Impact of nutrition on cognition and its association with blood and brain Alzheimer disease related biomarkers

Alzheimer’s disease (AD), the most common form of senile dementia, currently affects over 35 million people worldwide. While there is no cure or effective treatment, early intervention programs hold considerable promise. Following particular dietary patterns represents one potential intervention strategy accessible to all. Results from previous studies investigating the association of diet, cognition and biomarkers of AD are inconsistent: Positive results have been reported (1-7), whilst others have shown no associations. Prior to this thesis, no study has assessed the relationship of four dietary patterns to cognition, blood-based and neuroimaging biomarkers of AD in a large highly-characterised ageing cohort. Participants drawn from the Australian Imaging, Biomarkers, and Lifestyle study of ageing, provided a fasting blood sample, underwent comprehensive neuropsychological assessment and neuroimaging at baseline, 18 and 36 month follow-up assessments, and completed a Cancer Council of Victoria food frequency questionnaire (used to construct dietary patterns) at baseline. Chapter 3 explored the relationship between dietary pattern adherence and cognition. AD participants demonstrated reduced adherence to the ‘healthy’ Mediterranean (MeDi) and prudent diets, and higher adherence to the ‘unhealthy’ western diet and the inflammatory dietary index compared to cognitively healthy controls (HC). Longitudinal analysis conducted on individuals classified as HC at baseline proposes the importance of adhering to a ‘healthy’ dietary pattern such as the MeDi, with respect to reducing risk for cognitive decline: Executive function and visuospatial functioning appeared most susceptible to the influence of diet. Chapter 4 investigated the potential mechanisms underlying the observed effects of dietary patterns on cognition. A lack of significant associations between the MeDi and western diet patterns and biomarker indexes of metabolic syndrome and cardiovascular disease risk, suggests that modulation of these factors may not underlie the effects of diet on cognition reported in Chapter 3. Consistent with published literature, we found our western dietary pattern to be positively associated with levels of blood-based biomarkers of inflammation and the reverse to be true of our MeDi and prudent diet patterns. Our inflammatory dietary index was also strongly positively correlated with levels of numerous inflammatory biomarkers. The strong associations observed suggest that interplay between diet and elevated chronic inflammation may contribute to the effects of diet on cognition described in this thesis. Chapter 5 assessed the ‘reliability’ (similarity of 12 month dietary intake recalled on different occasions) and ‘validity’ (intake agreement between FFQ and a four-day weighed food record) of the online CSIROFFQ following addition of questions regarding foods of interest in AD research. Our results suggest that the modified CSIROFFQ is ‘reliable’ and a ‘relatively valid’ tool which provides acceptable assessment of long-term dietary intake in Australian older adults, particularly in the context of AD research. To our knowledge, this is the first study extensively comparing MeDi, inflammatory dietary index, western and prudent diet patterns to cognition and biomarkers of AD in an elderly, well-characterised cohort. Our results combined with published data, suggest diet has a role to play in AD prevention; however, it is clear that the complex link requires further characterisation

Genetic and cardiometabolic contributions to cognitive, structural brain and biomarker phenotypes

The number of individuals experiencing abnormal cognitive ageing is rapidly increasing, which can only in part be explained by an ageing population. Prevention of considerable cognitive decline is complicated by its heterogeneity and numerous risk factors. The most significant contributions to brain health and cognitive decline outside of age are higher genetic risk and poor cardiometabolic health. There are gaps in the literature and understanding regarding the extent to which common genetic or cardiometabolic conditions contribute to and interact with one another to influence brain health. Therefore, the overall aim of this PhD project is to explore genetic and cardiometabolic risks in relation to structural brain MRI measures, cognitive assessments, and blood biomarkers. This thesis used large-scale secondary data from the UK Biobank in which several analyses investigating associations between cardiometabolic conditions, genetic risks, cognition, and brain MRI data are the largest to date. The use of the UK Biobank cohort also allowed for controlling of confounders that have not been considered or accounted for in previous studies. The primary focus of this thesis was on genetic and cardiometabolic contributions to cognition and brain MRI. The main objectives were: (1) Contribute to the understanding of cardiovascular to brain health and (2) Determine the role of genetic risk factors on the brain and physical health in healthy adults. When examining multimorbidity, there were no clear trends between cardiometabolic groups and brain MRI metrics. However, this may have been due to a healthy selection bias in which those with multimorbidity were healthy enough for MRI assessments. When examining genetically elevated risk of cardiovascular disease (CVD) indexed by lipoprotein A (), we found associations with mean diffusivity and fractional anisotropy, suggesting a potential role of LpA in brain ageing. However, we found discrepancies between genetically elevated LpA and blood LpA, which should be further investigated. When calculating genetic risk scores for Alzheimer’s disease (AD) in healthy midlife adults, we found evidence for potential early ageing pathology within subfields of the hippocampus prior to significant cognitive impairments. We also found that this elevated genetic risk for AD was associated with elevated cystatin c. Elevated genetic risk of AD also showed significant sex differences in biomarker analyses. Creatinine and oestradiol were significantly associated with an elevated risk of Alzheimer’s in women but not men. These findings support routine stratification in exploratory research. This thesis emphasises the importance of epidemiological research that considers cardiometabolic, lifestyle and genetic risk factors together in the context of cognitive health. There is scope to build on this work in omics and cohort studies

Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes.

The last decade has witnessed a proliferation of neuroimaging studies characterising brain changes associated with Alzheimer's disease (AD), where both widespread atrophy and 'signature' brain regions have been implicated. In parallel, a prolonged latency period has been established in AD, with abnormal cerebral changes beginning many years before symptom onset. This raises the possibility of early therapeutic intervention, even before symptoms, when treatments could have the greatest effect on disease-course modification. Two important prerequisites of this endeavour are (1) accurate characterisation or risk stratification and (2) monitoring of progression using neuroimaging outcomes as a surrogate biomarker in those without symptoms but who will develop AD, here referred to as preclinical AD. Structural neuroimaging modalities have been used to identify brain changes related to risk factors for AD, such as familial genetic mutations, risk genes (for example apolipoprotein epsilon-4 allele), and/or family history. In this review, we summarise structural imaging findings in preclinical AD. Overall, the literature suggests early vulnerability in characteristic regions, such as the medial temporal lobe structures and the precuneus, as well as white matter tracts in the fornix, cingulum and corpus callosum. We conclude that while structural markers are promising, more research and validation studies are needed before future secondary prevention trials can adopt structural imaging biomarkers as either stratification or surrogate biomarkers.This study was supported by the National Institute for Health Research (NIHR, RG64473), Cambridge Biomedical Research Centre and Biomedical Research Unit in Dementia, and the Alzheimer's Society. Elijah Mak was in the receipt of the Gates Cambridge studentship

Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes.

The last decade has witnessed a proliferation of neuroimaging studies characterising brain changes associated with Alzheimer's disease (AD), where both widespread atrophy and 'signature' brain regions have been implicated. In parallel, a prolonged latency period has been established in AD, with abnormal cerebral changes beginning many years before symptom onset. This raises the possibility of early therapeutic intervention, even before symptoms, when treatments could have the greatest effect on disease-course modification. Two important prerequisites of this endeavour are (1) accurate characterisation or risk stratification and (2) monitoring of progression using neuroimaging outcomes as a surrogate biomarker in those without symptoms but who will develop AD, here referred to as preclinical AD. Structural neuroimaging modalities have been used to identify brain changes related to risk factors for AD, such as familial genetic mutations, risk genes (for example apolipoprotein epsilon-4 allele), and/or family history. In this review, we summarise structural imaging findings in preclinical AD. Overall, the literature suggests early vulnerability in characteristic regions, such as the medial temporal lobe structures and the precuneus, as well as white matter tracts in the fornix, cingulum and corpus callosum. We conclude that while structural markers are promising, more research and validation studies are needed before future secondary prevention trials can adopt structural imaging biomarkers as either stratification or surrogate biomarkers.This study was supported by the National Institute for Health Research (NIHR, RG64473), Cambridge Biomedical Research Centre and Biomedical Research Unit in Dementia, and the Alzheimer's Society. Elijah Mak was in the receipt of the Gates Cambridge studentship

Fish Intake and MRI Burden of Cerebrovascular Disease in Older Adults

BACKGROUND AND OBJECTIVE: Fish intake may prevent cerebrovascular disease (CVD), yet the mechanisms are unclear, especially regarding its impact on subclinical damage. Assuming that fish may have pleiotropic effect on cerebrovascular health, we investigated the association of fish intake with global CVD burden based on brain MRI markers. METHODS: This cross-sectional analysis included participants from the Three-City Dijon population-based cohort (aged >/=65 years) without dementia, stroke, or history of hospitalized cardiovascular disease, who underwent brain MRI with automated assessment of white matter hyperintensities, visual detection of covert infarcts, and grading of dilated perivascular spaces. Fish intake was assessed through a frequency questionnaire and the primary outcome measure was defined as the first component of a factor analysis of mixed data applied to MRI markers. The association of fish intake with the CVD burden indicator was studied using linear regressions. RESULTS: In total, 1,623 participants (mean age, 72.3 years; 63% women) were included. The first component of factor analysis (32.4% of explained variance) was associated with higher levels of all three MRI markers. Higher fish intake was associated with lower CVD burden. In a model adjusted for total intracranial volume, compared to participants consuming fish /=4 times per week had a beta = -0.19 (95% CI, -0.37; -0.01) and beta = -0.30 (-0.57; -0.03) lower indicator of CVD burden, respectively (P trend /=75 years. For comparison, in the younger age group, consuming fish 2-3 times a week was roughly equivalent (in opposite direction) to the effect of hypertension. DISCUSSION: In this large population-based study, higher frequency of fish intake was associated with lower CVD burden, especially among participants younger than 75 years, suggesting a beneficial effect on brain vascular health before manifestation of overt brain disease. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in individuals without stroke or dementia, higher fish intake is associated with lower subclinical CVD at MRI

The impact of APOE-ε4 status on sleep, rest-activity patterns and spatial navigation in healthy adults

INTRODUCTION Alzheimer's disease(AD) is the most common type of dementia manifesting mainly over the age of 65 with no curative treatment available. The risk of AD is increased in APOE-ɛ4 allele carriers and those with sleep and circadian disturbances. APOE-ε4 polymorphism was also shown to be associated with spatial navigation impairment, which has been proposed to serve as a potential early marker of AD. Yet, the interrelationships between APOE-ɛ4 carriership, sleep, rest-activity patterns and spatial navigation in healthy older adults are still unclear. The presented PhD project addresses this research gap. METHODS One-hundred-sixty-one healthy participants took part in extensive screening sessions (51 APOE-ε4+, age(M+SD)=63.18+7.84; 110 APOE-ε4-, age(M+SD)=65.66+9.98) of which fifty-eight (28 APOE-ε4+, age(M+SD)=64.45+7.36; 30 APOE-ε4-, age(M+SD)=65.23+10.34) participated in a 14-days-long actigraphy session supplemented by sleep diary. Thirty-five individuals (18 APOE-ε4+, age(M+SD)=64.21+8.58; 17 APOE-ε4-, age(M+SD)=65.00+9.54) underwent a 2.5-days-long laboratory session in dim light condition(<10lux) and followed a modified constant routine protocol in the Sleep and Brain Research Unit. After a baseline night, participants were randomly assigned to either a 40-h sleep deprivation(SD) or a multi-nap(MN) experimental condition followed by a recovery night. Cognitive assessments were administered every 4-hours. Nine 80-minute-long naps were scheduled every 160 minutes(MN condition). RESULTS and DISCUSSION Our results suggest that APOE-ɛ4 carriership in healthy elderly adults has a limited impact on subjective and objective sleep quality, daytime sleepiness and circadian rhythmicity measures besides a decrease in circadian rest-activity amplitude and a marginal decrease in the percentage of Total-Sleep-Time spent in N2 at baseline night. Yet, recovery sleep revealed an altered physiological recovery process in APOE-ɛ4 allele carriers that was reflected as a low percentage of deep sleep following SD protocol. Further, the outcomes suggest that spatial navigation performance is modulated neither by time-of-a-day nor is affected by increasing sleep pressure or by their associations with APOE-ɛ4 carriership

Exploring brain structure and blood metabolic profiles using Alzheimer's pathway specific polygenic risk scores

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects older people. It is common, affecting around one in ten people over 65 years old. In addition to the autosomal dominant AD genes and Apolipoprotein E (APOE), genome wide association studies (GWAS) have identified a number of small risk loci. These can be combined into polygenic risk scores (PRS) which can predict AD relatively accurately and are associated with a number of neurodegeneration phenotypes. Pathway analyses of GWAS data have implicated a number of biological processes, including the immune response and lipid metabolism. How AD pathway specific genetic burden manifests in brain structure or serum metabolic profiles is not well understood. In this thesis, volumetric and diffusion MRI and serum lipid and inflammatory markers were used to investigate manifestations of AD polygenic risk in two large population cohorts. Specifically, these analyses sought to determine 1) whether AD polygenic risk scores were associated with neuroimaging and blood marker phenotypes linked to neurodegeneration in younger and older adult cohorts; and 2) whether PRS informed by disease pathways were associated with different patterns of alteration in brain structure, serum lipids or inflammatory markers. The relationships between PRS and phenotypes were explored using linear regression. There were significant associations between pathway specific PRS, grey matter volumes and white matter microstructure. Although some of these attenuated when the APOE region was excluded from the score, some were maintained, in particular cortical thickness in mature adults, which appeared to be independent of APOE. Increased pathway specific polygenic risk for AD was also associated with serum markers such as increased blood lipids, particularly low density lipoprotein (LDL) cholesterol and total cholesterol, and decreased C-Reactive Protein (CRP). However, these effects seemed to be driven by the APOE locus. Further longitudinal studies, combining advanced MRI techniques with cerebrospinal fluid and neuroradiology biomarkers, will be required to confirm these findings and assess their biological significance

Computerized tools : a substitute or a supplement when diagnosing Alzheimer's disease?

Alzheimer’s disease (AD) is the most common form of dementia in the elderly characterized by difficulties in memory, disturbances in language, changes in behavior, and impairments in daily life activities. By the time cognitive impairment manifests, substantial synaptic and neuronal degeneration has already occurred. Therefore, patients need to be diagnosed as early as possible at a preclinical or presymptomatic stage. This will be important when disease-modifying treatments exist in the future. The main focus of this thesis is on the study of structural neuroimaging in AD and in prodromal stages of the disease. We emphasize the use of statistical learning for the analysis of structural neuroimaging data to achieve individual prediction of disease status and conversion from prodromal stages. The main aims of the thesis were to develop and validate computerized tools to identify patterns of atrophy with the potential of becoming markers of AD pathology using structural magnetic resonance imaging (sMRI) data and to develop a segmentation tool for Computed Tomography (CT). Using automated neuroanatomical software we measured multiple brain structures that were given to statistical learning techniques to create discriminative models for prediction of presence of disease and conversion from prodromal stages. Building statistical models based on sMRI data we investigated optimal normalization strategies for the combination of structural measures such as cortical thickness, cortical and subcortical volumes (Study I). A baseline model was created based on the optimal normalization strategy and combination of structural measures. This model was used to compare the discrimination ability of different statistical learning algorithms (decision trees, artificial neural networks, support vector machines and orthogonal partial least squares (OPLS)). Additionally, the addition of age, years of education and APOE phenotype was added to the baseline model to assess the impact on discrimination ability (Study II). The OPLS classification algorithm was trained on the baseline model to produce a structural index reflecting information about AD-like patterns of atrophy from each individual’s sMRI data. Additional longitudinal information at one-year follow-up was used to characterize the temporal evolution of the derived index (Study III). Since total intracranial volume (ICV) remains a morphological measure of interest and CT is today widely used in routine clinical investigations, we developed and validated an automated segmentation algorithm to estimate ICV from CT scans (Study IV). We believe computerized tools (automated neuroimaging software and statistical discriminative algorithms) have significantly enriched our knowledge and understanding of associated neurodegenerative pathology, its effects on cognition and interaction with age. These tools were mainly developed for research purposes but we believe all accumulated knowledge and insights could be translated into clinical settings, however, that is a challenge that remains open for future studies

Behavioural and neural characteristics of navigation impairments in preclinical Alzheimer’s disease

Detection of incipient Alzheimer disease (AD) pathophysiology is critical to identify preclinical individuals and target potentially disease-modifying therapies towards them. Cognitive fingerprints for incipient AD are virtually non-existent as diagnostics and outcomes measures are still focused on episodic memory deficits as the gold standard for AD, despite their low sensitivity and specificity for identifying at-risk preclinical individuals. This thesis focuses on spatial navigation deficits, which are increasingly shown to be present in atrisk individuals, because the navigation system in the brain overlaps substantially with the regions affected by AD in both animal models and humans. Experimental chapters 2 and 3, show that a novel test battery captures navigation deficits that precede the onset of verbal and non-verbal episodic memory deficits in preclinical disease and that resting-state functional connectivity between the EC and the PCC underpins such deficits. Evidence for moderate test re-test reliability in the same non-clinical sample is presented in chapter 4. Moving beyond detection of preclinical disease, and towards prevention, in chapter 5 we examined whether marine fish oils help preserve the volume of AD vulnerable brain regions and found that low circulating DHA blood concentration predicts preservation of hippocampal and entorhinal volume in preclinical AD. This is potentially due to increased DHA uptake from the blood to the brain due to preclinical disease. Taken together, the research advances our conceptual understanding of the pathological and compensatory changes that characterise preclinical AD and offers important information toward generating more accurate risk profiles for AD vulnerable adults