Dataset Information

Genome screen to detect linkage to intracranial aneurysm susceptibility genes: the Familial Intracranial Aneurysm (FIA) study.

ABSTRACT: Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA.Multiplex families having at least 2 individuals with "definite" or "probable" IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history of hypertension or present smoking were offered cerebral magnetic resonance angiography. A genome screen was completed using the Illumina 6K SNP system, and the resulting data from 192 families, containing 1155 genotyped individuals, were analyzed. Narrow and broad disease definitions were used when testing for linkage using multipoint model-independent methods. Ordered subset analysis was performed to test for a gene x smoking (pack-years) interaction.The greatest evidence of linkage was found on chromosomes 4 (LOD=2.5; 156 cM), 7 (LOD=1.7; 183 cM), 8 (LOD=1.9; 70 cM), and 12 (LOD=1.6; 102 cM) using the broad disease definition. Using the average pack-years for the affected individuals in each family, the genes on chromosomes 4 (LOD=3.5; P=0.03), 7 (LOD=4.1; P=0.01) and 12 (LOD=3.6; P=0.02) all appear to be modulated by the degree of smoking in the affected members of the family. On chromosome 8, inclusion of smoking as a covariate did not significantly strengthen the linkage evidence, suggesting no interaction between the loci in this region and smoking.We have detected possible evidence of linkage to 4 chromosomal regions. There is potential evidence for a gene x smoking interaction with 3 of the loci.

SUBMITTER: Foroud T

PROVIDER: S-EPMC2435164 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Genome screen to detect linkage to intracranial aneurysm susceptibility genes: the Familial Intracranial Aneurysm (FIA) study.

Foroud Tatiana T Sauerbeck Laura L Brown Robert R Anderson Craig C Woo Daniel D Kleindorfer Dawn D Flaherty Matthew L ML Deka Ranjan R Hornung Richard R Meissner Irene I Bailey-Wilson Joan E JE Rouleau Guy G Connolly E Sander ES Lai Dongbing D Koller Daniel L DL Huston John J Broderick Joseph P JP

Stroke 20080306 5

<h4>Background and purpose</h4>Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA.<h4>Methods</h4>Multiplex families having at least 2 individuals with "definite" or "probable" IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history ...[more]

PMID: 18323491

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Project description:<p>Our long-term objective is to identify susceptibility genes that are related to the formation of intracranial aneurysms (IA). Rupture of IAs occurs in 16,000 to 17,000 persons in the U.S. annually and nearly half of affected persons are dead within the first 30 days. An additional 6,000 to 7,000 persons with unruptured IAs are identified each year. Accumulated evidence indicates that a genetic component plays an important role in the development of IAs, but specific loci affecting the risk of IA have not been identified. The primary hypothesis of this study is that there are specific human chromosomal regions that are associated with an increased risk of IAs. Specific Aims of are: <ol> <li>Recruitment of 400 (475) families with multiple individuals who have an IA through 23 (25) referral centers throughout North America, Australia, and New Zealand that represent 35 (40) recruitment sites.</li> <li>Ascertainment of interviews and blood samples from all affected family members as well as their first-degree relatives. White blood cells from living persons with an IA will be cryopreserved at Coriell Institute for Medical Research for future immortalization of cells lines as indicated.</li> <li>Identification of unruptured IAs by obtaining MRAs in selected asymptomatic siblings (of affected individuals).</li> <li>Completion of a 10 cM genome series in persons with IAs as well as the spouses and children of persons with an IA who are deceased. We will perform finer mapping of chromosomal regions with suggestive evidence of linkage in the genome screen.</li> <li>Performance of a nonparametric (allele sharing) linkage analysis, including relevant environmental factors such as smoking, to identify chromosomal regions linked to IA. Reconstruction of the genotypes of deceased affected family members will be performed.</li> </ol> </p> <p>Identification of individuals who are genetically at high risk for the development of IAs would enable targeted and effective screening/prevention/treatment strategies to reduce the substantial mortality and morbidity associated with this devastating type of stroke. Only a multidisciplinary, collaborative effort to identify, accrue, and genotype FIA families will be successful in identifying sufficient high-risk families to characterize the genetic underpinnings of IA.</p>

Project description:BACKGROUND:Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods. METHODS:Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n?=?94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n?=?40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction. RESULTS:Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC)?=?0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance. CONCLUSIONS:We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

Dataset Information

Genome screen to detect linkage to intracranial aneurysm susceptibility genes: the Familial Intracranial Aneurysm (FIA) study.

Publications

Genome screen to detect linkage to intracranial aneurysm susceptibility genes: the Familial Intracranial Aneurysm (FIA) study.

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