Habitual dietary nitrate intake and cognition in the Australian Imaging, Biomarkers and Lifestyle Study of ageing: A prospective cohort study

Background & aims Dietary nitrate improves cardiovascular health via a nitric oxide (NO) pathway. NO is key to both cardiovascular and brain health. There is also a strong association between vascular risk factors and brain health. Dietary nitrate intake could therefore be associated with better cognitive function and reduced risk of cognitive decline. This is yet to be investigated. The aim of this study was to investigate the association between habitual intake of dietary nitrate from sources where nitrate is naturally present, and cognitive function, and cognitive decline, in the presence or absence of the apolipoprotein E (APOE) ε4 allele. Methods The study included 1254 older adult participants of the Australian Imaging, Biomarkers and Lifestyle Study of Ageing who were cognitively normal at baseline. Plant-derived, vegetable-derived, animal derived nitrate (not including meat where nitrate is an allowed additive), and total nitrate intakes were calculated from baseline food frequency questionnaires using comprehensive nitrate databases. Cognition was assessed at baseline and every 18 months over a follow-up period of 126 months using a comprehensive neuropsychological test battery. Multivariable-adjusted linear mixed effect models were used to examine the association between baseline nitrate intake and cognition over the 126 months (median [IQR] follow-up time of 36 [18–72] months), stratified by APOE ε4 carrier status. Results In non APOE ε4 carriers, for every 60 mg/day higher intake of plant-derived nitrate at baseline there was an associated higher language score [β (95% CI): 0.10 (0.01, 0.19)] over 126 months, after multivariable adjustments. In APOE ε4 carriers, there was an associated better episodic recall memory [0.24 (0.08, 0.41)] and recognition memory [0.15 (0.01, 0.30)] scores. Similar associations were seen for the intakes of vegetable-derived and total nitrate. Additionally, in APOE ε4 carriers, for every 6 mg/day higher intake of animal-derived nitrate (excluding meat with nitrate as an allowed additive) at baseline there was an associated higher executive function score [β (95% CI): 1.41 (0.42, 2.39)]. We did not find any evidence of an association between dietary nitrate intake and rate of cognitive decline. Conclusion Our results suggest that habitual intake of dietary nitrate from sources where nitrate is naturally present impacts cognitive performance in an APOE genotype contingent manner. Further work is needed to validate our findings and understand potential mechanisms underlying the observed effects

Amyloid-related memory decline in preclinical Alzheimer\u27s disease in dependent on APOE ε4 and is detectable over 18-months

High levels of β-amyloid (Aβ) in the brain and carriage of the APOE ε4 allele have each been linked to cognitive impairment in cognitively normal (CN) older adults. The aim of this study was to investigate the relationship between cerebral Aβ level, APOE ε4 carrier status, and cognitive decline over 18 monthes, in 317 cognitively healthy (CN) older adults (47% males, 52.4% females) aged between 60 and 89 years (Mean = 69.9, SC = 6.8). Cognition was assessed using the Cogstate Brief Battery (CBB) and the California Verbal Learning Test, Second Edition (CVLT-II). Planned comparisons indicated that CN older adults with high Aβ who were also APOE ε4 carriers demonstrated the most pronounced decline in learning and working memory. In CN older adults who were APOE ε4 non-carriers, high Aβwas unrelated to cognitive decline in learning and working memory. Carriage of APOE ε4 in CN older adults with low Aβ was associated with a significantly increased rate of decline in learning and unexpectedly, improved cognitive performance on measures of verbal episodic memory over 18 months. These results suggest that Aβ and APOE ε4 interact to increase the rate of cognitive decline in CN older adults and provide further support for the use of Aβ and APOE ε4 as biomarkers of early Alzheimer’s disease

Plasma high density lipoprotein small subclass is reduced in Alzheimer’s disease patients and correlates with cognitive performance

Background: The link between cholesterol and Alzheimer’s disease (AD) has received much attention, as evidence suggests high levels of cholesterol might be an AD risk factor. The carriage of cholesterol and lipids through the body is mediated via lipoproteins, some of which, particularly apolipoprotein E (ApoE), are intimately linked with AD. In humans, high density lipoprotein (HDL) is regarded as a “good” lipid complex due to its ability to enable clearance of excess cholesterol via ‘cholesterol reverse transport’, although its activities in the pathogenesis of AD are poorly understood. There are several subclasses of HDL; these range from the newly formed small HDL, to much larger HDL. Objective: We examined the major subclasses of HDL in healthy controls, mild cognitively impaired, and AD patients who were not taking statins to determine whether there were HDL profile differences between the groups, and whether HDL subclass levels correlated with plasma amyloid-β (Aβ) levels or brain Aβ deposition. Methods: Samples from AIBL cohort were used in this study. HDL subclass levels were assessed by Lipoprint while Aβ1–42 levels were assessed by ELISA. Brain Aβ deposition was assessed by PET scan. Statistical analysis was performed using parametric and non-parametric tests. Results: We found that small HDL subclass is reduced in AD patients and it correlates with cognitive performance while plasma Aβ concentrations do not correlate with lipid profile or HDL subfraction levels. Conclusion: Our data indicate that AD patients exhibit altered plasma HDL profile and that HDL subclasses correlate with cognitive performances

Buccal Cell Cytokeratin 14 Correlates with Multiple Blood Biomarkers of Alzheimer’s Disease Risk

Mild cognitive impairment (MCI) may reflect early stages of neurodegenerative disorders such as Alzheimer’s disease (AD). Our hypothesis was that cytokeratin 14 (CK14) expression could be used with blood-based biomarkers such as homocysteine, vitamin B12, and folate to identify individuals with MCI or AD from the Australian Imaging, Biomarkers and Lifestyle (AIBL) flagship study of aging. Buccal cells from 54 individuals were analyzed by a newly developed method that is rapid, automated, and quantitative for buccal cell CK14 expression levels. CK14 was negatively correlated with plasma Mg2 + and LDL, while positively correlated with vitamin B12, red cell hematocrit/volume, and basophils in the MCI group and positively correlated with insulin and vitamin B12 in the AD group. The combined biomarker panel (CK14 expression, plasma vitamin B12, and homocysteine) was significantly lower in the MCI (p = 0.003) and AD (p = 0.0001) groups compared with controls. Receiver-operating characteristic curves yielded area under the curve (AUC) values of 0.829 for the MCI (p = 0.002) group and 0.856 for the AD (p = 0.0003) group. These complex associations of multiple related parameters highlight the differences between the MCI and AD cohorts and possibly an underlying metabolic pathology associated with the development of early memory impairment. The changes in buccal cell CK14 expression observed in this pilot study supports previous results suggesting the peripheral biomarkers and metabolic changes are not restricted to brain pathology alone in MCI and AD and could prove useful as a potential biomarker in identifying individuals with an increased risk of developing MCI and eventually AD

Molecular genetics applied to clinical practice: the Cx26 hearing impairment

Mutations in the Cx26/GJB2 gene account for a large proportion of pre-lingual hearing impairment with a prevalence up to 50% in autosomal recessive cases and a still undefined prevalence in sporadic cases. Ninety-four subjects affected by non-syndromal sensorineural hearing impairment (NSHI) were enrolled in the study. The patients had either a family history of childhood hearing deficit or represented sporadic cases. The risk of an acquired cause of the deficit has been carefully excluded. Audiological characteristics were investigated. Cx26 mutations were found in 50% of subjects. Seventy-three per cent of mutations in this gene were 35delG, with significant geographical variations. In 7% of the putative Cx26 alleles no mutations were detected either in the coding region or in the non-coding exon 1. Cx26 hearing impairment involves all frequencies, is of variable severity, and is very rarely progressive and most frequently symmetrical between the two ears. The high occurrence of this type of pre-lingual hearing impairment argues for modification of the protocols used to investigate the aetiology of childhood hearing impairment. Early screening for Cx26 mutations in all patients with non-syndromal familial and sporadic permanent childhood hearing impairment seems justified

Relationship between atrophy and beta-amyloid deposition in Alzheimer disease

Objective: Elucidating the role of aggregated beta-amyloid in relation to gray matter atrophy is crucial to the understanding of the pathological mechanisms of Alzheimer disease and for the development of therapeutic trials. The present study aims to assess this relationship

A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease : results from the AIBL study

Dementia is a global epidemic with Alzheimer’s disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based screen.

The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals

Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages

The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals

Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages