Редактирование: ABCA7 (раздел)

==Publications==

{{medline-entry
|title=New genetic players in late-onset Alzheimer's disease: Findings of genome-wide association studies.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/30381536
|abstract=Late-onset Alzheimer's disease (LOAD) or sporadic AD is the most common form of AD. The precise pathogenetic changes that trigger the development of AD remain largely unknown. Large-scale genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms in multiple genes which are associated with AD; most notably, these are [[ABCA7]], bridging integrator 1 (B1N1), triggering receptor expressed on myeloid cells 2 (TREM2), [[CD33]], clusterin (CLU), complement receptor 1 (CRI), ephrin type-A receptor 1 (EPHA1), membrane-spanning 4-domains, subfamily A (MS4A) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes. The proteins coded by the candidate genes participate in a variety of cellular processes such as oxidative balance, protein metabolism, cholesterol metabolism and synaptic function. This review summarizes the major gene loci affecting LOAD identified by large GWASs. Tentative mechanisms have also been elaborated in various studies by which the proteins coded by these genes may exert a role in AD pathogenesis have also been elaborated. The review suggests that these may together affect LOAD pathogenesis in a complementary fashion.
|mesh-terms=* ATP-Binding Cassette Transporters
* Age of Onset
* Alzheimer Disease
* Clusterin
* Genetic Predisposition to Disease
* Genome-Wide Association Study
* Humans
* Membrane Glycoproteins
* Polymorphism, Single Nucleotide
* Receptors, Immunologic
* Risk Factors
* Sialic Acid Binding Ig-like Lectin 3
|keywords=* Alzheimer's disease
* Heart and Aging Research in Genomic Epidemiology
* LOAD
* Translational Genomics Research Institute
* genome-wide association study
* single nucleotide polymorphism
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206761
}}
{{medline-entry
|title=Whole-Exome Sequencing of an Exceptional Longevity Cohort.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/29750252
|abstract=Centenarians represent a unique cohort to study the genetic basis for longevity and factors determining the risk of neurodegenerative disorders, including Alzheimer's disease (AD). The estimated genetic contribution to longevity is highest in centenarians and super-cententenarians, but few genetic variants have been shown to clearly impact this phenotype. While the genetic risk for AD and other dementias is now well understood, the frequency of known dementia risk variants in centenarians is not fully characterized. To address these questions, we performed whole-exome sequencing on 100 individuals of 98-108 years age in search of genes with large effect sizes towards the exceptional aging phenotype. Overall, we were unable to identify a rare protein-altering variant or individual genes with an increased burden of rare variants associated with exceptional longevity. Gene burden analysis revealed three genes of nominal statistical significance associated with extreme aging, including [[LYST]], [[MDN1]], and [[RBMXL1]]. Several genes with variants conferring an increased risk for AD and other dementias were identified, including [[TREM2]], [[EPHA1]], [[ABCA7]], [[PLD3]], [[MAPT]], and [[NOTCH3]]. Larger centenarian studies will be required to further elucidate the genetic basis for longevity, and factors conferring protection against age-dependent neurodegenerative syndromes.
|mesh-terms=* Age Factors
* Aged, 80 and over
* Alzheimer Disease
* Cohort Studies
* Dementia
* Female
* Humans
* Longevity
* Male
* Risk Factors
* Whole Exome Sequencing
|keywords=* Alzheimer’s disease
* Centenarian
* Dementia
* SKAT
* Whole-exome sequencing
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696723
}}
{{medline-entry
|title=Recent studies on cellular and molecular mechanisms in Alzheimer's disease: focus on epigenetic factors and histone deacetylase.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/29397389
|abstract=Alzheimer's disease (AD) is one of the most common neurodegenerative disorders mainly affecting elderly people. It is characterized by progressive loss of memory and cognitive function. More than 95% of AD cases are related to sporadic or late-onset AD (LOAD). The etiology of LOAD is still unclear. It has been reported that environmental factors and epigenetic alterations play a significant role in AD pathogenesis. Furthermore, recently, genome-wide association studies (GWAS) identified 10 novel risk genes: [[ABCA7]], [[APOE]], [[BIN1]], [[CD2AP]], [[CD33]], [[CLU]], [[CR1]], [[MS4A6A]], [[MS4A4E]], and [[PICALM]], which play an important role for LOAD. In this review, the therapeutic approaches of AD by epigenetic modifications have been discussed. Nowadays, HDAC inhibitors have clinically proven its activity for epigenetic modifications. Furthermore, we try to establish the relationship between HDAC inhibitors and above mentioned LOAD risk genes. Finally, we are hoping that this review may open new area of research for AD treatment.
|mesh-terms=* Aging
* Alzheimer Disease
* Animals
* Cognition Disorders
* Epigenesis, Genetic
* Genetic Predisposition to Disease
* Genome-Wide Association Study
* Histone Deacetylase Inhibitors
* Histone Deacetylases
* Humans
|keywords=* Alzheimer’s disease
* GWAS
* HDAC inhibitors
* LOAD
* epigenetic modification
|full-text-url=https://sci-hub.do/10.1515/revneuro-2017-0049
}}
{{medline-entry
|title=Late Onset Alzheimer's Disease Risk Variants in Cognitive Decline: The PATH Through Life Study.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28269768
|abstract=Recent genome wide association studies have identified a number of single nucleotide polymorphisms associated with late onset Alzheimer's disease (LOAD). We examined the associations of 24 LOAD risk loci, individually and collectively as a genetic risk score, with cognitive function. We used data from 1,626 non-demented older Australians of European ancestry who were examined up to four times over 12 years on tests assessing episodic memory, working memory, vocabulary, and information processing speed. Linear mixed models were generated to examine associations between genetic factors and cognitive performance. Twelve SNPs were significantly associated with baseline cognitive performance ([[ABCA7]], [[MS4A4E]], SORL1), linear rate of change (APOE, [[ABCA7]], [[INPP5D]], [[ZCWPW1]], CELF1), or quadratic rate of change (APOE, [[CLU]], [[EPHA1]], [[HLA-DRB5]], [[INPP5D]], FERMT2). In addition, a weighted genetic risk score was associated with linear rate of change in episodic memory and information processing speed. Our results suggest that a minority of AD related SNPs may be associated with non-clinical cognitive decline. Further research is required to verify these results and to examine the effect of preclinical AD in genetic association studies of cognitive decline. The identification of LOAD risk loci associated with non-clinical cognitive performance may help in screening for individuals at greater risk of cognitive decline.
|mesh-terms=* Age of Onset
* Alzheimer Disease
* Australia
* Cognitive Dysfunction
* European Continental Ancestry Group
* Female
* Genetic Association Studies
* Genetic Loci
* Genetic Predisposition to Disease
* Humans
* Linear Models
* Longitudinal Studies
* Male
* Middle Aged
* Neuropsychological Tests
* Polymorphism, Single Nucleotide
|keywords=* Alzheimer’s disease
* cognitive aging
* genetic epidemiology
* genetic risk scores
* longitudinal studies
* single nucleotide polymorphisms
|full-text-url=https://sci-hub.do/10.3233/JAD-160774
}}
{{medline-entry
|title=Association and interaction effects of Alzheimer's disease-associated genes and lifestyle on cognitive aging in older adults in a Taiwanese population.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28199971
|abstract=Genome-wide association studies and meta-analyses implicated that increased risk of developing Alzheimer's diseases (AD) has been associated with the [[ABCA7]], [[APOE]], [[BIN1]], [[CASS4]], [[CD2AP]], [[CD33]], [[CELF1]], [[CLU]], [[CR1]], [[DSG2]], [[EPHA1]], [[FERMT2]], [[HLA-DRB1]], [[HLA-DRB4]], [[INPP5D]], [[MEF2C]], [[MS4A4A]], [[MS4A4E]], [[MS4A6E]], [[NME8]], [[PICALM]], [[PLD3]], [[PTK2B]], [[RIN3]], [[SLC24A4]], [[SORL1]], and [[ZCWPW1]] genes. In this study, we assessed whether single nucleotide polymorphisms (SNPs) within these 27 AD-associatedgenes are linked with cognitive aging independently and/or through complex interactions in an older Taiwanese population. We also analyzed the interactions between lifestyle and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examination (MMSE) scores were performed for all subjects to evaluate cognitive functions. Out of the 588 SNPs tested in this study, only the association between [[CASS4]]-rs911159 and cognitive aging persisted significantly (P = 2.2 x 10-5) after Bonferroni correction. Our data also showed a nominal association of cognitive aging with the SNPs in six more key AD-associated genes, including [[EPHA1]]-rs10952552, [[FERMT2]]-rs4901317, [[MEF2C]]-rs9293506, [[PLD3]]-rs11672825, [[RIN3]]-rs1885747, and [[SLC24A4]]-rs67063100 (P = 0.0018~0.0097). Additionally, we found the interactions among [[CASS4]]-rs911159, EPHA-rs10952552, [[FERMT2]]-rs4901317, [[MEF2C]]-rs9293506, or [[SLC24A4]]-rs67063100 on cognitive aging (P = 0.004~0.035). Moreover, our analysis suggested the interactions of [[SLC24A4]]-rs67063100 or [[MEF2C]]-rs9293506 with lifestyle such as alcohol consumption, smoking status, physical activity, or social support on cognitive aging (P = 0.008~0.041). Our study indicates that the AD-associated genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-lifestyle interactions.
|mesh-terms=* Age Factors
* Aged
* Alleles
* Alzheimer Disease
* Cognitive Aging
* Epistasis, Genetic
* Female
* Gene-Environment Interaction
* Genetic Association Studies
* Genetic Predisposition to Disease
* Humans
* Life Style
* Male
* Middle Aged
* Polymorphism, Single Nucleotide
* Risk Factors
* Taiwan
|keywords=* Alzheimer’s diseases
* Gerotarget
* Mini-Mental State Examination
* cognitive aging
* gene-gene and gene-lifestyle interactions
* single nucleotide polymorphisms
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5421828
}}
{{medline-entry
|title=Gene-based aggregate SNP associations between candidate AD genes and cognitive decline.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/27005436
|abstract=Single nucleotide polymorphisms (SNPs) in and near [[ABCA7]], [[BIN1]], [[CASS4]], [[CD2AP]], [[CD33]], [[CELF1]], [[CLU]], complement receptor 1 ([[CR1]]), [[EPHA1]], [[EXOC3L2]], [[FERMT2]], HLA cluster (DRB5-DQA), [[INPP5D]], [[MEF2C]], MS4A cluster (MS4A3-[[MS4A6E]]), [[NME8]], [[PICALM]], [[PTK2B]], [[SLC24A4]], [[SORL1]], and [[ZCWPW1]] have been associated with Alzheimer's disease (AD) in large meta-analyses. We aimed to determine whether established AD-associated genes are associated with longitudinal cognitive decline by examining aggregate variation across these gene regions. In two single-sex cohorts of older, community-dwelling adults, we examined the association between SNPs in previously implicated gene regions and cognitive decline (age-adjusted person-specific cognitive slopes) using a Sequence Kernel Association Test (SKAT). In regions which showed aggregate significance, we examined the univariate association between individual SNPs in the region and cognitive decline. Only two of the original AD-associated SNPs were significantly associated with cognitive decline in our cohorts. We identified significant aggregate-level associations between cognitive decline and the gene regions [[BIN1]], [[CD33]], [[CELF1]], [[CR1]], HLA cluster, and [[MEF2C]] in the all-female cohort and significant associations with [[ABCA7]], HLA cluster, [[MS4A6E]], [[PICALM]], [[PTK2B]], [[SLC24A4]], and [[SORL1]] in the all-male cohort. We also identified a block of eight correlated SNPs in [[CD33]] and several blocks of correlated SNPs in [[CELF1]] that were significantly associated with cognitive decline in univariate analysis in the all-female cohort. 
|mesh-terms=* Aged
* Aging
* Alzheimer Disease
* Cognition Disorders
* DNA
* Female
* Genetic Association Studies
* Genetic Predisposition to Disease
* Humans
* Male
* Polymorphism, Single Nucleotide
|keywords=* Candidate AD genes
* Cognitive decline
* SNP associations
|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005889
}}
{{medline-entry
|title=Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS).
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/22445811
|abstract=Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promising late-onset Alzheimer's disease (LOAD) susceptibility genes identified through several recent large genome-wide association studies (GWAS). These 10 LOAD genes ([[APOE]], [[CLU]], [[PICALM]], [[CR1]], [[BIN1]], [[ABCA7]], [[MS4A6A]], [[CD33]], [[CD2AP]], and EPHA1) have been tested for association with human aging in our dataset (1385 samples with documented age at death [AAD], age range: 58-108 years; mean age at death: 80.2) using the most significant single nucleotide polymorphisms (SNPs) found in the previous studies. Apart from the [[APOE]] locus (rs2075650) which showed compelling evidence of association with risk on human life span (p = 5.27 × 10(-4)), none of the other LOAD gene loci demonstrated significant evidence of association. In addition to examining the known LOAD genes, we carried out analyses using age at death as a quantitative trait. No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.
|mesh-terms=* Age Distribution
* Aging
* Alzheimer Disease
* Chromosome Mapping
* Genetic Markers
* Genetic Predisposition to Disease
* Genetic Variation
* Genome-Wide Association Study
* Humans
* Polymorphism, Single Nucleotide
* Prevalence

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120742
}}