Cognitive Resilience in Brain Health and Dementia Research

Abstract

With the expected rise in Alzheimer’s disease and related dementias (ADRD) in the coming decades due to the aging population and a lack of effective disease-modifying treatments, there is a need for preventive strategies that may tap into resilience parameters. A wide array of resilience strategies has been proposed including genetics, socioeconomic status, lifestyle modifications, behavioral changes, and management of comorbid disease. These different strategies can be broadly classified as distinguishing between modifiable and non-modifiable risk factors, some of which can be quantified so that their clinical intervention can be effectively accomplished. A clear shift in research focus from dementia risk to addressing disease resistance and resilience is emerging that has provided new potential therapeutic targets. Here we review and summarize the latest investigations of resilience mechanisms and methods of quantifying resilience for clinical research. These approaches include identifying genetic variants that may help identify novel pathways (e.g., lipid metabolism, cellular trafficking, synaptic function, inflammation) for therapeutic treatments and biomarkers for use in a precision medicine-like regimen. In addition, innovative structural and molecular neuroimaging analyses may assist in detecting and quantifying pathological changes well before the onset of clinical symptoms setting up the possibility of primary and secondary prevention trials. Lastly, we summarize recent studies demonstrating the study of resilience in caregivers of persons living with dementia may have direct and indirect impact on the quality of care and patient outcomes.

With the US population living longer with a greater life expectancy, the number of cases of Alzheimer’s disease and related dementias (ADRD) are expected to increase, roughly doubling every 20 years [1, 2]. While many older adults subjectively report changes in cognitive functioning as they age, some of these individuals will go on to develop objective cognitive decline first as mild cognitive impairment (MCI) and then ADRD when progressively declining cognitive performance interferes with everyday functioning. However, the risk, extent, degree, and progression of cognitive decline varies widely among individuals, leading to the fundamental question of why some individuals develop ADRD and other individuals, even those with similar risk factors do not. This variation can be ascribed to the presence of a collection of factors that could potentially alleviate or lessen the expression in the clinical manifestation of symptoms despite the presence of underlying neurodegenerative pathology. In other words, cognitive resilience (CR) is the ability of the brain to resist the effects of pathology and preserve or maintain function. CR could explain why some individuals do not appear to develop ADRD despite the presence of brain amyloid or other pathologies. It could explain why some individuals with MCI do not “convert” to ADRD or may even reverse. It could also explain why some individuals with ADRD progress more slowly than others. With the growing interest in primary, secondary, and tertiary prevention studies [3, 4], understanding CR could open new avenues of research.

Many risk factors have been associated with ADRD prevention efforts that include both modifiable (e.g., exposures, lifestyle, and social habits) and nonmodifiable (e.g., age, sex, genetics) risk factors with modifiable risk factors explaining up to 40% of the attributable risk [5]. More specifically, CR factors have been reported to include years of education, gender, social connectedness, diet, mindfulness, cognitive and physical activity [6]. Another concept frequently used to estimate resilience is the construct of cognitive reserve. It is defined as the reserve that actively compensates for AD pathology by maximizing performance through differential recruitment of brain networks. Cognitive reserve is a latent variable usually measured in some combination of education, cognitive performance, and/or occupational attainment [7-11]. Educational attainment is frequently reported as the number of years of formal schooling completed. However, the number of years of schooling may not be representative of the quality of the educational experience, and opportunities for advanced education may not be equal for all individuals. Occupational attainment may provide a more accurate measure of an individual’s practical cognitive reserve, as job opportunities and advancement may not necessarily match educational attainment [7, 8]. Other potential measures of cognitive reserve include neuropsychological testing of cognitive performance which often include an assessment of verbal IQ [9], although questions remain as to whether IQ tests have racial, ethnic and social biases [10]. To address these challenges, we created the Cognitive Reserve Unit Scale (Box 1) combining weighted scores of major occupation and educational attainment with more weight being placed on occupation [11]. The Cognitive Reserve Unit Scale provides a continuous measurement of CR that can be used for statistical analyses and comparisons across different individuals of different social, racial, ethnic, and geographic backgrounds.

Box 1. Cognitive Reserve Unit Scale (CRUS).

Other research methods to determine CR have focused on neuroimaging techniques such as magnetic resonance imaging (MRI) or positron emission tomography (PET) [12] providing quantitative measurements of cortical volume, thickness, and surface areas or measurements of amyloid or tau pathology. Another method of measuring resilience is to study the burden of pathology at autopsy in individuals with and without a prior clinical diagnosis of dementia [13, 14]. However, these extensive research methods may not be practical in all research projects and cannot be utilized in a clinical setting so that an appropriate dementia prevention and/or treatment regimen can be designed and implemented. This can include primary prevention limiting incidence of new cases, secondary prevention limiting prevalence of cases, and tertiary prevention limiting disability in existing cases. A clear understanding and definition of CR may help in preventing ADRD by modification of known risk factors, health promotion, healthful behavioral change, and management of comorbid medical conditions. In this review, we address existing measures of CR and summarize a recently described quantitative measure of resilience that can be used in multiple research and clinical settings [6].

MEASURES OF COGNITIVE RESILIENCE

To date, many measures of CR are qualitative rather than quantitative instruments, with some of the quantitative measurements relying on measurements of postmortem pathology. Stoner et al. [15] developed two methods for people with early-stage dementia; a positive psychology outcome measure and Engagement and Independence in Dementia Questionnaire, which included four themes—hope, resilience, a sense of independence, and social engagement. Both methods exhibited acceptable internal consistency and convergent validity, but the sample size used to acquire data was relatively small. Yao et al. [16] designed the AD Cognitive Resilience (AD-CR) score, which is defined as the difference between observed and expected cognition based on the AD pathology. It is a stand-alone, individual-level quantification of cognitive resilience validated by demonstrating strong associations with known factors related to CR. They also have proposed a framework for predicting whether an individual will have a high or low AD-CR score using measures collected during premortem assessments. A notable drawback of this method is that AD-CR score cannot be calculated during an individual’s lifetime since it uses postmortem pathology. Bowles et al. [17] analyzed data from well-characterized cases that came to autopsy which had intermediate to high levels of AD pathology. They reported that individuals who had a college education and/or the absence of non-AD pathology (e.g., vascular lesions, Lewy bodies) had higher resiliency. This data was supported by earlier studies demonstrating a clear link between higher education level and lower risk of dementia [18]. They assessed the data using CERAD (Consortium to Establish a Registry for Alzheimer’s Disease) score as none, sparse, moderate, or frequent. It was also observed that cognitively resilient people had higher average brain weights than those of non-resilient individuals. An apparent shortcoming of their study is that cognitively resilient people were categorized as such only after their death due to its reliance on neuropathology.

A more clinically relevant approach would be a continuous scale of resilience measurement considering processes that occur throughout aging. Hohman et al. [19] used a different approach to quantify resilience by leveraging AD biomarkers and baseline brain aging outcomes, including left hippocampal and right hippocampal volumes as primary outcome measurements from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cognitive reserve was measured using experiences like educational and occupational attainment [20]. This reserve was based on the proposal that past life experiences can enhance the brain reserve. However, there could be differences in efficiency and capacity of individuals’ cognitive networks. Positive lifestyles (diet, exercise, cognitive activity) and positive behaviors (mindfulness, optimism, self-efficacy) are examples of modifiable factors that have been shown to increase resilience [21-24]. Several studies have documented benefits of exposure to greenspaces in improved cognitive functions in older adults [25-27]. These studies are based on the hypothesis that spending time in nature in the form of greenspaces may slow the cognitive decline [28]. In a cross-sectional analysis of walkable neighborhoods, participants who are APOE ε4 carriers had worse cognition-related outcomes compared with non-carriers [29].

In a systematic review and meta-analysis, Meng and colleagues identified a positive link between mid-life vascular risk factors and significantly increased risk of AD [30]. Using a mixed random effects regression model, Li et al. demonstrated that subjects with vascular risk factors had increased AD dementia [31] and active intervention for vascular risk factors may slow the progression of cognitive decline. Negative lifestyle choices (e.g., smoking, alcohol consumption) and behaviors (e.g., depression, anxiety) are examples of modifiable factors which adversely affect cognitive resilience. In a meta-analysis of prospective cohort studies, as compared to non-smokers, current smokers showed an increased risk of all-cause dementia and there was 34% increased risk for every 20 cigarettes per day [32]. Excessive alcohol consumption (≥14 drinks per week) was associated with lower cognitive scores in older adults with and without cognitive impairment [33, 34]. A recent interesting meta-analysis shed light on the effect of binge drinking on the health of oral microbiome, which in turn enhance AD pathogenesis. The enhanced pathogenesis appears to be mediated through the blood-brain barrier leakage [35]. In a study of socio-economic impact on dementia in southern Taiwan, Liu et al. have observed that illiteracy and being female was associated with increased risk of dementia [36]. Being older and perceived insufficient income [37], age and education [38] had strong impact on dementia.

NEUROIMAGING STUDIES OF RESILIENCE

Studies conducted using the ADNI data have contributed significantly to the understanding of AD progression and contribution of resilience and immune response. Since the significance of recording continuous pathophysiological changes that occur several years prior to symptom appearance was well appreciated, imaging these changes was helpful in determining spatial and temporal ordering of biomarker changes. Insel et al. [39] estimated the trajectories of regional amyloid-β (Aβ) and tau PET uptake as a function of time, and observed Aβ deposition in the posterior cingulate cortex and precuneus 5–10 years before the onset of symptoms. Further, early tau PET uptake was noted in inferior temporal lobes, amygdala, and inferior parietal lobes. Libowitz et al. [40] demonstrated that abnormal cerebrospinal fluid (CSF) Aβ₄₂ was associated with smaller brain volumes in MRI, particularly in hippocampus and prefrontal cortex region.

Cerebrovascular diseases, manifested as white matter lesions, microinfarcts, and microhemorrhages, are increasingly believed to mediate not just vascular forms of dementia but also prominent in the brains of individuals with AD, and Lewy body dementia [41, 42]. The risk factors for cerebrovascular disease are also risk factors for ADRD, including hypertension [43, 44] and Type-2 diabetes mellitus [42]. Cerebrovascular disease and vascular risk factors may also directly affect cognition by hippocampal atrophy [45]. While neuroimaging can provide important clues to risk of ADRD and assist in differential diagnosis, at the present time there are no specific neuroimaging markers of CR.

FLUID BIOMARKER STUDIES OF RESILIENCE

Increasingly, fluid biomarkers such as Aβ₄₂, total tau (t-tau), and phosphorylated tau (p-tau) can be measured in CSF and blood to aid in developing personalized diagnosis and treatments for ADRD [46-48]. The deposition of Aβ occurs over decades but well before the symptom appearance leading to the occurrence of individuals with amyloid deposition but normal cognition known as preclinical AD [49]. What is particularly interesting is that although many individuals will eventually progress to MCI and clinical AD, not all do. This suggests that there may be resilience factors that offer protection. As amyloid levels do not appear to specify clinical dementia and several conditions (e.g., vascular dementia, Lewy body dementia) can have amyloid deposition as a comorbid pathology, ratios of t-tau/Aβ₄₂ and p-tau/Aβ₄₂ may outperform individual biomarkers in distinguishing AD from healthy controls and other forms of dementia [50]. In addition, other fluid biomarkers, particularly those that involve synaptic and intracellular processes such as SNAP-25, YKL-40, TREM-2, BACE-1, IP-10, α-synuclein, and TDP-43 may help identify ADRD (Table 1). Many of these are known to mediate inflammatory pathways, which in turn activate Aβ synthesis and tau phosphorylation [51]. Recently, Tible et al. [52] studied CSF biomarkers to differentiate between AD and non-AD disorders. Among those biomarkers, SNAP-25aa40 had maximal discriminative power and could be a potential candidate to aid in the clinical diagnosis of ADRD. Because CSF requires an invasive procedure, blood samples may offer an easier and more readily acceptable way to collect and analyze biomarkers. However, at the present time, most plasma assays are still early in the validation process. For example, tau monoclonal antibody method was developed to detect very low levels of tau present in plasma of AD patients [53]. Since then, several other groups have confirmed sensitivity of immunoassay for the plasma tau measurements [54, 55]. More recently, a blood-based biomarker combining plasma Aβ₄₀, Aβ₄₂, Apolipoprotein E (APOE) proteotypes was developed by a commercial company (C2N, St Louis, MO) to provide an amyloid prediction score to distinguish brain amyloid positive individuals from brain amyloid negative individuals. Despite these advances in fluid biomarkers, there are no markers that currently define CR.

Table 1.

Proteins postulated to participate in cognitive resilience

Protein	Chromosome	Role in resilience	Ref
α-Synuclein	4	Aggregation in neurons	[88]
ATP binding cassette transporter (ABCA1)	9	Aβ deposition	[89]
Phosphatidylinositol-binding clathrin assembly protein (PICALM)	11	Aβ clearance	[90]
Ras-related protein Rab-10 (RAB10)	2	Lipid droplet degradation	[91]
Disks large-associated protein 2 (DLGAP2)	8	Slower cognitive decline	[60]
Klotho	13	Longer lifespan	[92]
Restrictive element-1 silencing transcription factor (REST)	4	Repressor of pro-apoptotic genes	[93]
ATPase phospholipid transporting 8A (ATP8B)	18	Bile acid homeostasis	[57]
Sortillin related receptor 1 (SORL1)	11	Aβ degradation	[62]
Triggering receptor expressed on myeloid cell like 2 (TREM2)	17	Inflammation attenuation	[94]

GENETIC FACTORS ASSOCIATED WITH RESILIENCE

A large proportion (~40–50%) of cognitively normal individuals who die and come to autopsy have evidence of amyloid deposition in their brains suggesting that CR factors may come into play that offers protection from manifestation of clinical symptoms. The genetic factors contributing to the resilience to development of pathology are not well understood (Table 2). Identifying these factors may provide novel therapeutic targets for clinically treating AD and related diseases. Protective genes may function by attenuating effects of accumulating neuropathological burden, providing higher cognitive baseline, or mediating delayed onset of clinical disease. An example is the study showing presence of rare coding variants PLCG2, ABI3, and TREM 2 implicating innate immunity response observed in late onset AD [56]. Several genome wide association studies (GWAS) were conducted to identify protective or resilience genes. One of these studies [57] was performed by employing harmonized resilience metrices across cross-sectional A4 study and 3 longitudinal cohort studies of AD. They observed significant locus among participants with unimpaired cognition on the chromosome 18 upstream of ATP8B1, indicating a novel resilience gene along the bile acid metabolic pathway.

Table 2.

Genes postulated to mediate cognitive resilience

Gene	Chromosome	Role in resilience	Ref
PLCG2 (Phospholipase C Gamma 2)	16	Immune cell function	[95]
ABI3 (ABI gene family member 3)	17	Inflammation attenuation	[96]
TREM2 (triggering receptor expressed on myeloid cells-2)	17	Inflammation attenuation	[97]
Kdm6a (Lysine demethylase 6A)	X	Slower cognitive decline	[58]
SORL1 (Sortilin Related Receptor 1)	11	Aβ degradation	[98]
ABCA1 (ATP binding cassette subfamily A member 1)	9	Neutralizes Aβ aggregation	[99, 100]
KL-VS (Lifespan extending variant)	13	Slower cognitive decline	[101, 102]
BDNF (Brain derived neurotrophic factor)	11	Learning and memory	[103, 104]
DLGAP2 (Disk large-associated protein 2)	8	Slower cognitive decline	[60]
NLRP3 (NLR family pyrin domain containing 3)	1	Inflammasome	[105]
MS4A6A (Membrane Spanning 4-Domains A6A)	11	Braak plaques	[106]
RAB10 (member RAS oncogene family)	2	Lipid droplet degradation	[91]

Male patients with AD tend to exhibit more extensive cognitive deficits and may die early than women [1]. In an interesting mouse model of AD expressing the human amyloid precursor protein (hAPP), the X chromosome affects AD-related vulnerability [58]. XY-hAPP mice which were genetically modified to develop either testicles or ovaries had worse cognitive deficits and greater mortality than XX-hAPP mice. Further, mice with an X chromosome with or without a Y chromosome (e.g., XY or XO) had worse outcomes than XX mice. The observed resilience was hypothesized to be due to the candidate gene Kdm6a that resists X-linked inactivation and may attenuate Aβ neurotoxicity. Genetic variation in human Kdm6a gene was associated with less cognitive decline in aging. Seto et al. [59] provide an exhaustive review of resilient genes that focus on genes involved in lipid metabolism, synaptic function and inflammation. For example, Dlgap2 (disk large associated protein 2) is a protective candidate gene in a genetically diverse mouse model of AD [60]. DLGAP 2 protein, that is part of DLGAP 2 family, has been linked to neurological and psychiatric disorders including schizophrenia, AD, and Parkinson’s disease [61]. A variant of SORL1 (sortillin-related receptor 1) gene was found to be protective and is a receptor for APOE [62] (Table 2).

QUANTIFYING RESILIENCE IN BRAIN HEALTH AND ADRD

We recently developed a resilience index (RI) to address the need for a brief, easy to score quantifiable measure of brain health [6] based on six modifiable lifestyle factors including physical activity, cognitive activity, dietary patterns, social engagements, mindfulness, and cognitive reserve that each individually were demonstrated to have effects on cognitive performance and risk of disease. The RI demonstrated moderate-to-strong correlations with clinical and cognitive measures and provided very good discrimination between healthy controls, MCI, and ADRD. Further, within group analyses demonstrated that healthy controls, MCI, and ADRD cases with high RI had better cognitive, functional, behavioral, and global outcomes than those with low RI. Lower RI scores could be used as a guidance for referring patients for a more extensive evaluation of modifiable factors and development of a personalized prevention plan. While the initial application was in a cross-sectional study of individuals at a tertiary academic center, a quantifiable measure of resilience could assist with the discovery and validation of imaging, fluid, and genetic biomarkers of resilience as well as providing a basis for primary, secondary, and tertiary prevention programs.

RESILIENCE IN CAREGIVERS OF PEOPLE LIVING WITH DEMENTIA

With the expected increase in number of people with dementia in the coming decades, there will be corresponding increased demand for caregivers. Secondly, with the progressive worsening of disease, the person is more dependent on the assistance of caregiver and thus the caregiver may undergo increased stress and decline in their mental health. The caregiving activities may include assistance with chores of daily living, medical care, transportation, management of behaviors, and concerns related to cognitive decline. They have reported high levels of stress, depression, and experiencing significantly increased suicidal thoughts. These ill effects on caregivers may in turn negatively impact the quality of care for individuals living with dementia. However, not all caregivers are impacted to the same level by the ill effects of caregiving, and not all aspects of caregiving are perceived as negative. Caregivers can report positive feelings about caregiving (e.g., family togetherness and the satisfaction of helping others). Other perceived benefits associated with caregiving may include the opportunity to give back; improved relationships; feeling good about the quality of care; serving as a role model for others; increased self-esteem; an enhanced sense of purpose; and feelings of pleasure and satisfaction. Individuals with higher positive views of caregiving may report less burden and depression. We created the positive and negative appraisals of caregiving (PANAC) scale to better understand the caregiving experience [63]. Of note, caregivers with more positive appraisals had higher resilience including mindfulness and social engagement. Therefore, it is important to document their CR with systematic quantitative measurement of its parameters not just for their own brain health but also to potentially impact the cognitive health of the individuals they care for. The significance of quantifying CR is appreciated considering existing tools based on self-reported outcomes from caregivers, that could be influenced by depression, caregiver strain or burden, of reduced quality of life. The outcomes of these systematic resilience studies will help in developing intervention strategies so that caregivers are more effective in providing care for people living with MCI and ADRD.

Diest and Greef [64] conducted a caregiver study in which adult children were caring for a parent with dementia. It used a cross-sectional survey research design and analyzed both quantitative and qualitative data. The quantitative data were acquired using Family Attachment Changeability Index (FACI8). The family adaptations as an indicator of resilience were optimal in those families receiving community support. In addition, financial stability had a positive impact on family adaptation. Most participants identified factors that promoted family connectedness for a sustained resilience.

Several studies, using qualitative analysis, have focused on CR domains that are beneficial to caregivers, namely personal mastery, self-efficacy, and coping. These resilience domains had direct effect on the physical health outcomes with beneficial effects on biomarkers and clinical markers of disease including blood pressure. For example, in a sample of 100 spousal AD caregivers [65] higher levels of self-efficacy were associated with significantly lower mean arterial pressure. Another study [66] examined the protective effects of personal mastery on the relationship between stress and plasma levels of Plasminogen activator inhibitor-1 (PAI-1), which is implicated in development of cardiovascular disease. The data analysis showed that when the mastery was low, the stress was markedly related to PAI-1 levels in in-home spousal caregivers of AD patients.

Recently, Zhou et al. [67] have proposed a comprehensive framework for promoting CR in caregivers as part of intervention, based on prior qualitative and quantitative studies by other investigators. The framework focuses on strengths rather than hardships and burden faced by caregivers. They have carried out thematic analysis and proposed 4 domains as part of the framework: 1) problem response behaviors; 2) self-growth behaviors; 3) help related behaviors; and 4) learning related behaviors. The framework provides an insight into how dementia caregivers learn and develop resilience related behaviors. However, there is a clear gap in the studies that acquire and analyze physiological parameters like, blood pressure, immunity, heart rate, cortisol, and gene expression profiles. Han et al. [68] using resilience framework have attempted to identify challenges and resilience opportunities in a group of caregivers for hospice patients with dementia. The study identified unique challenges including difficulty in treatment decision making, prolonged caregiving burden, death with dignity, and lack of public awareness. Resilience parameters identified were self-control and appraisal, self-care, using visual materials, and option to choose good care facilities. The authors anticipate their findings help in design of supportive interventions for caregivers or families caring for hospice patients with ADRD.

PROMOTING AND ENHANCING RESILIENCE

With limited availability of treatments for dementia, prevention studies have gained importance in recent years. A diverse array of interventions—mindfulness, performing arts, and nutrition—are being proposed and tested in both persons living with dementia and family caregivers with most focusing on potentially modifiable CR factors. Several studies document the benefits of mindfulness-based exercises. It is a skill that could be developed at any age with a minimal training regimen. An 8-week Mindfulness-Based Stress Reduction training was provided to 7 dyads (an early-stage dementia patient and caregiver) [69]. The analyzed data showed a noticeable increase in quality of life for caregivers and all participants exhibited large increases in mindfulness. Another review of mind-body interventions such as mindfulness, Tai Chi, and Qigong, in MCI [70] showed improved cognitive function, reduction in depression and lowered dementia risk in older adults. Multi-modal performing arts intervention in caregivers of mild to moderately severe dementia patients [71] demonstrated significant decline in burden. However, the benefits declined at the end of the study showing the need for continued participation in the intervention program.

Modifiable risk factors play a vital role in prevention of dementia. Dietary modification is one such risk factor that may facilitate lowering the dementia. Accumulating evidence from both observational and clinical trials point to a protective association between certain nutrients or food groups and cognitive outcomes. Benefits were observed with B vitamins [72], antioxidants [73], curcumin [74], food groups such as seafood [75], fruits and vegetables [76], and nuts [77]. A literature review [78] was conducted of elevated plasma homocysteine as a risk factor for development of cognitive decline, dementia, and AD. Intervention in a trial using homocysteine lowering treatment with B vitamins markedly slowed the cognitive decline. Regular physical activity and exercise may serve as non-pharmacological intervention in dementia and AD. In several studies, physical exercise enhanced resilience in people with dementia [79-81]. A combined exercise and cognitive training system were effective in enhancing concentration and improving cognitive function in 100 dementia patients [82].

In recent years, many systematic trials are being undertaken to study the effectiveness of preventive measures for cognitive impairment and disability. An example is the FINGER study (Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability), which is a multicenter randomized clinical trial comprising of 1200 independently living persons in Finland [83]. The intervention comprised of 4 components: 1) nutritional guidance; 2) physical exercise; 3) cognitive training and social activity; and 4) intensive monitoring and management of metabolic and cardiovascular risk factors. After 2 years, significant intervention effects were observed on the primary outcome (overall cognition), main cognitive secondary outcomes (executive functioning and processing speed) [84]. Their findings suggested a multidomain intervention may improve cognitive functioning in at-risk older population. The encouraging data from the FINGER study has prompted the launching of worldwide FINGERS network (WW-FINGERS), a consortium of 25 countries, which is the global network of multidomain lifestyle intervention trials for dementia risk reduction and prevention [85]. This ambitious undertaking may facilitate adaptation of the interventions globally and establish opportunities for joint initiatives. It aims to test initially whether FINGER-based protocols are feasible and effective in various populations with diverse cultural contexts. The study is based on the premise that interventions targeting several risk factors simultaneously may provide optimal outcomes in preventing ADRD. Another trial called US POINTER (The US Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk) is a multisite randomized clinical trial designed to evaluate whether different lifestyle interventions protect cognitive function over a 2-year period in older adults at increased risk for cognitive impairment and dementia [86]. The study is designed to follow a global composite score that will allow harmonization with FINGER study and its associated trials through WW-FINGERS. An ancillary study, The POINTER Imaging, was initiated [87] where participants undergo PET imaging to measure Aβ and tau burden, and MRI to measure brain morphometry, white matter hyperintensities, and microstructure and cerebral blood flow. The outcomes from these exhaustive intervention trials are still awaited.

CONCLUDING COMMENTS

There are several avenues available to measure CR in older adults including genetic data, neuroimaging, biomarkers, and clinical tools (i.e., Resilience Index) that can used in clinical research and potentially in clinical practice. While each of these tools provides a “different peek into a different window”, combining these different instruments may afford a unique opportunity to study CR and design prevention studies. This review described an array of factors that may positively and negatively influence cognitive resilience (Fig. 1). Many resilience parameters are quantifiable and can be used in a clinical setting so that clinicians can develop personalized dementia prevention regimens to support brain health. An abundance of research in the coming years—delineating modifiable and nonmodifiable factors—may pave the way for effective strategies addressing ever increasing need for ADRD treatment and prevention.

Fig. 1.

Factors with positive and negative impact on cognitive resilience. The positive factors include cognitive reserve (education and occupation), positive lifestyles (diet, exercise, and cognitive activity), positive behaviors (mindfulness, optimism, and self-sufficiency), genetics (kdm6a, TREM2), greenspace (early and mid-life exposure to natural greenery), and socio-demographics (younger and high income). The negative factors are vascular risk factors (hypertension, diabetes, and obesity), negative lifestyles (head injury, smoking, and alcohol consumption), negative behaviors (depression and anxiety), genetics (MS4A6A, BDNF), co-morbidities (multiple medical conditions), and socio-demographics (low income, old age, racial/ethnic differences).