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      Relevance of a Truncated PRESENILIN 2 Transcript to Alzheimer’s Disease and Neurodegeneration

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          Abstract

          Background: The PRESENILIN genes (PSEN1, PSEN2) encoding for their respective proteins have critical roles in many aspects of Alzheimer’s disease (AD) pathogenesis. The PS2V transcript of PSEN2 encodes a truncated protein and is upregulated in AD brains; however, its relevance to AD and disease progression remains to be determined. Objective: Assess transcript levels in postmortem AD and non-AD brain tissue and in lymphocytes collected under the Australian Imaging Biomarker and Lifestyle (AIBL) study. Methods: Full length PSEN2 and PS2V transcript levels were assessed by quantitative digital PCR in postmortem brain tissue (frontal cortex and hippocampus) from control, AD, frontotemporal dementia (FTD), and Lewy body dementia (LBD). Transcript levels were also assessed in lymphocytes obtained from the Perth subset of the AIBL study (n = 160). Linear regression analysis was used to assess correlations between transcript copy number and brain volume and neocortical amyloid load. Results: PS2V levels increased in AD postmortem brain but PS2V was also present at significant levels in FTD and LBD brains. PS2V transcript was detected in lymphocytes and PS2V/PSEN2 ratios were increased in mild cognitive impairment (p = 0.024) and AD (p = 0.019) groups compared to control group. Increased ratios were significantly correlated with hippocampal volumes only (n = 62, β= –0.269, p = 0.03). Conclusion: Taken together, these results suggest that PS2V may be a marker of overall neurodegeneration.

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          Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study.

          Victor Villemagne, Samantha Burnham, Pierrick Bourgeat … (2013)
          Similar to most chronic diseases, Alzheimer's disease (AD) develops slowly from a preclinical phase into a fully expressed clinical syndrome. We aimed to use longitudinal data to calculate the rates of amyloid β (Aβ) deposition, cerebral atrophy, and cognitive decline. In this prospective cohort study, healthy controls, patients with mild cognitive impairment (MCI), and patients with AD were assessed at enrolment and every 18 months. At every visit, participants underwent neuropsychological examination, MRI, and a carbon-11-labelled Pittsburgh compound B ((11)C-PiB) PET scan. We included participants with three or more (11)C-PiB PET follow-up assessments. Aβ burden was expressed as (11)C-PiB standardised uptake value ratio (SUVR) with the cerebellar cortex as reference region. An SUVR of 1·5 was used to discriminate high from low Aβ burdens. The slope of the regression plots over 3-5 years was used to estimate rates of change for Aβ deposition, MRI volumetrics, and cognition. We included those participants with a positive rate of Aβ deposition to calculate the trajectory of each variable over time. 200 participants (145 healthy controls, 36 participants with MCI, and 19 participants with AD) were assessed at enrolment and every 18 months for a mean follow-up of 3·8 (95% CI CI 3·6-3·9) years. At baseline, significantly higher Aβ burdens were noted in patients with AD (2·27, SD 0·43) and those with MCI (1·94, 0·64) than in healthy controls (1·38, 0·39). At follow-up, 163 (82%) of the 200 participants showed positive rates of Aβ accumulation. Aβ deposition was estimated to take 19·2 (95% CI 16·8-22·5) years in an almost linear fashion-with a mean increase of 0·043 (95% CI 0·037-0·049) SUVR per year-to go from the threshold of (11)C-PiB positivity (1·5 SUVR) to the levels observed in AD. It was estimated to take 12·0 (95% CI 10·1-14·9) years from the levels observed in healthy controls with low Aβ deposition (1·2 [SD 0·1] SUVR) to the threshold of (11)C-PiB positivity. As AD progressed, the rate of Aβ deposition slowed towards a plateau. Our projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches our threshold of positivity at 17·0 (95% CI 14·9-19·9) years, hippocampal atrophy at 4·2 (3·6-5·1) years, and memory impairment at 3·3 (2·5-4·5) years before the onset of dementia (clinical dementia rating score 1). Aβ deposition is slow and protracted, likely to extend for more than two decades. Such predictions of the rate of preclinical changes and the onset of the clinical phase of AD will facilitate the design and timing of therapeutic interventions aimed at modifying the course of this illness. Science and Industry Endowment Fund (Australia), The Commonwealth Scientific and Industrial Research Organisation (Australia), The National Health and Medical Research Council of Australia Program and Project Grants, the Austin Hospital Medical Research Foundation, Victorian State Government, The Alzheimer's Drug Discovery Foundation, and the Alzheimer's Association. Copyright © 2013 Elsevier Ltd. All rights reserved.
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            Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer disease: a longitudinal study

            Brian A. Gordon, Tyler Blazey, Yi Su … (2018)
            Background Models of Alzheimer disease propose a sequence of amyloid-β (Aβ) accumulation, hypometabolism, and structural declines that precede the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. This study aimed to characterize where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal. Methods We analyzed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers collected between January 1st 2009 and December 31st 2015 from families carrying PSEN1, PSEN2, or APP mutations enrolled in the Dominantly Inherited Alzheimer’s Network. We analyzed [11C]Pittsburgh Compound B positron emission tomography (PiB PET), [18F]Fluorodeoxyglucose (FDG PET), and structural magnetic resonance imaging (MRI) data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years from symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. Findings PiB PET was available for 346 individuals, with 162 having longitudinal imaging; FDG PET was available for 352 (175 longitudinal); and MRI data was available for 377 (201 longitudinal). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from non-carriers first (on average across regions that showed a significant difference at −18·9 (sd 3·3) years before expected onset), followed by hypometabolism (−14·1 years, sd 5·1) and lastly structural declines (−4·7 years, sd 4·2). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region in each modality to show divergence between groups (−22·2 years before expected onset for Aβ accumulation, −18·8 years for hypometabolism, and −13·0 years for cortical thinning). Interpretation Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials.
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              The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease.

              Kathryn A Ellis, Ashley I Bush, David Darby … (2009)
              The Australian Imaging, Biomarkers and Lifestyle (AIBL) flagship study of aging aimed to recruit 1000 individuals aged over 60 to assist with prospective research into Alzheimer's disease (AD). This paper describes the recruitment of the cohort and gives information about the study methodology, baseline demography, diagnoses, medical comorbidities, medication use, and cognitive function of the participants. Volunteers underwent a screening interview, had comprehensive cognitive testing, gave 80 ml of blood, and completed health and lifestyle questionnaires. One quarter of the sample also underwent amyloid PET brain imaging with Pittsburgh compound B (PiB PET) and MRI brain imaging, and a subgroup of 10% had ActiGraph activity monitoring and body composition scanning. A total of 1166 volunteers were recruited, 54 of whom were excluded from further study due to comorbid disorders which could affect cognition or because of withdrawal of consent. Participants with AD (211) had neuropsychological profiles which were consistent with AD, and were more impaired than participants with mild cognitive impairment (133) or healthy controls (768), who performed within expected norms for age on neuropsychological testing. PiB PET scans were performed on 287 participants, 100 had DEXA scans and 91 participated in ActiGraph monitoring. The participants comprising the AIBL cohort represent a group of highly motivated and well-characterized individuals who represent a unique resource for the study of AD. They will be reassessed at 18-month intervals in order to determine the predictive utility of various biomarkers, cognitive parameters and lifestyle factors as indicators of AD, and as predictors of future cognitive decline.
              Article 0 comments Cited 142 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Title: Journal of Alzheimer's Disease
                Abbreviated Title: JAD
                Publisher: IOS Press
                ISSN (Print): 13872877
                ISSN (Electronic): 18758908
                Publication date Created: April 20 2021
                Publication date (Print): April 20 2021
                Volume: 80
                Issue: 4
                Pages: 1479-1489
                Affiliations
                [1 ]University of Adelaide, School of Biological Sciences, Centre for Molecular Pathology, Adelaide, SA, Australia
                [2 ]Collaborative Genomics and Translation Group, Strategic Research Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
                [3 ]School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
                [4 ]Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medical Research, Murdoch, Western Australia, Australia
                [5 ]School of Medicine, University of Western Australia, Crawley, Western Australia, Australia
                [6 ]Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, New South Wales, Australia
                [7 ]Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia
                [8 ]The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
                [9 ]School of Medical and Health Sciences, Edith Cowan University, Western Australia, Australia
                Article
                DOI: 10.3233/JAD-201133
                SO-VID: 195eebe5-c9e6-4b6c-a0fa-2a0399afa914
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