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.

Associations of an individual's need for cognition with structural brain damage and cognitive functioning/impairment: cross-sectional population-based study.

BACKGROUND: High cognitive activity possibly reduces the risk of cognitive decline and dementia. AIMS: To investigate associations between an individual's need to engage in cognitively stimulating activities (need for cognition, NFC) and structural brain damage and cognitive functioning in the Dutch general population with and without existing cognitive impairment. METHOD: Cross-sectional data were used from the population-based cohort of the Maastricht Study. NFC was measured using the Need For Cognition Scale. Cognitive functioning was tested in three domains: verbal memory, information processing speed, and executive functioning and attention. Values 1.5 s.d. below the mean were defined as cognitive impairment. Standardised volumes of white matter hyperintensities (WMH), cerebrospinal fluid (CSF) and presence of cerebral small vessel disease (CSVD) were derived from 3T magnetic resonance imaging. Multiple linear and binary logistic regression analyses were used adjusted for demographic, somatic and lifestyle factors. RESULTS: Participants (n = 4209; mean age 59.06 years, s.d. = 8.58; 50.1% women) with higher NFC scores had higher overall cognition scores (B = 0.21, 95% CI 0.17-0.26, P < 0.001) and lower odds for CSVD (OR = 0.74, 95% CI 0.60-0.91, P = 0.005) and cognitive impairment (OR = 0.60, 95% CI 0.48-0.76, P < 0.001) after adjustment for demographic, somatic and lifestyle factors. The association between NFC score and cognitive functioning was similar for individuals with and without prevalent cognitive impairment. We found no significant association between NFC and WMH or CSF volumes. CONCLUSIONS: A high need to engage in cognitively stimulating activities is associated with better cognitive functioning and less presence of CSVD and cognitive impairment. This suggests that, in middle-aged individuals, motivation to engage in cognitively stimulating activities may be an opportunity to improve brain health.

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.

Reference values for nerve conduction studies of the peroneal, tibial, and sural nerve derived from a large population-based cohort: Associations with demographic and anthropometric characteristics-The Maastricht study.

INTRODUCTION/AIMS: Nerve conduction studies (NCSs) are widely used to support the clinical diagnosis of neuromuscular disorders. The aims of this study were to obtain reference values for peroneal, tibial, and sural NCSs and to examine the associations with demographic and anthropometric factors. METHODS: In 5099 participants (aged 40-79 years) without type 2 diabetes of The Maastricht Study, NCSs of peroneal, tibial, and sural nerves were performed. Values for compound muscle action potential (CMAP) and sensory nerve action potential amplitude, nerve conduction velocity (NCV), and distal latency were acquired. The association of age, sex, body mass index (BMI), and height with NCS values was determined using uni- and multivariate linear regression analyses. RESULTS: Detailed reference values are reported per decade for men and women. Significantly lower NCVs and longer distal latencies were observed in all nerves in older and taller individuals as well as in men. In these groups, amplitudes of the tibial and sural nerves were significantly lower, whereas a lower peroneal nerve CMAP was only significantly associated with age. BMI showed a multidirectional association. After correction for anthropometric factors in the multivariate analysis, the association between sex and NCS values was less straightforward. DISCUSSION: These values from a population-based dataset could be used as a reference for generating normative values. Our findings show the association of NCS values with anthropometric factors. In clinical practice, these factors can be considered when interpreting NCS values.

Incretin-based therapy and the risk of diabetic foot ulcers and related events.

AIM: To investigate the effect of dipeptidyl peptidase-4 inhibitors (DPP4-Is) and glucagon-like peptide-1 receptor agonists (GLP1-RAs) on diabetic foot ulcer (DFU) and DFU-related outcomes (lower limb amputation [LLA], DFU-related hospitalization and mortality). METHODS: We performed a cohort study with data from the Clinical Practice Research Datalink Aurum database with linkage to hospital data. We included people with type 2 diabetes starting treatment with metformin. Then we propensity score matched new users of DPP4-Is and sulphonylureas (N = 98 770), and new users of GLP1-RAs and insulin (N = 25 422). Cox proportional hazards models estimated the hazard ratios (HRs) for the outcomes. RESULTS: We observed a lower risk of DFU with both DPP4-I use versus sulphonylurea use (HR 0.88, 95% confidence interval [CI]: 0.79-0.97) and GLP1-RA use versus insulin use (HR 0.44, 95% CI: 0.32-0.60) for short-term exposure (≤ 400 days) and HR 0.74 (95% CI: 0.60-0.92) for long-term exposure (>400 days). Furthermore, the risks of hospitalization and mortality were lower with both DPP4-I use and GLP1-RA use. The risk of LLA was lower with GLP1-RA use. The results remained consistent across several sensitivity analyses. CONCLUSIONS: Incretin-based therapy was associated with a lower risk of DFU and DFU-related outcomes. This suggests benefits for the use of this treatment in people at risk of DFU.

Socioeconomic inequalities in health-related functioning among people with type 2 Diabetes: longitudinal analyses in the Maastricht Study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a common chronic disease that disproportionally affects disadvantaged groups. People with a low socioeconomic position (SEP) have increased risk of T2DM and people with a low SEP and T2DM have higher HbA1c-levels compared to people with T2DM and high SEP. The aim of this study is to analyze longitudinal socioeconomic differences in health-related functioning in people with T2DM. METHODS: Longitudinal data from 1,537 participants of The Maastricht Study with T2DM were used (32.6% female, mean (SD) age 62.9 (7.7) years). SEP was determined by baseline measures of education, occupation and income. Health-related functioning (physical, mental and social) was measured with the Short-Form Health Survey and the Impact on Participation and Autonomy survey (all scored from 0 to 100). Associations of SEP and health-related functioning were studied annually over a 10-year period (median (IQR) 7.0 (5.0) years, baseline 2010-2018) using linear mixed methods adjusting for demographics, HbA1c-levels and lifestyle factors. RESULTS: Participants with a low SEP had significantly worse health-related functioning compared to those with a high SEP. For example, participants with low income had lower scores for physical (-4.49[CI -5.77;-3.21]), mental (-2.61[-3.78,-1.44]) and social functioning (-9.76[-12.30;-7.23]) compared to participants with high income on a scale from 0 to 100. In addition, participants with a low education significantly declined more over time in mental (score for interaction education with time - 0.23[-0.37;-0.09]) and social functioning (-0.44[-0.77;-0.11]) compared to participants with high education. Participants with low and intermediate incomes significantly declined more over time in physical functioning (-0.17 [-0.34, -0.01 and - 0.18 [-0.36, 0.00]) compared to participants with high income. CONCLUSIONS: Among people with T2DM, those with a lower SEP had worse health-related functioning in general than people with a higher SEP. Additionally, people with T2DM and low education developed poorer mental and social functioning over time compared to people with T2DM and high education. People with T2DM and low or intermediate income declined more in physical functioning over time than those with high incomes. In addition to HbA1c-levels and lifestyle patterns, more attention is needed for socioeconomic differences in health-related functioning for people living with T2DM.

Relationship between educational attainment and non-alcoholic fatty liver disease: A two-sample Mendelian randomization study.

BACKGROUND: Observational studies have identified an inverse association between education and non-alcoholic fatty liver disease (NAFLD). However, it is not possible to establish causality for this relationship. AIMS: To gain more insight into the causal nature of the relationship between education and NAFLD. METHODS: We performed two-sample Mendelian randomization (MR) analyses using summary-level, large-scale datasets to study the association of genetically predicted educational attainment (n = 1271 genetic instruments, obtained from 1,131,881 participants) with risk of NAFLD (i.e., liver fat [n = 32,858 participants] and electronic health record (EHR)-based NAFLD [n = 778,614 participants]). In sensitivity analyses, educational attainment was replaced by three education-related traits (i.e., genetically predicted cognition, math ability and highest math). RESULTS: Inverse-variance weighted method showed a statistically significant association between genetically predicted educational attainment and liver fat (beta: -0.251, 95%CI: -0.305; -0.198) and EHR-based NAFLD (OR: 0.609, 95%CI: 0.547; 0.677). MR-Egger regression did not show statistically significant intercepts. Similar findings were obtained when other MR tests were used or when educational attainment was replaced by education-related traits. CONCLUSIONS: This study suggests a causal, protective effect of higher education on NAFLD risk. Societal interventions targeted at people with low education are needed to alleviate the burden of NAFLD.

The associations of socioeconomic position with structural brain damage and connectivity and cognitive functioning: The Maastricht Study.

BACKGROUND: Socioeconomic inequalities in cognitive impairment may partly act through structural brain damage and reduced connectivity. This study investigated the extent to which the association of early-life socioeconomic position (SEP) with later-life cognitive functioning is mediated by later-life SEP, and whether the associations of SEP with later-life cognitive functioning can be explained by structural brain damage and connectivity. METHODS: We used cross-sectional data from the Dutch population-based Maastricht Study (n = 4,839; mean age 59.2 ± 8.7 years, 49.8% women). Early-life SEP was assessed by self-reported poverty during childhood and parental education. Later-life SEP included education, occupation, and current household income. Participants underwent cognitive testing and 3-T magnetic resonance imaging to measure volumes of white matter hyperintensities, grey matter, white matter, cerebrospinal fluid, and structural connectivity. Multiple linear regression analyses tested the associations between SEP, markers of structural brain damage and connectivity, and cognitive functioning. Mediation was tested using structural equation modeling. RESULTS: Although there were direct associations between both indicators of SEP and later-life cognitive functioning, a large part of the association between early-life SEP and later-life cognitive functioning was explained by later-life SEP (72.2%). The extent to which structural brain damage or connectivity acted as mediators between SEP and cognitive functioning was small (up to 5.9%). CONCLUSIONS: We observed substantial SEP differences in later-life cognitive functioning. Associations of structural brain damage and connectivity with cognitive functioning were relatively small, and only marginally explained the SEP gradients in cognitive functioning.

Hepatic glucokinase regulatory protein and carbohydrate response element binding protein attenuation reduce de novo lipogenesis but do not mitigate intrahepatic triglyceride accumulation in Aldob deficiency.

OBJECTIVE: Stable isotope studies have shown that hepatic de novo lipogenesis (DNL) plays an important role in the pathogenesis of intrahepatic lipid (IHL) deposition. Furthermore, previous research has demonstrated that fructose 1-phosphate (F1P) not only serves as a substrate for DNL, but also acts as a signalling metabolite that stimulates DNL from glucose. The aim of this study was to elucidate the mediators of F1P-stimulated DNL, with special focus on two key regulators of intrahepatic glucose metabolism, i.e., glucokinase regulatory protein (GKRP) and carbohydrate response element binding protein (ChREBP). METHODS: Aldolase B deficient mice (Aldob-/-), characterized by hepatocellular F1P accumulation, enhanced DNL, and hepatic steatosis, were either crossed with GKRP deficient mice (Gckr-/-) or treated with short hairpin RNAs directed against hepatic ChREBP. RESULTS: Aldob-/- mice showed higher rates of de novo palmitate synthesis from glucose when compared to wildtype mice (p < 0.001). Gckr knockout reduced de novo palmitate synthesis in Aldob-/- mice (p = 0.017), without affecting the hepatic mRNA expression of enzymes involved in DNL. In contrast, hepatic ChREBP knockdown normalized the hepatic mRNA expression levels of enzymes involved in DNL and reduced fractional DNL in Aldob-/- mice (p < 0.05). Of interest, despite downregulation of DNL in response to Gckr and ChREBP attenuation, no reduction in intrahepatic triglyceride levels was observed. CONCLUSIONS: Both GKRP and ChREBP mediate F1P-stimulated DNL in aldolase B deficient mice. Further studies are needed to unravel the role of GKRP and hepatic ChREBP in regulating IHL accumulation in aldolase B deficiency.

Effect of Magnetic Resonance Image Quality on Structural and Functional Brain Connectivity: The Maastricht Study.

In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas-template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R2 up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R2 up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to -59%), sex (up to -25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. This emphasizes the potential confounding effects of image quality in large population-based neuroimaging studies on brain connectivity and underscores the importance of accounting for it.

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.

Bone microarchitecture and strength assessed by HRpQCT in individuals with type 2 diabetes and prediabetes: the Maastricht study.

Type 2 diabetes (T2D) is a prevalent disease and has been associated with an increased fracture risk despite normal or even higher areal BMD. The aim of this study was to estimate the association between glucose metabolism status (GMS) and measurements of glycemic control with HRpQCT parameters of bone microarchitecture and strength. Participants of the Maastricht study who underwent an HRpQCT scan at the distal radius and tibia were included. GMS was determined by use of an oral glucose tolerance test and grouped into a normal glucose metabolism (NGM), prediabetes, or T2D. Linear regression models were used, stratified by sex with multiple adjustments. This study incorporated cross-sectional data from 1400 (796 [56.9%] NGM, 228 [16.3%] prediabetes, and 376 [26.9%] T2D) men and 1415 (1014 [71.7%] NGM, 211 [14.9%] prediabetes, and 190 [13.4%] T2D) women. The mean age was 59.8 ± 8.6 and 57.6 ± 9.0 yr for men and women, respectively. After adjustment, T2D was associated with a higher total BMD measured by HRpQCT and cortical thickness, and a smaller total and trabecular area in men and women compared with NGM. In women, T2D was additionally associated with a higher stiffness and failure load at the radius. Results were more pronounced at the distal radius than at the distal tibia. To conclude, these findings suggest that in this cohort of Maastricht study participants, total and trabecular bone area are smaller, but bone microarchitecture, density, and bone strength assessed by HRpQCT are not impaired in individuals with T2D.

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.

Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models.

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to €300,000. The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.