Tag: Type

Posted on by

Impact of chronic hepatitis on cardiovascular events among type 2 diabetes patients in Taiwan pay-for-performance program – Scientific Reports

Research subjects

Patients with T2DM who joined the P4P from 2008 to 2010 were enrolled. Patients with a confirmed diagnosis of T2DM were defined as those who were hospitalized at least once or came in for outpatient visits at least three times within 1 year and had a primary or secondary diagnosis International Classification of Diseases (ICD) code “250,” “250.00,” or “250.02”38,39. Among them, patients with type 1 DM “250.x1” * or “250.x3;” gestational DM “648.0” or “648.8;” neonatal DM “775.1;” abnormal glucose tolerance test “790.2;” age < 20 years or > 100 years; and those who died within 1 year of joining P4P were excluded. Finally, 283,793 patients were included (Fig. 1). Based on the status of comorbid chronic hepatitis at enrollment, the patients were divided into four groups: no comorbid chronic hepatitis, named as “No chronic hepatitis”; comorbid liver B, named as “Hepatitis B” group; comorbid liver, named as “Hepatitis C” group; patients without viral hepatitis and with comorbid fatty liver were named as the “Fatty liver disease” group and were followed-up until the end of 2017. The “no comorbid chronic hepatitis” group was used as the reference group to analyze the correlation between different types of chronic hepatitis and the risk of cardiovascular disease.

Figure 1
figure 1

Flowchart for study subject selection. DM diabetes mellitus, P4P pay-for-performance, HBV hepatitis B virus, HCV hepatitis C virus.

Ethics statements

The National Health Insurance Research Database (NHIRD) is derived from Taiwan’s mandatory National Health Insurance program was established by the National Health Insurance Administration Ministry of Health and Welfare and maintained by the National Health Research Institute (NHRI). The patient identifications in the National Health Insurance Research Database have been scrambled and de-identified by the Taiwan government, and the database is commonly used for different types of research such as in medical, and public health fields. Thus, informed consent was waived by the Research Ethics Committee of the China Medical University, and the study protocol was approved by the research ethics committee of China Medical University and Hospital (IRB number: CMUH106-REC3-153) and was conducted in accordance with the principles of the Declaration of Helsinki.

Data sources

This retrospective cohort study analyzed data from the National Health Insurance Research Database of the “Applied Health Research Data Integration Service from National Health Insurance Administration”. The data included outpatient prescriptions and treatments, outpatient prescriptions and medical orders, inpatient medical expense lists, inpatient medical expense and medical order lists, insurance details of persons, major injury and illness, medical institution master files, diagnosis, and P4P education records.

Definitions of variables

Hepatitis B: Those with ICD-9 070.2, 070.20, 070.21, 070.22, 070.23, 070.3070.31, 070.32, or 070.33 or ICD-10 B16, B17.0, B18.0, B18.1, or B19.1 as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment.

Hepatitis C: Those with ICD-9 070.41, 070.44, 070.51, or V02.62 or ICD-10 B17.10, B17.11, B18.2, B19.20, B19.21, or Z22.52 as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment.

NAFLD: Those with ICD-9 571.8, 571.9, or ICD-10 K74.4, K74.5, K74.60, K74.69, K76.0, K76.9, etc. as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment, and without the occurrence of a hepatitis B or C code, for whom the first hospital visit within 365 days was defined as the date of diagnosis. Patients with concurrent viral hepatitis and NAFLD were classified as having viral hepatitis.

Age-based categorization included 20–39, 40–54, 55–64, 65–74, and ≥ 75 years age groups. Monthly salary was divided into five grades, namely ≤ NTD 17,280, NTD 17,281–22,800, NTD 22,801–36,300, NTD 36,301–45,800, and ≥ NTD 45,801. Charlson comorbidity index was divided into 0, 1, 2, and ≥ 3 after excluding scores correlated with independent or dependent variables40.

The diabetes complications severity index (DCSI) was scored as 0, 1, and ≥ 2 points. The DCSI was calculated based on the classification and scoring method proposed by Young et al. If the patient had no complication, the score would be 0; for each complication, 1 point would be added; if the complication was serious, 2 points would be added. Based on this calculation method, the maximum score was 13 points41.

Cardiovascular disease: Those with ICD-9 398.91, 402.xx, 404.xx, 410.xx–414.xx, 422.xx, 425.xx or 428.xx, or ICD-10 I09.81, I11, I13, I20–I22, I24, I25, I40–I43, I50, R09.89, etc. as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment42.

Calculation of the coefficient of variation (CV% = standard deviation/mean) of HbA1c and fasting blood glucose: All measurements in the first year were used, and if the measurements were taken less than four times in the first year, measurements taken up to the second year were included. If measurements were taken less than four times in the 2 years, the patient would be excluded.

Adjusted CV = CV/√ (n/n − 1): When the examination data were limited, the examination times would affect the result of the CV. In this case, a relatively correct result of the CV with a reduced effect of the examination times could be obtained by correcting the examination times.

Analytical methods

Descriptive and inferential statistics were carried out according to the research objectives and framework. All research tests were based on a significance level of α = 0.05, and all statistical analyses were conducted using SAS software for Windows, version 9.4 (SAS Institute Inc., Cary, NC, USA). Descriptive statistics such as frequency, percentage, average, and standard deviation were used to describe the dependent and independent variables to be investigated in this study. This study adopted descriptive statistics to present the demographic characteristics, status of comorbidities, blood biochemical indicators, health status, economic factors, and medical care provider characteristics of patients with diabetes. The incidence of cardiovascular disease in patients with T2DM with chronic hepatitis per 1000 person-years was tested using univariate Poisson regression. The relative risks of cardiovascular disease in the four groups were calculated using a Cox proportional hazards model.

Posted on by

Genetic Mapping Predicts Risk of Cardiovascular Events in People With Type 2 Diabetes

CVD, cardiovascular, heart MRI, cardiac

Risk scores based on genetic mapping were found to correlate with hypertensive blood pressure (BP) traits and an increased likelihood of adverse cardiovascular events, such as stroke, myocardial infarction, and cardiovascular death, in individuals with type 2 diabetes (T2D), according to results of a study published in Hypertension. The risk of adverse cardiovascular events in those with higher genetic risk scores were unchanged by intensive glycemic therapy approaches.

Researchers conducted a post hoc analysis of the National Institutes of Health’s ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial (ClinicalTrials.gov Identifier: NCT00000620) to assess whether genetic variants influenced BP traits and adverse cardiovascular outcomes in individuals with T2D. Out of the 10,251 participants with T2D in the ACCORD trial, 6335 individuals had genetic data that were needed to calculate polygenic risk scores.

During the ACCORD trial, BP data were calculated using an average of 3 BP measurements with 5 minutes rest in between measurements. Overall, the median systolic blood pressure was 147 mm Hg, the median diastolic blood pressure was 83 mm Hg, and the median HbA1C was 8.1%.

Continue Reading

For the post hoc assessment, the researchers collected participant genotype data and compared these data with the Trans-OMICs Precision Medicine (TOPMed) Freeze 8 gene map, which consists of more than 1000 genetic variants known to affect blood pressure. The researchers calculated polygenic risk scores based on the number of matches between each participant’s DNA and the genetic variants known to influence BP. The greater the number of matches, the higher the risk score. The median polygenic risk score was 168.4 (range, 166.6-170.6).

After analyzing BP polygenic risk scores in relation to adverse cardiovascular outcomes, each degree of increase in the risk score was found to correlate with a 12% increased risk of cardiovascular events. Glycemic control therapy did not influence the BP polygenic risk scores, nor did it influence the primary outcome of cardiovascular risk prevention.

Study limitations included the pre-existing nature of the subset of participants available for analysis, as well as a lack of power to evaluate possible interactions due to the study’s post hoc design.

“These results invigorate the potential implications of [using] BP polygenic risk score in the primordial prevention of microvascular and macrovascular complications in T2D through early intensification of life-style measures such as healthy diet, exercise, smoking cessation, weight management, and BP control among those with high genetic risk,” the authors said.

This genetic risk assessment may especially benefit those with newly diagnosed T2D and those with prediabetes to encourage earlier adoption of a healthier lifestyle.

Reference

Parcha V, Pampana A, Bress AP, Irvin MR, Arora G, Arora P. Association of polygenic risk score with blood pressure and adverse cardiovascular outcomes in individuals with type II diabetes: insights from the ACCORD trial. Hypertension. Published online April 4, 2022. doi:10.1161/hypertensionaha.122.18976

Posted on by

Risk for major adverse CV events elevated with type 2 diabetes, cognitive impairment

Hertzel C. Gerstein, MD, MSc

April 21, 2022

2 min read


Disclosures:
Gerstein reports receiving research grants from AstraZeneca, Eli Lilly, Merck, Novo Nordisk and Sanofi; receiving honoraria for speaking from Boehringer Ingelheim, DKSH, Eli Lilly, Novo Nordisk, Roche, Sanofi and Zuellig; and receiving consulting fees from Abbott, Covance, Eli Lilly, Hanmi, Kowa, Novo Nordisk, Pfizer and Sanofi. Please see the study for all other authors’ relevant financial disclosures.


We were unable to process your request. Please try again later. If you continue to have this issue please contact customerservice@slackinc.com.

Adults with type 2 diabetes and cognitive impairment are more likely to experience major adverse cardiovascular events, stroke or CV mortality compared with those without cognitive impairment, according to study findings.

In an analysis of data from the REWIND trial, participants who scored 1.5 standard deviations below their country’s geometric mean on the Montreal Cognitive Assessment and the Digit Symbol Substitution Test were more likely to experience major adverse CV events, making cognitive impairment a potential predictor for CV health outcomes.


Hertzel C. Gerstein, MD, MSc

Gerstein is a professor and population health institute chair in diabetes research and care at McMaster University and Hamilton Health Sciences in Ontario, Canada.

“These findings highlight the relevance of cognitive function as an important risk factor for CV outcomes and suggest that patients with cognitive impairment should be offered proven cardioprotective therapies to mitigate their future risk of CV outcomes,” Hertzel C. Gerstein, MD, MSc, professor and population health institute chair in diabetes research and care at McMaster University and Hamilton Health Sciences in Ontario, Canada, told Healio.

Researchers collected data from 8,772 REWIND participants with type 2 diabetes who completed both the Montreal Cognitive Assessment and the Digit Symbol Substitution Test at baseline, 2 years, 5 years and their final trial visit. The Montreal Cognitive Assessment is a 30-item questionnaire assessing seven cognitive domains. The Digit Symbol Substitution Test presents nine symbols above blank squares, with a key corresponding each symbol to a number. Participants must place the correct number in each square in a spvan of 2 minutes. Scores on each test were standardized based on the participant’s country. Adults with a score 1.5 standard deviations below the mean score in their country were defined as having country-standardized substantive cognitive impairment. Those who had a mean score on both tests combined 1.5 standard deviations below their country’s mean were defined as having substantive cognitive impairment based on the geometric mean. Primary outcomes were incident major adverse CV events, incident stroke and CV mortality.

The findings were published in The Journal of Clinical Endocrinology & Metabolism.

Of the study cohort, 10.3% had substantive cognitive impairment and 6% had substantive cognitive impairment based on the geometric mean. Participants with substantive cognitive impairment did not have a significantly increased risk for major adverse CV events after adjusting for albuminuria, estimated glomerular filtration rate and retinopathy. However, in a fully adjusted model, those with substantive cognitive impairment based on the geometric mean had an increased risk for major adverse CV events compared with those without cognitive impairment (adjusted HR = 1.38; 95% CI, 1.09-1.77; P = .009).

Participants with substantive cognitive impairment (aHR = 1.35; 95% CI, 1.11-1.64; P = .002) and substantive cognitive impairment based on the geometric mean (aHR = 1.54; 95% CI, 1.22-1.93; P < .001) had an increased risk for either stroke or CV death compared with adults without cognitive impairment.

“These findings are consistent with other research suggesting that low cognitive scores on cognitive tests were a risk factor for a cardiovascular outcome,” Gerstein said. “This research extended those findings by using a composite measure of cognitive scores and prespecifying a threshold labeled substantive cognitive impairment. It also reported a novel way of combining the cognitive scores by calculating their geometric mean.”

For more information:

Hertzel C. Gerstein, MD, MSc, can be reached at gerstein@mcmaster.ca.


We were unable to process your request. Please try again later. If you continue to have this issue please contact customerservice@slackinc.com.

Posted on by

Study provides new understanding of the earliest molecular events in Type 1 Diabetes pathogenesis

Study provides new understanding of the earliest molecular events in Type 1 Diabetes pathogenesis

For the first time, researchers have revealed that during the development of Type 1 Diabetes (T1D), when insulin-producing cells in the pancreas are under attack from T lymphocytes, the cells lining the pancreatic duct reprogram themselves in an attempt to suppress autoimmune T cell responses. This study is published today in Nature Metabolism.

The first events that occur in a patient heading towards Type 1 Diabetes, the events that trigger autoimmunity, have been difficult for researchers to pin down because of our inability to biopsy the pancreas, and the fact that clinical diagnosis is only made once massive beta cell destruction has occurred. That is why it is so important to develop a better understanding of the earliest molecular events in T1D pathogenesis, so we can uncover more about biomarker identification and disease prevention.”


Golnaz Vahedi, PhD, senior author, associate professor of Genetics and member of the Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine at the University of Pennsylvania

Autoimmune diseases, which affect as many as 23.5 million Americans, occur when the body’s immune system attacks and destroys healthy organs, tissues and cells. There are more than 80 types of autoimmune diseases, including rheumatoid arthritis, inflammatory bowel disease, and T1D. In T1D, immune cells called T lymphocytes attack and destroy insulin-secreting pancreatic beta cells and the pancreas stops producing insulin, the hormone that controls blood sugar levels.

“Although it might be an ultimately unsuccessful attempt of the pancreas to limit the adaptive T cell response responsible for destroying beta cells, this finding that the ductal cells are capable of playing this suppressive role towards autoimmune T cell responses is unprecedented,” said co-senior author Klaus Kaestner, PhD, the Thomas and Evelyn Suor Butterworth Professor in Genetics. “Our study shows that these cells, which had never previously been linked to immunity, may change themselves to protect the pancreas.”

Established in 2016, the Human Pancreas Analysis Program (HPAP) is supported by a $28 million grant from the National Institutes of Health with major contributions from Penn, the University of Florida and Vanderbilt University. The HPAP, which is co-directed by Kaestner and Ali Naji MD, PhD, the J. William White Professor of Surgical Research, started collecting pancreatic tissues from hundreds of deceased organ donors diagnosed with T1D. Because many T1D patients harbor beta cell autoantibodies called Glutamic Acid Decarboxylase (GAD) in their bloodstream years before clinical diagnosis, HPAP also collects samples from autoantibody-positive donors, who are at risk for developing T1D but have not received that diagnosis.

“Our study took those quality tissue samples and created high-resolution measurements of millions of cells from patients at various stages of T1D progression, resulting in a single-cell atlas of pancreatic islets,” said co-senior author R. Babak Faryabi, PhD, an assistant professor of Pathology and Laboratory Medicine and a core member of Epigenetics Institute at Penn.

Blood tests to check for levels of GAD are common for patients with, or at risk for, T1D, and doctors use it as a diagnostic tool. Another finding of this study is the new understanding of what is happening on a molecular level in the pancreas and how it correlates to the findings of the GAD test.

“Our study is the first to show that even when a person is not clinically considered to have T1D, high levels detected in their GAD test indicate large-scale transcriptional remodeling of their beta cells,” said Naji, a study co-senior author. “It solidifies to clinicians to closely monitor patients with increasing levels of GAD, as we now know what cellular and molecular changes are in motion in relation to those levels.”

Although researchers do not yet know whether these transcriptional changes are contributing to or are consequences of disease pathogenesis, the discovery of molecular phenotypic changes in pancreatic cells of autoantibody-positive individuals advances the understanding of early pancreatic changes occurring in T1D, and sets the course for continued research in this area.

Source:

University of Pennsylvania School of Medicine

Journal reference:

Fasolino, M., et al. (2022) Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes. Nature Metabolism. doi.org/10.1038/s42255-022-00531-x.

Posted on by

Angiotensinogen and Risk of Stroke Events in Patients with Type 2 Diab | DMSO

Angiotensinogen and Risk of Stroke Events in Patients with Type 2 Diab | DMSO

Introduction

Type 2 diabetes has been considered a vital risk factor for promoting the occurrence and/or development of cardiovascular disease (CVD), such as stroke and coronary heart disease (CHD), and CVD mortality.1–3 Previous studies have shown that individuals with type 2 diabetes may have different severities of the disease, which depends on the presence of comorbidities or other risk factors.4 Well-understood risk heterogeneity and identifying individuals at long-term risk could help improve and personalize cardiovascular risk management for these individuals with type 2 diabetes.

Activation of the renin-angiotensin system (RAS) is a vital pathophysiological mechanism of CVD and renal insufficiency in diabetic patients.5 Many previous observational studies have demonstrated that inhibiting the RAS, which is currently the front-line treatment for diabetic nephropathy,5 could delay worsening renal function and reduce the risk of CVD morbidity and mortality in patients with diabetes.6–8 Importantly, although RAS inhibition has shown many beneficial effects, not all patients showed significant improvements in the prognosis of CVD complications. Hence, accurately estimating the active state of the intrarenal RAS might provide a good opportunity to help identify whether diabetic patients are at high risk of poor prognosis. The kidney has all parts of the RAS pathway that can produce angiotensinogen, which further promotes the production of angiotensin II (angII).9 AngII, produced by the kidney, has been reported to pose a key role in renal function and hemodynamics, affecting the development of cardiovascular pathology.10

Recently, several cross-sectional studies have reported that urinary angiotensinogen may be considered a potential biomarker of renal dysfunction in hypertensive patients.11,12 However, whether urinary and/or serum levels of angiotensinogen can be considered potential biomarkers for predicting stroke risk is still unclear. In this study, we measured urinary and serum levels of angiotensinogen in patients with type 2 diabetes. We aimed to assess whether angiotensinogen levels are associated with stroke prognosis.

Methods

Study Sample

We studied 488 hospitalized patients with type 2 diabetes from Tianjin Nankai Hospital in China between January 2009 and December 2015. None of the included patients had other serious chronic diseases, such as cancers, liver diseases, or respiratory diseases, before admission. After discharge, the patients with type 2 disease were contacted by telephone. A total of 21 patients with type 2 diabetes were excluded from this cohort study due to the diagnosis of serious chronic diseases within three months before admission, including neoplastic diseases (N=10), liver diseases (N=7) and other serious diseases (N=4). The diagnostic criteria for type 2 diabetes were determined by 3 endocrinologists.13 For the purposes of this study, during a mean follow-up of 5 years, ischemic or hemorrhagic stroke requiring hospitalization was defined as an endpoint event. The endpoint event was diagnosed by two neurologists. The Ethics Committee of Tianjin Nankai Hospital approved this study. This was a retrospective study, so this study applied for patients informed exemption according to the Declaration of Helsinki guidelines.

Follow-Up

The included diabetic patients were followed up by telephone and/or reviewing, until the occurrence of endpoint events. The endpoint events of this study were defined as ischemic stroke requiring rehospitalization, hemorrhagic stroke requiring rehospitalization and death caused by stroke. During the 5-year follow-up period, 7 patients with diabetes were lost to follow-up.

Measurement of Serum and Urinary Angiotensinogen Levels

Fasting venous blood samples were obtained from the diabetic patients in the first morning after inclusion. The concentrations of angiotensinogen in urine and serum samples were measured by using enzyme-linked immunosorbent assays (ELISA) at baseline.14 Angiotensinogen concentrations were tested three times in each patient, and the average value of the three results was used for statistical analysis. The interassay and intra-assay coefficients of variability for the serum and urine angiotensinogen assays were 6.5% and 4.5%, respectively.

The blood samples were also measured for serum albumin (ABL), glycosylated hemoglobin (HbA1c), hemoglobin (Hb), low density lipoprotein (LDL), high sensitivity C-reactive protein (hs-CRP) and high density lipoprotein (HDL) levels and were tested at the same time by using immunoassay on an ELECSYS2010 instrument (Roche Diagnostics, Germany). Serum levels of the estimated glomerular filtration rate (eGFR) were calculated by using the Chronic Kidney Disease (CKD) Epidemiology Collaboration equation.15 For research purposes, an eGFR<60 mL/min/1.73 m2 was considered renal insufficiency.

Statistical Analysis

All of the data were analyzed by using SPSS 22.0, and a P ≤ 0.05 was considered to be statistically significant. The Kolmogorov–Smirnov test was used to analyze the normality of the data. t-tests or chi-square tests were performed to compare the two groups (eGFR≥60 mL/min/1.73 m2 and eGFR<60 mL/min/1.73 m2). In the multivariate analysis, Cox regression analysis was performed to identify the independent values of serum and urinary angiotensinogen levels at baseline on predicting the risk of stroke events in patients with type 2 diabetes. To further evaluate the independent association, we further excluded the effect of “duration of diabetes” by sensitivity analysis. Moreover, we also analyzed the association between serum and urinary angiotensinogen levels at baseline and the risk of stroke events during the follow-up period using stratified analysis by adding “taking RAS inhibitors” and “an eGFR≥60 mL/min/1.73 m2”. Additionally, an endpoint (stroke event)-free curve was constructed by the Kaplan–Meier method, and the Log rank test was performed.

Results

Clinical Characteristics of the 467 Patients with Type 2 Diabetes at Baseline

The clinical characteristics of the patients with type 2 diabetes at baseline are presented in Table 1. According to the median value of the eGFR (57 mL/min/1.73 m2), all the patients were divided into two groups. The patients with low eGFRs (<57 mL/min/1.73 m2) tended to have longer durations of diabetes, higher systolic and diastolic blood pressures, and higher rates of ever being a smoker, ever being a drinker, taking RAS inhibitors and having a CVD history, compared with patients with high eGFRs (≥57 mL/min/1.73 m2, all P<0.05). For laboratory measurements, the patients with low eGFRs had higher levels of urinary angiotensinogen, LDL, HbA1c and Hs-CRP and lower levels of ALB and Hb than those with high eGFRs (all P<0.05). Interestingly, serum angiotensinogen was not significantly different between the two groups (P>0.05).

Table 1 Clinical Characteristics in 467 Patients with Type 2 Diabetes at Baseline

Cox Proportional Hazard Analysis for the Associations Between Serum and Urinary Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes

All included patients were prospectively followed up for a median period of 5 years, and 47 patients had stroke events (including ischemic and hemorrhagic stroke). Kaplan–Meier analysis showed that patients with low eGFRs (<57 mL/min/1.73 m2) had a significantly higher rate of stroke events than those with high eGFRs (Figure 1, P=0.040). To further investigate the potential risk for stroke events, a multivariate Cox proportional hazard regression model was used. Urinary angiotensinogen levels (HR=2.78, 95% CI 1.54–5.94, P=<0.001) were associated with an increased risk of stroke events when adjustments for age, sex, BMI, ever smoking and ever drinking were made, which was similar to serum angiotensinogen levels (HR=1.54, 95% CI 1.10–3.27, P=0.037) in Model 1 (Table 2). The significant associations changed slightly after adding systolic and diastolic blood pressures and CVD history in Model 1. After continuing to add the laboratory measurements into Model 2, our results suggested that urinary angiotensinogen levels (HR=2.74, 95% CI 1.50–5.88, P=<0.001, Model 3) were an independent predictor for the risk of stroke events in patients with type 2 diabetes, but not serum angiotensinogen levels (HR=1.42, 95% CI 0.95–2.65, P=0.071, Model 3).

Table 2 Cox Proportional Hazard Analysis for the Association Between Urinary and Serum Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes

Figure 1 Kaplan–Meier analysis of the endpoint-free curve stratified into 2 groups by median level of the eGFR.

We performed an additional sensitivity analysis to evaluate the associations of urinary and serum angiotensinogen levels with the risk of stroke events in patients with type 2 diabetes by adding “duration of diabetes” as a covariate (Table 3). Similarly, the results also suggested that higher urinary angiotensinogen levels still contributed to an increased risk of stroke events (HR=2.71, 95% CI 1.48–5.82, P<0.001, Model 3), but not serum angiotensinogen levels (HR=1.37, 95% CI 0.89–2.21, P=0.104, Model 3), after adjusting for the confounding factors.

Table 3 Sensitivity Analysis for the Association Between Urinary and Serum Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes

Stratified Analysis of the Associations Between Urinary and Serum Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes by “Taking RAS Inhibitors” and “an eGFR≥60 mL/Min/1.73 M2”

Stratified analysis was performed by adding “taking RAS inhibitors” and “an eGFR≥60 mL/min/1.73 m2” as covariates. Our results still showed that the association between urinary angiotensinogen levels and the risk of stroke events in patients with type 2 diabetes was significant (HR=2.64, 95% CI 1.45–5.78, P<0.001, Model 3) and was not affected by “taking RAS inhibitors”, as shown in Table 4. Importantly, the significant association was affected by “an eGFR≥60 mL/min/1.73 m2”, as shown in Table 5. We found that a significant association existed only in patients with eGFRs<60 mL/min/1.73 m2 (HR=2.78, 95% CI 1.59–6.30, P<0.001, Model 3) and not in patients with eGFRs≥60 mL/min/1.73 m2 (HR=1.39, 95% CI 0.95–3.53, P=0.054, Model 3). In addition, serum angiotensinogen levels still had no association with the risk of stroke events in the stratified analysis.

Table 4 Stratified Analysis for the Association Between Urinary and Serum Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes by “Taking RAS Inhibitors”

Table 5 Stratified Analysis for the Association Between Urinary and Serum Angiotensinogen Levels and Stroke Events in Patients with Type 2 Diabetes by “Egfr≥60 mL/Min/1.73 M2”

Discussion

In the present study, our baseline data suggested that patients with higher urinary levels of angiotensinogen had lower eGFRs. However, serum levels of angiotensinogen were not associated with the eGFR. Moreover, Cox regression analysis suggested that diabetic patients with high levels of urinary angiotensinogen had a high rate of stroke events. Our results documented that increasing urinary angiotensinogen levels were associated with a higher risk for stroke events in diabetic patients. Furthermore, the significant relationship of urinary angiotensinogen levels with stroke risk can be affected by renal function.

Although previous studies have documented that angiotensinogen can be produced and secreted from both the liver and kidneys,10 serum and urinary levels of angiotensinogen originating from different sources pose different impacts on renal function.16,17 Existing evidence suggests that human angiotensinogen cannot be detected in urine obtained from hypertensive and nonhypertensive rats that were injected with human angiotensinogen, which may be explained by the limited glomerular permeability of circulating angiotensinogen and/or degrading angiotensinogen in tubules.18 Under normal renal structure and function, it has been reported that angiotensinogen is expressed in proximal tubular cells and released into the ureter.10 However, in the case of hyperglycemia, the expression of angiotensinogen is significantly increased in proximal tubular cells.19,20 Furthermore, some clinical investigations have reported that diabetic patients have higher urinary angiotensinogen levels,21 whereas there was no difference in serum angiotensinogen levels between diabetic patients and control individuals.21 This previous evidence may suggest that blood angiotensinogen is not a direct source of urinary angiotensinogen. Consistently, our results also suggested that urinary angiotensinogen originates locally from the kidney instead of serum.

Increased angiotensinogen expression in tubules can promote the activation of the intrarenal RAS. Consistent with our study, diabetic patients with low eGFRs had a greater increase in urinary angiotensinogen levels than serum angiotensinogen levels. One similar finding showed that CKD patients with low eGFRs documented higher urinary angiotensinogen levels, suggesting a negative relationship between urinary angiotensinogen levels and renal function.22 Studies have long confirmed the correlation between abnormal renal function and CVDs.23 Our multivariate correlational analysis reported that elevated levels of urinary angiotensinogen contributed to high stroke risk. Hence, the increased levels of urinary angiotensinogen might contribute to the pathological development of stroke, which may be explained by renal dysfunction and/or the incidence of CVD caused by diabetes mellitus.

Our results have several obvious strengths. On the one hand, in the first morning after admission, blood and urinary tests can better reflect the levels of serum and urinary angiotensinogen in diabetic patients. We are the first to find that urinary angiotensinogen can be considered a valuable predictor for endpoints (stroke events requiring rehospitalization) in diabetic patients. On the other hand, our study confirmed complete follow-up and standardized adjudication of the endpoint, so our results are very reliable. Certainly, this study also has several limitations, including a small sample size in a single center. First, although many various confounding factors, including renal function, were adjusted in our study, which may be the most important factor influencing urinary angiotensinogen levels, some other potential confounding factors were not eliminated due to other unknown determinants of urinary angiotensinogen levels. Second, because urinary levels of angiotensinogen were measured in the first morning after admission, the time-dependent variables after discharge were not assessed, which might cause survivorship biases. Third, using many covariates in our Cox regression analysis may have caused overfitting of the model, leading to bias in the results. Finally, we did not further investigate the mechanisms underlying the association of urinary angiotensinogen levels with stroke. Additionally, our study only included the Asian race and limits the generalizability of our results to other races, such as white and black races. In summary, these limitations should be considered in future studies to elaborate on this work.

Conclusions

Our results suggested that elevated urinary levels of angiotensinogen contributed to higher stroke risk in diabetic patients. Reducing urinary levels of angiotensinogen might be a new biomarker to reduce stroke risk.

Funding

There is no funding to report.

Disclosure

The authors report no conflicts of interest in this work.

References

1. Roger VL, Go AS, Lloyd-Jones DM, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics–2011 update: a report from the American Heart Association. Circulation. 2011;123(4):e18–e209. doi:10.1161/CIR.0b013e3182009701

2. Selvin E, Juraschek SP, Coresh J. Kidney disease in people with diabetes: the expanding epidemic. Am J Kidney Dis. 2012;59(3):340–342. doi:10.1053/j.ajkd.2011.11.016

3. Foster MC, Rawlings AM, Marrett E, et al. Cardiovascular risk factor burden, treatment, and control among adults with chronic kidney disease in the United States. Am Heart J. 2013;166(1):150–156. doi:10.1016/j.ahj.2013.03.016

4. Di Angelantonio E, Kaptoge S, Wormser D, et al.; Emerging Risk Factors Collaboration. Association of cardiometabolic multimorbidity with mortality. JAMA. 2015;314(1):52–60. doi:10.1001/jama.2015.7008

5. Koya D, Araki S, Haneda M. Therapeutic management of diabetic kidney disease. J Diabetes Investig. 2011;2(4):248–254. doi:10.1111/j.2040-1124.2011.00112.x

6. Lewis EJ, Hunsicker LG, Clarke WR, et al.; Collaborative Study Group. Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med. 2001;345(12):851–860. doi:10.1056/NEJMoa011303

7. Brenner BM, Cooper ME, de Zeeuw D, et al.; RENAAL Study Investigators. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med. 2001;345(12):861–869. doi:10.1056/NEJMoa011161

8. Fried LF, Emanuele N, Zhang JH, et al.; VA NEPHRON-D Investigators. Combined angiotensin inhibition for the treatment of diabetic nephropathy. N Engl J Med. 2013;369(20):1892–1903. doi:10.1056/NEJMoa1303154

9. Ingelfinger JR, Zuo WM, Fon EA, Ellison KE, Dzau VJ. In situ hybridization evidence for angiotensinogen messenger RNA in the rat proximal tubule. An hypothesis for the intrarenal renin angiotensin system. J Clin Invest. 1990;85(2):417–423. doi:10.1172/JCI114454

10. Kobori H, Nangaku M, Navar LG, Nishiyama A. The intrarenal renin-angiotensin system: from physiology to the pathobiology of hypertension and kidney disease. Pharmacol Rev. 2007;59(3):251–287. doi:10.1124/pr.59.3.3

11. Kobori H, Alper AB Jr, Shenava R, et al. Urinary angiotensinogen as a novel biomarker of the intrarenal renin-angiotensin system status in hypertensive patients. Hypertension. 2009;53(2):344–350. doi:10.1161/HYPERTENSIONAHA.108.123802

12. Kobori H, Ohashi N, Katsurada A, et al. Urinary angiotensinogen as a potential biomarker of severity of chronic kidney diseases. J Am Soc Hypertens. 2008;2(5):349–354. doi:10.1016/j.jash.2008.04.008

13. Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet. 2017;389(10085):2239–2251. doi:10.1016/S0140-6736(17)30058-2

14. Katsurada A, Hagiwara Y, Miyashita K, et al. Novel sandwich ELISA for human angiotensinogen. Am J Physiol Renal Physiol. 2007;293(3):F956–60. doi:10.1152/ajprenal.00090.2007

15. Krogh J, Benros ME, Martin Balslev J, et al. The association between depressive symptoms, cognitive function, and inflammation in major depression[J]. Brain Behav Immun. 2014;35(1):70–76. doi:10.1016/j.bbi.2013.08.014

16. Sawaguchi M, Araki SI, Kobori H, et al. Association between urinary angiotensinogen levels and renal and cardiovascular prognoses in patients with type 2 diabetes mellitus. J Diabetes Investig. 2012;3(3):318–324. doi:10.1111/j.2040-1124.2011.00172.x

17. Yasue S, Masuzaki H, Okada S, et al. Adipose tissue-specific regulation of angiotensinogen in obese humans and mice: impact of nutritional status and adipocyte hypertrophy. Am J Hypertens. 2010;23(4):425–431. doi:10.1038/ajh.2009.263

18. Kobori H, Nishiyama A, Harrison-Bernard LM, Navar LG. Urinary angiotensinogen as an indicator of intrarenal Angiotensin status in hypertension. Hypertension. 2003;41(1):42–49. doi:10.1161/01.HYP.0000050102.90932.CF

19. Ohashi N, Urushihara M, Satou R, Kobori H. Glomerular angiotensinogen is induced in mesangial cells in diabetic rats via reactive oxygen species–ERK/JNK pathways. Hypertens Res. 2010;33(11):1174–1181. doi:10.1038/hr.2010.143

20. Hsieh TJ, Zhang SL, Filep JG, Tang SS, Ingelfinger JR, Chan JS. High glucose stimulates angiotensinogen gene expression via reactive oxygen species generation in rat kidney proximal tubular cells. Endocrinology. 2002;143(8):2975–2985. doi:10.1210/endo.143.8.8931

21. Saito T, Urushihara M, Kotani Y, Kagami S, Kobori H. Increased urinary angiotensinogen is precedent to increased urinary albumin in patients with type 1 diabetes. Am J Med Sci. 2009;338(6):478–480. doi:10.1097/MAJ.0b013e3181b90c25

22. Yamamoto T, Nakagawa T, Suzuki H, et al. Urinary angiotensinogen as a marker of intrarenal angiotensin II activity associated with deterioration of renal function in patients with chronic kidney disease. J Am Soc Nephrol. 2007;18(5):1558–1565. doi:10.1681/ASN.2006060554

23. Annon CP, Perkovic V, Agarwal R, et al. Evaluating the Effects of Canagliflozin on Cardiovascular and Renal Events in Patients With Type 2 Diabetes Mellitus and Chronic Kidney Disease According to Baseline HbA1c, Including Those With HbA1c <7%: results from the credence trial. Circulation. 2020;141(5):407–410. doi:10.1161/CIRCULATIONAHA.119.044359