Cognitive Subgroups Research Articles

Effect of randomised blood pressure lowering treatment and intensive glucose control on dementia and cognitive decline according to baseline cognitive function and other subpopulations of individuals with type 2 diabetes: results from the ADVANCE trial

Background and aims: Accumulating evidence indicates that reducing high blood pressure (BP) prevents dementia and mild cognitive impairment (MCI). Furthermore, although diabetes is a risk factor for dementia and MCI, there is uncertainty of the effect of intensive glucose control on these endpoints. This study aimed to determine the effects of BP-lowering (vs placebo) and intensive glucose-lowering (vs standard control) treatments according to baseline cognition and other characteristics on dementia and cognitive decline (CD) in people with type 2 diabetes mellitus (T2DM). Methods: The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial involved 11,140 individuals with T2DM. The effects of BP-lowering and intensive glucose-lowering treatments were explored in subgroups of baseline Mini-Mental State Examination (MMSE), categorised as cognitively normal (scores ≥28) and cognitive impairment (scores <28). The primary outcome was a composite of dementia/CD that accounted for the competing risk of death. Multinomial regression models, adjusted for common cardiovascular risk factors, were used to estimate odds ratios (OR) with 95% confidence intervals (CI) of the effects of the treatments on dementia/CD. Homogeneity of effects by subgroups were evaluated using interaction terms in the models. A two-sided p value less than 0.05 was regarded as statistically significant. Results: BP-lowering treatment (vs. placebo) was associated with a lower odds of dementia/CD in participants with cognitive impairment (OR 0.76, 95% CI 0.59-0.99) but not in those cognitively normal (OR 1.05, 95% CI 0.92-1.21; p for interaction 0.03). Those with a history of cardio-renal-metabolic syndrome did not experience a benefit of active BP lowering treatment compared with placebo on dementia/CD. There were no further subgroup effects of BP-lowering treatment. The effect of intensive glucose lowering (vs standard control) on the odds of dementia/CD did not vary by baseline cognition subgroup. However, it did vary by level of blood glucose at baseline (<7.9 mmol/L OR 1.12, 95%CI 0.96-1.30 vs ≥ 7.9 mmol/L 0.87 (0.75-1.00); p for interaction 0.02) and duration of T2DM (<10 years OR 0.92 (0.81-1.05) vs ≥10 years 1.16 (0.97-1.38); p for interaction 0.04). Conclusions: This study suggests greater effects of BP-lowering treatment in those with early loss of cognitive function than in those cognitively normal. There were also differential effects of intensive glucose-lowering on dementia and CD according to levels of blood glucose and duration of diabetes in people with T2DM. Clinical trial registration: ADVANCE is registered with ClinicalTrials.gov: number NCT00145925

A meta-analysis of data-driven cognitive subgroups in bipolar disorder

The delineation of cognitive subgroups of bipolar disorder (BD) might be helpful for identifying biologically valid subtypes of this disorder. This meta-analysis identified peer-reviewed literature on studies investigating cognitive subgroups of BD with data-driven clustering methods. Relevant studies were searched in PubMed, Scopus, and Web of Science. Random-effects meta-analysis was performed using R software. A total of 14 cross-sectional studies including euthymic or mildly symptomatic patients with BD were included in the current meta-analysis. The available studies have consistently supported a 3-cluster solution. The pooled prevalence of the severe-impairment, moderate-impairment, and major good-functioning groups were 23.1 % (95%CI, 18.5 %–27.7 %), 42.5 % (95%CI, 36.3 %–48.8 %), and 33.5 % (95%CI, 25.9 %–41.1 %) respectively. Compared to healthy controls, both the severe-impairment (g=−1.40 to −1.73) and moderate-impairment groups (g=−0.59 to −0.96) had significant deficits in all six cognitive domains (verbal memory, visual memory, executive functions, working memory, attention and processing speed). The good-performance subgroup had a small increase in the performance of executive functions (g=0.23) and normal functioning in all other domains. Compared to the good-performance subgroup, the severe-impairment subgroup was characterized by more severe functional impairment, more hospital admissions, a higher percentage of type I BD and antipsychotic use. The characteristics of the moderate-impairment subgroup were lying between the other two subgroups for most of the measures. The current findings support the existence of 3 cognitive subgroups in BD including severe-impairment and moderate-impairment groups which are associated with a more severe course of illness.

Cognitive function in older adults with stroke: A latent profile analysis

BackgroundPost-stroke cognitive impairment (PSCI) is one of the major complications after a stroke. Therefore, it is necessary to identify different categories of cognitive function in older adults with stroke and to explore factors associated with different levels of cognitive function in older adults after stroke. MethodsA cross-sectional survey was conducted using convenience sampling to collect data from 1076 older adults with stroke from 5 hospitals in Lanzhou City, Gansu Province, China, from June 2022 to August 2023. Latent Profile Analysis (LPA) was used to identify cognitive function subgroups among older adults with stroke, and multinomial logistic regression was used to analyze the related factors. Results1076 older adults with stroke were identified and classified as class-1: cognitive impairment, class-2: mild cognitive impairment, class-3: normal cognitive function. Age, gender, education level, hemorrhagic stroke, cerebrovascular disease are associated with different levels of cognitive function in older adults after stroke. ConclusionsThese findings highlight the heterogeneity of cognitive function in older adults with stroke. Our research could assist healthcare professionals in China to identify older adults with a high risk of cognitive impairment and to develop individualized interventions based on their characteristics.

Utility of cerebrovascular imaging biomarkers to detect cerebral amyloidosis.

The relationship between cerebrovascular disease (CVD) and amyloid beta (Aβ) in Alzheimer's disease (AD) is understudied. We hypothesized that magnetic resonance imaging (MRI)-based CVD biomarkers-including cerebral microbleeds (CMBs), lacunar infarction, and white matter hyperintensities (WMHs)-would correlate with Aβ positivity on positron emission tomography (Aβ-PET). We cross-sectionally analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, N=1352). Logistic regression was used to calculate odds ratios (ORs), with Aβ-PET positivity as the standard-of-truth. Following adjustment, WMHs (OR=1.25) and superficial CMBs (OR=1.45) remained positively associated with Aβ-PET positivity (p<0.001). Deep CMBs and lacunes exhibited a varied relationship with Aβ-PET in cognitive subgroups. The combined diagnostic model, which included CVD biomarkers and other accessible measures, significantly predicted Aβ-PET (pseudo-R2=0.41). The study highlights the translational value of CVD biomarkers in diagnosing AD, and underscores the need for more research on their inclusion in diagnostic criteria. gov: ADNI-2 (NCT01231971), ADNI-3 (NCT02854033). Cerebrovascular biomarkers linked to amyloid beta (Aβ) in Alzheimer's disease (AD). White matter hyperintensities and cerebral microbleeds reliably predict Aβ-PET positivity. Relationships with Aβ-PET vary by cognitive stage. Novel accessible model predicts Aβ-PET status. Study supports multimodal diagnostic approaches.

Childhood Traumas and Depressive Symptoms: The Moderating Role of Anxiety Sensitivity.

Depression is one of the most common public health problems. Considering the frequency of childhood trauma in people with depressive symptoms, determining mediating factors is important in understanding the relationship between them. Our study aimed to evaluate the mediating effect of anxiety sensitivity, one of the cognitive structures that plays a role in the etiology and maintenance of psychopathologies, on depression symptoms of childhood traumas. The study included 110 participants aged between 18 and 65, diagnosed with depression, and applied to the psychiatry outpatient clinic. Of the participants, 35 were male and 75 were female. The majority of participants were in the 18-25 age group (39.1%), followed by a smaller percentage in the 25-35 age group (32.7%). The Beck Depression Inventory (BDI-I), Childhood Trauma Questionnaire (CTQ), and Anxiety Sensitivity Index (ASI-3) were administered to participants between 15 February and 15 April 2024. When the sample was examined according to the history of depressive symptoms, it was found that the score of the cognitive subscale of ASI-3 and the scores of the physical neglect, emotional neglect, and emotional abuse subscales of the CTQ were significantly higher in the group with depressive symptoms. When the mediating effect of the scores of "Emotional neglect", "Physical neglect", and "Emotional abuse" subscales of CTQ, and the score of "Cognitive" subscale of ASI-3 score was examined with regression models, it was found that the history of emotional neglect and abuse in childhood predicted depressive symptoms through the cognitive sub-group of AS. In our study, it was shown that childhood trauma, which could cause a person to evaluate stressful life events as more depressogenic and the formation of negative cognitions about themselves and the world, predicted the severity and occurrence of depressive symptoms through fear of cognitive dysfunction.

Social Engagement and Happiness in Older Adults With and Without Cognitive Impairment.

This study investigated the associations between in-person and remote engagement and self-rated happiness in older adults aged 50 years and above in three cognitive function subgroups: Normal Cognition, Cognitive Impairment not Dementia (CIND), and Dementia. Data were obtained from the 2014 Health and Retirement Study. Results showed that remote engagement was significantly associated with higher self-rated happiness, particularly in the CIND group. However, its association with in-person engagement was less consistent. No significant association was observed among individuals with dementia. However, the direction of the relationship between the two types of social engagement and self-rated happiness was positive. Instrumental activities of daily living, depression, and social capital were identified as potential factors influencing the relationship between social engagement and self-rated happiness. These findings emphasize promotion of both in-person and remote social engagement opportunities to enhance the well-being of older adults across different cognitive function subgroups.

Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks

Cognitive deficits are prevalent in individuals with psychosis and are associated with neurobiological changes, potentially serving as an endophenotype for psychosis. Using the HCP-Early-Psychosis-dataset (n = 226), we aimed to investigate cognitive subtypes (deficit/intermediate/spared) through data-driven clustering in affective (AP) and non-affective psychosis patients (NAP) and controls (HC). We explored differences between three clusters in symptoms, cognition, medication, and grey matter volume. Applying principal component analysis, we selected features for clustering. Features that explained most variance were scores for intelligence, verbal recognition and comprehension, auditory attention, working memory, reasoning and executive functioning. Fuzzy K-Means clustering on those features revealed that the subgroups significantly varied in cognitive impairment, clinical symptoms, and, importantly, also in medication and grey matter volume in fronto-parietal and subcortical networks. The spared cluster (86%HC, 37%AP, 17%NAP) exhibited unimpaired cognition, lowest symptoms/medication, and grey matter comparable to controls. The deficit cluster (4%HC, 10%AP, 47%NAP) had impairments across all domains, highest symptoms scores/medication dosage, and pronounced grey matter alterations. The intermediate deficit cluster (11%HC, 54%AP, 36%NAP) showed fewer deficits than the second cluster, but similar symptoms/medication/grey matter to the spared cluster. Controlling for medication, cognitive scores correlated with grey matter changes and negative symptoms across all patients. Our findings generally emphasize the interplay between cognition, brain structure, symptoms, and medication in AP and NAP, and specifically suggest a possible mediating role of cognition, highlighting the potential of screening cognitive changes to aid tailoring treatments and interventions.

A taxonomy of cognitive phenotypes in Multiple Sclerosis: a 1-year longitudinal study

As meaningful measure of cognitive impairment (CI), cognitive phenotypes provide an avenue for symptom management and individualized rehabilitation. Since CI is highly variable in severity and progression, monitoring cognitive phenotypes over time may be useful to identify trajectory of cognitive decline in Multiple Sclerosis (MS). Based on cognitive and mood information from patient-reported outcomes (PROs) and clinician-assessed outcomes (CAOs), four cognitive subgroups of people with MS (PwMS) were identified: phenotype 1 (44.5%) showed a preserved cognitive profile; phenotype 2 (22.8%) had a mild-cognitive impairment profile with attention difficulties; phenotype 3 (24.3%) included people with marked difficulties in visuo-executive, attention, language, memory and information processing speed; lastly, phenotype 4 (8.4%) grouped individuals with a multi-domain impairment profile (visuo-executive, attention, language, memory, orientation, information processing speed and mood disorders). Although some fluctuations occurred considering the rate of impairment, cognitive phenotypes did not substantially vary at follow up in terms of type and number of impairments, suggesting that 1 year is a relatively brief temporal window to observe considerable changes. Our results corroborate that investigating cognitive phenotypes and their stability over time would provide valuable information regarding CI and, in addition, increase clinical importance of PROs and CAOs and their uptake in decision-making and individualized treatment planning for PwMS.

Longitudinal course of inflammatory-cognitive subgroups across first treatment severe mental illness and healthy controls.

While inflammation is associated with cognitive impairment in severe mental illnesses (SMI), there is substantial heterogeneity and evidence of transdiagnostic subgroups across schizophrenia (SZ) and bipolar (BD) spectrum disorders. There is however, limited knowledge about the longitudinal course of this relationship. Systemic inflammation (C-Reactive Protein, CRP) and cognition (nine cognitive domains) was measured from baseline to 1 year follow-up in first treatment SZ and BD (n = 221), and healthy controls (HC, n = 220). Linear mixed models were used to evaluate longitudinal changes separately in CRP and cognitive domains specific to diagnostic status (SZ, BD, HC). Hierarchical clustering was applied on the entire sample to investigate the longitudinal course of transdiagnostic inflammatory-cognitive subgroups. There were no case-control differences or change in CRP from baseline to follow-up. We confirm previous observations of case-control differences in cognition at both time-points and domain specific stability/improvement over time regardless of diagnostic status. We identified transdiagnostic inflammatory-cognitive subgroups at baseline with differing demographics and clinical severity. Despite improvement in cognition, symptoms and functioning, the higher inflammation - lower cognition subgroup (75% SZ; 48% BD; 38% HC) had sustained inflammation and lower cognition, more symptoms, and lower functioning (SMI only) at follow-up. This was in comparison to a lower inflammation - higher cognition subgroup (25% SZ, 52% BD, 62% HC), where SMI participants showed cognitive functioning at HC level with a positive clinical course. Our findings support heterogenous and transdiagnostic inflammatory-cognitive subgroups that are stable over time, and may benefit from targeted interventions.

Longitudinal association of adverse childhood experiences with cognitive function trajectories among middle-aged and older adults: group-based trajectory modeling.

Adverse childhood experiences (ACEs) impact cognitive function, but the relationship remains unclear. We aim to identify cognitive function trajectories and scrutinize the correlation between ACEs and cognitive function. To identify cognitive trajectories, we employed a group-based trajectory model, and influential factors were determined using multinomial unordered logistic regression analysis. Three cognitive decline subgroups emerged: low-start decline, high-start stability, and mid-start decline. There is no dose-response relationship between cumulative adverse childhood experiences and cognitive function. The high-start stability group had specific residence and education traits, while sibling death affected them. The mid-start decline group was vulnerable to parental death, physical abuse, and domestic violence. The low-start decline group should consider age structure and childhood friendships. No dose-response association between cumulative ACEs and cognitive decline. Still, specific ACE metrics are correlated with cognitive trajectories. We can incorporate patients' ACEs into cognitive function assessments for early risk factor identification and tailored interventions. Moreover, recognizing the influence of early-life experiences on cognitive function, we can advocate for nurturing positive family and societal environments to optimize cognitive function.

Cognitive Profiles in Treatment-Resistant Late-Life Depression and Their Impact on Treatment Outcomes

BackgroundLate-life depression (LLD) is associated with cognitive impairment, but substantial heterogeneity exists among patients. Data on the extent of cognitive impairments are inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant versus nonresistant LLD and aimed to identify distinct cognitive subgroups. We also examined whether cognitive subgroups responded differentially to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS). MethodsA total of 165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared with healthy control participants on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups. ResultsPatients with LLD, particularly TRD, exhibited significantly worse cognitive performance than healthy controls. A 3-cluster solution was found, including cognitively intact (n = 89), cognitively diminished (n = 29), and impaired memory (n = 47) subgroups. Both the cognitively diminished and impaired memory subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the cognitively intact group, although the latter difference did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment. ConclusionsPatients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationships among cognitive subgroups, cognitive decline, and neurodegeneration.

Utility of cerebrovascular imaging biomarkers to detect cerebral amyloidosis.

The relationship between cerebrovascular disease (CVD) and amyloid-β (Aβ) in Alzheimer disease (AD) is understudied. We hypothesized that magnetic resonance imaging (MRI)-based CVD biomarkers, including cerebral microbleeds (CMBs), ischemic infarction, and white matter hyperintensities (WMH), would correlate with Aβ positivity on positron emission tomography (Aβ-PET). We cross-sectionally analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, N=1,352). Logistic regression was used to calculate odds ratios (ORs), with Aβ-PET positivity as the standard-of-truth. Following adjustment, WMH (OR=1.25) and superficial CMBs (OR=1.45) remained positively associated with Aβ-PET positivity (p<.001). Deep CMBs and infarcts exhibited a varied relationship with Aβ-PET in cognitive subgroups. The combined diagnostic model, which included CVD biomarkers and other accessible measures, significantly predicted Aβ-PET (pseudo-R 2 =.41). The study highlights the translational value of CVD biomarkers in diagnosing AD, and underscores the need for more research on their inclusion in diagnostic criteria. ClinicalTrials.gov: ADNI-2 ( NCT01231971 ), ADNI-3 ( NCT02854033 ).

Longitudinal study on the trajectory and influencing factors of cognitive dysfunction in lung transplantation patients

IntroductionLung transplantation is an effective method for treating end-stage lung disease. It prolongs the survival time of patients, improves the quality of life, and prevents the degree of mental disability. In particular, postoperative cognitive dysfunction (POCD) is one of the complications after lung transplantation. Despite this, longitudinal studies on the identification and heterogeneity of cognitive dysfunction subgroup trajectories in transplant patients are lacking. Therefore, our study aimed to evaluate the factors that influence POCD in lung transplant patients. MethodsThis prospective longitudinal study included patients who underwent lung transplantation at the transplant center of Wuxi People's Hospital from September 2022 to September 2023. Patients with lung transplants were evaluated at 8 days (T1), 1 month (T2), 3 months (T3), and 6 months (T4) after the operation. The general information questionnaire evaluated cognitive functions using the Montreal Cognitive Assessment (MoCA) numerical rating scale (NRS) and the digital pain assessment to obtain the POCD values. Latent category growth model (LCGM) analysis was used to identify heterogeneous POCD subgroups in the four observation periods. Univariate and logistic regression analyses were used to identify factors affecting POCD classification and independent risk factors. ResultsBased on clinical outcomes, 79 patients completed all four surveys, of whom 16 were lost during the follow-up period (loss rate, 16.8%). The cognitive function by MoCA NRS score was 14.18 ± 5.32 points on day 8 (T1), 22.51 ± 5.13 points at 1 month (T2), 25.44 ± 3.61 at 3 months (T3), and 27.04 ± 3.03 points at 6 months (T4) after lung transplantation, showing an increasing trend. The LCGM, used to fit the trajectory of MoCA scores, observed a heterogeneous trajectory of changes in lung transplant patients. Based on this analysis, patients could be divided into two categories: those with high risk (25,32%) and those with low risk (54,68%). The single-factor analysis identified that POCD values were affected by early postoperative rehabilitation exercise, degree of pain, intensive care unit (ICU) stay time, and donor lung cold ischemia time (all P < 0.05). Using the low-risk group as the reference class, logistic regression analysis showed that the model could correctly classify the subjects. ConclusionOur 6-month observation of lung transplant patients showed that the degree of cognitive dysfunction had an overall downward trend and that patients could be divided into two trajectories of high and low risk for POCD. Early postoperative rehabilitation exercise, degree of pain, ICU stay time, and donor lung cold ischemia time were all influencing factors for POCD in lung transplant patients.

Predictors of post stroke cognitive impairment: VITATOPS cognition substudy

IntroductionPost stroke cognitive impairment (PSCI) is a common complication of ischemic stroke. PSCI can involve different depending on clinical and stroke related characteristics. The aim of this study is to determine the factors associated with impairments in specific cognitive domains. MethodsThe Vitamins to Prevent Stroke (VITATOPS) trial is a large, multinational randomised controlled trial. In this substudy, consecutive patients admitted for ischaemic stroke or transient ischaemic attack (TIA) at a tertiary hospital in Singapore were included. PSCI was defined as impairment of any of the six cognitive subgroups – visuoconstruction, attention, verbal memory, language, visual memory and visuomotor function – that were assessed annually for up to five years. Univariate and multivariate Cox proportional hazard models were used to determine factors associated with impairments in each of these cognitive domains. ResultsA total of 736 patients were included in this study, of which 173 (23.5 %) developed cognitive impairment. Out of the six cognitive domains, the greatest proportion of patients had an impairment in visuoconstruction (26.4 %) followed by attention (19.8 %), verbal memory (18.3 %), language (17.5 %), visual memory (17.3 %) and visuomotor function (14.8 %). Patients with posterior circulation cerebral infarction (POCI) as the index stroke subtype had higher rates of cognitive impairment. Further subgroup analyses show that Indian race and advanced age were predictive of language impairment, whilst fewer years of education and POCI were predictive of verbal memory impairment. POCI was predictive of visual memory impairment, and advanced age and POCI were predictive of visuomotor function impairment. ConclusionWe identified visuoconstruction and attention domains to be the most affected in our Asian cohort of PSCI. Advanced age, lower levels of education, posterior circulation strokes and concomitant comorbidities such as peripheral artery disease are independent predictors of PSCI.

The effect of the mind–body intervention on depression in people with cognitive impairment: A systematic review and meta‐analysis

AbstractPurposeTo assess the effect of the mind–body intervention on depression in people with cognitive impairment.MethodsFive databases (PubMed, Web of Science, Embase, Cochrane Library, and PsycINFO) were systematically searched, the Cochrane Collaboration's tool was used for quality assessment, and subgroup analyses were performed according to participant types, intervention types, and duration of interventions.FindingsA total of 16 randomized controlled trials were included, two of which were unable to obtain complete data and one had high heterogeneity. The overall meta‐analysis of 13 articles showed that the mind–body intervention was not effective in promoting depression in individuals with cognitive impairment (standardized mean difference [SMD] = −0.08; 95% confidence interval (CI) [−0.27, 0.11]; p = 0.419; I2 = 52.4%, 13 studies, 1406 participants) compared with the control group. Subgroup analysis showed that depression was significantly improved in the dementia subgroup after the mind–body intervention compared to the control group (SMD = −0.31; 95% CI [−0.57, −0.05]; p = 0.021. I2 = 29.2%, six studies, 399 participants), while no significant changes were observed in the mild cognitive impairment subgroup. Among different intervention types and durations, no intervention was found to have a significant positive effect on depression.ConclusionThe mind–body intervention is an effective intervention for improving depression in people with dementia, but its effect is not significant in individuals with overall cognitive impairment. Follow‐up high‐quality studies are needed to further verify the effects of different mind–body interventions on depression in people with different severities of cognitive impairment.Implications for Nursing Practice: By proving the effectiveness of the mind–body intervention in improving depression in people with dementia, it will provide evidence for the further development and improvement of the mode and content of the mind–body intervention and increase the attention and support of the healthcare system and society for the mind–body intervention.

Exploring older people’s understanding of the QOL-ACC, a new preference-based quality-of-life measure, for quality assessment and economic evaluation in aged care: the impact of cognitive impairment and dementia

BackgroundQuality-of-life is an essential outcome for quality assessment and economic evaluation in health and social care. The-Quality-of-Life – Aged Care Consumers (QOL-ACC) is a new preference-based quality-of-life measure, psychometrically validated with older people in aged care. More evidence is needed to inform the self-report reliability of the QOL-ACC in older people with varying levels of cognitive impairment and dementia.MethodsA think-aloud protocol was developed and applied with older residents. The Mini Mental State Examination (MMSE) was applied to assign participants to no cognitive impairment (NCI - MMSE score ≥ 27) and cognitive impairment (MMCI - MMSE score < 27) subgroups. Three independent raters utilised a Tourangeau survey response model-based framework to identify response issues. Data were compared across cognition subgroups and synthesized using a ‘traffic light’ grading to classify frequency and type of response issues. Gradings were utilised to assess self-report reliability according to different levels of cognitive impairment.ResultsQualitative data from 44 participants (NCI = 20, MMCI = 24) were included for analysis. Response issues were more evident in the cognitive impairment subgroup than the no cognitive impairment subgroup. All participants who received a ‘red’ grade had an MMSE score of < 20 and 66% of ‘amber’ grades occurred in the cognitive impairment subgroup.ConclusionsThe QOL-ACC is able to be completed reliably by older residents with an MMSE score > 17. Future research is needed to assess the generalisability of these findings to other preference-based quality of life instruments and for older people in other care settings including health systems.

Evaluating cognitive phenotypes and associations with neuroimaging biomarkers of dementia in a sample of aging individuals using unsupervised machine learning

AbstractBackgroundOtherwise cognitively normal individuals can experience age‐related cognitive dysfunction and may present with heterogenous patterns of cognitive impairment. There is limited knowledge regarding the presence and stability of cognitive subtypes observed in individuals with mild cognitive impairment and dementia (e.g., dysexecutive, non‐amnestic). Further, the extent to which cognitive subtypes related to age‐ and dementia‐related neuroimaging biomarkers is uncertain.MethodThis study sought to evaluate the presence and composition of cognitive subtypes in a large diverse community sample of aging individuals without dementia (NC; Baseline N = 337; Table 1). Participants enrolled in the Wake Forest ADRC and completed an annual battery of cognitive assessments (Uniform Data Set; NACC), the Mini‐Mental State Exam (MMSE), and Clinical Diagnostic Rating Scale (CDR). Unsupervised machine learning (e.g., clustering: hierarchical, k‐means, and k‐medoids algorithms; 1000 bootstrap iterations; majority voting rule) was applied to the battery of cognitive assessments. Demographic characteristics and neuroimaging measures of amyloid deposition (global PiB PET SUVr; Aβ‐PET), total brain volume (BVOL), diffusion‐weighted fractional anisotropy (FA), and NODDI freewater (FW) were compared across prospective clusters using general linear models. Highly correlated cognitive metrics (r&gt;.85) were removed prior to analysis.ResultCluster analyses using baseline cognitive scores suggested NC participants could be partitioned into two to eight clusters; two primary clusters representing one large homogenous group of relatively unimpaired individuals and another heterogenous cluster composed of 4‐7 possible cognitive subgroups (Figure 1). The two‐cluster solution partitioned NC participants into higher and lower cognitive performers. Across cluster solutions, lower performing individuals were older, had higher Aβ‐PET, and lower total brain volume on average (p&lt;.05; Figure 2).ConclusionWe did not observe well‐defined clusters representing distinct cognitive subtypes reported in previous studies (e.g., dysexecutive, amnestic, visuospatial). However, a heterogenous subset of NC participants exhibited substantial variability across assessments. Three‐ and four‐cluster solutions identified individuals with greater impairment in executive functioning, and verbal learning and memory respectively. Findings highlight the need to model complex patterns of cognitive abilities in otherwise healthy older adults. Future longitudinal work will assess how health information and neuroimaging biomarkers of dementia contribute to the composition and stability of cognitively defined subgroups.

Association of creatine kinase with cognition, neuroimaging, and Alzheimer’s pathology

AbstractBackgroundCreatine kinase (CK) and its related metabolites are known to imply cardiovascular system disease, whereas the cardiovascular metabolic state is associated with the state of cognitive well‐being of the brain. However, the extent to which CK levels is related with cognitive impairment has not been revealed.MethodThe Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used for this study. We first investigated the intergroup difference of participants demographic, cognitive status, Alzheimer’s disease (AD) diagnosis, and cerebrospinal fluid (CSF) AD pathology biomarkers. Next, we conducted to use liner regression model to examine the association of CK with CSF AD pathology biomarkers, cognition, and brain structure. Last, mediation analyses were utilized to explore whether the association between CK and cognition were mediated by CSF AD pathology biomarkers.ResultA total of 1,607 participants (mean age were 73.82±7.23 and 55.76% were male) from the ADNI database were involved in this cross‐sectional study. We found a significant difference through age, gender, AD diagnosis, and cognitive status subgroups in intergroup difference analysis (P&lt;0.05). Meanwhile, significant association of lower level of CK with decreased level of β‐amyloid1‐42 (Aβ; β = 0.069, P = 0.040) and increased level of phosphorylated tau (P‐tau; β = ‐0.084, P = 0.007), and total‐tau (T‐tau; β = ‐0.071, P = 0.021), respectively. Liner regression analysis also indicated that the lower level of CK was associated with worse cognition (Mini‐Mental State Examination: β = 0.059, P = 0.021; Alzheimer’s Disease Assessment Scale: β = ‐0.065, P = 0.012), however not to brain structure. Moreover, mediation analysis identified CSF AD pathology biomarkers mediated the association between level of CK and cognition.ConclusionOur findings offered detailed proof to advise that the lower level of CK was significantly associated with poor cognition and it might be mediated by CSF AD pathology biomarkers. For future research, it is necessary to identify the precise reason and process by which changed levels of CK impact cognition.

Relationship for co‐trajectories of cognitive decline and late‐life depression with postmortem neuropathology

AbstractBackgroundThe etiopathological relationship between late‐life cognitive decline and symptoms of depression remains unclear. Existing longitudinal studies have mostly grouped participants into distinct groups based on clinical diagnoses, and very few have analyzed postmortem neuropathology. Here we identified trajectories of both cognition and depressive symptoms in an elderly cohort over up to 27 years using growth mixture modeling (GMM), identifying co‐trajectory subgroups, and characterizing them with respect to postmortem neuropathologies.MethodWe analyzed 3,010 participants enrolled without dementia (mean age = 78) from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP). All included participants were evaluated for at least three annual visits for both depressive symptoms (using a modified Center for Epidemiologic Studies Depression Scale) and 19 cognitive tasks (yielding a global cognitive function summary score). A subset of 1,732 participants had complete postmortem neuropathological assessment data available. Latent trajectory subgroups were identified independently for global cognition and depressive symptoms using GMM with non‐linear time effects. Interaction effects of cognitive and depressive trajectory subgroups on neuropathologies were assessed using linear models.ResultThree trajectory subgroups (Figure 1) were identified for both cognitive decline (minimal (n = 1,232), slow (n = 1,325) and fast (n = 302)) and depressive symptoms (sustained low (n = 1,815), moderately increasing (n = 762) and consistently elevated (n = 433)). These subgroups showed significant overlap (chi‐square p = 0.0001), and their intersections defined nine co‐trajectories. A significant interaction effect (p = 0.0062) was identified between cognitive decline and depressive symptom trajectory subgroups for brain‐wide levels of paired helical filament tau; among only individuals experiencing fast cognitive decline, sustained lower depressive symptoms were associated with higher levels of tau (Figure 2).ConclusionLongitudinal cognitive decline and depressive symptom trajectories in late‐life are not independent. Intriguingly, we observed the highest tau burden in those individuals with both sustained low depressive symptoms and fast rates of cognitive decline. Given that use of antidepressants may lower tau levels (Dafsari &amp; Jessen, 2020), future models of neuropathology in trajectory‐based analyses will incorporate patterns of medication status.

Cognitive and inflammatory subgroups in severe mental illness: translating findings from blood to brain

Cognitive and inflammatory subgroups in severe mental illness: translating findings from blood to brain