Genetic evaluation and application of posterior cranial fossa traits as endophenotypes for Chiari type I malformation

Chiari Type I Malformation (CMI) is characterized by herniation of the cerebellar tonsils through the base of the skull. Although cerebellar tonsillar herniation (CTH) is hypothesized to result from an underdeveloped posterior cranial fossa (PF), patients are frequently diagnosed by the extent of CTH without cranial morphometric assessment. We recently completed the largest CMI whole genome qualitative linkage screen to date. Despite an initial lack of statistical evidence, stratified analyses using clinical criteria to reduce heterogeneity resulted in a striking increase in evidence for linkage. The present study focused on the use of cranial base morphometrics to further dissect this heterogeneity and increase power to identify disease genes. We characterized the genetic contribution for a series of PF traits and evaluated the use of heritable, disease-relevant PF traits in ordered subset analysis (OSA). Consistent with a genetic hypothesis for CMI, much of the PF morphology was found to be heritable and multiple genomic regions were strongly implicated from OSA, including regions on Chromosomes 1 (LOD = 3.07, p = 3 × 10(-3) ) and 22 (LOD = 3.45, p = 6 × 10(-5) ) containing several candidates warranting further investigation. This study underscores the genetic heterogeneity of CMI and the utility of PF traits in CMI genetic studies.

Ordered subset analysis identifies loci influencing lung cancer risk on chromosomes 6q and 12q

BACKGROUND

Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity.

METHODS

We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage.

RESULTS

A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23-25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31-q33, 14q11, and 16q24.

CONCLUSIONS

Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers.

IMPACT

OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci.

Taiwan Schizophrenia Linkage Study: lessons learned from endophenotype-based genome-wide linkage scans and perspective

Taiwan Schizophrenia Linkage Study (TSLS) was initiated with a linkage strategy for locating multiple genes, each of small to moderate effect, and aimed to recruit a large enough sample of pairs of affected siblings and their families ascertained from a multisite study. With a sample of 607 families successfully recruited, a total of 2,242 individuals (1,207 affected and 1,035 unaffected) from 557 families were genotyped using 386 microsatellite markers spaced at an average of 9-cM intervals. Here the author reviews the establishment of TSLS and initial signal derived from linkage scan using the diagnosis of schizophrenia. Based on the limited success of the initial linkage analysis, a sufficient-component causal model is proposed to incorporate endophenotypes and genes for schizophrenia. Four types of candidate endophenotype measured in TSLS, including schizotypal personality, Continuous Performance Test, Wisconsin Card Sorting Test, and niacin skin flush test, are briefly described. The author discusses different strategies of linkage analysis incorporating these endophenotypes, including quantitative trait loci (QTL) linkage analysis, clustering-derived subgroups, ordered subset analysis (OSA), and latent classes for linkage scan. Then the author summarizes the linkage signals generated from seven studies of endophenotype-based linkage analysis using TSLS, including QTL scan of neurocognitive performance, QTL scan of niacin skin flush, the family cluster of attention deficit and execution deficit, OSA by schizophrenia-schizotypy factors, nested OSA by age at onset and neurocognitive performance, and the latent class of deficit schizophrenia for linkage analysis. The perspective of combining next-generation sequencing with linkage analysis of families is also discussed.

Increased efficiency of case-control association analysis by using allele-sharing and covariate information

OBJECTIVE

We compared the efficiency of case selection strategies for following up a genome-wide linkage screen of multiplex families. We simulated datasets under three models by which continuous environmental or clinical covariates may contribute to disease risk or linkage heterogeneity: (i) a quantitative trait locus (QTL) underlying a continuous disease risk factor, (ii) a gene-environment interaction model, (iii) a heterogeneity model defined by distinct covariate distributions in linked and unlinked families.

METHODS

Marker genotypes and covariate values were generated for affected sibling pair (ASP) families, according to the three models above. We evaluated two case selection strategies relative to a reference design, which compared all family probands to a sample of unrelated controls ('all'). The first strategy ignored covariates and selected probands from families with NPL scores > or =0 ('linked best'). The second strategy selected probands from families identified by an ordered subset analysis (OSA), which utilizes family-specific linkage and covariate information.

RESULTS

The 'linked best' design provided power very similar to the 'all' design under all three models. Under some QTL and heterogeneity models, the OSA design was both most powerful and most efficient.

CONCLUSIONS

Incorporating allele sharing and covariate information from ASP families into a case-control study design can increase power and reduce genotyping cost.