Prediabetes is associated with lower brain gray matter volume in the general population. The Study of Health in Pomerania (SHIP)

A systematic review of the impact of type 2 diabetes on brain cortical thickness

Introduction

Type 2 diabetes (T2D) has been linked to cognitive impairment and dementia, but its impact on brain cortical structures in individuals prior to or without cognitive impairment remains unclear.

Methods

We conducted a systematic review of 2,331 entries investigating cerebral cortical thickness changes in T2D individuals without cognitive impairment, 55 of which met our inclusion criteria.

Results

Most studies (45/55) reported cortical brain atrophy and reduced thickness in the anterior cingulate, temporal, and frontal lobes between T2D and otherwise cognitively healthy controls. However, the balance of studies (10/55) reported no significant differences in either cortical or total brain volumes. A few reports also noticed changes in the occipital cortex and its gyri. As part of the reports, less than half of studies (18/55) described a correlation between T2D and hippocampal atrophy. Variability in sample characteristics, imaging methods, and software could affect findings on T2D and cortical atrophy.

Discussion

In conclusion, T2D appears linked to reduced cortical thickness, possibly impacting cognition and dementia risk. Microvascular disease and inflammation in T2D may also contribute to this risk. Further research is needed to understand the underlying mechanisms and brain health implications.

Chronic disease outcome metadata from German observational studies - public availability and FAIR principles

Metadata from epidemiological studies, including chronic disease outcome metadata (CDOM), are important to be findable to allow interpretability and reusability. We propose a comprehensive metadata schema and used it to assess public availability and findability of CDOM from German population-based observational studies participating in the consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health). Additionally, principal investigators from the included studies completed a checklist evaluating consistency with FAIR principles (Findability, Accessibility, Interoperability, Reusability) within their studies. Overall, six of sixteen studies had complete publicly available CDOM. The most frequent CDOM source was scientific publications and the most frequently missing metadata were availability of codes of the International Classification of Diseases, Tenth Revision (ICD-10). Principal investigators' main perceived barriers for consistency with FAIR principles were limited human and financial resources. Our results reveal that CDOM from German population-based studies have incomplete availability and limited findability. There is a need to make CDOM publicly available in searchable platforms or metadata catalogues to improve their FAIRness, which requires human and financial resources.

SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center

The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Association of hepatic steatosis derived from ultrasound and quantitative MRI with prediabetes in the general population

The aim of our study was to investigate the association of hepatic steatosis derived from quantitative ultrasound and magnetic resonance imaging (MRI) with prediabetes in a large population-based study conducted in Northeast Germany. Hepatic steatosis was assessed through transabdominal ultrasound and quantitative MRI. For analysis we included 1622 subjects with MRI who participated in an oral glucose tolerance test and reported no known type 2 diabetes mellitus (T2DM). We classified participants as proposed by the American Diabetes Association: isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), combined IFG and IGT (IFG + IGT), and undiagnosed T2DM. Regression models were adjusted for age, sex body mass index and alcohol consumption. We observed positive associations of hepatic steatosis with glycated hemoglobin, fasting glucose and insulin, 2-h glucose and insulin, as well as homeostasis model assessment-insulin resistance index. Similarly, individuals having hepatic steatosis as defined by MRI had a higher relative risk ratio (RR) to be in the prediabetes groups i-IFG (RR = 1.6; 95% confidence interval (CI) 1.2; 2.2), i-IGT (RR = 3.3, 95% CI 2.0; 5.6) and IFG + IGT (RR = 2.5, 95% CI 1.6; 3.9) or to have undiagnosed T2DM (RR = 4.8, 95% CI 2.6; 9.0). All associations were attenuated when defining hepatic steatosis by ultrasound. Hepatic steatosis is associated with prediabetes and undiagnosed T2DM in the general population. Quantitative liver MRI revealed stronger associations with prediabetes and undiagnosed T2DM compared to ultrasound, which indicates the higher sensitivity and specificity of MRI to determine hepatic steatosis.

Brain deficits in prediabetic adults: A systematic review

Previous findings on the relationship between prediabetes (the precursor stage of type 2 diabetes) and brain health in humans are inconsistent. Thus, this systematic review of cross-sectional and longitudinal studies aimed to summarize what is currently known about brain deficits in prediabetic adults. Following the PRISMA reporting standards for systematic reviews, we conducted a comprehensive review of peer-reviewed journal articles published from 2009 to present, focusing on studies that assessed brain volume, structural connectivity, and cerebrovascular health in prediabetic adults and older adults (i.e., 18 years or older). We systematically searched PsychINFO, Scopus, Web of Science, Ovid MEDLINE, CINAHL, and EMbase databases. Quality assessment was based on the NIH Quality Assessment Tool for Observational and Cross-sectional Studies. In total, 19 studies were included in our review. Results from these studies show that prediabetes may be associated with deficits in brain structure and pathology, however, several studies also refute these findings. Moreover, we identified clear inconsistencies in study methodologies, including diabetes measures and classification, across studies that may account for these conflicting findings.

Obesity is associated with reduced orbitofrontal cortex volume: A coordinate-based meta-analysis

Neural models of obesity vary in their focus upon prefrontal and striatal differences. Animal and human studies suggest that differential functioning of the orbitofrontal cortex is associated with obesity. However, meta-analyses of functional neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity. Meta-analyses of structural imaging studies of obesity have shown mixed findings with regards to an association with reduced orbitofrontal cortex gray matter volume. To clarify these findings, we conducted a meta-analysis of 25 voxel-based morphometry studies, and found that greater body mass index is associated with decreased gray matter volume in the right orbitofrontal cortex (Brodmanns' areas 10 and 11), where family-wise corrected p < .05, N = 7,612. Use of the right orbitofrontal cortex as a seed in a Neurosynth Network Coactivation analysis showed that this region is associated with activity in the left frontal medial cortex, left temporal lobe, right precuneus cortex, posterior division of the left middle temporal gyrus, and right frontal pole. When Neurosynth Network Coactivation results were submitted as regions of interest in the Human Connectome Project data, we found that greater body mass index was associated with greater activity in left frontal medial cortex response to the Gambling Task, where p < .05, although this did not survive Bonferroni-correction. Our findings highlight the importance of the orbitofrontal cortex structure and functioning in neural models of obesity. Exploratory analyses suggest more studies are needed that examine the functional significance of reduced orbitofrontal cortex gray matter volume in obesity, and the effect of age and weight changes on this relationship using longitudinal designs.

Association of impaired fasting glucose and Type 2 Diabetes Mellitus with brain volume changes in Alzheimer's Disease patients analyzed by MRI: a retrospective study

Objectives

Alzheimer’s disease (AD), impaired fasting glucose (IFG), and Type 2 diabetes mellitus (T2DM) were reported associated with smaller brain volumes. Nevertheless, the association of hyperglycemia with brain volume changes in AD patients remains unclear. To investigate this issue, structural magnetic resonance imaging was used to compare brain volumes among AD patients with different fasting glucose levels.

Methods

Eighty-five AD patients were divided into three groups based on their fasting glucose level as suggested by the American Diabetes Association: normal fasting glucose group (AD_NFG, n = 45), AD_IFG group (n = 15), and AD_T2DM group (n = 25). Sagittal 3D T1-weighted images were obtained to calculate the brain volume. Brain parenchyma and 33 brain structures were automatically segmented. Each regional volume was analyzed among groups. For regions with statistical significance, partial correlation analysis was used to evaluate their relationships with fasting glucose level, corrected for Mini-Mental State Examination score, age, education level, cholesterol, triglyceride, and blood pressure.

Results

Compared with the AD_IFG and AD_NFG groups, the volume of pons in AD_T2DM group was significantly smaller. Fasting glucose was negatively correlated with pontine volume.

Conclusions

T2DM may exacerbate pontine atrophy in AD patients, and fasting glucose level is associated with pontine volume.

Associations Between Cardiovascular Risk, Structural Brain Changes, and Cognitive Decline

BACKGROUND

The impact of cardiovascular risk burden on cognitive trajectories and brain structure changes remains unclear.

OBJECTIVES

This study aimed to examine whether cardiovascular risk burden assessed by the Framingham General Cardiovascular Risk Score (FGCRS) is associated with cognitive decline and structural brain differences.

METHODS

Within the Rush Memory and Aging Project, 1,588 dementia-free participants (mean age: 79.5 years) were followed for up to 21 years. FGCRS was assessed at baseline and categorized into tertiles (lowest, middle, and highest). Episodic memory, semantic memory, working memory, visuospatial ability, and perceptual speed were assessed annually with a battery of 19 tests, from which composite scores were derived. A subsample (n = 378) of participants underwent magnetic resonance imaging. Structural total and regional brain volumes were estimated. Data were analyzed using linear mixed-effects models and linear regression models.

RESULTS

In all participants, FGCRS ranged from 4 to 28 (mean score: 15.6 ± 3.7). Compared with the lowest tertile of FGCRS, the highest tertile was associated with faster decline in global cognition (β = -0.019; 95% confidence interval [CI]: -0.035 to -0.003), episodic memory (β = -0.023; 95% CI: -0.041 to -0.004), working memory (β = -0.021; 95% CI: -0.035 to -0.007), and perceptual speed (β = -0.027; 95% CI: -0.042 to -0.011) over the follow-up. In magnetic resonance imaging data analyses, higher FGCRS was related to smaller volumes of the hippocampus (β = -0.021; 95% CI: -0.042 to -0.000), gray matter (β = -1.569; 95% CI: -2.757 to -0.382), and total brain (β = -1.588; 95% CI: -2.832 to -0.344), and greater volume of white matter hyperintensities (β = 0.035; 95% CI: 0.001 to 0.069).

CONCLUSIONS

Higher cardiovascular risk burden may predict decline in episodic memory, working memory, and perceptual speed and is associated with neurodegeneration and vascular lesions in the brain.

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p < 0.001). These findings are relevant for preventive and therapeutic considerations and for neuroimaging studies, as they suggest to take information on metabolic status and renal function into account as potential confounders.

Glucose and insulin levels are associated with arterial stiffness and concentric remodeling of the heart

BACKGROUND

Mortality attributable to heart failure remains high. The prevalence of heart failure in patients with diabetes mellitus ranges from 19 to 26%. It is estimated that up to 21.1 million adults in the United States have diagnosed diabetes mellitus and around 80.8 million have impaired fasting glucose. We investigated the associations of fasting glucose (FG) and fasting insulin (FI), the homeostasis model assessment-insulin resistance index (HOMA-IR) and 2-h postload glucose (2HG) and insulin (2HI) with parameters of left ventricular geometry and function and arterial stiffness determined by magnetic resonance imaging in individuals without diagnosed type 2 diabetes.

METHODS

Cross-sectional analyses of 1001 individuals (453 women, 45.3%), aged 21 to 80 years, from two independent population-based studies, the Study of Health in Pomerania (SHIP-TREND-0) and KORA FF4 Study. FG, FI, HOMA-IR, 2HG and 2HI, as well as glucose tolerance categories, were analyzed for associations with heart and arterial parameters using multivariable-adjusted linear regression models.

RESULTS

In total, 390 individuals (39%) had prediabetes (isolated impaired fasting glucose, isolated glucose tolerance or both), and 49 (4.9%) were found to have unknown type 2 diabetes. In the multivariable-adjusted analysis, positive linear associations of FG, FI, HOMA-IR, 2HG and 2HI with arterial stiffness index and left ventricular wall-thickness and concentricity and inverse linear associations with left ventricular end-diastolic volume were observed. A 1 mmol/l higher FG was associated with a 1.18 ml/m^2.7 (1.80 to 0.57; p < 0.001) lower left ventricular end-diastolic volume index, a 0.042 mm/m^2.7 (0.014 to 0.070) higher left ventricular wall-thickness index, a 0.12 mmHg m^2.7/ml (0.06 to 0.17; p < 0.001) greater arterial stiffness index and a 0.037 g/ml (0.018 to 0.056; p < 0.001) higher left ventricular concentricity.

CONCLUSIONS

Our findings suggest that higher glucose levels in the prediabetic range and insulin resistance might lead to higher arterial stiffness and concentric remodeling of the heart.

Effects of adiposity and metabolic dysfunction on cognition: A review

Obesity and metabolic dysfunction are both correlated with increased rates of cognitive decline. However, because these two conditions often co-occur, it remains unclear whether their cognitive consequences are independent. In this review, we carefully consider literature examining the effects of metabolic dysfunction and increased adiposity on cognition across the lifespan, including only well-controlled studies that attempt to dissociate their effects. We found a total of 36 studies, 17 examining metabolic dysfunction and 19 examining the effects of adiposity. We found evidence from the literature suggesting that increased adiposity and metabolic dysfunction may contribute to deficits in executive function, memory, and medial temporal lobe structures largely independent of one another. These deficits are thought to arise principally from physiological changes associated with inflammation, vascularization, and oxidative stress, among others. Such processes may result from excess adipose tissue and insulin resistance that occur independently and can further exacerbate when the two conditions co-occur. However, we also find it likely that impaired cognition plays a role in behavioral and lifestyle choices that lead to increased adiposity and metabolic dysfunction, which can then perpetuate and augment cognitive decline. We recommend additional prospective and longitudinal studies to examine whether impaired cognition is a cause and/or consequence of these factors.

Changes in default mode network connectivity in different glucose metabolism status and diabetes duration

Aims/hypotheses

It is now generally accepted that diabetes increases the risk for cognitive impairment, but the precise mechanisms are poorly understood. In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly used to investigate the neural basis of cognitive dysfunction in type 2 diabetes (T2D) patients. Alterations in brain functional connectivity may underlie diabetes-related cognitive dysfunction and brain damage. The aim of this study was to investigate the changes in default mode network (DMN) connectivity in different glucose metabolism status and diabetes duration.

Methods

We used a seed-based fMRI analysis to investigate positive and negative DMN connectivity in four groups (39 subjects with normal glucose metabolism [NGM], 23 subjects with impaired glucose metabolism [IGM; i.e., prediabetes], 59 T2D patients with a diabetes duration of <10 years, and 24 T2D patients with a diabetes duration of ≥10 years).

Results

Negative DMN connectivity increased and then regressed with deteriorating glucose metabolism status and extending diabetes duration. DMN connectivity showed a significant correlation with diabetes duration.

Conclusion/interpretation

This study suggests that DMN connectivity may exhibit distinct patterns in different glucose metabolism status and diabetes duration, providing some potential neuroimaging evidence for early diagnosis and further understanding of the pathophysiological mechanisms of diabetic brain damage.

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Subjects include NGM, IGM, and T2D with different glucose metabolism status.

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DMN connectivity exhibited distinct patterns in different glucose metabolism status.

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Compensatory enhancement was observed in the negative DMN FC.

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DMN FC showed a significant correlation with diabetes duration.

Moderating Effect of Insulin Resistance on the Relationship between Gray Matter Volumes and Cognitive Function

Background: It is controversial whether exposure to insulin resistance accelerates cognitive deterioration. The present study aimed to investigate the association between insulin resistance and gray matter volume loss to predict the cognitive decline. Methods: We recruited 160 participants (78 with Alzheimer’s disease and 82 without Alzheimer’s disease). Insulin resistance, regional gray matter volume, and cognitive function were assessed. A hierarchical moderated multiple regression (MMR) model was used to determine any associations among insulin resistance, structural changes in the brain, and cognitive decline. Results: The volumes of 7 regions in the gray matter were negatively related to insulin resistance in Alzheimer’s disease (p =0.032). Hierarchical MMR analysis indicated that insulin resistance did not directly affect the cognitive decline but moderated the cognitive decline through the decrease in gray matter volume in the key brain regions, i.e., inferior orbitofrontal gyrus (left), middle cingulate gyrus (right), hippocampus (right), and precuneus (right) (p < 0.05 in each case). Conclusion: Insulin resistance appears to exacerbate the cognitive decline associated with several gray matter volume loss.