Somatic copy number variant load in neurons of healthy controls and Alzheimer’s disease patients

Download

index.pdf

Date

2022-12-01

Author

Turan, Zeliha Gözde
Richter, Vincent
Bochmann, Jana
Parvizi, Poorya
Yapar, Etka
Işıldak, Ulas
Waterholter, Sarah-Kristin
Leclere-Turbant, Sabrina
Son, Çağdaş Devrim
Duyckaerts, Charles
Yet, İdil
Arendt, Thomas
Somel, Mehmet
Ueberham, Uwe

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

130
views

70
downloads

The possible role of somatic copy number variations (CNVs) in Alzheimer’s disease (AD) aetiology has been controversial. Although cytogenetic studies suggested increased CNV loads in AD brains, a recent single-cell whole-genome sequencing (scWGS) experiment, studying frontal cortex brain samples, found no such evidence. Here we readdressed this issue using low-coverage scWGS on pyramidal neurons dissected via both laser capture microdissection (LCM) and fluorescence activated cell sorting (FACS) across five brain regions: entorhinal cortex, temporal cortex, hippocampal CA1, hippocampal CA3, and the cerebellum. Among reliably detected somatic CNVs identified in 1301 cells obtained from the brains of 13 AD patients and 7 healthy controls, deletions were more frequent compared to duplications. Interestingly, we observed slightly higher frequencies of CNV events in cells from AD compared to similar numbers of cells from controls (4.1% vs. 1.4%, or 0.9% vs. 0.7%, using different filtering approaches), although the differences were not statistically significant. On the technical aspects, we observed that LCM-isolated cells show higher within-cell read depth variation compared to cells isolated with FACS. To reduce within-cell read depth variation, we proposed a principal component analysis-based denoising approach that significantly improves signal-to-noise ratios. Lastly, we showed that LCM-isolated neurons in AD harbour slightly more read depth variability than neurons of controls, which might be related to the reported hyperploid profiles of some AD-affected neurons.

Subject Keywords

Alzheimer’s disease, Brain, Copy number variation, Denoising, Fluorescence-activated cell sorting, Laser capture microdissection, Single-cell whole-genome sequencing

URI

https://hdl.handle.net/11511/101791

Journal

Acta Neuropathologica Communications

DOI

https://doi.org/10.1186/s40478-022-01452-2

Collections

Department of Biology, Article

Suggestions

OpenMETU
Core

SOMATIC COPY NUMBER VARIANT LOAD IN NEURONS OF HEALTHY CONTROLS AND ALZHEIMER’S DISEASE PATIENTS Turan, Zeliha Gozde; Somel , Mehmet; Idil, Yet; Department of Biology (2023-1-9) The possible role of somatic copy number variations (CNVs) in Alzheimer’s disease (AD) aetiology has been controversial. Although cytogenetic studies suggested increased CNV loads in AD brains, a recent single-cell whole-genome sequencing (scWGS) experiment, studying frontal cortex brain samples, found no such evidence. Here we readdressed this issue using low-coverage scWGS on pyramidal neurons dissected via both laser capture microdissection (LCM) and fluorescence activated cell sorting (FACS) across five...
Meta analysis of alzheimer’s disease at the gene expression level İzgi, Hamit; Somel, Mehmet; Department of Biology (2017) In this study, publicly available microarray gene expression datasets are used to investigate common gene expression changes in different postmortem brain regions in Alzheimer’s Disease (AD) patients compared to control subjects, and to find possible functional associations related to these changes. The hypothesis is that pathogenesis of the disease converges into common patterns of dysregulation/alteration or dysfunction in molecular pathways across different brain regions in AD. In total, I studied 13 dat...
Computer-aided diagnosis of alzheimer’s disease and mild cognitive impairment with MARS/CMARS classification using structural MR images Çevik, Alper; Eyüboğlu, Behçet Murat; Weber, Gerhard Wilhelm; Department of Biomedical Engineering (2017) Early detection of Alzheimer’s disease (AD) and its prodromal stage, amnestic mild cognitive impairment (MCI), has drawn remarkable attention in recent years. Despite the impressive developments in fields of image analysis, pattern classification, and machine learning, no computer-aided diagnosis system has yet been a part of the clinical routine to diagnose the AD. This thesis study aims to propose a thorough procedure which involves detecting the early signs of disease-originated deformations by fully-aut...
COMPARATIVE ANALYSIS OF BRAIN CELL CULTURES AND TISSUES IN ALZHEIMER’S DISEASE BASED ON DIFFERENTIAL EXPRESSION AND GENE SET ENRICHMENT Burduroğlu, Hüseyin Cahit; Aydın Son, Yeşim; Department of Bioinformatics (2023-1-25) Alzheimer’s disease is currently the most common cause of dementia in the world. It is a neurodegenerative disease that is diagnosed neuropathologically by observing B-amyloid plaques and neurofibrillary tangles in the brain. Transcriptional differentiations, protein regulations, and the interactions in between have been investigated by recent studies to understand from which brain cell type the disease stems, such as microglia, astrocytes, and neurons. These studies are mostly performed on brain tiss...
Transcriptomic network analysis of brain aging and alzheimers disease Parvizi, Poorya; Somel, Mehmet; Tunçbağ, Nurcan; Department of Biology (2017) Multiple studies have investigated aging brain transcriptomes to identify for age-dependent expression changes and determine genes that may participate in age-related dysfunction. However, aging is a highly complex and heterogeneous process where multiple genes contribute at different levels depending on individuals’ environments and genotypes. Both this biological heterogeneity of aging, as well as technical biases and weaknesses inherent to transcriptome measurements, limit the information gained from a s...

Citation Formats

Z. G. Turan et al., “Somatic copy number variant load in neurons of healthy controls and Alzheimer’s disease patients,” Acta Neuropathologica Communications, vol. 10, no. 1, pp. 0–0, 2022, Accessed: 00, 2023. [Online]. Available: https://hdl.handle.net/11511/101791.