Risk Of Future Dementia Research Articles

Subjective cognitive complaints and future risk of dementia and cognitive impairment, which matters most

ABSTRACT Many older adults report subjective cognitive decline (SCD); however, the specific types of complaints most strongly associated with early disease detection remain unclear. This study examines which complaints from the Everyday Cognition Scales (ECog) are associated with progression from normal cognition to mild cognitive impairment (MCI)/dementia. 415 older adults were monitored annually for 5 years, on average. Cox proportional hazards models assessed associations between ECog complaints and progression to MCI/dementia. Follow-up models included depression as a covariate. Numerous Memory (5 items), Language (3 items), Visuospatial (1 item), Planning (2 items), and Organization (1 item) complaints were associated with diagnostic progression. After covarying for depression, remembering appointments and understanding spoken instructions remained significant predictors of diagnostic progression. While previous work has focused largely on memory-based SCD complaints, the current findings support a wider assessment of complaints may be useful in identifying those at risk for a neurodegenerative disease.

Facial aging, cognitive impairment, and dementia risk

BackgroundFacial aging, cognitive impairment, and dementia are all age-related conditions. However, the temporal relation between facial age and future risk of dementia was not systematically examined.ObjectivesTo investigate the relationship between facial age (both subjective/perceived and objective) and cognitive impairment and/or dementia risk.MethodsThe study included 195,329 participants (age ≥ 60 y) from the UK Biobank (UKB) with self-perceived facial age and 612 participants from the Nutrition and Health of Aging Population in China Project (NHAPC) study (age ≥ 56 y) with objective assessment of facial age. Cox proportional hazards model was used to prospectively examine the hazard ratios (HRs) and their 95% confidence intervals (CIs) of self-perceived facial age and dementia risk in the UKB, adjusting for age, sex, education, APOE ε4 allele, and other potential confounders. Linear and logistic regressions were performed to examine the cross-sectional association between facial age (perceived and objective) and cognitive impairment in the UKB and NHAPC, with potential confounders adjusted.ResultsDuring a median follow-up of 12.3 years, 5659 dementia cases were identified in the UKB. The fully-adjusted HRs comparing high vs. low perceived facial age were 1.61 (95% CI, 1.33 ~ 1.96) for dementia (P-trend ≤ 0.001). Subjective facial age and cognitive impairment was also observed in the UKB. In the NHAPC, facial age, as assessed by three objective wrinkle parameters, was associated with higher odds of cognitive impairment (P-trend < 0.05). Specifically, the fully-adjusted OR for cognitive impairment comparing the highest versus the lowest quartiles of crow’s feet wrinkles number was 2.48 (95% CI, 1.06 ~ 5.78).ConclusionsHigh facial age was associated with cognitive impairment, dementia and its subtypes after adjusting for conventional risk factors for dementia. Facial aging may be an indicator of cognitive decline and dementia risk in older adults, which can aid in the early diagnosis and management of age-related conditions.

Multimodal Attention Network for Dementia Prediction.

The early identification of an individual's dementia risk is crucial for disease prevention and the design of insurance products in an aging society. This study aims to accurately predict the future incidence risk of dementia in individuals by leveraging the advantages of neural networks. This is, however, complicated by the high dimensionality and sparsity of the International Classification of Diseases (ICD) codes when utilizing data from Taiwan's National Health Insurance, which includes individual profiles and medical records. Inspired by the click-through rate (CTR) problem in recommendation systems, where future user behavior is predicted based on their past consumption records, we address these challenges with a multimodal attention network for dementia (MAND), which incorporates an ICD code embedding layer and multihead self-attention to encode ICD codes and capture interactions among diseases. Additionally, we investigate the applicability of several CTR methods to the dementia prediction problem. MAND achieves an AUC of 0.9010, surpassing traditional CTR models and demonstrating its effectiveness. The highly flexible pipelined design allows for module replacement to meet specific requirements. Furthermore, the analysis of attention scores reveals diseases highly correlated with dementia, aligning with prior research and emphasizing the interpretability of the model. This research deepens our understanding of the diseases associated with dementia, and the accurate prediction provided can serve as an early warning for dementia occurrence, aiding in its prevention.

In Case You Haven't Heard…

Keeping your brain sharp as you age has a lot to do with your heart — and the younger you start taking better care of it, the better — according to a new scientific statement published by the American Heart Association (AHA), CNN Health reported Oct. 10. “Dementia is commonly seen as an incurable and relentless disease that cannot be prevented,” said Fernando Testai, M.D., Ph.D., a professor of neurology and rehabilitation at the University of Illinois College of Medicine in Chicago, in a statement. “Evidence shows, however, that adopting a healthy lifestyle and identifying and treating vascular risk factors early may help preserve normal brain function and reduce the burden of Alzheimer's disease and other related dementias,” said Testai, who chaired the statement writing group. Nearly 130 million adults in the United States have some form of heart disease, according to the AHA. The disease also takes a toll on the brain. The narrowing of arteries that occurs with coronary heart disease and high blood pressure can reduce blood flow and cause damage to the small blood vessels in the brain, resulting in cognitive impairment, the AHA said. High blood pressure and Type 2 diabetes can also reduce blood flow to the brain and increase inflammation, leading to cognitive decline and dementia. Having coronary heart disease raises the risk of future dementia by 27% compared with people without heart disease, the AHA statement said.

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction.

DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both βs 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-drivenhealth deficitselection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA's impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA's limited contribution suggests caution in their use for individual risk assessment of dementia.

Individualized, cross-validated prediction of future dementia using cognitive assessments in people with mild cognitive symptoms.

We aimed to develop an algorithm to predict the individualized risk of future dementia using brief cognitive tests suitable for primary care. We included 612 participants with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, assessed for at least 4 years or until progression to dementia. A logistic regression model, using cognitive tests as predictors and dementia progression as an outcome, stratified participants into low, intermediate, or high risk. A second model, including 1-year cognitive test changes, was applied to the intermediate group. The models were replicated in 392 SCD/MCI participants from the BioFINDER-1 study. The best two-step model for predicting dementia incorporated Trail Making Test B (attention/executive function), Animal Fluency (verbal fluency), Mini-Mental State Examination (global cognition), and 10-word list recall (memory). The model's positive predictive value in ADNI was 85.8% and negative predictive value was 92.2% versus 62.5% and 95.6%, respectively, in BioFINDER-1. This two-step model accurately predicts individualized dementia risk. To our knowledge, this is the first algorithm for predicting all-cause dementia using a novel two-step model utilizing brief cognitive tests. Applying a validated model including the Trail Making Test B, Animal Fluency, MMSE, Alzheimer's Disease Assessment Scale delayed, and immediate recall can robustly and accurately categorize individuals into low, intermediate, or high risk of dementia progression and can facilitate clinical decision-making and personalized patient care. We created an app that is available for research and educational purposes at https://brainapps.shinyapps.io/PredictAllCauseDementia to provide an individualized risk score for dementia progression.

Plasma proteome-wide analysis of cerebral small vessel disease identifies novel biomarkers and disease pathways.

Cerebral small vessel disease (SVD), as defined by neuroimaging characteristics such as white matter hyperintensities (WMHs), cerebral microhemorrhages (CMHs), and lacunar infarcts, is highly prevalent and has been associated with dementia risk and other clinical sequelae. Although conditions such as hypertension are known to contribute to SVD, little is known about the diverse set of subclinical biological processes and molecular mediators that may also influence the development and progression of SVD. To better understand the mechanisms underlying SVD and to identify novel SVD biomarkers, we used a large-scale proteomic platform to relate 4,877 plasma proteins to MRI-defined SVD characteristics within 1,508 participants of the Atherosclerosis Risk in Communities (ARIC) Study cohort. Our proteome-wide analysis of older adults (mean age: 76) identified 13 WMH-associated plasma proteins involved in synaptic function, endothelial integrity, and angiogenesis, two of which remained associated with late-life WMH volume when measured nearly 20 years earlier, during midlife. We replicated the relationship between 9 candidate proteins and WMH volume in one or more external cohorts; we found that 11 of the 13 proteins were associated with risk for future dementia; and we leveraged publicly available proteomic data from brain tissue to demonstrate that a subset of WMH-associated proteins was differentially expressed in the context of cerebral atherosclerosis, pathologically-defined Alzheimer's disease, and cognitive decline. Bidirectional two-sample Mendelian randomization analyses examined the causal relationships between candidate proteins and WMH volume, while pathway and network analyses identified discrete biological processes (lipid/cholesterol metabolism, NF-kB signaling, hemostasis) associated with distinct forms of SVD. Finally, we synthesized these findings to identify two plasma proteins, oligodendrocyte myelin glycoprotein (OMG) and neuronal pentraxin receptor (NPTXR), as top candidate biomarkers for elevated WMH volume and its clinical manifestations.

FC48: Using Complexity Analysis to Explore the Differences of Resting- state fMRI Data Among Late- life Depressed, Mild Cognitive Impaired, and Cognitive Normal Older Adults

Introduction: Late-life depression (LLD) is associated with cognitive deficit with risk of future dementia. By examining the entropy of the spontaneous brain activity, we aimed to understand the neural mechanism pertaining to cognitive decline in LLD.Methods: We collected MRI scans in older adults with LLD (n = 32), mild cognitive impairment [MCI (n = 25)] and normal cognitive function [NC, (n = 47)]. Multiscale entropy analysis (MSE) was applied to resting-state fMRI data. Under the scale factor (tau) 1 and 2, reliable separation of fMRI data and noise was achieved. We calculated the brain entropy in 90 brain regions based on automated anatomical atlas (AAL). Due to exploratory nature of this study, we presented data of group-wise comparison in brain entropy between LLD vs. NC, MCI vs. NC, and LLD and MCD with a p-value below 0.001.Results: The mean Mini-Mental State Examination (MMSE) score of LLD and MCI was 27.9 and 25.6. Under tau 2, we found higher brain entropy of LLD in left globus pallidus than MCI (p = 0.002) and NC (p = 0,009). Higher brain entropy of LLD than NC was also found in left frontal superior gyrus, left middle superior gyrus, left amygdala and left inferior parietal gyrus. The only brain region with higher brain entropy in MCI than control was left posterior cingulum (p-value = 0.015). Under tau 1, higher brain entropy was also found in LLD than in MCI in right orbital part of medial frontal gyrus and left globus pallidus (p-value = 0.007 and 0.005).Conclusions: Our result is consistent with prior hypothesis where higher brain entropy was found during early aging process as compensation. We found such phenomenon particular in left globus pallidus in LLD, which could be served as a discriminative brain region. Being a key region in reward system, we hypothesis such region may be associated with apathy and with unique pathway of cognitive decline in LLD. We will undertake subsequent analysis longitudinally in this cohortKey words: resting-state fMRI, Late-life depression, Brain entropy, globus pallidus, cognitive decline

Delirium in the United States: Results From the 2023 Cross-Sectional World Delirium Awareness Day Prevalence Study

Delirium is an acute brain dysfunction associated with an increased risk of mortality and future dementia. To describe the prevalence of clinically documented delirium in the United States on World Delirium Awareness Day2023. This is a sub-analysis of a prospective, cross-sectional, online, international survey. All health care settings were eligible, with the exception of operating rooms and outpatient clinics. Health care clinicians, administrators, and researchers completed the survey. The primary outcome was the prevalence of clinically documented delirium at 8:00 a.m. and 8:00 p.m. on March 15, 2023. Secondary outcomes were related to health care delivery. Descriptive statistics are reported. Differences between unit types (non-intensive care unit vs intensive care unit) were examined for all outcomes. Ninety-one hospital units reported on 1318/1213 patients. The prevalence of clinically documented delirium was 16.4% (n= 216/1318) at 8:00 a.m. and 17.9% (n= 217/1213) at 8:00 p.m. (P=0.316) and significantly differed between age groups, reported discipline, unit, and hospital types. Significant differences were identified between non-intensive care unit and intensive care unit settings in the use of delirium-related protocols, nonpharmacologic and pharmacologic management, educational processes, and barriers to evidence-based delirium care. To our knowledge, this is the first epidemiologic survey of clinically documented delirium across two time points in the United States. Delirium remains a significant burden and challenge for health care systems. The high percentage of units using delirium management protocols suggests administrator and clinician awareness of evidence-based strategies for its detection and mitigation. We provide recommendations for future studies and quality improvement projects to improve clinical recognition and management of delirium.

P.023 Review of imaging changes, cognitive decline, and dementia risk in cancer survivors after chemotherapy

Background: Cancer survival rates in Canada have been improving, leading to a steady increase in the number of survivors entering the typical ages of dementia onset. Yet, some cancer treatments (e.g. chemotherapy) are neurotoxic and adversely affect normal brain functioning. We conducted a review to examine changes observed in brain imaging and cognitive measures in survivorship, and long-term risk of dementia among cancer survivors. Methods: 91 Primary studies were selected from PubMed. Inclusion criteria were studies investigating the changes in brain imaging, cognition, and future dementia risk among adult survivors who received chemotherapy. Study quality was assessed based on 1) prospective, controlled design, 2) sample size, and 3) validated imaging and cognitive metrics. Results: Imaging studies identified MRI-based structural grey and white matter changes and functional network changes among survivors. Cognitive studies reported heterogeneous impairments in attention, memory, and executive function. In studies that examined dementia risk among cancer survivors, 67% reported lower risk of dementia, while 33% reported no association or a higher risk. Conclusions: While short-term cognitive impairment with associated changes on brain imaging is widely reported, findings concerning future or long-term cognitive impairment are mixed. Studies are warranted to identify potential connections between short-term and long-term cognitive function after cancer treatment.

Antidepressant exposure and long-term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder.

The use of antidepressants in major depressive disorder (MDD) has been reported to influence long-term risk of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD), but studies are conflicting. We used inverse probability weighted (IPW) Cox models with time-varying covariates in a retrospective cohort study among midlife veterans with MDD within the US Veterans Affairs healthcare system from January 1, 2000 to June 1, 2022. A total of 35,200 patients with MDD were identified. No associations were seen regarding the effect of being exposed to any antidepressant versus no exposure on AD/ADRD risk (events=1,056, hazard ratio=0.94, 95% confidence interval: 0.81 to 1.09) or the exposure to specific antidepressant classes versus no exposure. A risk reduction was observed for female patients in a stratified analysis; however, the number of cases was small. Our study suggests that antidepressant exposure has no effect on AD/ADRD risk. The association in female patients should be interpreted with caution and requires further attention. We studied whether antidepressant use was associated with future dementia risk. We specifically focused on patients after their first-ever diagnosis of depression. We used IPW Cox models with time-varying covariates and a large observation window. Our study did not identify an effect of antidepressant use on dementia risk. A risk reduction was observed in female patients, but the number of cases was small.

Subjective hearing loss is not associated with an increased risk of Alzheimer's disease dementia

Hearing loss is a risk-factor for dementia but the reasons for this are unclear. Subjective hearing loss is related to increased future dementia risk, however, this metric has not been previously examined with cognitive, neuroimaging and biochemical measures that are relevant to Alzheimer's disease. We assessed Cognitively Normal and Mild Cognitively Impaired participants from the Alzheimer's Disease Neuroimaging Initiative with subjective hearing loss to examine if they had faster decline in episodic memory scores, hippocampal volume and greater pTau positivity. The likelihood of a dementia diagnosis in hearing impaired participants over a 5-year period was also assessed. There were no statistically significant differences between the hearing subgroups over a 5-year period nor were there in conversions to a dementia diagnosis. Objective hearing loss metrics may provide a more reliable link between hearing loss and dementia risk.

Abstract MP23: Cardiovascular Diseases and Risk of Dementia in the General Population: Observational and Genetic Studies

Importance: Cardiovascular diseases are associated with increased risk of subtypes of dementia. The causal nature is however unclear. Objective: To assess observational and genetic associations between a range of cardiovascular disease and risk of all-cause dementia and its major subtypes. Design, Settings, and Participants: We performed time-dependent Cox regression analyses in three prospective cohorts, the Copenhagen City Heart Study (N=10,373), the Copenhagen General Population Study (N=101,582), and the UK Biobank (N=377,706); median follow-up times were 15, 9, and 13 years, respectively. Estimates from each cohort were pooled in meta-analyses using fixed-effects models. Subsequently, we investigated genetic susceptibility for cardiovascular diseases and risk of all-cause dementia, Alzheimer’s disease, and vascular dementia, using individual-level data from the UK Biobank and summary statistics from the FinnGen study. Exposures: Ischemic heart disease, myocardial infarction, peripheral arterial disease, hypertensive heart disease, stroke, ischemic stroke, atrial fibrillation, heart failure, and the combination of all. Main Outcomes and Measures: Outcomes include all-cause dementia, Alzheimer’s disease, and vascular dementia. Measures are hazard ratios (HRs) and 95% confidence intervals (CIs) in observational studies and odds ratios (ORs) and 95% CIs in genetic studies. Results: Observationally, cardiovascular diseases were associated with high future risk of incident all-cause dementia, Alzheimer’s disease, and vascular dementia in meta-analyses, with HRs up to 7.49 (95% CI: 6.63, 8.46). Genetically, using individual level data from the UK Biobank, predisposition to ischemic stroke was associated with high risk of all-cause dementia, Alzheimer’s disease, and vascular dementia, with ORs of 1.64 (1.35, 1.98), 1.44 (1.10, 1.89), and 2.06 (1.41, 3.01), respectively, with similar estimates for ischemic stroke; genetic predisposition to ischemic heart disease was associated with high risk of vascular dementia, with an OR of 1.24 (1.03, 1.50). Genetic summary-level data from the FinnGen study confirmed the estimates for stroke and ischemic stroke. Conclusion and Relevance: Our study provides novel evidence that the association between stroke and all-cause dementia and its major subtypes may be of a causal nature. Further, we observe that genetic susceptibility for ischemic heart disease is associated with incident vascular dementia. These findings underscore the importance of integrating cardiovascular disease prevention into interventions to reduce dementia risk.

Relationship of Perivascular Space Markers With Incident Dementia in Cerebral Small Vessel Disease.

Recent studies, using diffusion tensor image analysis along the perivascular space (DTI-ALPS), suggest impaired perivascular space (PVS) function in cerebral small vessel disease, but they were cross-sectional, making inferences on causality difficult. We determined associations between impaired PVS, measured using DTI-ALPS and PVS volume, and cognition and incident dementia. In patients with lacunar stroke and confluent white matter hyperintensities, without dementia at baseline, recruited prospectively in a single center, magnetic resonance imaging was performed annually for 3 years, and cognitive assessments, including global, memory, executive function, and processing speed, were performed annually for 5 years. We determined associations between DTI-ALPS and PVS volume with cerebral small vessel disease imaging markers (white matter hyperintensity volume, lacunes, and microbleeds) at baseline and with changes in imaging markers. We determined whether DTI-ALPS and PVS volume at baseline and change over 3 years predicted incident dementia. Analyses were controlled for conventional diffusion tensor image metrics using 2 markers (median mean diffusivity [MD] and peak width of skeletonized MD) and adjusted for age, sex, and vascular risk factors. A total of 120 patients, mean age 70.0 years and 65.0% male, were included. DTI-ALPS declined over 3 years, while no change in PVS volume was found. Neither DTI-ALPS nor PVS volume was associated with cerebral small vessel disease imaging marker progression. Baseline DTI-ALPS was associated with changes in global cognition (β=0.142, P=0.032), executive function (β=0.287, P=0.027), and long-term memory (β=0.228, P=0.027). Higher DTI-ALPS at baseline predicted a lower risk of dementia (hazard ratio, 0.328 [0.183-0.588]; P<0.001), and this remained significant after including median MD as a covariate (hazard ratio, 0.290 [0.139-0.602]; P<0.001). Change in DTI-ALPS predicted dementia conversion (hazard ratio, 0.630 [0.428-0.964]; P=0.048), but when peak width of skeletonized MD and median MD were entered as covariates, the association was not significant. There was no association between baseline PVS volume, or PVS change over 3 years, and conversion to dementia. DTI-ALPS predicts future dementia risk in patients with lacunar strokes and confluent white matter hyperintensities. However, the weakening of the association between change in DTI-ALPS and incident dementia after controlling for peak width of skeletonized MD and median MD suggests part of the signal may represent conventional diffusion tensor image metrics. PVS volume is not a predictor of future dementia risk.

Visual processing speed and its association with future dementia development in a population-based prospective cohort: EPIC-Norfolk

Visual processing deficits have frequently been reported when studied in individuals with dementia, which suggests their potential utility in supporting dementia screening. The study uses EPIC-Norfolk Prospective Population Cohort Study data (n = 8623) to investigate the role of visual processing speed assessed by the Visual Sensitivity Test (VST) in identifying the risk of future dementia using Cox regression analyses. Individuals with lower scores on the simple and complex VST had a higher probability of a future dementia diagnosis HR1.39 (95% CI 1.12, 1.67, P < 0.01) and HR 1.56 (95% CI 1.27, 1.90, P < 0.01), respectively. Although other more commonly used cognitive dementia screening tests were better predictors of future dementia risk (HR 3.45 for HVLT and HR 2.66, for SF-EMSE), the complex VST showed greater sensitivity to variables frequently associated with dementia risk. Reduced complex visual processing speed is significantly associated with a high likelihood of a future dementia diagnosis and risk/protective factors in this cohort. Combining visual processing tests with other neuropsychological tests could improve the identification of future dementia risk.

The usability and reliability of a smartphone application for monitoring future dementia risk in ageing UK adults.

The rising number of dementia diagnoses and imminent adoption of disease-modifying treatments necessitate innovative approaches to identify individuals at risk, monitor disease course and intervene non-pharmacologically earlier in the disease course. Digital assessments of dementia risk and cognitive function have the potential to outperform traditional in-person assessments in terms of their affordability, accuracy and longitudinal tracking abilities. However, their accessibility and reliability in older adults is unclear. To evaluate the usability and reliability of a smartphone assessment of lifestyle and cognitive factors relevant to dementia risk in a group of UK-based older adults. Cognitively healthy adults (n = 756) recruited through the Dementias Platform UK Great Minds volunteer register completed three assessments of cognitive function and dementia risk over a 3-month period and provided usability feedback on the Five Lives smartphone application (app). We evaluated cognitive test scores for age, gender and higher education effects, normality distributions, test-retest reliability and their relationship with participants' lifestyle dementia risk factors. Participants found the app 'easy to use', 'quick to complete' and 'enjoyable'. The cognitive tests showed normal or near-to-normal distributions, variable test-retest reliabilities and age-related effects. Only tests of verbal ability showed gender and education effects. The cognitive tests did not correlate with lifestyle dementia risk scores. The Five Lives assessment demonstrates high usability and reliability among older adults. These findings highlight the potential of digital assessments in dementia research and clinical practice, enabling improved accessibility and better monitoring of cognitive health on a larger scale than traditional in-person assessments.

Association between pre-dementia psychiatric diagnoses and all-cause dementia is independent from polygenic dementia risks in the UK Biobank

Psychiatric disorders have been associated with higher risk for future dementia. Understanding how pre-dementia psychiatric disorders (PDPD) relate to established dementia genetic risks has implications for dementia prevention. In this retrospective cohort study, we investigated the relationships between polygenic risk scores for Alzheimer's disease (AD PRS), PDPD, alcohol use disorder (AUD), and subsequent dementia in the UK Biobank (UKB) and tested whether the relationships are consistent with different causal models. Among 502,408 participants, 9352 had dementia. As expected, AD PRS was associated with greater risk for dementia (odds ratio (OR) 1.62, 95% confidence interval (CI), 1.59-1.65). A total of 94,237 participants had PDPD, of whom 2.6% (n=2519) developed subsequent dementia, compared to 1.7% (n=6833) of 407,871 participants without PDPD. Accordingly, PDPD were associated with 73% greater risk of incident dementia (OR 1.73, 1.65-1.83). Among dementia subtypes, the risk increase was 1.5-fold for AD (n=3365) (OR 1.46, 1.34-1.59) and 2-fold for vascular dementia (VaD, n=1823) (OR 2.08, 1.87-2.32). Our data indicated that PDPD were neither a dementia prodrome nor a mediator for AD PRS. Shared factors for both PDPD and dementia likely substantially account for the observed association, while a causal role of PDPD in dementia could not be excluded. AUD could be one of the shared causes for PDPD and dementia. Psychiatric diagnoses were associated with subsequent dementia in UKB participants, and the association is orthogonal to established dementia genetic risks. Investigating shared causes for psychiatric disorders and dementia would shed light on this dementia pathway. US NIH (K08AG054727).

Effects of rhythm-control and rate-control strategies on cognitive function and dementia in atrial fibrillation: a systematic review and meta-analysis.

Growing evidence suggests that atrial fibrillation (AF) is an independent risk factor for cognitive impairment and dementia, even in the absence of thromboembolic events and stroke. Whether rhythm-control therapy can protect cognitive function remains unclear. We aimed to evaluate the efficacy of rhythm-control strategies in patients with AF regarding cognitive function and dementia risk. We systematically searched the PubMed, Embase and Cochrane Library databases for randomised clinical trials, cohort and case-control studies evaluating the associations between rhythm-control strategies and cognitive function outcomes up to May 2023. We assessed the risk of bias using the ROBINS-I and the Cochrane risk-of-bias tool. Both fixed- and random-effects models were used to create summary estimates of risk. We included a total of 14 studies involving 193,830 AF patients. In the pooled analysis, compared with rate-control, rhythm-control therapy was significantly associated with a lower risk of future dementia (hazard ratio (HR) 0.74; 95% confidence interval (CI) 0.62-0.89; I2= 62%). Among the rhythm-control strategies, AF ablation is a promising treatment that was related to significantly lower risks of overall dementia (HR 0.62; 95% CI 0.56-0.68; I2= 42%), Alzheimer's disease (HR 0.78; 95% CI 0.66-0.92; I2= 0%) and vascular dementia (HR 0.58; 95% CI 0.42-0.80; I2= 31%). Pooled results also showed that compared with patients without ablation, those who underwent AF ablation had significantly greater improvement in cognitive score (standardized mean difference (SMD) 0.85; 95% CI 0.30-1.40; P = 0.005; I2 = 76%). Rhythm-control strategies, especially ablation, are effective in protecting cognitive function, reducing dementia risk and thus improving quality of life in AF patients.

Predicting Four-Year's Alzheimer's Disease Onset Using Longitudinal Neurocognitive Tests and MRI Data Using Explainable Deep Convolutional Neural Networks.

Prognosis of future risk of dementia from neuroimaging and cognitive data is important for optimizing clinical management for patients at early stage of Alzheimer's disease (AD). However, existing studies lack an efficient way to integrate longitudinal information from both modalities to improve prognosis performance. In this study, we aim to develop and evaluate an explainable deep learning-based framework to predict mild cognitive impairment (MCI) to AD conversion within four years using longitudinal whole-brain 3D MRI and neurocognitive tests. We proposed a two-stage framework that first uses a 3D convolutional neural network to extract single-timepoint MRI-based AD-related latent features, followed by multi-modal longitudinal feature concatenation and a 1D convolutional neural network to predict the risk of future dementia onset in four years. The proposed deep learning framework showed promising to predict MCI to AD conversion within 4 years using longitudinal whole-brain 3D MRI and cognitive data without extracting regional brain volumes or cortical thickness, reaching a balanced accuracy of 0.834, significantly improved from models trained from single timepoint or single modality. The post hoc model explainability revealed heatmap indicating regions that are important for predicting future risk of AD. The proposed framework sets the stage for future studies for using multi-modal longitudinal data to achieve optimal prediction for prognosis of AD onset, leading to better management of the diseases, thereby improving the quality of life.

CORTICAL CONTROL OF MOBILITY: MOVING TOWARD CLINICAL OUTCOMES AND INTERVENTIONS

Abstract A three-year series of pre-conference workshops at GSA a decade ago brought together leading scientists in the multidisciplinary field of brain, aging, and mobility. Since then, the field has advanced the understanding of motor control as a predominantly subcortical phenomenon to the attentional and cortical control of mobility and has extended the view of cognitive and motor functions as distinct to there being shared causes of cognitive and mobility declines. Emerging studies are further elucidating mechanisms of motor control (Holtzer, Baillargeon), demonstrating relations with important clinical outcomes, including dementia (Tian) and community mobility (Rosso), and exploring novel interventions on clinical and neurophysiological outcomes (Kahya), as demonstrated by the series of talks in this symposium. Roee Holtzer assesses prefrontal cortex efficiency over repeated trials of attention-demanding dual-task walking in older adults with and without multiple sclerosis. Emma Baillargeon explores the heterogeneity of prefrontal responses to walking among older adults and describes the relation of prefrontal response with performance metrics. Qu Tian demonstrates trajectories of gait variability measures over time predict future dementia risk. Andrea Rosso investigates prefrontal activation as a biomarker of gait automaticity and its relation to community mobility. Finally, Melike Kahya demonstrates brain stimulation through transcranial direct current stimulation as a potential intervention to improve standing balance during cognitively challenging tasks and examines the mechanisms of its action through dual-task cost and electroencephalograph (EEG) recordings. Together, these studies will provide an overview of the current understanding of cortical control of mobility and its implications for clinical outcomes and interventions.