Variation of HbA1c affects cognition and white matter microstructure in healthy, young adults

The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance

Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of age and insulin resistance to the association of cerebral blood flow and glucose metabolism; both critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Lower cerebral blood flow was also associated with worse working memory and slower reaction time in tasks requiring cognitive flexibility and response inhibition. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive correlation. In insulin resistant younger adults, the association showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates of and associations between cerebral blood flow and glucose metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan.

Associations of depression and perceived physical fatigability with white matter integrity in older adults

BACKGROUNDS

Fatigability is prevalent in older adults. However, it is often associated with depressed mood. We aim to investigate these two psychobehavioral constructs by examining their underpinning of white matter structures in the brain and their associations with different medical conditions.

METHODS

Twenty-seven older adults with late-life depression (LLD) and 34 cognitively normal controls (CN) underwent multi-shell diffusion MRI. Fatigability was measured with the Pittsburgh Fatigability Scale. We examined white matter integrity by measuring the quantitative anisotropy (QA), a fiber tracking parameter with better accuracy than the traditional imaging technique.

RESULTS

We found those with LLD had lower QA in the 2nd branch of the left superior longitudinal fasciculus (SLF-II), and those with more physical fatigability had lower QA in more widespread brain regions. In tracts associated with more physical fatigability, the lower QA in left acoustic radiation and left superior thalamic radiation correlated with higher blood glucose (r = - 0.46 and - 0.49). In tracts associated with depression, lower QA in left SLF-II correlated with higher bilirubin level (r = - 0.58).

DISCUSSION

Depression and fatigability were associated with various white matter integrity changes, which correlated with biochemistry biomarkers all related to inflammation.

The nonlinear association between HbA1c and cognitive impairment in patients with alcohol use disorder

Background: Extensive research has indicated that higher levels of glycated hemoglobin (HbA1c) are associated with poor cognitive performance regardless of the presence of diabetes. To our knowledge, the association between HbA1c levels and cognitive decline in patients with alcohol use disorder is not well understood. This study aimed to investigate whether HbA1c was associated with cognitive impairment in patients with alcohol use disorder. Methods: Patients admitted to the Psychiatry Department of the Third Hospital of Quzhou with a confirmed diagnosis of alcohol-related cognitive impairment were recruited between January 2019 and February 2022. Their HbA1c levels were measured, and they completed the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) after at least one week of monitored abstinence from alcohol. Univariate linear regression, multivariate linear regression and generalized additive models (GAMs) were used to investigate the association of HbA1c with MMSE and MoCA scores. Results: In total, 227 patients were included. Univariate and multivariate regression analyses suggested that HbA1c was negatively associated with MMSE and MoCA scores after adjustment for potential confounders (P < 0.05). The GAM analysis revealed that the relationships between the HbA1c level and the MMSE and MoCA scores were bell-shaped. The inflection points were 5.3% and 5.2% for the MMSE and MoCA respectively. Conclusion: The results of this study suggest that HbA1c levels are significantly related to cognitive impairment in patients with alcohol use disorder. Future studies are required to determine the effects of optimal glucose control in people with alcohol use disorder.

Regional Vulnerability of the Corpus Callosum in the Context of Cardiovascular Risk

Many factors outside of cardiovascular health can impact the structure of white matter. Identification of reliable and clinically meaningful biomarkers of the neural effects of systemic and cardiovascular health are needed to refine etiologic predictions. We examined whether the corpus callosum demonstrates regional vulnerability to systemic cardiovascular risk factors. Three hundred and ninety-four older adults without dementia completed brain MRI, neurobehavioral evaluations, and blood draws. A subset (n = 126, n = 128) of individuals had blood plasma analyzed for inflammatory markers of interest (IL-6 and TNF-alpha). Considering diffusion tensor imaging (DTI) is a particularly reliable measure of white matter integrity, we utilized DTI to examine fractional anisotropy (FA) of anterior and posterior regions of the corpus callosum. Using multiple linear regression models, we simultaneously examined FA of the genu and the splenium to compare their associations with systemic and cardiovascular risk factors. Lower FA of the genu but not splenium was associated with greater systemic and cardiovascular risk, including higher systolic blood pressure (β = -0.17, p = .020), hemoglobin A1C (β = -0.21, p = .016) and IL-6 (β = -0.34, p = .005). FA of the genu was uniquely associated with cognitive processing speed (β = 0.20, p = .0015) and executive functioning (β = 0.15, p = .012), but not memory performances (β = 0.05, p = .357). Our results demonstrated differential vulnerability of the corpus callosum, such that frontal regions showed stronger, independent associations with biomarkers of systemic and cardiovascular health in comparison to posterior regions. Posterior white matter integrity may not reflect cardiovascular health. Clinically, these findings support the utility of examining the anterior corpus callosum as an indicator of cerebrovascular health.

Beyond BMI: cardiometabolic measures as predictors of impulsivity and white matter changes in adolescents

Obesity is characterized by cardiometabolic and neurocognitive changes. However, how these two factors relate to each other in this population is unknown. We tested the association that cardiometabolic measures may have with impulse behaviors and white matter microstructure in adolescents with and without an excess weight. One hundred and eight adolescents (43 normal-weight and 65 overweight/obesity; 11-19 years old) were medically and psychologically (Temperament Character Inventory Revised, Three-Factor Eating Questionnaire-R18, Conners' Continuous Performance Test-II, Stroop Color and Word Test, Wisconsin Card Sorting Test, Kirby Delay Discounting Task) evaluated. A subsample of participants (n = 56) underwent a brain magnetic resonance imaging acquisition. In adolescents, higher triglycerides and having a body mass index indicative of overweight/obesity predicted a more impulsive performance in Conners' Continuous Performance Test-II (higher commission errors). In addition, higher glucose and diastolic blood pressure values predicted increments in the Three-Factor Eating Questionnaire-R18 emotional eating scale. Neuroanatomically, cingulum fractional anisotropy showed a negative relationship with glycated hemoglobin. The evaluation of the neurocognitive differences associated with obesity, usually based on body mass index, should be complemented with cardiometabolic measures.

The link between cognition and somatic conditions related to insulin resistance in the UK Biobank study cohort: a systematic review

Clinical and genomic studies have shown an overlap between neuropsychiatric disorders and insulin resistance (IR)-related somatic conditions, including obesity, type 2 diabetes, and cardiovascular diseases. Impaired cognition is often observed among neuropsychiatric disorders, where multiple cognitive domains may be affected. In this review, we aimed to summarise previous evidence on the relationship between IR-related diseases/traits and cognitive performance in the large UK Biobank study cohort. Electronic searches were conducted on PubMed, Scopus, and Web of Science until April 2022. Eighteen articles met the inclusion criteria and were qualitatively reviewed. Overall, there is substantial evidence for an association between IR-related cardio-metabolic diseases/traits and worse performance on various cognitive domains, which is largely independent of possible confoundings. The most consistent findings referred to IR-related associations with poorer verbal and numerical reasoning ability, as well as slower processing speed. The observed associations might be mediated by alterations in immune-inflammation, brain integrity/connectivity, and/or comorbid somatic or psychiatric diseases/traits. Our findings provide impetus for further research into the underlying neurobiology and possible new therapeutic targets.

Towards the Interpretability of Deep Learning Models for Multi-modal Neuroimaging: Finding Structural Changes of the Ageing Brain

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n=2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture aging at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected aging reflected cardiovascular risk factors and accelerated aging was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-aging in healthy and at-risk individuals throughout adulthood.

Tractography in Type 2 Diabetes Mellitus With Subjective Memory Complaints: A Diffusion Tensor Imaging Study

The brain white matter (WM) structural injury caused by type 2 diabetes mellitus (T2DM) has been linked to cognitive impairment. However, the focus was mainly on the mild cognitive impairment (MCI) stage in most previous studies, with little attention made to subjective memory complaints (SMC). The main purpose of the current study was to investigate the characteristics of WM injury in T2DM patients and its correlation with SMC symptoms. In a group of 66 participants (33 HC and 33 T2DM-S), pointwise differences along WM tracts were identified using the automated fiber quantification (AFQ) approach. Then we investigated the utility of DTI properties along major WM tracts as features to distinguish patients with T2DM-S from HC via the support vector machine (SVM). Based on AFQ analysis, 10 primary fiber tracts that represent the subtle alterations of WM in T2DM-S were identified. Lower fractional anisotropy (FA) in the right SLF tract (r = −0.538, p = 0.0013), higher radial diffusivity (RD) in the thalamic radiation (TR) tract (r = 0.433, p = 0.012), and higher mean diffusivity (MD) in the right inferior fronto-occipital fasciculus (IFOF) tract (r = 0.385, p = 0.0029) were significantly associated with a long period of disease. Decreased axial diffusivity (AD) in the left arcuate was associated with HbA_1c (r = −0.368, p = 0.049). In addition, we found a significant negative correlation between delayed recall and abnormal MD in the left corticospinal tract (r = −0.546, p = 0.001). The FA of the right SLF tracts and bilateral arcuate can be used to differentiate the T2DM-S and the HC at a high accuracy up to 88.45 and 87.8%, respectively. In conclusion, WM microstructure injury in T2DM may be associated with SMC, and these abnormalities identified by DTI can be used as an effective biomarker.

Altered dynamic functional architecture in type 2 diabetes mellitus

INTRODUCTION

Type 2 diabetes mellitus (T2DM) can accelerate cognitive decline and even dementia so that the underlying mechanism deserves further exploration. In the resting state, brain function is still changing dynamically. At present, it is still unknown whether the dynamic functional connectivity (dFC) between various brain regions is in a stable state. It is necessary to interpret brain changes from a new perspective, that is, the stability of brain architecture.

METHODS

In this study, we used a fixed dynamic time scale to explore the stability of dynamic functional architecture in T2DM, then the dynamic effective connectivity (dEC) was used to further explain how information flows through dynamically fluctuating brain architecture in T2DM.

RESULT

Two brain regions with decreased stability were found including the right supra-marginal gyrus (SMG) and the right median cingulate gyrus (MCG) in T2DM subjects. The dEC variation has increased between the left inferior frontal gyrus (IFG) and the right MCG. The direction of causal flow is from the right MCG to the left IFG.

CONCLUSION

The combination of stability and dEC can not only show the stability of dynamic functional architecture in brain but also reflect the fluidity of brain information, which is an innovative and interesting attempt in the field of neuroimaging. The changes of dynamic architecture in T2DM patients may present an innovative perspective and explanation for their cognitive decline.

Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study

Cognitive deficits are central attendant symptoms of major depressive disorder (MDD) with a crucial impact in patients' everyday life. Thus, it is of particular clinical importance to understand their pathophysiology. The aim of this study was to investigate a possible relationship between brain structure and cognitive performance in MDD patients in a well-characterized sample. N = 1007 participants (N_MDD = 482, healthy controls (HC): N_HC = 525) were selected from the FOR2107 cohort for this diffusion-tensor imaging study employing tract-based spatial statistics. We conducted a principal component analysis (PCA) to reduce neuropsychological test results, and to discover underlying factors of cognitive performance in MDD patients. We tested the association between fractional anisotropy (FA) and diagnosis (MDD vs. HC) and cognitive performance factors. The PCA yielded a single general cognitive performance factor that differed significantly between MDD patients and HC (P < 0.001). We found a significant main effect of the general cognitive performance factor in FA (P_tfce-FWE = 0.002) in a large bilateral cluster consisting of widespread frontotemporal-association fibers. In MDD patients this effect was independent of medication intake, the presence of comorbid diagnoses, the number of previous hospitalizations, and depressive symptomatology. This study provides robust evidence that white matter disturbances and cognitive performance seem to be associated. This association was independent of diagnosis, though MDD patients show more pronounced deficits and lower FA values in the global white matter fiber structure. This suggests a more general, rather than the depression-specific neurological basis for cognitive deficits.

MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI

PURPOSE

Diffusion-weighted imaging allows investigators to identify structural, microstructural, and connectivity-based differences between subjects, but variability due to session and scanner biases is a challenge.

METHODS

To investigate DWI variability, we present MASiVar, a multisite data set consisting of 319 diffusion scans acquired at 3 T from b = 1000 to 3000 s/mm2 across 14 healthy adults, 83 healthy children (5 to 8 years), three sites, and four scanners as a publicly available, preprocessed, and de-identified data set. With the adult data, we demonstrate the capacity of MASiVar to simultaneously quantify the intrasession, intersession, interscanner, and intersubject variability of four common DWI processing approaches: (1) a tensor signal representation, (2) a multi-compartment neurite orientation dispersion and density model, (3) white-matter bundle segmentation, and (4) structural connectomics. Respectively, we evaluate region-wise fractional anisotropy, mean diffusivity, and principal eigenvector; region-wise CSF volume fraction, intracellular volume fraction, and orientation dispersion index; bundle-wise shape, volume, fractional anisotropy, and length; and whole connectome correlation and maximized modularity, global efficiency, and characteristic path length.

RESULTS

We plot the variability in these measures at each level and find that it consistently increases with intrasession to intersession to interscanner to intersubject effects across all processing approaches and that sometimes interscanner variability can approach intersubject variability.

CONCLUSIONS

This study demonstrates the potential of MASiVar to more globally investigate DWI variability across multiple levels and processing approaches simultaneously and suggests harmonization between scanners for multisite analyses should be considered before inference of group differences on subjects.

Baseline associations between biomarkers, cognitive function, and self-regulation indices in the Cognitive and Self-regulatory Mechanisms of Obesity Study

OBJECTIVE

Understanding how biological, cognitive, and self-regulatory factors are related to obesity, and weight regulation is clearly needed to optimize obesity prevention and treatment. The objective of this investigation was to understand how baseline biological, cognitive, and self-regulatory factors are related to adiposity at the initiation of a behavioral weight loss intervention among treatment-seeking adults with overweight/obesity.

METHODS

Participants (N = 107) in the Cognitive and Self-regulatory Mechanisms of Obesity Study (Identifier-NCT02786238) completed a baseline assessment with anthropometric, cardiometabolic, inflammatory, cognitive function, and self-regulation measures as part of a larger on-going trial. Data were analyzed with linear regression.

RESULTS

At baseline, body mass index, body fat percentage, and waist circumference (WC) were positively associated with fasting insulin and insulin resistance. Higher WC was related to higher fasting glucose and hemoglobin A1c (HbA1c). Higher glucose and insulin resistance levels were related to lower list sorting working memory. Higher glucose and HbA1c levels were negatively associated with reading scores. Cognitive function and self-regulation indices were unrelated.

CONCLUSIONS

In adults with overweight/obesity entering a weight loss treatment study: (1) elevated WC and associated glycemic impairment were negatively associated with cognition, (2) poorer executive function and reading abilities were associated with poorer glycemic control, and (3) objectively measured cognitive functions were unrelated to self-reported/behavioral measures of self-regulation. Such findings increase understanding of the relationships between adiposity, biomarkers, cognition, and self-regulation at treatment initiation and may ultimately inform barriers to successful obesity treatment response.

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy

BACKGROUND

Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT.

METHODS

To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc.

RESULTS

Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT.

LIMITATIONS

Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change.

CONCLUSION

Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.

Targeting the microbiome-gut-brain axis for improving cognition in schizophrenia and major mood disorders: A narrative review

Cognitive impairment has been consistently found to be a core feature of serious mental illnesses such as schizophrenia and major mood disorders (major depression and bipolar disorder). In recent years, a great effort has been made in elucidating the biological causes of cognitive deficits and the search for new biomarkers of cognition. Microbiome and gut-brain axis (MGB) hormones have been postulated to be potential biomarkers of cognition in serious mental illnesses. The main aim of this review was to synthesize current evidence on the association of microbiome and gut-brain hormones on cognitive processes in schizophrenia and major mood disorders and the association of MGB hormones with stress and the immune system. Our review underscores the role of the MGB axis on cognitive aspects of serious mental illnesses with the potential use of agents targeting the gut microbiota as cognitive enhancers. However, the current evidence for clinical trials focused on the MGB axis as cognitive enhancers in these clinical populations is scarce. Future clinical trials using probiotics, prebiotics, antibiotics, or faecal microbiota transplantation need to consider potential mechanistic pathways such as the HPA axis, the immune system, or gut-brain axis hormones involved in appetite control and energy homeostasis.

Cognitive impairment among patients with diabetes in Saudi Arabia: a cross-sectional study

Background

The incidence of cognitive impairment (CI) is higher in patients with diabetes mellitus (DM). The association between DM and CI and the risk factors for CI need to be addressed to estimate the prevalence of cognitive impairment in patients with DM and to identify the potential risk factors. The study is a cross-sectional study using a convenient sample of 269 subjects. Sociodemographic diabetes-related variables including biochemical markers were collected. CI and diabetes-related distress (DRD) were assessed using the Arabic version of Montreal Cognitive Assessment scale (MoCA) and the Diabetes Distress Screening Scale respectively.

Results

Overall, 80.3% had cognitive impairment while 33.8% had severe impairment. Older age, female gender, low level of education, and low income were associated with CI; duration of diabetes and DRD were associated with CI while ophthalmic complications were associated with severe CI. Duration of diabetes was inversely associated with CI. Level of HbA1c was significantly higher in patients with severe CI, and the probability of CI increased as the level of HbA1c increased. Low level of education was associated with severe CI, and CI was two times more likely among patients with DRD.

Conclusion

CI was higher than worldwide figures. Elderly females with low educational level, long duration of DM, and low socioeconomic status are at more risk. The probability of severe CI increased with increased level of HbA1c. Screening for CI in patients with diabetes along with intervention programs while considering the DRD and the level of HbA1c is crucial.

Associations Between Physical Fitness and Brain Structure in Young Adulthood

A comprehensive analysis of associations between physical fitness and brain structure in young adulthood is lacking, and further, it is unclear the degree to which associations between physical fitness and brain health can be attributed to a common genetic pathway or to environmental factors that jointly influences physical fitness and brain health. This study examined genotype-confirmed monozygotic and dizygotic twins, along with non-twin full-siblings to estimate the contribution of genetic and environmental factors to variation within, and covariation between, physical fitness and brain structure. Participants were 1,065 young adults between the ages of 22 and 36 from open-access Young Adult Human Connectome Project (YA-HCP). Physical fitness was assessed by submaximal endurance (2-min walk test), grip strength, and body mass index. Brain structure was assessed using magnetic resonance imaging on a Siemens 3T customized 'Connectome Skyra' at Washington University in St. Louis, using a 32-channel Siemens head coil. Acquired T1-weighted images provided measures of cortical surface area and thickness, and subcortical volume following processing by the YA-HCP structural FreeSurfer pipeline. Diffusion weighted imaging was acquired to assess white matter tract integrity, as measured by fractional anisotropy, following processing by the YA-HCP diffusion pipeline and tensor fit. Following correction for multiple testing, body mass index was negatively associated with fractional anisotropy in various white matter regions of interest (all | z| statistics > 3.9) and positively associated with cortical thickness within the right superior parietal lobe (z statistic = 4.6). Performance-based measures of fitness (i.e., endurance and grip strength) were not associated with any structural neuroimaging markers. Behavioral genetic analysis suggested that heritability of white matter integrity varied by region, but consistently explained >50% of the phenotypic variation. Heritability of right superior parietal thickness was large (∼75% variation). Heritability of body mass index was also fairly large (∼60% variation). Generally, 1 2 to 2 3 of the correlation between brain structure and body mass index could be attributed to heritability effects. Overall, this study suggests that greater body mass index is associated with lower white matter integrity, which may be due to common genetic effects that impact body composition and white matter integrity.

The impact of chronic stress on energy metabolism

The brain is exceptionally demanding in terms of energy metabolism. Approximately 20% of the calories consumed are devoted to our cerebral faculties, with the lion's share provided in the form of glucose. The brain's stringent energy dependency requires a high degree of harmonization between the elements responsible for supplying- and metabolizing energetic substrates. However, chronic stress may jeopardize this homeostatic energy balance by disruption of critical metabolic processes. In agreement, stress-related mental disorders have been linked with perturbations in energy metabolism. Prominent stress-induced metabolic alterations include the actions of hormones, glucose uptake and mitochondrial adjustments. Importantly, fundamental stress-responsive metabolic adjustments in humans and animal models bear a striking resemblance. Here, an overview is provided of key findings, demonstrating the pervasive impact of chronic stress on energy metabolism. Furthermore, I argue that medications, aimed primarily at restoring metabolic homeostasis, may constitute a novel approach to treat mental disorders.

Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder

Major depressive disorder (MDD) is associated to affected brain wiring. Little is known whether these changes are stable over time and hence might represent a biological predisposition, or whether these are state markers of current disease severity and recovery after a depressive episode. Human white matter network ("connectome") analysis via network science is a suitable tool to investigate the association between affected brain connectivity and MDD. This study examines structural connectome topology in 464 MDD patients (mean age: 36.6 years) and 432 healthy controls (35.6 years). MDD patients were stratified categorially by current disease status (acute vs. partial remission vs. full remission) based on DSM-IV criteria. Current symptom severity was assessed continuously via the Hamilton Depression Rating Scale (HAMD). Connectome matrices were created via a combination of T1-weighted magnetic resonance imaging (MRI) and tractography methods based on diffusion-weighted imaging. Global tract-based metrics were not found to show significant differences between disease status groups, suggesting conserved global brain connectivity in MDD. In contrast, reduced global fractional anisotropy (FA) was observed specifically in acute depressed patients compared to fully remitted patients and healthy controls. Within the MDD patients, FA in a subnetwork including frontal, temporal, insular, and parietal nodes was negatively associated with HAMD, an effect remaining when correcting for lifetime disease severity. Therefore, our findings provide new evidence of MDD to be associated with structural, yet dynamic, state-dependent connectome alterations, which covary with current disease severity and remission status after a depressive episode.

Glycosylated hemoglobin level, race/ethnicity, and cognition in midlife and early old age

Empirical evidence linking racial/ethnic differences in glycosylated hemoglobin levels (HbA1c) to cognitive function in midlife and early old age is limited. We use biomarker data from the Health and Retirement Study (HRS, 2006-2014), on adults 50-64 years at baseline (57-73 years by 2014), and fit multinomial logistic regression models to assess the association between baseline HbA1c, cognitive function (using Langa-Weir classifications) and mortality across 8-years. Additionally, we test for modification effects by race/ethnicity. In age- and sex-adjusted models high HbA1c level was associated with lower baseline cognition and higher relative risk ratios (RRR; vs. normal cognition) for cognitive impairment no dementia (CIND; RRR= 2.3; 95%CI=[1.38;3.84]; p<0.01), and dementia (RRR= 4.00; 95%CI=[1.76;9.10]; p<0.01). Adjusting for sociodemographic, behavioral risk factors, and other health conditions explained the higher RRR for CIND and attenuated the RRR for dementia by approximately 30%. HbA1c levels were not linked to the slope of cognitive decline, and we found no evidence of modification effects for HbA1c by race/ethnicity. Targeting interventions for glycemic control in the critical midlife period can protect baseline cognition and buffer against downstream development of cognitive impairment. This can yield important public health benefits and reductions in burdens associated with cognitive impairment, particularly among race/ethnic minorities who are at higher risk for metabolic diseases.

Glycated Haemoglobin Is Associated With Poorer Cognitive Performance in Patients With Recent-Onset Psychosis

BACKGROUND

Glucose abnormalities and cognitive alterations are present before the onset of schizophrenia. We aimed to study whether glucose metabolism parameters are associated with cognitive functioning in recent-onset psychosis (ROP) patients while adjusting for hypothalamic-pituitary adrenal (HPA) axis measures.

METHODS

Sixty ROP outpatients and 50 healthy subjects (HS) were studied. Cognitive function was assessed with the MATRICS Consensus Cognitive Battery. Glycated haemoglobin (HbA1_c), glucose, insulin, and C-peptide levels were determined in plasma. The HOMA-insulin resistance index was calculated. Salivary samples were obtained at home on another day to assess the cortisol awakening response and cortisol levels during the day. Univariate analyses were conducted to explore the association between glucose metabolism parameters and cognitive tasks. For those parameters that were more clearly associated with the cognitive outcome, multiple linear regression analyses were conducted to adjust for covariates. Each cognitive task was considered the dependent variable. Covariates were age, sex, education level, diagnosis, antipsychotic and benzodiazepine treatment, body mass index (BMI), smoking, and HPA axis measures. Potential interactions between diagnosis and glucose parameters were tested.

RESULTS

There were no significant differences in HPA axis measures or glucose parameters, with the exception of C-peptide (that was higher in ROP patients), between groups. ROP patients had a lower performance than HS in all cognitive tasks (p < 0.01 for all tasks). Of all glucose metabolism parameters, HbA1c levels were more clearly associated with cognitive impairment in cognitive tasks dealing with executive functions and visual memory in both ROP patients and HS. Multivariate analyses found a significant negative association between HbA1c and cognitive functioning in five cognitive tasks dealing with executive functions, visual memory and attention/vigilance (a ROP diagnosis by HbA1_c negative interaction was found in this latter cognitive domain, suggesting that HBA1_c levels are associated with impaired attention only in ROP patients).

CONCLUSIONS

Our study found that HbA1_c was negatively associated with cognitive functioning in both ROP patients and HS in tasks dealing with executive functions and visual memory. In ROP patients, HbA1_c was also associated with impaired attention. These results were independent of BMI and measures of HPA axis activity.