Machine learning nominates the inositol pathway and novel genes in Parkinson's disease

There are 78 loci associated with Parkinson's disease in the most recent genome-wide association study (GWAS), yet the specific genes driving these associations are mostly unknown. Herein, we aimed to nominate the top candidate gene from each Parkinson's disease locus and identify variants and pathways potentially involved in Parkinson's disease. We trained a machine learning model to predict Parkinson's disease-associated genes from GWAS loci using genomic, transcriptomic and epigenomic data from brain tissues and dopaminergic neurons. We nominated candidate genes in each locus and identified novel pathways potentially involved in Parkinson's disease, such as the inositol phosphate biosynthetic pathway (INPP5F, IP6K2, ITPKB and PPIP5K2). Specific common coding variants in SPNS1 and MLX may be involved in Parkinson's disease, and burden tests of rare variants further support that CNIP3, LSM7, NUCKS1 and the polyol/inositol phosphate biosynthetic pathway are associated with the disease. Functional studies are needed to further analyse the involvements of these genes and pathways in Parkinson's disease.

Using Twitter to Understand COVID-19 Vaccine-Related Ageism During the Pandemic

BACKGROUND AND OBJECTIVES

During the rollout of coronavirus 2019 (COVID-19) vaccines, older adults in high-income countries were often prioritized for inoculation in efforts to reduce COVID-19-related mortality. However, this prioritization may have contributed to intergenerational tensions and ageism, particularly with the limited supply of COVID-19 vaccines. This study examines Twitter discourse to understand vaccine-related ageism during the COVID-19 pandemic to inform future vaccination policies and practices to reduce ageism.

RESEARCH DESIGN AND METHODS

We collected 1,369 relevant tweets on Twitter using the Twint application in Python from December 8, 2020, to December 31, 2021. Tweets were analyzed using thematic analysis, and steps were taken to ensure rigor.

RESULTS

Our research identified four main themes including (a) blame and hostility: "It's all their fault"; (b) incompetence and misinformation: "clueless boomer"; (c) ageist political slander; and (d) combatting ageism: advocacy and accessibility.

DISCUSSION AND IMPLICATIONS

Our findings exposed issues of victim-blaming, hate speech, pejorative content, and ageist political slander that is deepening the divide of intergenerational conflict. Although a subset of tweets countered negative outcomes and demonstrated intergenerational solidarity, our findings suggest that ageism may have contributed to COVID-19 vaccine hesitancy among older adults. Consequently, urgent action is needed to counter vaccine misinformation, prohibit aggressive messaging, and promote intergenerational unity during the COVID-19 pandemic and beyond.

The molecular spectrum of amyloid-beta (Aβ) in neurodegenerative diseases beyond Alzheimer's disease

This study investigated the molecular spectrum of amyloid-beta (Aβ) in neurodegenerative diseases beyond Alzheimer's disease (AD). We analyzed Aβ deposition in the temporal cortex and striatum in 116 autopsies, including Lewy body disease (LBD; N = 51), multiple system atrophy (MSA; N = 10), frontotemporal lobar degeneration-TDP-43 (FTLD-TDP; N = 16), and progressive supranuclear palsy (PSP; N = 39). The LBD group exhibited the most Aβ deposition in the temporal cortex and striatum (90/76%, respectively), followed by PSP (69/28%), FTLD-TDP (50/25%), and the MSA group (50/10%). We conducted immunohistochemical analysis using antibodies targeting eight Aβ epitopes in the LBD and PSP groups. Immunohistochemical findings were evaluated semi-quantitatively and quantitatively using digital pathology. Females with LBD exhibited significantly more severe Aβ deposition, particularly Aβ42 and Aβ43 , along with significantly more severe tau pathology. Furthermore, a quantitative analysis of all Aβ peptides in the LBD group revealed an association with the APOE-ε4 genotypes. No significant differences were observed between males and females in the PSP group. Finally, we compared striatal Aβ deposition in cases with LBD (N = 15), AD without α-synuclein pathology (N = 6), and PSP (N = 5). There were no differences in the pan-Aβ antibody (6F/3D)-immunolabeled deposition burden among the three groups, but the deposition burden of peptides with high aggregation capacity, especially Aβ43 , was significantly higher in the AD and LBD groups than in the PSP group. Furthermore, considerable heterogeneity was observed in the composition of Aβ peptides on a case-by-case basis in the AD and LBD groups, whereas it was relatively uniform in the PSP group. Cluster analysis further supported these findings. Our data suggest that the type of concomitant proteinopathies influences the spectrum of Aβ deposition, impacted also by sex and APOE genotypes.

Learning exceptions to category rules varies across the menstrual cycle

Ways in which ovarian hormones affect cognition have been long overlooked despite strong evidence of their effects on the brain. To address this gap, we study performance on a rule-plus-exception category learning task, a complex task that requires careful coordination of core cognitive mechanisms, across the menstrual cycle (N = 171). Results show that the menstrual cycle distinctly affects exception learning in a manner that parallels the typical rise and fall of estradiol across the cycle. Participants in their high estradiol phase outperform participants in their low estradiol phase and demonstrate more rapid learning of exceptions than a male comparison group. A likely mechanism underlying this effect is estradiol's impact on pattern separation and completion pathways in the hippocampus. These results provide novel evidence for the effects of the menstrual cycle on category learning, and underscore the importance of considering female sex-related variables in cognitive neuroscience research.

Cumulative Stress Exposure and Cognitive Function Among Older Adults: The Moderating Role of a Healthy Lifestyle

OBJECTIVES

Although chronic stress is a risk factor for poor age-related cognitive health, there is limited research that has examined how cumulative stress across the lifespan affects cognitive aging. There may also be resilience factors that minimize the effects of cumulative stress on cognitive health. Engaging in a healthy lifestyle is protective against cognitive decline and may therefore interact with cumulative stress to buffer the stress-cognition relationship. The objective of the current study was to examine the moderating role of a healthy lifestyle, comprised of physical activity, social engagement, and sleep quality, in the relationship between cumulative stress exposure (CSE) and baseline and change in cognitive performance (global cognition, episodic memory, executive function) over 9 years among 1,297 older adults in the Midlife in the United States cohort (Mage = 69.0 ± 6.4, 57.8% female).

METHODS

CSE and healthy lifestyle behaviors were indexed using self-reported questionnaires at baseline, and cognitive function was assessed using a battery of standardized neuropsychological tests at baseline and follow-up.

RESULTS

Controlling for age, sex, education, race, marital status, employment status, hypertension, diabetes, and depression, higher CSE was associated with poorer baseline performance and slower decline over time in global cognition and executive function, but not episodic memory. A healthy lifestyle did not significantly moderate the relationship between cumulative stress and cognitive function. Exploratory analyses showed a significant cumulative stress-cognition relationship among females only.

DISCUSSION

This study lends support for a lifespan model of cognitive aging and suggests that the cognitive health consequences of stress extend beyond immediate timescales.

Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data

OBJECTIVE

This work investigates if deep learning (DL) models can classify originating site locations directly from magnetic resonance imaging (MRI) scans with and without correction for intensity differences.

MATERIAL AND METHODS

A large database of 1880 T1-weighted MRI scans collected across 41 sites originally for Parkinson's disease (PD) classification was used to classify sites in this study. Forty-six percent of the datasets are from PD patients, while 54% are from healthy participants. After preprocessing the T1-weighted scans, 2 additional data types were generated: intensity-harmonized T1-weighted scans and log-Jacobian deformation maps resulting from nonlinear atlas registration. Corresponding DL models were trained to classify sites for each data type. Additionally, logistic regression models were used to investigate the contribution of biological (age, sex, disease status) and non-biological (scanner type) variables to the models' decision.

RESULTS

A comparison of the 3 different types of data revealed that DL models trained using T1-weighted and intensity-harmonized T1-weighted scans can classify sites with an accuracy of 85%, while the model using log-Jacobian deformation maps achieved a site classification accuracy of 54%. Disease status and scanner type were found to be significant confounders.

DISCUSSION

Our results demonstrate that MRI scans encode relevant site-specific information that models could use as shortcuts that cannot be removed using simple intensity harmonization methods.

CONCLUSION

The ability of DL models to exploit site-specific biases as shortcuts raises concerns about their reliability, generalization, and deployability in clinical settings.

DNA Methylation Age Acceleration as a Potential Biomarker for Early Onset of Rapid Eye Movement Sleep Behavior Disorder

Rapid eye movement sleep behavior disorder (RBD) is the strongest prodromal marker for α-synucleinopathies. The Horvath DNA methylation age (DNAm-age) is an epigenetic clock reflecting biological aging. We found an association of DNAm-age acceleration with RBD age at onset at baseline (N = 162, B = -0.68, standard error [SE] = 0.12, p = 2.59e-08) and follow-up (n = 45, B = -1.07, SE = 0.21, p = 9.73e-06). The result remained similar after accounting for genetic risk factors (eg, RBD polygenic risk score). On average, RBD patients with faster versus slow/normal epigenetic aging had a 5.2-year earlier phenoconversion, and the Cox regression analysis revealed a trend toward significance (n = 53, hazard ratio = 1.05, 95% confidence interval = 0.99-1.11, p = 0.06). Our findings suggest that DNAm-age acceleration is a potential biomarker for earlier RBD onset. ANN NEUROL 2023.

Machine learning-based prediction of longitudinal cognitive decline in early Parkinson's disease using multimodal features

Patients with Parkinson's Disease (PD) often suffer from cognitive decline. Accurate prediction of cognitive decline is essential for early treatment of at-risk patients. The aim of this study was to develop and evaluate a multimodal machine learning model for the prediction of continuous cognitive decline in patients with early PD. We included 213 PD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Machine learning was used to predict change in Montreal Cognitive Assessment (MoCA) score using the difference between baseline and 4-years follow-up data as outcome. Input features were categorized into four sets: clinical test scores, cerebrospinal fluid (CSF) biomarkers, brain volumes, and genetic variants. All combinations of input feature sets were added to a basic model, which consisted of demographics and baseline cognition. An iterative scheme using RReliefF-based feature ranking and support vector regression in combination with tenfold cross validation was used to determine the optimal number of predictive features and to evaluate model performance for each combination of input feature sets. Our best performing model consisted of a combination of the basic model, clinical test scores and CSF-based biomarkers. This model had 12 features, which included baseline cognition, CSF phosphorylated tau, CSF total tau, CSF amyloid-beta1-42, geriatric depression scale (GDS) scores, and anxiety scores. Interestingly, many of the predictive features in our model have previously been associated with Alzheimer's disease, showing the importance of assessing Alzheimer's disease pathology in patients with Parkinson's disease.

Health service use before and after dementia diagnosis: a retrospective matched case-control study

OBJECTIVES

This study investigated patterns in health service usage among older adults with dementia and matched controls over a 10-year span from 5 years before until 5 years after diagnosis.

DESIGN

Population-based retrospective matched case-control study.

SETTING

Administrative health data of individuals in Saskatchewan, Canada from 1 April 2008 to 31 March 2019.

PARTICIPANTS

The study included 2024 adults aged 65 years and older living in the community at the time of dementia diagnosis from 1 April 2013 to 31 March 2014, matched 1:1 to individuals without a dementia diagnosis on age group, sex, rural versus urban residence, geographical region and comorbidity.

OUTCOME MEASURES

For each 5-year period before and after diagnosis, we examined usage of health services each year including family physician (FP) visits, specialist visits, hospital admissions, all-type prescription drug dispensations and short-term care admissions. We used negative binomial regression to estimate the effect of dementia on yearly average health service utilisation adjusting for sex, age group, rural versus urban residence, geographical region, 1 year prior health service use and comorbidity.

RESULTS

Adjusted findings demonstrated that 5 years before diagnosis, usage of all health services except hospitalisation was lower among persons with dementia than persons without dementia (all p<0.001). After this point, differences in higher health service usage among persons with dementia compared to without dementia were greatest in the year before and year after diagnosis. In the year before diagnosis, specialist visits were 59.7% higher (p<0.001) and hospitalisations 90.5% higher (p<0.001). In the year after diagnosis, FP visits were 70.0% higher (p<0.001) and all-type drug prescriptions 29.1% higher (p<0.001).

CONCLUSIONS

Findings suggest the year before and year after diagnosis offer multiple opportunities to implement quality supports. FPs are integral to dementia care and require effective resources to properly serve this population.

17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson's disease are associated with LRRC37A/2 expression in astrocytes

BACKGROUND

Parkinson's disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified.

METHODS

To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue.

RESULTS

We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue.

CONCLUSION

These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types.

Association of sex differences in dementia risk factors with sex differences in memory decline in a population-based cohort spanning 20-76 years

Sex differences in late-life memory decline may be explained by sex differences in dementia risk factors. Episodic memory and dementia risk factors were assessed in young, middle-aged and older adults over 12 years in a population-based sample (N = 7485). For men in midlife and old age, physical, cognitive and social activities were associated with less memory decline, and financial hardship was associated with more. APOE e4 and vascular risk factors were associated with memory decline for women in midlife. Depression, cognitive and physical activity were associated with memory change in older women. Incident midlife hypertension (β = - 0.48, 95% CI - 0.87, - 0.09, p = 0.02) was associated with greater memory decline in women and incident late-life stroke accounted for greater memory decline in men (β = - 0.56, 95% CI - 1.12, - 0.01), p = 0.05). Women have fewer modifiable risk factors than men. Stroke and hypertension explained sex differences in memory decline for men and women respectively.

Early-Onset Alzheimer's Disease: What Is Missing in Research?

PURPOSE OF REVIEW

Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward.

RECENT FINDINGS

EOAD cases make up 5-10% of AD cases but only 10-15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear. While great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.

Portals to frailty? Data-driven analyses detect early frailty profiles

BACKGROUND

Frailty is an aging condition that reflects multisystem decline and an increased risk for adverse outcomes, including differential cognitive decline and impairment. Two prominent approaches for measuring frailty are the frailty phenotype and the frailty index. We explored a complementary data-driven approach for frailty assessment that could detect early frailty profiles (or subtypes) in relatively healthy older adults. Specifically, we tested whether (1) modalities of early frailty profiles could be empirically determined, (2) the extracted profiles were differentially related to longitudinal cognitive decline, and (3) the profile and prediction patterns were robust for males and females.

METHODS

Participants (n = 649; M age = 70.61, range 53-95) were community-dwelling older adults from the Victoria Longitudinal Study who contributed data for baseline multi-morbidity assessment and longitudinal cognitive trajectory analyses. An exploratory factor analysis on 50 multi-morbidity items produced 7 separable health domains. The proportion of deficits in each domain was calculated and used as continuous indicators in a data-driven latent profile analysis (LPA). We subsequently examined how frailty profiles related to the level and rate of change in a latent neurocognitive speed variable.

RESULTS

LPA results distinguished three profiles: not-clinically-frail (NCF; characterized by limited impairment across indicators; 84%), mobility-type frailty (MTF; characterized by impaired mobility function; 9%), and respiratory-type frailty (RTF; characterized by impaired respiratory function; 7%). These profiles showed differential neurocognitive slowing, such that MTF was associated with the steepest decline, followed by RTF, and then NCF. The baseline frailty index scores were the highest for MTF and RTF and increased over time. All observations were robust across sex.

CONCLUSIONS

A data-driven approach to early frailty assessment detected differentiable profiles that may be characterized as morbidity-intensive portals into broader and chronic frailty. Early inventions targeting mobility or respiratory deficits may have positive downstream effects on frailty progression and cognitive decline.

One third of dementia cases can be prevented within the next 25 years by tackling risk factors. The case "for" and "against"

BACKGROUND

Recently, it has been suggested that up to a third of the dementia cases might be preventable. While prevention is always better than cure, this is particularly important in the field of dementia, as current interventions are not able to modify the disease. This article revises the evidence "for" and "against" dementia primary prevention.

DISCUSSION

Evidence "for" is sustained by the Lancet Commission on Dementia Prevention, Intervention and Care that noted a reduction of age-related incidence of dementia in high-income countries. Based on results from large cohort studies and using population attributable risk, the commission concluded that up to 35% of dementia cases could be prevented by modifying nine risk factors: low education, midlife hearing loss, obesity, hypertension, late-life depression, smoking, physical inactivity, diabetes, and social isolation. In this life course conceptual framework, modifications of risk factors can influence dementia decades before clinical disease onset. However, evidence "against" is supported by large randomized controlled trials (RCT, > 250 participants per arm, minimum of 6 months follow-up), primarily set to prevent dementia using lifestyle interventions that have shown modest or negative results. The 2017 National Academy of Medicine report concluded that the current evidence is limited and there are no specific interventions to warrant a public health recommendation for dementia prevention. Multiple pathological pathways are involved in the development of dementia which are theoretically treatable by managing midlife hearing loss and hypertension, and with physical exercise and education, as suggested by robust observational studies. However, evidence from large clinical trials is not conclusive to support that a third of dementia cases might be prevented. Current initiatives testing the effect of lifestyle interventions in larger clinical trials may help to settle this debate.

Assessing care models implemented in primary healthcare for persons with dementia: a mixed-methods study protocol

INTRODUCTION

Dementia is on the rise in Canada and globally. Ensuring accessibility to diagnosis, treatment and management throughout the course of the disease is a very significant problem worldwide. In order to provide comprehensive care to patients and their caregivers, enhancing primary care-based dementia care is seen as the way forward. In many Canadian provinces various collaborative care models (collCMs) anchored in primary care to improve dementia care have been developed and implemented. The overall objective of our research programme is to identify key factors for the successful implementation of collCMs, and to facilitate dissemination and scale-up of dementia best practices.

METHODS AND ANALYSIS

We will use a convergent mixed-methods design. An observational study using chart review (2014-2016) and questionnaires (2014-2018; repeated in 2020) will measure application of guidelines and implementation of collCMs. This study will be complemented with a qualitative descriptive study using interviews (2017-2020) conducted in parallel. Quantitative and qualitative results will be further integrated using a matrix representing sites and findings. An integrated knowledge exchange strategy will ensure uptake by principal stakeholders throughout the research.

ETHICS AND DISSEMINATION

Our study has been approved by all relevant ethics committees. Our dissemination plan follows an integrated knowledge transfer strategy using provincial, national and international councils. We will present the results individually to the clinical sites and then to these councils. Our research will be the first provincial and cross jurisdictional evaluation of primary care models for patients living with dementia, providing evidence on the ongoing debate on the respective role of clinicians in primary care and specialists in caring for patients with dementia.

Frailty effects on non-demented cognitive trajectories are moderated by sex and Alzheimer's genetic risk

BACKGROUND

Age-related frailty reflects cumulative multisystem physiological and health decline. Frailty increases the risk of adverse brain and cognitive outcomes, including differential decline and dementia. In a longitudinal sample of non-demented older adults, we examine whether (a) the level and/or change in frailty predicts trajectories across three cognitive domains (memory, speed, and executive function (EF)) and (b) prediction patterns are modified by sex or Alzheimer's genetic risk (Apolipoprotein E (APOE)).

METHODS

Participants (n = 632; M age = 70.7, range 53-95; 3 waves) were from the Victoria Longitudinal Study. After computing a frailty index, we used latent growth modeling and path analysis to test the frailty effects on level and change in three latent variables of cognition. We tested two potential moderators by stratifying by sex and APOE risk (ε4+, ε4-).

RESULTS

First, frailty levels predicted speed and EF performance (level) and differential memory change slopes. Second, change in frailty predicted the rate of decline for both speed and EF. Third, sex moderation analyses showed that females were selectively sensitive to (a) frailty effects on memory change and (b) frailty change effects on speed change. In contrast, the frailty effects on EF change were stronger in males. Fourth, genetic moderation analyses showed that APOE risk (e4+) carriers were selectively sensitive to frailty effects on memory change.

CONCLUSION

In non-demented older adults, increasing frailty is strongly associated with the differential decline in cognitive trajectories. For example, higher (worse) frailty was associated with more rapid memory decline than was lower (better) frailty. These effects, however, are moderated by both genetic risk and sex.

Combined impairments in vision, hearing and cognition are associated with greater levels of functional and communication difficulties than cognitive impairment alone: Analysis of interRAI data for home care and long-term care recipients in Ontario

OBJECTIVES

The objective of the current study was to understand the added effects of having a sensory impairment (vision and/or hearing impairment) in combination with cognitive impairment with respect to health-related outcomes among older adults (65+ years old) receiving home care or residing in a long-term care (LTC) facility in Ontario, Canada.

METHODS

Cross-sectional analyses were conducted using existing data collected with one of two interRAI assessments, one for home care (n = 291,824) and one for LTC (n = 110,578). Items in the assessments were used to identify clients with single sensory impairments (e.g., vision only [VI], hearing only [HI]), dual sensory impairment (DSI; i.e., vision and hearing) and those with cognitive impairment (CI). We defined seven mutually exclusive groups based on the presence of single or combined impairments.

RESULTS

The rate of people having all three impairments (i.e., CI+DSI) was 21.3% in home care and 29.2% in LTC. Across the seven groups, individuals with all three impairments were the most likely to report loneliness, to have a reduction in social engagement, and to experience reduced independence in their activities of daily living (ADLs) and instrumental ADLs (IADLs). Communication challenges were highly prevalent in this group, at 38.0% in home care and 49.2% in LTC. In both care settings, communication difficulties were more common in the CI+DSI group versus the CI-alone group.

CONCLUSIONS

The presence of combined sensory and cognitive impairments is high among older adults in these two care settings and having all three impairments is associated with higher rates of negative outcomes than the rates for those having CI alone. There is a rising imperative for all health care professionals to recognize the potential presence of hearing, vision and cognitive impairments in those for whom they provide care, to ensure that basic screening occurs and to use those results to inform care plans.