Baseline Mild Cognitive Impairment Research Articles

Changes in mild cognitive impairment and sociodemographic disparity among adults aged 55 years and above in 4 provinces of China

To investigate the changes in mild cognitive impairment(MCI) and sociodemographic disparity among adults aged 55 years and above in 4 provinces of China. A total of 4687 adults aged 55 years and above from Community-based Cohort Study on Nervous System Disease who did not have Alzheimer's disease, participated in both rounds of the survey, and had complete baseline sociodemographic data and two rounds of data on cognitive function were selected. Generalized estimation equations were used to analyse the effect of sociodemographic factors on MCI. The detection rates of MCI in adults aged 55 years and above without Alzheimer's disease in 4 provinces of China in 2018 and 2020 were 48.56% and 42.56% respectively. MCI occurred in 30.11% of those with normal cognition(NC) at baseline, and 44.24% of those with MCI at baseline reverted to NC. The risk of MCI increased and the likelihood of MCI reversion decreased with increasing age and decreasing per capita monthly household income. In the baseline NC population, the risk of MCI in the junior high school and above group was 35% lower than that in the illiterate group(RR=0.65, 95%CI 0.53-0.80), the risk of MCI was lower in those living in rural areas(RR=0.56, 95%CI 0.49-0.65), and the risk of MCI was 1.17 times(95%CI 1.03-1.32) higher in those with a history of chronic diseases than in those without it. In the baseline MCI population, the likelihood of MCI reversion increased with education, the likelihood of MCI reversion was 1.04 times higher for workers than for non-workers(95%CI 1.00-1.08). The incidence and reversal rates of MCI were high in adults aged ≥55 years in four provinces of China. Advanced age, low education and low income level are risk factors for cognitive dysfunction.

Baseline Frailty and Domain‐specific Cognitive Declines in Healthy and MCI Older Adults

AbstractBackgroundBoth physical frailty and cognitive decline increase with age and each place adults at elevated risk for loss of independence. Inconsistent associations have been found between frailty and risk for cognitive declines across cognitive domains. However, most studies were cross‐sectional and did not include a comprehensive battery of neuropsychological tests. We hypothesized that frail older adults, whether with or without Mild Cognitive Impairment (MCI) at baseline, are at risk for accelerated domain‐specific cognitive declines.MethodThe Ginkgo Evaluation of Memory Study (GEMS) was a prospective study of 3069 dementia‐free older adults aged 72‐96 years, followed for up to 7.5 years or a diagnosis of dementia, 482 of whom were diagnosed with MCI at baseline. A modified physical frailty phenotype was constructed using GEMS baseline data. A Neuropsychological Battery consisted of 13 tests reflecting global cognition, memory, visual‐spatial construction, language, psychomotor speed/attention, and executive function were administered annually. Linear random effects models were used to compare differences in baseline and rate of change in domain scores among individuals with and without baseline frailty.ResultOverall, frail participants showed poorer baseline cognitive function in all domains, and greater declines in all cognitive domains. When stratified by baseline MCI, among non‐MCI participants, those with frailty revealed poorer baseline psychomotor speed/attention and executive function, and greater declines in all cognitive domains. Among MCI participants, those with frailty exhibited lower baseline visual‐spatial construction, and greater declines in all cognitive domains except for visual‐spatial construction and executive function. In all cognitive domains, the estimated effect of frailty on cognitive decline was greater in MCI participants than non‐MCI participants.ConclusionFrailty was predictive of accelerated cognitive declines across domains and more so in those with baseline MCI. The results from this study highlight the importance of assessing frailty as a risk factor for accelerated cognitive declines, particularly among those at elevated preclinical cognitive risk. These individuals may be at the greatest risk of transitioning to dementia.

Apathy and dysfunction in Lewy Body Disease

AbstractBackgroundStudies in Alzheimer’s disease and frontal temporal lobe dementia have shown high prevalence and persistence of apathy at different disease stages and its strong association with functional decline. Here we use well‐established methods to examine the relationship between apathy and function in a cohort of well‐characterized patients with Lewy Body Disease (LBD) who had regular assessments over time.MethodSample includes participants in the National Alzheimer’s Coordinating Center Uniform Data Set (NACC‐UDS, 9/2005‐12/2019) who had at baseline (1) cognitive status of mild cognitive impairment (MCI) or dementia, (2) presumed etiologic diagnosis of LBD, and (3) ≥1 follow‐up. Baseline diagnosis of Parkinson’s disease (PD) was assessed. Apathy was identified using clinician judgment. Participants’ function was measured using the Functional Assessment Questionnaire (FAQ). Multivariable linear mixed model (LMM) was used to estimate relationships between apathy, cognitive status (baseline MCI vs dementia), and function over time.ResultThe sample included 339 participants with MCI and 748 with dementia. Average age = 72.7±8.3, 74% male, 86% non‐Hispanic white, 15.4±3.4 years of education, baseline MMSE = 23.7±5.8, with 3.4±1.7 years of follow‐up. Proportion of participants who reported difficulty with function at baseline ranged according to task complexity from 48% (Heating water, making a cup of coffee, turning off stove after use) to 85% (Assembling tax records, business affairs, or papers); with total FAQ = 13.0±9.1. Presence of apathy increased from 52% at baseline to 60% at visit 4. Across all follow‐ups, 24% of the participants were never apathetic, 13.7% had apathy intermittently (<50% of all visits), 28.3% persistently (≥50% of all visits), and 34.0% were apathetic at all visits. LMM estimation results showed that, compared to participants who were never apathetic, FAQ was 3.8±0.8 points higher, i.e., greater dysfunction, at baseline in participants who were always apathetic, and 3.3±0.7 points higher in those who had intermittent/persistent apathy (both p<0.001). Rate of functional decline was 0.41±0.3 points faster each year in those always apathetic compared to never apathetic (p<0.1).ConclusionApathy is highly prevalent in individuals with LBD. Independent of cognitive status, more persistent apathy was strongly associated with worse function.

Investigating Potential Racial Differences in Dementia‐Related Plasma Biomarkers

AbstractBackgroundBlack self‐identified individuals are disproportionately affected by dementia, a phenomenon best attributable to differences in social determinants of health (SDOH). Plasma protein levels can serve as antemortem indicators of dementia pathology; recent findings indicate potential race‐specific differences in these biomarkers of tau and non‐tau pathologies between Black self‐identified or White individuals.MethodsThis sample included 568 participants (77, 13.56% Black self‐identified, Table 1) from the Boston University Alzheimer’s Disease and Research Center (BUADRC). Participants completed a battery of neuropsychological tests and cognitive diagnoses were made during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using ELISA methods for YKL‐40 levels and using Simoa platform for phosphorylated tau (p‐tau 181, p‐tau231), total‐tau, glial fibrillary acidic (GFAP), and neurofilament light chain (NfL) levels. ANCOVAs tested for a cross‐sectional association between racial identity and each plasma biomarker and stratified by cognitive impairment status with covariates for age, education (in years), sex assigned at birth, and APOE ε4 carrier status. Cox proportional‐hazards models were used for longitudinal analyses of the interaction effect between racial identity and plasma biomarkers in the risk for conversion from normal cognition (NC) to mild cognitive impairment (MCI) and reversion from MCI to NC.ResultsBaseline YKL‐40 was lower among Black self‐identified participants (adjusted mean diff = 0.37 SD, p<.001); this association was particularly salient within the MCI group (adjusted mean diff = 0.62 SD, p<.001). The longitudinal analysis revealed interaction effects between race and GFAP for risk for conversion from NC to MCI and reversion from MCI to NC. Among White participants, higher GFAP predicted increased risk for conversion from NC to MCI and lower levels predicted reversion. However, no significant effects were found among Black self‐identified participants; these findings might be limited by sample size (n = 18) resulting from the high occurrence of baseline MCI diagnoses and subsequent lack of conversion or reversion among Black self‐identified participants.ConclusionIn the context of an unrepresentative sample, we found trivial differences in plasma biomarkers between Black self‐identified and White participants. Recruitment of Black self‐identified participants representative of the population and further exploration of SDOH is essential in understanding the disproportionate risk for dementia carried by Black self‐identified individuals.

4 Misinterpreting cognitive change over multiple timepoints: When practice effects meet age-related decline

Objective:Practice effects (PE) on cognitive testing impede our ability to accurately assess change. In particular, they hamper the detection of mild cognitive impairment (MCI) and progression to dementia by delaying the point at which test scores fall below diagnostic impairment cutoffs. When decline over time is expected, as with older adults or progressive diseases, failure to adequately address PEs may lead to inaccurate conclusions because PEs artificially boost scores while pathology-related or age-related decline reduces scores. The participant-replacement method accounts for PEs by comparing performance of demographically-matched replacement participants to returnees who have been tested previously. Unlike most methods, the participant-replacement method can separate pathology- or age-related decline from PEs; however, this method has only been used across two timepoints. Neuropsychologists tend to think that PEs level out after the first follow-up, but this issue has not been evaluated in models that allow PEs in the presence of overall decline. Including more than two timepoints makes it possible to determine if PEs level out after the first follow-up, but it is analytically challenging because individuals may not be assessed at every timepoint.Participants and Methods:We examined 1190 older adults in the Alzheimer’s Disease Neuroimaging Initiative who were cognitively unimpaired (n=809) or had MCI (n=381) at baseline. Participants completed six neuropsychological measures (Trails A, Trials B, Boston Naming Test, Category Fluency, Logical Memory, Rey Auditory Verbal Learning Task) at three timepoints (baseline, 12-month, 24-month). We implemented the participant-replacement method using generalized estimating equations in comparisons of matched returnees and replacements to calculate PEs. Propensity scores matched individuals on age, education, sex, and an estimate of premorbid functioning. Generalized estimating equations modeled PEs and age-related decline separately for each cognitive measure.Results:We observed significant PEs for 5 of the 6 measures in the cognitively unimpaired group and 4 measures in the baseline MCI group. PEs did not uniformly decrease across time; some—specifically on episodic memory measures—continued to increase beyond the first follow-up for both groups of participants. Without accounting for PEs, cognitive function appeared to improve or stay the same. In contrast, when PEs were included in the models, cognitive function appeared to decline or stay the same across time.Conclusions:The replacement method of PE adjustment revealed significant PEs across two follow-ups. PEs for episodic memory, in particular, did not level out, but actually increased after the first follow-up, two years after baseline. As expected in these older adults, accounting for PEs revealed cognitive decline, in some cases, even when PE-unadjusted scores improved. This method of assessing PEs, in turn, means earlier detection of cognitive deficits, including progression to MCI, and more accurate characterization of longitudinal change.

Bidirectional association between depressive symptoms and mild cognitive impairment over 20 years: Evidence from the Health and Retirement Study in the United States

BackgroundResearch examining the association between depressive symptoms and mild cognitive impairment (MCI) has yielded conflicting results. This study aimed to examine the bidirectional association between depressive symptoms and MCI, and the extent to which this bidirectional association is moderated by gender and education. MethodsData come from the US Health and Retirement Study over a 20-year period (older adults aged ≥50 years). Competing-risks regression is employed to examine the association between baseline high-risk depressive symptoms and subsequent MCI (N = 9317), and baseline MCI and subsequent high-risk depressive symptoms (N = 9428). Interactions of baseline exposures with gender and education are tested. ResultsAfter full adjustment, baseline high-risk depressive symptoms were significantly associated with subsequent MCI (SHR = 1.20, 95%CI 1.08–1.34). Participants with baseline MCI are more likely to develop subsequent high-risk depressive symptoms than those without baseline MCI (SHR = 1.16, 95%CI 1.01–1.33). Although gender and education are risk factors for subsequent depression and MCI, neither moderates the bidirectional association. LimitationsItems used to construct the composite cognitive measure are limited; selection bias due to missing data; and residual confounding. ConclusionsOur study found a bidirectional association between depressive symptoms and MCI. High-risk depressive symptoms are related to a higher risk of subsequent MCI; and MCI predicts subsequent high-risk depression. Though neither gender nor education moderated the bidirectional association, public health interventions crafted to reduce the risk of depression and MCI should pivot attention to older women and those with less formal education.

Impact of Lifestyle Modification on Glycemic Control and Cognitive Function Among Type II Diabetes Mellitus Patients

Assessing impact of lifestyle modification on Type 2 diabetes mellitus (T2DM) glycemic control and cognitive function. Prospective study was conducted on T2DM patients (92 patients as interventional group and 92 patients conventional therapy). After 6months, significant improvements of HbA1c, oxidant and antioxidant, lipid profile, and cognitive function among only the interventional group (p<0.05). Using logistic analysis, conventional therapy, DM duration >10years, lower education, HbA1c baseline >7 were significant predictive risks for uncontrolled DM (AOR 4.2, 2.9, 2.7and 2.2, respectively). While, conventional therapy, baseline mild cognitive impairment (MCI) and females were significant risks for MCI (AOR 11.5, 10.8and 4.8, respectively). Lifestyle modification is a very important for glycemic control and cognitive function.Clinical Trial Registration: NCT04891887 (ClinicalTrials.gov).

Association of Circulating Caprylic Acid with Risk of Mild Cognitive Impairment and Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Cohort.

Medium-chain fatty acids (MCFAs) can rapidly cross the blood-brain barrier and provide an alternative energy source for the brain. This study aims to determine 1) whether plasma caprylic acid (C8:0) is associated with risk of incident mild cognitive impairment (MCI) among baseline cognitively normal (CN) participants, and incident Alzheimer's Disease (AD) among baseline MCI participants; and 2) whether these associations differ by sex, comorbidity of cardiometabolic diseases, apolipoprotein E (APOE) ε4 alleles, and ADAS-Cog 13. Within the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, plasma C8:0 was measured at baseline in 618 AD-free participants aged 55 to 91. Logistic regression models were used to estimate odds ratios (ORs) and 95% CIs with incident MCI and AD as dependent variables, separately. The inverse association between circulating C8:0 and risk of incident MCI was of borderline significance. The inverse association between circulating levels of C8:0 and risk of incident MCI was significant among CN participants with ≥1 cardiometabolic diseases [OR (95% CI): 0.75 (0.58-0.98) (P=0.03)], those with one copy of APOE ε4 alleles [OR (95% CI): 0.43 (0.21-0.89) (P=0.02)], female [OR (95% CI): 0.60 (0.38-0.94) (P=0.02)], and ADAS-Cog 13 above the median [OR (95%CI): 0.69 (0.50-0.97)(P=0.03)] after adjusting for all covariates. The inverse associations were present only among subgroups of CN participants, including female individuals, those with one or more cardiometabolic diseases, or one APOE ε4 allele, or higher ADAS-Cog 13 scores. If confirmed, this finding will facilitate precision prevention of MCI, in turn, AD among CN older adults.

The association between serum mercury concentration and mild cognitive impairment: the REGARDS study

AbstractBackgroundAnimal studies have demonstrated the toxicology and pathology of mercury in relation to brain function. However, human studies provided mixed findings in relation to cognitive aging. This study aims to examine the association between serum mercury concentration and the incidence of mild cognitive impairment (MCI).MethodParticipants were from a random sub‐cohort (n = 2666) of the REasons for Geographic and Racial Differences in Stroke cohort study (2003–present). After excluding participants with baseline MCI and stroke, and those with missing baseline serum mercury concentration, the final sample size was 2136. Participants were classified into tertiles based on serum mercury concentration (&lt;0.023, 0.023–0.049, and &gt;0.049 µg/dL). MCI was determined primarily based on most recent performance on the enhanced cognitive battery (ECB) containing assessments of Word List Learning, Delayed Recall, Animal Fluency, and letter F Fluency. For those who did not have a score on ECB (n = 474), the Six Item Screener (SIS) was used to determine MCI instead. Therefore, the outcome included three levels: MCI based on the ECB, MCI based on the SIS, and control. Multinomial logistic regression was used to assess serum mercury concentration in relation to incident MCI. We also performed stratified analyses to assess whether gender and race modified the potential associations. All tests were two‐sided with α = 0.05.ResultThe number of participants with MCI on the ECB and SIS were 48 and 36, respectively. After adjustment for the demographic and clinical characteristics in model 2 (Table 1), the direction suggests a positive association between mercury and incident MCI, although this is not statistically significant presumably due to insufficient statistical power (Tertile 3 vs. tertile 1: odds ratio (OR), 1.68; 95% confidence interval (CI), 0.79–3.55; P for trend = 0.025). After further adjustment for fish oil intake, the association became significant (OR: 2.56; 95% CI: 1.003‐6.55; P for trend = 0.043). The observed association was not materially modified by sex or race. We did not observe an association between serum mercury and impairment on SIS.ConclusionThis prospective study suggests that serum mercury concentrations are associated with incident MCI assessed by ECB in US population.

Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49–89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06–1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76–3.61), p < 0.001 for dementia]. Baseline brain age residual was predictive of future cognitive worsening even after adjusting for apolipoprotein E e4 and amyloid status [Hazard Ratio, (95% CI): 1.94 (1.33–2.81), p = 0.001 for total 336 follow-up sample; 2.31 (1.44–3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43–4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment in older adults.

Accounting for practice effects improves stability of MCI diagnosis and uncovers new impairments

AbstractBackgroundWe previously showed that failure to account for practice effects (PEs) delays detection of conversion from unimpaired to mild cognitive impairment (MCI) and reduces diagnostic accuracy based on biomarker positivity data. Even among those who decline, PE can mask steeper declines by inflating cognitive scores. Within MCI samples, PEs may increase reversion rates and impede detection of new impairments. Here, within a baseline MCI sample, we evaluated how PEs affect prevalence, reversion rates, and progression from single‐domain to multi‐domain MCI at follow‐up.MethodWe examined 347 baseline Alzheimer’s Disease Neuroimaging Initiative MCI participants (mean age=73.2; SD=7.4). We used Jak/Bondi diagnostic criteria (6 tests). We also calculated PEs on a cognitive composite (ADAS‐cog 11) and a cognitive screener (MMSE). We identified participants who were demographically matched to returning subjects at their 1‐year follow‐up. The only difference was that one group was tested once and the other had completed prior testing. We subtracted PEs—based on comparing these groups—from follow‐up scores and recalculated MCI diagnoses.ResultPEs were absent or small for 5 tests (Cohen’s d=.00‐.06) and medium for 1 (d=.50). There was a PE on the MMSE (Cohen’s d =.16), but none was found on the ADAS‐cog 11. Accounting for PEs increased MCI prevalence at follow‐up by 6% (252 vs 268), and reduced reversion rate by 15% (95 vs 79). PEs also masked progression from single‐domain to multi‐domain MCI: 24 vs 36 (+50.0% after accounting for PEs).ConclusionAlthough PEs were small, accounting for them in baseline MCI participants after 1‐year, increased MCI prevalence and progression from single‐domain to multi‐domain, and decreased reversion rates. PEs may be masked within a composite measures, but were present on a short cognitive screener. Failure to consider PEs reduces accuracy regarding conclusions about MCI stability/change and weakens our ability to determine when impairment spreads to new domains.

Pet Caretaking and Risk of Mild Cognitive Impairment and Dementia in Older US Adults

ABSTRACT The purpose of this study was to compare risk factors for dementia in pet caretakers and non-pet caretakers in adults aged 50 years and older, and to examine the association between pet caretaking and conversion of normal baseline cognition to mild cognitive impairment (MCI) and conversion of baseline MCI to dementia over a 12-year timespan, accounting for confounding variables. Data were drawn from the Health and Retirement Study, a longitudinal cohort study based on a national probability sample of US adults aged 50 years and older. Study participants included those who reported taking care of a pet (n = 673) and those who reported not taking care of a pet (n = 1,578) for 12 years (2002–2014). As age increased, the odds of pet caretaking decreased, Black participants had lower odds of pet caretaking than White participants, and those engaging in more physical activity had higher odds of pet caretaking, yet those who had diabetes and a history of smoking also had higher odds of pet caretaking. When adjusted for potentially confounding baseline factors, there was no evidence that the risk of MCI among those with normal baseline cognition or dementia among those with baseline MCI differed between pet caretakers and non-caretakers (p = 0.52 and p = 0.39, respectively). This study provides evidence for the associations between pet caretaking with younger age, race (White), and more physical activity in older adults. However, pet caretakers had higher odds of diabetes and history of smoking, and there was no link with incident MCI or dementia. More research is warranted to determine if physically active older adults acquire pets, if pet caretaking improves physical activity, if pets are the reason why older adults with diabetes decide to own pets, and if pets affect diabetes or other health outcomes.

Evaluating the association between latent classes and competing risks outcomes with multiphenotype data.

Latent class analysis is an intuitive tool to characterize disease phenotype heterogeneity. With data more frequently collected on multiple phenotypes in chronic disease studies, it is of rising interest to investigate how the latent classes embedded in one phenotype are related to another phenotype. Motivated by a cohort with mild cognitive impairment (MCI) from the Uniform Data Set (UDS), we propose and study a time-dependent structural model to evaluate the association between latent classes and competing risk outcomes that are subject to missing failure types. We develop a two-step estimation procedure which circumvents latent class membership assignment and is rigorously justified in terms of accounting for the uncertainty in classifying latent classes. The new method also properly addresses the realistic complications for competing risks outcomes, including random censoring and missing failure types. The asymptotic properties of the resulting estimator are established. Given that the standard bootstrapping inference is not feasible in the current problem setting, we develop analytical inference procedures, which are easy to implement. Our simulation studies demonstrate the advantages of the proposed method over benchmark approaches. We present an application to the MCI data from UDS, which uncovers a detailed picture of the neuropathological relevance of the baseline MCIsubgroups.

Predictors of Mild Cognitive Impairment Stability, Progression, or Reversion in the Lothian Birth Cohort 1936.

Background:Mild cognitive impairment (MCI) describes a borderland between healthy cognition and dementia. Progression to and reversion from MCI is relatively common but more research is required to understand the factors affecting this fluidity and improve clinical care interventions.Objective:We explore these transitions in MCI status and their predictive factors over a six-year period in a highly-phenotyped longitudinal study, the Lothian Birth Cohort 1936.Methods:MCI status was derived in the LBC1936 at ages 76 (n = 567) and 82 years (n = 341) using NIA-AA diagnostic guidelines. Progressions and reversions between healthy cognition and MCI over the follow-up period were assessed. Multinomial logistic regression assessed the effect of various predictors on the likelihood of progressing, reverting, or maintaining cognitive status.Results:Of the 292 participants who completed both time points, 41 (14%) participants had MCI at T1 and 56 (19%) at T2. Over the follow-up period, 74%remained cognitively healthy, 12%transitioned to MCI, 7%reverted to healthy cognition, and 7%maintained their baseline MCI status. Findings indicated that membership of these transition groups was affected by age, cardiovascular disease, and number of depressive symptoms.Conclusion:Findings that higher baseline depressive symptoms increase the likelihood of reverting from MCI to healthy cognition indicate that there may be an important role for the treatment of depression for those with MCI. However, further research is required to identify prevention strategies for those at high risk of MCI and inform effective interventions that increase the likelihood of reversion to, and maintenance of healthy cognition.

MRI decline pattern in early onset MCI due to Alzheimer’s disease

AbstractBackgroundStructural neuroimaging longitudinal studies in Alzheimer’s disease (AD) have consistently defined a “cortical signature” of gray matter loss. Apparently, early‐onset AD (EOAD) has a greater density of amyloid, a more generalized atrophy and a more aggressive evolution than late‐onset AD (LOAD). We hypothesize EOAD would show pronounced longitudinal cortical atrophy, especially in associative areas like precuneus and in addition to temporal lobe loss.MethodsWe investigate longitudinal 3T‐MRI structural data from the Alzheimer’s disease Neuroimaging Initiative (ADNI) 2 cohort. We included patients aged ≤65 years with a baseline mild cognitive impairment (MCI) diagnosis. According to AD biomarkers at baseline, patients were divided into MCI due to AD with high likelihood (MCI‐AD) and MCI unlikely due to AD (MCI‐nonAD). We downloaded the summary of longitudinal measures for volume and cortical thickness. We used linear mixed effects in SPSS25 with data at baseline and month 24 to compare atrophy progression between groups. We focused on “AD's cortical signature”, including entorhinal, inferior temporal, middle temporal, inferior parietal, fusiform areas, and also precuneus and posterior cingulate. In addition, we studied volume of hippocampus (HpV) and total subcortical supratentorial (SSupratV). We tested for group by time interactions and significance level was set at p&lt;0.05, FDR corrected.ResultsWe included 22 MCI‐AD and 26 MCI‐nonAD patients. MMSE mean score was lower in MCI‐AD [Table1]. MCI‐AD had significant lower baseline Cth in precuneus, middle temporal and entorhinal and lower HpV. At group by time interactions, MCI‐AD showed significant greater CTh atrophy in middle temporal, enthorhinal and posterior cingulate, and higher volume decrease in HpV and SSupratV than MCI‐nonAD [Figure1]. Notably, the rest of areas studied were not significantly different at baseline or at group by time effects.ConclusionCompared to MCI‐nonAD, MCI‐AD showed greater decline in only some of the areas previously defined as the cortical AD signature and in hippocampal volume and global subcortical volume. The study could be biased by the small sample size, by the age being close to LOAD and by no stratification by clinical symptoms. Further analyses are needed to understand AD atrophy progression pattern in relation to age at onset.

Predicting Mental Decline Rates in Mild Cognitive Impairment From Baseline MRI Volumetric Data.

In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whether volumetric data from baseline magnetic resonance imaging (MRI) can predict accelerated cognitive decline. The authors retrospectively examined Alzheimer Disease Neuroimaging Initiative data to obtain serial Mini-Mental Status Exam (MMSE) scores, diagnoses, and the following baseline MRI volumes: total intracranial volume, whole-brain and ventricular volumes, and volumes of the hippocampus, entorhinal cortex, fusiform gyrus, and medial temporal lobe. Subjects with <24 months or <4 measurements of MMSE data were excluded. Predictive modeling of fast cognitive decline (defined as >0.6/year) from baseline volumetric data was performed on subjects with MCI using a single hidden layer neural network. Among 698 baseline MCI subjects, the median annual decline in the MMSE score was 1.3 for converters to dementia versus 0.11 for stable MCI (P<0.001). A 0.6/year threshold captured dementia conversion with 82% accuracy (sensitivity 79%, specificity 85%, area under the receiver operating characteristic curve 0.88). Regional volumes on baseline MRI predicted fast cognitive decline with a test accuracy of 71%. An MMSE score decrease of >0.6/year is associated with MCI-to-dementia conversion and can be predicted from baseline MRI.

Assessment of Speech Understanding After Cochlear Implantation in Adult Hearing Aid Users

Cochlear implants were approved for use in adults in the 1980s, but use remains low owing to a lack of awareness regarding cochlear implantation candidacy criteria and expected outcomes. There have been limited, small series examining the safety and effectiveness of cochlear implantation in adult hearing aid (HA) users with and without mild cognitive impairment (MCI). To investigate the safety and effectiveness of a single-ear cochlear implant in a group of optimized adult HA users with and without MCI across a variety of domains. In this nonrandomized controlled trial, a multicenter, prospective, repeated-measures investigation was conducted at 13 US institutions. The setting was academic and community-based cochlear implant programs. Eligible participants were 100 adults (aged >18 years) with postlinguistic onset of bilateral moderate sloping to profound or worse sensorineural hearing loss (≤20 years' duration). Fluent English speakers underwent an optimized bilateral HA trial for at least 30 days. Individuals with aided Consonant-Vowel Nucleus-Consonant (CNC) word score in quiet of 40% or less correct in the ear to be implanted and 50% or less correct in the contralateral ear were offered cochlear implants. The first participant was enrolled on February 20, 2017, and the last participant was enrolled on May 3, 2018. The final follow-up was on December 21, 2018. Participants received the same cochlear implant system and contralateral HA. The primary outcome measure was speech understanding in quiet (CNC word score) using both the cochlear implant and opposite ear HA. Secondary outcome measures included the following: adverse events; speech understanding in noise (AzBio signal-to-noise ratio of +10 db [+10 SNR]) Health Utilities Index Mark 3 (HUI3); Speech, Spatial, and Qualities of Hearing Questionnaire 49 (SSQ49); and Montreal Cognitive Assessment (MoCA). The median age at cochlear implantation of the 96 patients included in the trial was 71 years (range, 23-91 years), and 62 patients (65%) were male. Three serious adverse events requiring revision surgery occurred, and all resolved without sequelae. By 6 months after activation, the absolute marginal mean change in CNC word score and AzBio +10 SNR was 40.5% (95% CI, 35.9%-45.0%) and 24.1% (95% CI, 18.9%-29.4%), respectively. Ninety-one percent (87 of 96) of participants had a clinically important improvement (>15%) in the CNC word score in the implant ear. Mild cognitive impairment (MoCA total score ≤25) was observed in 48 of 81 study participants (59%) at baseline. Speech perception marginal mean improvements were similar between individuals with and without baseline MCI, with values of 40.9% (95% CI, 35.2%-46.6%) and 39.6% (95% CI, 31.8%-47.4%), respectively, for CNC word score and 27.5% (95% CI, 21.0%-33.9%) and 17.8% (95% CI, 9.0%-26.6%), respectively, for AzBio +10 SNR. Statistically significant and clinically important improvements in the HUI3 and SSQ49 were evident at 6 months. The findings of this nonrandomized controlled trial seem to indicate that cochlear implants are safe and effective in restoring speech understanding in both quiet and noise and improve quality of life in individuals with and without MCI. ClinicalTrials.gov Identifier: NCT03007472.

Predicting Alzheimer's disease based on survival data and longitudinally measured performance on cognitive and functional scales

This study assessed how well longitudinally taken cognitive and functional scales from people with mild cognitive impairment (MCI) predict conversion to Alzheimer's disease (AD). Participants were individuals with baseline MCI from the Alzheimer's Disease Neuroimaging Initiative. Scales included the Alzheimer Disease Assessment Scale-Cognitive (ADAS-Cog) 11 and 13, the Mini Mental State Examination (MMSE), and the Functional Assessment Questionnaire (FAQ). A joint modelling approach compared performance on the four scales for dynamic prediction of risk for AD. The goodness of fit measures included log likelihood, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The area under the curve (AUC) of the receiver operating characteristic assessed predictive accuracy. The parameter α in the ADAS-Cog11, ADAS-Cog13, MMSE, and FAQ joint models was statistically significant. Joint MMSE and FAQ models had better goodness of fit. FAQ had the best predictive accuracy. Cognitive and functional impairment assessment scales are strong screening predictors when repeated measures are available. They could be useful for predicting risk for AD in primary healthcare.

Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences

IntroductionWhile Alzheimer’s disease (AD) is divided into severity stages, mild cognitive impairment (MCI) remains a solitary construct despite clinical and prognostic heterogeneity. This study aimed to characterize differences in genetic, cerebrospinal fluid (CSF), neuroimaging, and neuropsychological markers across clinician-derived MCI stages.MethodsVanderbilt Memory & Aging Project participants with MCI were categorized into 3 severity subtypes at screening based on neuropsychological assessment, functional assessment, and Clinical Dementia Rating interview, including mild (n = 18, 75 ± 8 years), moderate (n = 89 72 ± 7 years), and severe subtypes (n = 18, 78 ± 8 years). At enrollment, participants underwent neuropsychological testing, 3T brain magnetic resonance imaging (MRI), and optional fasting lumbar puncture to obtain CSF. Neuropsychological testing and MRI were repeated at 18-months, 3-years, and 5-years with a mean follow-up time of 3.3 years. Ordinary least square regressions examined cross-sectional associations between MCI severity and apolipoprotein E (APOE)-ε4 status, CSF biomarkers of amyloid beta (Aβ), phosphorylated tau, total tau, and synaptic dysfunction (neurogranin), baseline neuroimaging biomarkers, and baseline neuropsychological performance. Longitudinal associations between baseline MCI severity and neuroimaging and neuropsychological trajectory were assessed using linear mixed effects models with random intercepts and slopes and a follow-up time interaction. Analyses adjusted for baseline age, sex, race/ethnicity, education, and intracranial volume for MRI models.ResultsStages differed at baseline on APOE-ε4 status (early < middle = late; p-values < 0.03) and CSF Aβ (early > middle = late), phosphorylated and total tau (early = middle < late; p-values < 0.05), and neurogranin concentrations (early = middle < late; p-values < 0.05). MCI stage related to greater longitudinal cognitive decline, hippocampal atrophy, and inferior lateral ventricle dilation (early < late; p-values < 0.03).DiscussionClinician staging of MCI severity yielded longitudinal cognitive trajectory and structural neuroimaging differences in regions susceptible to AD neuropathology and neurodegeneration. As expected, participants with more severe MCI symptoms at study entry had greater cognitive decline and gray matter atrophy over time. Differences are likely attributable to baseline differences in amyloidosis, tau, and synaptic dysfunction. MCI staging may provide insight into underlying pathology, prognosis, and therapeutic targets.

Mild cognitive impairment in Aboriginal Australians.

IntroductionAboriginal Australians have among the highest rates of dementia worldwide, yet no study has investigated the subtypes, risk factors, or longer term outcomes of mild cognitive impairment (MCI) in this population.MethodsA total of 336 community‐dwelling Aboriginal Australians aged ≥60 years participated in a longitudinal study, completing a structured interview at baseline. MCI (amnestic subtype, aMCI; non‐amnestic subtype, naMCI) and dementia were diagnosed via cognitive screening, medical assessment, and clinical consensus. Associations between life‐course factors and baseline MCI subtypes were examined using logistic regression. Conversion to dementia was assessed at 6‐year follow‐up.ResultsPrevalent aMCI (n = 24) was associated with older age (odds ratio [OR] = 1.68, 95% confidence interval [CI]: 1.12 to 2.53), head injury (OR = 3.19, 95% CI: 1.35 to 7.56), symptoms of depression (OR = 1.52, 95% CI: 1.04 to 2.24), and lower blood pressure (OR = 0.53, 95% CI: 0.33 to 0.86). Prevalent naMCI (n = 29) was associated with low education (OR = 4.46, 95% CI: 1.53 to 13.05), unskilled work history (OR = 5.62, 95% CI: 2.07 to 13.90), higher body mass index (OR = 1.99, 95% CI: 1.30 to 3.04), and moderate to severe hearing loss (OR = 2.82, 95% CI: 1.06 to 7.55). A small proportion of MCI cases reverted to intact at follow‐up (15%), but most remained stable (44%), developed dementia and/or died (41%).DiscussionSociodemographic and clinical factors both contributed to baseline MCI and were distinct for MCI subtypes, with similar patterns of conversion to dementia for amnestic and non‐amnestic MCI.