Nectin-2 in general and in the brain

Mizutani, Kiyohito; Miyata, Muneaki; Shiotani, Hajime; Kameyama, Takeshi; Takai, Yoshimi

doi:10.1007/s11010-021-04241-y

Cited by 19 publications

(20 citation statements)

References 95 publications

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“…NECTIN2 is expressed in regions of the brain, having multiple functions, such as contribution to homeostasis of astrocytes and neurons, as well as the formation of synapses. Other SNPs in this genetic region have been previously shown to be associated with AD (Mizutani et al ., 2022). The rs10629382 variant is associated with B-cell CLL/lymphoma 3 ( BCL3 ), a proto-oncogene candidate that has been associated with late-onset familial AD and other cognitive impairment-related diseases (Nho et al ., 2017).…”

Section: Resultsmentioning

confidence: 99%

New genetic loci discovery for Alzheimer’s disease using explainable deep neural networks

Gkertsou,

Parameshwarappa,

Shiyanbola

et al. 2023

Preprint

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BackgroundGenome-wide association studies (GWAS) have shed light on various complex diseases and traits, by detecting more than 400,000 associated genetic loci. This number is expected to drastically increase because of the use of novel artificial intelligence methods offering new ways to study the effects of variants. Deep learning using artificial neural networks (ANN) is a sub-field of artificial intelligence, which simulates how the human brain learns. We aimed at assessing the potential of deep learning in human genetic studies of Alzheimer’s Disease (AD) and how these compare to the traditional statistical methods used in GWAS, by simultaneously testing the two approaches on the same dataset, while discovering new genetic loci associated to AD.MethodsTo address this aim, phenotypic and genome-wide SNP data from the UK Biobank was analysed on a binary outcome, AD diagnosis, in two different data balance options, of one-to-one and one-to-two case-control datasets, using 2,764 cases vs 2,764 controls and 5,528 controls respectively matched on gender, age, ethnicity, PC1-20 and genotyping array. Genetic data handling and GWAS were performed using PLINK, whereas neural networks were trained using GenNet, a new ANN tool, with the same datasets, separated into training (60%), validation (20%) and test (20%) sets. Neural network layers were determined using biological knowledge, by annotating SNPs to genes and genes to AD related pathways, using ANNOVAR annotations followed by GeneSCF and KEGG.ResultsSignificant associations were detected between four SNPs linked to two different genes and AD for the 1 to 1 case-control study design and six SNPs linked to four different genes for the 1 to 2 case-control study design by using PLINK. All identified regions have been previously associated to AD. GenNet identified twelve SNPs on seven genes to be associated with AD, all with biological plausibility, achieving an AUC of 0.80 when using three biologically determined layers and 0.73 when using two layers at the neural networks. No common top SNPs were identified between the machine learning and GWAS models.ConclusionThis is one of the first studies attempting to compare the traditional GWAS to more sophisticated state-of-art methods for understanding the genetic architecture of complex phenotypes using the same dataset. More systematic comparisons with such approaches on real data are needed to enable best practises for machine learning in the analysis of genome-wide genetic data.

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Section: Resultsmentioning

confidence: 99%

New genetic loci discovery for Alzheimer’s disease using explainable deep neural networks

Gkertsou,

Parameshwarappa,

Shiyanbola

et al. 2023

Preprint

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“… 15 GWAS analyses have reported a distinct association between rs6859 polymorphisms and several human diseases, such as Alzheimer’s disease, coronary heart disease, and multiple sclerosis. 15 , 37 , 38 The rs10198139, located in the first intron of HPCAL1, may impact the binding of regulatory elements and splicing of transcripts, but its role in disease development has not been documented. Simultaneously, rs6859 and rs10198139 may approach the DNase Ⅰ hypersensitivity peak clusters and transcription factor ChIP-seq clusters.…”

Section: Discussionmentioning

confidence: 99%

N6-methyladenosine-associated genetic variants in NECTIN2 and HPCAL1 are risk factors for abdominal aortic aneurysm

Li,

Wu,

Yang

et al. 2024

iScience

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“…Active epigenetic markers including ATAC-seq, H3K27ac, and H3K4me3 in this locus were noted in microglia, neurons, and oligodendrocytes. NECTIN2 is also known as CD112 or PVR-related 2 (PVRL2/PRR2) and its two splice variants (α and δ) are expressed in multiple tissues including brain neurons and astrocytes [50]. Genetic global ablation of NECTIN2 causes loss of neurons and nerve fibers in mouse brains at 6-months of age [51], indicating a protective role of NECTIN2 in neurodegeneration.…”

Section: Discussionmentioning

confidence: 99%

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer’s disease

Wang,

Nykänen,

Western

et al. 2023

Preprint

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Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16x10-19; rs142232675 p.D87N, P=2.71x10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86x10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we functionally validated that overexpression of TGFBR2 increased sTREM2 and silencing reduced sTREM2, whereas modulating RBMS3 did not. The last novel locus NECTIN2 on chr 19 (rs11666329, P=2.52x10-8) was independent of APOE genotype and colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

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Nectin-2 in general and in the brain

Cited by 19 publications

References 95 publications

New genetic loci discovery for Alzheimer’s disease using explainable deep neural networks

New genetic loci discovery for Alzheimer’s disease using explainable deep neural networks

N6-methyladenosine-associated genetic variants in NECTIN2 and HPCAL1 are risk factors for abdominal aortic aneurysm

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer’s disease

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