Cerebral circulation - cognition and behavior最新文献

Brain health means optimal physiological brain function across the normal life-course. It encompasses not only healthy brain aging but also brain diseases, their diagnosis and treatment. In all these areas, molecular science has advanced our understanding.

This multi-disciplinary review combines viewpoints from laboratory science, clinical medicine and the bioscience industry. First, we review the advances that molecular science has brought to brain health in the past twenty years. These include therapeutic antibodies for CNS diseases (multiple sclerosis, Alzheimer disease) and the dramatic introduction of RNA-targeted therapeutics. Second, we highlight areas where greater molecular understanding is needed. Salient examples are the relation of brain structure to cognitive symptoms, and molecular biomarkers for diagnosis, target discovery and testing of interventions. Finally, we speculate on aspects of molecular science that are likely to advance brain health in the next twenty years. These include: cell senescence and chronobiology; gene editing (notably, CRISPR) and RNA targeting (RNA interference, miRNA manipulation); brain-immune interactions; novel drug targets (AQP4, HIF1, Toll-like receptors); and novel chemistry to make new drugs (molecular machines, quantum molecular modelling and “click” chemistry). Early testing of the relationships between molecular pathways and clinical manifestations will drive much-needed breakthroughs in neurology and psychiatry.

Introduction

Two of the main causes for dementia are Alzheimer's disease (AD) pathology and vascular pathology. Plasma biomarkers for AD pathology have recently emerged, including amyloid-beta, p-tau, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Vascular pathology can be assessed on MRI via white matter hyperintensities (WMH) and infarcts. Our aim was to estimate the relationship between plasma AD biomarkers and MRI markers of vascular pathology and neurodegeneration in non-demented individuals with manifest arterial disease.

Methods

Data from 594 individuals (mean (SD) age: 64 (8) years; 17% female) were included from the SMART-MR Study, a prospective cohort study from the UMC Utrecht in the Netherlands. Vascular and neurodegenerative MRI markers included WMH volume, presence of infarcts (yes/no), total brain volume (TBV), and hippocampal volume (HV) assessed on 1.5T MRI. AD plasma markers (amyloid-beta 42/40 ratio, ptau-181, NfL, and GFAP) were assessed using Single Molecular Array (Simoa; Quanterix) assays. Linear regressions were performed for each plasma marker with WMH volume, TBV, and HV, correcting for age, sex, education, and ICV. Additionally, logistic regressions were performed for the presence of lacunar and cortical infarcts. Plasma AD levels were converted to z-scores.

Results

Higher ptau-181 was associated with larger WMH volume (β=0.16, 95% CI=0.06; 0.26, p=0.001). Higher NfL (β=-5.63, 95% CI=-8.95; -2.31, p=0.001) was associated with lower TBV. Higher NfL levels (.R=1.58, 95% CI=1.20; 2.08, p=0.001) and higher GFAP levels (OR=1.45, 95% CI=1.09; 1.92, p=0.010) were associated with cortical infarcts.

Discussion

In our sample of patients with manifest arterial disease, NfL was related to both brain volume and infarcts. Further, an association between ptau-181 and WMH was found, as well as between GFAP and cortical infarcts. Plasma biomarkers offer the potential to easily measure a wider range of pathophysiological processes related to cognitive decline.

Introduction

Cerebral small vessel disease (SVD) contributes to 45% of dementia cases worldwide. Only a minority of SVD patients develop dementia, yet we lack a reliable model for predicting incident dementia in SVD. Most attempts to date have relied on traditional statistical approaches, whereas machine learning (ML) methods are increasingly used for clinical prediction in other settings.

Methods

We investigated whether ML methods improved prediction of incident dementia in SVD over traditional statistical. We included three cohorts with varying SVD severity (RUN DMC, n=503; SCANS, n=121; HARMONISATION, n=265). Baseline demographics, vascular risk factors, cognitive scores, and MRI features of SVD were used for prediction. We conducted both survival analysis and classification analysis predicting 3-year dementia risk. For each analysis, several ML methods were evaluated against standard Cox or logistic regression. Finally, we compared the feature importance ranking by different models.

Results

We included 789 participants without missing data in the survival analysis, among whom 108 (13.7%) developed dementia during a median (IQR) follow-up period of 5.4 (4.1, 8.7) years. After excluding those censored before three years, we included 750 participants in the classification analysis, among whom 48 (6.4%) developed dementia by year 3. Comparing statistical and ML models, only the regularised Cox/logistic regression models outperformed their statistical counterparts overall, but not significantly so in survival analysis. Baseline cognitive scores were highly predictive, and all methods ranked global cognition as the most important feature.

Discussion

ML survival or classification models brought little improvement over traditional statistical approaches in predicting incident dementia in SVD. ML approaches may be better suited to prediction problems using a larger number of input variables.

Introduction

The Kazakh population has been increasing in age over the last two decades. Life expectancy in Kazakhstan in 2022 was 73.8 years (y). Noncommunicable diseases (NCDs) accounted for ∼84% of deaths, particularly among men, and included cardiovascular disease, diabetes, chronic respiratory disease and cancer. It is anticipated that life expectancy trends will be similar among People Living With HIV (PLWH) who are virally suppressed in Kazakhstan. However, the prevalence and types of aging-related NCDs among Kazakh PLWH are unknown, despite ∼40% of Kazakh PLWH being age >40 years (y). In addition, and limited knowledge exists about the NCD-HIV care continuum.

Methods

An ongoing cross-sectional study is being conducted among PLWH, >40y at the Almaty AIDS center. Cardiovascular, clinical, sociodemographic, mental health, medical history, health behavior, and HIV measures are collected. The Montreal Cognitive Assessment was included (range: 0-30).

Results

113 PLWH were interviewed over ∼6 months (43.4% females; 54.9% age 40-49y, 30.1%, 11.5% and 3.5% age 50-59, 60-69, >70 years, respectively; gender: 58.3% cis men, 41.7% cis women; 20.4% self-reported Asian (Kazakh) race, 56.6% White (Russian), 23.0% unknown; 55.4% were employed; 25.7% reported education beyond college; 65.5% consumed alcohol; 76.1% were current smokers and 26.5% drug users. 54% had healthy BMI (18.5- <25 kg/m2). Systolic blood pressure range was 90-140mmHg (median 120); diastolic blood pressure range, 60-100mmHg (median 80). Median oxygen saturation was 98%. 76.7% participants had undetectable HIV viral load (<50 copies/ml), and 16.7% exhibited CD4 cell count <200 cells/mm3. However, 36.3% had high NT-pro-BNP (≥125 pg/ml), which was accompanied by a higher mean HIV viral load (p=0.026). Mean plasma glucose (mmol/l) and triglycerides were higher (p<0.10) among those with NT- proBNP ≥125 pg/ml. Among those taking antiretroviral therapies over a longer time period, there was higher NT-proBNP, however p>0.05. The MoCA indicated that 61.9% scored <26 (raw score); average 23.1. Comparing those with MoCA <26 versus ≥26, there were no differences in pro-BNP or lipid levels, HIV viral load or CD4+ count. However, diastolic blood pressure was higher among those with MoCA<26 (p=0.043).

Discussion

Further investigation to understand cardiovascular contributors to cognitive impairment among PLWH is necessary.

Introduction

Cerebral small vessel disease (cSVD) is a major contributor to stroke and vascular cognitive impairment. However, other potential physical and psychological consequences have been described. Our aim was to provide an overview of systematic reviews describing clinical phenotypes associated with cSVD.

Methods

We searched four multidisciplinary databases from inception to December 2022. We included reviews describing concurrent clinical phenotypes in individuals with neuroimaging evidence of cSVD, defined using the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE-1) criteria. We broadly classified phenotypes into cognitive, mood and neuropsychiatric, respiratory, cardiovascular, renal-urinary, peripheral nervous system, locomotor, and gastrointestinal. We included studies assessing multiple cSVD features or using a summary cSVD score, and studies examining individual cSVD markers. We extracted risk-factor adjusted effect estimates, where possible, and assessed methodological quality using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) tool.

Results

We included 24 systematic reviews reporting on 685 original studies and >1,135,940 participants. Cognitive and neuropsychiatric phenotypes were examined most often, particularly in relation to white matter hyperintensities (range of risk ratios for neurocognitive phenotypes, 1.21-1.49; and for neuropsychiatric, 1.02-5.71). Two reviews focused solely on perivascular spaces. No reviews assessed lacunes or small subcortical infarcts separately from other cSVD features. Reviews on peripheral nervous system, urinary or gastrointestinal phenotypes were lacking. Fourteen reviews had high methodological quality. Heterogeneity in cSVD definitions and phenotypic assessments was substantial.

Discussion

Neuroimaging markers of cSVD are associated with various concurrent clinical conditions. Cognitive and neuropsychiatric phenotypes have been reviewed most extensively, while few reviews assessed gait and mobility. Reviews for many body systems were lacking. Similarly, while white matter hyperintensities were relatively well studied, there were limited data on phenotypes associated with perivascular spaces and lacunes. Future studies should characterize the full clinical spectrum of cSVD, and explore clinical associations beyond neurocognitive and neuropsychiatric presentations.

Introduction

HCHS/SOL is a representative study of Hispanic/Latinos living in the US. SOL-INCA examines cognition amongst those of HCHS/SOL over age 50 and SOL-INCA-MRI obtains quantitative MRI measures on a subgroup of these individuals. Prior research in SOL-INCA found that vascular risk factors summarized by the Framingham Cardiovascular Risk Score (Fram CVD) is associated with Mild Cognitive Impairment (MCI)1. We hypothesize that the extent of white matter hyperintensities (WMH) will partially mediate this impact of Fram CVD on MCI prevalence in this cohort.

Methods

SOL-INCA-MRI consists of 2366 individuals of Hispanic/Latino Heritage from 4 centers across the US. Demographics of the cohort are summarized in the Table. High resolution MRI were acquired and WMH burden measured by previously reported methods2. WMH volumes were natural log transformed and corrected for scanner type using NeuroCombat. General linear models were used to test the associated between diagnosis (normal, questionable impairment and MCI) and Fram CVD and WMH adjusting for age, gender, education, heritage, and center. Casual mediation analysis was also performed to assess the extent to which WMH mediated the association between Fram CVD and diagnosis.

Results

Subjects were 64.6 + 6.8 years of age at MRI, 68.5% were female, 16% had questionable impairment and 13% had MCI. Mean Fram CVD risk was 11.4 + 0.9%. Mean log WMH was -0.13 +1.55. Diagnosis was significantly associated with Fram CVD (beta= 780, p <0.0001) and WMH (beta =34, p <0.0001). Fram CVD was also strongly associated with WMH (beta = 2.6, p <0.0001). Causal mediation analysis found that WMH significantly mediated the association of Fram CVD to Diagnosis (p < 0.0001) by a proportion of 10%.

Discussion

These results indicate that at least part of the impact of Fram CVD of MCI prevalence is mediated by the impact of Fram CVD on white matter injury suggesting that microvascular disease is a strong predictor of cognitive impairment amongst Hispanic/Latinos in the US.

Introduction

To investigate the psychometric properties, administration efficiency and implementational feasibility of a previously piloted voice recognition- based digital cognitive screener for dementia detection in a large-scale community of elderly participants.

Methods

Eligible participants completed the demographic, lifestyle investigations and the DCS. Domain-specific and global cognition was assessed by a comprehensive neuropsychological test battery. Diagnosis of mild cognitive impairment(MCI) and dementia was made based on the clinical dementia rating. Completion rate and administration time for the DCS were recorded. Correlation between the DCS and domain-specific and global cognitive performance were assessed. Receiver operating characteristic (ROC) analyses examined the discriminate validity of the DCS in detecting MCI and dementia. A cost-consequences analysis was conducted to compare the screening efficacy of DCS with two traditionally administered cognitive assessment tools, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), was conducted.

Results

Among a total of 11,186 participants, the completion rate of the DCS was 97·5% with a conduction time of 5·6–6·1 minutes, regardless of gender, age and education stratifications. DCS total score was significantly associated with domain-specific and global cognitive z-scores. Area under the curves (AUCs) of the DCS were 0·95 (0·92, 0·99) and 0·83 (0·79, 0·88) for dementia and MCI detection, respectively. There was no significant difference on the AUCs among different age- and education-stratified subgroups. Comparing with the MoCA and MMSE, DCS resulted in time savings of 35·4%–36·0% and 30·7%–31·2% for identifying dementia cases, as well as 22·6%–22·8% and 16·2%–16·4% for identifying MCI cases.

Discussion

Our findings demonstrated that the DCS was an effective and efficient tool for case-finding of dementia and MCI in a Chinese community. The large-scale implementation of the DCS among older Chinese adults could be a practical cognitive screening strategy to improve the management of healthcare resources.

Introduction

Nutrition, a modifiable risk factor, presents a low-cost prevention strategy to reduce the burden of cognitive impairment and dementia. However, studies examining the effects of dietary patterns on cognition are lacking in multi-ethnic Asian populations. We investigate the association between diet quality, measured with the Alternative Healthy Eating Index (AHEI)-2010, and cognitive impairment in middle-and old-aged adults of different ethnicities (Chinese, Malay, Indian) in Singapore.

Methods

This cross-sectional study (n=3138) was based on data from the Singapore Multi-Ethnic Cohort. Dietary intake collected with a validated semi-quantitative Food Frequency Questionnaire were converted into AHEI-2010 scores, where trans-fat and sodium consumption were not considered and a score range of 0-90 was allowed. Higher AHEI-2010 score indicates better compliance to recommended dietary pattern. Cognition, assessed with the Mini-Mental State Examination (MMSE), was analysed as a continuous or binary outcome (cognitively impaired is defined using education-based cut-offs of <23, 25 or 27 for participants with no education, primary school education and secondary school education and above). Multivariable linear and logistic regression models were used to examine associations between AHEI-2010 and cognition, adjusting for covariates.

Results

Participants have a mean age of 56.6 (SD = 9.3) years, and 41.6% were male. Participants have a mean AHEI-2010 score of 52.4 (SD = 9.8) and 988 (31.5%) participants had cognitive impairment. Ethnic Chinese (mean = 51.3, SD = 9.6) and Indians (mean = 51.3, SD = 9.7) had higher AHEI-2010 score than Malays (mean = 47.6, SD = 9.9). Higher AHEI-2010 scores were significantly associated with higher MMSE score (p trend < 0.001) and lower odds of cognitive impairment (p trend = 0.01). Compared with lowest quartile, participants from highest quartile had 0.44 (95%CI 0.22, 0.67) higher MMSE score and 31% less cognitive impairment odds (OR = 0.69, 95%CI 0.54, 0.88) after adjusting for all the covariates. However, no significant associations were observed for individual dietary components of the AHEI-2010 with MMSE or cognitive impairment.

Discussion

Healthier dietary patterns were associated with better cognitive function in middle- aged and older Singaporeans. These findings could inform better support to promote healthier dietary patterns in Asian populations.

The Global Burden of Disease Study projects an almost tripling of dementia cases worldwide in the next 30 years making it important to recognize and understand modifiable risks and preventatives for cognitive impairment. Recent studies suggest that prevention or treatment of cardiovascular risks may be an important strategy to prevent or slow the progression of cognitive impairment. In 2017, the American Heart Association and American Stroke Association introduced metrics for "optimal brain health". These metrics defined brain health in terms of ideal health behaviors and factors.

Since then and leading up to 2017, a number of clinical trials have been conducted to investigate the potential of modification of cardiovascular risks on prevention of dementia or cognitive impairment and thus, enhancement of brain health. This discussion is a review of findings from clinical trials focusing on interventions, including antihypertensive agents, glycemic control and lipid-lowering therapies, multidomain approaches, and antithrombotic medications. Notably, the results highlight the promise of intensive blood pressure lowering strategies and multidomain approaches, as evidenced by the FINGER trial. The review also discusses the potential of treatment or prevention of cerebral small vessel disease (cSVD) and the application of Mendelian randomization as a strategy to preserve brain structure and function.

Brain health initiatives and programs are gaining traction worldwide. Some are clinically based, others research based, and some are a combination of clinical and research action plans. Achievement of global brain health is a challenging endeavor with prerequisites including but not limited to multidisciplinary and multisectoral approaches, strengthening of neurologic policies at local and regional levels, global advocacy, leadership and collaboration amongst stakeholders, development of technical and guidance documents, and strengthening and interpretation of the relevant evidence. Over 1 billion persons worldwide are impacted by neurologic disorders, and brain health initiatives are needed to curb the human suffering and cost of these disorders. We provide a brief review of select brain health initiatives and programs and offer possible steps to achieve brain health globally.