Meta-Analysis of Genome-Wide Linkage Studies in Celiac Disease.

OBJECTIVE: A meta-analysis of genome-wide linkage studies allows us to summarize the extensive information available from family-based studies, as the field moves into genome-wide association studies. METHODS: Here we apply the genome scan meta-analysis (GSMA) method, a rank-based, model-free approach, to combine results across eight independent genome-wide linkages performed on celiac disease (CD), including 554 families with over 1,500 affected individuals. We also investigate the agreement between signals we identified from this meta-analysis of linkage studies and those identified from genome-wide association analysis using a hypergeometric distribution. RESULTS: Not surprisingly, the most significant result was obtained in the HLA region. Outside the HLA region, suggestive evidence for linkage was obtained at the telomeric region of chromosome 10 (10q26.12-qter; p = 0.00366), and on chromosome 8 (8q22.2-q24.21; p = 0.00491). Testing signals of association and linkage within bins showed no significant evidence for co-localization of results. CONCLUSION: This meta-analysis allowed us to pool the results from available genome-wide linkage studies and to identify novel regions potentially harboring predisposing genetic variation contributing to CD. This study also shows that linkage and association studies may identify different types of disease-predisposing variants

Publisher Correction: Cancer genetics, precision prevention and a call to action.

In the version of this article originally published, there was an error in the second-to-last sentence of the abstract. In this sentence, the final phrase "to identify carriers of first-wave gene mutation carriers" should have instead read "to identify carriers of first-wave gene mutation." The error has been corrected in the HTML and PDF versions of the paper

Genome-Wide Association Studies in Glioma.

Since the first reports in 2009, genome-wide association studies (GWAS) have been successful in identifying germline variants associated with glioma susceptibility. In this review, we describe a chronological history of glioma GWAS, culminating in the most recent study comprising 12,496 cases and 18,190 controls. We additionally summarize associations at the 27 glioma-risk SNPs that have been reported so far. Future efforts are likely to be principally focused on assessing association of germline-risk SNPs with particular molecular subgroups of glioma, as well as investigating the functional basis of the risk loci in tumor formation. These ongoing studies will be important to maximize the impact of research into glioma susceptibility, both in terms of insight into tumor etiology as well as opportunities for clinical translation. Cancer Epidemiol Biomarkers Prev; 27(4); 418-28. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer.

Capture Hi-C Library Generation and Analysis to Detect Chromatin Interactions.

Chromosome conformation capture (3C), coupled with next-generation sequencing (Hi-C), provides a means for deciphering not only the principles underlying genome folding and architecture, but more broadly, the role 3D chromatin structure plays in gene regulation and the replication and repair of DNA. The recently implemented modification, in situ Hi-C, maintains nuclear integrity during digestion and ligation steps, reducing random ligation of Hi-C fragments. Although Hi-C allows for genome-wide characterization of chromatin contacts, it requires high-depth sequencing to discover significant contacts. To address this, Capture Hi-C (CHi-C) enriches standard Hi-C libraries for regions of biological interest, for example by specifically targeting gene promoters, aiding identification of biologically significant chromatin interactions compared to conventional Hi-C, for an equivalent number of sequence reads. Illustrating the application of CHi-C applied to genome-wide analysis of chromatin interactions with promoters, we detail the protocols for in situ Hi-C and CHi-C library generation for sequencing, as well as the bioinformatics tools for data analysis. © 2018 by John Wiley & Sons, Inc

Realistic expectations are key to realising the benefits of polygenic scores.

We must not let enthusiasm around polygenic scores allow us to forget other factors that are bigger, more modifiable, and relevant for everyone, argue Amit Sud, Rachel Horton, and colleague

Realistic expectations are key to realising the benefits of polygenic scores

We must not let enthusiasm around polygenic scores allow us to forget other factors that are bigger, more modifiable, and relevant for everyone, argue Amit Sud, Rachel Horton, and colleague

Genome-wide homozygosity signature and risk of Hodgkin lymphoma.

Recent studies have reported that regions of homozygosity (ROH) in the genome are detectable in outbred populations and can be associated with an increased risk of malignancy. To examine whether homozygosity is associated with an increased risk of developing Hodgkin lymphoma (HL) we analysed 589 HL cases and 5,199 controls genotyped for 484,072 tag single nucleotide polymorphisms (SNPs). Across the genome the cumulative distribution of ROH was not significantly different between cases and controls. Seven ROH at 4q22.3, 4q32.2, 7p12.3-14.1, 7p22.2, 10p11.22-23, 19q13.12-2 and 19p13.2 were associated with HL risk at P < 0.01. Intriguingly 4q22.3 harbours an ROH to which the nuclear factor NF-kappa-B p105 subunit (NFKB1) maps (P = 0.002). The ROH at 19q13.12-2 has previously been implicated in B-cell precursor acute lymphoblastic leukaemia. Aside from these observations which require validation, it is unlikely that levels of measured homozygosity caused by autozygosity, uniparental isodisomy or hemizygosity play a major role in defining HL risk in predominantly outbred populations

CanVar: A resource for sharing germline variation in cancer patients.

The advent of high-throughput sequencing has accelerated our ability to discover genes predisposing to disease and is transforming clinical genomic sequencing. In both contexts knowledge of the spectrum and frequency of genetic variation in the general population and in disease cohorts is vital to the interpretation of sequencing data. While population level data is becoming increasingly available from publicly accessible sources, as exemplified by The Exome Aggregation Consortium (ExAC), the availability of large-scale disease-specific frequency information is limited. These data are of particular importance to contextualise findings from clinical mutation screens and small gene discovery projects. This is especially true for cancer, which is typified by a number of hereditary predisposition syndromes.  Although mutation frequencies in tumours are available from resources such as Cosmic and The Cancer Genome Atlas, a similar facility for germline variation is lacking. Here we present the Cancer Variation Resource (CanVar) an online database which has been developed using the ExAC framework to provide open access to germline variant frequency data from the sequenced exomes of cancer patients. In its first release, CanVar catalogues the exomes of 1,006 familial early-onset colorectal cancer (CRC) patients sequenced at The Institute of Cancer Research. It is anticipated that CanVar will host data for additional cancers, providing a resource for others studying cancer predisposition and an example of how the research community can utilise the ExAC framework to share sequencing data

Undefined familial colorectal cancer and the role of pleiotropism in cancer susceptibility genes.

Although family history is a major risk factor for colorectal cancer (CRC) a genetic diagnosis cannot be obtained in over 50 % of familial cases when screened for known CRC cancer susceptibility genes. The genetics of undefined-familial CRC is complex and recent studies have implied additional clinically actionable mutations for CRC in susceptibility genes for other cancers. To clarify the contribution of non-CRC susceptibility genes to undefined-familial CRC we conducted a mutational screen of 114 cancer susceptibility genes in 847 patients with early-onset undefined-familial CRC and 1609 controls by analysing high-coverage exome sequencing data. We implemented American College of Medical Genetics and Genomics standards and guidelines for assigning pathogenicity to variants. Globally across all 114 cancer susceptibility genes no statistically significant enrichment of likely pathogenic variants was shown (6.7 % cases 57/847, 5.3 % controls 85/1609; P = 0.15). Moreover there was no significant enrichment of mutations in genes such as TP53 or BRCA2 which have been proposed for clinical testing in CRC. In conclusion, while we identified genes that may be considered interesting candidates as determinants of CRC risk warranting further research, there is currently scant evidence to support a role for genes other than those responsible for established CRC syndromes in the clinical management of familial CRC