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Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10.

ABSTRACT: A broad region of chromosome 10 (chr10) has engendered continued interest in the etiology of late-onset Alzheimer Disease (LOAD) from both linkage and candidate gene studies. However, there is a very extensive heterogeneity on chr10. We converged linkage analysis and gene expression data using the concept of genomic convergence that suggests that genes showing positive results across multiple different data types are more likely to be involved in AD. We identified and examined 28 genes on chr10 for association with AD in a Caucasian case-control dataset of 506 cases and 558 controls with substantial clinical information. The cases were all LOAD (minimum age at onset > or = 60 years). Both single marker and haplotypic associations were tested in the overall dataset and 8 subsets defined by age, gender, ApoE and clinical status. PTPLA showed allelic, genotypic and haplotypic association in the overall dataset. SORCS1 was significant in the overall data sets (p=0.0025) and most significant in the female subset (allelic association p=0.00002, a 3-locus haplotype had p=0.0005). Odds Ratio of SORCS1 in the female subset was 1.7 (p<0.0001). SORCS1 is an interesting candidate gene involved in the Abeta pathway. Therefore, genetic variations in PTPLA and SORCS1 may be associated and have modest effect to the risk of AD by affecting Abeta pathway. The replication of the effect of these genes in different study populations and search for susceptible variants and functional studies of these genes are necessary to get a better understanding of the roles of the genes in Alzheimer disease.

SUBMITTER: Liang X

PROVIDER: S-EPMC2713862 | biostudies-literature | 2009 Mar

REPOSITORIES: biostudies-literature

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Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10.

Liang Xueying X Slifer Michael M Martin Eden R ER Schnetz-Boutaud Nathalie N Bartlett Jackie J Anderson Brent B Züchner Stephan S Gwirtsman Harry H Gilbert John R JR Pericak-Vance Margaret A MA Haines Jonathan L JL

Human mutation 20090301 3

A broad region of chromosome 10 (chr10) has engendered continued interest in the etiology of late-onset Alzheimer Disease (LOAD) from both linkage and candidate gene studies. However, there is a very extensive heterogeneity on chr10. We converged linkage analysis and gene expression data using the concept of genomic convergence that suggests that genes showing positive results across multiple different data types are more likely to be involved in AD. We identified and examined 28 genes on chr10 ...[more]

PMID: 19241460

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Project description:BACKGROUND: Alzheimer's disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. RESULTS: Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (SR) based method followed by prioritization using clusters derived from PPI network. SR for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes. CONCLUSIONS: With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.

Project description:ImportanceMutations in APP, PSEN1, and PSEN2 lead to early-onset Alzheimer disease (EOAD) but account for?only approximately?11% of EOAD overall, leaving most of the genetic risk for the most severe form of Alzheimer disease unexplained. This extreme phenotype likely harbors highly penetrant risk variants, making it primed for discovery of novel risk genes and pathways for AD.ObjectiveTo search for rare variants contributing to the risk for EOAD.Design, setting, and participantsIn this case-control study, whole-exome sequencing (WES) was performed in 51 non-Hispanic white (NHW) patients with EOAD (age at onset <65 years) and 19 Caribbean Hispanic families previously screened as negative for established APP, PSEN1, and PSEN2 causal variants. Participants were recruited from John P. Hussman Institute for Human Genomics, Case Western Reserve University, and Columbia University. Rare, deleterious, nonsynonymous, or loss-of-function variants were filtered to identify variants in known and suspected AD genes, variants in multiple unrelated NHW patients, variants present in 19 Hispanic EOAD WES families, and genes with variants in multiple unrelated NHW patients. These variants/genes were tested for association in an independent cohort of 1524 patients with EOAD, 7046 patients with late-onset AD (LOAD), and 7001 cognitively intact controls (age at examination, >65 years) from the Alzheimer's Disease Genetics Consortium. The study was conducted from January 21, 2013, to October 13, 2016.Main outcomes and measuresAlzheimer disease diagnosed according to standard National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer Disease and Related Disorders Association criteria. Association between Alzheimer disease and genetic variants and genes was measured using logistic regression and sequence kernel association test-optimal gene tests, respectively.ResultsOf the 1524 NHW patients with EOAD, 765 (50.2%) were women and mean (SD) age was 60.0 (4.9) years; of the 7046 NHW patients with LOAD, 4171 (59.2%) were women and mean (SD) age was 77.4 (8.6) years; and of the 7001 NHW controls, 4215 (60.2%) were women and mean (SD) age was 77.4 (8.6) years. The gene PSD2, for which multiple unrelated NHW cases had rare missense variants, was significantly associated with EOAD (P?=?2.05?×?10-6; Bonferroni-corrected P value [BP]?=?1.3?×?10-3) and LOAD (P?=?6.22?×?10-6; BP?=?4.1?×?10-3). A missense variant in TCIRG1, present in a NHW patient and segregating in 3 cases of a Hispanic family, was more frequent in EOAD cases (odds ratio [OR], 2.13; 95% CI, 0.99-4.55; P?=?.06; BP?=?0.413), and significantly associated with LOAD (OR, 2.23; 95% CI, 1.37-3.62; P?=?7.2?×?10-4; BP?=?5.0?×?10-3). A missense variant in the LOAD risk gene RIN3 showed suggestive evidence of association with EOAD after Bonferroni correction (OR, 4.56; 95% CI, 1.26-16.48; P?=?.02, BP?=?0.091). In addition, a missense variant in RUFY1 identified in 2 NHW EOAD cases showed suggestive evidence of an association with EOAD as well (OR, 18.63; 95% CI, 1.62-213.45; P?=?.003; BP?=?0.129).Conclusions and relevanceThe genes PSD2, TCIRG1, RIN3, and RUFY1 all may be involved in endolysosomal transport-a process known to be important to development of AD. Furthermore, this study identified shared risk genes between EOAD and LOAD similar to previously reported genes, such as SORL1, PSEN2, and TREM2.

Project description:Usher syndrome 1C (USH1C) is a congenital condition manifesting profound hearing loss, the absence of vestibular function, and eventual retinal degeneration. The USH1C locus has been mapped genetically to a 2- to 3-cM interval in 11p14-15.1 between D11S899 and D11S861. In an effort to identify the USH1C disease gene we have isolated the region between these markers in yeast artificial chromosomes (YACs) using a combination of STS content mapping and Alu-PCR hybridization. The YAC contig is approximately 3.5 Mb and has located several other loci within this interval, resulting in the order CEN-LDHA-SAA1-TPH-D11S1310-(D11S1888/KCNC1 )-MYOD1-D11S902D11S921-D11S 1890-TEL. Subsequent haplotyping and homozygosity analysis refined the location of the disease gene to a 400-kb interval between D11S902 and D11S1890 with all affected individuals being homozygous for the internal marker D11S921. To facilitate gene identification, the critical region has been converted into P1 artificial chromosome (PAC) clones using sequence-tagged sites (STSs) mapped to the YAC contig, Alu-PCR products generated from the YACs, and PAC end probes. A contig of >50 PAC clones has been assembled between D11S1310 and D11S1890, confirming the order of markers used in haplotyping. Three PAC clones representing nearly two-thirds of the USH1C critical region have been sequenced. PowerBLAST analysis identified six clusters of expressed sequence tags (ESTs), two known genes (BIR, SUR1) mapped previously to this region, and a previously characterized but unmapped gene NEFA (DNA binding/EF hand/acidic amino-acid-rich). GRAIL analysis identified 11 CpG islands and 73 exons of excellent quality. These data allowed the construction of a transcription map for the USH1C critical region, consisting of three known genes and six or more novel transcripts. Based on their map location, these loci represent candidate disease loci for USH1C. The NEFA gene was assessed as the USH1C locus by the sequencing of an amplified NEFA cDNA from an USH1C patient; however, no mutations were detected.

Dataset Information

Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10.

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Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10.

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