Genotype patterns at PICALM, CR1, BIN1, CLU , and APOE genes are associated with episodic memory
Sandra BarralThomas D. BirdAlison GoateMR FarlowRamon Diaz‐ArrastiaDavid A. BennettN. R. Graff-RadfordBradley F. BoeveRobert A. SweetYaakov SternR. J. WilsonTatiana ForoudJürg OttRichard MayeuxRobert C. GreenNeil W. KowallLindsay A. FarrerJennifer WilliamsonVincent SantanaDonald E. SchmechelPeter GaskelBernardino GhettiMartin R. FarlowKelley FaberHeather A. PrenticeKelly HornerJohn H. GrowdonDeborah BlackerRudolph E. TanziBradley T. HymanBradley F. BoeveKaren M. KuntzLindsay NorgaardNathan LarsonDana KistlerFrancine ParfittJenny HaddowJeremy M. SilvermanMichal Schnaider BeeriMary SanoJoy WangRachel LallyNancy JohnsonMarcel MesulamSandra WeıntraubEileen H. BigioJeffrey KayePatricia KramerJessica Payne-MurphyDavid A. BennettHolli JacobsJoon ChangDanielle ArendsLindy HarrellGeorge BartzokisJeffery L. CummingsPo H. LuUsha TolandCharles SmithAlise BrickhouseJohn Q. TrojanowskiVivianna M. Van DeerlinElisabeth McCarty WoodSteven T. DeKoskyRobert A. SweetElise A. WeamerHelena C. ChuiArousiak VarpetianRamon Diaz‐ArrastiaRoger N. RosenbergBárbara DavisThomas D. BirdGerard D. SchellenbergMurray A. RaskindMalia RumbaughKate NickelAlison GoateJohn MorrisJoanne NortonDenise LevitchB. GrantMary A. CoatsAllen LeveyAmi RosenEzinna Anosike
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Abstract:
Several genome-wide association studies (GWAS) have associated variants in late-onset Alzheimer disease (LOAD) susceptibility genes; however, these single nucleotide polymorphisms (SNPs) have very modest effects, suggesting that single SNP approaches may be inadequate to identify genetic risks. An alternative approach is the use of multilocus genotype patterns (MLGPs) that combine SNPs at different susceptibility genes.Using data from 1,365 subjects in the National Institute on Aging Late-Onset Alzheimer's Disease Family Study, we conducted a family-based association study in which we tabulated MLGPs for SNPs at CR1, BIN1, CLU, PICALM, and APOE. We used generalized estimating equations to model episodic memory as the dependent endophenotype of LOAD and the MLGPs as predictors while adjusting for sex, age, and education.Several genotype patterns influenced episodic memory performance. A pattern that included PICALM and CLU was the strongest genotypic profile for lower memory performance (β = -0.32, SE = 0.19, p = 0.021). The effect was stronger after addition of APOE (p = 0.016). Two additional patterns involving PICALM, CR1, and APOE and another pattern involving PICALM, BIN1, and APOE were also associated with significantly poorer memory performance (β = -0.44, SE = 0.09, p = 0.009 and β = -0.29, SE = 0.07, p = 0.012) even after exclusion of patients with LOAD. We also identified genotype pattern involving variants in PICALM, CLU, and APOE as a predictor of better memory performance (β = 0.26, SE = 0.10, p = 0.010).MLGPs provide an alternative analytical approach to predict an individual's genetic risk for episodic memory performance, a surrogate indicator of LOAD. Identifying genotypic patterns contributing to the decline of an individual's cognitive performance may be a critical step along the road to preclinical detection of Alzheimer disease.Keywords:
Apolipoprotein E
Genome-wide Association Study
Clusterin
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Genetic Association
Genome‐wide association studies (GWAS) are a popular approach for identifying common genetic variants and epistatic effects associated with a disease phenotype. The traditional statistical analysis of such GWAS attempts to assess the association between each individual single‐nucleotide polymorphism (SNP) and the observed phenotype. Recently, kernel machine‐based tests for association between a SNP set (e.g., SNPs in a gene) and the disease phenotype have been proposed as a useful alternative to the traditional individual‐SNP approach, and allow for flexible modeling of the potentially complicated joint SNP effects in a SNP set while adjusting for covariates. We extend the kernel machine framework to accommodate related subjects from multiple independent families, and provide a score‐based variance component test for assessing the association of a given SNP set with a continuous phenotype, while adjusting for additional covariates and accounting for within‐family correlation. We illustrate the proposed method using simulation studies and an application to genetic data from the Genetic Epidemiology Network of Arteriopathy (GENOA) study.
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Genome-wide association studies (GWAS) play a critical role in identifying many loci for common diseases and traits. There has been a rapid increase in the number of GWAS over the past decade. As additional GWAS are being conducted, it is unclear whether a novel signal associated with the trait of interest is independent of single nucleotide polymorphisms (SNPs) in the same region that has been previously associated with the trait of interest. The general approach to determining whether the novel association is independent of previous signals is to examine the association of the novel SNP with the trait of interest conditional on the previously identified SNP and/or calculate linkage disequilibrium (LD) between the two SNPs. However, the role of epistasis and SNP by SNP interactions are rarely considered. Through simulation studies, we examined the role of SNP by SNP interactions when determining the independence of two genetic association signals. We have created an R package on Github called gxgRC to generate these simulation studies based on user input. In genetic association studies of asthma, we considered the role of SNP by SNP interactions when determining independence of signals for SNPs in the ARG1 gene and bronchodilator response.
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Abstract: Expression of the glycoprotein clusterin is markedly increased following tissue injury. One function of clusterin is to promote cell interactions which are perturbed in these pathologic settings. Clusterin causes cell aggregation and adhesion in vitro yet the molecular mechanism for this effect is not known. In order to identify the active site(s) of clusterin, 34 peptides, each 15 amino acid residues in length, were synthesized from hydrophilic regions of human clusterin. When studied individually, none of the peptides caused aggregation of LLC‐PK1 cells, a porcine renal epithelial cell line. However, two out of the 34 peptides inhibited clusterin‐induced cell aggregation in a dose‐dependent manner. Scrambled versions of these two ‘active’ peptides did not inhibit cell aggregation. Seven peptides promoted cell adhesion. In conclusion, these findings provide evidence for novel amino acid sequences mediating clusterin‐induced renal cell interactions.
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clusterin은 모든 포유류의 체액에 존재하는 이종 이량성 당단백질이며, 지금까지 연구된 거의 모든 종류의 세포에서 유도 및 발현된다. 또한 다기능성 단백질로 면역계, 남성생식계, 중추신경계에 관여하며, 보체, 지방수송, 분비 등의 기능에도 관여하는 것으로 알려져 있다. 특히 clusterin이 구강 내에 유리되면 구강 내 세균을 응집시켜 여러 가지 구강병소 발현에 영향을 미칠 수 있다. 이에 스트레스, 임신, 당뇨, 간염과 같은 전신질환자의 타액 내 clusterin의 발현유무를 확인하여, clusterin의 역할을 구명함으로써, 전신질환과 구강질환 간의 상호관계를 보다 과학적으로 확인하는데 기초를 마련하고자 본 실험을 시행하였다. 먼저 타액에서 clusterin의 발현유무를 확인하기 위하여, 스트레스, 임신, 당뇨, 간염과 같은 전신증상을 가지고 있는 실험군과 정상군을 설정한 후 각각의 전 타액 및 이하선의 순수 타액을 채취하고, clusterin의 양성 표식자로사용하기 위하여 정상인의 혈청을 채취하였다. 스트레스군은 발치 직전의 환자와 평소 스트레스를 호소하는 본과에 내원 환자를 선택하였다. 채취한 표본을 가열군과 비가열군으로 분류한 후 원심 분리하여 상층액 만을 분리한 후 각각의 표본에 western blot분석법을 시행하여 전신 질환과 관련된 타액 내 clusterin의 발현 유무를 관찰하였다. 1.타액과 혈청의 경우 비가열처리 군에서 단백질의 끌림 현상이 관찰되었으나,가열처리 군에서는 선명하게 관찰 되었다. 2. 가열처리한 사람의 전 타액에서 전신질환자군 및 정상군 중 스트레스군 일부와 임신군에서 clusterin이 관찰되었다. 3. 가열처리한 사람의 이하선 순수 타액에서는 전신질환자군 및 정상군 모두에서 clusterin이 발현되지 않았다. 사람의 타액 실험 중 스트레스, 임신, 당뇨, 간염과 같은 전신증상을 가지고 있는 실험군의 전 타액을 이용하여 clusterin의 변화를 관찰한 결과, 가열처리를 함에 따라 단백질의 끌림 현상이 해결되었던 것으로 보아 타액 중의 clusterin을 관찰하기 위해서는 가열처리가 필수적이라고 생각된다. 또한 통법에 의한 western blot을 통하여 실시하였을 때 clusterin이 발현되지 않았던 것은 전신질환과 관련된 타액 내의 clusterin의 분비가 매우 미약하거나 또는 다른 변수에 의하여 변성되는 것이 아닌가 생각하였다. 그러나 침전과정을 통하여 단백질의 양을 크게 늘려 관찰하였을 때, 일부 전 타액에서 clusterin의 발현을 관찰할 수 있었던 것으로 보아 전신상태의 변화에 따라 소량이나마 존재한다는 것을 확인하였고, 향후 구강 내로 분비된 clusterin이 구강 병소나 구강 내 미생물에 어떠한 영향을 미치는지의 연구가 수행되어야 할 것으로 생각된다.
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Aim: Recent genome‐wide association studies (GWAS) of bipolar disorder (BD) have detected new candidate genes, including DGKH , DFNB31 and SORCS2 . However, the results of these GWAS were not necessarily consistent, indicating the importance of replication studies. In this study, we tested the genetic association of DGKH , DFNB31 and SORCS2 with BD. Methods: We genotyped 18 single‐nucleotide polymorphisms (SNP) in DGKH , DFNB31 and SORCS2 using Japanese samples (366 cases and 370 controls). We also performed a meta‐analysis of four SNP in DGKH , using the previously published allele frequency data of Han‐Chinese case–control samples (1139 cases and 1138 controls). Results: In the association analysis using Japanese samples, a SNP in SORCS2 (rs10937823) showed nominal genotypic association. However, we could not find any association in an additional analysis of tag SNP around rs10937823. In the meta‐analysis of SNP in DGKH , rs9315897, which was not significantly associated with BD in the previous Chinese study, showed nominal association. Conclusion: Although the association was not strong, the result of this study would support the association between DGKH and BD.
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Amyloid β protein (Aβ) ending at amino acid 40 (Aβ40) and 42 (Aβ42) accumulates in human brain with aging and as a defining pathological component in Alzheimer's disease (AD). Plasma Aβ has been suggested as a marker of AD susceptibility, diagnosis and treatment effects. Moreover, clear heritability of plasma Aβ levels has been shown in late onset AD pedigrees, supporting the importance of genes in plasma Aβ regulation. In our study we aim to identify genetic factors involved in the regulation of Aβ levels in human plasma. In this study we investigated 1282 individuals within the Uppsala Longitudinal Study of Adult Men (ULSAM). ELISA measurements of Aβ40 and Aβ42 were performed in more than 2400 plasma samples collected at the 70, 77 and 82 year follow-ups. In addition, over 1100 DNA samples from ULSAM participants have been genotyped for 3 118 SNP's in 370 candidate genes for common diseases. Using UNPHASED software we have performed association analysis between quantitative measures of Aβ and genetic variants. We have performed association analyses between SNP's and Aβ40 and Aβ42 levels at age 70, 77 and 82. We have also performed association analysis between SNP's and averaged Aβ40 and Aβ42 levels from two or three time points. Over 70 genes showed association with levels of Aβ40 or Aβ42 at individual time points. Average levels of Aβ40 were associated with polymorphisms in 16 genes and average levels of Aβ42 were associated with polymorphisms in 13 genes (p < 0.05). However, only six genes showed association with both Aβ40 and Aβ42. Interestingly, carriers of the known AD susceptibility gene APOE ϵ4 allele have lower Aβ40 and Aβ42 levels in plasma, as compared to individuals without the ϵ4 allele. These results support a genetic component to plasma amyloid beta protein levels that may also reflect AD risk.
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