Hypoglycemia and hyperinsulinemia induced by phenolic uremic toxins in CKD and DKD patients

doi:10.21203/rs.3.rs-3963882/v1

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Hypoglycemia and hyperinsulinemia induced by phenolic uremic toxins in CKD and DKD patients

https://doi.org/10.21203/rs.3.rs-3963882/v1

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Patients with end-stage renal disease have lower fasting plasma glucose and HbA1c levels, with significantly higher insulin levels. For a long time, it has been believed that this higher insulin level in renal failure is due to decreased insulin clearance caused by reduced renal function. However, here we reported that accumulation of the gut microbiota-derived uremic toxin, phenyl sulfate (PS) in the renal failure, increased insulin secretion from the pancreas by enhanced glucose-induced insulin secretion. Other endogenous sulfides compounds which accumulated as in the renal failure also increased glucose-induced insulin secretion form b-cells. In addition, we also found that PS increased insulin resistance through lncRNA expression and Erk1/2 phosphorylation in the adipocytes. To confirm the relationship between PS and glucose metabolism in human, we recruited 2 clinical cohort studies (DKD and CKD), and found that here was a weak negative correlation between PS and HbA1c. Because these trials did not collect fasting insulin level, we alternatively used the urinary C-peptide/creatinine ratio (UCPCR) as an indicator of insulin resistance. We found that PS-induced insulin resistance in patients with eGFR < 60 ml/min/1.73 m². These data suggest that the accumulation of uremic toxins modulates glucose metabolism and induced insulin resistance in CKD and DKD patients.

Health sciences/Medical research/Translational research

Health sciences/Nephrology/Kidney diseases/Chronic kidney disease

Biological sciences/Drug discovery

CKD

DKD

phenyl sulfate

uremic toxin

insulin secretion

insulin resistance

gut microbiota

The kidney is involved in the insulin metabolism including filtration of insulin by glomerulus and degradation in the tubules and decline in kidney function modulates its condition¹. So far, it is well-known that patients with CKD show an incident of hypoglycemia, especially in the end-stage renal disease (ESRD)^2–4. These findings are supported by clinical data showing lower fasting plasma glucose (FPG) and HbA1c levels, and notably higher insulin level in patients with ESRD. It was well thought that the decreased kidney filtration capacity of insulin might lead to an accumulation of insulin in the body⁵. On the other hand, recent reports showed controversial results that the C-peptide levels are increased in the ESRD patients³. Oher factors such as deterioration in nutritional status, changes due to diabetes medications⁶ and reduced gluconeogenesis in the renal failure have been suggested⁷. Furthermore, decline in kidney function is also thought to induce insulin resistance⁸. Diabetic kidney disease (DKD) is characterized by renal dysfunction and difficulty in blood sugar management⁹. The destruction of podocytes plays a significant role in its pathophysiology¹⁰. Our research has shown that phenyl sulfate (PS), a uremic toxin derived from gut bacteria that accumulates with declining kidney function, is involved. PS is an important marker for the diagnosis and prognosis of DKD, especially harmful to podocytes¹¹. While PS accumulates in CKD as well, it has become clear that it damages podocytes, a site of action for PS, and exacerbates DKD. During this research, it was also shown that PS levels have a negative correlation with HbA1c¹¹. Inspired by this, we embarked on research considering whether PS is behind the changes in glucose metabolism in DKD. In this report, we explored the effects of PS on insulin secretion and insulin resistance, investigating how PS enhances insulin secretion from the islets of Langerhans, and how increased PS levels are related to renal dysfunction in DKD. These findings form the basis for developing new treatment strategies to improve blood sugar control in patients with DKD.

PS induced insulin secretion but not resistance in normal mice

In both diabetic mice and human DKD subjects, we previously reported that PS exhibits nephrotoxic effects by mesangial damage with increased albuminuria¹¹. To clarify the relationship between PS and insulin metabolism, we firstly examined the effect of PS on normal mice. PS was orally administered for 5 weeks (50 mg/kg/day), and it was found that there was no significant change in body weight, albuminuria, or the mesangial region in the kidney (Fig. 1A, B, C). In the PS-treated group, fasting glucose was decreased (Fig. 1D) and also the fasting insulin level was increased (Fig. 1E). Under the condition, we performed a glucose tolerance test (GTT). The glucose level and glucose induced insulin secretion were not changed between control- and PS-treated group (Fig. 1F). We also performed intraperitoneal insulin tolerance test (ipITT; 2 U/kg insulin), to examine the insulin sensitivity. The ipITT test showed no significant difference in the ratio of change in blood glucose between the groups (Fig. 1G). These data demonstrated that PS stimulates insulin secretion without altering insulin sensitivity in normal mice. To uncover the underlying mechanism, we measured the size of the pancreatic islets, which is considered an indicator of insulin secretion in humans¹². In PS-treated mice, the size of insulin-positive β cells significantly increased (Fig. 1H). In contrast, no histological changes were observed in adipocytes, liver, or skeletal muscle, which are typically implicated in insulin resistance (Fig. 1I). These data suggested that PS exerts a hypoglycemic effect by promoting insulin secretion.

PS induced insulin secretion and resistance in the diabetic mouse

To further examine the effect of PS on insulin metabolism, we administered PS to KKAY mice, a type 2 DM model, fed a high-fat (HF) diet (PS-treated KKAY-HF mice)¹³. After 5 weeks of administration (50 mg/kg/day), albuminuria significantly increased, unlike that in normal mice although there was no change in the body weight (Fig. 2A, B). Enlargement of the mesangial region was also observed, although body weight did not change (Fig. 2C). Concerning glucose metabolism, in the PS-treated group, fasting glucose level was also decreased in the PS-treated group (Fig. 2D) and basal insulin level was tended to be higher in the PS group (p = 0.05, Fig. 2E). Under the condition, we further performed a glucose tolerance test was performed (GTT, 2 g/kg) (Fig. 2F). As a result, glucose levels did not differ between the groups; however, insulin level was slightly higher in the PS-treated group but not significant (Fig. 2F). Next, we examined ipITT to determine whole-body sensitivity (Fig. 2G). The ipITT test showed that the glucose level after insulin injection (2 units/kg) was significant increase in the ratio of change in blood glucose in PS-treated KKAY-HF mice compared with that in control mice, further suggesting insulin resistance (Fig. 2G). Histologically, the number of insulin-positive cells was increased in the pancreas of PS-treated KKAY-HF mice, suggesting that the insulin-secretion capacity of the PS-treated group was high (Fig. 2H). Because liver and muscle are involved in the insulin resistance, we next examine the histological change in the liver and muscle and no significant change was observed (Fig. 2I). It is also well known that hypertrophy of adipocytes is the main mechanism of adult fat mass expansion and insulin resistance^14,15, so, we further measured the size of the white adipose tissue (WAT). In KKAY-HF mice treated with PS, the size of adipocytes increased and the number of white adipose tissue cells per area in WAT decreased (Fig. 2I). Collectively, these data suggest that PS has two effects: i) it increases insulin secretion from islets, and ii) it induces insulin resistance in adipocytes.

PS stimulated insulin secretion in the pancreatic β-cells

To elucidate the relationship between PS and insulin secretion, we evaluated the effects of PS on glucose-induced insulin secretion (GSIS) in a rat βcell line (INS-1e)^16,17. In INS-1e cells, 20 mM glucose showed a 4.5-fold increase in insulin secretion compared to 2 mM glucose. We decided the loading amount of PS by our previous report¹¹. Under these conditions, PS (10 µM) significantly enhanced 20 mM GSIS by 1.3-fold, and 100 µM PS further increased GSIS by 2.1-fold (Fig. 3A). To confirm the stimulatory effect of PS on insulin secretion, we examined GSIS in mouse isolated pancreatic islets¹⁸. Isolated mouse islets in a medium with a glucose level of 2.8 mM were incubated with 11 mM glucose, with or without PS (100 µM), and the secreted insulin was measured. As shown in Fig. 3B, PS (100 µM) stimulated GSIS by 2.8-fold compared to islets without PS. In contrast, the pancreatic insulin content was not changed by PS stimulation (Fig. 3C). These data suggest that PS stimulates insulin secretion by stimulating secretion from islets, and not by increasing insulin production.

Endogenous PS analogs stimulated insulin secretion from the islet

PS is a sulfurized metabolite of phenol generated by dietary tyrosine in the gut bacteria¹¹. Various sulfurized endogenous and exogenous compounds exist in the human body, and we found that uremic toxins, including phenol and sulfurized derivatives, accumulate in the circulation of patients with CKD and DKD patients¹⁹. In addition, sulfation is an important metabolic pathway for xenobiotics, hormones, and neurotransmitters in humans and is catalyzed by cytosolic sulfotransferase²⁰. By searching the Human Metabolome Database (HMDB, https://hmdb.ca), we identified 11 endogenous sulfate compounds (p-cresyl sulfate, p-nitrophenyl sulfate, o-cresyl sulfate, androsterone sulfate, dihydroxy ferulic acid 4-sulfate, testosterone sulfate, o-methoxyphenyl sulfate, vanillin sulfate, 4-methoxyphenylethanyl sulfate, pyrocatechol sulfate, and 4-acetaminophe sulfate) in humans. We also found four sulfate analogs (2-naphthyl sulfate, 8-quinolinyl sulfate, 1-naphthyl sulfate, and cyclohexanyl sulfate) synthesized in humans, and total 15 sulfate compounds (Table 1) were analyzed for their effect on GSIS. Among the 11 endogenous compounds, eight compounds (p-cresyl sulfate, p-nitrophenyl sulfate, o-cresyl sulfate, androsterone sulfate, dihydroxyferulic acid 4-sulfate, testosterone sulfate, o-methoxyphenyl sulfate, and 4-methoxyphenylethanyl sulfate) and PS enhanced 20 mM GSIS (100 µM, Fig. 3D). In addition, 2-naphthyl sulfate, 8-quinolinyl sulfate, 1-naphthyl sulfate, and cyclohexanyl sulfate also increased the concentration of 20 mM GSIS. Because some PS, p-cresyl sulfate, androsterone sulfate, and o-methoxyphenyl sulfate were found as uremic toxins and the concentration was increased in CKD and DKD^19,21, the accumulation of these compounds in CKD and DKD patients may enhance the secretion of insulin or inducing insulin resistance in CKD and DKD.

Stimulated insulin secretion through the Ddah2 and AMPK pathways in the pancreas

To clarify the mechanism underlying the effect of PS on insulin secretion, we performed RNA sequencing (RNA-seq) of INS-1e cells treated with or without PS. A result of 29504 genes was detected by RNA-seq, and the enhanced volcano plots showed differences in gene expression in each group (Fig. 3E). Among the genes, we identified two that exhibited significant changes by PS exposure (|log2FC| > 2.5, -log₁₀P > 2.5, normalized read counts > 0) The heatmap also showed that the top 25 transcripts were upregulated or downregulated following PS treatment (Fig. 3F, H). First, dimethylarginine dimethylaminohydrolase 2 (Ddah2) was up-regulated by PS (Fig. 3G). Ddah2 has been reported to be an enzyme that regulates the metabolism of nitric oxide and has been identified as one of the genes that regulates insulin secretion in the pancreas²². It enhances insulin secretion by regulating transcription through a Sirt1-dependent mechanism. Second, the Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 1 (Prkag1) was downregulated by PS treatment (Fig. 3I). Prkag1 is a component of AMPK subunits, and downregulation of Prkag1 and subsequent AMPK downregulation promotes the mTOR pathway²³, which is known to increase insulin secretion²⁴. These results suggested that this novel regulator of insulin secretion may be a promising target for diabetes treatment.

In addition, because PS induces mitochondrial damage in podocytes and increases albuminuria in DKD¹¹, we focused on mitochondria-related genes. Therefore, we comprehensively analyzed the expression of mitochondria-related genes, as shown in the heatmap (Fig. 3J). The results showed that PS treatment decreased mitochondrial respiratory chain complexes I (Ndufa4, Ndufv2, Ndufa2, Dmac1, and Ndufa3), III (Uqcrh and Ociad2), IV (Cox6c, Micos13, Cox6b1, and Cox7c), and V (Fmc1). These results are consistent with previous experiments showing that PS also acts on the mitochondrial electron transport system¹¹. Furthermore, these pathway analyses revealed that PS acts on the pancreas to positively regulate insulin secretion, which is involved in the cellular response to glucose stimuli. Based on the RNA-seq result shows that PS increases insulin secretion via the activation of pancreatic cells, even though PS decreases mitochondrial function.

PS increased insulin resistance through lncRNA expression and Erk1/2 phosphorylation in the adipocyte

To further clarify the mechanism underlying the effect of PS on insulin resistance, we performed RNA-seq using 3T3-L1 adipocytes treated with and without PS. 41710 genes were detected by the RNA-seq, and volcano plots showed the difference of gene expression in each group. (|log2FC| > 2.5, -log₁₀P > 2.5, normalized read counts > 0; Fig. 4A). A heat map of the top 25 transcripts upregulated by PS is shown (Fig. 4B). The RNA-seq results showed many variations in lncRNA expression. In particular, changes in long non-coding RNA (lncRNAs), such as Neat1 or Malat1were observed and Gm206877 and Kcnq1ot1 are also known as lncRNAs (Fig. 4C, 4D). Because lncRNAs have been reported to be key substances for adipogenesis or insulin resistance^25–27, these data suggest that insulin resistance caused by PS may be due to the action of PS on the transcriptional regulation of lncRNAs in adipocytes. However, among the downregulated genes (Fig. 4E), several (e.g., Ccnb1, Mad2l1, Top2a, and Foxm1; Fig. 4F) were involved in cell cycle and cell division processes. A reduction in the expression of these genes suggests decreased cell division. Cell cycle suppression induces obesity and insulin resistance²⁸. The adipocyte changes observed in mice and changes in gene expression suggest that white adipocytes do not divide or swell to induce insulin resistance via adipocytokines.

Adipocytes are one of the major insulin target tissues responsible for maintaining glucose homeostasis. Insulin stimulates GLUT4 translocation to the cell surface, which promotes glucose uptake by the cells and increases insulin sensitivity²⁹, which is also controlled by GLUT4 translocation to the membrane³⁰. Recently, we established that differentiated 3T3-L1 adipocytes are equipped with the basic GLUT4 translocation machinery, which can be activated by insulin stimulation^31,32. Using this system, we examined the effects of PS on insulin-mediated GLUT4 translocations. As shown in Supplemental Figure S1A, PS did not affect insulin-mediated GLUT4 translocations. Akt phosphorylation is known to play an important role in GLUT4 translocation. Overexpression of a constitutively active Akt mutant is sufficient to recruit GLUT4 to the cell surface³³. So, we examined the effects of PS on Akt phosphorylation induced by 100 nM insulin in 3T3-L1 adipocytes. However, PS did not affect Akt phosphorylation (Supplemental Figure S1B). Sortilin plays an essential role in adipocyte and muscle glucose metabolism by controlling GLUT4 localization^34,35 and impaired insulin signaling is induced by reduced sortilin expression³⁶. Therefore, we further examined the effects of PS on sortilin expression. The protein expression level of sortilin 1 increased after differentiation (day 8), but the expression level of sortilin did not change after PS treatment (1-100 µM, Supplemental Figure S1C). These data suggest that insulin resistance evoked by PS is not related to GLUT4. The ERK signaling pathway is also a potential cause of insulin resistance in type 2 diabetes^13,37. So, we next examined the effects of PS on insulin-induced ERK phosphorylation in differentiated 3T3-L1 adipocytes. As shown in Supplemental Figure S1D, ERK phosphorylation was unaffected by insulin treatment alone (100 nM). However, ERK phosphorylation induced by insulin was significantly increased by PS (10µM) (Fig. 4G). These data further suggest that PS promotes ERK phosphorylation. These results suggest that, in addition to the activation of lncRNAs, Erk phosphorylation may also be involved in PS-induced insulin resistance.

Clinical cohort studies show PS changes glucose metabolism by modulating insulin.

To confirm the relationship between PS and glucose metabolism clinically, we recruited 362 diabetic patients from a DKD patient cohort study, U-CARE (urinary biomarker for the continuous and rapid progression of diabetic nephropathy) study^11,38,39. In this study, patients with DKD had a mean age of 63.3 years and 56.9% were male. The mean blood glucose concentration (BS) was 154.2 ± 56.4 mg/dl and the HbA1c was 7.2 ± 1.1%. eGFR was 73.8 (17.1–115.4) ml/min/1.73 m² and the albumin-to-creatinine ratio (ACR) was 11.0 (1.0–6407.4) mg/gCr¹¹. HbA1c is a useful parameter for monitoring serum glycemic control and progression of diabetes mellitus over several months⁴⁰. We examined the relationship between PS and HbA1c level in this cohort. As shown in Fig. 5A, there was a weak relationship between HbA1c levels and PS (p = 0.0169, r= -0.1254). We also classified patients with DKD (eGFR < 60) and found no relationship between PS and HbA1c level (Fig. 5B, p = 0.8696, r = 0.02203). We further examined the relationship between PS and HbA1c using another cohort of 100 outpatients of Tohoku University Hospital recruited from the non-diabetic population or those with well-controlled diabetes (HbA1c is 5.9 ± 0.5, average ± SE, as shown in Table 2). The results showed a weak negative correlation between PS and HbA1c levels in this cohort (p = 0.022, r= -0.2235; Fig. 5C). A weak correlation was obtained when the two previous cohorts were limited to patients with renal failure (eGFR < 60) (p = 0.022, r= -0.2466, Fig. 5D).

Clinically, to examine insulin resistance and PS, HOMA2-IR is used for a standard method⁴¹. To calculate HOMA2-IR, the value of fasting insulin and glucose values were necessary. However, in the U-CARE and Tohoku cohort, we measured BS when patients visited the hospital. To overcome this limitation, the urinary C-peptide/creatinine ratio (UCPCR) is used. It has been reported that UCPCR correlates with HOMA2-IR, fasting C-peptide (FCP), and postprandial C-peptide (PCP)⁴². Additionally, UCPCR is positively correlated with the prognosis of DKD and coronary heart disease (CHD)⁴². Among the 362 patients with DKD who underwent U-CARE, no relationship was observed between plasma PS and UCPCR (p = 0.456, r= -0.04008; Fig. 5E). Because PS is a uremic toxin and its concentration may increase from CKD stage 3⁴³, we classified patients with DKD as having CKD (eGFR < 60). Accordingly, a close relationship was observed between serum PS levels and UCPCR in patients with DKD (p = 0.023, r = 0.3034) (Fig. 5F). To further confirm the relationship between PS and UCPCR in patients without DM, we used a non-DM cohort from Tohoku University Hospital. There was a slight correlation between PS and UCPCR in all non-diabetic patients (p = 0.23321, r= -0.12, Fig. 5G), but not in patients with CKD (eGFR < 60) (p = 0.2506, r= -0.1729, Fig. 5H). These data suggest that PS-induced insulin resistance in patients with eGFR < 60. To further investigate whether obesity could be a factor in determining insulin resistance by PS, the correlation between PS and UCPCR was examined only in patients with CKD with a BMI > 25 or higher. PS did not correlate with insulin resistance in patients with high BMI, suggesting that renal insufficiency was still a contributing factor to insulin resistance (Fig. 5I).

In our previous study, we found a negative correlation between the serum PS concentration and eGFR¹¹. PS accumulates due to renal dysfunction⁴⁴ and exacerbates diabetic nephropathy by damaging podocytes. Accumulation of PS is both a consequence and a contributing factor to further renal impairment, underlining its significance in renal disease progression. In healthy mice, PS did not induce albuminuria, suggesting that the presence of DM is necessary for PS to trigger albuminuria. Furthermore, we discovered that PS exacerbated glycemic control by increasing insulin resistance in patients with CKD (eGFR < 60). It has been reported that higher insulin levels and insulin secretion in ESRD patients are mainly a response to impaired insulin sensitivity in order to maintain normal glucose regulation and decreased insulin clearance ³. However, our results suggest that PS accumulation causes both elevated insulin levels and impaired insulin sensitivity is caused by PS accumulation¹¹. In terms of insulin secretion, experiments in healthy mice, KKAY-HF mice, cells, and cohorts of non-DM and DM patients have shown that PS acts on the pancreas to promote insulin secretion. Ddah2 and Prkag1, among others, may be involved in this pathway, and the results of RNA-seq pathway analysis suggest that PS acts on the pancreas to promote insulin secretion. Ddah2 is a promising target molecule for the treatment of diabetes as it regulates nitric oxide metabolism and the transcription of secretagogin through a Sirt1-dependent mechanism. Additionally, downregulation of Prkag1 and AMPK activates the mTOR pathway, leading to increased insulin secretion. These findings highlight the potential of PS as a therapeutic agent against diabetes by targeting these genes. Based on these findings, we suggest that PS could be an innovative target for CKD treatment to improve renal function and glycemic control. However, further studies are required to confirm the exact mechanisms by which PS affects insulin secretion, and to establish the safety and efficacy of PS as a treatment for diabetes.

Notably, PS is produced by the human gut microbiota, and we demonstrated that endogenous PS analogs can enhance insulin secretion more efficiently than PS. These results suggest that PS could promote insulin secretion in patients with good renal function, and that PS analogs may have the potential to become new therapeutic agents for diabetes mellitus. RNA-seq results have revealed that PS impairs mitochondrial function, a finding consistent with our past research¹¹ and the known role of PS in oxidative stress⁴⁵. However, further investigation is needed to clarify the link between this mitochondrial impairment and insulin secretion. These findings highlight the need for deeper understanding of PS's impact on cellular metabolism and its implications in metabolic regulation.

In contrast, comparisons between healthy and KKAY-HF mice, as well as between cohorts of non-DM and DM patients, indicated that PS acts on insulin resistance in renal failure, especially in CKD. Previous studies have reported that renal insulin resistance is induced by renal failure and that PS may be the causative agent of this phenomenon. The phenomenon by which PS acts only on adipocytes in renal failure, suggesting insulin resistance, is thought to occur because PS remains in the body longer and acts on adipocytes more easily when renal function is reduced.

Our research also indicates that increased phosphorylation of Erk1/2 in adipocytes contributes to insulin resistance, a process typically linked to oxidative stress. We infer that oxidative stress, particularly induced by PS, plays a crucial role in this mechanism by promoting Erk1/2 phosphorylation⁴⁶. This suggests that PS-induced oxidative stress is a key factor in metabolic dysregulation, affecting insulin signaling in adipocytes. Our findings thus reveal a potential mechanistic pathway wherein PS not only exacerbates oxidative stress but also contributes to insulin resistance and metabolic disorders. Furthermore, the activation of Erk 1/2 disrupts the regulation of adipocytokines¹³, including the malignant adipocytokine TNF-α, which also activates Erk 1/2⁴⁷. Therefore, PS may heighten the risk of insulin resistance and related diseases by initiating a cycle of Erk activation and abnormal adipocytokine release. Adipocytokines are considered one of the causes of many metabolic diseases, and their effects and impacts are being studied. It is well known that obesity confers an increased risk for serious metabolic diseases including type 2 diabetes, non-alcoholic fatty liver disease, and cardiovascular diseases. In addition, adipocytokines are thought to increase the risk of these diseases^{48 49}. Improvement of the gut microbiota by probiotics and other means may help ameliorate diabetes and reduce the risk of metabolic diseases by inhibiting PS and, consequently, Erk activation and adipocytokine release.

Our RNA-seq analysis revealed changes in the expression of several genes, including lncRNAs, in PS-treated 3T3-L1 adipocytes. Since lncRNAs have been implicated in adipogenesis and insulin resistance^25–27, these changes suggest that PS treatment may affect these cellular processes. Neat1 is involved in adipogenesis^50,51 and may cause mitochondria impairment⁵². Furthermore, changes in genes related to the cell cycle indicated the swelling of adipocytes, which was also observed in mouse tissues. We also reported that PS impairs mitochondrial function in podocyte¹¹ and that Neat1 may be a cause of this. Malat1 is also a lncRNA involved in adipogenesis⁵³. Further studies are required to understand the underlying mechanisms and the potential clinical implications of PS in metabolic disorders. We previously suggested that a tyrosine phenol-lyase (TPL) inhibitor, which blocks PS production by the gut microbiota, reduces the PS concentration in the serum and albuminuria in diabetic mice¹¹. PS induces insulin resistance in KKAY mice fed a high-fat diet and in human patients with CKD G3. Controlling PS production using TPL inhibitors may be a novel strategy for the treatment of insulin resistance and albuminuria in CKD.

One potential limitation of our study is the absence of fasting glucose and insulin level to estimate HOMA2-IR in the two DKD and CKD cohort examined. Here, to overcome this, we alternatively used urinary C-peptide/creatinine ratio (UCPCR)⁴². Indeed, in this study, we found a significant correlation between blood PS concentration and insulin resistance using UCPCR. However, it is necessary to measure blood insulin levels to clarify more accurate relationships with hypertension and obesity. By examining the relationship in the future, it is thought that the relationship between PS, insulin secretion, and insulin resistance will be clarified.

In conclusion, our data highlighted that PS and endogenous sulfate metabolites that accumulated in CKD induced insulin secretion from b-cells, and PS also increased insulin resistance through lncRNA expression and Erk1/2 phosphorylation in adipocytes, resulting in changes in glucose metabolism in CKD and DKD patients.

Material details

PS was synthesized by Sundia MediTech (Shanghai, China) and ISOTEC (Sigma-Aldrich, Burlington, MA). Phenol analogs were chemically synthesized. INS-1e was kindly provided by Dr. Hisamitsu Ishihara of the Nihon University. 3T3-L1 cells were purchased from JCRB cell bank (Kobe, Japan).

Animal experiments

All animal experiments were performed following the ARRIVE guidelines, and approved by the Tohoku University Institutional Animal Care and Use Committee (2013-001-9). The study was conducted in accordance with the Guide for the Care and Use of Laboratory Animals. All male C57BL/6N and KKAY mice were obtained from CLEA (Tokyo, Japan) in 4 weeks old. They were acclimated for 2 weeks. KKAY mice were fed a high-fat diet (15.3% fat, 424.5 cal/100 g; Quick fat, CLEA, Tokyo, Japan) and had free access to tap water. PS intake was estimated (50 mg/kg/day) by measuring the amount of water intake. PS was administrated with 0.1% PS included water for 5 weeks. Urinary albumin levels were determined by ELISA (Exocell Inc., Philadelphia, PA).

Glucose tolerance test (GTT) and insulin tolerance test (ITT)

GTT and ITT were performed as previously described¹⁶ with n = 3–5. Briefly, an oral glucose tolerance test (OGTT) was performed after overnight fasting. and had ad libitum access to water. Glucose (2 g/kg) was administered intraperitoneally. For insulin tolerance testing (ITT), 8-hour fasted mice were intraperitoneally injected with regular human insulin (2 U/kg body weight). Blood samples were collected from the retro-orbital sinus at 15, 30, 60, and 120 minutes. Each blood sample was centrifuged, and the plasma was removed and stored at − 20°C until analysis of glucose and insulin concentrations. The glucose and insulin concentrations were measured according to the manufacturer’s instructions (Wako Pure Chemical, Osaka, Japan).

Histological examination

The pancreas and white adipose tissue (WAT) were fixed in 10% neutral buffered formalin and embedded in paraffin. Pancreatic sections were stained with anti-insulin antibody (1:1000, # I2018, Sigma, Burlington, MA). WAT sections were stained with hematoxylin and eosin (HE). The images were captured and processed using a BZ-X810 fluorescence microscope (KEYENCE, Osaka, Japan), using a Plan Apochromat 10x objective(NA0.45, BZ-PA10, KEYENCE, Osaka, Japan). The BZ-X810 Analyzer software was used for the extraction and quantification of insulin-positive areas and quantification of WAT as the number of cells per unit area. The area of mesangial region was measured in HE staining with ImageJ software (Version 1.54, National Institutes of Health).

Cell culture

INS-1e cells¹⁶ were grown in RPMI-1640 medium, 3T3-L1 cells were grown in DMEM (high glucose) medium. They were processed by trypsin-EDTA and passaged.

Effects of phenol analogs on glucose-stimulated insulin secretion (GSIS)

INS-1e cells were grown in RPMI-1640 medium and GSIS was measured as previously reported. Briefly, approximately 80% confluent cells were incubated in the presence or absence of PS or a phenyl analog for 24 h. Cells were then maintained for 1 h, washed twice, and preincubated at 37°C for 1 h in a buffer containing (in mM):135 NaCl, 3.6 KCl, 5 NaHCO₃, 0.5 NaH₂PO₄, 0.5 MgCl₂, 1.5 CaCl₂, 10 mM HEPES, and 0.1% BSA 0.1%, pH 7.4¹⁶. The cells were then incubated in buffer containing glucose for 1 h. The insulin concentration was measured using a rat insulin ELISA kit (Mercodia, Uppsala, Sweden).

Measurement of insulin secretion from isolated islets, and their protein content.

The isolation of islets and the measurement of insulin secretion from islets were performed as described¹⁸. Briefly, groups of 10 islets were initially incubated in Krebs Ringer bicarbonate solution (KRB) with 2.8 mmol/L glucose for one hour at 37°C in an atmosphere of 95% O2 and 5% CO2. Following this, they were incubated for another hour in 0.1 mL of fresh KRB, but this time with varying glucose concentrations. Separately, cells (100,000 cells per well in a 48-well plate) were seeded and grown in DMEM for two days, then treated with or without 100µM PS. On the experiment day, these cells were immersed in a 2-(4-[2-hydroxyethyl]ff-1-piperazine) ethanesulfonic acid (HEPES)-balanced KRB solution (KRH), which included 119 mmol/L NaCl, 4.7 mmol/L KCl, 2.5 mmol/L CaCl2, 1.2 mmol/L MgCl2, 1.2 mmol/L KH2PO4, 25 mmol/L NaHCO3, and 20 mmol/L HEPES, pH 7.4. This solution was also supplemented with 5 mg/mL BSA and 2.8 mmol/L glucose and maintained at 37°C for two hours. Afterwards, they were incubated in fresh KRH with different glucose or KCl concentrations for two hours. Post incubation, the medium was removed from the islets or cells, and the insulin levels in the medium were measured using an insulin ELISA kit (Morinaga Institute of Biological Science, Yokohama, Japan). Additionally, the total protein content of the islets or cells was quantified using the Micro-BCA Protein Assay Reagent (PIERCE Biotechnology Inc., Rockford, IL).

RNA sequencing

Total RNA was extracted by RNeasy plus mini kit (QIAGEN). RNA sequence library preparation was performed using a QIAseq Stranded RNA Library Kit (QIAGEN), according to the manufacturer's instructions. Illumina libraries were converted into circular single-stranded DNA libraries using the MGI Easy Universal Library Conversion Kit (App-A) (MGI Tech) according to the manufacturer’s instructions. The converted libraries were sequenced on a DNBSEQ-G400RS (MGI Tech) platform using 2x 150 bp paired-end mode. RNA sequencing was performed using a DNAFORM (Yokohama, Kanagawa, Japan). Sequence reads in Fastq format were assessed for quality using FastQC. Raw reads were filtered to remove low-quality reads using Trimmomatic-0.39. The obtained reads were mapped to mouse GRCm39 and mRatBN7.2/rn7 genomes using STAR (version 2.7.10a). Reads on annotated genes were counted using StringTie software (v2.2.0). Gene expression levels were measured using the Bioconductor package, edgeR (version 3.15).

Phosphorylation assay

3T3L1 adipocytes were plated in 96 multi-well plates and grown until they reached 90% confluence. After 3 h of serum starvation, cells were treated with PS (10 µΜ) for 1 h. Cells were stimulated with insulin (100 nM) for 30 min. The cell monolayers were treated as described in the text and processed using the ERK1/2 (pT202/Y204 + Total) ELISA Kit (ab176660) (Abcam, Cambridge, UK), following the manufacturer’s guidelines, and adding the HALT protease and phosphatase inhibitor cocktail (Thermo Fisher Scientific, Waltham. MA) was added to the lysis buffer provided in the kit. The results were read on a Spectramax 190 (Molecular Devices, San Jose, CA) and analyzed as the pERK/total ERK signal ratio⁵⁴.

Western Blotting

3T3-L1 cells expressing myc-GLUT4-EGFP were serum-starved for 3 h, washed thrice with KRPH buffer, and stimulated with insulin (0-200 nM) for 30 min in the presence or absence of PS (10 µM) for 60 min. Phosphorylation of protein kinase B (Akt; Ser473) and Erk1/2 was analyzed by western blotting as described previously⁵⁵.

Recruitment and measurement of the U-CARE cohort study¹¹

The Urinary Biomarker for Continuous and Rapid Progression of Diabetic Nephropathy (U-CARE) study is a multicenter, observational clinical study that aimed to investigate urinary biomarkers in diabetic nephropathy (UMIN 00011525). The U-CARE assay was performed as previously described¹¹. We recruited 362 patients (U-CARE, registered at UMIN 00011525). The Tohoku University Ethics Committee (2017-1-870) and Okayama University Ethics Committee (1702-026). Human samples were collected in accordance with the guidelines of Tohoku University (2017-1-870) and written informed consent was obtained from Okayama University (UMIN 00011525 and 1702-026). The phlebotomy protocol was as follows: The estimated GFR (eGFR) was calculated according to sex, age, and serum Cr concentration using the Japanese Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI). U-CARE urine C-peptide levels were measured by ELISA using a C-peptide ELISA kit (Mercodia, Uppsala, Sweden), according to the manufacturer’s instructions.

Recruitment and measurement of the non-DM cohort

We recruited 100 patients treated at the outpatient clinic of the Tohoku University Hospital. The study protocol was approved by the Ethics Committee of Tohoku University (2022-1-823, 2012-3-19) and complied with the guidelines of the Declaration of Helsinki. Written informed consent was obtained from all the patients. Urine C-peptide levels were measured by ELISA using a C-peptide ELISA kit (Mercodia, Uppsala, Sweden), according to the manufacturer’s instructions.

Quantification of PS by LC/MS/MS

PS levels in animal plasma were measured as we recently reported⁵⁶. Deuterated internal standards were used for all analytes, and a TSQ Quantum Ultra triple quadrupole mass spectrometer (Thermo Fisher Scientific, Waltham, MA) equipped with a heated ESI source system was used. The mass spectrometer was operated in both the positive and negative ionization modes. The samples were analyzed in single reaction monitoring mode by monitoring the ion transitions at m/z 173.0–>93.3 PS. Data were acquired and analyzed using the Xcalibur™ software (version 2.1, Thermo Scientific). For human samples, the PS level in fresh-frozen plasma was measured by LSI Medience Co. (Tokyo, Japan) using another method to help clinicians measure the PS. Briefly, LC–MS/MS datasets were acquired using a liquid chromatograph Nexera X2 LC0AD equipped with an ESI and triple quadrupole mass spectrometer 8050 (Shimadzu, Japan). The mass spectrometer was operated in the negative mode. Data acquisition and analysis were performed using Shimadzu Lab Solutions version 5.89. The correlation between each measurement was confirmed to be greater than 0.99269.

Statistical Analysis

Data are presented as mean ± standard error. Statistical significance was determined using the Student’s t-test. A P-value significance was set at p < 0.05. GraphPad Prism 9 (Version 9.5.1) (GraphPad Software, Boston, MA) was used for statistical analyses.

used:

BUN

blood urea nitrogen, CE-TOFMS:capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry; CKD:chronic kidney disease; Cr:creatine CVD:cardiac vascular disease, DDAH2:dimethylarginine dimethylaminohydrolase 2, DKD:diabetic kidney disease, ESRD:end-stage renal failure, FCP:fasting C-peptide, GSIS:glucose-stimulated insulin secretion, GTT:Glucose tolerance test, HF:High-fat, IS:indoxyl sulfate, ITT:insulin tolerance test, lncRNAs:long non-coding RNAs, PCP:postprandial C-peptide, Prkag1:Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 1, PS:phenyl sulfate, RF:Renal failure, TMAO:trimethylamine-N-oxide, urinary C-peptide/creatinine ratio (UCPCR), U-CARE:Urinary Biomarker for Continuous and Rapid Progression of Diabetic Nephropathy, WAT:white adipose tissue.

Competing of interests

None

Fundings

This work was supported in part by the National Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (18H02822), the Japan Agency for Medical Research and Development (AMED) 20ek0210133h0001, 20ak0101127h0001, and JP22zf0127001, and Anzai memorial diabetes research grant by Gonryo for the promotion of medical science.

Author Contribution

Y.T and T.A. participated in the conception and design of the study, Y.T., H.H., C.K., Y.M., K.S., performed in vitro experiments, Y. T. analyzed in vitro, in vivo data, clinical data and wrote the manuscript. Funding were acquired by T.A., T.K. T.K. performed RNA-seq and analyzed the data. Y.A. and K.K. performed in vivo experiments. Y.M., R.K., and Y.T. measured uremic toxins. T.A.., T.T., and J.W. collected the clinical information. T.A. oversaw data collection and interpretation. M.K., K.N., T.K., S.W., K.K., T.T., T.S., and T.A. contributed to writing the discussion. All authors read and approved the final manuscript.

Acknowledgement

We thank Fumiko Date, Miki Yoshizawa, Naoko Shibata, and Chika Tazawa (Histological platform, Tohoku University School of Medicine) for their histological assistance.

Data availability

The data of RNA-seq are deposited as PRJNA1026807.

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Tables 1 and 2 are available in the Supplementary Files section.

No competing interests reported.

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Hypoglycemia and hyperinsulinemia induced by phenolic uremic toxins in CKD and DKD patients

Status:

Version 1

Abstract

Figures

Introduction

Results

PS induced insulin secretion but not resistance in normal mice

PS induced insulin secretion and resistance in the diabetic mouse

PS stimulated insulin secretion in the pancreatic β-cells

Endogenous PS analogs stimulated insulin secretion from the islet

Stimulated insulin secretion through the Ddah2 and AMPK pathways in the pancreas

PS increased insulin resistance through lncRNA expression and Erk1/2 phosphorylation in the adipocyte

Discussion

Methods and materials

Material details

Animal experiments

Glucose tolerance test (GTT) and insulin tolerance test (ITT)

Histological examination

Cell culture

Effects of phenol analogs on glucose-stimulated insulin secretion (GSIS)

RNA sequencing

Phosphorylation assay

Western Blotting

Recruitment and measurement of the U-CARE cohort study11

Recruitment and measurement of the non-DM cohort

Quantification of PS by LC/MS/MS

Statistical Analysis

Abbreviations

Declarations

Competing of interests

Fundings

Author Contribution

Acknowledgement

Data availability

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Recruitment and measurement of the U-CARE cohort study¹¹