Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer’s disease-associated genes: DTNB and DLG2

Abstract

Alzheimer’s disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10−6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (pmeta = 4.74 × 10−8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta = 1 × 10−6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.

Bioinformatics pipeline to guide post‐GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants

“…Rare variants near the APOE region have been reported to be associated with cerebrospinal fluid and neuroimaging biomarkers of AD and were hypothesized to account for some of the missing heritability of AD not explained by the common variation assessed by GWAS 70 . Analysis of rare variation from whole‐genome sequencing datasets also revealed two novel AD‐associated genes: DTNB and DLG2 71 …”

A Deficiency of the Psychiatric Risk Gene DLG2/PSD-93 Causes Excitatory Synaptic Deficits in the Dorsolateral Striatum

“…Genetic variations in DLG2/PSD-93 have been implicated in various disorders, including schizophrenia ( Walsh et al, 2008 ; Kirov et al, 2012 ; Fromer et al, 2014 ), intellectual disability ( Reggiani et al, 2017 ), and ASD ( Ruzzo et al, 2019 ), as well as neurodegenerative disorders, such as AD ( Hondius et al, 2016 ; Lawingco et al, 2021 ; Prokopenko et al, 2022 ) and Parkinson’s disease (PD) ( Foo et al, 2017 ; Wu et al, 2018 ; Zhao et al, 2020 ). However, the neural substrate for the genetic disruption of DLG2/PSD-93 has not been well understood.…”

Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data

“…These prior WGS studies include a family‐based study conducted in 2247 subjects from the National Institute of Mental Health (NIMH)/National Institute on Aging (NIA) with replication in 1669 independent participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI)/ADSP 4 . More recently, the same team investigated the association of groups of rare variants in the same datasets using a sliding‐window approach 5 . Additional studies conducted in Asian populations highlighted the importance of increasing the representation of understudied population groups and the potential of WGS to uncover population‐specific genetic loci 6,7 .…”

“…Previous studies that used WGS to identify genetic loci associated with AD performed genome‐wide association with limited sample sizes. 4 , 5 , 6 , 7 These prior WGS studies include a family‐based study conducted in 2247 subjects from the National Institute of Mental Health (NIMH)/National Institute on Aging (NIA) with replication in 1669 independent participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI)/ADSP. 4 More recently, the same team investigated the association of groups of rare variants in the same datasets using a sliding‐window approach.…”

“… 4 More recently, the same team investigated the association of groups of rare variants in the same datasets using a sliding‐window approach. 5 Additional studies conducted in Asian populations highlighted the importance of increasing the representation of understudied population groups and the potential of WGS to uncover population‐specific genetic loci. 6 , 7 We posit that until WGS is available in much larger samples, this data type is better suited for interrogation of previously identified loci rather than identification of novel loci.…”