Sixteen-year longitudinal evaluation of blood-based DNA methylation biomarkers for early prediction of Alzheimer\u27s disease

BACKGROUND: DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for Alzheimer\u27s disease (AD) prediction. OBJECTIVE: Testing long-term predictive ability ( \u3e 15 years) of existing DNAm-based epigenetic age acceleration (EAA) measures and identifying novel early blood-based DNAm AD-prediction biomarkers. METHODS: EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models (LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers were generated with epigenome-wide LMMs, and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10-16 years), and post-AD-onset time-points. RESULTS: EAA did not differentiate cases from controls during the follow-up time (p \u3e 0.05). Three new DNA biomarkers showed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions (p-values: 0.022- \u3c 0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOE 4-carriership (OR = 1.38 per 1 SD DNAm score increase versus OR = 13.58 for 4-allele carriage; AUCs = 77.2% versus 87.0%). Literature review showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs

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

Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer's disease.

Aging and Alzheimer's disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD

Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture

© 2020, The Author(s). Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

Background People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. Results We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. Conclusions We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences

Enhanced Fuzzy Elephant Herding Optimization-Based OTSU Segmentation and Deep Learning for Alzheimer’s Disease Diagnosis

Several neurological illnesses and diseased sites have been studied, along with the anatomical framework of the brain, using structural MRI (sMRI). It is critical to diagnose Alzheimer’s disease (AD) patients in a timely manner to implement preventative treatments. The segmentation of brain anatomy and categorization of AD have received increased attention since they can deliver good findings spanning a vast range of information. The first research gap considered in this work is the real-time efficiency of OTSU segmentation, which is not high, despite its simplicity and good accuracy. A second issue is that feature extraction could be automated by implementing deep learning techniques. To improve picture segmentation’s real-timeliness, enhanced fuzzy elephant herding optimization (EFEHO) was used for OTSU segmentation, and named EFEHO-OTSU. The main contribution of this work is twofold. One is utilizing EFEHO in the recommended technique to seek the optimal segmentation threshold for the OTSU method. Second, dual attention multi-instance deep learning network (DA-MIDL) is recommended for the timely diagnosis of AD and its prodromal phase, mild cognitive impairment (MCI). Tests show that this technique converges faster and takes less time than the classic OTSU approach without reducing segmentation performance. This study develops a valuable tool for quick picture segmentation with good real-time efficiency. Compared to numerous conventional techniques, the suggested study attains improved categorization performance regarding accuracy and transferability

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