Secondary Prevention of Dementia: Combining Risk Factors and Scalable Screening Technology

Modifiable dementia risk factors associated with objective and subjective cognition

INTRODUCTION

Early detection of both objective and subjective cognitive impairment is important. Subjective complaints in healthy individuals can precede objective deficits. However, the differential associations of objective and subjective cognition with modifiable dementia risk factors are unclear.

METHODS

We gathered a large cross-sectional sample (N = 3327, age 18 to 84) via a smartphone app and quantified the associations of 13 risk factors with subjective memory problems and three objective measures of executive function (visual working memory, cognitive flexibility, model-based planning).

RESULTS

Depression, socioeconomic status, hearing handicap, loneliness, education, smoking, tinnitus, little exercise, small social network, stroke, diabetes, and hypertension were all associated with impairments in at least one cognitive measure. Subjective memory had the strongest link to most factors; these associations persisted after controlling for depression. Age mostly did not moderate these associations.

DISCUSSION

Subjective cognition was more sensitive to self-report risk factors than objective cognition. Smartphones could facilitate detecting the earliest cognitive impairments.

HIGHLIGHTS

Smartphone assessments of cognition were sensitive to dementia risk factors. Subjective cognition had stronger links to most factors than did objective cognition. These associations were not fully explained by depression. These associations were largely consistent across the lifespan.

Emerging Technologies for Preventing the 'New' Dementia: Ambiguous Optimism in the Canadian Context

Experts' views on the use of mostly digital technologies for dementia prevention are characterized by a simultaneity of "gerontechnological optimism" and skeptical hesitancy. Despite the hope for progress in dementia prevention through preventive technologies, experts also point to the complexity of prevention, the importance of environmental factors and public health policies, and the danger of an excessive focus on individual interventions. Without questioning the positive impact such technologies can have on many people, we claim that the experts' ambiguity reveals a deeper concern, a kind of "cruel optimism" that is based on a fantasy of "supported autonomy".

Long-term risk of cardiovascular disease after traumatic brain injury: screening and prevention

Traumatic brain injury (TBI) is highly prevalent among individuals participating in contact sports, military personnel, and in the general population. Although it is well known that brain injury can cause neurological and psychiatric complications, evidence from studies on individuals exposed to a single or repetitive brain injuries suggests an understudied association between TBI and the risk of developing chronic cardiovascular diseases and risk factors for cardiovascular disease. Several studies have shown that people without pre-existing comorbidities who sustain a TBI have a significantly higher risk of developing chronic cardiovascular disease, than people without TBI. Similar observations made in military and professional American-style football cohorts suggest causal pathways through which modifiable cardiovascular risk factors might mediate the relationship between brain injury and chronic neurological diseases. A better understanding of cardiovascular disease risk after TBI combined with a proactive, targeted screening programme might mitigate long-term morbidity and mortality in individuals with TBI, and improve their quality of life.

Understanding Barriers to the Collection of Mobile and Wearable Device Data to Monitor Health and Cognition in Older Adults: A Scoping Review

Advances in technology have made continuous/remote monitoring of digital health data possible, which can enable the early detection and treatment of age-related cognitive and health declines. Using Arksey and O'Malley's methodology, this scoping review evaluated potential barriers to the collection of mobile and wearable device data to monitor health and cognitive status in older adults with and without mild cognitive impairment (MCI). Selected articles were US based and focused on experienced or perceived barriers to the collection of mobile and wearable device data by adults 55 years of age or older. Fourteen articles met the study's inclusion criteria. Identified themes included barriers related to usability, users' prior experiences with health technologies, first and second level digital divide, aesthetics, comfort, adherence, and attitudinal barriers. Addressing these barriers will be crucial for effective digital data-collection among older adults to achieve goals of improving quality of life and reducing care costs.

Insulin resistance, age and depression's impact on cognition in middle-aged adults from the PREVENT cohort

BACKGROUND

Alzheimer's disease (AD), type 2 diabetes mellitus (characterised by insulin resistance) and depression are significant challenges facing public health. Research has demonstrated common comorbidities among these three conditions, typically focusing on two of them at a time.

OBJECTIVE

The goal of this study, however, was to assess the inter-relationships between the three conditions, focusing on mid-life (defined as age 40-59) risk before the emergence of dementia caused by AD.

METHODS

In the current study, we used cross-sectional data from 665 participants from the cohort study, PREVENT.

FINDINGS

Using structural equation modelling, we showed that (1) insulin resistance predicts executive dysfunction in older but not younger adults in mid-life, that (2) insulin resistance predicts self-reported depression in both older and younger middle-aged adults and that (3) depression predicts deficits in visuospatial memory in older but not younger adults in mid-life.

CONCLUSIONS

Together, we demonstrate the inter-relations between three common non-communicable diseases in middle-aged adults.

CLINICAL IMPLICATIONS

We emphasise the need for combined interventions and the use of resources to help adults in mid-life to modify risk factors for cognitive impairment, such as depression and diabetes.

Effect of β-amyloid on blood-brain barrier properties and function

The deposition of beta-amyloid (Aβ) aggregates in the brain, accompanied by impaired cognitive function, is a characteristic feature of Alzheimer's disease (AD). An important role in this process is played by vascular disorders, in particular, a disturbance of the blood-brain barrier (BBB). The BBB controls the entry of Aβ from plasma to the brain via the receptor for advanced glycation end products (RAGE) and the removal of brain-derived Aβ via the low-density lipoprotein receptor-related protein (LRP1). The balance between the input of Aβ to the brain from the periphery and its output is disturbed during AD. Aβ changes the redox-status of BBB cells, which in turn changes the functioning of mitochondria and disrupts the barrier function of endothelial cells by affecting tight junction proteins. Aβ oligomers have the greatest toxic effect on BBB cells, and oligomers are most rapidly transferred by transcytosis from the brain side of the BBB to the blood side. Both the cytotoxic effect of Aβ and the impairment of barrier function are partly due to the interaction of Aβ monomers and oligomers with membrane-bound RAGE. AD therapies based on the disruption of this interaction or the creation of decoys for Aβ are being developed. The question of the transfer of various Aβ isoforms through the BBB is important, since it can influence the development of AD. It is shown that the rate of input of Aβ40 and Aβ42 from the blood into the brain is different. The actual question of the transfer of pathogenic Aβ isoforms with post-translational modifications or mutations through the BBB still remains open.

Urinary proteome profiles associated with cognitive decline in community elderly residents—A pilot study

Non-invasive and simple methods enabling easy identification of individuals at high risk of cognitive decline are needed as preventive measures against dementia. This pilot study aimed to explore protein biomarkers that can predict cognitive decline using urine, which can be collected non-invasively. Study subjects were selected from participants in a cohort study of middle-aged and older community-dwelling adults who underwent cognitive testing using the Mini-Mental State Examination and provided spot urine samples at two time points with an interval of approximately 5 years. Seven participants whose cognitive function declined 4 or more points from baseline (Group D) and 7 sex- and age-matched participants whose cognitive function remained within the normal range during the same period (Group M) were selected. Urinary proteomics using mass spectrometry was performed and discriminant models were created using orthogonal partial least squares-discriminant analysis (OPLS-DA). OPLS-DA yielded two models that significantly discriminated between the two groups at baseline and follow-up. Both models had ORM1, ORM2, and SERPINA3 in common. A further OPLS-DA model using baseline ORM1, ORM2, and SERPINA3 data showed similar predictive performance for data at follow-up as it did for baseline data (sensitivity: 0.85, specificity: 0.85), with the receiver operating characteristic curve analysis yielding an area under the curve of 0.878. This prospective study demonstrated the potential for using urine to identify biomarkers of cognitive decline.

Neurodegenerative disease of the brain: a survey of interdisciplinary approaches

Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.