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2nd May 2022
Having atopic eczema in older life increases the risk for developing Alzheimer’s disease, according to a study by researchers from UC Berkeley School of Public Health, Berkeley, California, USA.
Alzheimer’s disease (AD) is a neurodegenerative disorder which is progressive and characterised clinically by cognitive decline and physiologically by the presence of two core pathologies; amyloid β plaques (Aβ) and neurofibrillary tangles (NFTs). AD is the most common form of dementia which, according to the World Health Organization (WHO), affected some 55 million people in 2021 with AD accounting for 60-70% of all dementia cases.
Among those with AD, there is a sustained inflammatory response in the brain which is thought to represent a persistent immune response and a factor exacerbating both Aβ and NFTs. Moreover, there is emerging evidence that peripheral inflammation is an early event in the pathogenesis of AD. Atopy, which manifests as either allergic rhinitis, atopic eczema or asthma, represents a set of peripheral inflammatory diseases that have been found to be associated with a modestly increased risk of AD and dementia. To date, only one study has suggested that atopic eczema may be an independent risk factor for new-onset dementia and in particular, AD.
For the present analysis, the team set out to determine whether active atopic eczema among older adults was associated with incident AD and wondered if the strength of this association was dependent upon atopic eczema disease severity. They performed a longitudinal cohort study of patient data collected from the Health Improvement Network, which provides information on a representative sample of patients from UK general practitioners. For their analysis, the researchers included patients aged 60 to 100 years of age without a prior diagnosis of AD or dementia and for whom the primary exposure was the presence of active atopic eczema and for which at least two prescriptions for treatment of the condition had been issued. The severity of atopic eczema during follow-up was categorised as either mild moderate or severe and the primary outcome was a new diagnosis of dementia during the period of follow-up. The researchers also examined the reported disease codes for dementia and excluded those where the condition was drug- or alcohol-related or due to trauma or a rarer form (e.g. Huntington’s). The analysis was adjusted for potential confounders including gender, smoking, alcohol status, etc.
Atopic eczema and risk of Alzheimer’s disease
In a total of 1,767,667 individuals aged 60 to 100 years of age at baseline, 57,263 were diagnosed with dementia over mean of 6.8 years of follow-up. The median age of patients with a dementia diagnosis was 82 years, of whom, two-thirds (65%) were female.
Atopic eczema was diagnosed in 12% of the whole cohort and using mild disease severity as the default, 44% had moderate and 5% disease severity over the follow-up period.
Considering AD, the analysis showed that after adjustment for confounders, mild atopic eczema was associated with a 22% higher risk of AD (HR = 1.22) and this risk was higher still for those with moderate (HR = 1.37) and severe (HR = 1.52) disease.
With AD being the most common form of dementia, the researchers also examined the link between atopic eczema and the risk of developing dementia. The incidence of dementia was 57/10,000 person-years among those with atopic eczema compared to 44/10,000 person-years among those without the condition. Overall, patients with atopic eczema had a 27% higher risk for dementia after adjustment for potential confounders (hazard ratio, HR = 1.27, 95% CI 1.23 – 1.30). Further adjustment for co-morbidities slighted attenuated this risk but it remained significant (HR = 1.19, 95% CI 1.16 – 1.22).
The authors concluded that given the increased risk of AD among adults with atopic eczema, clinicians consider the impact of screening those with eczema for signs of cognitive impairment.
Magyari A et al. Adult atopic eczema and the risk of dementia: A population-based cohort study J Am Acad Dermatol 2022
22nd April 2022
People who adopt a healthy lifestyle are not only more likely to live longer but also have a reduced risk of developing Alzheimer’s disease compared with those who lead a less healthy lifestyle. This was the finding of an analysis of data from the Chicago Health and Ageing Project (CHAP) by a team from the Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, USA.
Alzheimer’s disease is the most common form of dementia with a high level of inheritability which is thought to be between 60% and 80%. Nevertheless, while genetic factors are associated with a higher risk of developing AD, the extent to which lifestyle modification can off-set this risk is unclear, although some data shows that a favourable lifestyle was associated with a lower dementia risk even among participants with high genetic risk. In fact, evidence suggests that when compared to those with no to only one healthy lifestyle factor, the risk of Alzheimer dementia was 60% lower in those with 4 to 5 healthy lifestyle factors. Since the greatest risk factor for Alzheimer’s disease is advanced age, for the present study, the US team wanted to explore the impact of a healthy lifestyle on both life expectancy lived with and without AD.
The researchers turned to the CHAP, which is a prospective study designed to assess risk factors for AD. To explore the impact of a healthy lifestyle, they created a scoring system which included five recognised and modifiable lifestyle factors: diet, cognitive activities (e.g., reading, doing crosswords, puzzles etc), physical activity, smoking and alcohol consumption. For each of these five factors, researchers assigned individuals a score of 1 (if they met the threshold for a healthy or low risk score) or 0 (where they did not meet the criteria). An individual’s score was then summed, ranging from 0 to 5. The main outcome of interest was life expectancy with and without AD in both sexes.
Healthy lifestyle and life expectancy
A total of 2449 individuals with a mean age of 76.2 years were included in the analysis and the mean lifestyle score was 2.3.
During 13,047 person years of follow-up, 20.8% of participants developed incident AD. Among women with between 4 and 5 healthy lifestyle factors, the risk of AD compared to those with 0 or 1 factors was significantly reduced (hazard ratio, HR = 0.44, 95% CI 0.32 – 0.59). A similar reduction was also evident for me (HR = 0.30, 95% CI 0.19 – 0.47).
The benefits of a healthy lifestyle also led to a reduced mortality risk compared to those with 0 to 1 factors in both women (HR = 0.56, 95% CI 0.49 – 0.65) and men (HR = 0.47, 95% CI 0.39 – 0.57).
The authors calculated that the life expectancy of women aged 65 but without Alzheimer’s dementia and four or five healthy factors was 21.5 years compared to 17 years for those with either 0 or 1 healthy factors. Similar benefits were also seen for men.
The impact of a high healthy lifestyle score also affected the number of years spent with AD. For example, of the total life expectancy of women aged 65, those with four or five healthy factors spent 2.6 years (10.8%) with Alzheimer’s dementia. In contrast, women with 0 or one healthy factor, spent 4.1 years (19.3%) with the disease. Again, similar benefits were seen for men.
The authors concluded that a healthy lifestyle not only increased life expectancy but it was likely to reduce the proportion of remaining years lived with AD.
Dhana K et al. Healthy lifestyle and life expectancy with and without Alzheimer’s dementia: population based cohort study BMJ 2022
8th April 2022
The use of an MRI-based deep learning algorithm has been shown to be superior to both amyloid and tau pathology biomarkers for the detection of prodromal Alzheimer’s disease (AD) according to a study by researchers from the Department of Biomedical Engineering, Columbia University, New York,
Alzheimer’s disease biomarkers play an important role in the early diagnosis of the disease and neuropathological hallmarks include amyloid β (Aβ)-containing plaques and tau-containing neurofibrillary tangles throughout the brain. The current AD biomarkers are based on amyloid-β plaques and of tau-related neuro-degeneration whereas brain positron emission tomography can also be used in the diagnosis of Alzheimer dementia.
MRI-based deep learning systems are able to assist with both AD classification and AD’s structural neuroimaging signatures and, for the present study, the US team wondered if a deep learning algorithm might be either comparable to, or even better than, existing biomarkers for the identification of the disease. In addition, because there are cellular changes prior to evidence of neuronal loss, it might be possible for a deep learning system to detect some of these more nuanced changes prior to the development of AD. The development of AD is progressive and transitions from a prodromal stage, characterised by mild cognitive impairment (MCI), before the onset of dementia. However, the diagnosis of prodromal AD in a patient with MCI is difficult. Therefore, if a deep learning algorithm could identify prodromal AD it would represent an invaluable ‘add-on’ to the conventionally acquired MRI scan and have potential utility as a screening tool. The team therefore wanted to train the MRI-based deep learning algorithm to recognise the prodromal phase and then compared the diagnostic performance against current biomarkers including cerebrospinal fluid (CSF) tau and amyloid beta levels (AB) as well as the tau/AB ratio.
MRI-based deep learning diagnostic accuracy
The deep learning algorithm was first trained using 975 MRI scans from AD patients compared to 1943 MRI scans from control patients. Using receiver operating characteristic analysis (ROC), the deep learning algorithm classified AD dementia compared to healthy controls with an area under the curve (AUC) of 0.973.
Next, the team identified two cohorts of patients; one group diagnosed with MCI but who remained stable over time, and a second group who subsequently progressed to AD. For both groups, CFS amyloid and tau biomarker values were available and used for comparative purposes. Using ROC analysis, the researcher found that the AUC for the deep learning algorithm was 0.788 for distinguishing between the MCI stable and progressive groups. The corresponding CSF AB, tau and tau/AB ratio AUC values for the same comparison were 0.702, 0.682 and 0.703 respectively and all differences were statistically significant. In other words, the deep learning algorithm was the best tool for identifying patients with prodromal AD.
Using survival analysis, the researchers also found that the deep learning algorithm outperformed the biomarkers in predicting progression to full AD dementia.
They concluded that the MRI-based deep learning could enhance the value of existing MRI scans by identifying useful information for the purpose of prodromal AD detection, adding that this approach potentially reduces patient burden, risk, and cost.
Feng X et al. A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer’s disease Alzheimers Res Ther 2022.
11th March 2022
The presence of higher tau levels seen on positron emission tomography (PET) scans in several areas of the brain are associated with psychosis and a more rapid and functional decline in patients with Alzheimer’s disease (AD). This was the conclusion of a study by a team from the Feinstein Institutes for Medical Research, New York, US.
Psychotic symptoms occur in 40-60% of patients with AD and are linked to more severe cognitive deficits and a more rapidly deteriorating course. In fact, it has been found that psychosis in AD patients defines a phenotype of greater severity, with worsened functional progression and increased mortality risk. Other work has found that within cerebrospinal fluid, the level of total tau was significantly elevated in participants who developed psychosis. Furthermore, other data suggest that elevated tau phosphorylation may be accelerated in AD with psychosis.
With the above data suggesting that higher tau levels in AD patients may be linked to the development of psychosis, there have been no imaging studies of the in vivo relationship between these two factors.
In the present study, the US team used [18F]-AV1451, which is a PET ligand with a high affinity for insoluble paired-helical filaments (PHFs) of hyper-phosphorylated tau to explore this relationship. It is already known, that the distribution of the [18F]AV-1451 signal as seen on PET imaging, is a valid marker of clinical symptoms and neuro-degeneration. The researchers turned to data held in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. This was designed primarily to explore whether a range of imaging modality scans combined with other biological markers and clinical/neuropsychological assessment could be used to measure the progression of mild cognitive impairment and early AD. Using the ADNI database, the team identified patients who had [18F]-AV1451 imaging at baseline and who subsequently became psychotic and matched these individuals to a cohort who also had [18F]-AV1451 imaging but did not become psychotic. To assess changes in cognition, the annualised rate of change (ARC) in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) and mini-mental state exam (MMSE) were used with higher CDR-SB and lower MMSE scores indicative of more severe cognitive impairment.
Higher tau levels and the development of psychosis
A total of 17 patients who developed psychosis (AD+P) and with a mean age of 79.23 years (58.8% male) were identified and matched with 50 AD patients (mean age 78.8 years, 60% male) who did not become psychotic. The mean CDR-SB+P score was significantly higher in the AD+P group (6.29 vs 2.65, p < 0.0001) and the MMSE score significantly lower (20.94 vs 26.42, p < 0.0001). Using the mean ARC for the two groups, there were significant differences for both CDR-SB+P and MMSE, suggesting that AD+P patients declined more rapidly in terms of cognitive integrity (based on the MMSE score) and functional impairment (CDR-SB+P score) than those without psychosis over time.
The AD+P participants showed increases in tau uptake at baseline with higher tau levels in the frontal, temporal and occipital cortices. These differences in tau retention remained significantly greater in those who would become psychotic within all three Braak-derived regions of interest, i.e., transentorhinal, limbic and isocortical. This suggested that in addition to localised regions, psychosis may be associated with a more aggressive spread of tau.
The authors concluded that their findings would suggest that psychosis in those with AD leads to rapid cognitive impairment and that this was largely driven by higher tau levels in multiple locations of the brain. They added how there was a need to determine whether tau pathologies in the affected regions of the brain were of predictive value in prospective trials.
Gomar JJ et al. Increased retention of tau PET ligand [18F]-AV1451 in Alzheimer’s Disease Psychosis Trans Psychiatry 2022