Mild cognitive impairment: Long-term course of four clinical subtypes

Undernutrition, cognitive decline and dementia: The collaborative PROMED-COG pooled cohorts study

BACKGROUND & AIMS

Undernutrition may negatively impact cognitive function, but evidence of this relationship is not yet consolidated. Under the "PROtein enriched MEDiterranean diet to combat undernutrition and promote healthy neuroCOGnitive ageing" (PROMED-COG) project, we evaluated the association between undernutrition, and cognitive decline and incident dementia in older adults.

METHODS

Retrospective data harmonization was performed on three Italian population-based studies: the Italian Longitudinal Study of Ageing (ILSA), the Progetto Veneto Anziani (Pro.V.A.), and the Bollate Eye Study-Follow-Up (BEST-FU). The associations between undernutrition, operationalized using the Global Leadership Initiative on Malnutrition (GLIM) criteria, and decline on the Mini-Mental State Examination (MMSE) or dementia incidence follow-up were evaluated with Cox proportional hazard regression models.

RESULTS

The pooled cohort comprised 9071 individuals (52% females) aged between 42 and 101 years. The prevalence of undernutrition at the baseline was 14.3%, significantly higher among females (15.4% vs 13%) and in older age, ranging from 3.5% in those aged <60 years to 28.8% in those 85+ years. Undernutrition was associated with both cognitive decline over a median 8.3-year follow-up (Hazard Ratio (HR) 1.20, 95% Confidence Interval (CI) 1.02-1.41, p = 0.028) and incidence of dementia over a median 8.6-year follow-up (HR = 1.57, 95%CI 1.01-2.43, p = 0.046). For cognitive decline, the association with undernutrition was more marked in males than females (HR = 1.36, 95%CI 1.05-1.77, p = 0.019 vs HR = 1.10, 95% CI 0.89-1.36, p = 0.375).

CONCLUSION

Undernutrition is prevalent among older people and is associated with an increased risk of experiencing cognitive decline and dementia. The prevention and early identification of undernutrition could be an important nonpharmacologic strategy to counteract neurodegeneration.

Association study of brain structure-function coupling and glymphatic system function in patients with mild cognitive impairment due to Alzheimer's disease

Background

Mild cognitive impairment (MCI) is a critical transitional phase from healthy cognitive aging to dementia, offering a unique opportunity for early intervention. However, few studies focus on the correlation of brain structure and functional activity in patients with MCI due to Alzheimer's disease (AD). Elucidating the complex interactions between structural-functional (SC-FC) brain connectivity and glymphatic system function is crucial for understanding this condition.

Method

The aims of this study were to explore the relationship among SC-FC coupling values, glymphatic system function and cognitive function. 23 MCI patients and 18 healthy controls (HC) underwent diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). DTI analysis along the perivascular space (DTI-ALPS) index and SC-FC coupling values were calculated using DTI and fMRI. Correlation analysis was conducted to assess the relationship between Mini-Mental State Examination (MMSE) scores, DTI-ALPS index, and coupling values. Receiver operating characteristic (ROC) curves was conducted on the SC-FC coupling between the whole brain and subnetworks. The correlation of coupling values with MMSE scores was also analyzed.

Result

MCI patients (67.74 ± 6.99 years of age) exhibited significantly lower coupling in the whole-brain network and subnetworks, such as the somatomotor network (SMN) and ventral attention network (VAN), than HCs (63.44 ± 6.92 years of age). Whole-brain network coupling was positively correlated with dorsal attention network (DAN), SMN, and visual network (VN) coupling. MMSE scores were significantly positively correlated with whole-brain coupling and SMN coupling. In MCI, whole-brain network demonstrated the highest performance, followed by the SMN and VAN, with the VN, DAN, limbic network (LN), frontoparietal network (FPN), and default mode network (DMN). Compared to HCs, lower DTI-ALPS index was observed in individuals with MCI. Additionally, the left DTI-ALPS index showed a significant positive correlation with MMSE scores and coupling values in the whole-brain network and SMN.

Conclusion

These findings reveal the critical role of SC-FC coupling values and the ALPS index in cognitive function of MCI. The positive correlations observed in the left DTI-ALPS and whole-brain and SMN coupling values provide a new insight for investigating the asymmetrical nature of cognitive impairments.

Different MMSE domains are associated to cognitive decline and education

The Mini-Mental State Examination (MMSE) is a long-established test to screen for dementia, estimate the severity and monitor the progression of cognitive impairment. The MMSE total score is dependent upon demographic factors, particularly education, but little is known about how education influences the 6 distinct MMSE cognitive domains. The present study aims to understand how the performances in the MMSE cognitive domains reflect clinical diagnosis and educational level. The study recruited 1043 participants, comprising 388 healthy controls, 360 patients with Mild Cognitive Impairment (MCI) and 295 patients with dementia. The association of the MMSE cognitive domains scores with clinical diagnosis (healthy, MCI, dementia) and educational level (primary education, middle school, high school and university/college) was analyzed with a multivariate ordinal regression model. The scores in all MMSE domains were generally higher in healthy controls as compared to patients with MCI, and higher in these as compared to patients with dementia. The MMSE domain Constructional ability was associated to the education level, the domains Orientation, Recall and Language were associated to diagnosis, Attention and calculation was associated to both education level and diagnosis, and Registration was not associated to either education or diagnosis. In conclusion, impairment in specific MMSE domains pinpoints cognitive decline, probably indicating brain areas affected by neurodegeneration, and impairment in others reflects lower education levels and the lack of acquisition of relevant schooling abilities.

Association between physical activity, peak expiratory flow, and cognitive function in aging: a cross-sectional analysis

BACKGROUND

The aging global population is experiencing escalating challenges related to cognitive deficits and dementia. This study explored the interplay between pulmonary function, physical activity, and cognitive function in older U.S. adults to identify modifiable risk factors for cognitive decline.

METHODS

Utilizing NHANES 2011-2012 data, we conducted a cross-sectional analysis of 729 participants aged ≥ 60 years. Cognitive function, peak expiratory flow (PEF), and physical activity were assessed. Weighted logistic regression and mediation analyses were employed to examine associations.

RESULTS

The sample size was 729 (weighted mean [SD] age, 67.1 [5.3] years; 53.6% female participants). Preliminary correlation analysis indicated a positive correlation between the global cognitive score and physical activity (β = 0.16; p < 0.001), recreational activity (β = 0.22; p < 0.001), and PEF in percent predicted (PEF%) (β = 0.18; p < 0.001). Compared to those with a PEF% >100%, the PEF% (80-100%) group (OR, 2.66; 95% CI, 1.34-5.29; p = 0.005) and PEF% <80% group (OR, 3.36; 95% CI, 1.67-6.76; p = 0.001) were significantly associated with higher cognitive deficits risk. Recreational activity meeting guidelines was linked to a lower risk of cognitive deficits (OR, 0.24; 95% CI, 0.10-0.57; p = 0.001). Mediation analysis demonstrated that PEF mediates the relationship between physical activity and cognitive function.

CONCLUSION

This study revealed significant associations between lower PEF, diminished physical activity, and increased cognitive deficits in elderly individuals. The results supported the hypothesis that pulmonary function may mediate the connection between activity and cognitive health, emphasizing the importance of respiratory health in cognitive aging. Recognizing these associations is crucial for clinical care and public health policy aiming to mitigate cognitive decline in aging populations. While these findings are intriguing, validation through longitudinal design studies is deemed necessary.

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment

Objectives

Accurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI.

Methods

We recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-β (Aβ) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network.

Results

The proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aβ (+) than with Aβ (-).

Conclusion

The proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

Fasting Plasma Glucose Levels and Longitudinal Motor and Cognitive Outcomes in Parkinson's Disease Patients

OBJECTIVE

Hyperglycemia and diabetes mellitus have been identified as poor prognostic factors for motor and nonmotor outcomes in patients with Parkinson's disease (PD), although there is some controversy with this finding. In the present study, we investigated the effects of fasting plasma glucose (FPG) levels on longitudinal motor and cognitive outcomes in PD patients.

METHODS

We included a total of 201 patients who were diagnosed with PD between January 2015 and January 2020. The patients were categorized based on FPG level into euglycemia (70 mg/dL < FPG < 100 mg/dL), intermediate glycemia (100 mg/dL ≤ FPG < 126 mg/dL), and hyperglycemia (FPG ≥ 126 mg/dL), and longitudinal FPG trajectories were analyzed using group-based trajectory modeling. Survival analysis was conducted to determine the time until motor outcome (Hoehn and Yahr stage ≥ 2) and the conversion from normal cognition to mild cognitive impairment.

RESULTS

Among the patient cohort, 82 had euglycemia, 93 had intermediate glycemia, and 26 had hyperglycemia. Intermediate glycemia (hazard ratio 1.747, 95% confidence interval [CI] 1.083-2.816, p = 0.0221) and hyperglycemia (hazard ratio 3.864, 95% CI 1.996-7.481, p < 0.0001) were found to be significant predictors of worsening motor symptoms. However, neither intermediate glycemia (hazard ratio 1.183, 95% CI 0.697-2.009, p = 0.5339) nor hyperglycemia (hazard ratio 1.297, 95% CI 0.601-2.800, p = 0.5078) demonstrated associations with the longitudinal progression of cognitive impairment. Diabetes mellitus, defined by self-reported medical history, was not related to poor motor or cognitive impairment outcomes.

CONCLUSION

Our.

RESULTS

suggest that both impaired glucose tolerance and hyperglycemia could be associated with motor progression in PD patients.

Determining optimal cutoff scores of Cognitive Abilities Screening Instrument to identify dementia and mild cognitive impairment in Taiwan

BACKGROUND

The early detection of dementia depends on efficient methods for the assessment of cognitive capacity. Existing cognitive screening tools are ill-suited to the differentiation of cognitive status, particularly when dealing with early-stage impairment.

METHODS

The study included 8,979 individuals (> 50 years) with unimpaired cognitive functions, mild cognitive impairment (MCI), or dementia. This study sought to determine optimal cutoffs values for the Cognitive Abilities Screening Instrument (CASI) aimed at differentiating between individuals with or without dementia as well as between individuals with or without mild cognitive impairment. Cox proportional hazards models were used to evaluate the value of CASI tasks in predicting conversion from MCI to all-cause dementia, dementia of Alzheimer's type (DAT), or to vascular dementia (VaD).

RESULTS

Our optimized cutoff scores achieved high accuracy in differentiating between individuals with or without dementia (AUC = 0.87-0.93) and moderate accuracy in differentiating between CU and MCI individuals (AUC = 0.67 - 0.74). Among individuals without cognitive impairment, scores that were at least 1.5 × the standard deviation below the mean scores on CASI memory tasks were predictive of conversion to dementia within roughly 2 years after the first assessment (all-cause dementia: hazard ratio [HR] = 2.81 - 3.53; DAT: 1.28 - 1.49; VaD: 1.58). Note that the cutoff scores derived in this study were lower than those reported in previous studies.

CONCLUSION

Our results in this study underline the importance of establishing optimal cutoff scores for individuals with specific demographic characteristics and establishing profiles by which to guide CASI analysis.

A randomized placebo-controlled trial of nicotinamide riboside in older adults with mild cognitive impairment

Nicotinamide riboside (NR) increases blood levels of NAD+, a cofactor central to energy metabolism, and improves brain function in some rodent models of neurodegeneration. We conducted a placebo-controlled randomized pilot study with the primary objective of determining safety of NR in older adults with mild cognitive impairment (MCI). Twenty subjects with MCI were randomized to receive placebo or NR using dose escalation to achieve, and maintain, a final dose of 1 g/day over a 10-week study duration. The primary outcome was post-treatment change from baseline measures of cognition (Montreal Cognitive Assessment, MoCA). Predefined secondary outcomes included post-treatment changes in cerebral blood flow (CBF); blood NAD+ levels; and additional neurocognitive, psychometric, and physical performance tests. DNA methylation was assessed in peripheral blood mononuclear cells (PBMCs) as an exploratory outcome. The target NR dose was safely achieved as evidenced by a 2.6-fold increase in blood NAD+ in the NR group (p < 0.001, 95% CI [17.77, 43.49]) with no between-group difference in adverse event reporting. MoCA and other neurocognitive and psychometric metrics remained stable throughout the study. NR reduced CBF in the default mode network (DMN) with greatest differences observed in the left inferior parietal lobe (IPL) (DMN p = 0.013, μ = 0.92, 95% CI [0.23, 1.62]; left IPL p = 0.009, μ = 1.66, 95% CI [0.5, 2.82]). Walking speed in the placebo group significantly improved across the study duration suggestive of a practice effect but did not change in the NR group (p = 0.0402 and p = 0.4698, respectively). Other secondary outcome measures remained stable. Global methylation analyses indicated a modest NR-associated increase in DNA methylation and concomitant reduction in epigenetic age as measured by PhenoAge and GrimAge epigenetic clock analyses. In summary, NR significantly increased blood NAD+ concentrations in older adults with MCI. NR was well tolerated and did not alter cognition. While CBF was reduced by NR treatment, statistical significance would not have withstood multiple comparisons correction. A larger trial of longer duration is needed to determine the potential of NR as a strategy to improve cognition and alter CBF in older adults with MCI. ClinicalTrials.gov NCT02942888.

Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter-cohort validation of Shanghai Memory Study and ADNI

Mild cognitive impairment (MCI) is a critical prodromal stage of Alzheimer's disease (AD), and the mechanism underlying the conversion is not fully explored. Construction and inter-cohort validation of imaging biomarkers for predicting MCI conversion is of great challenge at present, due to lack of longitudinal cohorts and poor reproducibility of various study-specific imaging indices. We proposed a novel framework for inter-cohort MCI conversion prediction, involving comparison of structural, static, and dynamic functional brain features from structural magnetic resonance imaging (sMRI) and resting-state functional MRI (fMRI) between MCI converters (MCI_C) and non-converters (MCI_NC), and support vector machine for construction of prediction models. A total of 218 MCI patients with 3-year follow-up outcome were selected from two independent cohorts: Shanghai Memory Study cohort for internal cross-validation, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for external validation. In comparison with MCI_NC, MCI_C were mainly characterized by atrophy, regional hyperactivity and inter-network hypo-connectivity, and dynamic alterations characterized by regional and connectional instability, involving medial temporal lobe (MTL), posterior parietal cortex (PPC), and occipital cortex. All imaging-based prediction models achieved an area under the curve (AUC) > 0.7 in both cohorts, with the multi-modality MRI models as the best with excellent performances of AUC > 0.85. Notably, the combination of static and dynamic fMRI resulted in overall better performance as relative to static or dynamic fMRI solely, supporting the contribution of dynamic features. This inter-cohort validation study provides a new insight into the mechanisms of MCI conversion involving brain dynamics, and paves a way for clinical use of structural and functional MRI biomarkers in future.

Prevalence and associated factors of mild cognitive impairment among middle-aged and older adults: Results of the first phase of Ardakan Cohort Study on Aging

Background and Aims

Data on mild cognitive impairment (MCI) in low- to middle-income countries are still being determined, despite the fact that most future older adults are expected to reside in these regions. This study aimed to investigate the prevalence and associated factors of MCI in Iran.

Methods

A cross-sectional study was conducted on 4938 community-dwelling subjects aged 50 years or above in the first wave of the Ardakan Cohort Study on Aging. MCI was evaluated using the Mini-Mental State Examination (MMSE) and the Abbreviated Mental Test Score (AMTS) in literate and illiterate individuals. The relationship between factors associated with the odds of MCI was assessed through logistic regression.

Results

The prevalence of MCI among all participants, the literates and illiterates, was 15.8%, 6.3%, and 36.4%, respectively. It was found that failure to accomplish any of the MMSE or AMTS items was significantly related to MCI (p < 0.001). Age ([odds ratio (OR): 1.05; p < 0.001 in the literates], [OR: 1.06; p < 0.001 in the illiterates]), sex (OR: 0.13; p < 0.001 in the illiterates), history of stroke ([OR: 2.86; p = 0.006 in the literates], [OR: 2.04; p = 0.045 in the illiterates]), and depression ([OR: 1.87; p < 0.001 in the literates], [OR: 1.41; p = 0.008 in the illiterates]) were significantly associated with MCI.

Conclusion

This study highlights the significant associations between age, education, depression, stroke, and MCI in Iranian participants. These findings emphasize the need for targeted interventions in low-literacy populations, mental health screening, and stroke prevention strategies to mitigate the burden of MCI and enhance cognitive health.

Multiple sclerosis lesions that impair memory map to a connected memory circuit

BACKGROUND

Nearly 1 million Americans are living with multiple sclerosis (MS) and 30-50% will experience memory dysfunction. It remains unclear whether this memory dysfunction is due to overall white matter lesion burden or damage to specific neuroanatomical structures. Here we test if MS memory dysfunction is associated with white matter lesions to a specific brain circuit.

METHODS

We performed a cross-sectional analysis of standard structural images and verbal memory scores as assessed by immediate recall trials from 431 patients with MS (mean age 49.2 years, 71.9% female) enrolled at a large, academic referral center. White matter lesion locations from each patient were mapped using a validated algorithm. First, we tested for associations between memory dysfunction and total MS lesion volume. Second, we tested for associations between memory dysfunction and lesion intersection with an a priori memory circuit derived from stroke lesions. Third, we performed mediation analyses to determine which variable was most associated with memory dysfunction. Finally, we performed a data-driven analysis to derive de-novo brain circuits for MS memory dysfunction using both functional (n = 1000) and structural (n = 178) connectomes.

RESULTS

Both total lesion volume (r = 0.31, p < 0.001) and lesion damage to our a priori memory circuit (r = 0.34, p < 0.001) were associated with memory dysfunction. However, lesion damage to the memory circuit fully mediated the association of lesion volume with memory performance. Our data-driven analysis identified multiple connections associated with memory dysfunction, including peaks in the hippocampus (T = 6.05, family-wise error p = 0.000008), parahippocampus, fornix and cingulate. Finally, the overall topography of our data-driven MS memory circuit matched our a priori stroke-derived memory circuit.

CONCLUSIONS

Lesion locations associated with memory dysfunction in MS map onto a specific brain circuit centered on the hippocampus. Lesion damage to this circuit fully mediated associations between lesion volume and memory. A circuit-based approach to mapping MS symptoms based on lesions visible on standard structural imaging may prove useful for localization and prognosis of higher order deficits in MS.

Greater executive dysfunction in patients post-COVID-19 compared to those not infected

BACKGROUND

A number of patients post-coronavirus disease-19 (COVID-19) report cognitive impairment (CI), even months after acute infection. We aimed to assess if COVID-19 is associated with increased incidence of CI in comparison to controls.

METHODS

We analyzed data from the Mount Sinai Health System Post-COVID-19 Registry in New York City, a prospective cohort of patients post-COVID-19 ≥18 years of age and non-infected controls. CI was defined by scores ≥ 1.0 standard deviation below population norms, and was assessed using well-validated measures of attention, working memory, processing speed, executive functioning/cognitive flexibility, language, learning, and memory. Logistic regression models assessed odds for CI in each domain in patients post-COVID-19 vs. controls after adjusting for potential confounders. In exploratory analyses, we assessed odds for CI by site of acute COVID-19 care as a proxy for disease severity.

FINDINGS

417 patients post-COVID-19 and 151 controls (mean age 49 years, 63% female, 21% Black, 17% Latinx) were included. In adjusted analyses, patients were significantly more likely than controls to have CI in executive functioning (odds ratio [OR]: 2.19; 95% confidence interval [CI]: 1.03 to 4.67), particularly those treated in outpatient (OR: 2.22; 95% CI: 1.02 to 4.82) and inpatient hospital (OR: 3.59; 95% CI: 1.27 to 10.16) settings. There were no significant associations between CI in other domains and history of COVID-19 or site of acute care.

INTERPRETATION

Patients post-COVID-19 have greater odds of executive dysfunction, suggesting that focused cognitive screening may be prudent, even in those with mild to moderate disease. Studies should explore the pathophysiology and potential treatments for CI in this population.

FUNDING

This work was funded by the Icahn School of Medicine at Mount Sinai.

Current Challenges in the Diagnosis of Progressive Neurocognitive Disorders: A Critical Review of the Literature and Recommendations for Primary and Secondary Care

Screening for early symptoms of cognitive impairment enables timely interventions for patients and their families. Despite the advances in dementia diagnosis, the current nosography of neurocognitive disorders (NCDs) seems to overlook some clinical manifestations and predictors that could contribute to understanding the conversion from an asymptomatic stage to a very mild one, eventually leading to obvious disease. The present review examines different diagnostic approaches in view of neurophysiological and neuropsychological evidence of NCD progression, which may be subdivided into: (1) preclinical stage; (2) transitional stage; (3) prodromal or mild stage; (4) major NCD. The absence of univocal criteria and the adoption of ambiguous or narrow labels might complicate the diagnostic process. In particular, it should be noted that: (1) only neuropathological hallmarks characterize preclinical NCD; (2) transitional NCD must be assessed through proactive neuropsychological protocols; (3) prodromal/mild NCDs are based on cognitive functional indicators; (4) major NCD requires well-established tools to evaluate its severity stage; (5) insight should be accounted for by both patient and informants. Therefore, the examination of evolving epidemiological and clinical features occurring at each NCD stage may orient primary and secondary care, allowing for more targeted prevention, diagnosis, and/or treatment of both cognitive and functional impairment.

Virtually-Delivered Emotion Focused Mindfulness Therapy (EFMT) Group vs. Wait-List Control for Late-Life Anxiety: A Randomized Controlled Trial

BACKGROUND

The worldwide annual prevalence of anxiety in older adults is estimated to be between 6% and 10%. Emotion Focused Mindfulness Therapy (EFMT) is a mindfulness-based group intervention that has been demonstrated to reduce symptoms of anxiety in community dwelling adults. No study has yet assessed EFMT for older adults with late-life anxiety. The aim of this study was to determine the feasibility of video-delivered group EFMT for older adults living in community settings, a novel and potentially scalable intervention.

METHODS

This was a feasibility randomized controlled trial (RCT) of 48 older adults (≥55 years old), recruited through primary care, community organizations and snowball methods. Participants were randomized to group EFMT delivered by Zoom vs. a wait-list control. Data were collected at baseline (T1), 9 weeks following baseline (T2, primary study endpoint) and 17 weeks following baseline (T3). Random allocation was conducted immediately after each group of 12 participants had been enrolled into the trial, with groups beginning on a rolling basis each time a block of 12 participants had been enrolled. The main efficacy outcome examined changes over time to anxiety.

RESULTS

Recruitment was successfully completed in 32 weeks. Enrollment was calculated at 62.3% (48 of 77 people screened). Retention (80.0%) and adherence (100.0% for intervention group participants) were excellent. The EFMT group had significant improvements in anxiety at T2 compared to the wait-list control group (-3.47 [4.12] vs.-1.22 [3.25] points, p = 0.05).

CONCLUSIONS

Virtually-delivered EFMT appears to be a feasible, acceptable, and efficacious group treatment to improve late-life anxiety.

Characterizing mild cognitive impairment to predict incident dementia in adults with bipolar disorder: What should the benchmark be?

Objective: Although mild cognitive impairment (MCI) is generally considered a risk state for dementia, its prevalence and association with dementia are impacted by the number of tests and cut-points used to assess cognition and define "impairment," and sources of norms. Here, we investigate how these methodological variations impact estimates of incident dementia in adults with bipolar disorder (BD), a vulnerable population with pre-existing cognitive deficits and increased dementia risk. Method: Neuropsychological data from 148 adults with BD and 13,610 healthy controls (HC) were drawn from the National Alzheimer's Coordinating Center. BD participants' scores were standardized against published norms and again using regression-based norms generated from HC within the same catchment area as individual BD patients ("site-specific norms"), varying the number of within-domain tests (one vs. two) and the cut-points (-1 vs. -1.5 SD) used to operationalize MCI. Results: Site-specific norms were more sensitive to incident dementia (88.6%-94.3%) than published norms (74.3%-88.6%), but only when using a "single test" definition of impairment. Specificity (22.1%-74.3%), accuracy (37.8%-68.9%), and positive predictive values (26.1%-38.3%) were overall poor. Applying a "single test" definition of impairment resulted in better negative predictive values using site-specific (92.3%-93.3%) than published norms (83.6%-86.2%), and a substantial increase in relative risk of incident dementia relative to published norms. Conclusions: Neuropsychologists should define "impairment" as scores below -1.0 or -1.5 SD on at least two within-domain measures when using published norms to interpret cognitive performance in adults with BD.

Rates of Undiagnosed Cognitive Impairment and Performance on the Montreal Cognitive Assessment Among Older Adults in Primary Care

BACKGROUND

The number of adults in the USA with cognitive impairment is increasing; however, few studies report prevalence rates of undiagnosed cognitive impairment among older adults in primary care.

OBJECTIVE

To determine the prevalence of undiagnosed cognitive impairment among adults ages 55 years and older in primary care settings and provide normative data for the Montreal Cognitive Assessment in this context.

DESIGN

Single interview, observational study.

PARTICIPANTS

English-speaking adults ages 55 years and older without diagnoses of cognitive impairment recruited from primary care practices in New York City, NY, and Chicago, IL (n = 872).

MAIN MEASURES

Montreal Cognitive Assessment (MoCA). Undiagnosed cognitive impairment was defined by age and education adjusted z-scores more than 1.0 and 1.5 standard deviations below published norms, corresponding to mild or moderate to severe cognitive impairment, respectively.

KEY RESULTS

The mean age was 66.8 (8.0) years, 44.7% were male, 32.9% were Black or African-American, and 29.1% were Latinx. Undiagnosed cognitive impairment was identified in 20.8% of subjects (mild impairment, 10.5%; moderate-severe impairment, 10.3%). Impairment at any level of severity was associated in bivariate analyses with several patient characteristics, most notably for race and ethnicity (White, non-Latinx, 6.9% vs. Black, non-Latinx, 26.8%, Latinx, 28.2%, other race, 21.9%; p < 0.0001), place of birth (US 17.5% vs. non-US 30.7%, p < 0.0001), depression (33.1% vs. no depression, 18.1%; p < 0.0001), and impairment in activities of daily living (≥ 1 ADL impairment, 34.0% vs. no ADL impairment, 18.2%; p < 0.0001).

CONCLUSIONS

Undiagnosed cognitive impairment is common among urban dwelling older adults attending primary care practices, and was associated with several patient characteristics, including non-White race and ethnicity and depression. Normative data for the MoCA from this study may serve as a useful resource for studies of similar patient populations.

Blood Kallikrein-8 and Non-Amnestic Mild Cognitive Impairment: An Exploratory Study

Background: Blood kallikrein-8 is supposed to be a biomarker for mild cognitive impairment (MCI) due to Alzheimer’s disease (AD), a precursor of AD dementia. Little is known about the association of kallikrein-8 and non-AD type dementias. Objective: To investigate whether blood kallikrein-8 is elevated in individuals with non-amnestic MCI (naMCI), which has a higher probability to progress to a non-AD type dementia, compared with cognitively unimpaired (CU) controls. Methods: We measured blood kallikrein-8 at ten-year follow-up (T2) in 75 cases and 75 controls matched for age and sex who were participants of the population-based Heinz Nixdorf Recall study (baseline: 2000–2003). Cognitive performance was assessed in a standardized manner at five (T1) and ten-year follow-up. Cases were CU or had subjective cognitive decline (SCD) at T1 and had naMCI at T2. Controls were CU at both follow-ups. The association between kallikrein-8 (per 500 pg/ml increase) and naMCI was estimated using conditional logistic regression: odds ratios (OR) and 95% confidence intervals (95% CI) were determined, adjusted for inter-assay variability and freezing duration. Results: Valid kallikrein-8 values were measured in 121 participants (45% cases, 54.5% women, 70.5±7.1 years). In cases, the mean kallikrein-8 was higher than in controls (922±797 pg/ml versus 884±782 pg/ml). Kallikrein-8 was not associated with having naMCI compared to being CU (adjusted; OR: 1.03 [95% CI: 0.80–1.32]). Conclusion: This is the first population-based study that shows that blood kallikrein-8 tends not to be elevated in individuals with naMCI compared with CU. This adds to the evidence of the possible AD specificity of kallikrein-8.

Modular Level Alterations Of Structural-Functional Connectivity Coupling in Mild Cognitive Impairment Patients and Interactions with Age Effect

BACKGROUND

Structural-functional connectivity (SC- FC) coupling is related to various cognitive functions and more sensitive for the detection of subtle brain alterations.

OBJECTIVE

To investigate whether decoupling of SC-FC was detected in mild cognitive impairment (MCI) patients on a modular level, the interaction effect of aging and disease, and its relationship with network efficiency.

METHODS

73 patients with MCI and 65 healthy controls were enrolled who underwent diffusion tensor imaging and resting-state functional MRI to generate structural and functional networks. Five modules were defined based on automated anatomical labeling 90 atlas, including default mode network (DMN), frontoparietal attention network (FPN), sensorimotor network (SMN), subcortical network (SCN), and visual network (VIS). Intra-module and inter-module SC-FC coupling were compared between two groups. The interaction effect of aging and group on modular SC-FC coupling was further analyzed by two-way ANOVA. The correlation between the coupling and network efficiency was finally calculated.

RESULTS

In MCI patients, aberrant intra-module coupling was noted in SMN, and altered inter-module coupling was found in the other four modules. Intra-module coupling exhibited significant age-by-group effects in DMN and SMN, and inter-module coupling showed significant age-by-group effects in DMN and FPN. In MCI patients, both positive or negative correlations between coupling and network efficiency were found in DMN, FPN, SCN, and VIS.

CONCLUSION

SC-FC coupling could reflect the association of SC and FC, especially in modular levels. In MCI, SC-FC coupling could be affected by the interaction effect of aging and disease, which may shed light on advancing the pathophysiological mechanisms of MCI.

Use of Intrinsic Capacity Domains as a Screening Tool in Public Health

The World Health Organization (WHO) created the concept of Integrated Care for Older People and one of its constructs is intrinsic capacity (IC). The study aimed to carry out a screening with the tools designated by the WHO to assess the IC domains and whether they can be used as indicators for decision-making on integrated care for older people based on risk categorization. The interaction between the risk category and the domain scores was verified. One hundred and sixty three (163) community-dwelling older people of both genders were evaluated. Domains assessed: cognitive, psychological, vitality, locomotion, and sensory. Scores indicating a low, moderate and high risk were assigned to each domain. For all domains, there were individuals in all risk groups. Effect of risk on the domains: cognitive [χ²(2) = 134.042; p < 0.001], psychological [χ²(2) = 92.865; p < 0.001], vitality [χ²(2) = 129.564; p < 0.001], locomotion [χ²(2) = 144.101; p < 0.001], and sensory [χ²(2) = 129.037; p < 0.001]. Scores of the CI domains were affected by the risk category. There were individuals in all risk groups, demonstrating the importance of screening as a public health strategy, making it possible to know which risk category each elderly person belongs to and thus develop strategies in the short-, medium- and long-term.

Musical and psychomotor interventions for cognitive, sensorimotor, and cerebral decline in patients with Mild Cognitive Impairment (COPE): a study protocol for a multicentric randomized controlled study

BACKGROUND

Regular cognitive training can boost or maintain cognitive and brain functions known to decline with age. Most studies administered such cognitive training on a computer and in a lab setting. However, everyday life activities, like musical practice or physical exercise that are complex and variable, might be more successful at inducing transfer effects to different cognitive domains and maintaining motivation. "Body-mind exercises", like Tai Chi or psychomotor exercise, may also positively affect cognitive functioning in the elderly. We will compare the influence of active music practice and psychomotor training over 6 months in Mild Cognitive Impairment patients from university hospital memory clinics on cognitive and sensorimotor performance and brain plasticity. The acronym of the study is COPE (Countervail cOgnitive imPairmEnt), illustrating the aim of the study: learning to better "cope" with cognitive decline.

METHODS

We aim to conduct a randomized controlled multicenter intervention study on 32 Mild Cognitive Impairment (MCI) patients (60-80 years), divided over 2 experimental groups: 1) Music practice; 2) Psychomotor treatment. Controls will consist of a passive test-retest group of 16 age, gender and education level matched healthy volunteers. The training regimens take place twice a week for 45 min over 6 months in small groups, provided by professionals, and patients should exercise daily at home. Data collection takes place at baseline (before the interventions), 3, and 6 months after training onset, on cognitive and sensorimotor capacities, subjective well-being, daily living activities, and via functional and structural neuroimaging. Considering the current constraints of the COVID-19 pandemic, recruitment and data collection takes place in 3 waves.

DISCUSSION

We will investigate whether musical practice contrasted to psychomotor exercise in small groups can improve cognitive, sensorimotor and brain functioning in MCI patients, and therefore provoke specific benefits for their daily life functioning and well-being.

TRIAL REGISTRATION

The full protocol was approved by the Commission cantonale d'éthique de la recherche sur l'être humain de Genève (CCER, no. 2020-00510) on 04.05.2020, and an amendment by the CCER and the Commission cantonale d'éthique de la recherche sur l'être humain de Vaud (CER-VD) on 03.08.2021. The protocol was registered at clinicaltrials.gov (20.09.2020, no. NCT04546451).

Screening of Mild Cognitive Impairment Through Conversations With Humanoid Robots: Exploratory Pilot Study

BACKGROUND

The rising number of patients with dementia has become a serious social problem worldwide. To help detect dementia at an early stage, many studies have been conducted to detect signs of cognitive decline by prosodic and acoustic features. However, many of these methods are not suitable for everyday use as they focus on cognitive function or conversational speech during the examinations. In contrast, conversational humanoid robots are expected to be used in the care of older people to help reduce the work of care and monitoring through interaction.

OBJECTIVE

This study focuses on early detection of mild cognitive impairment (MCI) through conversations between patients and humanoid robots without a specific examination, such as neuropsychological examination.

METHODS

This was an exploratory study involving patients with MCI and cognitively normal (CN) older people. We collected the conversation data during neuropsychological examination (Mini-Mental State Examination [MMSE]) and everyday conversation between a humanoid robot and 94 participants (n=47, 50%, patients with MCI and n=47, 50%, CN older people). We extracted 17 types of prosodic and acoustic features, such as the duration of response time and jitter, from these conversations. We conducted a statistical significance test for each feature to clarify the speech features that are useful when classifying people into CN people and patients with MCI. Furthermore, we conducted an automatic classification experiment using a support vector machine (SVM) to verify whether it is possible to automatically classify these 2 groups by the features identified in the statistical significance test.

RESULTS

We obtained significant differences in 5 (29%) of 17 types of features obtained from the MMSE conversational speech. The duration of response time, the duration of silent periods, and the proportion of silent periods showed a significant difference (P<.001) and met the reference value r=0.1 (small) of the effect size. Additionally, filler periods (P<.01) and the proportion of fillers (P=.02) showed a significant difference; however, these did not meet the reference value of the effect size. In contrast, we obtained significant differences in 16 (94%) of 17 types of features obtained from the everyday conversations with the humanoid robot. The duration of response time, the duration of speech periods, jitter (local, relative average perturbation [rap], 5-point period perturbation quotient [ppq5], difference of difference of periods [ddp]), shimmer (local, amplitude perturbation quotient [apq]3, apq5, apq11, average absolute differences between the amplitudes of consecutive periods [dda]), and F0cov (coefficient of variation of the fundamental frequency) showed a significant difference (P<.001). In addition, the duration of response time, the duration of silent periods, the filler period, and the proportion of fillers showed significant differences (P<.05). However, only jitter (local) met the reference value r=0.1 (small) of the effect size. In the automatic classification experiment for the classification of participants into CN and MCI groups, the results showed 66.0% accuracy in the MMSE conversational speech and 68.1% accuracy in everyday conversations with the humanoid robot.

CONCLUSIONS

This study shows the possibility of early and simple screening for patients with MCI using prosodic and acoustic features from everyday conversations with a humanoid robot with the same level of accuracy as the MMSE.

A Critical Review of Neuropsychological Actuarial Criteria for Mild Cognitive Impairment

BACKGROUND

The concept of mild cognitive impairment (MCI) has evolved since its original conception. So, too, have MCI diagnostic methods, all of which have varying degrees of success in identifying individuals at risk of conversion to dementia. The neuropsychological actuarial method is a straightforward diagnostic approach that has shown promise in large datasets in identifying individuals with MCI who are likely to have progressive courses. This method has been increasingly applied in various iterations and samples, raising questions of how best to apply this method and when caution should be used.

OBJECTIVE

Our objective was to review the literature investigating use of the neuropsychological actuarial method to diagnose MCI to identify strengths and weaknesses of this approach, as well as highlight areas for further research.

METHODS

Databases PubMed and PsychInfo were systematically searched for studies that compared the neuropsychological actuarial method to some other diagnostic method.

RESULTS

We identified 13 articles and extracted relevant study characteristics and findings. Existing literature was reviewed and integrated, with focus on the neuropsychological actuarial method's performance relative to existing diagnostic methods/criteria as well as associations with longitudinal outcomes and biomarkers. Tables with pertinent methodological information and general findings are also provided.

CONCLUSION

The neuropsychological actuarial method to diagnose MCI has shown utility some in large-scale homogenous databases compared to research criteria. However, its standing relative to consensus diagnostic methods is unclear, and emerging evidence suggests the neuropsychological actuarial method may be more prone to diagnostic errors in more demographically diverse populations.

Neurocognitive Operations Underlying Working Memory Abilities: An Analysis of Latency and Time-Based Parameters

BACKGROUND

The theory of executive attention (Fuster, 2015) suggests considerable plasticity regarding when specific neurocognitive operations are recruited to bring executive tasks to fruition.

OBJECTIVE

We tested the hypothesis that differing neurocognitive operations are recruited upon the initiation of a response, but that other distinct neurocognitive operations are recruited towards the middle or end of a response.

METHODS

The Backward Digit Span Test (BDST) was administered to 58 memory clinic patients (MCI, n = 22; no-MCI, n = 36). Latency to generate all correct 5-span responses was obtained. Statistical analyses found that optimal group classification was achieved using the first and third digit backward. First and third response latencies were analyzed in relation to verbal working memory (WM), visual WM, processing speed, visuospatial operations, naming/lexical access, and verbal episodic memory tests.

RESULTS

For the first response, slower latencies were associated with better performance in relation to verbal WM and visuospatial test performance. For the third response, faster latencies were associated with better processing speed and visuospatial test performance.

CONCLUSION

Consistent with the theory of executive attention, these data show that the neurocognitive operations underlying successful executive test performance are not monolithic but can be quite nuanced with differing neurocognitive operations associated with specific time epochs. Results support the efficacy of obtaining time-based latency parameters to help disambiguate successful executive neurocognitive operations in memory clinic patients.

The Early Stage of Abnormal Aging: Cognitive Impairment

Cognitive impairment has become an important aspect affecting the health and quality of life of middle-aged and elderly people, which is defined as the difficulty of thought processing and leads to memory loss, difficulties making decisions, the inability to concentrate, and difficulties learning. The process of cognitive ability decline with age goes through subjective cognitive impairment (SCI) to mild cognitive impairment (MCI). There is abundant evidence supporting the link between cognitive impairment and several modifiable risk factors, such as physical activity, social activity, mental activity, higher education, and management of cardiovascular risk factors (diabetes, obesity, smoking, hypertension, and obesity). Meanwhile, these factors also provide a new perspective for the prevention of cognitive impairment and dementia.

Mild cognitive impairment among rural-dwelling older adults in China: A community-based study

BACKGROUND

Epidemiological studies of mild cognitive impairment (MCI) and subtypes of MCI have rarely focused on rural residents in China.

METHODS

This population-based study included 5068 participants (age ≥60 years) who were living in rural communities. We defined MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) following the Petersen's criteria that integrated neuropsychological assessments with in-person clinical evaluations.

RESULTS

The overall prevalence of MCI, aMCI, and naMCI was 26.48%, 22.30%, and 4.18%, respectively. The prevalence of MCI increased with age. The adjusted odds ratio (OR) of MCI was 0.71 (95% confidence interval [CI] 0.61 to 0.82) for primary school (vs. illiteracy), 0.30 (0.24 to 0.39) for middle school or above, 1.35 (1.09 to 1.67) for being farmers, 0.65 (0.54 to 0.78) for alcohol consumption, 1.43 (1.20 to 1.70) for stroke history, and 1.14 (0.95 to 1.36) for any apolipoprotein E (APOE) ε4 allele (vs ε3/ε3).

CONCLUSIONS

MCI affects over one-fourth of rural older adults in China. Overall MCI was associated with demographic factors, non-alcohol consumption, and stroke, but not with APOE genotype and cardiometabolic factors.

Amyloid-β PET in Alzheimer's disease: A systematic review and Bayesian meta-analysis

BACKGROUND

In recent years, longitudinal studies of Alzheimer's disease (AD) have been successively concluded. Our aim is to determine the efficacy of amyloid-β (Aβ) PET in diagnosing AD and early prediction of mild cognitive impairment (MCI) converting to AD. By pooling studies from different centers to explore in-depth whether diagnostic performance varies by population type, radiotracer type, and diagnostic approach, thus providing a more comprehensive theoretical basis for the subsequent widespread application of Aβ PET in the clinical setting.

METHODS

Relevant studies were searched through PubMed. The pooled sensitivities, specificities, DOR, and the summary ROC curve were obtained based on a Bayesian random-effects model.

RESULTS

Forty-eight studies, including 5967 patients, were included. Overall, the pooled sensitivity, specificity, DOR, and AUC of Aβ PET for diagnosing AD were 0.90, 0.80, 35.68, and 0.91, respectively. Subgroup analysis showed that Aβ PET had high sensitivity (0.91) and specificity (0.81) for differentiating AD from normal controls but very poor specificity (0.49) for determining AD from MCI. The pooled sensitivity and specificity were 0.84 and 0.62, respectively, for predicting the conversion of MCI to AD. The differences in diagnostic efficacy between visual assessment and quantitative analysis and between 11 C-PIB PET and 18 F-florbetapir PET were insignificant.

CONCLUSIONS

The overall performance of Aβ PET in diagnosing AD is favorable, but the differentiation between MCI and AD patients should consider that some MCI may be at risk of conversion to AD and may be misdiagnosed. A multimodal diagnostic approach and machine learning analysis may be effective in improving diagnostic accuracy.

Alterations of amplitude of low-frequency fluctuations and fractional amplitude of low-frequency fluctuations in end-stage renal disease on maintenance dialysis: An activation likelihood estimation meta-analysis

BACKGROUND

Cognitive impairment (CI) is a common complication of end-stage renal disease (ESRD). Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have identified abnormal spontaneous low-frequency brain activity in ESRD dialysis patients. However, these studies have reported inconsistent results. So far, no meta-analyses on this topic have been published. This meta-analysis aimed to identify the more consistently vulnerable brain regions in ESRD patients at rest and to reveal its possible neuropathophysiological mechanisms.

METHODS

We systematically searched PubMed, Cochrane Library, Web of Science, Medline, and EMBASE databases up to July 20, 2022 based on the amplitude of low-frequency fluctuation (ALFF) or fractional amplitude of low-frequency fluctuation (fALFF). Brain regions with abnormal spontaneous neural activity in ESRD compared to healthy controls (HCs) from previous studies were integrated and analyzed using an activation likelihood estimation (ALE) method. Jackknife sensitivity analysis was carried out to assess the reproducibility of the results.

RESULTS

In total, 11 studies (380 patients and 351 HCs) were included in the final analysis. According to the results of the meta-analysis, compared with HCs, ESRD patients had decreased ALFF/fALFF in the right precuneus, right cuneus, and left superior temporal gyrus (STG), while no brain regions with increased brain activity were identified. Jackknife sensitivity analysis showed that our results were highly reliable.

CONCLUSION

Compared to HCs, ESRD dialysis patients exhibit significant abnormalities in spontaneous neural activity associated with CI, occurring primarily in the default mode network, visual recognition network (VRN), and executive control network (ECN). This contributes to the understanding of its pathophysiological mechanisms.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022348694].

Working memory assessment using cambridge neuropsychological test automated battery can help in the diagnosis of mild cognitive impairment: a systematic review and meta-analysis

ABSTRACT Mild cognitive impairment (MCI) is an interstitial state between normal aging and dementia. Objective: In this study, we investigated working memory (WM) profiles of MCI patients using the Cambridge Neuropsychological Test Automated Battery (CANTAB). We also examined the diagnostic accuracy and possible associated factors as secondary outcomes of the study. Methods: We conducted an electronic search on EMBASE, PubMed, and ScienceDirect databases. Studies with MCI participants and using CANTAB battery subtests for the assessment of WM were included. Meta-analysis was conducted using the CMA2 software. Results: Out of 1537 records, 14 studies were covered in this systematic review, and 7 of them were included in the meta-analysis. There was a significant difference between MCI patients and healthy controls in spatial working memory (SWM) (SDM: 0.535; 95%CI 11–96; p-value=0.014), spatial span (SSP) (SDM: 0.649 95%CI 0.297–0.100; p-value<0.01), and rapid visual information processing (RVP) (SDM: 0.52; 95%CI 0.386–0.654; p-value<0.01). WM function of MCI patients was associated with the cerebrospinal fluid (CSF) levels of tau-protein and amyloid-beta (Aβ). Conclusions: WM is an impaired cognitive domain in MCI. CANTAB WM subtests including SSP, SWM, and RVP are accurate enough to be used as a proper assessment tool for the diagnosis of MCI in clinical settings. Tau-protein and Aβ are associated with lower WM scores in MCI patients; however, sex, age, psychiatric disorders, apolipoprotein 4 allele, and functional activity scores cannot affect WM.

Subjective cognitive decline, mild cognitive impairment, and dementia - syndromic approach: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

ABSTRACT This consensus, performed by the Brazilian Academy of Neurology (BAN) will approach practically how to evaluate patients with cognitive complaints and how to clinically and etiologically diagnose the three clinical syndromes associated with the different stages of cognitive decline: subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia. This BAN consensus discusses SCD diagnosis for the first time, updates MCI and dementia diagnoses, recommends the adequate cognitive tests and the relevant etiological work-up and care of patients with cognitive decline at different levels of care within the Brazilian Unified Health System. We also review the main assessment instruments used in Brazil and Latin America.

Declínio cognitivo subjetivo, comprometimento cognitivo leve e demência - diagnóstico sindrômico: recomendações do Departamento Científico de Neurologia Cognitiva e do Envelhecimento da Academia Brasileira de Neurologia

RESUMO Este consenso realizado pela Academia Brasileira de Neurologia (ABN) abordará de maneira prática como avaliar pacientes com queixas cognitivas e como realizar o diagnóstico clínico e etiológico das três síndromes clínicas associadas aos estágios de declínio cognitivo: declínio cognitivo subjetivo (DCS), comprometimento cognitivo leve (CCL) e demência. O diagnóstico de DCS é discutido pela primeira vez em consenso da ABN e as atualizações para o diagnóstico de CCL e demência são abordadas, bem como a recomendação para o uso de testes cognitivos apropriados, investigação etiológica pertinente e cuidados aos pacientes com declínio cognitivo nos diferentes níveis de atenção do Sistema Único de Saúde. Foi realizada pesquisa dos principais instrumentos de avaliação utilizados em nosso meio e na América Latina.

Prediction of conversion to dementia using interpretable machine learning in patients with amnestic mild cognitive impairment

Purpose

Amnestic mild cognitive impairment (aMCI) is a transitional state between normal aging and Alzheimer's disease (AD). However, not all aMCI patients are observed to convert to AD dementia. Therefore, developing a predictive algorithm for the conversion of aMCI to AD dementia is important. Parametric methods, such as logistic regression, have been developed; however, it is difficult to reflect complex patterns, such as non-linear relationships and interactions between variables. Therefore, this study aimed to improve the predictive power of aMCI patients' conversion to dementia by using an interpretable machine learning (IML) algorithm and to identify the factors that increase the risk of individual conversion to dementia in each patient.

Methods

We prospectively recruited 705 patients with aMCI who had been followed-up for at least 3 years after undergoing baseline neuropsychological tests at the Samsung Medical Center between 2007 and 2019. We used neuropsychological tests and apolipoprotein E (APOE) genotype data to develop a predictive algorithm. The model-building and validation datasets were composed of data of 565 and 140 patients, respectively. For global interpretation, four algorithms (logistic regression, random forest, support vector machine, and extreme gradient boosting) were compared. For local interpretation, individual conditional expectations (ICE) and SHapley Additive exPlanations (SHAP) were used to analyze individual patients.

Results

Among the four algorithms, the extreme gradient boost model showed the best performance, with an area under the receiver operating characteristic curve of 0.852 and an accuracy of 0.807. Variables, such as age, education, the scores of visuospatial and memory domains, the sum of boxes of the Clinical Dementia Rating scale, Mini-Mental State Examination, and APOE genotype were important features for creating the algorithm. Through ICE and SHAP analyses, it was also possible to interpret which variables acted as strong factors for each patient.

Conclusion

We were able to propose a predictive algorithm for each aMCI individual's conversion to dementia using the IML technique. This algorithm is expected to be useful in clinical practice and the research field, as it can suggest conversion with high accuracy and identify the degree of influence of risk factors for each patient.

A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease

In clinical practice, several standardized neuropsychological tests have been designed to assess and monitor the neurocognitive status of patients with neurodegenerative diseases such as Alzheimer's disease. Important research efforts have been devoted so far to the development of multivariate machine learning models that combine the different test indexes to predict the diagnosis and prognosis of cognitive decline with remarkable results. However, less attention has been devoted to the explainability of these models. In this work, we present a robust framework to (i) perform a threefold classification between healthy control subjects, individuals with cognitive impairment, and subjects with dementia using different cognitive indexes and (ii) analyze the variability of the explainability SHAP values associated with the decisions taken by the predictive models. We demonstrate that the SHAP values can accurately characterize how each index affects a patient's cognitive status. Furthermore, we show that a longitudinal analysis of SHAP values can provide effective information on Alzheimer's disease progression.

Multivariate Base Rates of Low Neuropsychological Test Scores in Cognitively Intact Older Adults with Subjective Cognitive Decline from a Specialist Memory Clinic

OBJECTIVE

To avoid misdiagnosing mild cognitive impairment (MCI), knowledge of the multivariate base rates (MVBRs) of low scores on neuropsychological tests is crucial. Base rates have typically been determined from normative population samples, which may differ from clinically referred samples. The current study addresses this limitation by calculating the MVBR of low or high cognitive scores in older adults who presented to a memory clinic experiencing subjective cognitive decline but were not diagnosed with MCI.

METHOD

We determined the MVBRs on the Kaplan-Baycrest Neurocognitive Assessment for 107 cognitively healthy older adults (M age = 75.81), by calculating the frequency of patients producing n scores below or above different cut-off values (i.e., 1, 1.5, 2.0, 2.5 SD from the mean), stratifying by education and gender.

RESULTS

Performing below or above cut-off was common, with more stringent cut-offs leading to lower base rates (≥1 low scores occurred in 84.1% of older adults at -1 SD, 55.1% at -1.5 SD, and 39.3% at -2 SD below the mean; ≥1 high scores occurred in 80.4% of older adults at +1 SD, 35.5% at +1.5 SD, and 16.8% at +2 SD above the mean). Higher education was associated with varying base rates. Overall, the MVBR of obtaining a low cognitive test score was higher in this clinic sample, compared with prior studies of normative samples.

CONCLUSIONS

MVBRs for clinically referred older adults experiencing memory complaints provide a diagnostic benefit, helping to prevent attributing normal variability to cognitive impairment and limiting false positive diagnoses.

Incremental diagnostic value of 18F-Fluetemetamol PET in differential diagnoses of Alzheimer's Disease-related neurodegenerative diseases from an unselected memory clinic cohort

To evaluate the incremental diagnostic value of 18F-Flutemetamol PET following MRI measurements on an unselected prospective cohort collected from a memory clinic. A total of 84 participants was included in this study. A stepwise study design was performed including initial analysis (based on clinical assessments), interim analysis (revision of initial analysis post-MRI) and final analysis (revision of interim analysis post-18F-Flutemetamol PET). At each time of evaluation, every participant was categorized into SCD, MCI or dementia syndromal group and further into AD-related, non-AD related or non-specific type etiological subgroup. Post 18F-Flutemetamol PET, the significant changes were seen in the syndromal MCI group (57%, p < 0.001) involving the following etiological subgroups: AD-related MCI (57%, p < 0.01) and non-specific MCI (100%, p < 0.0001); and syndromal dementia group (61%, p < 0.0001) consisting of non-specific dementia subgroup (100%, p < 0.0001). In the binary regression model, amyloid status significantly influenced the diagnostic results of interim analysis (p < 0.01). 18F-Flutemetamol PET can have incremental value following MRI measurements, particularly reflected in the change of diagnosis of individuals with unclear etiology and AD-related-suspected patients due to the role in complementing AD-related pathological information.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

DWI-based MR thermometry: could it discriminate Alzheimer's disease from mild cognitive impairment and healthy subjects?

PURPOSE

The aim of this study is to compare lateral ventricular cerebrospinal fluid (CSF) temperature of the patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy subjects (HS) using diffusion-weighted imaging (DWI)-based magnetic resonance (MR) thermometry.

METHODS

Seventy-two patients (37 AD, 19 MCI, 16 HS) who underwent 3-T MR examination from September 2018 to August 2019 were included in this study. Smoking habits, education level, disease duration, and comorbidity status were recorded. Patients were assessed using Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating (CDR) score. Brain temperatures were measured using DWI-based MR thermometry. Group comparisons of brain temperature were performed using the Pearson chi-square, Mann-Whitney, and Kruskal-Wallis tests. Further analysis was performed using the post hoc Bonferroni test. Receiver operating characteristic (ROC) analysis was also used.

RESULTS

A CDR score of 0.5, 1, and 2 was 2 (5.4%), 14 (37.8%), and 21 (56.8%) in AD, respectively. The median MMSE score had significant differences among groups and also in pairwise comparisons. The median CSF temperature (°C) values showed statistically significant difference among groups (HS: 38.5 °C, MCI: 38.17 °C, AD: 38.0 °C). The post hoc Mann-Whitney U test indicated a significant difference between AD patients and HS (p = 0.009). There were no significant CSF temperature differences in other pairwise comparisons.

CONCLUSION

Lower CSF temperatures were observed in AD patients than in HS, probably due to decreased brain metabolism in AD. DWI-based MR thermometry as a noninvasive imaging method enabling the measurement of CSF temperatures may contribute to the diagnosis of AD.

Effect of intensive blood pressure control on subtypes of mild cognitive impairment and risk of progression from SPRINT study

BACKGROUND

To examine the effect of intensive blood pressure control on the occurrence of subtypes of mild cognitive impairment (MCI) and determine the risk of progression to dementia or death.

METHODS

Secondary analysis of a randomized trial of community-dwelling adults (≥50 years) with hypertension. Participants were randomized to a systolic blood pressure (SBP) goal of <120 mm Hg (intensive treatment; n = 4678) or <140 mm Hg (Standard treatment; n = 4683). Outcomes included adjudicated MCI, MCI subtype (amnestic, non-amnestic, multi-domain, single domain), and probable dementia. Multistate survival models were used to examine transitions in cognitive status accounting for the competing risk of death.

RESULTS

Among 9361 randomized participants (mean age, 67.9 years; 3332 women [35.6%]), 640 participants met the protocol definition for MCI, with intensive treatment reducing the risk of MCI overall (hazard ratio [HR], 0.81 [95% confidence interval {CI}, 0.69-0.94]), as previously reported. This effect was largely reflected in amnestic subtypes (HR, 0.78 [95% CI, 0.66-0.92]) and multi-domain subtypes (HR, 0.78 [95% CI, 0.65-0.93]). An adjudication of MCI, as compared with normal cognitive function, substantially increased the probability of progressing to probable dementia (5.9% [95% CI: 4.5%-7.7%] vs. 0.6% [95% CI: 0.3%-0.9%]) and to death (10.0% [95% CI: 8.3%-11.9%] vs. 2.3% [95% CI: 2.0%-2.7%]) within 2 years.

CONCLUSIONS

Intensive treatment reduced the risk for amnestic and multi-domain subtypes of MCI. An adjudication of MCI was associated with increased risk of progression to dementia and death, highlighting the relevance of MCI as a primary outcome in clinical and research settings.

Brain network hierarchy reorganization in Alzheimer's disease: A resting‐state functional magnetic resonance imaging study

Hierarchy is a fundamental organizational principle of the human brain network. Whether and how the network hierarchy changes in Alzheimer's disease (AD) remains unclear. To explore brain network hierarchy alterations in AD and their clinical relevance. Forty‐nine healthy controls (HCs), 49 patients with mild cognitive impairment (MCI), and 49 patients with AD were included. The brain network hierarchy of each group was depicted by connectome gradient analyses. We assessed the network hierarchy changes by comparing the gradient values in each network across the AD, MCI, and HC groups. Whole‐brain voxel‐level gradient values were compared across the AD, MCI, and HC groups to identify abnormal brain regions. Finally, we examined the relationships between altered gradient values and clinical features. In the secondary gradient, the posterior default mode network (DMN) gradient values decreased significantly in patients with AD compared with HCs. Regionally, compared with HCs, both MCI and AD groups showed that most of the brain regions with increased gradient values were located in anterior DMN, while most of the brain regions with decreased gradient values were located in posterior DMN. The decrease of gradients in the left middle occipital gyrus was associated with better logical memory performance. The increase of gradients in the right middle frontal gyrus was associated with lower rates of dementia. The network hierarchy changed characteristically in patients with AD and was closely related to memory function and disease severity. These results provide a novel view for further understanding the underlying neuro‐mechanisms of AD.

Hippocampal Volumes in Amnestic and Non-Amnestic Mild Cognitive Impairment Types Using Two Common Methods of MCI Classification

OBJECTIVES

Mild cognitive impairment (MCI) types may have distinct neuropathological substrates with hippocampal atrophy particularly common in amnestic MCI (aMCI). However, depending on the MCI classification criteria applied to the sample (e.g., number of abnormal test scores considered or thresholds for impairment), volumetric findings between MCI types may change. Additionally, despite increased clinical use, no prior research has examined volumetric differences in MCI types using the automated volumetric software, Neuroreader™.

METHODS

The present study separately applied the Petersen/Winblad and Jak/Bondi MCI criteria to a clinical sample of older adults (N = 82) who underwent neuropsychological testing and brain MRI. Volumetric data were analyzed using Neuroreader™ and hippocampal volumes were compared between aMCI and non-amnestic MCI (naMCI).

RESULTS

T-tests revealed that regardless of MCI classification criteria, hippocampal volume z-scores were significantly lower in aMCI compared to naMCI (p's < .05), and hippocampal volume z-scores significantly differed from 0 (Neuroreader™ normative mean) in the aMCI group only (p's < .05). Additionally, significant, positive correlations were found between measures of delayed recall and hippocampal z-scores in aMCI using either MCI classification criteria (p's < .05).

CONCLUSIONS

We provide evidence of correlated neuroanatomical changes associated with memory performance for two commonly used neuropsychological MCI classification criteria. Future research should investigate the clinical utility of hippocampal volumes analyzed via Neuroreader™ in MCI.

Risk of conversion from mild cognitive impairment to dementia in low- and middle-income countries: A systematic review and meta-analysis

Introduction

With no treatment for dementia, there is a need to identify high risk cases to focus preventive strategies, particularly in low- and middle-income countries (LMICs) where the burden of dementia is greatest. We evaluated the risk of conversion from mild cognitive ompairment (MCI) to dementia in LMICs.

Methods

Medline, Embase, PsycINFO, and Scopus were searched from inception until June 30, 2020. The search was restricted to observational studies, conducted in population-based samples, with at least 1 year follow-up. There was no restriction on the definition of MCI used as long as it was clearly defined. PROSPERO registration: CRD42019130958.

Results

Ten thousand six hundred forty-seven articles were screened; n = 11 retained. Of the 11 studies, most were conducted in China (n = 7 studies), with only two studies from countries classified as low income. A qualitative analysis of n = 11 studies showed that similar to high-income countries the conversion rate to dementia from MCI was variable (range 6 . 0%-44 . 8%; average follow-up 3 . 7 years [standard deviation = 1 . 2]). A meta-analysis of studies using Petersen criteria (n = 6 studies), found a pooled conversion rate to Alzheimer's disease (AD) of 23 . 8% (95% confidence interval = 15 . 4%-33.4%); approximately one in four people with MCI were at risk of AD in LMICs (over 3 . 0-5 . 8 years follow-up). Risk factors for conversion from MCI to dementia included demographic (e.g., age) and health (e.g., cardio-metabolic disease) variables.

Conclusions

MCI is associated with high, but variable, conversion to dementia in LMICs and may be influenced by demographic and health factors. There is a notable absence of data from low-income settings and countries outside of China. This highlights the urgent need for research investment into aging and dementia in LMIC settings. Being able to identify those individuals with cognitive impairment who are at highest risk of dementia in LMICs is necessary for the development of risk reduction strategies that are contextualized to these unique settings.

Decreased integrity of the monoaminergic tract is associated with a positive response to MPH in patients with vascular cognitive impairment - proof of principle study STREAM-VCI

Background

Patients with vascular cognitive impairment (VCI) are very heterogeneous in both symptoms and type of cerebrovascular pathology. This might be an important reason why there is no symptomatic treatment available for VCI patients. In this study, we investigated in patients with VCI, whether there was an association between a positive response to methylphenidate and galantamine and the type of cerebrovascular disease, structural damage to specific neurotransmitter systems, cerebral perfusion, and presence of co-morbid Alzheimer (AD) pathology.

Methods

We included 27 VCI patients (mean age 67 years ± 8,30% female) from the STREAM-VCI trial who received placebo, methylphenidate(10 mg), and galantamine(16 mg) in a single challenge, cross-over design. In this study, we classified patients improving on a task for executive functioning after methylphenidate compared to placebo as methylphenidate responders (MPH+; resp. non-responders, MPH-) and patients improving on a task for memory after galantamine compared to placebo as galantamine responders (GAL+; resp. non-responders, GAL-). On baseline MRI, we visually assessed measures of cerebrovascular disease, automatically segmented white matter hyperintensities, used diffusion tensor imaging to visualize the integrity of monoaminergic and cholinergic neurotransmitter systems with mean diffusivity (MD) and fractional anisotropy (FA). Comorbid AD pathology was assessed using CSF or amyloid-PET. We tested differences between responders and non-responders using ANOVA, adjusting for age and sex.

Results

Nine patients were MPH+ vs 18 MPH-. MPH+ had higher MD (1.22 ± 0.07 vs 0.94 ± 0.05); p = .001) and lower FA (0.38 ± .01 vs 0.43 ± .01); p = .04) in the monoaminergic tract compared to MPH-. Eight patients were GAL+ and 18 GAL-. We found no differences between GAL+ and GAL- in any of the MRI measures. Information on co-morbid AD pathology was present in 17 patients. AD pathology tended to be more frequent in GAL+ vs GAL- (5(71%) vs 2(20%); p = .06).

Conclusions

In patients with VCI, we found that decreased integrity of the monoaminergic tract is associated with a positive response to MPH. Responsiveness to galantamine may be related to co-morbid AD pathology.

Cognitive Impairment in Heart Failure: Landscape, Challenges, and Future Directions

Heart failure (HF) is a major global healthcare problem accounting for substantial deterioration of prognosis. As a complex clinical syndrome, HF often coexists with multi-comorbidities of which cognitive impairment (CI) is particularly important. CI is increasing in prevalence among patients with HF and is present in around 40%, even up to 60%, of elderly patients with HF. As a potent and independent prognostic factor, CI significantly increases the hospitalization and mortality and decreases quality of life in patients with HF. There has been a growing awareness of the complex bidirectional interaction between HF and CI as it shares a number of common pathophysiological pathways including reduced cerebral blood flow, inflammation, and neurohumoral activations. Research that focus on the precise mechanism for CI in HF is still ever insufficient. As the tremendous adverse consequences of CI in HF, effective early diagnosis of CI in HF and interventions for these patients may halt disease progression and improve prognosis. The current clinical guidelines in HF have begun to emphasize the importance of CI. However, nearly half of CI in HF is underdiagnosed, and few recommendations are available to guide clinicians about how to approach CI in patients with HF. This review aims to synthesize knowledge about the link between HF and cognitive dysfunction, issues pertaining to screening, diagnosis and management of CI in patients with HF, and emerging therapies for prevention. Based on data from current studies, critical gaps in knowledge of CI in HF are identified, and future research directions to guide the field forward are proposed.

Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level

Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer's disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer's Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer's Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer's disease.

Reducing misclassification of mild cognitive impairment based on base rate information from the Uniform data set

The current study aimed to define and validate the criteria for characterizing possible and probable cognitive deficits based on the psychometric approach using the Uniform data set Czech version (UDS-CZ 2.0) to reduce the rate of misdiagnosis. We computed the prevalence of low scores on the 14 subtests of UDS-CZ 2.0 in a normative sample of healthy older adults and validated criteria for possible and probable cognitive impairment on the sample of amnestic Mild Cognitive Impairment (MCI) patients. The misclassification rate of the validation sample using psychometrically derived criteria remained low: for classification as possible impairment, we found 66-76% correct classification in the clinical sample and only 2-8% false positives in the healthy control validation sample, similar results were obtained for probable cognitive impairment. Our findings offer a psychometric approach and a computational tool to minimize the misdiagnosis of mild cognitive impairment compared to traditional criteria for MCI.

[Prognosis of amnestic mild cognitive impairment: clinical and immunological correlations]

OBJECTIVE

To determine the long-term (three-year) prognosis of the cognitive deficits progression in elderly people with amnestic mild cognitive impairment (aMCI) based on the analysis of the initial clinical and immunological parameters.

MATERIAL AND METHODS

This study is based on a clinical and follow-up study of 252 outpatients with aMCI, who were observed in the Federal State Budgetary Scientific Institution «Mental Health Research Center» from 2018 to 2020. The psychometric assessment complex included the following scales and tests: MMSE, MoCA, The 10 words test, BNT, David Wechsler's Scale, subtest 6, CDT, Memory test of 5 geometric shapes, BVRT Test, DRS - Mattis Dementia Rating Scale: Verbal fluency, DRS - Mattis Dementia Rating Scale, The Munsterberg Test. As part of the study, the level of cytokines (TNF-a, IL-1, IL-6, IL-8, IL-10) in the blood serum was determined in all patients by enzyme immunoassay (ELISA), using diagnostic kits manufactured by Cytokine LLC.

RESULTS

In patients with a progression of aMCI syndrome, an increase in proinflammatory cytokines IL-1, IL-6, IL-8, TNF-α is initially detected, which may reflect the level of systemic inflammation or functional insufficiency of anti-inflammatory mechanisms. In turn, the group with a subsequent improvement in cognitive functioning, on the contrary, is distinguished by an initially increased level of the anti-inflammatory interleukin system (IL-10).

CONCLUSION

We provide new data on the presence of systemic inflammation and immune disturbances and their association with clinical course of disease in the majority of elderly patients with aMCI.

CONCLUSION

Signs of a chronic low-level systemic inflammatory response in patients with aMCI is the unfavorable prognosis criterion: in such patients, cognitive deficit significantly progresses or dementia due to Alzheimer disease develops within three years.

The relationship between vascular endothelial growth factor (VEGF) and amnestic mild cognitive impairment among older adults living with HIV

Older people with HIV (PWH) experience increased risk of age-related neurodegenerative disorders and cognitive decline, such as amnestic mild cognitive impairment (aMCI). The objective of this study was to examine the relationship between aMCI and plasma VEGF biomarkers among older PWH. Data were collected at a university-based research center from 2011 to 2013. Participants were 67 antiretroviral therapy-treated, virally suppressed PWH. Participants completed comprehensive neurobehavioral and neuromedical evaluations. aMCI status was determined using adapted Jak/Bondi criteria, classifying participants as aMCI + if their performance was > 1 SD below the normative mean on at least two of four memory assessments. VEGF family plasma biomarkers (i.e., VEGF, VEGF-C, VEGF-D, and PIGF) were measured by immunoassay. Logistic regression models were conducted to determine whether VEGF biomarkers were associated with aMCI status. Participants were mostly non-Hispanic white (79%) men (85%) with a mean age of 57.7 years. Eighteen (26.9%) participants met criteria for aMCI. Among potential covariates, only antidepressant drug use differed by aMCI status, and was included as a covariate. VEGF-D was significantly lower in the aMCI + group compared to the aMCI - group. No other VEGF levels (VEGF, VEGF-C, PIGF) differed by aMCI classification (ps > .05). In a sample of antiretroviral therapy-treated, virally suppressed PWH, lower levels of VEGF-D were associated with aMCI status. Longitudinal analyses in a larger and more diverse sample are needed to support VEGF-D as a putative biological marker of aMCI in HIV.

Coupling feature extraction method of resting state EEG Signals from amnestic mild cognitive impairment with type 2 diabetes mellitus based on weight permutation conditional mutual information

This study aimed to find a good coupling feature extraction method to effectively analyze resting state EEG signals (rsEEG) of amnestic mild cognitive impairment(aMCI) with type 2 diabetes mellitus(T2DM) and normal control (NC) with T2DM. A method of EEG signal coupling feature extraction based on weight permutation conditional mutual information (WPCMI) was proposed in this research. With the WPCMI method, coupling feature strength of two time series in Alpha1, Alpha2, Beta1, Beta2 and Gamma bands for aMCI with T2DM and NC with T2DM could be extracted respectively. Then selected three frequency bands coupling feature matrix with the help of multi-spectral image transformation method to map it as spectral image characteristics. And finally classified these characteristics through the convolution neural network method(CNN). For aMCI with T2DM and NC with T2DM, the highest classification accuracy of 96%, 95%, 95% could be achieved respectively in the combination of three frequency bands (Alpha1, Alpha2, Gamma), (Beta1, Beta2 and Gamma) and (Alpha2, Beta1, Beta2). This WPCMI method highlighted the coupling dynamic characteristics of EEG signals, and its classification performance was better than all previous methods in aMCI with T2DM diagnosis field. WPCMI method could be used as an effective biomarker to distinguish EEG signals of aMCI with T2DM and NC with T2DM. The coupling feature extraction method used in this paper provided a new perspective for the EEG analysis of aMCI with T2DM.

Diffusion imaging of fornix and interconnected limbic deep grey matter is linked to cognitive impairment in multiple sclerosis

Diffusion tensor imaging (DTI) and volumetric magnetic resonance imaging (MRI) have shown white matter (WM) and deep grey matter (GM) abnormalities in the limbic system of multiple sclerosis (MS) participants. Structures like the fornix have been associated with cognitive impairment (CI) in MS, but the diffusion metrics are often biased by partial volume effects from cerebrospinal fluid (CSF) due to its small bundle size and intraventricular location. These errors in DTI parameter estimation worsen with atrophy in MS. The goal here was to evaluate DTI parameters and volumes of the fornix, as well as associated deep GM structures like the thalamus and hippocampus, with high-resolution fluid-attenuated inversion recovery (FLAIR)-DTI at 3T in 43 MS patients, with and without CI, versus 43 controls. The fornix, thalamus and hippocampus displayed atrophy and/or abnormal diffusion metrics, with the fornix showing the most extensive changes within the structures studied here, mainly in CI MS. The affected fornix volumes and diffusion metrics were associated with thalamic atrophy and atypical diffusion metrics in interconnected limbic GM, larger total lesion volume and global brain atrophy. Lower fractional anisotropy (FA) and higher mean and radial diffusivity in the fornix, lower hippocampus FA and lower thalamus volume were strongly correlated with CI in MS. Hippocampus FA and thalamus atrophy were negatively correlated with fatigue and longer time since MS symptoms onset, respectively. FLAIR-DTI and volumetric analyses provided methodologically superior evidence for microstructural abnormalities and extensive atrophy of the fornix and interconnected deep GM in MS that were associated with cognitive deficits.