Predictors Of Mild Cognitive Impairment Research Articles

Risk of Alzheimer's disease is associated with longitudinal changes in plasma biomarkers in the multi-ethnic Washington Heights-Hamilton Heights-Inwood Columbia Aging Project (WHICAP) cohort.

Alzheimer's disease (AD) biomarkers can help differentiate cognitively unimpaired (CU) individuals from mild cognitive impairment (MCI) and dementia. The role of AD biomarkers in predicting cognitive impairment and AD needs examination. In 628 CU individuals from a multi-ethnic cohort, amyloid beta (Aβ)42, Aβ40, phosphorylated tau-181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were measured in plasma. Higher baseline levels of p-tau181/Aβ42 ratio were associated with an increased risk of incident dementia. A biomarker pattern (with elevated Aβ42/Aβ40 but low p-tau181/Aβ42) was associated with decreased dementia risk. Compared to CU, participants who developed MCI or dementia had a rapid decrease in this protective biomarker pattern reflecting AD-specific pathological change. Elevated levels of AD biomarker p-tau181/Aβ42, by itself or combined with a low Aβ42/Aβ40 level, predicts clinically diagnosed AD. Individuals with a rapid change in these biomarkers may need close monitoring for the potential downward trajectory of cognition. We discuss a multi-ethnic, urban community study of elderly individuals. The study consisted of a longitudinal assessment over 6 years with repeated clinical assessments. The study used blood-based biomarkers as predictors of mild cognitive impairment and Alzheimer's disease.

Predictors of Mild Cognitive Impairment in a Hypertensive Population

Predictors of Mild Cognitive Impairment in a Hypertensive Population

Neurobiological mechanisms involved in the relationship between loneliness, depression, and cognitive decline in older adults

AbstractBackgroundLoneliness among older adults is one of the risk factors for developing dementia. Yet, little is known about the neurobiological and psychological conditions that link loneliness to cognitive decline. The current study had several aims: First, it sought to determine whether the relationship between loneliness and cognitive decline is sex‐specific in older adults. Second, it sought to identify neurobiological and psychological pathways that may account for the relationship between loneliness and decline across several cognitive domains. These pathways included depressive symptoms, gray matter volume, and conditional analyses of pro‐inflammatory cytokines and brain‐derived neurotrophic factor (BDNF) expression. Third, it examined loneliness as a predictor of mild cognitive impairment (MCI) and Alzheimer’s disease (AD).MethodLongitudinal data were collected from 2130 Rush Memory and Aging Project MAP participants. Participants underwent annual cognitive and psychological assessments and neuroimaging procedures. BDNF gene expression was measured in the dorsolateral prefrontal cortex, and the final clinical diagnosis was identified upon autopsy at death. Cytokines were measured in serum. Linear mixed models and multinomial logistic regression analyses were used. All models controlled for age at baseline, education, and sex.ResultParticipants were largely women (73%), and Caucasian (93%). The average age at baseline was 80.05 (SD = 7.57) and education was 14.93 (SD = 3.34). Results showed that gray matter volume and depressive symptoms partially mediated the relationship between loneliness and cognitive decline. BDNF expression was positively related to cognitive performance, and its interaction with loneliness was related to slower cognitive decline in semantic memory and better visuospatial performance. Finally, the current study also established that loneliness was a predictor of the incidence of AD and other dementias.ConclusionThe present findings suggest that loneliness may elicit physiological changes in our brains that lead to cognitive decline over time. Future research can explore a wide range of biological and psychological expressions of loneliness to clarify how loneliness relates to dementia.

Psychological and neurobiological mechanisms involved in the relationship between loneliness and cognitive decline in older adults

Loneliness, among older adults, is one of the risk factors for developing dementia. Still, little is known about the neurobiological and psychological conditions that link loneliness to cognitive decline. The current study investigated several research aims: First, it sought to identify neurobiological and psychological pathways that may account for the relationship between loneliness and decline across several cognitive domains. These pathways included depressive symptoms, total gray matter volume, and conditional analyses of pro-inflammatory cytokines and brain-derived neurotrophic factor (BDNF) expression. Second, it examined loneliness as a predictor of mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Third, it sought to determine whether the relationship between loneliness and cognitive decline is sex-specific in older adults. Longitudinal data were collected from 2130 Rush Memory and Aging Project participants. Participants underwent annual cognitive and psychological assessments and neuroimaging procedures every year. BDNF gene expression was measured in the dorsolateral prefrontal cortex, cytokines were measured in serum, and the final consensus clinical diagnosis was identified at the time of death. All linear mixed and multinomial logistic regression models controlled for age at baseline, education, sex, and APOE genotype. Participants were largely women (73 %), and Caucasian (93 %). The average education was 14.93 (SD = 3.34). The average age at baseline was 80.05 (SD = 7.57). Results showed that gray matter volume and depressive symptoms partially mediated the relationship between loneliness and cognitive decline. There was a significant interaction between loneliness and BDNF expression in relation to cognitive decline. Higher levels of BDNF expression was associated with slower decline in semantic memory and visuospatial ability. Finally, the current study also established that higher levels of loneliness was positively associated with the incidence of AD and other dementias. The present findings support the growing literature, which tends to show that the consequence of loneliness goes beyond the feeling of being isolated. Loneliness may induce physiological changes in our brains, leading to cognitive decline. Future research can explore a wide range of biological and psychological expressions of loneliness to clarify how loneliness relates to dementia.

A - 19 Cognitive Test Score Dispersion VS. Traditional Memory Composite Scores: Predicting Mild Cognitive Impairment (MCI) & Dementia among Cognitively Impaired, Not MCI Patients.

To compare mild cognitive impairment (MCI) and dementia conversion rates between global neuropsychological dispersion (GD) and traditional memory neuropsychological composite score (MComp) in participants with baseline evidence of cognitive decline but no diagnosis of MCI or dementia. Data from the National Alzheimer's Coordinating Center (NACC) for 364 participants with a CDR of 0.5, no initial diagnosis of MCI or dementia, and five visits were analyzed. GD was the intraindividual standard deviation across baseline normative (NACC norms) neuropsychological performance. MComp was the mean of the four verbal and visual memory normed scores. Multinomial logistic regression models fit statistics compared GD and MComp as predictors of conversion to MCI/dementia, adjusting for age, sex, race, ethnicity, ApoE4 status, and stratified by suspected etiology (Alzheimer's disease [ad] or no-ad). Lower Akaike Information Criteria (AIC) values indicate better model fit and predictions. 37% progressed to MCI, and 47% to dementia by visit 5. 53% of these were suspected to have ad etiology, and 47% non-ad. MComp showed a better fit with significant predictions of MCI and dementia progression in both suspected ad (AIC: 351.77, p < 0.001) or non-ad etiology (AIC: 215.02, p < 0.004), versus GD was only significant for non-ad etiology (AIC: 385.74, p < 0.003). Better memory performance predicted a lower likelihood of conversion to non-ad MCI (B = -0.65, p = 0.003) and non-ad dementia (B = -1.33, p < 0.001). GD predicted eventual progression to non-ad dementia (B = 2.311, p = 0.004), but not non-ad MCI. Traditional memory composite score may be a better predictor of MCI and dementia conversion than cognitive dispersion in individuals with early cognitive decline who do not yet meet MCI criteria.

A - 05 Insight and Anxiety Ratings as Predictors of Mild Cognitive Impairment and Dementia.

Insight has been investigated as a predictor of mood symptoms and psychosis onset. Little research has examined insight as a predictor of diagnosis, especially given possible confounding factors such as anxiety. This cross-sectional study included 223 adult patients diagnosed with Mild Cognitive Impairment (MCI) or Dementia as a result of outpatient neuropsychological evaluation. Patients completed either the Depression Anxiety Stress Scale (DASS-42) or the Beck Anxiety Inventory (BAI) and the Behavioral Dyscontrol Scale (BDS-II). Participants were divided into four groups (MCI, Dementia, MCI + Anxiety, or Dementia+Anxiety) utilizing DASS-42 anxiety scale ≥7, or BAI score ≥ 7 (clinical anxiety). Insight grouping (four categories: 0 [no insight] to 3 [intact insight]) was determined by the BDS-II clinician-based insight rating. Diagnosis and insight groups were compared using one-way ANOVAs. Predictive value of BDS-II insight scores was determined by logistic regression. The sample was 52.9% male and 87.9% non-Hispanic White, with mean age 75.54 (SD = 8.24) and education 16.1years (SD = 2.9). There was a significant difference between diagnoses and insight levels for the four conditions [F(3, 219) = 6.06, p < 0.001]. The logistic regression model was significant [χ2(9, N = 223) = 25.79, p < 0.01]. The model explained 11.9% of the variance in diagnosis and correctly identified 47.1% of the cases. Insight appears to affect the diagnostic outcomes in cases of MCI and dementia. Clinicians should consider insight ratings, along with clinical history, behavioral observations, and test findings when evaluating possible MCI and dementia. Future research should examine neurocognitive disorder subtypes to identify those most affected by reduced insight.

Receded near point of convergence as a predictor of mild cognitive impairment in the general geriatric population: results from a population-based study.

To investigate the relationship between near point of convergence (NPC) and mild cognitive impairment (MCI) in the general elderly population. The present report is a part of the Tehran Geriatric Eye Study (TGES): a population-based cross-sectional study conducted on individuals 60 years of age and above living in Tehran, Iran using the multi-stage stratified random cluster sampling method. Cognitive status was assessed using the Persian version of the Mini-Mental State Examination (MMSE). All study participants underwent complete ocular examination including measurement of uncorrected and best-corrected visual acuity, objective and subjective refraction, cover testing, NPC measurement, and slit-lamp biomicroscopy. The data of 1190 individuals were analyzed for this report. The mean age of the participants analyzed was 66.82±5.42 (60-92y) and 728 (61.2%) of them were female. Patients with MCI had a significantly more receded NPC compared to subjects with normal cognitive status (10.89±3.58 vs 7.76±2.71 cm, P<0.001). In the multivariable logistic regression model and in the presence of confounding variables, a receded NPC was statistically significantly associated with an increased risk of MCI (odds ratio: 1.334, 95% confidence interval: 1.263 to 1.410, P<0.001). According to receiver operating characteristic (ROC) analysis, a cut point NPC> 8.5 cm (area under the curve: 0.764, P<0.001) could predict the presence of MCI with a sensitivity and specificity of 70.9% and 69.5%, respectively. A receded NPC can be clinically proposed as a predictor of MCI in older adults. It is recommended that elderly with a receded NPC>8.50 cm undergo detailed cognitive screening for a definite diagnosis of MCI. In this case, the necessary interventions can be carried out to slow down MCI progression to dementia.

Blood and cerebrospinal fluid biomarker changes in patients with HIV-associated neurocognitive impairment treated with lithium: analysis from a randomised placebo-controlled trial

HIV-associated neurocognitive disorders (HAND) persist in the era of antiretroviral therapy (ART). Thus, ART does not completely halt or reverse the pathological processes behind HAND. Adjuvant mitigating treatments are, therefore, prudent. Lithium treatment is known to promote neuronal brain–derived neurotrophic factors (BDNF). Lithium is also an inhibitor of glycogen synthase kinase-3 beta (GSK-3-β). We analyzed biomarkers obtained from participants in a randomized placebo-controlled trial of lithium in ART-treated individuals with moderate or severe HAND. We assayed markers at baseline and 24 weeks across several pathways hypothesized to be affected by HIV, inflammation, or degeneration. Investigated biomarkers included dopamine, BDNF, neurofilament light chain, and CD8 + lymphocyte activation (CD38 + HLADR +). Alzheimer’s Disease (AD) biomarkers included soluble amyloid precursor protein alpha and beta (sAPPα/β), Aβ38, 40, 42, and ten other biomarkers validated as predictors of mild cognitive impairment and progression in previous studies. These include apolipoprotein C3, pre-albumin, α1-acid glycoprotein, α1-antitrypsin, PEDF, CC4, ICAM-1, RANTES, clusterin, and cystatin c. We recruited 61 participants (placebo = 31; lithium = 30). The age baseline mean was 40 (± 8.35) years and the median CD4 + T-cell count was 498 (IQR: 389–651) cells/μL. Biomarker concentrations between groups did not differ at baseline. However, both groups’ blood dopamine levels decreased significantly after 24 weeks (adj. p < 002). No other marker was significantly different between groups, and we concluded that lithium did not confer neuroprotection following 24 weeks of treatment. However, the study was limited in duration and sample size.

Association between cognition and olfaction-specific parameters in patients with chronic rhinosinusitis.

Patients with chronic rhinosinusitis (CRS) have reported significantly cognitive and olfactory dysfunction. This study aimed to explore the relationship between cognitive function and olfaction-specific parameters in patients with CRS. A cross-sectional survey method was used to investigate 98 participants, including 75 patients with CRS and 23 healthy controls. Cognitive function and psychophysical olfactory tests were performed. Olfactory cleft endoscopy scale and olfactory cleft computed tomography (CT) scores were obtained. Multivariate logistic regression was used to analyze the risk factors of Mild Cognitive Impairment (MCI) in patients with CRS. There are significant differences in age, Montreal Cognitive Assessment (MoCA) scores, number of MCI, Lund-Mackay olfactory cleft (LM-OC) score, and blood eosinophil count between CRS with and without olfactory dysfunction groups (all P < 0.05). Total MoCA scores were positively correlated with thresholds-discrimination-identification (TDI) score (r = 0.541, P < 0.001), olfactory threshold (OT) (r = 0.440, P < 0.001), olfactory discrimination (OD) (r = 0.541, P < 0.001), and olfactory identification (OI) (r = 0.382, P = 0.001) scores. Furthermore, total MoCA scores were negatively correlated with LM-OC scores (r = - 0.351, P = 0.002). After adjusting for patient demographics, only the OD score was an independent risk factor for MCI among patients with CRS (odds ratio = 0.792; P = 0.039). The OD scores less than 11.5 were the best predictor of MCI in patients with CRS. Olfaction-specific clinical parameters were highly correlated with cognitive function in patients with CRS and the OD score was an independent risk factor for MCI in patients with CRS.

A potential biomarker of cognitive impairment: The olfactory dysfunction and its genes expression.

Accumulation evidence has reported that olfactory impairment may be an essential clinical marker and predictor of mild cognitive impairment or Alzheimer's disease. Participants were enrolled in the population-based, prospective study in Fuxin county, Liaoning province, China between 2019 and 2021. An inverse probability weighting logistic regression and mixed-effect models were performed to explore the association between dysosmia and cognition and rate of change in cognition, respectively. Besides, we utilized the Robust Rank Aggregation method to integrated three eligible datasets from the Gene Expression Omnibus to identify differential expressed genes. A total of 4695 participants were enrolled and 4221 of those were eligible for our cross-sectional study. The mean (SD) age was 59.93(9.78) years, 64.8% were men. Over a 2-year follow-up, of the 2088 participants who completed follow-up, 1559 participants were eligible for our longitude cohort study. We observed an association between dysosmia and an increased risk of cognitive impairment (OR, 0.47, [95% CI, 0.35-0.64]; p < 0.001). The OR (95% CI) for cognition in females with dysosmia was higher than (OR, 0.73[0.51, 1.05], p=.007) that for males with dysosmia (OR, 0.25[0.15, 0.42], p < 0.001; P for interaction <0.001). Dysosmia was also associated with more rapid decline in calculation ability (p < 0.001). Besides, several DEGs were identified, which are mainly associated with olfactory transduction, detection of chemical stimulus involved in sensory perception of smell, sensory perception of smell, olfactory receptor activity and odorant binding. These findings proved novel insight into identifying olfactory dysfunction as potential biomarker for diagnosis of cognitive impairment.

Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment.

Various resources exist for treating mild cognitive impairment (MCI) or dementia separately as terminal events or for focusing solely on a 1-way path from MCI to dementia without taking into account heterogeneous transitions. Little is known about the trajectory of reversion from MCI to normal cognition (NC) or near-NC and patterns of postreversion, which refers to cognitive trajectories of patients who have reversed from MCI to NC. Our objectives were to (1) quantitatively predict bidirectional transitions of MCI (reversion and progression), (2) explore patterns of future cognitive trajectories for postreversion, and (3) estimate the effects of demographic characteristics, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms on transition probabilities. We constructed a retrospective cohort by reviewing patients with an MCI diagnosis at study entry and at least 2 follow-up visits between June 2005 and February 2021. Defining NC or near-NC and MCI as transient states and dementia as an absorbing state, we used continuous-time multistate Markov models to estimate instantaneous transition intensity between states, transition probabilities from one state to another at any given time during follow-up, and hazard ratios of reversion-related variables. Among 24,220 observations from 6,651 participants, there were 2,729 transitions to dementia and 1,785 reversions. As for postreversion, there were 630 and 73 transitions of progression to MCI and dementia, respectively. The transition intensity of progression to MCI for postreversion was 0.317 (2.48-fold greater than that for MCI progression or reversion). For postreversion participants, the probability of progressing to dementia increased by 2% yearly. Participants who progressed to MCI were likely to reverse again (probability of 40% over 15 years). Age, independence level, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms were significant predictors of bidirectional transitions. The nature of bidirectional transitions cannot be ignored in multidimensional MCI research. We found that postreversion participants remained at an increased risk of progression to MCI or dementia over the longer term and experienced recurrent reversions. Our findings may serve as a valuable reference for future research and enable health care professionals to better develop proactive management plans and targeted interventions.

The Challenge of Subjective Cognitive Complaints and Executive Functions in Middle-Aged Adults as a Preclinical Stage of Dementia: A Systematic Review.

Subjective cognitive complaints correspond to a heterogeneous construct that frequently occurs in the early stages of older adult life. Despite being a common source of worry for middle-aged people, it can be underestimated when clinical and neuropsychological assessments discard any underlying pathological processes. Negative age stereotyping but also self-stereotyping can contribute to doing so. Although its diagnosis is a challenge, its implication as a possible predictor of mild cognitive impairment or dementia increases the interest in its early diagnosis and intervention. The present systematic review analyzes the empirical data on the relationship between these complaints and early executive dysfunction with possible predictive value for preclinical stages of dementia. The sixteen papers obtained from the PubMed and Embase databases were exploratory, cross-sectional and prospective in scope. The studies corroborated the relationship between subjective cognitive complaints and some executive processes, which is noteworthy since many people with subjective executive complaints progress to dementia. The relational studies confirmed that impaired executive performance is associated with CSF biomarkers and reduced cortical volume in specific brain regions. However, the heterogeneity of reports in these studies demands stronger efforts in future research with specific tools applied in clinical and neuropsychological assessments and analyzed under a gender perspective.

Subjective cognitive decline, APOE e4 allele, and the risk of neurocognitive disorders: Age- and sex-stratified cohort study.

Subjective cognitive decline and APOE e4 allele (APOE4) are known predictors of mild cognitive impairment and dementia (mild cognitive impairment/dementia), with recent evidence showing interaction between subjective cognitive decline and APOE4 in amplifying the risk of mild cognitive impairment/dementia. However, the literature is unclear whether the interaction effect is seen across various age and sex strata. This study examined the interaction between subjective cognitive decline and APOE4-across different age and sex strata-on the risk of mild cognitive impairment/dementia. This cohort study included 16,221 participants aged ⩾50 years and had normal cognition at baseline. Participants were evaluated for subjective cognitive decline and APOE4 at baseline, and followed-up almost annually for mild cognitive impairment/dementia (median follow-up = 4.5 years). Interaction effects were examined in Cox regression using Relative Excess Risk due to Interaction, stratified by age (⩽70 vs >70 years) and sex. Subjective cognitive decline and APOE4 were independently associated with mild cognitive impairment/dementia (hazard ratio: 1.4-1.8), with the highest risk when subjective cognitive decline and APOE4 co-occurred (hazard ratio: 2.6). APOE4 amplified the association between subjective cognitive decline and mild cognitive impairment/dementia in older women (Relative Excess Risk due to Interaction 1.0; 95% confidence interval = [0.3, 1.6]), but not in other age or sex strata. Among older women, half of them developed mild cognitive impairment/dementia by 12.1 years in the absence of subjective cognitive decline or APOE4. This duration shortened to 8.1-10.3 years in the presence of either subjective cognitive decline or APOE4, and to 4.4 years in the presence of both subjective cognitive decline and APOE4. Interaction effect among older women remained consistent when alternate outcomes were used (i.e. mild cognitive impairment and dementia due to Alzheimer's disease; dementia; and Alzheimer's dementia) (Relative Excess Risk due to Interaction 1.2-2.5). APOE4 amplifies the association between subjective cognitive decline and neurocognitive disorders in older women, with the findings suggesting the need for further research to delineate underlying neurobiology. APOE4 may potentially have a role in facilitating further risk stratification of older women with subjective cognitive decline in clinical practice.

Subjective memory complaints as a predictor of mild cognitive impairment and Alzheimer\u2019s disease

While there is a multitude of studies on mild cognitive impairment (MCI; more than 80,000 articles), subjective memory complaints (SMC) have received less attention as a prodromal stage of Alzheimer’s disease (AD; less than 2000 articles). In this perspective review article, we argue that SMC should also be considered as another risk factor for the development of AD, and perhaps a pre-MCI condition. This recognition of SMC could help clinicians to identify individuals at risk of developing dementia and could provide protective treatment for them. Accordingly, in this perspective article, we review key studies that outline the nature of SMC, discuss how SMC is measured, explore SMC in MCI, introduce some approaches to SMC treatment, and we discuss future directions for SMC research. Overall, we argue that, like MCI, there should be more research on SMC as a risk factor for developing AD. Consequentially, we aim to highlight the need for further research on SMC and the condition’s role as a potential neuroprotector against AD (e.g., early-stage marker).

Apathy as a Risky Neuropsychiatric Syndrome of Progression From Normal Aging to Mild Cognitive Impairment and Dementia: A Systematic Review and Meta-Analysis

Background: Apathy has been suggested as a potential predictor of mild cognitive impairment (MCI) progression to dementia. Whether it might predict the transition from normal cognitive function to cognitive impairment has been less studied. The current study aimed to provide a comprehensive summary of the evidence on the association between apathy and the transition from normal cognitive function to cognitive impairment.Methods: We searched the PubMed, Embase, and Web of Science databases for longitudinal prospective cohort studies that evaluated apathy at baseline in the cognitively normal population and had cognitive impairment as the outcome. Random effects models were used, and heterogeneity was explored with stratification. The stability of the synthesized result was indicated using sensitivity analysis by excluding one study each time and recalculating the overall effect.Results: Ten studies comprising 26,195 participants were included. Apathy status was available for 22,101 participants. Apathy was present in 1,803 of 22,101 participants (8.16%). Follow-up ranged from 1 to 13 years. The combined odds ratio (OR) of cognitive impairment for patients with apathy was 2.07 (95% CI: 1.43–2.99; I2 = 86%), and the combined hazard ratio was 2.70 (95% CI: 1.38–5.27; I2 = 94%). The OR meta-analyses for different conversion outcomes were MCI (OR = 3.38, 95% CI: 1.57–7.28; I2 =71%), cognitive decline (OR = 1.27, 95% CI: 0.81–2.00; I2 = 64%) and dementia (OR = 2.12, 95% CI: 1.32–3.41; I2 = 86%). Subgroup analysis suggested that the association between apathy and cognitive impairment changed with age, depression adjustments, apathy measurement, and follow-up time.Conclusions: Apathy was associated with a greater than 2-fold increased risk of progression to cognitive impairment in the cognitively normal population. Future interventions targeting apathy management in the general population may reduce the risk of cognitive impairment.

Motor and Sensory Function as Predictors of MCI and Dementia in the Baltimore Longitudinal Study of Aging (BLSA)

Motor and sensory impairments are linked with dementia risk, but whether there is a joint effect of deficits in motor and sensory function is unknown. We analyzed 649 BLSA participants (aged 72±11 years; 55% women; 68% white) who had concurrent baseline 6-meter usual gait speed and sensory function (vision, hearing) between 2012-2019. Mild cognitive impairment (MCI) and dementia were adjudicated during an average follow-up of 3 years. We examined the association between baseline gait speed, z-scored sensory function, and a gait*sensory interaction with risk of MCI/dementia using Cox proportional hazard models, adjusted for demographics and chronic conditions. Each .01 m/s faster baseline gait was associated with a reduced risk (HR:0.98 (0.96-0.99)) of MCI/dementia, and each 1 SD higher in hearing and vision z-score was associated with an increased risk (HR:1.84 (1.1-3.1)) increased risk. The was no significant interaction, suggesting motor and sensory impairments may be independently associated with MCI/dementia risk.

Abstract 10561: Attending Cardiac Rehabilitation Reduces Incidence of Dementia but Not Mild Cognitive Impairment in Patients with Coronary Artery Disease

Introduction: Coronary artery disease (CAD) has been associated with cognitive decline. Cardiac rehabilitation (CR) is a class 1A recommendation for patients with CAD as it reduces future cardiac events and mortality. However, the impact of CR on incidence of mild cognitive impairment (MCI) and dementia has not been extensively studied. We investigated the association of CAD on incidence of MCI and dementia; and whether CR attendance reduces incidence of MCI and dementia in patients with CAD Methods: The Mayo Clinic Study of Aging (MCSA), a prospective, population-based cohort was probed for this study. At baseline and every 15-months thereafter, subjects were evaluated for MCI and dementia using a standardized protocol. Data on CR participation were collected via record linkage to the Rochester Epidemiology Project. To evaluate association with incident MCI or dementia, cox proportional hazard models were used and adjusted for age, sex, and clinical predictors of cognitive decline. Participants with MCI at baseline were excluded for MCI analysis and adjusted for in dementia analysis. Results: We included 5960 MCSA participants (female: 50%; age: 70±13). Of those, 1934 participants (32%) had CAD and 702 (12%) had MCI at baseline. Mean follow-up was 3.9±3.7yrs, with 760 incident cases of MCI (13%) and 290 cases of dementia (5%). CAD was a significant predictor of MCI and dementia, although after adjustment for other clinical predictors, CAD was only associated with MCI incidence ( Table 1, Figure ). Incidence of dementia was reduced in CAD patients who had a greater attendance at CR when adjusted for other predictors of cognitive decline ( Table 2 ). Attendance at CR did not reduce incidence of MCI ( Table 2 ). Conclusions: CAD was a significant predictor of MCI and dementia. In patients with CAD, a higher attendance of CR was associated with reduced incidence of dementia but not MCI. Specific CR programming and outcome targets may be needed to prevent MCI in patients with CAD.

Examining the Use of Electroencephalography for the Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment

Introduction: Alzheimer’s disease is a type of dementia characterized by a buildup of -amyloid plaques and neurofibrillary tangles. Prior to the development of Alzheimer’s disease, patients may experience mild cognitive impairment, characterized by a decline in cognitive abilities while maintaining independent function. Electroencephalography has shown promise as a clinical predictor of mild cognitive impairment. The purpose of this study is to review the existing literature on clinical biomarkers using resting-state electroencephalography or event-related potentials to differentiate Alzheimer’s disease or mild cognitive impairment from normal aging. Methods: A search of primary research articles was conducted in PubMed. Selected articles examined mild cognitive impairment and Alzheimer’s disease utilising electroencephalography, event-related potential data, and resting-state data. Reviews, conference abstracts, and studies without human controls were excluded. Results: Our search identified 100 and 125 records on resting-state and event-related potential data, respectively. The most common findings from resting-state studies included a reduction in alpha power, an increase in delta and theta power, a reduction in signal complexity, and differences in functional connectivity. The most common findings from event-related potential studies included reduction in P3 wave amplitude, as well as latency in both P3 and N2 waves. Discussion: Resting-state and event-related potential electroencephalography studies indicate distinct changes in oscillatory brain activity and waveform shape which indicate distinct differences in MCI or AD compared to HC which may be clinically relevant. Conclusion: There is evidence to support the use of certain electroencephalographic biomarkers for the diagnosis of Alzheimer’s disease or mild cognitive impairment. Future research should seek to examine how best to apply these findings in a clinical setting.

Exploration of Rapid Automatized Naming and Standard Visual Tests in Prodromal Alzheimer Disease Detection.

Visual tests in Alzheimer disease (AD) have been examined over the last several decades to identify a sensitive and noninvasive marker of the disease. Rapid automatized naming (RAN) tasks have shown promise for detecting prodromal AD or mild cognitive impairment (MCI). The purpose of this investigation was to determine the capacity for new rapid image and number naming tests and other measures of visual pathway structure and function to distinguish individuals with MCI due to AD from those with normal aging and cognition. The relation of these tests to vision-specific quality of life scores was also examined in this pilot study. Participants with MCI due to AD and controls from well-characterized NYU research and clinical cohorts performed high and low-contrast letter acuity (LCLA) testing, as well as RAN using the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number test, and vision-specific quality of life scales, including the 25-Item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and 10-Item Neuro-Ophthalmic Supplement. Individuals also underwent optical coherence tomography scans to assess peripapillary retinal nerve fiber layer and ganglion cell/inner plexiform layer thicknesses. Hippocampal atrophy on brain MRI was also determined from the participants' Alzheimer disease research center or clinical data. Participants with MCI (n = 14) had worse binocular LCLA at 1.25% contrast compared with controls (P = 0.009) and longer (worse) MULES test times (P = 0.006) with more errors in naming images (P = 0.009) compared with controls (n = 16). These were the only significantly different visual tests between groups. MULES test times (area under the receiver operating characteristic curve [AUC] = 0.79), MULES errors (AUC = 0.78), and binocular 1.25% LCLA (AUC = 0.78) showed good diagnostic accuracy for distinguishing MCI from controls. A combination of the MULES score and 1.25% LCLA demonstrated the greatest capacity to distinguish (AUC = 0.87). These visual measures were better predictors of MCI vs control status than the presence of hippocampal atrophy on brain MRI in this cohort. A greater number of MULES test errors (rs = -0.50, P = 0.005) and worse 1.25% LCLA scores (rs = 0.39, P = 0.03) were associated with lower (worse) NEI-VFQ-25 scores. Rapid image naming (MULES) and LCLA are able to distinguish MCI due to AD from normal aging and reflect vision-specific quality of life. Larger studies will determine how these easily administered tests may identify patients at risk for AD and serve as measures in disease-modifying therapy clinical trials.

Developing a cognitive dysfunction risk score for use with opioid-dependent persons in drug treatment

BackgroundCognitive dysfunction is common in persons seeking medication for opioid use disorder (MOUD) and may hinder many addiction-related services. Brief but accurate screening measures are needed to efficiently assess cognitive dysfunction in these resource-limited settings. The study aimed to develop a brief predictive risk score tailored for use among patients in drug treatment. MethodsThe present study examined predictors of mild cognitive impairment (MCI), objectively assessed via the NIH Toolbox, among 173 patients receiving methadone as MOUD at an urban New England drug treatment facility. Predictors of MCI were identified in one subsample using demographic characteristics, medical chart data, and selected items from the Brief Inventory of Neuro-Cognitive Impairment (BINI). Predictors were cross-validated in a second subsample using logistic regression. Receiver operating curve (ROC) analyses determined an optimal cut-off score for detecting MCI. ResultsA cognitive dysfunction risk score (CDRS) was calculated from patient demographics (age 50+, non-White ethnicity, less than high school education), medical and substance use chart data (history of head injury, overdose, psychiatric diagnosis, past year polysubstance use), and selected self-report items (BINI). The CDRS discriminated acceptably well, with a ROC curve area of 70.6 %, and correctly identified 78 % of MCI cases (sensitivity = 87.5 %; specificity = 55.6 %). ConclusionsThe CDRS identified patients with cognitive challenges at a level likely to impede treatment engagement and/or key outcomes. The CDRS may assist in efficiently identifying patients with cognitive dysfunction while requiring minimal training and resources. Larger validation studies are needed in other clinical settings.