Lower urinary pH is useful for predicting renovascular disorder onset in patients with diabetes

Generalized metabolic flux analysis framework provides mechanism-based predictions of ophthalmic complications in type 2 diabetes patients

Chronic metabolic diseases arise from changes in metabolic fluxes through biomolecular pathways and gene networks accumulated over the lifetime of an individual. While clinical and biochemical profiles present just real-time snapshots of the patients' health, efficient computation models of the pathological disturbance of biomolecular processes are required to achieve individualized mechanistic insights into disease progression. Here, we describe the Generalized metabolic flux analysis (GMFA) for addressing this gap. Suitably grouping individual metabolites/fluxes into pools simplifies the analysis of the resulting more coarse-grain network. We also map non-metabolic clinical modalities onto the network with additional edges. Instead of using the time coordinate, the system status (metabolite concentrations and fluxes) is quantified as function of a generalized extent variable (a coordinate in the space of generalized metabolites) that represents the system's coordinate along its evolution path and evaluates the degree of change between any two states on that path. We applied GMFA to analyze Type 2 Diabetes Mellitus (T2DM) patients from two cohorts: EVAS (289 patients from Singapore) and NHANES (517) from the USA. Personalized systems biology models (digital twins) were constructed. We deduced disease dynamics from the individually parameterized metabolic network and predicted the evolution path of the metabolic health state. For each patient, we obtained an individual description of disease dynamics and predict an evolution path of the metabolic health state. Our predictive models achieve an ROC-AUC in the range 0.79-0.95 (sensitivity 80-92%, specificity 62-94%) in identifying phenotypes at the baseline and predicting future development of diabetic retinopathy and cataract progression among T2DM patients within 3 years from the baseline. The GMFA method is a step towards realizing the ultimate goal to develop practical predictive computational models for diagnostics based on systems biology. This tool has potential use in chronic disease management in medical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-023-00218-x.

Urine pH and imaging findings of prostate useful predictors of prolonged duration of hematospermia

BACKGROUND

Few investigations regarding hematospermia duration have been reported thus far. The aim of this study was to identify clinical factors associated with the duration of hematospermia.

METHODS

Clinical data of 198 patients with hematospermia treated at Toho University Omori Medical Center from 2007 to 2022 were retrospectively evaluated. To identify independent predictors of hematospermia duration, uni- and multivariate Cox analyses were performed. Receiver operating characteristic analysis, Kaplan-Meier survival curves, and propensity score matching were applied for statistical evaluations.

RESULTS

Multivariate analysis of all 198 patients showed urine pH (UpH) level and any abnormal imaging finding of the prostate to be independent predictors of hematospermia duration. Based on the receiver-operating curve of UpH level for hematospermia improvement, the patients were divided into two groups using a threshold of 6.0 (Low-UpH 5.0-6.0, n=128; High-UpH 7.0-9.0, n=70). Kaplan-Meier curves indicated that patients in the High-UpH group or with any abnormal imaging finding had a higher rate of hematospermia persistence (both P<0.05). Even after matching between the groups classified by UpH (n=60 each), multivariate analysis showed that UpH level (hazard ratio 0.75, 95% CI: 0.61-0.92; P=0.006) and any abnormal imaging finding (hazard ratio 1.55, 95% CI: 1.04-2.31; P=0.033) were independent predictors of hematospermia duration. In Kaplan-Meier analysis findings of matched cohorts, High-UpH and presence of any abnormal imaging findings remained significantly correlated with higher rate of hematospermia persistence, while further stratification using a combination of these two factors identified a stepwise reduction in that rate (P=0.019). In addition, the proportion of patients with these two factors present simultaneously was significantly higher in the group with hematospermia for two months or more, and especially with a duration of greater than six months, than in the group with a duration of less than two months.

CONCLUSIONS

Although further research is needed, both UpH level and imaging findings of the prostate are considered useful biomarkers for predicting prolonged hematospermia.

Association of low urine pH as a metabolic feature with abdominal obesity

Objective

Low urine pH (LUP) is not only affected by environmental factors, but is also a feature of metabolic syndrome (MS), which is characterized by insulin resistance, abdominal obesity, dyslipidaemia and hypertension. However, it is unclear which factors contribute most to urine acidity. This study investigated factors influencing LUP and the link between LUP and metabolic traits in South Korea.

Methods

Participants were middle-aged subjects (age, 52.2 ± 8.9 years; average body mass index, 24.6 ± 3.2 kg/m²), of whom 4,626 had urine pH of 5.0 and were assigned to the LUP group and 4,185 had urine pH > 5.0 and were assigned to the control group. The association between LUP and various phenotypes, including environmental and metabolic traits, was analysed.

Results

LUP was significantly associated with MS diagnostic components and with environmental exposures such as smoking, alcohol intake and low-fibre diet. Multivariate analysis showed that the waist-to-hip ratio was the best predictor for LUP compared with other MS components (OR: 2.439).

Conclusions

LUP is an indicator of MS and is mainly related to the MS diagnostic criterion of abdominal obesity, even after adjusting for environmental influences on urine acidity.

SARS-CoV-2 and hypokalaemia: evidence and implications

The global pandemic secondary to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading to unprecedented global morbidity and mortality. With a bewildering array of complications, renal involvement in various forms is common, including serum electrolyte derangements. Hypokalaemia secondary to SARS-CoV-2 was common in a reported Chinese cohort. Here we review the emerging evidence on hypokalaemia and SARS-CoV-2 infection, the potential pathophysiological mechanisms based on early clinical and histopathological data and important clinical implications. Mechanisms of hypokalaemia are multifactorial and so the electrolyte disturbance can be difficult to avoid. We provide further support to the theory of renin-angiotensin-aldosterone (RAS) activation, discuss the strengths and weaknesses of implicating RAS involvement and highlight the importance of calculating the transtubular potassium gradient to identify those at risk of hypokalaemia and its complications.

Electrolyte Disturbances in SARS-CoV-2 Infection

The global pandemic secondary to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading to unprecedented global morbidity and mortality. With a bewildering array of complications, renal involvement in various forms is common, including serum electrolyte derangements. Hypokalaemia secondary to SARS-CoV-2 was common in a reported Chinese cohort. Here we review the emerging evidence on hypokalaemia and SARS-CoV-2 infection, the potential pathophysiological mechanisms based on early clinical and histopathological data and important clinical implications. Mechanisms of hypokalaemia are multifactorial and so the electrolyte disturbance can be difficult to avoid. We provide further support to the theory of renin-angiotensin-aldosterone (RAS) activation, discuss the strengths and weaknesses of implicating RAS involvement and highlight the importance of calculating the transtubular potassium gradient to identify those at risk of hypokalaemia and its complications.

Prognostic value of spot testing urine pH as a novel marker in patients with ST-segment elevation myocardial infarction

Aim: To investigate the relationship between urinary pH (UpH) and clinical outcome in patients with ST-segment elevation myocardial infarction undergoing percutaneous coronary intervention. Methods: Data of 2081 patients with ST-segment elevation myocardial infarction were analyzed, including UpH. Patients were divided into UpH <6.0, 6.0≤ UpH <7.0 and UpH ≥7.0 based on UpH level. The primary outcome was in-hospital all-cause mortality and major adverse clinical events. Results: The incidence of in-hospital clinical outcomes was significantly higher in low UpH group. Multivariate analysis found low UpH (<6.0) was an independent predictor of in-hospital all-cause mortality (OR: 2.85) and major adverse clinical events (OR: 2.39). A Kaplan-Meier analysis showed long-term all-cause mortality was also significantly higher in low UpH group. The multivariate cox analysis demonstrated that low UpH was an independent predictor of long-term all-cause mortality (HR: 2.57). Conclusion: Low UpH is a simple, accessible and powerful marker of poor clinical outcomes in such patients.

Hypoglycemic Effects of Oat Oligopeptides in High-Calorie Diet/STZ-Induced Diabetic Rats

The study was aimed to determine whether treatment with oat oligopeptides (OOPs) could modulate hyperglycemia related to type 2 diabetes mellitus (T2DM) in Sprague–Dawley (SD) rats. Diabetic SD rats modeling by a joint effect of high-calorie diet for 45 days and twice intraperitoneal injection of 30 mg/kg streptozotocin at one-week interval were observed with or without OOPs administration (0.25, 0.50, 1.00, and 2.00 g/kg Body Weight) for 12 weeks. Fasting blood glucose (FBG), oral glucose test tolerance (OGTT), serum insulin, level of antioxidant, and hepatic enzymes were measured. In addition, frequency of micturition was recorded in this study for the first time. It was observed that the administration of OOPs (2.00 g/kg Body Weight) resulted in a significant decrease (p < 0.05) in FBG since 6th week and a significant decrease (p < 0.05) in the OGTT-AUC on 6th and 10th week. In addition, the administration of OOPs (2.00 g/kg Body Weight) reduced HOMA-IR index and 24-h urine volume significantly (p < 0.05) whereas increased SOD activity significantly (p < 0.05). These results suggested that OOPs may have a hypoglycemic effect in diabetic rats.

Urinary pH is a predictor of diabetes in men; a population based large scale cohort study

AIMS

Previous cross-sectional studies revealed that patients with type 2 diabetes were associated with low urine pH. However, the association between urinary pH and incident type 2 diabetes is still unclear. Thus, we investigated the association between urinary pH and incident type 2 diabetes.

METHODS

This is a 5-year observational study of 3119men. We divided participants into four groups according to quartile of urinary pH. Multivariate logistic regression analysis was performed to calculate adjusted odds ratios (ORs) and 95% CIs for incident type 2 diabetes. We adjusted for age, body mass index, smoking, exercise, alcohol consumption, hypertension, hypertriglyceridemia, low high-density lipoprotein cholesterol levels and impaired fasting glycaemia.

RESULTS

In the follow-up examination, 113men diagnosed as diabetes. The proportion of incident diabetes was 6.9% (case/N=22/318) in the lowest urinary pH group (urinary pH = 5.0), 3.4% (46/1366) in the second lowest group (urinary pH = 5.5), 3.5% (30/856) in the third lowest group (urinary pH = 6.0) and 2.6% (15/579) in the highest group (urinary pH≥6.5). The lowest urinary pH group was associated with the increased risk of incident diabetes compared to the other urinary pH groups (multivariate OR=1.91, 95% CI 1.05-3.36, p=0.033 for the second lowest, multivariate OR=1.99, 95% CI 1.05-3.71, p=0.036 for the third lowest and multivariate OR 2.69, 95% CI 1.30-5.72, p=0.008 for the highest urinary pH groups).

CONCLUSIONS

Low urine pH is an independent predictor of diabetes. We suggest that the urine pH can be an easy practical marker for diabetes.