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the Type 2 Diabetes Knowledge Portal as a paradigm
Facilitating complex disease research by providing organized, accessible genetic information and analysis tools: the Type 2 Diabetes Knowledge Portal as a paradigm Maria C. Costanzo, on behalf of the Accelerating Medicines Partnership in Type 2 Diabetes Medical and Population Genetics, Broad Institute of MIT and Harvard Biocuration 2017 March 29, 2017
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Diabetes: A global emergency
Type 2 diabetes (T2D) is indeed a global emergency, affecting around 10% of the world’s population. Its incidence is increasing and it costs billions in health care dollars as well as untold human misery, so it’s an important problem to address. Both genetic and environmental factors contribute to T2D risk, and our project looks at the genetic factors.
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Genetic association studies can identify genomic regions with a role in T2D risk
T2D cases The core data in the T2D Knowledge Portal comes from genetic association studies. Here’s a quick refresher on what that means. To do genetic association analysis, you start with a group of people and categorize them according to the presence or absence of a disease of interest. You can also measure quantitative traits, such as height. You also look at variation in their genomes. This is often done using genome-wide association studies (GWAS), which query specific sets of nucleotides in the genome that vary between people (single-nucleotide polymorphisms, or SNPs). Other techniques include exome sequencing and whole-genome sequencing. Finally, the presence of variants at certain positions is compared with the incidence of the disease of interest. In the example shown, the control group is equally likely to have a C or a T at this position in their genomes, while people with T2D are much more likely to have a C. This suggests that having a C is associated with a higher risk of developing T2D. It’s important to remember that the effect is likely not due to that particular C, but instead to something nearby that is genetically linked to it. These genetic association hits give us important clues for further fine-grained analysis to find out what is really contributing to T2D risk. controls
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Hundreds of genes may affect complex diseases
Type 2 diabetes odds ratio When we do genetic association analysis for T2D, we find a complicated landscape. In this figure, each column represents a gene, and the height of the column represents the magnitude of its effect on T2D risk. You can see that many genes have relatively small effects on T2D. Linkage Candidate Gene GWAS Targeted gene sequencing Whole genome sequencing Exome sequencing Genes implicated in T2D Figure courtesy of Miriam Udler
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Challenges in complex disease genetics
data are large and complicated! datasets are “siloed” at their consortia of origin data from different studies need to be aggregated and harmonized for greater statistical power because of privacy concerns, access to data must be carefully controlled In addition to the complicated genetic landscape, there are other challenges in studying the genetics of complex diseases.
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Accelerating Medicines Partnership (AMP) T2D
public-private partnership (government, industry, non- profit organizations, universities AMP T2D Mission: generate data for T2D and complications make T2D genetic information more broadly accessible, via the T2D Knowledge Portal accelerate the translation of genetic information into actionable clinical knowledge and discovery of new drug targets The Accelerating Medicines Partnership Type 2 Diabetes Project (AMP T2D), is a multi-sector, pre-competitive partnership among government, industry, and nonprofit organizations, the goal of which is to harness collective capabilities, scale and resources toward improving current efforts to develop new therapies for complex, heterogeneous diseases. The T2D Knowledge Portal is a freely-accessible web resource, and the software behind it is open-source. AMP T2D funders
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Data in the T2D Knowledge Portal
Current: 17,000 T2D Exomes from T2D-GENES, SIGMA, GoT2D Exome chip results for ~82,000 samples of European ancestry Whole genome sequencing results for ~3,000 from GoT2D GWAS data for 9,000 samples of Mexican and Latin American ancestry GWAS results from 12,171 cases and 56,862 controls (gender-stratified, MetaboChip, and fine mapping results) Meta-analysis results from GWAS Consortia: MAGIC, CARDIoGRAM, CKDGen, GIANT, GLGC, VATGen, PGC 1000 Genomes ExAC exome sequences GWAS for 3,700 samples from (CAMP) Cardiology and Metabolic Patient Cohort* GWAS for 9,200 individuals from BioMe Biobank, Mt. Sinai Medical Center Imminent: 70KforT2D mega-analysis of 70,000 GWAS samples GENESIS insulin sensitivity GWAS (~2,700 samples) 2,000 samples added to T2D exome sequence set MAGIC insulin secretion GWAS gnomAD exome and whole genome sequences The T2D Knowledge Portal aggregates a wide range of data, both publicly available and generated within the AMP T2D consortium.
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Entry points to the T2D Knowledge Portal
Browse by genomic location: gene, variant, or region Create a set of variants answering specific criteria Start with a phenotype and view its genetic associations across the genome The T2D Knowledge Portal home page offers three different entry points into the data.
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Two goals of the T2D Knowledge Portal:
present straightforward information about genetic associations that non-experts can understand give experts greater access to and ability to manipulate data, while still protecting privacy There isn’t time in this presentation to give a guided tour of the Portal, but I’d like to touch on our approach to two major goals of the Portal: providing clear summary information that is meaningful to researchers who are not experts in human genetics; and providing tools that give experts the ability to interact with and manipulate the data.
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Gene page summarizes aggregate associations with T2D and related traits
This is a mockup of the next version of our Gene page, which is currently being developed. The upper section gives an immediate indication of which phenotypes are strongly associated with variants in this gene. Lower sections allow the user to drill down to greater detail.
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odds ratio and direction of effect
Variant page summary Genetic associations dataset significance odds ratio and direction of effect sample size allele count Our current Variant page already provides a clear, immediate summary of the associations for a variant and their relative significance. allele frequency
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Interactive burden test
Run on-the-fly association analysis to calculate the aggregate association of a custom set of variants with a specific phenotype Phenotype filters allow you to run analysis using a specific subset of samples Our interactive burden test gives expert users the ability to select many parameters in order to design and run custom association analysis. Sets of variants with specific predicted effects on the encoded protein may be selected, or users may add and remove individual variants from the set. Samples may be filtered by phenotypic ranges as well as by ancestry and by case/control status. For example, an analysis could be designed to compare lean T2D cases to obese controls. Other parameters that may be customized include the dataset and covariates.
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HNF1A interactive burden test results
Default parameters: burden test shows no significant associations Custom set of functionally important variants reveals significant T2D association This is an example showing the utility of designing a custom association test. In the top panel, the burden test was run for the gene HNF1A, which encodes a transcription factor, using the default parameters and looking at all variants across the gene. It appears that there is no significant association with T2D. In the bottom panel, the test was run for a specific set of variants that were found by Najmi et al. (Diabetes Feb;66(2): PMID: ) to decrease or block HNF1A transcription factor activity. Using this set, a significant association with T2D is uncovered.
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LocusZoom interactive visualization
Another interactive tool that offers versatility for expert users is LocusZoom. Display variant associations for a range of phenotypes View variant linkage disequilibrium relationships; change LD reference Run custom association analysis while conditioning on specific variant(s)
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Variant Finder: build queries for sets of variants
Which variants are associated with altered levels of fasting glucose, cholesterol, and serum creatinine at genome-wide significance? Are there any variants that are associated with T2D at genome-wide significance, have a protective effect against T2D, and cause missense mutations? The Variant Finder allows users to build complex queries to find specific sets of variants of interest.
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Future directions more data more phenotypes: T2D complications
more distillation of information more tutorials, guides, and help documentation download capability sister portals – stroke and myocardial infarction genetics Future plans include the addition of more data, including transcription and epigenetic information, as well as more phenotypes, focusing on complications of T2D. We will continue to work towards better distillation of complex information and providing users with clear guidance. In the near future we plan to provide the capability to download summary statistics in bulk for some datasets. And, since the pipeline and framework behind the T2D Knowledge Portal are applicable to genetic data for other complex diseases, we are collaborating with other groups on the creation of portals for stroke and heart attack genetic associations.
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Visit us at www.type2diabetesgenetics.org
Principal investigator Jose Florez Senior group leader Jason Flannick Associate director, operations Noël Burtt Manager, content and community Maria Costanzo Software engineers Benjamin Alexander Marc Duby Clint Gilbert Todd Green Dong-Keun Jang Oliver Reubenacker David Siedzik Preeti Singh Kaan Yuksel Computational biologists Marcin von Grotthuss Ryan Koesterer Clinical phenotyping Miriam Udler Project manager Lizz Caulkins Please take a look at the T2D Knowledge Portal, follow us on Twitter and LinkedIn, and feel free to contact the team any time with questions or suggestions! @T2DKP Type 2 Diabetes Knowledge Portal
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