Establishing an adjusted p-value threshold to control the family-wide type 1 error in genome wide association studies

<p>Abstract</p> <p>Background</p> <p>By assaying hundreds of thousands of single nucleotide polymorphisms, genome wide association studies (GWAS) allow for a powerful, unbiased review of the entire genome to localize common genetic variants that influence health and disease. Although it is widely recognized that some correction for multiple testing is necessary, in order to control the family-wide Type 1 Error in genetic association studies, it is not clear which method to utilize. One simple approach is to perform a Bonferroni correction using all <it>n single nucleotide polymorphisms (</it>SNPs) across the genome; however this approach is highly conservative and would "overcorrect" for SNPs that are not truly independent. Many SNPs fall within regions of strong linkage disequilibrium (LD) ("blocks") and should not be considered "independent".</p> <p>Results</p> <p>We proposed to approximate the number of "independent" SNPs by counting 1 SNP per LD block, plus all SNPs outside of blocks (interblock SNPs). We examined the <it>effective </it>number of independent SNPs for Genome Wide Association Study (GWAS) panels. In the CEPH Utah (CEU) population, by considering the interdependence of SNPs, we could reduce the total number of effective tests within the Affymetrix and Illumina SNP panels from 500,000 and 317,000 to 67,000 and 82,000 "independent" SNPs, respectively. For the Affymetrix 500 K and Illumina 317 K GWAS SNP panels we recommend using 10^-5, 10^-7and 10^-8and for the Phase II HapMap CEPH Utah and Yoruba populations we recommend using 10^-6, 10^-7and 10^-9as "suggestive", "significant" and "highly significant" p-value thresholds to properly control the family-wide Type 1 error.</p> <p>Conclusion</p> <p>By approximating the effective number of independent SNPs across the genome we are able to 'correct' for a more accurate number of tests and therefore develop 'LD adjusted' Bonferroni corrected p-value thresholds that account for the interdepdendence of SNPs on well-utilized commercially available SNP "chips". These thresholds will serve as guides to researchers trying to decide which regions of the genome should be studied further.</p

Best practices for bioinformatic characterization of neoantigens for clinical utility

Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor-normal sequencing data, and then ranked according to their predicted capability in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types

GeneLink: a database to facilitate genetic studies of complex traits

BACKGROUND: In contrast to gene-mapping studies of simple Mendelian disorders, genetic analyses of complex traits are far more challenging, and high quality data management systems are often critical to the success of these projects. To minimize the difficulties inherent in complex trait studies, we have developed GeneLink, a Web-accessible, password-protected Sybase database. RESULTS: GeneLink is a powerful tool for complex trait mapping, enabling genotypic data to be easily merged with pedigree and extensive phenotypic data. Specifically designed to facilitate large-scale (multi-center) genetic linkage or association studies, GeneLink securely and efficiently handles large amounts of data and provides additional features to facilitate data analysis by existing software packages and quality control. These include the ability to download chromosome-specific data files containing marker data in map order in various formats appropriate for downstream analyses (e.g., GAS and LINKAGE). Furthermore, an unlimited number of phenotypes (either qualitative or quantitative) can be stored and analyzed. Finally, GeneLink generates several quality assurance reports, including genotyping success rates of specified DNA samples or success and heterozygosity rates for specified markers. CONCLUSIONS: GeneLink has already proven an invaluable tool for complex trait mapping studies and is discussed primarily in the context of our large, multi-center study of hereditary prostate cancer (HPC). GeneLink is freely available at

IL-6 selectively suppresses cDC1 specification via C/EBPβ

Cytokines produced in association with tumors can impair antitumor immune responses by reducing the abundance of type 1 conventional dendritic cells (cDC1), but the mechanism remains unclear. Here, we show that tumor-derived IL-6 generally reduces cDC development but selectively impairs cDC1 development in both murine and human systems through the induction of C/EBPβ in the common dendritic cell progenitor (CDP). C/EBPβ and NFIL3 compete for binding to sites in the Zeb2 -165 kb enhancer and support or repress Zeb2 expression, respectively. At homeostasis, pre-cDC1 specification occurs upon Nfil3 induction and consequent Zeb2 suppression. However, IL-6 strongly induces C/EBPβ expression in CDPs. Importantly, the ability of IL-6 to impair cDC development is dependent on the presence of C/EBPβ binding sites in the Zeb2 -165 kb enhancer, as this effect is lost in Δ1+2+3 mutant mice in which these binding sites are mutated. These results explain how tumor-associated IL-6 suppresses cDC1 development and suggest therapeutic approaches preventing abnormal C/EBPβ induction in CDPs may help reestablish cDC1 development to enhance antitumor immunity

Transcription factor C/EBPα is required for the development of Ly6Chi monocytes but not Ly6Clo monocytes

Monocytes comprise two major subsets, Ly6

Cancer-associated mutations reveal a novel role for EpCAM as an inhibitor of cathepsin-L and tumor cell invasion

BACKGROUND: EpCAM (Epithelial cell adhesion molecule) is often dysregulated in epithelial cancers. Prior studies implicate EpCAM in the regulation of oncogenic signaling pathways and epithelial-to-mesenchymal transition. It was recently demonstrated that EpCAM contains a thyroglobulin type-1 (TY-1) domain. Multiple proteins with TY-1 domains are known to inhibit cathepsin-L (CTSL), a cysteine protease that promotes tumor cell invasion and metastasis. Analysis of human cancer sequencing studies reveals that somatic EpCAM mutations are present in up to 5.1% of tested tumors. METHODS: The Catalogue of Somatic Mutations in Cancer (COSMIC) database was queried to tabulate the position and amino acid changes of cancer associated EpCAM mutations. To determine how EpCAM mutations affect cancer biology we studied C66Y, a damaging TY-1 domain mutation identified in liver cancer, as well as 13 other cancer-associated EpCAM mutations. In vitro and in vivo models were used to determine the effect of wild type (WT) and mutant EpCAM on CTSL activity and invasion. Immunoprecipitation and localization studies tested EpCAM and CTSL protein binding and determined compartmental expression patterns of EpCAM mutants. RESULTS: We demonstrate that WT EpCAM, but not C66Y EpCAM, inhibits CTSL activity in vitro, and the TY-1 domain of EpCAM is responsible for this inhibition. WT EpCAM, but not C66Y EpCAM, inhibits tumor cell invasion in vitro and lung metastases in vivo. In an extended panel of human cancer cell lines, EpCAM expression is inversely correlated with CTSL activity. Previous studies have demonstrated that EpCAM germline mutations can prevent EpCAM from being expressed at the cell surface. We demonstrate that C66Y and multiple other EpCAM cancer-associated mutations prevent surface expression of EpCAM. Cancer-associated mutations that prevent EpCAM cell surface expression abrogate the ability of EpCAM to inhibit CTSL activity and tumor cell invasion. CONCLUSIONS: These studies reveal a novel role for EpCAM as a CTSL inhibitor, confirm the functional relevance of multiple cancer-associated EpCAM mutations, and suggest a therapeutic vulnerability in cancers harboring EpCAM mutations

Reconciling differences in natural tags to infer demographic and genetic connectivity in marine fish populations

Processes regulating population connectivity are complex, ranging from extrinsic environmental factors to intrinsic individual based features, and are a major force shaping the persistence of fish species and population responses to harvesting and environmental change. Here we developed an integrated assessment of demographic and genetic connectivity of European flounder Platichthys flesus in the northeast Atlantic (from the Norwegian to the Portuguese coast) and Baltic Sea. Specifically, we used a Bayesian infinite mixture model to infer the most likely number of natal sources of individuals based on otolith near core chemical composition. Simultaneously, we characterised genetic connectivity via microsatellite DNA markers, and evaluated how the combined use of natural tags informed individual movement and long-term population exchange rates. Individual markers provided different insights on movement, with otolith chemistry delineating Norwegian and Baltic Sea sources, whilst genetic markers showed a latitudinal pattern which distinguished southern peripheral populations along the Iberian coast. Overall, the integrated use of natural tags resulted in outcomes that were not readily anticipated by individual movement or gene flow markers alone. Our ecological and evolutionary approach provided a synergistic view on connectivity, which will be paramount to align biological and management units and safeguard species’ biocomplexityFundação para a Ciência e a Tecnologia | Ref. UID/MAR/04292/2013Fundação para a Ciência e a Tecnologia | Ref. PTDC/AAG-GLO/5849/2014Fundação para a Ciência e a Tecnologia | Ref. PTDC/MAR-EST/2098/201

Consequences of “natural” disasters on aquatic life and habitats

“Natural” disasters (also known as geophysical disasters) involve physical processes that have a direct or indirect impact on humans. These events occur rapidly and may have severe consequences for resident flora and fauna as their habitat undergoes dramatic and sudden change. Although most studies have focused on the impact of natural disasters on humans and terrestrial systems, geophysical disasters can also impact aquatic ecosystems. Here, we provide a synthesis on the effects of the most common and destructive geophysical disasters on aquatic systems (life and habitat). Our approach spanned realms (i.e., freshwater, estuarine, and marine) and taxa (i.e., plants, vertebrates, invertebrates, and microbes) and included floods, droughts, wildfires, hurricanes/cyclones/typhoons, tornadoes, dust storms, ice storms, avalanches (snow), landslides, volcanic eruptions, earthquakes (including limnic eruptions), tsunamis, and cosmic events. Many geophysical disasters have dramatic effects on aquatic systems. The evidence base is somewhat limited for some natural disasters because transient events (e.g., tornadoes and floods) are difficult to study. Most natural disaster studies focus on geology/geomorphology and hazard assessment for humans and infrastructure. However, the destruction of aquatic systems can impact humans indirectly through loss of food security, cultural services, or livelihoods. Many geophysical disasters interact in complex ways (e.g., wildfires often lead to landslides and flooding) and can be magnified or otherwise mediated by human activities. Our synthesis reveals that geophysical events influence aquatic ecosystems, often in negative ways, yet systems can be resilient provided that effects are not compounded by anthropogenic stressors. It is difficult to predict or prevent geophysical disasters but understanding how aquatic ecosystems are influenced by geophysical events is important given the inherent connection between peoples and aquatic ecosystems.acceptedVersio