Biomarkers of Renal Function in Type 2 Diabetic Patients with Cognitive Impairment

Untargeted Metabolomic Profiling Reveals Differentially Expressed Serum Metabolites and Pathways in Type 2 Diabetes Patients with and without Cognitive Decline: A Cross-Sectional Study

Diabetes is recognized as a risk factor for cognitive decline, but the underlying mechanisms remain elusive. We aimed to identify the metabolic pathways altered in diabetes-associated cognitive decline (DACD) using untargeted metabolomics. We conducted liquid chromatography-mass spectrometry-based untargeted metabolomics to profile serum metabolite levels in 100 patients with type 2 diabetes (T2D) (54 without and 46 with DACD). Multivariate statistical tools were used to identify the differentially expressed metabolites (DEMs), and enrichment and pathways analyses were used to identify the signaling pathways associated with the DEMs. The receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of a set of metabolites. We identified twenty DEMs, seven up- and thirteen downregulated in the DACD vs. DM group. Chemometric analysis revealed distinct clustering between the two groups. Metabolite set enrichment analysis found significant enrichment in various metabolite sets, including galactose metabolism, arginine and unsaturated fatty acid biosynthesis, citrate cycle, fructose and mannose, alanine, aspartate, and glutamate metabolism. Pathway analysis identified six significantly altered pathways, including arginine and unsaturated fatty acid biosynthesis, and the metabolism of the citrate cycle, alanine, aspartate, glutamate, a-linolenic acid, and glycerophospholipids. Classifier models with AUC-ROC > 90% were developed using individual metabolites or a combination of individual metabolites and metabolite ratios. Our study provides evidence of perturbations in multiple metabolic pathways in patients with DACD. The distinct DEMs identified in this study hold promise as diagnostic biomarkers for DACD patients.

Chronic kidney disease and cognitive decline in patients with type 2 diabetes at elevated cardiovascular risk

AIMS

We addressed the question whether chronic kidney disease (CKD) may contribute to cognitive decline in type 2 diabetes.

METHODS

Participants with type 2 diabetes with elevated cardiovascular risk or CKD from cognition substudies of two large trials were studied prospectively (CARMELINA: n = 2666, mean ± SD age 68.1 ± 8.7 years, CAROLINA: n = 4296; 64.7 ± 9.4 years). Estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) at baseline were related to cognitive performance (Mini-Mental State Examination (MMSE) and attention and executive functioning score (A&E)) in linear regression analyses, adjusted for demographics, cardiovascular risk factors and treatment, at baseline and follow-up.

RESULTS

CKD at baseline was more common in CARMELINA than CAROLINA (eGFR<60 in 72.6 % and 19.6 %, macroalbuminuria in 35.0 % and 4.1 %, respectively). Baseline eGFR was related to A&E in CARMELINA (b = 0.02 per 10 ml/min/1.73m², 95%CI [0.01,0.03]). Baseline UACR was related to A&E in CAROLINA (b = -0.01 per doubling of UACR mg/g, 95%CI [-0.02,-0.002]). Baseline UACR predicted decline in A&E in CAROLINA (median 6.1 years follow-up; b = -0.01, 95%CI [-0.03,-0.0001] per doubling of UACR mg/g).

CONCLUSIONS

eGFR and UACR were associated with A&E in two cohorts with type 2 diabetes, enriched for CKD and cardiovascular disease. The small effect size estimates indicate limited impact of kidney dysfunction on cognition in this setting.

GOV IDENTIFIERS

NCT01897532 NCT01243424.

Diagnostic, Prognostic, and Mechanistic Biomarkers of Diabetes Mellitus-Associated Cognitive Decline

Cognitive dysfunctions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and other forms of dementia are recognized as common comorbidities of type 2 diabetes mellitus (T2DM). Currently, there are no disease-modifying therapies or definitive clinical diagnostic and prognostic tools for dementia, and the mechanisms underpinning the link between T2DM and cognitive dysfunction remain equivocal. Some of the suggested pathophysiological mechanisms underlying cognitive decline in diabetes patients include hyperglycemia, insulin resistance and altered insulin signaling, neuroinflammation, cerebral microvascular injury, and buildup of cerebral amyloid and tau proteins. Given the skyrocketing global rates of diabetes and neurodegenerative disorders, there is an urgent need to discover novel biomarkers relevant to the co-morbidity of both conditions to guide future diagnostic approaches. This review aims to provide a comprehensive background of the potential risk factors, the identified biomarkers of diabetes-related cognitive decrements, and the underlying processes of diabetes-associated cognitive dysfunction. Aging, poor glycemic control, hypoglycemia and hyperglycemic episodes, depression, and vascular complications are associated with increased risk of dementia. Conclusive research studies that have attempted to find specific biomarkers are limited. However, the most frequent considerations in such investigations are related to C reactive protein, tau protein, brain-derived neurotrophic factor, advanced glycation end products, glycosylated hemoglobin, and adipokines.

Serum cystatin C levels are negatively correlated with post-stroke cognitive dysfunction

Stroke is the leading cause of death and long-term disability worldwide, and cognitive impairment and dementia are major complications of ischemic stroke. Cystatin C (CysC) has been found to be a neuroprotective factor in animal studies. However, the relationship between CysC levels and cognitive dysfunction in previous studies has revealed different results. This prospective observational study investigated the correlation between serum CysC levels and post-stroke cognitive dysfunction at 3 months. Data from 638 patients were obtained from the China Antihypertensive Trial in Acute Ischemic Stroke (CATIS). Cognitive dysfunction was assessed using the Mini-Mental State Examination (MMSE) at 3 months after stroke. According to the MMSE score, 308 patients (52.9%) had post-stroke cognitive dysfunction. After adjusting for potential confounding factors, the odds ratio (95% CI) of post-stroke cognitive dysfunction for the highest quartile of serum CysC levels was 0.54 (0.30–0.98), compared with the lowest quartile. The correlation between serum CysC and cognitive dysfunction was modified by renal function status. We observed a negative linear dose-response correlation between CysC and cognitive dysfunction in patients with normal renal function (P_linearity = 0.044), but not in those with abnormal renal function. Elevated serum CysC levels were correlated with a low risk of 3-month cognitive dysfunction in patients with acute ischemic stroke, especially in those with normal renal function. The current results suggest that CysC is a protective factor for post-stroke cognitive dysfunction, and could be used to treat post-stroke cognitive dysfunction. The CATIS study was approved by the Institutional Review Boards at Soochow University from China (approval No. 2012-02) on December 30, 2012, and was registered at ClinicalTrials.gov (identifier No. NCT01840072) on April 25, 2013.

Positive correlation between cognitive impairment and renal microangiopathy in patients with type 2 diabetic nephropathy: a multicenter retrospective study

Objective

This study was performed to explore the correlation between cognitive impairment and renal microangiopathy in patients with type 2 diabetic nephropathy (T2DN) by detecting changes in cognitive function and cerebral metabolism in these patients with different stages of T2DN.

Methods

Prospectively maintained databases were reviewed from 2006 to 2017. Blood biochemical indexes and the urinary albumin excretion rate (UAER) were measured in all participants. Cognitive function was assessed by the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA). Cognitive impairment was the primary endpoint. Renal microangiopathy was the secondary endpoint. Pearson correlation analysis was used to assess correlations.

Results

Two hundred sixteen patients with type 2 diabetes mellitus (T2DM) were divided into three groups according to their UAER: T2DM without nephropathy (n=72), early T2DM with nephropathy (n=74), and the clinical stage of early T2DM with nephropathy (n=70). Healthy participants were selected as the normal control group (n=70). Pearson correlation analysis demonstrated that the total MMSE and MoCA score was negatively correlated with the UAER (r=−0.327) and positively correlated with the estimated glomerular filtration rate (r=0.428) in patients with T2DN.

Conclusions

The present study showed a positive correlation between cognitive impairment and renal microangiopathy in patients with T2DN.

Biomarkers for cognitive decline in patients with diabetes mellitus: evidence from clinical studies

Diabetes mellitus is considered as an important factor for cognitive decline and dementia in recent years. However, cognitive impairment in diabetic patients is often underestimated and kept undiagnosed, leading to thousands of diabetic patients suffering from worsening memory. Available reviews in this field were limited and not comprehensive enough. Thus, the present review aimed to summarize all available clinical studies on diabetic patients with cognitive decline, and to find valuable biomarkers that might be applied as diagnostic and therapeutic targets of cognitive impairment in diabetes. The biomarkers or risk factors of cognitive decline in diabetic patients could be classified into the following three aspects: serum molecules or relevant complications, functional or metabolic changes by neuroimaging tools, and genetic variants. Specifically, factors related to poor glucose metabolism, insulin resistance, inflammation, comorbid depression, micro-/macrovascular complications, adipokines, neurotrophic molecules and Tau protein presented significant changes in diabetic patients with cognitive decline. Besides, neuroimaging platform could provide more clues on the structural, functional and metabolic changes during the cognitive decline progression of diabetic patients. Genetic factors related to cognitive decline showed inconsistency based on the limited studies. Future studies might apply above biomarkers as diagnostic and treatment targets in a large population, and regulation of these parameters might shed light on a more valuable, sensitive and specific strategy for the diagnosis and treatment of cognitive decline in diabetic patients.

Cognitive impairment in elderly patients with type 2 diabetes mellitus: prevalence and related clinical factors

Aim

Diabetes mellitus is reported to be a risk factor for dementia. We evaluated the cognitive function in elderly diabetic patients and estimated the prevalence of patients with cognitive impairment and looked for any related clinical factors.

Subjects and methods

Using 281 elderly (65 years of age or older) Japanese patients with type 2 diabetes mellitus who were free of clinically evident cognitive impairment, we evaluated their cognitive function with the Mini Mental State Examination (MMSE).

Results

The MMSE score of all the participants was 27.3 ± 2.4 with 31.3% of them being in the abnormal range (tentatively defined normal range as having an MMSE score of 27-30). Multiple regression analysis disclosed that fasting serum non-esterified fatty acid (NEFA), estimated glomerular filtration ratio (eGFR) and insulin treatment were significantly related factors for the MMSE score, in addition to age and schooling history, which are extremely strong factors.

Conclusions

We revealed that approximately one-third of elderly type 2 diabetic patients who were free of clinically evident cognitive impairment had impaired cognitive function, demonstrating that the MMSE score was significantly correlated with fasting NEFA level, renal function, insulin treatment, age and schooling history.