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

Abstract

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.

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

“…As the MAD values we obtained using dMDA were poor, we recalculated MAD after gradually increasing the bin size up to 5 Mb, which improved the values as expected 9 . We also found that MAD can be further improved by removing noise using principal component analysis (see methods) 33 ( Supplementary Fig. 2 ).…”

“…We removed these calls from downstream analyses, as they could result from either dry lab/wet lab artifacts or germline mutations. 33,55 Filtering of Ginkgo CNV calls…”

“…CNV calling can then be performed using the residuals from the regression, instead of using normalized read counts. Somatic CNVs that are randomly distributed in the genome should remain unaffected 33 . We ran Ginkgo for different bin sizes (500 kb, 1 Mb, 2.5 Mb, 5 Mb), and for each bin size, we removed common variation, starting from 40% and increasing up to 90% in 10% increments.…”

“…The median CNV size was identical (3.52 Mb PicoPLEX, 3.51 Mb Copykit). For CNVs called by both, Copykit sizes were slightly smaller (median difference -0.54 Mb), with three notable large CNVs extending to the short arm telomere being much smaller (by[19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] in Copykit. As Copykit has not been formally benchmarked to our knowledge, while Ginkgo has been found to be accurate in calling breakpoints…”

Beyond C9orf72: repeat expansions and copy number variations as risk factors of amyotrophic lateral sclerosis across various populations

“…Although, based on a large genome scan study, rare CNVs with larger effect sizes do not play an essential role in ALS [ 57 ], investigating copy number variants in ALS might be prosperous. In other neurodegenerative diseases such as Alzheimer’s dementia and Parkinson’s disease the role of copy number variants has been extensively studied with convincing positive results [ 71 , 72 ].…”