Onset age of diabetes and incident dementia: A prospective cohort study

Development and validation of a convenient dementia risk prediction tool for diabetic population: A large and longitudinal machine learning cohort study

BACKGROUND

Diabetes mellitus has been shown to increase the risk of dementia, with diabetic patients demonstrating twice the dementia incidence rate of non-diabetic populations. We aimed to develop and validate a novel machine learning-based dementia risk prediction tool specifically tailored for diabetic population.

METHODS

Using a prospective from 42,881 diabetic individuals in the UK Biobank, a rigorous multi-stage selection framework was implemented to optimize feature-outcome associations from 190 variables, and 32 predictors were final retained. Subsequently, eight data analysis strategies were used to develop and validate the dementia risk prediction model. Model performance was assessed using area under the curve (AUC) metrics.

RESULTS

During a median follow-up of 9.60 years, 1337 incident dementia cases were identified among diabetic population. The Adaboost classifier demonstrated robust performance across different predictor sets: full model with 32 predictors versus streamlined simplified model with 13 predictors selected through forward feature subset selection algorithm (AUC: 0.805 ± 0.005 vs. 0.801 ± 0.005; p = 0.200) in model development employing an 8:2 data split (5-fold cross-validation for training). To facilitate community generalization and clinical applicability, the simplified model, named DRP-Diabetes, was deployed to a visual interactive web application for individualized dementia risk assessment.

LIMITATIONS

Some variables were based on self-reported.

CONCLUSIONS

A convenient and reliable dementia risk prediction tool was developed and validated for diabetic population, which could help individuals identify their potential risk profile and provide guidance on precise and timely actions to promote dementia delay or prevention.

Longitudinal trends in dementia prevalence among individuals with type 2 diabetes in Taiwan (2009-2022)

OBJECTIVE

This study examined the population-based epidemiological prevalence of early- and late-onset dementia in individuals with type 2 diabetes mellitus (T2DM) compared with the general population in Taiwan from 2009 to 2022.

METHODS

A 14-year nationwide population-based epidemiology study from 2009 to 2022 in Taiwan using the Taiwan National Health Insurance Research Database was conducted to examine the crude and age-standardized dementia prevalence in individuals aged <65 and ≥65. Multivariable logistic regression was used to assess factors associated with dementia prevalence in the T2DM population.

RESULTS

Among individuals aged ≥65 with T2DM, age-standardized dementia prevalence increased from 5.83 per 100 in 2009 to 7.11 per 100 in 2022, while the crude prevalence ratio compared to the general population ranged from 1.19 to 1.08. In the 40-64 age group, standardized dementia prevalence ranged from 0.58 to 0.43 per 100, with crude ratios ranging from 1.76 to 1.41. Our study found a higher risk of dementia prevalence among individuals aged 65 years and older, particularly among those with T2DM. Although the overall prevalence of dementia in the 40-64 age group was lower compared to older adults, individuals in this younger group with T2DM exhibited a significantly higher risk of developing dementia. Given these findings, public policy should prioritize early preventive strategies for individuals with T2DM to monitor and mitigate dementia progression in patients with T2DM.

Association between age at diabetes diagnosis and the development and progression of diabetic retinopathy

This study aimed to investigate the relationship between age at diabetes diagnosis (ADD) and the development and progression of diabetic retinopathy (DR). This study combined analysis of the National Health and Nutrition Examination Survey (NHANES) data with Mendelian randomization (MR). We employed regression models, propensity score matching, generalized additive model smoothing splines (GAM), random forest algorithms, and other analytical techniques. Cross-sectional analysis of NHANES data (n = 877) showed that the DR group had a significantly younger ADD compared to the DR-free group (P < 0.001). Regression analysis revealed a significant inverse association between ADD and DR prevalence (OR = 0.96, P < 0.001). MR analysis further supported this inverse relationship (OR = 0.42, P = 0.003). Two non-linear analytical approaches identified peak DR occurrence probability at ages 24.45 (GAM) and 24.2 (Shapley additive explanations dependence plots). Additionally, younger ADD was associated with increased DR severity across all categories (P < 0.05). In conclusion, older ADD was associated with a protective effect against the development and progression of DR, as supported by both analysis of NHANES data and MR. These findings underscore the importance of increased vigilance and more frequent screening for DR in patients diagnosed with diabetes at a young age.

Association of cardiovascular-kidney-metabolic health and apolipoprotein E4 genotype with risk of dementia and mortality

BackgroundPoor cardiovascular-kidney-metabolic (CKM) health is becoming prevalent; however, sparse data exist regarding the association of CKM health with incident dementia and all-cause mortality.ObjectiveThis study aimed to examine whether poor CKM health is associated with a higher risk of dementia and all-cause mortality, regardless of APOE4 carrier status.MethodsIn this prospective cohort study, 352,364 participants from the UK Biobank were included. CKM syndrome was identified as a medical condition with the presence of metabolic risk factors, cardiovascular disease, and chronic kidney disease, and was classified into five stages (stage 0 to 4). Cox proportional hazards models were applied to explore the association of CKM health with incident dementia and all-cause mortality.ResultsParticipants in stage 2-3 and stage 4 had 1.12-fold (95% CI: 1.02-1.23, p = 0.023) and 2.18-fold (95% CI: 1.96-2.43, p < 0.001) increased risk of incident all-cause dementia compared with those in stage 0. Similarly, participants in stage 4 also had an increased risk of Alzheimer's disease (HR = 1.51, 95% CI: 1.28-1.78, p < 0.001) and vascular dementia (HR = 4.62, 95% CI: 3.54-6.03, p < 0.001). Participants in later stages were at higher risk of all-cause mortality. We found an interaction between CKM health and APOE4 carrier status (p for interaction <0.001), and the relationship between CKM health and dementia was more pronounced in non-APOE4 carriers. Moreover, there were significant additive interactions between APOE4 carrier status and CKM health on the risk of dementia.ConclusionsPoor CKM health is independently associated with an increased risk of dementia, regardless of APOE4 carrier status, and all-cause mortality. These findings imply that promoting CKM health may help to reduce the risk of subsequent dementia and mortality.

Exploring Care Challenges and Needs of People With Diabetes Comorbid Cognitive Impairment From the Triangular Perspectives

The study explored the challenges and needs in diabetes care for people with diabetes and comorbid cognitive impairment from the triangular perspectives of diabetes educators, patients, and family caregivers. The study employed a phenomenological research design with qualitative data collection, involving semi-structured interviews with 8 diabetes educators, 7 patients, and 6 caregivers. The data were gathered from a health education center in a hospital in Taiwan. Thematic analysis was utilized to analyze the qualitative data. Three categories with eight themes emerged. Challenges included "care challenges in compliance", "limited family involvement", and "caregiver distress". Needs were identified as "training for educators on cognitive impairments", "caregiver education", and "standard care procedures". Clinical realities showed "inconsistent awareness" and "lack of consensus on resource referrals among professionals". Diabetes care for people with cognitive impairment faces challenges including poor compliance and limited family cooperation, requiring better comorbidity training for educators and caregivers, and standardized care procedures for healthcare professionals. Findings can guide future training programs and serve as a resource for caregivers.

Associations of age at diagnosis of breast cancer with incident myocardial infarction and heart failure: A prospective cohort study

Background

The associations of age at diagnosis of breast cancer with incident myocardial infarction (MI) and heart failure (HF) remain unexamined. Addressing this problem could promote understanding of the cardiovascular impact of breast cancer.

Methods

Data were obtained from the UK Biobank. Information on the diagnosis of breast cancer, MI, and HF was collected at baseline and follow-ups (median = 12.8 years). The propensity score matching method and Cox proportional hazards models were employed.

Results

A total of 251,277 female participants (mean age: 56.8 ± 8.0 years), of whom 16,241 had breast cancer, were included. Among breast cancer participants, younger age at diagnosis (per 10-year decrease) was significantly associated with elevated risks of MI (hazard ratio [HR] = 1.36, 95% confidence interval [CI] 1.19-1.56, p<0.001) and HF (HR = 1.31, 95% CI 1.18-1.46, p<0.001). After propensity score matching, breast cancer patients with younger diagnosis age had significantly higher risks of MI and HF than controls without breast cancer.

Conclusions

Younger age at diagnosis of breast cancer was associated with higher risks of incident MI and HF, underscoring the necessity to pay additional attention to the cardiovascular health of breast cancer patients diagnosed at younger age to conduct timely interventions to attenuate the subsequent risks of incident cardiovascular diseases.

Funding

This study was supported by grants from the National Natural Science Foundation of China (82373665 and 81974490), the Nonprofit Central Research Institute Fund of Chinese Academy of Medical Sciences (2021-RC330-001), and the 2022 China Medical Board-open competition research grant (22-466).

Age of type 2 diabetes onset as a risk factor for dementia: A 13-year retrospective cohort study

AIMS

To examine whether age at type 2 diabetes onset is an independent predictor of dementia risk.

METHODS

Retrospective cohort drawn from healthcare administrative records of all inhabitants within Romagna's catchment area, Italy, with an estimated onset of type 2 diabetes in 2008-2017 and aged ≥ 55, with follow-up until 2020. Time to dementia or censoring was estimated with the Kaplan-Meier method, using diabetes onset as the time origin. Age groups were compared with the log-rank test. Multivariable competing-risks analysis was used to assess predictors of dementia.

RESULTS

In patients aged ≥ 75 years, dementia-free survival (DFS) declined to below 90 % within five years and linearly decreased to 68.8 % until the end of follow-up. In contrast, DFS for those aged 55-64 years showed a marginal decrease, reaching 97.4 % after 13 years. Competing-risks regression showed that individuals aged ≥ 75 and 65-74 had a significantly higher risk of dementia compared to those aged 55-64 years. Having more comorbidities at diabetes onset and initial treatment with ≥ 2 antidiabetics were clinical predictors.

CONCLUSIONS

Later age at onset of diabetes is strongly associated with dementia. A better understanding of the diabetes-dementia relationship is needed to inform strategies for promoting specific healthcare pathways.

Diabetes and vascular mild cognitive impairment among Chinese ≥50 years: A cross-sectional study with 2020 participants

BACKGROUND

With the decline of cognitive function in vascular cognitive impairment, the burden on the family and society will increase. Therefore, early identification of vascular mild cognitive impairment (VaMCI) is crucial. The focus of early identification of VaMCI is on the attention of risk factors. Therefore, this study aimed to investigate the relationship between diabetes and VaMCI among the Chinese, hoping to predict the risk of VaMCI by diabetes and to move the identification of vascular cognitive impairment forward.

METHODS

We collected data from seven clinical centers and nine communities in China. All participants were over 50 years of age and had cognitive complaints. We collected basic information of the participants, and cognitive function was professionally assessed by the Montreal Cognitive Assessment scale. Finally, logistic regression analysis was used to analyze the correlation between each factor and VaMCI.

RESULTS

A total of 2020 participants were included, including 1140 participants with VaMCI and 880 participants with normal cognition. In univariate logistic regression analysis, age, heavy smoking, and diabetes had a positive correlation with VaMCI. At the same time, being married, high education, and light smoking had a negative correlation with VaMCI. After correction, only diabetes (OR = 1.04, 95% CI: 1.01-1.09, p = 0.05) had a positive correlation with VaMCI, and high education (OR = 0.60, 95% CI:.45-.81, p = 0.001) had a negative correlation with VaMCI.

CONCLUSION

In our study, we found that diabetes had a positive correlation with VaMCI, and high education had a negative correlation with VaMCI. Therefore, early identification and timely intervention of diabetes may reduce the risk of VaMCI and achieve early prevention of VaMCI.

Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

[Cognition and depression in older people with diabetes]

Cognitive dysfunction, dementia and depression are typical comorbidities of diabetes and are more common in older people with diabetes than in the general population. Both comorbid diseases have a substantial impact on the therapy of diabetes and lead to a reduction of the functional level in everyday life, the quality of life and are associated with increased mortality. This article summarizes the most important results on the etiology of cognitive dysfunction and depression and their consequences for clinical practice.

Is it time to repurpose geroprotective diabetes medications for prevention of dementia?

See related Editorial by Tang et al. in this issue.