Cassandra Szoeke

Increased Risk of Cognitive Impairment in Patients With Diabetes Is Associated With Metformin

OBJECTIVE To investigate the associations of metformin, serum vitamin B12, calcium supplements, and cognitive impairment in patients with diabetes. RESEARCH DESIGN AND METHODS Participants were recruited from the Primary Research in Memory (PRIME) clinics study, the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, and the Barwon region of southeastern Australia. Patients with Alzheimer disease (AD) (n = 480) or mild cognitive impairment (n = 187) and those who were cognitively intact (n = 687) were included; patients with stroke or with neurodegenerative diseases other than AD were excluded. Subgroup analyses were performed for participants who had either type 2 diabetes (n = 104) or impaired glucose tolerance (n = 22). RESULTS Participants with diabetes (n = 126) had worse cognitive performance than participants who did not have diabetes (n = 1,228; adjusted odds ratio 1.51 [95% CI 1.03–2.21]). Among participants with diabetes, worse cognitive performance was associated with metformin use (2.23 [1.05–4.75]). After adjusting for age, sex, level of education, history of depression, serum vitamin B12, and metformin use, participants with diabetes who were taking calcium supplements had better cognitive performance (0.41 [0.19–0.92]). CONCLUSIONS Metformin use was associated with impaired cognitive performance. Vitamin B12 and calcium supplements may alleviate metformin-induced vitamin B12 deficiency and were associated with better cognitive outcomes. Prospective trials are warranted to assess the beneficial effects of vitamin B12 and calcium use on cognition in older people with diabetes who are taking metformin.

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

BACKGROUND Similar to most chronic diseases, Alzheimers 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. METHODS 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. FINDINGS 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). INTERPRETATION 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. FUNDING 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 Alzheimers Drug Discovery Foundation, and the Alzheimers Association.

Amyloid imaging results, from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging

The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, a participant of the worldwide Alzheimers Disease Neuroimaging Initiative (ADNI), performed (11)C-Pittsburgh Compound B (PiB) scans in 177 healthy controls (HC), 57 mild cognitive impairment (MCI) subjects, and 53 mild Alzheimers disease (AD) patients. High PiB binding was present in 33% of HC (49% in ApoE-epsilon4 carriers vs 21% in noncarriers) and increased with age, most strongly in epsilon4 carriers. 18% of HC aged 60-69 had high PiB binding rising to 65% in those over 80 years. Subjective memory complaint was only associated with elevated PiB binding in epsilon4 carriers. There was no correlation with cognition in HC or MCI. PiB binding in AD was unrelated to age, hippocampal volume or memory. Beta-amyloid (Abeta) deposition seems almost inevitable with advanced age, amyloid burden is similar at all ages in AD, and secondary factors or downstream events appear to play a more direct role than total beta amyloid burden in hippocampal atrophy and cognitive decline.

Longitudinal Assessment of Aβ and Cognition in Aging and Alzheimer Disease

Assess Aβ deposition longitudinally and explore its relationship with cognition and disease progression.

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

BACKGROUND 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 Alzheimers 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. METHODS 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. RESULTS 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. CONCLUSION 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.

Intensity of dementia through latent variable modelling (I-DeLV) in the AIBL cohort

69% of Mild Cognitively Impaired and 96% of AD. Conclusions: The described models provide accurate estimations of NAB based on demographic corrected cognitive test scores. If NAB is a predictor for progression to AD and given such models can accurately predict NAB, it follows that this work may lead to an effective and economical screen for early detection of individuals at risk of developing AD, in-turn providing justification for further confirmatory tests (e.g. PET) or to identify suitable participants for intervention or therapeutic trials.

Relationship between atrophy and β‐amyloid deposition in Alzheimer disease

Elucidating the role of aggregated β‐amyloid in relation to gray matter atrophy is crucial to the understanding of the pathological mechanisms of Alzheimer disease and for the development of therapeutic trials. The present study aims to assess this relationship.

β-Amyloid burden in the temporal neocortex is related to hippocampal atrophy in elderly subjects without dementia

Objective: To investigate whether global and regional β-amyloid (Aβ) burden as measured with 11C Pittsburgh compound B (PIB) PET is associated with hippocampal atrophy characterized using MRI in healthy controls and patients with amnestic mild cognitive impairment (aMCI) or Alzheimer disease (AD). Methods: Ninety-two elderly healthy controls, 32 subjects with aMCI, and 35 patients with AD were imaged using 11C-PIB PET and MRI. Hippocampal volume was measured and PIB standardized uptake value ratio was extracted after partial volume correction within 41 regions of interest. Global, regional, and voxel-based correlations between PIB and hippocampal volume were computed for each group. Results: In healthy control participants with elevated neocortex PIB retention, significant correlation was found between PIB retention in the inferior temporal region and hippocampal volume using both region-based and voxel-based approaches. No correlation was found in any other group. Conclusions: The strong correlation between hippocampal atrophy and β-amyloid (Aβ) burden in the Pittsburgh compound B–positive healthy control group suggests that Aβ deposition in the inferior temporal neocortex is related to hippocampal synaptic and neuronal degeneration.

Multicentre search for genetic susceptibility loci in sporadic epilepsy syndrome and seizure types: a case-control study.

BACKGROUND The Epilepsy Genetics (EPIGEN) Consortium was established to undertake genetic mapping analyses with augmented statistical power to detect variants that influence the development and treatment of common forms of epilepsy. METHODS We examined common variations across 279 prime candidate genes in 2717 case and 1118 control samples collected at four independent research centres (in the UK, Ireland, Finland, and Australia). Single nucleotide polymorphism (SNP) and combined set-association analyses were used to examine the contribution of genetic variation in the candidate genes to various forms of epilepsy. FINDINGS We did not identify clear, indisputable common genetic risk factors that contribute to selected epilepsy subphenotypes across multiple populations. Nor did we identify risk factors for the general all-epilepsy phenotype. However, set-association analysis on the most significant p values, assessed under permutation, suggested the contribution of numerous SNPs to disease predisposition in an apparent population-specific manner. Variations in the genes KCNAB1, GABRR2, KCNMB4, SYN2, and ALDH5A1 were most notable. INTERPRETATION The underlying genetic component to sporadic epilepsy is clearly complex. Results suggest that many SNPs contribute to disease predisposition in an apparently population-specific manner. However, subtle differences in phenotyping across cohorts, combined with a poor understanding of how the underlying genetic component to epilepsy aligns with current phenotypic classifications, might also account for apparent population-specific genetic risk factors. Variations across five genes warrant further study in independent cohorts to clarify the tentative association.

Effect of amyloid on memory and non-memory decline from preclinical to clinical Alzheimer’s disease

High amyloid has been associated with substantial episodic memory decline over 18 and 36 months in healthy older adults and individuals with mild cognitive impairment. However, the nature and magnitude of amyloid-related memory and non-memory change from the preclinical to the clinical stages of Alzheimers disease has not been evaluated over the same time interval. Healthy older adults (n = 320), individuals with mild cognitive impairment (n = 57) and individuals with Alzheimers disease (n = 36) enrolled in the Australian Imaging, Biomarkers and Lifestyle study underwent at least one positron emission tomography neuroimaging scan for amyloid. Cognitive assessments were conducted at baseline, and 18- and 36-month follow-up assessments. Compared with amyloid-negative healthy older adults, amyloid-positive healthy older adults, and amyloid-positive individuals with mild cognitive impairment and Alzheimers disease showed moderate and equivalent decline in verbal and visual episodic memory over 36 months (ds = 0.47-0.51). Relative to amyloid-negative healthy older adults, amyloid-positive healthy older adults showed no decline in non-memory functions, but amyloid-positive individuals with mild cognitive impairment showed additional moderate decline in language, attention and visuospatial function (ds = 0.47-1.12), and amyloid-positive individuals with Alzheimers disease showed large decline in all aspects of memory and non-memory function (ds = 0.73-2.28). Amyloid negative individuals with mild cognitive impairment did not show any cognitive decline over 36 months. When non-demented individuals (i.e. healthy older adults and adults with mild cognitive impairment) were further dichotomized, high amyloid-positive non-demented individuals showed a greater rate of decline in episodic memory and language when compared with low amyloid positive non-demented individuals. Memory decline does not plateau with increasing disease severity, and decline in non-memory functions increases in amyloid-positive individuals with mild cognitive impairment and Alzheimers disease. The combined detection of amyloid positivity and objectively-defined decline in memory are reliable indicators of early Alzheimers disease, and the detection of decline in non-memory functions in amyloid-positive individuals with mild cognitive impairment may assist in determining the level of disease severity in these individuals. Further, these results suggest that grouping amyloid data into at least two categories of abnormality may be useful in determining the disease risk level in non-demented individuals.