Association between APOC1 Polymorphism and Alzheimer’s Disease: A Case-Control Study and Meta-Analysis

Zhou, Qin; Zhao, Fan; Lv, Zhen; Zheng, Chengchao; Zheng, Weidong; Sun, Liang; Wang, Nana; Pang, Shenghang; Andrade, Fabiana Michelsen de; Fu, Mian; He, Xinqi; Hui, Juan; Jiang, WenyYu; Yang, Chuyu; Shi, Xiaohong; Zhu, Xiaoquan; Pang, Guo‐Fang; Yu, Yan; Xie, Haiqun; Zhang, Wandong; Hu, Chengping; Yang, Ze

doi:10.1371/journal.pone.0087017

Cited by 62 publications

(51 citation statements)

References 32 publications

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“…Little is known about the specific role of APOC1 in AD; however, as it is also a lipid carrier transport protein that, like APOE, is known to recruit the innate immune system, it may also have a role in regulation of microglial activation. More specifically, there are isolated studies which demonstrate linkage between APOC1 and declining cognition and memory in specific ethnic groups [59,60]. Consistent with the APOC1 role in lipid transport and immune activation, our expanded cell process enrichments specifically identified phagocytosis and activation of immune response (Fig.…”

Section: Apoc1 -Ceacam19 -Clptm1 Chr19supporting

confidence: 73%

“…While APOC1, CEACAM19, and CLPTM1 are associated with AD, both in this study and previous studies [60][61][62], a causal association to AD remains unclear. However, there is a small literature pointing to a role for CLPTM1 in the regulation of GABA receptor trafficking from the ER to the plasma membrane, suggesting that CLPTM1 could regulate inhibitory neurotransmission [63,64].…”

Section: Apoc1 -Ceacam19 -Clptm1 Chr19contrasting

confidence: 55%

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Multi-Tissue Neocortical Transcriptome-Wide Association Study Implicates 8 Genes Across 6 Genomic Loci in Alzheimer’s Disease

Gockley

Montgomery

Poehlman

et al. 2020

Preprint

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AbstractBackgroundAlzheimer’s disease (AD), an incurable neurodegenerative disease, currently affecting 1.75% of the United States population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD-risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION Transcriptome Wide Association Study (TWAS) pipeline to ingest expression from multiple neocortical regions, provide a set of 6780 gene weights which are abstracatable across the neocortex, and leverage these to find 8 genes from six loci with associated AD risk validated through summary mendelian randomization (SMR) utilizing IGAP summary statistics.MethodA combined dataset of 2003 genotypes clustered to Central European (CEU) ancestry was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles across 6 Neo-cortical tissues (TCX=248, FP=50, IFG=41, STG=34, PHG=34, DLPFC=461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene’s surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and provide support for cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues.ResultsCis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR < 5%: N=6775 (99.92%), Bonferroni: N=6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR < 0.05); APOC1, EED, CD2AP, CEACAM19, CLPTM1, MTCH2, TREM2, KNOP1.ConclusionWe provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

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Section: Apoc1 -Ceacam19 -Clptm1 Chr19supporting

confidence: 73%

Section: Apoc1 -Ceacam19 -Clptm1 Chr19contrasting

confidence: 55%

Multi-Tissue Neocortical Transcriptome-Wide Association Study Implicates 8 Genes Across 6 Genomic Loci in Alzheimer’s Disease

Gockley

Montgomery

Poehlman

et al. 2020

Preprint

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“…Our target was a 41-nt fragment of Apolipoprotein C1 (APOC1) mRNA (APOC1_41), a biomarker associated with the occurrence of Alzheimer’s disease. 42–44 We designed a second nanocarrier (referred to as Carrier2) to bind a fragment of APOC1_41 with its complementary PNA fragment (Table S1) and have the same polycationic peptide tag as Carrier1. In our nanopore experiments, we found the Carrier2•APOC1_41 complex to block the ionic current much more effectively ( I / I 0 =31.3±1.5%, Fig.…”

Section: Resultsmentioning

confidence: 99%

Interference-Free Detection of Genetic Biomarkers Using Synthetic Dipole-Facilitated Nanopore Dielectrophoresis

et al. 2017

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The motion of polarizable particles in a non-uniform electric field, i.e., dielectrophoresis, has been extensively used for concentration, separation, sorting, and transport of biological particles, from cancer cells and viruses to biomolecules such as DNAs and proteins. However, current approaches to dielectrophoretic manipulation are not sensitive enough to selectively target individual molecular species. Here we describe the application of the dielectrophoretic principle for selective detection of DNA and RNA molecules using an engineered biological nanopore. The key element of our approach is a synthetic polycationic nanocarrier that selectively binds to the target biomolecules, dramatically increasing their dielectrophoretic response to the electric field gradient generated by the nanopore. The dielectrophoretic capture of the nanocarrier-target complexes is detected as a transient blockade of the nanopore ionic current while any non-target nucleic acids are repelled from the nanopore by electrophoresis and thus do not interfere with the signal produced by the target’s capture. Strikingly, we show that even modestly charged nanocarriers can be used to capture DNA or RNA molecules of any length or secondary structure and simultaneously detect several molecular targets. Such selective, multiplex molecular detection technology would be highly desirable for real-time analysis of complex clinical samples.

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“…The expression regulation of other genes within the 19q13.32 region in relation to human diseases also has been investigated. For example, it has been shown that cis -modulation of APOC1 expression contributes to LOAD susceptibility [30], and that TOMM40 -mRNA levels are increased in LOAD brains and regulated by an intronic poly-T variant [25–27]. These findings suggest that the genetic pleiotropic effect is mediated by molecular mechanisms of gene expression regulation including, but not limited to, transcriptional regulation.…”

Section: Introductionmentioning

confidence: 99%

The effects of PPARγ on the regulation of the TOMM40 - APOE - C1 genes cluster

Subramanian¹,

Gottschalk²,

Kim³

et al. 2017

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Diseas

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Chromosome 19q13.32 is a gene rich region, and has been implicated in multiple human phenotypes in adulthood including lipids traits, Alzheimer’s disease, and longevity. Peroxisome Proliferator Activated Receptor Gamma (PPARγ) is a ligand-activated nuclear transcription factor that plays a role in human complex traits that are also genetically associated with the chromosome 19q13.32 region. Here, we study the effects of PPARγ on the regional expression regulation of the genes clustered within chromosome 19q13.32, specifically TOMM40, APOE, and APOC1, applying two complementary approaches. Using the short hairpin RNA (shRNA) method in the HepG2 cell-line we knocked down PPARγ expression and measured the effect on mRNA expression. We discovered PPARγ knock down increased the levels of TOMM40-, APOE-, and APOC1-mRNAs, with the highest increase in expression observed for APOE-mRNA. To complement the PPARγ knockdown findings we also examined the effects of low doses of PPARγ agonists (nM range) on mRNA expression of these genes. Low (nM) concentrations of Pioglitazone (Pio) decreased transcription of TOMM40, APOE and APOC1 genes, with the lowest mRNA levels for each gene observed at 1.5 nM. Similar to the effect of PPARγ knockdown, the strongest response to Pioglitazone was also observed for APOE-mRNA, and Rosiglitazone (Rosi), another PPARγ agonist, produced results that were consistent with these. In conclusion, our results further established a role for PPARγ in regional transcriptional regulation of chr19q13.32, underpinning the association between PPARγ, the chr19q13.32 genes cluster, and human complex traits and disease.

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Association between APOC1 Polymorphism and Alzheimer’s Disease: A Case-Control Study and Meta-Analysis

Cited by 62 publications

References 32 publications

Multi-Tissue Neocortical Transcriptome-Wide Association Study Implicates 8 Genes Across 6 Genomic Loci in Alzheimer’s Disease

Multi-Tissue Neocortical Transcriptome-Wide Association Study Implicates 8 Genes Across 6 Genomic Loci in Alzheimer’s Disease

Interference-Free Detection of Genetic Biomarkers Using Synthetic Dipole-Facilitated Nanopore Dielectrophoresis

The effects of PPARγ on the regulation of the TOMM40 - APOE - C1 genes cluster

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