Significant Predictor Of Cognitive Decline Research Articles

Detecting and Predicting Cognitive Decline in Individuals with Traumatic Brain Injury: A Longitudinal Telephone-Based Study.

Traumatic brain injuries (TBIs) can lead to long-lasting cognitive impairments, and some survivors experience cognitive decline post-recovery. Early detection of decline is important for care planning, and understanding risk factors for decline can elucidate targets for prevention. While neuropsychological testing is the gold standard approach to characterizing cognitive function, there is a need for brief, scalable tools that are capable of detecting clinically significant changes in post-TBI cognition. This study examines whether a clinically significant change can be detected using the Brief Test of Adult Cognition by Telephone (BTACT) in a sample of individuals with chronic TBI and investigates whether potentially modifiable factors are associated with cognitive decline. Ninety participants aged 40 or older with complicated mild-to-severe TBI participated in two telephone-based study visits ∼1 year apart. Demographic, head trauma exposure, comorbid medical conditions, physical, and psychosocial functioning data were collected via self-report. The BTACT, a brief measure of global cognitive function, was used to assess cognitive performance across six domains. A reliable change index for quantifying clinically significant changes in BTACT performance was calculated. Results revealed cognitive decline in 10-27% of participants across various cognitive domains. More specifically, only depressive symptoms, including depressed affect and anhedonia, were significantly associated with cognitive decline after correcting for multiple comparisons using false discovery rate (FDR). Other factors such as the number of blows to the head, male gender, dyspnea, increased anxiety symptoms, seizures, illicit drug use, and fewer cardiovascular comorbidities should be considered hypothesis generating. Importantly, age was not a significant predictor of cognitive decline, which challenges the assumption that cognitive decline is solely related to the natural aging process. It suggests that there are unique factors associated with TBI that impact cognitive function, and these factors can affect individuals across the lifespan. The BTACT is a brief and sensitive tool for identifying clinically meaningful changes in cognitive function over a relatively brief period (i.e., 1 year) in a sample of individuals in the chronic stages of TBI (i.e., x̄ = 6.7 years post-TBI). Thus, the BTACT may be useful in surveillance efforts aimed at understanding and detecting decline, particularly in situations where in-person cognitive screening is impractical or unfeasible. We also identified potentially modifiable targets for the prevention of post-TBI cognitive decline. These findings can offer insights into treatment goals and preventive strategies for individuals at risk for cognitive decline, as well as help to facilitate early identification efforts.

Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients.

Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI). Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity. Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity. Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

Characterizing Neighborhood Vulnerabilities in Mild Cognitive Impairment using the Environmental Justice Index.

There is a need for integration and comprehensive characterization of environmental determinants of Alzheimer's disease. The Environmental Justice Index (EJI) is a new measure that consolidates multiple environmental health hazards. This analysis aims to explore how environmental vulnerabilities vary by race/ethnicity and whether they predict cognitive outcomes in a clinical trial of mild cognitive impairment (MCI). We used data from a clinical trial of 107 MCI participants (28% minorities). Using the EJI, we extracted 40 measures of neighborhood environmental and social vulnerability including air and water pollution, access to recreational spaces, exposure to coal and lead mines, and area poverty. We also examined the relationship of the EJI to the Area Deprivation Index (ADI). Data was analyzed using regressions, correlations, and t-tests. Environmental Burden Rank (EBR) across the sample (0.53±0.32) was near the 50th percentile nationally. When divided by race/ethnicity, environmental (p = 0.025) and social (p < 0.0001) vulnerabilities were significantly elevated for minorities, specifically for exposure to ozone, diesel particulate matter, carcinogenic air toxins, and proximity to treatment storage and disposal sites. ADI state decile was not correlated with the EBR. Neither EBR nor ADI were a significant predictor of cognitive decline. To our knowledge, this is the first study to link the EJI to an MCI trial. Despite limitations of a relatively small sample size, the study illustrates the potential of the EJI to provide deeper phenotyping of the exposome and diversity in clinical trial subjects.

Cerebrospinal fluid growth-associated protein 43 levels in patients with progressive and stable mild cognitive impairment.

Cerebrospinal fluid (CSF) growth-associated protein 43 (GAP-43) is prominently elevated in Alzheimer's disease (AD) dementia patients in comparison to normal controls. CSF GAP-43 levels in mild cognitive impairment (MCI) individuals who have different clinical trajectories need to be studied. We examined 137 cognitively normal (CN) controls, 218 stable MCI patients (sMCI), 99 progressive MCI (pMCI) patients, and 120 AD dementia patients. Associations between the CSF GAP-43 levels and the four diagnosis groups were evaluated with multiple-variable linear regression. The relationships between CSF GAP-43 and core CSF biomarkers were assessed by Spearman correlations. Cox regression analysis was performed to assess the values of GAP-43 in predicting MCI conversion. We examined associations between baseline CSF GAP-43 levels and longitudinal cognitive function, hippocampal volumes, and brain glucose metabolism using linear mixed-effects models. CSF GAP-43 was elevated in the pMCI and AD groups in comparison to the CN group and in the pMCI and AD groups in comparison to the sMCI group. CSF GAP-43 significantly predicted conversion from MCI to AD. CSF GAP-43 was a significant predictor of cognitive decline, hippocampal atrophy, and brain hypometabolism over time. Furthermore, elevated CSF GAP-43 levels were associated with accelerated deterioration in cognition and neurodegeneration. CSF GAP-43 is increased in the predementia stage of AD, and it may enhance the neurodegenerative process. Future efforts on pharmacological interventions targeting synaptic dysfunction could be promising in AD treatment.

Exploring relationships between neuroticism, depression, and the progression of cognitive decline over time

<h3>Introduction</h3> Cognitive decline is prevalent in older adults, and predicting onset of cognitive decline in patients is a significant challenge for physicians. Studies have shown a relationship between neuroticism and the onset of cognitive decline in a ten-year time span, and have identified one aspect of neuroticism (N6 – vulnerability to stress) to be specifically elevated in those who later develop cognitive impairment. However, little is known about the onset of cognitive decline in a shorter time span, or if other aspects of neuroticism might be predictors. In addition, the effects of depression in this relationship have yet to be determined. The purpose of this study is to evaluate the relationship between the various facets of neuroticism and the onset of cognitive decline in a 1 to 3 year time span in the presence and absence of depression in a cohort of elderly subjects. <h3>Methods</h3> This is a retrospective cohort study. Subjects participated in "Neurobiology of Late-life Depression" (NBOLD) study at the University of Connecticut Health Center (UCHC) and Olin Neuropsychiatry Research Center at the Institute of Living in Hartford Hospital. Participants were screened for depression using the Center for Epidemiologic Studies – Depression (CES-D) scale, with a score of 16 or greater as a cut-off for depression. The NEO PI-R was used to screen for neuroticism. CERAD neurophysiological tests were used to screen for cognitive decline, and were administered annually. Statistical analysis of the data involved linear regression and correlation analysis was done to assess the significance of the predictive value of various facets of neuroticism in future cognitive decline development. Mixed model analysis was done to examine how changes in neuroticism score can moderate the rate of cognitive decline. Analysis was done by using baseline neuroticism scores and cognition scores after one, two, and three years. <h3>Results</h3> 163 subjects were enrolled. 28.8% of subjects identified as male, and 71.2% identified as female. The mean age was 72.27 ± 7.44 years. 89.6% identified as White, 7.7% identified as Black or African American, 1.8% identified as Asian, and 0.61% identified as mixed race. 1.8% had completed 9^th grade, 14.1% had graduated high school, 22.7% had completed some college, 20.9% had a college degree, and 40.5% had completed post-graduate education124 subjects had depression at the time of baseline measurement, and 39 comparison subjects did not have depression at baseline. Two facets of neuroticism were shown to be statistically significant predictors of cognitive decline in the non-depressed patients. High baseline N6 (vulnerability of stress) was a predictor of a lower CERAD score at 1 year (p=0.08) and 3 years (p=0.09). High baseline N4 (self-consciousness) was also found to be a predictor of lower CERAD score at 1 year (p=0.01), 2 years (p=0.03), and 3 years (p=0.08). In addition, improvement in N4 over time was shown to cause a lower rate of progression of cognitive decline in non-depressed patients. The findings for depressed patients were not found to be statistically significant. <h3>Conclusions</h3> Both N6 and N4 are statistically significant predictors of cognitive decline 1 to 3 years after baseline neuroticism measurement. Improvement in N4 is associated with a lower rate of cognitive decline. These results were found in non-depressed patients but not depressed patients. These findings raise the possibility that longer periods of follow-up are needed to illustrate the association between neuroticism, cognitive decline, and depression. Investigating predictive factors of cognitive decline is key to foreseeing the development of the disease early on, allowing patients to prepare and access care that may be difficult to obtain as cognitive conditions progress. <h3>This research was funded by</h3> All subjects in the study were enrolled in NBOLD, a NIMH R01 grant entitled "Neurobiology and Adverse Outcomes of Neuroticism in Late-Life Depression".

76 PREDICTIVE MODEL FOR MOBILITY DECLINE: INDIVIDUAL TRIAL MISTAKE THRESHOLDS IN SUSTAINED ATTENTION TO RESPONSE TASK (SART)

Abstract Background The Sustained Attention to Response Task (SART) is a standard computer-based cognitive test designed to measure the sustained attention, fundamental for completing tasks that require supervision over time (Robertson et al., 1997). However, commonly used average features may result in loss of information and data misinterpretation, leading to inability to detect clinically expected associations (O’Halloran et al., 2014). Methods Here, we present a new method to visualise the full information obtained from the SART test, ordering by age, and categorising in groups based on mobility status in a large population-based study of ageing in Ireland. A new threshold, derived from the visualisation and based on the individual trial number of mistakes, was employed to individuate poorer SART performances, and to predict mobility and cognitive decline after 4 years in binary logistic regression models. Results Raw SART data were available for 4,864 participants aged 50 years and over at baseline. The new variable bad performances, expressing the number of SART trials with at least 4 mistakes, was the most significant predictor of mobility decline, defined as the transition from Timed Up-and-Go (TUG) &amp;lt; 12 to TUG ≥12 seconds (Odds Ratio (OR) = 1.29; 95% Confidence Interval (CI) 1.14–1.46; p &amp;lt; 0.001), and the only significant predictor of new falls (OR = 1.11; 95% CI 1.03–1.21; p = 0.011) compared to traditional SART variables in models adjusted for multiple covariates. No SART-related variables resulted significant predictors of cognitive decline, defined as a decrease of at least 2 points in the Mini-Mental State Examination (MMSE) score. Conclusion This multimodal visualisation and the new threshold approach could help clinicians to easily develop relevant hypotheses, and better identify subjects at higher risk of future mobility decline.

Role of white matter hyperintensities, hemoglobin and vitamin B‐12 on cognitive decline: Two‐year follow‐up data from the Tata Longitudinal Study of Ageing (TLSA)

AbstractBackgroundThe presence of white matter hyperintensities is commonly seen in elderly individuals and many studies have identified its relation to cognitive decline, however the effect size of this relationship has been seen to be relatively small. Evidence also suggests that among older individuals, low levels of hemoglobin and Vitamin B‐12 are indicators of cognitive decline. This study seeks to identify the role of white matter hyperintensities, hemoglobin and Vitamin B‐12 on cognitive change among an urban elderly population in Bangalore, India.MethodA subset of 87 individuals (49 Males and 38 Females, mean age=65.9 years) from TLSA Cohort above the age of 45 participated in the TATA longitudinal Study of Ageing, conducted in Bangalore, India. All participants underwent the Addenbrooke’s Cognitive Examination III (ACE‐III), blood investigations and Magnetic Resonance Imaging (MRI) scans as per the Alzheimer's Disease Neuroimaging Initiative (ADNI‐II) protocol at baseline. Brain images were acquired with a 3T Siemens Skyra MR Scanner. MRI scans were then visually rated on Fazeka’s scale for white matter lesions. Cognitive assessments were repeated two years later, on all participants. Change in cognition was calculated by subtracting followup scores from baseline scores. Regression analysis was conducted in order to examine the relation between White matter hyperintensities, vitamin b‐12 and hemoglobin at baseline with change in cognitive scores over time.ResultThe results indicate that Fazeka’s deep white matter scores, hemoglobin and vitamin B‐12 are significant predictors of changes in ACE‐III Memory scores at a 2 year follow up. A significant regression equation was found (F(3,38)=6.73, p&lt;0.001), with an R2 of 0.347.ConclusionThe findings of the study suggest that an individual’s deep white matter hyperintensity, along with hemoglobin levels and Vitamin B12 at baseline are potential indicator of cognitive change during follow up. Future longitudinal studies with larger sample size are required to examine whether this model is a significant predictor of cognitive decline and dementia.

Estimating Sample Size Required to Establish an Association Between Walnut Intake and Cognitive Change in Older Adults: An Application of Monte Carlo Power Analysis

Abstract Objectives Observational studies support a cross-sectional association between walnut intake and cognitive function among older adults, but few of these studies identify walnut intake as a predictor of cognitive change. This project estimates the sample size required to establish a statistically significant association between walnut intake and cognitive change in an observational study using Monte Carlo power analysis. Methods Initial observations were drawn from the 2012, 2014, and 2016 Health and Retirement Study (HRS) and the 2013 Health Care and Nutrition Study (HCNS; age ≥ 65, n = 3632). Global cognitive function was measured using the Telephone Interview for Cognitive Status and two operationalizations of walnut intake were investigated (none, low intake (.01 – .08 servings/day), and moderate intake (&amp;gt; .08 servings/day); no intake vs. any intake). Latent growth models adjusting for covariates and complex sample design were used to estimate age-based developmental trajectories of TICS scores as a function of walnut intake. Parameter estimates from these models were used as starting values in Monte Carlo simulation models replicated for sample sizes from 1000–50,000. Results Model estimation required around 1200 hours of processing time. When measured as a trichotomous variable, the observed association between walnut intake and cognitive change was weak (for moderate intake, b = −0.030, SE = .03) and would require at least 42,000 observations to reduce the standard error to a level where 80% or more of random samples would identify the effect as statistically significant (P &amp;lt; .05). When measured as a dichotomous variable, the observed effect was small (b = −0.013, SE = 0.025) and required a sample size of at least 39,000 observations to identify power above .80. Conclusions Given that the HRS and HCNS are nationally-representative studies, the population size from which an adequate sample would need to be drawn to identify walnut intake as a significant predictor of cognitive decline would exceed the number of adults age 65 and older currently living in the US. Rather than increase sample size of observational studies, researchers should apply quasi-experimental methods and detailed measurement of walnut intake to establish an association between walnut intake and cognitive change. Funding Sources This research was funded by the California Walnut Commission.

Predict cognitive decline with clinical markers in Parkinson\u2019s disease (PRECODE-1)

Over the course of the disease, about 80% of Parkinson’s disease patients will develop cognitive impairment. However, predictive factors associated with cognitive decline are still under investigation. Here, we investigated which clinically available markers are predictive of cognitive impairment in a cohort of early drug-naïve Parkinson’s disease patients. 294 drug-naïve Parkinson’s disease patients, who were cognitively normal at baseline, were recruited from the Parkinson’s Progression Markers Initiative. At 36-month follow-up, patients were diagnosed with cognitive impairment according to two levels: Level 1 diagnosis was defined as MoCA < 26 and Level 2 diagnosis was defined as MoCA < 26, alongside an impaired score on at least two neuropsychological tests. Predictive variables with a validated cut-off were divided into normal or abnormal measures, whilst others were divided into normal or abnormal measures based on the decile with the highest power of prediction. At 3 years’ follow-up, 122/294 Parkinson’s disease (41.5%) patients had cognitive decline. We found that age at Parkinson’s disease onset, MDS-UPDRS Part-III, Hopkin’s Learning Verbal Test-Revised Recall, Semantic Fluency Test and Symbol Digit Modalities Test were all predictors of cognitive decline. Specifically, age at Parkinson’s disease onset, Semantic Fluency Test and symbol Digit Modalities Test were predictors of cognitive decline defined by Level 2. The combination of three abnormal tests, identified as the most significant predictors of cognitive decline, gave a 63.6–86.7% risk of developing cognitive impairment defined by Level 2 and Level 1 criteria, respectively, at 36-month follow-up. Our findings show that these clinically available measures encompass the ability to identify drug-naïve Parkinson’s disease patients with the highest risk of developing cognitive impairment at the earliest stages. Therefore, by implementing this in a clinical setting, we can better monitor and manage patients who are at risk of cognitive decline.

Rate of Cognitive Decline in Alzheimer's Disease Stratified by Age.

There is only limited information available about the effect of age on course of cognitive decline in patients with onset of Alzheimer's disease (AD) over the age of 64 years. We compared the rate of, and factors affecting, cognitive decline in patients with AD aged < 65 years (young-onset AD), 65-74 years (middle-onset AD), and ≥75 years (late-onset AD). The study used longitudinal data from the Essex Memory Clinic which included a total of 305 participants; 56 had YOAD, 73 had MOAD, and 176 had LOAD. The rate of cognitive decline was measured using scores from the Mini-Mental State Examination (MMSE), and the data were examined using multilevel models analysis. There was evidence of a difference in cognitive decline across the age groups with the YOAD group declining 2.8 MMSE points per year, those with MOAD declined 2.0 MMSE points per year, and the LOAD group declined 1.4 MMSE points per year. Patients with LOAD have a better prognosis than YOAD and MOAD. However, even between the MOAD and LOAD groups, age is a significant predictor of cognitive decline, with older patients having a more benign course.

Transcranial magnetic stimulation predicts cognitive decline in patients with Alzheimer’s disease

ObjectiveTo determine the ability of transcranial magnetic stimulation (TMS) in detecting synaptic impairment in patients with Alzheimer’s disease (AD) and predicting cognitive decline since the early phases of the disease.MethodsWe...

T53. LTP-like cortical plasticity is associated with memory and predicts cognitive decline in Alzheimer’s disease patients

To determine the ability of transcranial magnetic stimulation (TMS) in detecting synaptic impairment in Alzheimer’s disease (AD) patients and predicting cognitive decline since the early phases of the disease. We evaluated long-term potentiation (LTP)-like cortical plasticity in 60 newly diagnosed AD patients. Pearson r correlation coefficient or Kruskal-Wallis runk sum test explored any relationship between LTP, demographics, cognition and AD-related biomarkers. Univariable analyses examined the association between LTP (respect to other AD-related biomarkers) and cognitive decline. Multivariable regression model revealed the best parameters able to predict disease progression. LTP plasticity was not significantly associated with sex (z = 0.89, p = 0.37), age (r = −0.02, p = 0.75) or APOE genotype (z = −0.81, p = 0.41). We confirm a significant association between LTP and both CSF t-tau (r = −0.34, p < 0.01) and p-tau levels (r = −0.26, p = 0.04), while no significant association was find for Ab1–42 (r = −0.01, p = 0.89). Higher values of LTP were associated with higher long-term verbal memory performances (CVLT delayed: r = 0.45; p = 0.002), while neither visual-spatial long-term memory (RCF delayed: r = 0.08; p = 0.53), general intelligence (RPM test: r = 0.11; p = 0.45), executive functions (FVF: r = −0.13; p = 0.36) or visual-spatial abilities (RCF copy: r = −0.08; p = 0.54) showed any association. Among AD patients, higher values of LTP were associated with better long-term verbal memory performances (r = 0.45; p = 0.002). Notably, LTP was a significant predictor of disease progression (p = 0.02), while no other neurophysiological, neuropsychological and demographic parameters, was associated with cognitive decline, except for a trend regarding sex (p = 0.07), long-term verbal memory (p = 0.07), visuospatial abilities (p = 0.10) and CSF total-tau levels (p = 0.09). Multivariable analysis then promoted LTP as the best significant predictor of cognitive decline (p = 0.01). Synaptic dysfunction may be an early pathologic process in AD, and could be easily detected by means of TMS. Our data showed a significant correlation between episodic memory and LTP-like cortical plasticity, reinforcing the notion that this measure could be a neurophysiological surrogate of memory. Furthermore, our data show that LTP-like cortical plasticity is able alone to predict cognitive decline in AD patients. TMS could be a viable tool to assess synaptic impairment in AD patients, with LTP-like plasticity as the most sensitive marker of memory and predictor of cognitive decline progression.

Cognition in epilepsy patients with hypothalamic hamartomas

Many patients with epilepsy caused by hypothalamic hamartomas (HHs) have cognitive impairments during the course of the disease or following neurosurgical treatment. The purpose of this study was to assess cognitive function in these patients, as well as factors influencing preoperative cognitive performance and cognitive outcome after neurosurgical treatment. Using the two largest and most detailed neuropsychology datasets on HH and epilepsy from two centers, we retrospectively report on cognitive functions in 48 patients with structural epilepsy due to HH (mean age ± standard deviation [SD] 20±12 years, range 5-53 years, median 16years; disease duration mean 17±11years). Intelligence, verbal learning and recall, and speed and executive functions (processing speed and cognitive flexibility) were assessed before and on average 19 (±11) months after surgery (interstitial radiosurgery: N=22; neurosurgical resection/disconnection: N=26). Prior to neurosurgical treatment, 52% of patients showed impaired executive and 62% showed reduced verbal memory functions. A trend for a detrimental effect of higher drug load on cognitive functioning was found. After neurosurgical treatment, intellectual functions for the entire cohort tended to increase. This correlated with improved seizure frequency and decreased number of antiepileptic drugs (AEDs). However, postoperative outcomes for individual patients were highly variable, with significant deteriorations in 17% (processing speed) to 34% (cognitive flexibility and verbal learning), and performance increases in 17% (intellectual functioning) up to 39% (processing speed) of the patients. Higher levels of presurgical performance were significant predictors of cognitive decline after surgery. These results are highly relevant for patient consultation and may help with therapeutic decisions.

Serum SHBG Levels are not Associated with Longitudinal Cognitive Decline in Mild Cognitive Impairment.

Prior studies have noted gender differences in cognition, imaging, and pathological markers in mild cognitive impairment (MCI) subjects. Sex hormone-binding globulin (SHBG), a major controlling factor in the proportion of bioavailable versus bound testosterone and estrogen, has been proposed to contribute to links between hormones and dementia, but has not yet been investigated fully in a prospective biomarker trial. This study examined whether, among subjects with MCI, SHBG levels predict future rate of cognitive decline. We examine the effect of gender on cognitive decline and factors modulating potential gender differences in 378 MCI subjects (134 females, 244 males) in the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1), followed for up to 8 years (mean ± SE, 4.0 ± 0.1 years). Cognition was assessed using the ADAS-cog-11. Multivariate models examined the effect of gender covarying for age, ApoE4, baseline cognition, years of education, and SHBG levels. MCI women declined significantly faster than men in cognition over the follow up period. Baseline SHBG levels differed significantly between men and women (p < 0.0001), and by age in men, but not by ApoE4 status. In the multivariate models, SHBG levels were not a significant predictor of cognitive decline in men or women but ApoE4 status, baseline cognition, years of education, and female gender were. SHBG levels did not influence the rate of cognitive decline in MCI. Further studies to confirm these findings and uncover other potential mechanisms of gender differences in the risk for AD may be warranted.

Effects of Transient Versus Chronic Loneliness on Cognitive Function in Older Adults: Findings From the Chinese Longitudinal Healthy Longevity Survey

Loneliness is a risk factor for poor cognitive function in older adults (OAs); to date, however, no studies have explored whether transient and chronic loneliness have differential effects on OAs' cognitive function. The present study evaluates the impacts of transient versus chronic loneliness on cognitive function in OAs. A 6-year follow-up cohort study. Rural and urban communities of 22 provinces in China. 2,995 OAs who were cognitively healthy (the modified Mini-Mental State Examination [mMMSE] ≥ 14) and completed the 2005, 2008, and 2011 waves of the Chinese Longitudinal Healthy Longevity Survey. Self-report loneliness and mMMSE. Both transient (β = -0.389, t = -2.191, df = 2994, p = 0.029) and chronic loneliness (β = -0.640, t = -2.109, df = 2994, p = 0.035) were significantly associated with lower mMMSE scores 6 years later, net of potential confounding effects of baseline covariates. Sensitivity analyses found that regression coefficients of mMMSE scores on transient loneliness were statistically significant and relatively stable across samples with various levels of cognitive function. In contrast, coefficients of mMMSE scores on chronic loneliness were statistically significant only among samples with normal cognitive function and the absolute values of these coefficients increased with the degree of cognitive health of the analytic sample. In the sample with mMMSE greater than or equal to 21, the coefficient of chronic loneliness was 2.59 times as large as that of transient loneliness (-1.017 versus -0.392). Both transient and chronic loneliness are significant predictors of cognitive decline in OAs. Relative to transient loneliness, chronic loneliness has more pronounced negative effects on the brain health of OAs.

Visual Hallucinations and Amyloid Deposition in Parkinson's Disease Dementia: A Case Report.

Parkinson's disease dementia (PDD) is notorious for its debilitating clinical course and high mortality rates. Consequently, various attempts to investigate predictors of cognitive decline in Parkinson's disease (PD) have been made. Here we report a case of a 75-year-old female patient with PD who visited the clinic with complaints of recurrent visual hallucinations and cognitive decline, whose symptoms were ameliorated by the titration of rivastigmine. Imaging results showed pronounced diffuse cortical amyloid deposition evidenced by 18F-florbetaben amyloid positron emission tomography (PET) imaging. This observation suggests that pronounced amyloid deposition and visual hallucinations in PD patients could be clinically significant predictors of cognitive decline in PD patients. Future research should concentrate on accumulating more evidence for possible predictors of cognitive decline and their association with PD pathology that can enable an early intervention and standardized treatment in PDD patients.

Community‐Based Comprehensive Geriatric Assessment of Short‐ and Long‐Term Predictors of Cognitive Decline in Elderly Adults

To the Editor: Only little is known regarding successful approaches to primary or secondary prevention of most dementia. There is a need for detecting and modifying specific risk factors assessable in the community. From a combined global and local viewpoint, a community-based comprehensive geriatric assessment (CGA) of older adults in a rural Japanese town was performed to investigate its association with cognitive status. Recent investigations have shown that physical performance is an important predictor of change in cognitive function1-3 and that blood pressure (BP) is associated with cognitive performance.4-6 How changes in cognitive function may relate to changes in physical assessments, brachial and central systolic BP and other cardiovascular and clinical endpoints was investigated after 3 and 5 years of follow-up. Annual community-based CGA of elderly adults living in Tosa (Kochi prefecture) has been performed since 2004. Of health check participants aged 75 to 99 in 2005 (reference; second year of project), 133 (94 women, 39 men, mean 2005 age 80.1) were followed up in 2008 and 108 (77 women, 31 men, mean 2005 age 79.9) again in 2010. Left brachial BP and right radial arterial pulse waves were noninvasively measured using oscillometry and tonometry (HEM-9000AI, Omron Healthcare Co., Ltd., Kyoto, Japan).7 SBP2 (radial augmentation index (AI) × (brachial SBP–brachial DBP) + brachial DBP) and AI were determined using pulse wave analysis.8 Because central SBP by direct measurement is reportedly closely associated with radial SBP2,8 radial SBP2 was used as the derived central aortic pressure. Subjects grouped in terms of declining, unchanged, or improving cognitive function were compared using one-way analysis of variance or chi-square tests, complemented by Student t-tests. P < .05 was considered statistically significant. In 2005, mean Mini–Mental State Examination (MMSE) score was 27.5 (range 24–30), mean Hasegawa Dementia Rating Scale—Revised (HDS-R) score was 26.8 (range 19–30), mean modified Kohs’ block design test score was 21.7 (range 2–46), and mean Clock Drawing Test (CDT) score was 8.5 (range 1–10) (Table 1). Improvement (or decline) in cognitive function was defined as an increase (or decrease) of three points on the MMSE. In 2008 (3-year follow-up), men were more likely to have declined than women (P = .04), CDT was larger (P = .01), Timed Up and Go was faster (P = .02), and serum creatinine was higher in the improved than in the unchanged group (P = .04). In 2010 (5-year follow-up), central systolic BP was higher in the declined than in the unchanged group (P = .02), and hemoglobin was higher in the improved than in the unchanged group (P = .002) (Table 1). Anemia in older adults is reportedly associated with greater risk of dementia in the next 11 years,9 perhaps related to chronic brain hypoxia. In the current study, central systolic BP was a predictor of cognitive decline at 5-year follow-up, and physical activity assessed according to the Timed Up and Go test was a short-term predictor of cognitive function. Slow gait was also a strong and early risk factor for cognitive decline in a study of 767 participants aged 70 and older studied over 36.5 months (dementia hazard ratio = 3.27, 95% confidence interval (CI) = 1.55–6.90).2 Other investigations also suggest that high BP in midlife increases the risk of dementia and Alzheimer's disease in older age. High systolic BP was a risk factor for dementia in younger elderly adults (<75) but not in older adults in a less-than-10-year prospective community-based cohort study.4 In a transverse investigation, central BP, but not brachial BP, was a sensitive indicator of cognitive function.6 This is in keeping with the current investigation confirming in older adults that central systolic BP, but not brachial systolic BP, was a statistically significant predictor of cognitive decline at five but not 3 years. Central hemodynamic variables are independently associated with organ damage and incident cardiovascular disease, suggesting that central BP may be different from BP measured on the arm.6, 10 It may thus be more relevant to the study of cognitive function, given that blood is delivered to the brain through the large central arteries. In conclusion, central BP is a long-term predictor of cognitive decline in older adults, whereas preserved physical activity, represented by the Timed Up and Go test is a short-term predictor of cognitive improvement. We would like to extend our thanks to all participants of this study. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: Kikuchi: data analysis and writing of the manuscript. Sasaki, Oinuma, Yamanaka G., Okajima, Yamanaka T., Okumiya: data collection. Cornelissen, Matsubayashi, Otsuka: study concept. Sponsor's Role: None.

Abstract 19813: Sleep Disturbance, Heart Failure, and Cognitive Function in Older Individuals: The Aging Demographics, and Memory Study (ADAMS)

Introduction: Approximately 50% of heart failure (HF) patients experience cognitive decline. In the general population, sleep disturbance is associated with cognitive decline. Sleep disturbance may alter the cellular or chemical homeostasis triggering cognitive decline. Up to 70% of individuals with HF report sleep disturbance. Although the etiology of cognitive decline in HF is unknown, sleep fragmentation and short sleep duration from sleep disturbance may partially explain cognitive decline among individuals with HF. This study investigates the possible mediating role of sleep disturbance on the relationship between HF and cognition. Methods: This cross-sectional study examined 856 older adults’ (mean age: 81.6 years, SD: 7.1, male: 355 (41%), Caucasian: 658 (77 %), HF: 100 (11.7%)) data from Aging, Demographics, and Memory Study. To explore the possibility of meditating effects of sleep disturbance on relationship between HF and cognition, we used a structural equation model. Cognition was measured by neuropyshological tests. Sleep disturbance was determined if a subject was positive on one of the following three questions: 1) “Do you have problem falling asleep?”, 2) “Do you wake frequently during sleep?”, and 3) “Do you wake up too early?” Results: Individuals with HF were likely to have a higher degree of sleep disturbance (β=0.229,p=0.003). Sleep disturbance was a significant predictor of cognitive decline (β=-6.52,p=0.028). However, there was no significant mediating effect of sleep disturbance on the relationship between HF and cognition (β=-0.011,p=0.978) after controlling for age, sex, and comorbidities. Conclusion: Findings from this study suggest that HF can exacerbate sleep disturbance and sleep disturbance can deteriorate cognition. However, the mediating role of sleep disturbance on the relationship between HF and cognitive decline remains questionable. Future studies using objective measures and longitudinal design would enhance our knowledge related to the relationship between heart failure, sleep disturbance, and cognition.

B-52 * First 15 Seconds of Letter Fluency Predicts Cognitive Impairment at 1 Year Follow-up in Individuals with HIV: A Pilot Study

Objective: Deficits in initiation, the ability to mobilize cognitive resources, may underlie both executive functioning and processing speed impairments frequently observed in HIV-associated neurocognitive disorders (HAND). We therefore explored the utility of a measure of cognitive initiation (FAS15) as a predictor of cognitive decline from normal to mild neurocognitive disorder (MND) over time. FAS15 is the percentage of total correct responses on an FAS letter fluency task given in the first 15 second epoch. Method: A cognitively normal HIV+ group that remained cognitively normal at average one-year follow-up (n = 19) was compared to a demographically similar HIV+ group that converted from cognitively normal to MND at one-year average follow-up (n = 21) on baseline measures of FAS15 and FAS total correct. Results: The two groups did not differ on demographic or disease variables. After controlling for age, WRAT-3 reading score, and CD4 count, binary logistic regression identified baseline FAS15 as a significant predictor of conversion from cognitively normal to MND over the course of a year, χ2(4) = 6.37, p = .012. However, FAS total correct did not emerge as a significant predictor of cognitive decline, χ2(4) = 1.48, p > .05. Age, reading score, viral load, and CD4 count did not independently predict group conversion. Conclusion(s): The findings suggest that FAS15 (cognitive initiation), but not FAS total (a measure of executive functioning), may serve as an early predictor of conversion from cognitively normal to MND in those with HIV. These findings require replication in a larger sample.

The Alzheimer's Disease Neuroimaging Initiative: Progress report and future plans

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.