Greater exposure to PM2.5 and PM10 was associated with lower corneal nerve measures: the Maastricht study - a cross-sectional study.

BACKGROUND: Epidemiological and toxicological studies indicate that increased exposure to air pollutants can lead to neurodegenerative diseases. To further confirm this relationship, we evaluated the association between exposure to ambient air pollutants and corneal nerve measures as a surrogate for neurodegeneration, using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from The Maastricht Study including N = 3635 participants (mean age 59.3 years, 51.6% were women, and 19.9% had type 2 diabetes) living in the Maastricht area. Using the Geoscience and hEalth Cohort COnsortium (GECCO) data we linked the yearly average exposure levels of ambient air pollutants at home address-level [particulate matter with diameters of ≤ 2.5 µm (PM2.5), and ≤ 10.0 µm (PM10), nitrogen dioxide (NO2), and elemental carbon (EC)]. We used linear regression analysis to study the associations between Z-score for ambient air pollutants concentrations (PM2.5, PM10, NO2, and EC) and Z-score for individual corneal nerve measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length, and fractal dimension). RESULTS: After adjustment for potential confounders (age, sex, level of education, glucose metabolism status, corneal confocal microscopy lag time, inclusion year of participants, smoking status, and alcohol consumption), higher Z-scores for PM2.5 and PM10 were associated with lower Z-scores for corneal nerve bifurcation density, nerve density, nerve length, and nerve fractal dimension [stß (95% CI): PM2.5 -0.10 (-0.14; -0.05), -0.04 (-0.09; 0.01), -0.11 (-0.16; -0.06), -0.20 (-0.24; -0.15); and PM10 -0.08 (-0.13; -0.03), -0.04 (-0.09; 0.01), -0.08 (-0.13; -0.04), -0.17 (-0.21; -0.12)], respectively. No associations were found between NO2 and EC and corneal nerve measures. CONCLUSIONS: Our population-based study demonstrated that exposure to higher levels of PM2.5 and PM10 are associated with higher levels of corneal neurodegeneration, estimated from lower corneal nerve measures. Our results suggest that air pollution may be a determinant for neurodegeneration assessed in the cornea and may impact the ocular surface health as well.

Brain structure and connectivity mediate the association between lifestyle and cognition: The Maastricht Study.

Life-course exposure to risk and protective factors impacts brain macro- and micro-structure, which in turn affects cognition. The concept of brain-age gap assesses brain health by comparing an individual's neuroimaging-based predicted age with their calendar age. A higher BAG implies accelerated brain ageing and is expected to be associated with worse cognition. In this study, we comprehensively modelled mutual associations between brain health and lifestyle factors, brain age and cognition in a large, middle-aged population. For this study, cognitive test scores, lifestyle and 3T MRI data for n = 4881 participants [mean age (± SD) = 59.2 (±8.6), 50.1% male] were available from The Maastricht Study, a population-based cohort study with extensive phenotyping. Whole-brain volumes (grey matter, cerebrospinal fluid and white matter hyperintensity), cerebral microbleeds and structural white matter connectivity were calculated. Lifestyle factors were combined into an adapted LIfestyle for BRAin health weighted sum score, with higher score indicating greater dementia risk. Cognition was calculated by averaging z-scores across three cognitive domains (memory, information processing speed and executive function and attention). Brain-age gap was calculated by comparing calendar age to predictions from a neuroimaging-based multivariable regression model. Paths between LIfestyle for BRAin health tertiles, brain-age gap and cognitive function were tested using linear regression and structural equation modelling, adjusting for sociodemographic and clinical confounders. The results show that cerebrospinal fluid, grey matter, white matter hyperintensity and cerebral microbleeds best predicted brain-age gap (R 2 = 0.455, root mean squared error = 6.44). In regression analysis, higher LIfestyle for BRAin health scores (greater dementia risk) were associated with higher brain-age gap (standardized regression coefficient ß = 0.126, P < 0.001) and worse cognition (ß = -0.046, P = 0.013), while higher brain-age gap was associated with worse cognition (ß=-0.163, P < 0.001). In mediation analysis, 24.7% of the total difference in cognition between the highest and lowest LIfestyle for BRAin health tertile was mediated by brain-age gap (ß indirect = -0.049, P < 0.001; ß total = -0.198, P < 0.001) and an additional 3.8% was mediated via connectivity (ß indirect = -0.006, P < 0.001; ß total = -0.150, P < 0.001). Findings suggest that associations between health- and lifestyle-based risk/protective factors (LIfestyle for BRAin health) and cognition can be partially explained by structural brain health markers (brain-age gap) and white matter connectivity markers. Lifestyle interventions targeted at high-risk individuals in mid-to-late life may be effective in promoting and preserving cognitive function in the general public.

Retinal microvascular function and incidence and trajectories of clinically relevant depressive symptoms: the Maastricht Study.

BACKGROUND: Cerebral microvascular dysfunction may contribute to depression via disruption of brain structures involved in mood regulation, but evidence is limited. We investigated the association of retinal microvascular function, a proxy for microvascular function in the brain, with incidence and trajectories of clinically relevant depressive symptoms. METHODS: Longitudinal data are from The Maastricht Study of 5952 participants (59.9 ± 8.5 years/49.7% women) without clinically relevant depressive symptoms at baseline (2010-2017). Central retinal arteriolar equivalent and central retinal venular equivalent (CRAE and CRVE) and a composite score of flicker light-induced retinal arteriolar and venular dilation were assessed at baseline. We assessed incidence and trajectories of clinically relevant depressive symptoms (9-item Patient Health Questionnaire score ⩾10). Trajectories included continuously low prevalence (low, n = 5225 [87.8%]); early increasing, then chronic high prevalence (early-chronic, n = 157 [2.6%]); low, then increasing prevalence (late-increasing, n = 247 [4.2%]); and remitting prevalence (remitting, n = 323 [5.4%]). RESULTS: After a median follow-up of 7.0 years (range 1.0-11.0), 806 (13.5%) individuals had incident clinically relevant depressive symptoms. After full adjustment, a larger CRAE and CRVE were each associated with a lower risk of clinically relevant depressive symptoms (hazard ratios [HRs] per standard deviation [s.d.]: 0.89 [95% confidence interval (CI) 0.83-0.96] and 0.93 [0.86-0.99], respectively), while a lower flicker light-induced retinal dilation was associated with a higher risk of clinically relevant depressive symptoms (HR per s.d.: 1.10 [1.01-1.20]). Compared to the low trajectory, a larger CRAE was associated with lower odds of belonging to the early-chronic trajectory (OR: 0.83 [0.69-0.99]) and a lower flicker light-induced retinal dilation was associated with higher odds of belonging to the remitting trajectory (OR: 1.23 [1.07-1.43]). CONCLUSIONS: These findings support the hypothesis that cerebral microvascular dysfunction contributes to the development of depressive symptoms.

Microvascular Dysfunction and Whole-Brain White Matter Connectivity: The Maastricht Study.

BACKGROUND: Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. METHODS AND RESULTS: Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (ß per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. CONCLUSIONS: These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Disease severity-based subgrouping of type 2 diabetes does not parallel differences in quality of life: the Maastricht Study.

AIMS/HYPOTHESIS: Type 2 diabetes is a highly heterogeneous disease for which new subgroups ('clusters') have been proposed based on disease severity: moderate age-related diabetes (MARD), moderate obesity-related diabetes (MOD), severe insulin-deficient diabetes (SIDD) and severe insulin-resistant diabetes (SIRD). It is unknown how disease severity is reflected in terms of quality of life in these clusters. Therefore, we aimed to investigate the cluster characteristics and cluster-wise evolution of quality of life in the previously defined clusters of type 2 diabetes. METHODS: We included individuals with type 2 diabetes from the Maastricht Study, who were allocated to clusters based on a nearest centroid approach. We used logistic regression to evaluate the cluster-wise association with diabetes-related complications. We plotted the evolution of HbA1c levels over time and used Kaplan-Meier curves and Cox regression to evaluate the cluster-wise time to reach adequate glycaemic control. Quality of life based on the Short Form 36 (SF-36) was also plotted over time and adjusted for age and sex using generalised estimating equations. The follow-up time was 7 years. Analyses were performed separately for people with newly diagnosed and already diagnosed type 2 diabetes. RESULTS: We included 127 newly diagnosed and 585 already diagnosed individuals. Already diagnosed people in the SIDD cluster were less likely to reach glycaemic control than people in the other clusters, with an HR compared with MARD of 0.31 (95% CI 0.22, 0.43). There were few differences in the mental component score of the SF-36 in both newly and already diagnosed individuals. In both groups, the MARD cluster had a higher physical component score of the SF-36 than the other clusters, and the MOD cluster scored similarly to the SIDD and SIRD clusters. CONCLUSIONS/INTERPRETATION: Disease severity suggested by the clusters of type 2 diabetes is not entirely reflected in quality of life. In particular, the MOD cluster does not appear to be moderate in terms of quality of life. Use of the suggested cluster names in practice should be carefully considered, as the non-neutral nomenclature may affect disease perception in individuals with type 2 diabetes and their healthcare providers.

Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study.

INTRODUCTION: The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS: We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS: After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION: The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.

Traditional lifestyle factors partly mediate the association of socioeconomic position with intrahepatic lipid content: The Maastricht study.

Background & Aims: Recent studies have unveiled an association between socioeconomic position (SEP) and intrahepatic lipid (IHL) content. The aim of this study was to examine to what extent traditional lifestyle factors mediate the relationship between SEP and IHL content, independent of aetiology, and non-alcoholic fatty liver disease (NAFLD). Methods: We used cross-sectional data derived from The Maastricht Study (N = 4,001; mean age: 60 years, 49% women, 32% low education level, 21% diabetes, 21% NAFLD). Education, income, and occupation were used as indicators of SEP. Physical activity (accelerometer), intake of total energy, alcohol, saturated fat, protein, vitamin E, dietary fibre, and fructose from sugar-sweetened beverages (SSBs) and fruit juice (food frequency questionnaires) were potential mediators. IHL content was quantified by magnetic resonance imaging. Age, sex, and type 2 diabetes were covariates. Multiple parallel mediation analyses (bootstraps = 10,000) were performed. Results: Individuals with a low education level had a 1.056-fold higher IHL content (95% CI: 1.03-1.08) and a 44% greater NAFLD risk (OR:1.44; 95% CI:1.18-1.77) compared with those with higher education levels. Approximately 8.9% of educational disparity in risk of IHL content was attributable to moderate-to-vigorous physical activity; 6.3% to fructose intake from SSBs; 5.5% to dietary fibre; and -23% to alcohol. Approximately 8.7% of educational disparity in risk of NAFLD was attributable to moderate-to-vigorous physical activity; and 7.7% to fructose intake from SSBs. However, the indirect effect of these mediators was small (0.998 for IHL content and 1.045 for NAFLD) in comparison to the total effect. Similar results were found when income and occupation were used as SEP indicators. Conclusions: Societal measures may alleviate the burden of NAFLD and further studies that identify mediators other than traditional lifestyle factors are warranted to define the relationship underlying SEP and IHL content. Impact and implications: Individuals with a low or medium level of education, income, or occupational status had more fat accumulation in their livers than individuals with a higher education, income, or occupational status. This difference may be attributed to the influence of unhealthy lifestyle factors, such as reduced physical activity and a higher intake of sugar-sweetened beverages among individuals with lower socioeconomic position. Nevertheless, other yet unknown factors may also play a role.

Both short and long sleep durations are associated with type 2 diabetes, independent from traditional lifestyle risk factors-The Maastricht Study.

OBJECTIVES: This study examined the cross-sectional association between sleep duration, prediabetes, and type 2 diabetes, and its independence from the traditional lifestyle risk factors diet, physical activity, smoking behavior, and alcohol consumption. METHODS: Cross-sectional data from 5561 people aged 40-75 years recruited into The Maastricht Study between 2010 and 2018 were used (1:1 female:male and mean age: 60.1 years [standard deviation: 8.6]). Sleep duration was operationalized as in-bed time, algorithmically derived from activPAL3 accelerometer data (median 7 nights, IQR 1). Glucose metabolism status was determined with an oral glucose tolerance test. Multinomial logistic regression was used to assess the association of sleep duration as restricted cubic spline with prediabetes and type 2 diabetes. We adjusted for sex, age, educational level, the use of sleep medication or antidepressants, and the following lifestyle risk factors: diet quality, physical activity, smoking behavior, and alcohol consumption. RESULTS: A U-shaped association between sleep duration and type 2 diabetes was found. Compared to those with a sleep duration of 8 hours, participants with a sleep duration of 5 and 12 hours had higher odds of type 2 diabetes (OR: 2.9 [95% CI 1.9 to 4.4] and OR 3.2 [2.0 to 5.2], respectively). This association remained after further adjustment for the lifestyle risk factors (OR: 2.6 [1.7 to 4.1] and OR 1.8 [1.1 to 3.1]). No such association was observed between sleep duration and prediabetes. CONCLUSIONS: Both short and long sleep durations are associated positively and independently of lifestyle and cardiovascular risk factors with type 2 diabetes, but not with prediabetes.

(Pre)diabetes and a higher level of glycaemic measures are continuously associated with corneal neurodegeneration assessed by corneal confocal microscopy: the Maastricht Study.

AIMS/HYPOTHESIS: To assess the associations between glucose metabolism status and a range of continuous measures of glycaemia with corneal nerve fibre measures, as assessed using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from the Maastricht Study of N=3471 participants (mean age 59.4 years, 48.4% men, 14.7% with prediabetes, 21.0% with type 2 diabetes) to study the associations, after adjustment for demographic, cardiovascular risk and lifestyle factors, between glucose metabolism status (prediabetes and type 2 diabetes vs normal glucose metabolism) plus measures of glycaemia (fasting plasma glucose, 2 h post-load glucose, HbA1c, skin autofluorescence [SAF] and duration of diabetes) and composite Z-scores of corneal nerve fibre measures or individual corneal nerve fibre measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length and fractal dimension). We used linear regression analysis, and, for glucose metabolism status, performed a linear trend analysis. RESULTS: After full adjustment, a more adverse glucose metabolism status was associated with a lower composite Z-score for corneal nerve fibre measures (ß coefficients [95% CI], prediabetes vs normal glucose metabolism -0.08 [-0.17, 0.03], type 2 diabetes vs normal glucose metabolism -0.14 [-0.25, -0.04]; linear trend analysis showed a p value of 0.001), and higher levels of measures of glycaemia (fasting plasma glucose, 2 h post-load glucose, HbA1c, SAF and duration of diabetes) were all significantly associated with a lower composite Z-score for corneal nerve fibre measures (per SD: -0.09 [-0.13, -0.05], -0.07 [-0.11, -0.03], -0.08 [-0.11, -0.04], -0.05 [-0.08, -0.01], -0.09 [-0.17, -0.001], respectively). In general, directionally similar associations were observed for individual corneal nerve fibre measures. CONCLUSIONS/INTERPRETATION: To our knowledge, this is the first population-based study to show that a more adverse glucose metabolism status and higher levels of glycaemic measures were all linearly associated with corneal neurodegeneration after adjustment for an extensive set of potential confounders. Our results indicate that glycaemia-associated corneal neurodegeneration is a continuous process that starts before the onset of type 2 diabetes. Further research is needed to investigate whether early reduction of hyperglycaemia can prevent corneal neurodegeneration.

Symptoms and quality of life before, during, and after a SARS-CoV-2 PCR positive or negative test: data from Lifelines.

This study evaluates to what extent symptoms are present before, during, and after a positive SARS-CoV-2 polymerase chain reaction (PCR) test, and to evaluate how the symptom burden and quality of Life (QoL) compares to those with a negative PCR test. Participants from the Dutch Lifelines COVID-19 Cohort Study filled-out as of March 2020 weekly, later bi-weekly and monthly, questions about demographics, COVID-19 diagnosis and severity, QoL, and symptoms. The study population included those with one positive or negative PCR test who filled out two questionnaires before and after the test, resulting in 996 SARS-CoV-2 PCR positive and 3978 negative participants. Nearly all symptoms were more often reported after a positive test versus the period before the test (p < 0.05), except fever. A higher symptom prevalence after versus before a test was also found for nearly all symptoms in negatives (p < 0.05). Before the test, symptoms were already partly present and reporting of nearly all symptoms before did not differ between positives and negatives (p > 0.05). QoL decreased around the test for positives and negatives, with a larger deterioration for positives. Not all symptoms after a positive SARS-CoV-2 PCR test might be attributable to the infection and symptoms were also common in negatives.

The association between the food environment and adherence to healthy diet quality: the Maastricht Study.

OBJECTIVE: The purpose of this study is to determine if healthier neighbourhood food environments are associated with healthier diet quality. DESIGN: This was a cross-sectional study using linear regression models to analyse data from the Maastricht Study. Diet quality was assessed using data collected with a FFQ to calculate the Dutch Healthy Diet (DHD). A buffer zone encompassing a 1000 m radius was created around each participant home address. The Food Environment Healthiness Index (FEHI) was calculated using a Kernel density analysis within the buffers of available food outlets. The association between the FEHI and the DHD score was analysed and adjusted for socio-economic variables. SETTING: The region of Maastricht including the surrounding food retailers in the Netherlands. PARTICIPANTS: 7367 subjects aged 40-75 years in the south of the Netherlands. RESULTS: No relationship was identified between either the FEHI (B = 0·62; 95 % CI = -2·54, 3·78) or individual food outlets, such as fast food (B = -0·07; 95 % CI = -0·20, 0·07) and diet quality. Similar null findings using the FEHI were identified at the 500 m (B = 0·95; 95 % CI = -0·85, 2·75) and 1500 m (B = 1·57; 95 % CI = -3·30, 6·44) buffer. There was also no association between the food environment and individual items of the DHD including fruits, vegetables and sugar-sweetened beverages. CONCLUSION: The food environment in the Maastricht area appeared marginally unhealthy, but the differences in the food environment were not related to the quality of food that participants reported as intake.

Retinal Functional and Structural Neural Indices: Potential Biomarkers for the Monitoring of Cerebral Neurodegeneration: The Maastricht Study.

BACKGROUND: If retinal indices of neurodegeneration are to be biomarkers for the monitoring of cerebral neurodegeneration, it is important to establish whether potentially modifiable risk factors for dementia are associated with retinal neurodegenerative changes. OBJECTIVE: To study associations of dementia risk factors with retinal sensitivity, an index of retinal neural function, and retinal nerve fiber layer (RNFL) thickness, an index of retinal neural structure. METHODS: We used cross-sectional data from The Maastricht Study (up to 5,666 participants, 50.5% men, mean age 59.7), and investigated associations with regression analyses (adjusted for potential confounders). RESULTS: Most risk factors under study (i.e., hyperglycemia, unhealthy diet, lower cardiorespiratory fitness, smoking, alcohol consumption, and hypertension) were significantly associated with lower retinal sensitivity and lower RNFL thickness. CONCLUSION: Findings of this population-based study support the concept that retinal neural indices may be biomarkers for the monitoring of therapeutic strategies that aim to prevent early-stage cerebral neurodegeneration and, ultimately, dementia.

Lower heart rate variability, an index of worse autonomic function, is associated with worse beta cell response to a glycemic load in vivo-The Maastricht Study.

OBJECTIVE: We investigated, using population-based data, whether worse autonomic function, estimated from lower 24-hour heart rate variability (HRV), was associated with beta cell function, assessed from beta cell response during an oral glucose tolerance test (OGTT). RESEARCH DESIGN AND METHODS: We used cross-sectional data from The Maastricht Study, a population-based cohort study (N = 2,007; age, mean ± SD:60 ± 8 years; 52% men; and 24% with type 2 diabetes). We used linear regression analyses with adjustment for potential confounders (demographic, cardiovascular, and lifestyle factors) to study the associations of time- and frequency-domain HRV (composite scores) with overall beta cell response (estimated from a composite score calculated from: C-peptidogenic index, overall insulin secretion, beta cell glucose sensitivity, beta cell potentiation factor, and beta cell rate sensitivity). In addition, we tested for interaction by sex and glucose metabolism status. RESULTS: After full adjustment, lower time- and frequency-domain HRV was significantly associated with lower overall beta cell response composite score (standardized beta, -0.055 [-0.098; -0.011] and - 0.051 [-0.095; -0.007], respectively). These associations were not modified by sex and there was no consistent pattern of interaction by glucose metabolism status. CONCLUSION: The present etiological study found that worse autonomic function, estimated from lower HRV, was associated with worse beta cell function, estimated from a composite score in a population-based sample which covered the entire spectrum of glucose metabolism. Hence, autonomic dysfunction may contribute to beta cell dysfunction and, ultimately, to the alteration of glucose metabolism status from normal glucose metabolism to prediabetes and type 2 diabetes.

Sex comparisons in the association of prediabetes and type 2 diabetes with cognitive function, depression, and quality of life: The Maastricht study.

AIMS: There are sex differences in the excess risk of diabetes-associated cardiovascular disease. However, it is not clear whether these sex differences exist with regard to other complications like mental health aspects. Therefore, we investigated sex differences in the association of prediabetes and type 2 diabetes (T2D) with cognitive function, depression, and quality of life (QoL). MATERIALS AND METHODS: In a population-based cross-sectional cohort study (n = 7639; age 40-75 years, 50% women, 25% T2D), we estimated sex-specific associations, and differences therein, of prediabetes and T2D (reference: normal glucose metabolism) with measures of cognitive function, depression, and physical and mental QoL. Sex differences were analysed using multiple regression models with interaction terms. RESULTS: In general, T2D, but not prediabetes, was associated with higher odds of cognitive impairment, major depressive disorder, and poorer QoL. The odds ratio (OR) of cognitive impairment associated with T2D was 1.29 (95% CI: 0.96-1.72) for women and 1.39 (1.10-1.75) for men. The OR of major depressive disorder associated with T2D was 1.19 (0.69-2.04) for women and 1.68 (1.02-2.75) for men. The mean difference of the physical QoL score (ranging from 0 to 100, with 100 indicating the best possible QoL) associated with T2D was -2.09 (-2.92 to -1.25) for women and -1.81 (-2.48 to -1.13) for men. The mean difference of the mental QoL score associated with T2D was -0.90 (-1.79 to -0.02) for women and -0.52 (-1.23 to 0.20) for men. There was no clear pattern of sex differences in the associations of either prediabetes or T2D with measures of cognitive function, depression, or QoL. CONCLUSIONS: In general, T2D was associated with worse cognitive function, depression, and poorer QoL. The strength of these associations was similar among women and men.

Circulating and adipose tissue immune cells in tissue-specific insulin resistance in humans with overweight and obesity.

OBJECTIVE: A proinflammatory adipose tissue (AT) microenvironment and systemic low-grade inflammation may differentially affect tissue-specific insulin sensitivity. This study investigated the relationships of abdominal subcutaneous AT (aSAT) and circulating immune cells, aSAT gene expression, and circulating inflammatory markers with liver and skeletal muscle insulin sensitivity in people with overweight and obesity. METHODS: Individuals with overweight and obesity from the PERSonalized Glucose Optimization Through Nutritional Intervention (PERSON) Study (n = 219) and the Maastricht Study (replication cohort; n = 1256) underwent a seven-point oral glucose tolerance test to assess liver and muscle insulin sensitivity, and circulating inflammatory markers were determined. In subgroups, flow cytometry was performed to identify circulating and aSAT immune cells, and aSAT gene expression was evaluated. RESULTS: The relative abundances of circulating T cells, nonclassical monocytes, and CD56dim CD16+ natural killer cells were inversely associated with liver, but not muscle, insulin sensitivity in the PERSON Study. The inverse association between circulating (classical) monocytes and liver insulin sensitivity was confirmed in the Maastricht Study. In aSAT, immune cell populations were not related to insulin sensitivity. Furthermore, aSAT gene expression of interleukin 6 and CD14 was positively associated with muscle, but not liver, insulin sensitivity. CONCLUSIONS: The present findings demonstrate that circulating immune cell populations and inflammatory gene expression in aSAT show distinct associations with liver and muscle insulin sensitivity.

Alcohol consumption and microvascular dysfunction: a J-shaped association: The Maastricht Study.

BACKGROUND: Microvascular dysfunction (MVD) is an important contributor to major clinical disease such as stroke, dementia, depression, retinopathy, and chronic kidney disease. Alcohol consumption may be a determinant of MVD. OBJECTIVE: Main objectives were (1) to study whether alcohol consumption was associated with MVD as assessed in the brain, retina, skin, kidney and in the blood; and (2) to investigate whether associations differed by history of cardiovascular disease or sex. DESIGN: We used cross-sectional data from The Maastricht Study (N = 3,120 participants, 50.9% men, mean age 60 years, and 27.5% with type 2 diabetes [the latter oversampled by design]). We used regression analyses to study the association between total alcohol (per unit and in the categories, i.e. none, light, moderate, high) and MVD, where all measures of MVD were combined into a total MVD composite score (expressed in SD). We adjusted all associations for potential confounders; and tested for interaction by sex, and history of cardiovascular disease. Additionally we tested for interaction with glucose metabolism status. RESULTS: The association between total alcohol consumption and MVD was non-linear, i.e. J-shaped. Moderate versus light total alcohol consumption was significantly associated with less MVD, after full adjustment (beta [95% confidence interval], -0.10 [-0.19; -0.01]). The shape of the curve differed with sex (Pinteraction = 0.03), history of cardiovascular disease (Pinteraction < 0.001), and glucose metabolism status (Pinteraction = 0.02). CONCLUSIONS: The present cross-sectional, population-based study found evidence that alcohol consumption may have an effect on MVD. Hence, although increasing alcohol consumption cannot be recommended as a policy, this study suggests that prevention of MVD may be possible through dietary interventions.

Sex differences in body composition in people with prediabetes and type 2 diabetes as compared with people with normal glucose metabolism: the Maastricht Study.

AIMS/HYPOTHESIS: Obesity is a major risk factor for type 2 diabetes. However, body composition differs between women and men. In this study we investigate the association between diabetes status and body composition and whether this association is moderated by sex. METHODS: In a population-based cohort study (n=7639; age 40-75 years, 50% women, 25% type 2 diabetes), we estimated the sex-specific associations, and differences therein, of prediabetes (i.e. impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes (reference: normal glucose metabolism [NGM]) with dual-energy x-ray absorptiometry (DEXA)- and MRI-derived measures of body composition and with hip circumference. Sex differences were analysed using adjusted regression models with interaction terms of sex-by-diabetes status. RESULTS: Compared with their NGM counterparts, both women and men with prediabetes and type 2 diabetes had more fat and lean mass and a greater hip circumference. The differences in subcutaneous adipose tissue, hip circumference and total and peripheral lean mass between type 2 diabetes and NGM were greater in women than men (women minus men [W-M] mean difference [95% CI]: 15.0 cm2 [1.5, 28.5], 3.2 cm [2.2, 4.1], 690 g [8, 1372] and 443 g [142, 744], respectively). The difference in visceral adipose tissue between type 2 diabetes and NGM was greater in men than women (W-M mean difference [95% CI]: -14.8 cm2 [-26.4, -3.1]). There was no sex difference in the percentage of liver fat between type 2 diabetes and NGM. The differences in measures of body composition between prediabetes and NGM were generally in the same direction, but were not significantly different between women and men. CONCLUSIONS/INTERPRETATION: This study indicates that there are sex differences in body composition associated with type 2 diabetes. The pathophysiological significance of these sex-associated differences requires further study.

Cognitive resilience depends on white matter connectivity: The Maastricht Study.

INTRODUCTION: Differences in brain network connectivity may reflect the capability of the neurological substrate to compensate for brain damage and preserve cognitive function (cognitive reserve). We examined the associations between white matter connectivity, brain damage markers, and cognition in a population sample of middle-aged individuals. METHODS: A total of 4759 participants from The Maastricht Study (mean age = 59.2, SD = 8.7, 50.2% male) underwent cognitive testing and diffusion magnetic resonance imaging (dMRI), from which brain volume, structural connectivity, and vascular damage were quantified. Multivariable linear regression was used to investigate whether connectivity modified the association between brain damage and cognition, adjusted for demographic and cardiometabolic risk factors. RESULTS: More atrophic and vascular brain damage was associated with worse cognition scores. Increasing connectivity moderated the negative association between damage and cognition (χ2 = 8.64, df = 3, p ≤ 0.001); individuals with high damage but strong connectivity showed normal cognition. DISCUSSION: Findings support the reserve hypothesis by showing that brain connectivity is associated with cognitive resilience.