Редактирование: FERMT2 (раздел)

==Publications==

{{medline-entry
|title=Extended Multiplexing of Tandem Mass Tags (TMT) Labeling Reveals Age and High Fat Diet Specific Proteome Changes in Mouse Epididymal Adipose Tissue.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28325852
|abstract=The lack of high-throughput methods to analyze the adipose tissue protein composition limits our understanding of the protein networks responsible for age and diet related metabolic response. We have developed an approach using multiple-dimension liquid chromatography tandem mass spectrometry and extended multiplexing (24 biological samples) with tandem mass tags (TMT) labeling to analyze proteomes of epididymal adipose tissues isolated from mice fed either low or high fat diet for a short or a long-term, and from mice that aged on low [i]versus[/i] high fat diets. The peripheral metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet and advancing age, with long-term high fat diet exposure being the worst. In response to short-term high fat diet, 43 proteins representing lipid metabolism ([i]e.g.[/i] [[AACS]], [[ACOX1]], ACLY) and red-ox pathways ([i]e.g.[/i] CPD2, CYP2E, SOD3) were significantly altered (FDR < 10%). Long-term high fat diet significantly altered 55 proteins associated with immune response ([i]e.g.[/i] IGTB2, [[IFIT3]], LGALS1) and rennin angiotensin system ([i]e.g.[/i] [[ENPEP]], [[CMA1]], [[CPA3]], ANPEP). Age-related changes on low fat diet significantly altered only 18 proteins representing mainly urea cycle ([i]e.g.[/i] [[OTC]], [[ARG1]], CPS1), and amino acid biosynthesis ([i]e.g.[/i] GMT, AKR1C6). Surprisingly, high fat diet driven age-related changes culminated with alterations in 155 proteins involving primarily the urea cycle ([i]e.g.[/i] [[ARG1]], CPS1), immune response/complement activation ([i]e.g.[/i] [[C3]], C4b, C8, [[C9]], [[CFB]], [[CFH]], FGA), extracellular remodeling ([i]e.g.[/i] [[EFEMP1]], [[FBN1]], [[FBN2]], [[LTBP4]], [[FERMT2]], [[ECM1]], [[EMILIN2]], ITIH3) and apoptosis ([i]e.g.[/i] [[YAP1]], [[HIP1]], [[NDRG1]], [[PRKCD]], MUL1) pathways. Using our adipose tissue tailored approach we have identified both age-related and high fat diet specific proteomic signatures highlighting a pronounced involvement of arginine metabolism in response to advancing age, and branched chain amino acid metabolism in early response to high fat feeding. Data are available via ProteomeXchange with identifier PXD005953.
|mesh-terms=* Adipose Tissue
* Aging
* Animals
* Diet, High-Fat
* Epididymis
* Gene Regulatory Networks
* Immunoblotting
* Male
* Mass Spectrometry
* Metabolic Networks and Pathways
* Mice, Inbred C57BL
* Proteome
* Proteomics
* Reproducibility of Results
* Sample Size

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5417827
}}
{{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
}}