Genome-Wide Meta-Analysis of Late-Onset Alzheimer’s Disease Using Rare Variant Imputation in 65,602 Subjects Identifies Novel Rare Variant Locus <i>NCK2</i>: The International Genomics of Alzheimer’s Project (IGAP)

Naj, Adam C; Leonenko, Ganna; Jian, Xueqiu; Grenier‐Boley, Benjamin; Mc, Dalmasso; Bellenguez, Céline; J, Sha; Zhao, Yi; Sj, van der Lee; Sims, Rebecca; Chouraki, Vincent; Jc, Bis; Bw, Kunkle; Holmans, Peter Alan; Leung, Yuk Yee; Jj, Farrell; Chesi, Alessandra; Chen, H; Vardarajan, Badri N.; Benchek, Penelope; Barral, Sandra; C, Lee; Kuksa, Pavel P.; Haut, J; Lee, EB; M, Li; Zhang, Y; Grant, Struan F.A.; Phillips-Cremins, Jennifer E.; H, Comic; Pitsillides, Achilleas N.; R, Xia; Kl, Hamilton-Nelson; Kuzma, Amanda B.; Valladares, Otto; Fulton‐Howard, Brian; Dupuis, Josée; Ws, Bush; Wang, L; Je, Below; Farrer, Lindsay A.; Duijn, Cornelia M. van; Mayeux, Richard; Jl, Haines; Al, DeStefano; Pericak‐Vance, M. A.; Ramı́rez, Alfredo; Seshadri, Sudha; Amouyel, Philippe; Williams, Julie; Lambert, Jean‐Charles; Gd, Schellenberg

doi:10.1101/2021.03.14.21253553

Cited by 11 publications

(9 citation statements)

References 148 publications

(122 reference statements)

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“…Genome-wide meta-analysis using rare variant imputation identified a novel association of a rare variant (rs143080277) in NCK adaptor protein 2 (NCK2) with AD [57]. The same variant was identified in a genomewide meta-analysis, fine-mapping, and integrative prioritization study.…”

Section: Replicated Genes Harboring Rare Variants With Reduced Penetr...mentioning

confidence: 90%

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer’s disease

Khani

Gibbons

Brás

et al. 2022

Mol Neurodegeneration

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The search for rare variants in Alzheimer’s disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful.Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs.Multiple independent studies have now shown associations of rare variants in NOTCH3, TREM2, SORL1, ABCA7, BIN1, CLU, NCK2, AKAP9, UNC5C, PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions.Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.

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Section: Replicated Genes Harboring Rare Variants With Reduced Penetr...mentioning

confidence: 90%

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer’s disease

Khani

Gibbons

Brás

et al. 2022

Mol Neurodegeneration

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“…In a recent paper available in preprint [79] using the largest number of 111,326 (46,828 proxy) AD cases along with 677,633 controls have identified the most number of 68 loci in one study that also included 35 new loci: SORT1, ADAM17, PRKD3, WDR12, MME, IDUA, RHOH, ANKH, COX7C, RASGEF1C, HS3ST5, UMAD1, ICA1, JAZF1, SEC61G, CTSB, SHARPIN, ABCA1, ANK3, BLNK, PLEKHA1, TPCN1, IGH cluster, SNX1, CTSH, DOC2A, MAF, FOXF1, PRDM7, WDR81, MYO15A, KLF16, SIGLEC11, RBCK1, and SLC2A4RG. Another paper in preprint [80] has identified two of these loci (SHARPIN, ATF/SIGLEC11) in a total sample of 80,685 AD cases and 243,682 controls.…”

Section: Gwas In Europeans/whitesmentioning

confidence: 99%

Genomics and Functional Genomics of Alzheimer's Disease

Kamboh

2022

Neurotherapeutics

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Alzheimer’s disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5–10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

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“…Therefore, KnockoffScreen-AL can be easily applied to whole-genome studies without the need to phase, a substantial advantage given the high computational cost of phasing and the challenges in accurately phasing rare variants beyond reference panels. Even though the current AD application is based on a smaller sample size compared to recent AD GWAS, 15,23,24,34,35,36 it demonstrates the ability of the proposed Knockoffscreen-AL method to handle large biobankscale data. Compared to the analysis of the UK Biobank data in Jansen et al, 15 the data version we used (March 2021 update of the UK Biobank resource) contains more reported AD-affected individuals (ICD10 code) and more reported parental AD (due to 2 nd visits for some participants), so our single-variant/window analysis is better powered.…”

Section: Discussionmentioning

confidence: 96%

“…Head-to-head comparisons of the conventional and knockoff-based analyses emphasize the higher statistical power of Knockoffscreen-AL which highlighted additional loci, including known AD loci such as CLNK/HS3ST1, CD2AP, ABI3/ACE, and SORL1. Therefore, re-analysis of large datasets such as that in de Rojas et al 34 or other recent AD datasets 23,35,36 has great potential to discover additional loci, and the proposed optimization of computing time and memory usage makes such analyses feasible.…”

Section: Discussionmentioning

confidence: 99%

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Genome-wide analysis of common and rare variants via multiple knockoffs at biobank scale, with an application to Alzheimer disease genetics

Guen

Liu

et al. 2021

The American Journal of Human Genetics

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Summary Knockoff-based methods have become increasingly popular due to their enhanced power for locus discovery and their ability to prioritize putative causal variants in a genome-wide analysis. However, because of the substantial computational cost for generating knockoffs, existing knockoff approaches cannot analyze millions of rare genetic variants in biobank-scale whole-genome sequencing and whole-genome imputed datasets. We propose a scalable knockoff-based method for the analysis of common and rare variants across the genome, KnockoffScreen-AL , that is applicable to biobank-scale studies with hundreds of thousands of samples and millions of genetic variants. The application of KnockoffScreen-AL to the analysis of Alzheimer disease (AD) in 388,051 WG-imputed samples from the UK Biobank resulted in 31 significant loci, including 14 loci that are missed by conventional association tests on these data. We perform replication studies in an independent meta-analysis of clinically diagnosed AD with 94,437 samples, and additionally leverage single-cell RNA-sequencing data with 143,793 single-nucleus transcriptomes from 17 control subjects and AD-affected individuals, and proteomics data from 735 control subjects and affected indviduals with AD and related disorders to validate the genes at these significant loci. These multi-omics analyses show that 79.1% of the proximal genes at these loci and 76.2% of the genes at loci identified only by KnockoffScreen-AL exhibit at least suggestive signal (p < 0.05) in the scRNA-seq or proteomics analyses. We highlight a potentially causal gene in AD progression, EGFR , that shows significant differences in expression and protein levels between AD-affected individuals and healthy control subjects.

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Genome-Wide Meta-Analysis of Late-Onset Alzheimer’s Disease Using Rare Variant Imputation in 65,602 Subjects Identifies Novel Rare Variant Locus NCK2: The International Genomics of Alzheimer’s Project (IGAP)

Cited by 11 publications

References 148 publications

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer’s disease

Challenge accepted: uncovering the role of rare genetic variants in Alzheimer’s disease

Genomics and Functional Genomics of Alzheimer's Disease

Genome-wide analysis of common and rare variants via multiple knockoffs at biobank scale, with an application to Alzheimer disease genetics

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