\u003eGrowing body of evidence has revealed the therapeutic potential of SCFAs, including propionate and butyrate, to protect against CKD in \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e models. \u003csup\u003e18\u0026ndash;22\u003c/sup\u003e Propionate and butyrate supplements were shown to significantly mitigate impaired kidney function in a CKD animal model,\u003csup\u003e19, 21\u003c/sup\u003e and they were shown to suppress the expressions of pro-inflammatory factors (such as TNF-α, IL-1β, MCP-1, and IL-6) and fibrosis-related genes (such as TGF-β, Col-1a, and Col-3), and enhance intestinal barrier function and mucosal immunity in mouse kidneys.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e In addition, butyrate was shown to alleviate kidney failure in a CKD animal model by improving 5'adenosine monophosphate-activated protein kinase phosphorylation, promoting colonic mucin and tight junction proteins, and increasing glucagon-like peptide-1 secretion.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e In another DKD animal model, butyrate was shown to inhibit oxidative stress and inflammatory gene expressions, and then ameliorate kidney fibrosis and pathological changes by inhibiting HDAC.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Moreover, butyrate has been reported to partially alleviate T2D-related kidney injury by inhibiting oxidative stress and nuclear factor kappa B signaling via GPR43 activation in DKD mice.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Taken together, the data from these animal studies suggests that SCFAs, especially propionate and butyrate, may reduce the risk of a decline in kidney function in patients with CKD or DKD. However, the impact of SCFAs on kidney outcomes in humans, particularly those with T2D, remains largely unclear. Our findings demonstrated the protective effects of propionate and butyrate against kidney function decline in our T2D cohort, highlighting their potential as both therapeutic agents and predictive biomarkers for kidney injury in T2D patients.\u003c/p\u003e\u003cp\u003eIn addition to propionate and butyrate, we also found that circulating formate level was negatively associated with ESKD or doubling of serum creatinine, and that circulating formate and valerate levels were inversely related with a rapid decline in kidney function. Formate and valerate have not traditionally been considered to be of particular clinical significance among clinical physicians, and few reports have discussed their physiological effects on kidney disease. Formate, a single-carbon molecule, serves as a mediator of metabolic interactions between the host and the gut microbiome.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e It is believed to be an endogenous byproduct of amino acids in mitochondria \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, and reduced formate levels may induce oxidative stress response and aggravate mitochondrial dysfunction.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Valerate, a five-carbon molecule, is the salt of a straight-chain alkyl carboxylic acid, and it is considered to be an important modulator of immune response, oxidative stress, and inflammation pathways.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e We found that high circulating valerate levels may lower the risk of accelerated kidney function loss, which is consistent with the findings of Zhong et al.\u003csup\u003e31\u003c/sup\u003e Taken together, we speculate that propionate, butyrate, formate, and valerate may exert a therapeutic effect on DKD. Additional translational studies are required to evaluate the potential of SCFAs, particularly propionate, butyrate, formate, and valerate, as prognostic biomarkers and therapeutic targets for the prevention and management of kidney complications in T2D individuals.\u003c/p\u003e\u003cp\u003eThis study has some limitations that should be considered. First, the biological samples and clinical data were derived from a single medical center, which may limit the generalizability of the findings. Second, only single baseline serum SCFA level and covariate data were measured, and thus their time-variant effects on kidney outcomes may be underestimated. In addition, the observational design of our study means that we cannot draw conclusions regarding causality, and further studies are needed to clarify this issue. Although general dietary patterns were documented, the lack of detailed data on energy intake and specific food components may have underestimated the influence of diet on host SCFA production. Furthermore, this study follow-up was conducted up to 2021, which is another limitation as it does not account for the impact of more recent therapies.\u003c/p\u003e\u003cp\u003eConclusively, our results indicate that elevated circulating SCFA levels, and mainly propionate, butyrate, formate, and valerate, were associated with a decreased risk of adverse kidney outcomes in T2D patients, especially in those who were younger, with proper glycemic control, and preserved baseline kidney function. Our results suggest that SCFAs, together with eGFR and UACR, may serve as dependable indicators for predicting adverse kidney outcomes in patients with T2D. Further studies are needed to clarify our findings and the role of SCFAs in adverse kidney outcomes, which could contribute to the development of new therapeutic approaches for preventing and managing adverse kidney outcomes in T2D patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception or design: Yi-Chun Tsai, Wei-Wen Hung, Wei-Chun Hung, Shang-Jyh Hwang,\u0026nbsp;Ping-Hsun Wu, Mei-Chuan Kuo\u003c/p\u003e\n\u003cp\u003eAcquisition, analysis, or interpretation of data: Ping-Shaou Yu, Yi-Chun Tsai, Hui-Ju Tsai\u003c/p\u003e\n\u003cp\u003eDrafting the work or revising: Hui-Ju Tsai\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinal approval of the manuscript: Hui-Ju Tsai, Yi-Chun Tsai\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by grants from Kaohsiung Medical University Hospital, Kaohsiung, Taiwan (KMUH-112-2R30,\u0026nbsp;KMUH-113-3R26, KMUH-113-R010), and from National Science and Technology Council (NSTC 113-2314-B-037-071). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDeng Y, Li N, Wu Y, et al. Global, Regional, and National Burden of Diabetes-Related Chronic Kidney Disease From 1990 to 2019. Front Endocrinol (Lausanne). 2021;12:672350.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang JS, Yen FS, Lin KD, et al. Epidemiological characteristics of diabetic kidney disease in Taiwan. J Diabetes Investig Dec. 2021;12(12):2112\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR\u0026iacute;os-Covi\u0026aacute;n D, Ruas-Madiedo P, Margolles A, de Gueimonde M. Los Reyes-Gavil\u0026aacute;n CG, Salazar N. Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health. Front Microbiol. 2016;7:185.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCummings JH, Pomare EW, Branch WJ, Naylor CP, Macfarlane GT. Short chain fatty acids in human large intestine, portal, hepatic and venous blood. Gut Oct. 1987;28(10):1221\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlaak EE, Canfora EE, Theis S, et al. Short chain fatty acids in human gut and metabolic health. Benef Microbes Sep. 2020;1(5):411\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMandaliya DK, Seshadri S. Short Chain Fatty Acids, pancreatic dysfunction and type 2 diabetes. 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The potential role of the gut microbiota in modulating renal function in experimental diabetic nephropathy murine models established in same environment. Biochim Biophys Acta Mol Basis Dis Jun. 2020;1(6):165764.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu J, Shen H, Lv Y, et al. Age over sex: evaluating gut microbiota differences in healthy Chinese populations. Front Microbiol. 2024;15:1412991.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRodriguez-Gutierrez R, Montori VM. Glycemic Control for Patients With Type 2 Diabetes Mellitus: Our Evolving Faith in the Face of Evidence. Circ Cardiovasc Qual Outcomes Sep. 2016;9(5):504\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShurraw S, Hemmelgarn B, Lin M, et al. Association between glycemic control and adverse outcomes in people with diabetes mellitus and chronic kidney disease: a population-based cohort study. Arch Intern Med Nov. 2011;28(21):1920\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhan S, Jena G. Sodium butyrate, a HDAC inhibitor ameliorates eNOS, iNOS and TGF-beta1-induced fibrogenesis, apoptosis and DNA damage in the kidney of juvenile diabetic rats. Food Chem Toxicol Nov. 2014;73:127\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMikami D, Kobayashi M, Uwada J, et al. Short-chain fatty acid mitigates adenine-induced chronic kidney disease via FFA2 and FFA3 pathways. Biochim Biophys Acta Mol Cell Biol Lipids Jun. 2020;1865(6):158666.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang W, Man Y, Gao C, et al. Short-Chain Fatty Acids Ameliorate Diabetic Nephropathy via GPR43-Mediated Inhibition of Oxidative Stress and NF-kappaB Signaling. Oxid Med Cell Longev. 2020;2020:4074832.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou T, Xu H, Cheng X, et al. Sodium Butyrate Attenuates Diabetic Kidney Disease Partially via Histone Butyrylation Modification. Mediators Inflamm. 2022;2022:7643322.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDong W, Jia Y, Liu X, et al. Sodium butyrate activates NRF2 to ameliorate diabetic nephropathy possibly via inhibition of HDAC. J Endocrinol Jan. 2017;232(1):71\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa X, Fan PX, Li LS, Qiao SY, Zhang GL, Li DF. Butyrate promotes the recovering of intestinal wound healing through its positive effect on the tight junctions. J Anim Sci Dec. 2012;90(Suppl 4):266\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarzocco S, Fazeli G, Di Micco L et al. Supplementation of Short-Chain Fatty Acid, Sodium Propionate, in Patients on Maintenance Hemodialysis: Beneficial Effects on Inflammatory Parameters and Gut-Derived Uremic Toxins, A Pilot Study (PLAN Study). J Clin Med Sep 30 2018;7(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagliocca G, Mone P, Di Iorio BR, Heidland A, Marzocco S. Short-Chain Fatty Acids in Chronic Kidney Disease: Focus on Inflammation and Oxidative Stress Regulation. Int J Mol Sci May 11 2022;23(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGonzalez A, Krieg R, Massey HD, et al. Sodium butyrate ameliorates insulin resistance and renal failure in CKD rats by modulating intestinal permeability and mucin expression. Nephrol Dial Transpl May. 2019;1(5):783\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes ER, Winter MG, Duerkop BA, et al. Microbial Respiration and Formate Oxidation as Metabolic Signatures of Inflammation-Associated Dysbiosis. Cell Host Microbe Feb. 2017;8(2):208\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu W, Xue W, Zhou Z, et al. Formate Might Be a Novel Potential Serum Metabolic Biomarker for Type 2 Diabetic Peripheral Neuropathy. Diabetes Metab Syndr Obes. 2023;16:3147\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJayaraj RL, Beiram R, Azimullah S et al. Valeric Acid Protects Dopaminergic Neurons by Suppressing Oxidative Stress, Neuroinflammation and Modulating Autophagy Pathways. Int J Mol Sci Oct 16 2020;21(20).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuu M, Pautz S, Kohl V, et al. The short-chain fatty acid pentanoate suppresses autoimmunity by modulating the metabolic-epigenetic crosstalk in lymphocytes. Nat Commun Feb. 2019;15(1):760.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhong C, Bai X, Chen Q, et al. Gut microbial products valerate and caproate predict renal outcome among the patients with biopsy-confirmed diabetic nephropathy. Acta Diabetol Nov. 2022;59(11):1469\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes, short-chain fatty acids, end-stage kidney disease, estimated glomerular filtration rate","lastPublishedDoi":"10.21203/rs.3.rs-7791885/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7791885/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe impact of short-chain fatty acids (SCFAs) on kidney outcomes in individuals with Type 2 diabetes (T2D) is not clearly understood. This study aimed to investigate the relationship between serum SCFA levels and adverse kidney outcomes in T2D patients. T2D patients were recruited between October 2016 and June 2020 and followed until December 2021. The serum levels of nine SCFAs were assessed using liquid chromatography-mass spectrometry. The primary kidney outcomes were defined as a doubling of serum creatinine levels or progression to end-stage kidney disease (ESKD). Secondary outcomes included an annual decline in estimated glomerular filtration rate (eGFR) of more than 5 ml/min/1.73 m\u0026sup2; or a rapid 25% reduction in eGFR during the follow-up period. The mean age of the 480 T2D participants was 62.0 years. The individuals in tertile 3 of serum propionate, butyrate, and formate levels showed an 86%, 79%, and 75% reduction, respectively, in the adjusted risk of experiencing a doubling of serum creatinine or progression to ESKD, compared to those in tertiles 1 and 2 of serum propionate, butyrate and formate levels. Adjusted logistical analysis showed that the individuals in tertile 3 of serum propionate, butyrate, formate and valerate levels had a reduced risk of rapid eGFR decline by 62%, 59%, 54%, and 58%, respectively. In conclusion, T2D patients who have higher circulating levels of SCFAs, particularly propionate, butyrate, and formate, are at a reduced risk of unfavorable kidney outcomes. These SCFAs may serve as indicative biomarkers for kidney function deterioration in T2D individuals.\u003c/p\u003e","manuscriptTitle":"Trajectories of Short-Chain Fatty Acids and Risk of Adverse Kidney Outcomes in Type 2 Diabetes: A Prospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 15:49:57","doi":"10.21203/rs.3.rs-7791885/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ad34f442-c7a6-404d-9ac7-b15636eabae9","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-28T23:48:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 15:49:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7791885","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7791885","identity":"rs-7791885","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}