Article

A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

1Department of Epidemiology and Biostatistics, Case Western Reserve University.
Cancer Epidemiology Biomarkers & Prevention (Impact Factor: 4.32). 09/2012; 21(12). DOI: 10.1158/1055-9965.EPI-12-0703
Source: PubMed

ABSTRACT BACKGROUND: We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma. METHODS: First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis. RESULTS: Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. (1) who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum LOD. Conclusions/Impact: Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.

2 Followers
 · 
143 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Objective: To explore the clinical manifestations and imaging characteristics of gliomatosis cerebri to raise the awareness and improve its diagnostic accuracy for patients. Materials and Methods: Clinical data, imaging characteristics and pathological examination of 12 patients with GC from Jan., 2008 to Jan., 2012 were analyzed retrospectively. Results: Patients with GC were clinically manifested with headache, vomiting, repeated seizures, fatigue and unstable walking, most of whom had more than 2 lesions involving in parietal lobe, followed by temporal lobe, frontal lobe, periventricular white matter and corpus callosum. Magnetic resonance imaging (MRI) showed diffuse distribution, T1-weighted images (T1WI) with equal and low signals and T2-weighted images (T2WI) with bilateral symmetrical high diffuse signals. There was no reinforcement by enhancement scanning and signals were different in diffusion-weighted images (DWI). The higher the tumor staging, the stronger the signals. Pathological examination showed neuroastrocytoma in which tumor tissues were manifested by infiltrative growth in blood vessels and around neurons. Conclusions: In clinical diagnosis of GC, much attention should be paid to the diffuse distribution of imaging characteristics, incomplete matching between clinical and imaging characteristics and confirmation by combining with histopathological examination.
    Asian Pacific journal of cancer prevention: APJCP 06/2014; 15(11):4487-91. DOI:10.7314/APJCP.2014.15.11.4487 · 1.50 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Gliomas are the most common primary intracranial tumor, representing 81% of malignant brain tumors. Although relatively rare, they cause significant mortality and morbidity. Glioblastoma, the most common glioma histology (∼45% of all gliomas), has a 5-year relative survival of ∼5%. A small portion of these tumors are caused by Mendelian disorders, including neurofibromatosis, tuberous sclerosis, and Li-Fraumeni syndrome. Genomic analyses of glioma have also produced new evidence about risk and prognosis. Recently discovered biomarkers that indicate improved survival include O(6)-methylguanine-DNA methyltransferase methylation, isocitrate dehydrogenase mutation, and a glioma cytosine-phosphate-guanine island methylator phenotype. Genome-wide association studies have identified heritable risk alleles within 7 genes that are associated with increased risk of glioma. Many risk factors have been examined as potential contributors to glioma risk. Most significantly, these include an increase in risk by exposure to ionizing radiation and a decrease in risk by history of allergies or atopic disease(s). The potential influence of occupational exposures and cellular phones has also been examined, with inconclusive results. We provide a "state of the science" review of current research into causes and risk factors for gliomas in adults.
    Neuro-Oncology 05/2014; DOI:10.1093/neuonc/nou087 · 5.29 Impact Factor

Full-text

Download
46 Downloads
Available from
May 17, 2014