Abstract

AbstractBackgroundAlzheimer’s disease (AD) is up to 60‐80% heritable, but less than ∼20% is explained by studies analyzing single nucleotide variants (SNVs). One limitation of short‐read whole‐genome sequencing (SRS) is the standard read length of 150 base pairs, which does not enable the detection of longer structural variants (SVs). Here we sequenced individuals using long‐read sequencing (LRS), which can sequence reads with an average length of ∼20 kilobases, allowing us to identify SVs previously uncaptured.MethodAll participants underwent whole‐genome LRS (∼15x coverage) and a subgroup (84%) underwent SRS. Out of 576 participants (47% males, age = 70.6±7.9 y.o.), 115 were diagnosed with AD or mild cognitive impairment, 365 were healthy controls, and 96 were diagnosed with a synucleinopathy (either Parkinson or Lewy Body disease). Eighty‐three index SNVs from loci associated with AD risk through GWAS (Bellenguez et al., Nature Genetics 2022) were genotyped with 30x coverage SRS, in addition to APOE2‐4. A 1Mbp window was defined around these SNVs to construct the discovery range for SVs (Sniffles2 population mode). Linkage disequilibrium (LD) was assessed between SNVs and SVs (CubeX).ResultA total of 14854 SVs were found across the AD risk loci (Figure1). After LD calculation, N = 197 SVs had a R2>0.1 (Figure2). The SVs with the highest LD (R2>0.7) are reported in Table1, among which there is a 322 bp deletion in the 3’ UTR region of the TMEM106B in high LD (R2 = 0.918) with the intronic SNV rs13237518. This TMEM106B locus has been previously associated with the risk of frontotemporal lobar dementia with TDP‐43 pathology in addition to AD, but the causative SNV has not been identified yet. This large deletion may mediate TMEM106B’s risk‐modulating role in AD and FTLD‐TDP (Chemparathy et al. medRxiv 2023). At the complex MAPT locus, three SVs showed a high LD with rs199515.ConclusionInsights into the role of SVs in neurodegenerative disorders have been hampered due to limitations with SRS. Using LRS in a large AD‐related sample, we characterized for the first time the genetic variation of SVs in known AD risk loci and provide a roadmap to identify potential causal SVs driving the AD association signal.

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