Aims

Aging is the main risk factor for most of the neurodegenerative diseases. The aim of this study was to investigate cortical thinning changes across lifespan in healthy brain revealing structural network vulnerability to neurodegeneration.

Methods

The cohort included 128 healthy individuals aged 20-85 years, who underwent an MRI scan. T1-weighted images were used to estimate vertex-wise cortical thickness maps, then grouped into 83 regions. For each region, cortical thickness trajectory with advancing age was estimated, including sex as covariate. Regions were ranked based on their relative thickness at the end of the observed lifetime, assessing regional changes over time. Mean regional thickness was correlated with relative change over time.

Results

The highest cortical thinning was observed in the temporal lobe (parahippocampal, entorhinal, superior and middle temporal and fusiform), frontal lobe (lateral orbitofrontal, superior and inferior frontal, including pars triangularis and opercularis, and rostral anterior cingulate), parietal lobe (the isthmus of cingulate, precuneus, supramarginal and inferior parietal) and in the insular cortex. Interestingly, occipital regions (cuneus, lateral occipital, lingual, pericalcarine), and motor and premotor areas (precentral, postcentral and paracentral regions) showed the least cortical thickness change compared to the whole brain across lifespan. Finally, positive correlation was found between mean regional thickness and its relative change over time.

Conclusions

This study highlights structural vulnerability of brain regions to aging and provides information concerning trajectories of normal brain aging, identifying those areas that might be more vulnerable to the attack of neurodegeneration.

Supported by: European Research Council (StG-2016_714388_NeuroTRACK).

Aims

Some individuals maintain high levels of cognitive health despite reaching extreme ages. To identify molecular mechanisms that confer resilience or resistance to age- or disease-related cognitive decline, we compared the proteome of brain tissues from centenarians with non-demented individuals and Alzheimer’s disease (AD) patients covering an age-continuum of 50-95 years.

Methods

We performed quantitative proteomics on middle temporal lobe tissues collected from 58 centenarians from the 100-plus Study, 61 non-demented individuals and 91 AD patients from the Netherlands Brain Bank. Next, we investigated protein-abundance using age and Braak stages as independent variables and put findings in centenarians in both contexts.

Results

We identified 3,448 proteins across all samples: the expression of 472 proteins associated with Braak stages, and 174 proteins associated with age. The abundance of 13 Braak stage related proteins differed between centenarians and AD cases, including ubiquitin, cytoskeletal- and synaptic proteins. For 97 proteins that associated with increasing age, we observed that expression in cognitively healthy centenarians resembled abundances observed at younger ages (e.g., microtubular, intermediate filament and myelin-associated proteins).

Conclusions

We present a unique view on both aging and AD, attempting to disentangle the effects of the two. We identified unique patterns of regulation of (i) Braak stage-related, (ii) age-related, and (iii) age- and Braak stage-related proteins. The 13 proteins differentially regulated in centenarians compared to AD cases at Braak stage IV, may point to mechanisms involved in resilience against the presence of tangles. In contrast, the 97 differentially regulated aging proteins point towards key mechanisms in brain aging.

Aims

Despite of huge amounts of genomic determinants for the late onset Alzheimer’s disease (LOAD), the clinical translation of genetic risk estimates remains challenging. We aimed to undertake an omnigenic analysis of common variants and to assess the effects of omnigenic risk score on cumulative risk of LOAD in a clinical prevention context.

Methods

We investigated incident dementia in cognitively healthy participant (aged >60 years) from the community-based Gwangju Alzheimer’s & Related Dementias (GARD) study, an ongoing prospective cohort study based in Republic of Korea, focusing on all progressive stages of Alzheimer development in elderly people. The GARD study comprises participants in various baseline (initiated in 2013), who are followed up every 1-2 years and monitored by multi-modal records Here, we developed an ethnicity adjustment method incorporating the prior genome-wide association (GWA) knowledge and applied it to build a prediction model in Bayesian framework based on omnigenic risk score (ORS). Briefly, we estimated omnigenic effects of those GWA genes using multi-modal AD phenotypes and evaluated the risk probability of LOAD by applying likelihood ratios derived from integration of omnigenic common variants to age- and sex-appropriate probabilities.

Results

Blind test of this approach with three different independent dataset showed its validity in application for screening and prevention purpose. When validated with 3 different independent samples, the proposed model showed 75.3%±1.82% of accuracy (max 79.1%) with 74.8%±3.27% and 73.7%±0.03% of sensitivity (max 80.5%) and specificity (73.7%), respectively.

Conclusions

The proposed model shows its validity in application for screening of AD patients, specially in preclinical stage.

Aims

Objectives: The mechanisms by which modifiable risk factors influence dementia are poorly understood, impeding the development of preventive interventions. We aimed to characterise the shared genetic architecture between Alzheimer’s disease (AD) and its risk factors using novel multivariate genomic methods.

Methods

Methods: We used genomic structural equation modelling (SEM) to model the genetic covariance between AD and its major modifiable risk factors. We subsequently performed multivariate GWAS to identify the genetic variants driving the covariance within our model and conducted functional annotation to explore the potential biological effects of these loci.

Results

Results: AD and hypertension were largely genetically distinct, whereas the other risk factors displayed widespread genetic overlap. Genomic SEM identified a Common Factor of genetic covariance between AD and its risk factors and three additional sub-clusters of covariance between specific sets of risk factors. GWAS identified distinct groups of shared loci reaching genome-wide significance, including 285 loci associated with the Common Factor. These loci were highly enriched in brain tissues and mapped to genes implicated in a range of neuronal functions.

Conclusions

Conclusions: Our findings demonstrate extensive genetic overlap between dementia modifiable risk factors that can be explained by four groupings of genetic variants that are highly expressed in the brain and are associated with neuronal function. This suggests that risk factors may increase dementia risk via genetic pathways linked to poor brain health rather than via dementia-specific pathways. Future studies that incorporate these variants within polygenic risk scores or causal analyses may help to improve our knowledge of dementia risk.

Aims

Epidemiological studies have suggested a link between rheumatoid arthritis and Parkinson’s disease (PD). Aim was to evaluate how use of disease-modifying anti-rheumatic drugs (DMARDs) is associated with risk of PD in persons with rheumatoid arthritis.

Methods

Nested nationwide case-control study was conducted within the Finnish Parkinson’s disease (FINPARK) cohort that includes 22,189 Finnish persons who got clinically verified PD diagnosis in 1996-2015. Cases were Finnish persons with PD diagnosed during 1999-2015 and rheumatoid arthritis diagnosed ≥3 years before PD (N=315). Cases were matched with up to seven control persons by age, sex, duration of rheumatoid arthritis and university hospital district (N=1,571). DMARDs were categorised into five classes and data on drug use was identified from the Prescription Register since 1995. Associations were studied with conditional logistic regression adjusted for confounders.

Results

Use of DMARDs was not associated with risk of PD with three-year lag period applied between exposure and outcome, except chloroquine/hydroxychloroquine which associated with decreased risk (adjusted odds ratio 0.74; 95% confidence interval 0.56-0.97). Other DMARDs, including sulfasalazine, methotrexate, gold preparations and immunosuppressants, had no association with risk of PD.

Conclusions

Our results suggest that the previously implied lower risk of PD in people with rheumatoid arthritis is not explained by DMARD use as these drugs in general did not modify the risk of PD among persons with rheumatoid arthritis. Association between chloroquine/hydroxychloroquine and lower risk of PD as well as the possible underlying mechanisms should be further investigated.

Aims

Despite an incidence rate of up to 80% suffering post-operative cognitive decline (POCD), there is no clinical or standard means for identifying at-risk patients. As such, POCD presents an unmet need, particularly as surgery can significantly accelerate cognitive impairment in patients with preoperative diagnosis of mild-cognitive-impairment or Alzheimer’s disease. Here we present results from a secondary analysis of the ‘Biomarker Development for Postoperative Cognitive Impairment in the Elderly’ study, to characterise cognitive and clinical risk factors.

Methods

Analysis was carried out in n = 928 elective surgery patients. Patients were ≥65 years with MMSE scores >23, and had clinical and cognitive evaluations sampled prior to surgery (baseline), at discharge (7-days post-surgery) and at 3-month follow-up. Cognitive tests from the CANTAB battery covered domains of memory, attention and executive function. Key clinical factors included: disease history, health/lifestyle risks, delirium, sedation, pain, medication and drug scales.

Results

Baseline performance on individual measures of cognition and various clinical variables were significant predictors of cognitive decline on day 7 and 3 months post-surgery; using a global composite score of cognitive function to measure PCOD. Linear regression models revealed key predictors, including: low baseline performance on tests of verbal, episodic and working memory, alongside increased age, anesthesia, and frailty.

Conclusions

A secondary analysis of a large European dataset successfully identified a combination of cognitive and clinical factors determining POCD. A standardized way to account for key factors associated with risk would provide major medical advancement to this field and should continue to be the focus of future research.

Abstract Body

AIMS: There is increasing interest in primary, secondary, and tertiary prevention approaches to address mild cognitive impairment (MCI) and Alzheimer’s disease and related dementias (ADRD). A significant challenge is measurement of resilience and vulnerability factors that can (a) distinguish between healthy brain aging and MCI/ADRD, and (b) serve as intervention targets. To address this challenge, we created the Resilience Index (RI), a quantifiable measure of brain health, and the Vulnerability Index (VI), a weighted measure of MCI/ADRD risk.

METHODS: We analyzed 241 participants completing a comprehensive clinical-cognitive evaluation. Six lifestyle factors (physical activity, cognitive activity, social engagement, dietary patterns, mindfulness, cognitive reserve) were combined to derive the RI. Twelve easily-obtained sociodemographic, medical, and functional factors were used to develop the VI.

RESULTS: The RI had a 9-fold odds ratio to discriminate individuals with and without cognitive impairment. Individuals with high RI scores (>143) had better cognitive, functional, and behavioral ratings than individuals with low RI scores. The VI had a 17-fold odd ratio to discriminate individuals with and without cognitive impairment. Individuals with high VI scores (≥8) had worse cognitive, functional, and behavioral ratings than those with low VI scores. Combining RI and VI scores differentiated between healthy controls and MCI/ADRD and provided insight into risk of transition/conversion.

CONCLUSIONS: The RI and VI are brief yet powerful indices of brain health and risk of MCI/ADRD. Combining resilience and vulnerability could provide a guide to develop personalized prevention plans to support brain health and identifying asymptomatic individuals for risk of MCI/ADRD.