Association of resting heart rate with cognitive decline and dementia in older adults: A population-based cohort study

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

BACKGROUND

Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI).

OBJECTIVE

This study aimed to use data collected from fitness trackers to predict MCI status.

METHODS

In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status.

RESULTS

Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time.

CONCLUSIONS

Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

Resting heart rate and risk of dementia: a Mendelian randomization study in the international genomics of Alzheimer's Project and UK Biobank

Background

Observational studies have demonstrated that a higher resting heart rate (RHR) is associated with an increased risk of dementia. However, it is not clear whether the association is causal. This study aimed to determine the causal effects of higher genetically predicted RHR on the risk of dementia.

Methods

We performed a two-sample Mendelian randomization analysis to investigate the causal effect of higher genetically predicted RHR on Alzheimer's disease (AD) using summary statistics from genome-wide association studies. The generalized summary Mendelian randomization (GSMR) analysis was used to analyze the corresponding effects of RHR on following different outcomes: 1) diagnosis of AD (International Genomics of Alzheimer's Project), 2) family history (maternal and paternal) of AD from UK Biobank, 3) combined meta-analysis including these three GWAS results. Further analyses were conducted to determine the possibility of reverse causal association by adjusting for RHR modifying medication.

Results

The results of GSMR showed no significant causal effect of higher genetically predicted RHR on the risk of AD (βGSMR = 0.12, P = 0.30). GSMR applied to the maternal family history of AD (βGSMR = -0.18, P = 0.13) and to the paternal family history of AD (βGSMR = -0.14, P = 0.39) showed the same results. Furthermore, the results were robust after adjusting for RHR modifying drugs (βGSMR = -0.03, P = 0.72).

Conclusion

Our study did not find any evidence that supports a causal effect of RHR on dementia. Previous observational associations between RHR and dementia are likely attributed to the correlation between RHR and other cardiovascular diseases.

Resting heart rate causally affects the brain cortical structure: Mendelian randomization study

Resting heart rate (RHR) has been linked to impaired cortical structure in observational studies. However, the extent to which this association is potentially causal has not been determined. Using genetic data, this study aimed to reveal the causal effect of RHR on brain cortical structure. A Two-Sample Mendelian randomization (MR) analysis was conducted. Sensitivity analyses, weighted median, MR Pleiotropy residual sum and outlier, and MR-Egger regression were conducted to evaluate heterogeneity and pleiotropy. A causal relationship between RHR and cortical structures was identified by MR analysis. On the global scale, elevated RHR was found to decrease global surface area (SA; P < 0.0125). On a regional scale, the elevated RHR significantly decreased the SA of pars triangularis without global weighted (P = 1.58 × 10-4) and the thickness (TH) of the paracentral with global weighted (P = 3.56 × 10-5), whereas it increased the TH of banks of the superior temporal sulcus in the presence of global weighted (P = 1.04 × 10-4). MR study provided evidence that RHR might be causally linked to brain cortical structure, which offers a different way to understand the heart-brain axis theory.

Individual differences in seated resting heart rate are associated with multisensory perceptual function in older adults

There is evidence that cardiovascular function can influence sensory processing and cognition, which are known to change with age. However, whether the precision of unisensory and multisensory temporal perception is influenced by cardiovascular activity in older adults is uncertain. We examined whether seated resting heart rate (RHR) was associated with unimodal visual and auditory temporal discrimination as well as susceptibility to the audio-visual Sound Induced Flash Illusion (SIFI) in a large sample of older adults (N = 3232; mean age = 64.17 years, SD = 7.74, range = 50-93; 56% female) drawn from The Irish Longitudinal Study on Ageing (TILDA). Faster seated RHR was associated with better discretization of two flashes (but not two beeps) and increased SIFI susceptibility when the audio-visual stimuli were presented close together in time but not at longer audio-visual temporal offsets. Our findings suggest a significant relationship between cardiovascular activity and the precision of visual and audio-visual temporal perception in older adults, thereby providing novel evidence for a link between cardiovascular function and perceptual function in aging.

Autonomic nervous system dysfunction throughout menopausal transition: A potential mechanism underpinning cardiovascular and cognitive alterations during female ageing

Cardiovascular diseases (CVD) and neurodegenerative disorders, such as Alzheimer's disease (AD), are highly prevalent conditions in middle-aged women that severely impair quality of life. Recent evidence suggests the existence of an intimate cross-talk between the heart and the brain, resulting from a complex network of neurohumoral circuits. From a pathophysiological perspective, the higher prevalence of AD in women may be explained, at least in part, by sex-related differences in the incidence/prevalence of CVD. Notably, the autonomic nervous system, the main heart-brain axis physiological orchestrator, has been suggested to play a role in the incidence of adverse cardiovascular events in middle-aged women because of decreases in oestrogen-related signalling during transition into menopause. Despite its overt relevance for public health, this hypothesis has not been thoroughly tested. Accordingly, in this review, we aim to provide up to date evidence supporting how changes in circulating oestrogen levels during transition to menopause may trigger autonomic dysfunction, thus promoting cardiovascular and cognitive decline in women. A main focus on the effects of oestrogen-mediated signalling at CNS structures related to autonomic regulation is provided, particularly on the role of oestrogens in sympathoexcitation. Improving the understanding of the contribution of the autonomic nervous system on the development, maintenance and/or progression of both cardiovascular and cognitive dysfunction during the transition to menopause should help improve the clinical management of elderly women, with the outcome being an improved life quality during the natural ageing process.

Sex differences in the age-related decrease of spontaneous baroreflex function in healthy individuals

The baroreflex is a powerful physiological mechanism for rapidly adjusting heart rate in response to changes in blood pressure. Spontaneous baroreflex sensitivity (BRS) has been shown to decrease with age. However, studies of sex differences in these age-related changes are rare. Here we investigated several markers of spontaneous baroreflex function in a large sample of healthy individuals. Cardiovascular signals were recorded in the supine position under carefully controlled resting conditions. After quality control, n = 980 subjects were divided into five age groups [age < 30 yr (n = 612), 30-39 yr (n = 140), 40-49 yr (n = 95), 50-59 yr (n = 61), and >60 yr (n = 72)]. Spontaneous baroreflex function was assessed in the time domain (bradycardic and tachycardic slope) and in the frequency domain in the low- and high-frequency band (LF-α, HF-α) applying the transfer function. General linear models showed a significant effect of factor age (P < 0.001) and an age × sex interaction effect (P < 0.05) on each indicator of the baroreflex function. Simple main effects showed a significantly higher BRS as indicated by tachycardic slope, LF-α and HF-α in middle-aged women compared with men (30-39 yr) and higher LF-α, bradycardic and tachycardic slope in men compared with women of the oldest age group (>60 yr). Changes in BRS over the lifespan suggest that baroreflex function declines more slowly but earlier in life in men than in women. Our findings could be linked to age-related changes in major sex hormone levels, suggesting significant implications for diverse cardiovascular outcomes and the implementation of targeted preventive strategies.NEW & NOTEWORTHY In this study, we demonstrate that the age-related decrease of spontaneous baroreflex sensitivity is different in men and women by analyzing resting state cardiovascular data of a large sample of healthy individuals.

Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors

BACKGROUND

Developing a screening method for identifying individuals at higher risk of elevated brain amyloid burden is important to reduce costs and burden to patients in clinical trials on Alzheimer's disease or the clinical setting. We developed machine learning models using objectively measured lifestyle factors to predict elevated brain amyloid burden on positron emission tomography.

METHODS

Our prospective cohort study of non-demented, community-dwelling older adults aged ≥ 65 years was conducted from August 2015 to September 2019 in Usuki, Oita Prefecture, Japan. One hundred and twenty-two individuals with mild cognitive impairment or subjective memory complaints (54 men and 68 women, median age: 75.50 years) wore wearable sensors and completed self-reported questionnaires, cognitive test, and positron emission tomography imaging at baseline. Moreover, 99 individuals in the second year and 61 individuals in the third year were followed up. In total, 282 eligible records with valid wearable sensors, cognitive test results, and amyloid imaging and data on demographic characteristics, living environments, and health behaviors were used in the machine learning models. Amyloid positivity was defined as a standardized uptake value ratio of ≥ 1.4. Models were constructed using kernel support vector machine, Elastic Net, and logistic regression for predicting amyloid positivity. The mean score among 10 times fivefold cross-validation repeats was utilized for evaluation.

RESULTS

In Elastic Net, the mean area under the receiver operating characteristic curve of the model using objectively measured lifestyle factors alone was 0.70, whereas that of the models using wearable sensors in combination with demographic characteristics and health and life environment questionnaires was 0.79. Moreover, 22 variables were common to all machine learning models.

CONCLUSION

Our machine learning models are useful for predicting elevated brain amyloid burden using readily-available and noninvasive variables without the need to visit a hospital.

TRIAL REGISTRATION

This prospective study was conducted in accordance with the Declaration of Helsinki and was approved by the local ethics committee of Oita University Hospital (UMIN000017442). A written informed consent was obtained from all participants. This research was performed based on the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.

Predicting 1-, 3-, 5-, and 8-year all-cause mortality in a community-dwelling older adult cohort: relevance for predictive, preventive, and personalized medicine

BACKGROUND

Population aging is a global public health issue involving increased prevalence of age-related diseases, and concomitant burden on medical resources and the economy. Ninety-two diseases have been identified as age-related, accounting for 51.3% of the global adult disease burden. The economic cost per capita for older people over 60 years is 10 times that of the younger population. From the aspects of predictive, preventive, and personalized medicine (PPPM), developing a risk-prediction model can help identify individuals at high risk for all-cause mortality and provide an opportunity for targeted prevention through personalized intervention at an early stage. However, there is still a lack of predictive models to help community-dwelling older adults do well in healthcare.

OBJECTIVES

This study aims to develop an accurate 1-, 3-, 5-, and 8-year all-cause mortality risk-prediction model by using clinical multidimensional variables, and investigate risk factors for 1-, 3-, 5-, and 8-year all-cause mortality in community-dwelling older adults to guide primary prevention.

METHODS

This is a two-center cohort study. Inclusion criteria: (1) community-dwelling adult, (2) resided in the districts of Chaonan or Haojiang for more than 6 months in the past 12 months, and (3) completed a health examination. Exclusion criteria: (1) age less than 60 years, (2) more than 30 incomplete variables, (3) no signed informed consent. The primary outcome of the study was all-cause mortality obtained from face-to-face interviews, telephone interviews, and the medical death database from 2012 to 2021. Finally, we enrolled 5085 community-dwelling adults, 60 years and older, who underwent routine health screening in the Chaonan and Haojiang districts, southern China, from 2012 to 2021. Of them, 3091 participants from Chaonan were recruited as the primary training and internal validation study cohort, while 1994 participants from Haojiang were recruited as the external validation cohort. A total of 95 clinical multidimensional variables, including demographics, lifestyle behaviors, symptoms, medical history, family history, physical examination, laboratory tests, and electrocardiogram (ECG) data were collected to identify candidate risk factors and characteristics. Risk factors were identified using least absolute shrinkage and selection operator (LASSO) models and multivariable Cox proportional hazards regression analysis. A nomogram predictive model for 1-, 3-, 5- and 8-year all-cause mortality was constructed. The accuracy and calibration of the nomogram prediction model were assessed using the concordance index (C-index), integrated Brier score (IBS), receiver operating characteristic (ROC), and calibration curves. The clinical validity of the model was assessed using decision curve analysis (DCA).

RESULTS

Nine independent risk factors for 1-, 3-, 5-, and 8-year all-cause mortality were identified, including increased age, male, alcohol status, higher daily liquor consumption, history of cancer, elevated fasting glucose, lower hemoglobin, higher heart rate, and the occurrence of heart block. The acquisition of risk factor criteria is low cost, easily obtained, convenient for clinical application, and provides new insights and targets for the development of personalized prevention and interventions for high-risk individuals. The areas under the curve (AUC) of the nomogram model were 0.767, 0.776, and 0.806, and the C-indexes were 0.765, 0.775, and 0.797, in the training, internal validation, and external validation sets, respectively. The IBS was less than 0.25, which indicates good calibration. Calibration and decision curves showed that the predicted probabilities were in good agreement with the actual probabilities and had good clinical predictive value for PPPM.

CONCLUSION

The personalized risk prediction model can identify individuals at high risk of all-cause mortality, help offer primary care to prevent all-cause mortality, and provide personalized medical treatment for these high-risk individuals from the PPPM perspective. Strict control of daily liquor consumption, lowering fasting glucose, raising hemoglobin, controlling heart rate, and treatment of heart block could be beneficial for improving survival in elderly populations.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13167-023-00342-4.

Resting heart rate, cognitive function, and inflammation in older adults: a population-based study

BACKGROUND

Emerging evidence has linked elevated resting heart rate (RHR) with poor cognitive function in older adults, but the mechanisms underlying their association are poorly understood.

METHODS

This population-based cross-sectional study included 4510 dementia-free participants (age ≥ 65 years; 56.9% females; 38.3% no formal education) in the baseline examination of the Multidomain Interventions to Delay Dementia and Disability in Rural China study. Of these, 1,386 had data on serum proinflammatory cytokines and adhesion molecules. RHR was measured using 12-lead electrocardiograph. We used the Mini-Mental State Examination (MMSE) and a neuropsychological test battery to assess cognitive function. Data were analyzed using the general linear and restricted cubic splines models.

RESULTS

People with high RHR were more likely to have cardiometabolic diseases and worse cognitive function (p < 0.05). There was an inverted J-shaped association of RHR with MMSE and attention scores. Having RHR ≥ 80 bpm (vs. 60-69 bpm) was significantly associated with the multivariable-adjusted β coefficients of - 0.58 [95% confidence interval (CI), - 1.00, - 0.16] for MMSE score and - 0.08 (- 0.15, - 0.01) for attention score. In the serum biomarker subsample, RHR was linearly associated with serum interleukin-6 (IL-6) (β coefficient = 0.19; 95%CI 0.14, 0.24), IL-8 (0.08; 0.02, 0.13), IL-10 (0.09; 0.04, 0.15), tumor necrosis factor-α (0.06; 0.01, 0.11), monocyte chemotactic protein-1 (0.09; 0.04, 0.15), intercellular adhesion molecule-1 (0.16; 0.11, 0.22), and vascular cell adhesion molecule-1 (0.11; 0.06, 0.16).

CONCLUSIONS

There is an inverted J-shaped association of RHR with attention and global cognition. Poor cognitive function and high RHR may be linked through systemic low-grade inflammation and endothelial injury.

Heart rate variability and risk of agitation in Alzheimer's disease: the Atherosclerosis Risk in Communities Study

Agitation in Alzheimer's disease is common and may be related to impaired emotion regulation capacity. Heart rate variability, a proposed index of autonomic and emotion regulation neural network integrity, could be associated with agitation propensity in Alzheimer's disease. We used the Atherosclerosis Risk in Communities Study cohort data, collected over seven visits spanning over two decades, to investigate whether heart rate variability (change) was associated with agitation risk in individuals clinically diagnosed with dementia due to Alzheimer's disease. Agitation (absence/presence) at Visit 5, the primary outcome, was based on the Neuropsychiatric Inventory agitation/aggression subscale, or a composite score comprising the total number of agitation/aggression, irritability, disinhibition and aberrant motor behaviour subscales present. Visit 1-5 heart rate variability measures were the log-transformed root mean square of successive differences in R-R intervals and standard deviation of normal-to-normal R-R intervals obtained from resting, supine, standard 12-lead ECGs. To aid interpretability, heart rate variability data were scaled such that model outputs were expressed for each 0.05 log-unit change in heart rate variability (which approximated to the observed difference in heart rate variability with every 5 years of age). Among 456 participants who had dementia, 120 were clinically classified to have dementia solely attributable to Alzheimer's disease. This group showed a positive relationship between heart rate variability and agitation risk in regression models, which was strongest for measures of (potentially vagally mediated) heart rate variability change over the preceding two decades. Here, a 0.05 log-unit of heart rate variability change was associated with an up to 10-fold increase in the odds of agitation and around a half-unit increase in the composite agitation score. Associations persisted after controlling for participants' cognitive status, heart rate (change), sociodemographic factors, co-morbidities and medications with autonomic effects. Further confirmatory studies, incorporating measures of emotion regulation, are needed to support heart rate variability indices as potential agitation propensity markers in Alzheimer's disease and to explore underlying mechanisms as targets for treatment development.

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

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

The connection between heart rate variability (HRV), neurological health, and cognition: A literature review

The heart and brain have bi-directional influences on each other, including autonomic regulation and hemodynamic connections. Heart rate variability (HRV) measures variation in beat-to-beat intervals. New findings about disorganized sinus rhythm (erratic rhythm, quantified as heart rate fragmentation, HRF) are discussed and suggest overestimation of autonomic activities in HRV changes, especially during aging or cardiovascular events. When excluding HRF, HRV is regulated via the central autonomic network (CAN). HRV acts as a proxy of autonomic activity and is associated with executive functions, decision-making, and emotional regulation in our health and wellbeing. Abnormal changes of HRV (e.g., decreased vagal functioning) are observed in various neurological conditions including mild cognitive impairments, dementia, mild traumatic brain injury, migraine, COVID-19, stroke, epilepsy, and psychological conditions (e.g., anxiety, stress, and schizophrenia). Efforts are needed to improve the dynamic and intriguing heart-brain interactions.

Hypertension and hyperhomocysteinemia as modifiable risk factors for Alzheimer's disease and dementia: New evidence, potential therapeutic strategies, and biomarkers

This review summarizes recent evidence on how mid-life hypertension, hyperhomocysteinemia (HHcy) and blood pressure variability, as well as late-life hypotension, exacerbate Alzheimer's disease (AD) and dementia risk. Intriguingly, HHcy also increases the risk for hypertension, revealing the importance of understanding the relationship between comorbid cardiovascular risk factors. Hypertension-induced dementia presents more evidently in women, highlighting the relevance of sex differences in the impact of cardiovascular risk. We summarize each major antihypertensive drug class's effects on cognitive impairment and AD pathology, revealing how carbonic anhydrase inhibitors, diuretics modulating cerebral blood flow, have recently gained preclinical evidence as promising treatment against AD. We also report novel vascular biomarkers for AD and dementia risk, highlighting those associated with hypertension and HHcy. Importantly, we propose that future studies should consider hypertension and HHcy as potential contributors to cognitive impairment, and that uncovering the underlying molecular mechanisms and biomarkers would aid in the identification of preventive strategies.

Associations of resting heart rate with incident dementia, cognition, and brain structure: a prospective cohort study of UK biobank

BACKGROUND

Resting heart rate (RHR) has been linked with an increased risk of dementia. However, evidence characterizing the associations of RHR with different dementia subtypes and their underlying mechanisms remains scarce. This study aims to investigate the relationships of RHR with different dementia types, cognitive function, and brain structural abnormalities.

METHODS

Three hundred thirty-nine thousand nine hundred one participants with no prior diagnosis of dementia from the UK biobank were analyzed. Cox regression and restricted cubic spline models examined the associations between RHR with all-cause dementia (ACD) and its major subtypes-Alzheimer's disease (AD) and vascular dementia (VaD). Logistic regression models assessed the associations of RHR with cognitive function, and linear regression models estimated the associations with hippocampal subfield volume and white matter tract integrity indexed by magnetic resonance imaging data.

RESULTS

During an average of 3148 (± 941.08) days of follow-up, 4177 individuals were diagnosed with dementia, including 2354 AD and 989 VaD cases. RHR ≥ 80bpm was associated with ACD (HR: 1.18, 95% CI: 1.08-1.28, P < 0.001) and VaD (HR: 1.29, 95% CI: 1.08-1.54, P = 0.005) but not AD in multi-adjusted models. A 10-bpm increment of RHR demonstrated non-linear effects in VaD, consisting of J-shape relationships. Several heterogeneities were indicated in stratified analysis, in which RHR measures only showed associations with dementia incidents in relatively younger populations (age ≤ 65) and females. Apart from dementia analysis, elevated RHR was associated with worsening performance in fluid intelligence and reaction time of cognitive tasks, decreased hippocampal subfields volume, and poor white matter tract integrity.

CONCLUSIONS

RHR is associated with increased risks of ACD and VaD but also presented with few heterogeneities across different sex and age groups. Elevated RHR also appears to have deleterious effects on cognitive function and is distinctively associated with volume reduction in hippocampal subfields and impaired white matter tract integrity.

Migraine, Cognitive Decline, and Dementia in Older Adults: A Population-Based Study

Background: The potential impact of migraine on cognitive aging among older adults remains controversial. Objective: To examine the relationship of migraine and subtypes with cognitive decline and dementia in an older Swedish population. Methods: This population-based study included 3069 participants (age≥60) from the Swedish National study on Aging and Care in Kungsholmen, Stockholm. Baseline examination was conducted in 2001–2004, and participants were followed every 3 or 6 years until 2013–2016. Data were collected through face-to-face interviews, clinical examinations, laboratory tests, and linkage with registers. Global cognitive function was measured with the Mini-Mental State Examination (MMSE). Dementia was diagnosed according to the DSM-IV criteria. Migraine and subtypes were defined following the international classification system. Data were analyzed using logistic regression, Cox regression, and linear mixed-effects models. Results: At baseline, 305 participants were defined with non-migraine headache and 352 with migraine. The cross-sectional analysis showed that the multivariable-adjusted odds ratio (95% confidence interval) of prevalent dementia was 0.49 (0.20–1.21) for migraine and 0.66 (0.26–1.66) for migraine without aura. The longitudinal analysis showed that the multivariable-adjusted hazard ratios of incident dementia associated with migraine and subtypes ranged 0.68–0.89 (p > 0.05). Furthermore, migraine and subtypes were not significantly associated with either baseline MMSE score or MMSE changes during follow-ups (p > 0.05). The nonsignificant associations did not vary substantially by age, APOE ɛ4 allele, cerebrovascular disease, and antimigraine treatment (p for interactions > 0.05). Conclusion: This study shows no evidence supporting the associations of migraine and its subtypes with cognitive decline and dementia among older adults.

Heart rate variability and cognitive performance in adults with cardiovascular risk

BACKGROUND

Heart rate variability (HRV), a measure of autonomic function, has been associated with both cardiovascular disease and cognitive dysfunction. In turn, cardiovascular risk has been linked to an increased risk of dementia onset. However, whether autonomic dysfunction may represent an early marker of cognitive decline in individuals with high cardiovascular risk is still an open issue.

METHODS

We performed a complete 24-hour HRV analysis in 50 middle-aged and elderly subjects with cardiovascular risk as assessed with the European Society of Cardiology Systematic Coronary Risk Evaluation (ESC SCORE). Cognitive performance was evaluated by Montreal Cognitive Assessment (MoCA), Free and Cued Selective Reminding Test (FCSRT) and Stroop Color and Word Test. Stepwise regression was used to identify significant associations between 24-hour ambulatory ECGs parameters and cognitive performances.

RESULTS

There were 30 women and 20 men with mean age of 64.9 years (range 51-77) and the mean ESC SCORE was 6%. Four subjects were diagnosed with mild cognitive impairment. Associations were found between measures of HRV and measures of cognition. Ultra-low frequency (ULF) band power of HRV significantly correlated with MoCA (r = 0.424, p = 0.003), also after adjustment for demographics and education. A significant association was also found between the ESC SCORE and ULF band power (r = -0.470, p = 0.0009).

CONCLUSIONS

Ultra-low frequency band power of HRV is associated with cognitive performance of middle-aged and elderly subjects with cardiovascular risk. This finding may indicate that autonomic nervous system dysregulation plays a role in developing cardiovascular risk and cognitive decline.

Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations

Alzheimer's Disease (AD) is a neurodegenerative disorder that is still not fully understood. Sex modifies AD vulnerability, but the reasons for this are largely unknown. We utilize two independent electronic medical record (EMR) systems across 44,288 patients to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations in AD. Embeddings and network representation of patient diagnoses demonstrate greater comorbidity interactions in AD in comparison to matched controls. Enrichment analysis identifies multiple known and new diagnostic, medication, and lab result associations across the whole cohort and in a sex-stratified analysis. With this data-driven method of phenotyping, we can represent AD complexity and generate hypotheses of clinical factors that can be followed-up for further diagnostic and predictive analyses, mechanistic understanding, or drug repurposing and therapeutic approaches.