Dataset Information

Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease.

ABSTRACT:

Introduction

The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain.

Methods

We genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome-wide association study.

Results

We confirm that variation in/near APOE/TOMM40 (P = 6 × 10(-14)) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2.83, P = .0007). We found evidence for risk in/near CR1 (P = 7 × 10(-4)), ABCA7 (P = .02) and BIN1 (P = .04). ORs at variants near INPP5D and NME8 did not overlap between PCA and typical AD. Exploratory genome-wide association studies confirmed APOE and identified three novel loci: rs76854344 near CNTNAP5 (P = 8 × 10(-10) OR = 1.9 [1.5-2.3]); rs72907046 near FAM46A (P = 1 × 10(-9) OR = 3.2 [2.1-4.9]); and rs2525776 near SEMA3C (P = 1 × 10(-8), OR = 3.3 [2.1-5.1]).

Discussion

We provide evidence for genetic risk factors specifically related to PCA. We identify three candidate loci that, if replicated, may provide insights into selective vulnerability and phenotypic diversity in AD.

SUBMITTER: Schott JM

PROVIDER: S-EPMC4982482 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease.

Schott Jonathan M JM Crutch Sebastian J SJ Carrasquillo Minerva M MM Uphill James J Shakespeare Tim J TJ Ryan Natalie S NS Yong Keir X KX Lehmann Manja M Ertekin-Taner Nilufer N Graff-Radford Neill R NR Boeve Bradley F BF Murray Melissa E ME Khan Qurat Ul Ain QU Petersen Ronald C RC Dickson Dennis W DW Knopman David S DS Rabinovici Gil D GD Miller Bruce L BL González Aida Suárez AS Gil-Néciga Eulogio E Snowden Julie S JS Harris Jenny J Pickering-Brown Stuart M SM Louwersheimer Eva E van der Flier Wiesje M WM Scheltens Philip P Pijnenburg Yolande A YA Galasko Douglas D Sarazin Marie M Dubois Bruno B Magnin Eloi E Galimberti Daniela D Scarpini Elio E Cappa Stefano F SF Hodges John R JR Halliday Glenda M GM Bartley Lauren L Carrillo Maria C MC Bras Jose T JT Hardy John J Rossor Martin N MN Collinge John J Fox Nick C NC Mead Simon S

Alzheimer's & dementia : the journal of the Alzheimer's Association 20160315 8

<h4>Introduction</h4>The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain.<h4>Methods</h4>We genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome-wide association study.<h4>Results</h4>We confirm that variation in/near APOE/TOMM40 (P = 6 × 10(-14)) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2. ...[more]

PMID: 26993346

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Project description:ObjectivesTo investigate the global cortical and regional quantitative features of cortical neural architecture in the brains of patients with posterior cortical atrophy (PCA) and typical Alzheimer's disease (tAD) compared with elderly healthy controls (HC).MethodsA novel diffusion MRI method, that has been shown to correlate with minicolumnar organization changes in the cerebral cortex, was used as a surrogate of neuropathological changes in dementia. A cohort of 15 PCA patients, 23 tAD and 22 healthy elderly controls (HC) were enrolled to investigate the changes in cortical diffusivity among groups. For each subject, 3 T MRI T1-weighted images and diffusion tensor imaging (DTI) scans were analysed to extract novel cortical DTI derived measures (AngleR, PerpPD and ParlPD). Receiver operating characteristics (ROC) curve analysis and the area under the curve (AUC) were used to assess the group discrimination capability of the method.ResultsThe results showed that the global cortical DTI derived measures were able to detect differences, in both PCA and tAD patients compared to healthy controls. The AngleR was the best measure to discriminate HC from tAD (AUC?=?0.922), while PerpPD was the best measure to discriminate HC from PCA (AUC?=?0.961). Finally, the best global measure to differentiate the two patient groups was ParlPD (AUC?=?0.771). The comparison between PCA and tAD patients revealed a different pattern of damage within the AD spectrum and the regional comparisons identified significant differences in key regions including parietal and temporal lobe cortical areas. The best AUCs were shown by PerpPD right lingual cortex (AUC?=?0.856), PerpPD right superior parietal cortex (AUC?=?0.842) and ParlPD right lateral occipital cortex (AUC?=?0.826).ConclusionsDiagnostic group differences were found, suggesting that the new cortical DTI analysis method may be useful to investigate cortical changes in dementia, providing better characterization of neurodegeneration, and potentially aiding differential diagnosis and prognostic accuracy.

Project description:IntroductionIn vivo clinical, anatomical and metabolic differences between posterior cortical atrophy (PCA) patients presenting with different Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers profiles are still unknown.MethodsTwenty-seven PCA patients underwent CSF examination and were classified as 1) PCA with a typical CSF AD profile (PCA-tAD; abnormal amyloid and T-tau/P-tau biomarkers, n = 13); 2) PCA with an atypical AD CSF profile (PCA-aAD; abnormal amyloid biomarker only, n = 9); and 3) PCA not associated with AD (PCA-nonAD; normal biomarkers, n = 5). All patients underwent clinical and cognitive assessment, structural MRI, and a subset of them underwent brain 18F-FDG PET.ResultsAll patients' groups showed a common pattern of posterior GM atrophy and hypometabolism typical of PCA, as well as equivalent demographics and clinical/cognitive profiles. PCA-tAD patients showed a group-specific pattern of hypometabolism in the left fusiform gyrus and inferior temporal gyrus. PCA-aAD did not present a group-specific atrophy pattern. Finally, group-specific gray matter atrophy in the right dorsolateral prefrontal cortex, left caudate nucleus and right medial temporal regions and hypometabolism in the right supplementary motor area and paracentral lobule were observed in PCA-nonAD patients.ConclusionOur findings suggest that both PCA-tAD and PCA-aAD patients are on the AD continuum, in agreement with the recently suggested A/T/N model. Furthermore, in PCA, the underlying pathology has an impact at least on the anatomo-functional presentation. Brain damage observed in PCA-tAD and PCA-aAD was mostly consistent with the well-described presentation of the disease, although it was more widespread in PCA-tAD group, especially in the left temporal lobe. Additional fronto-temporal (especially dorsolateral prefrontal) damage seems to be a clue to underlying non-AD pathology in PCA, which warrants the need for longitudinal follow-ups to investigate frontal symptoms in these patients.

Project description:ObjectiveTo determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria (i.e., dorsal, ventral, dominant-parietal, and caudal) we assessed associations between latent atrophy factors and cognition.MethodsWe employed a data-driven Bayesian modeling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multicenter cohort of 119 individuals with PCA (age 64 ± 7 years, 38% male, Mini-Mental State Examination 21 ± 5, 71% β-amyloid positive, 29% β-amyloid status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, MRI scanner field strength, and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a priori classification. Individual factor expressions were correlated to 4 PCA-specific cognitive domains (object perception, space perception, nonvisual/parietal functions, and primary visual processing) using general linear models.ResultsThe model revealed 4 distinct yet partially overlapping atrophy factors: right-dorsal, right-ventral, left-ventral, and limbic. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the large majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiologic phenotype.ConclusionOur results indicate that specific brain behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain regions and symptoms, indicating that classification into 4 mutually exclusive variants is unlikely to be clinically useful.

Project description:The neuropathologic basis of in vivo cortical atrophy in clinical dementia syndromes remains poorly understood. This includes primary progressive aphasia (PPA), a language-based dementia syndrome characterized by asymmetric cortical atrophy. The neurofibrillary tangles (NFTs) and amyloid-ß plaques (APs) of Alzheimer's disease (AD) can cause PPA, but a quantitative investigation of the relationships between NFTs, APs and in vivo cortical atrophy in PPA-AD is lacking. The present study measured cortical atrophy from corresponding bilateral regions in five PPA-AD participants with in vivo magnetic resonance imaging scans 7-30 months before death and acquired stereologic estimates of NFTs and dense-core APs visualized with the Thioflavin-S stain. Linear mixed models accounting for repeated measures and stratified by hemisphere and region (language vs. non-language) were used to determine the relationships between cortical atrophy and AD neuropathology and their regional selectivity. Consistent with the aphasic profile of PPA, left language regions displayed more cortical atrophy (P = 0.01) and NFT densities (P = 0.02) compared to right language homologues. Left language regions also showed more cortical atrophy (P < 0.01) and NFT densities (P = 0.02) than left non-language regions. A subset of data was analyzed to determine the predilection of AD neuropathology for neocortical regions compared to entorhinal cortex in the left hemisphere, which showed that the three most atrophied language regions had greater NFT (P = 0.04) and AP densities (P < 0.01) than the entorhinal cortex. These results provide quantitative evidence that NFT accumulation in PPA selectively targets the language network and may not follow the Braak staging of neurofibrillary degeneration characteristic of amnestic AD. Only NFT densities, not AP densities, were positively associated with cortical atrophy within left language regions (P < 0.01) and right language homologues (P < 0.01). Given previous findings from amnestic AD, the current study of PPA-AD provides converging evidence that NFTs are the principal determinants of atrophy and clinical phenotypes associated with AD.

Dataset Information

Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease.

Introduction

Methods

Results

Discussion

Publications

Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease.

Similar Datasets

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