Friday, February 15, 2019

New AMP T2D funding opportunities

The Foundation for the National Institutes of Health is announcing two new Requests for Proposals (RFPs) to augment and expand the Type 2 Diabetes Knowledge Portal.

RFP 8b, "Evidence-based target lists: portal visualization and multi-algorithm development", has these objectives:
1. Develop algorithms including genetic (noncoding and coding), epigenetic, and genomic data to prioritize and rank evidence for causal genes conferring T2D or other complications.
2. In collaboration with the Knowledge Portal (KP team) at the Broad Institute, build tools for the KP to visualize these data.
3. Build processes to regularly update (i.e. every quarter) highly ranked causal genes with underlying algorithm annotations.
4. Compare and validate algorithms to advance AMP-T2D KP analytic tools and data visualizations.

The objective of RFP 10, "Deposition of Available Diabetes Complications Data", is to deposit, harmonize and publicly display GWAS, exome, and whole genome data within the KP for any of the following traits:
• Chronic Kidney Disease and/or Diabetic Kidney Disease related traits
• NASH and liver disease related traits
• Cardiovascular and lipid related traits, including heart failure
• Obesity related traits
• Diabetic retinopathy
• Other complications

Proposals are due on March 15, 2019. Find full details and contact information here.

Friday, December 21, 2018

Last 2018 T2DKP release, dedicated to Todd Green

Todd Green
Today's release in the Type 2 Diabetes Knowledge Portal of multiple new datasets, including associations for 17 new phenotypes, is dedicated to the memory of Todd Green, a Portal team member who passed away unexpectedly on November 19. Todd was an integral part of the Portal project since its inception several years ago, and had worked at the Broad Institute for many years previously. His expertise in applying statistical methods to GWAS and sequencing studies earned him co-authorship on more than 50 papers on the genetics of complex traits, focusing on inflammatory bowel disease and type 2 diabetes. The Portal team will miss him greatly, and we will carry on his spirit in the work that we do.

This release adds to the T2DKP nine new datasets:
  • ADIPOGen GWAS, a study by Dastani et al. and the ADIPOGen Consortium, is a multi-ethnic meta-analysis of adiponectin associations in nearly 46,000 subjects. Levels of the hormone adiponectin are inversely associated with type 2 diabetes and other metabolic traits. 
  • Leptin GWAS, published by Kilpeläinen et al., is a meta-analysis of 23 association studies, with over 32,000 subjects, for unadjusted and BMI-adjusted circulating levels of leptin. Levels of leptin, a hormone secreted by adipocytes, correlate with adiposity measures such as body fat mass and body fat index. 
  • Four MAGIC HbA1c GWAS ancestry-specific datasets. This study from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), published by Wheeler et al., is a meta-analysis of HbA1c levels. The results in the T2DKP comprise separate datasets for four ancestries: African American (~7,600 subjects), East Asian (~21,000 subjects), European (~124,000 subjects), and South Asian (~9,000 subjects). 
  • CHARGE Fatty Acid GWAS, published in two papers (Guan et al. and Wu et al.) from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, includes associations with plasma levels of nine different fatty acids and phospholipids in nearly 9,000 individuals of European ancestry. 
  • Global Urate Genetics Consortium GWAS, published by Köttgen et al., is a meta-analysis of variant associations with levels of serum urate across more than 100,000 European-ancestry individuals. Although levels of serum urate are not on their own considered to be associated with T2D risk, a recent clustering analysis (Udler et al.) found that loci associated with decreased serum urate concentrations cluster with loci associated with liver function and lipid metabolism, potentially identifying biochemical pathways involved in a sub-type of type 2 diabetes.
  • JDRF Diabetic Nephropathy Collaborative Research Initiative GWAS (Salem et al.) represents pre-publication sharing of results from a genome-wide association study across nearly 19,500 individuals with type 1 diabetes who were assessed for a wide range of phenotypes related to kidney function and kidney disease. Results for associations with ten different phenotypes (both unadjusted, and adjusted for HbA1c and BMI) are integrated into the T2DKP.

Summary statistics for all of the datasets listed above except for the unpublished JDRF DNCRI dataset are available for public download. In addition, researchers in the Slim Initiative in Genomic Medicine for the Americas (SIGMA) Consortium have made three sets of summary statistics available for download: GWAS SIGMA, SIGMA exome chip analysis, and the exome sequences from the SIGMA cohorts that are included in the 19k exome chip analysis dataset. Find details and the download links here.

This release also includes a new feature: a column showing the gene in which a variant resides is now included by default in the table of High-impact variants on the Gene page.

The High-impact variants table on the CDC123 gene page

This table is meant to highlight variants that impact the coding sequence of a gene and thus may exert their effects on disease risk through that gene product. However, since the Gene page integrates information about variants across the region of a gene, including 100kb of up- and downstream sequences, the variants shown in this table may be located in the coding sequences of nearby genes rather than in the gene that is the focus of the Gene page. In the example shown above, from the CDC123 gene page, only one of the variants in the table affects the CDC123 coding sequence; the inclusion of the Gene column makes this immediately clear.

As 2018 draws to a close, we on the T2DKP team extend our best wishes to T2DKP visitors for health, happiness, and good research results. We look forward to hearing from you in the New Year!

Wednesday, November 7, 2018

Meet the Knowledge Portal team at AHA

This weekend, cardiovascular researchers from around the globe will be meeting in Chicago for the 2018 Scientific Sessions of the American Heart Association. Members of the Knowledge Portal Network team will be there to meet and talk with geneticists and biologists who use the Portals and get your input on how we can improve them.

Please come visit us at booth #2249 in the Exhibit Hall! We'll be there on Saturday, Nov. 10 from 11am-5pm; on Sunday, Nov. 11 from 10am-4:30pm; and on Monday, Nov. 12 from 10am-3pm.

Tuesday, October 23, 2018

New features and a new Portal released at ASHG

The Knowledge Portal team is back at work after a fantastic week at the American Society of Human Genetics meeting. We had many great conversations with researchers at our exhibit booth and at the Broad Institute exhibit booth, where we had a couple of guest spots. This year, we also held a workshop session on the Knowledge Portal Network and the Diabetes Epigenome Atlas (DGA), and about 80 people came to learn the basics of navigating the Knowledge Portals and the DGA. We were asked to provide the slides from that session, and they can be viewed here, but please note that they may not be easy to interpret without the accompanying oral presentation. We are working on creating both instructional webinars and short videos explaining different aspects of the Portals; stay tuned! And in the meantime, please contact us with any questions--we're here to help.

Part of the Knowledge Portal Network team at our ASHG booth

As usual, we released a number of new features on the Type 2 Diabetes Knowledge Portal in time for the ASHG meeting:

Calculated credible sets

Credible sets are useful because they assign to individual variants in a locus a probability of being causal for a phenotype. On Gene Pages (see an example), when viewing the type 2 diabetes phenotype, the Credible sets tab displays credible sets generated and published by Mahajan et al. (2018). However, credible sets have not been generated by researchers for phenotypes in the T2DKP other than T2D.

Now, the T2DKP provides calculated credible sets for all phenotypes. When viewing a phenotype other than T2D on the Gene page, the Credible sets tab is replaced by a Calculated credible set tab. This LocusZoom module, developed by our AMP T2D partners at the University of Michigan, automatically calculates posterior probabilities from p-values. Calculated credible sets include up to 10 variants; the credible interval covered by the set may vary, depending on the strength of associations across the region.

UK Biobank PheWAS

Recently, we added to the T2DKP another LocusZoom module for displaying phenome-wide associations. The PheWAS display, showing associations for a variant across all of the phenotypes included in the T2DKP, is the default visualization in the "Associations at a glance" section of Variant pages (see an example). Now, by checking the "Use UKBB data" box, you can view associations for a variant across about 1,400 UK Biobank phenotypes from an analysis performed by our AMP T2D partners at the University of Michigan.

New LocusZoom visualization shows variant associations across UK Biobank phenotypes

Forest plot visualization of variant associations

We also provide yet another LocusZoom visualization on a separate tab of the "Associations at a glance" section of the Variant page. The Forest plot is an alternative way to visualize phenotypic associations for a variant. In addition to displaying the significance of associations, the Forest plot also shows the direction of effect and the confidence interval for variant associations.

Forest plot on the Variant page

Genetic Risk Score module

The T2DKP now includes an initial version of the Genetic Risk Score module.  This is an instantiation of the same custom burden test that is found on Gene pages, but instead of using as input a set of variants across a gene, the module uses a set of 243 variants identified by Mahajan et al. (2018) that are significantly associated with T2D risk. The module draws on 9 different datasets, including 3 housed at the Broad Data Coordinating Center and 6 housed at the T2DKP Federated node at EBI. Just like the burden test, it allows you to choose a phenotype for analysis, adjust the set of variants if desired, filter the sample set by many criteria, and set custom covariates before running the analysis. The results obtained from this module can potentially reveal genetic relationships between phenotypes. The module is still under development, and we would appreciate your feedback on it!

New Knowledge Portal added to the network

At the ASHG meeting we unveiled the newest member of the Knowledge Portal Network: the Sleep Disorder Knowledge Portal (SDKP),  for the genetics of sleep and circadian traits. There is currently one dataset for sleep genetic associations in the SDKP, "UK Biobank Sleep Traits GWAS," which includes chronotype, sleep duration, insomnia, daytime sleepiness, and nap traits. Additional association datasets are available for type 2 diabetes and glycemic traits, anthropometric traits, measures of kidney function, and psychiatric traits, and more sleep data will be added soon.

Monday, October 15, 2018

Connect with the Knowledge Portal Network team at ASHG!

This week, the human genetics research community will come together in San Diego for one of the most important conferences of the year: the annual American Society of Human Genetics meeting. The Knowledge Portal Network team will be there, and in addition to presenting all the new data and features in the Type 2 DiabetesCerebrovascular Disease, and Cardiovascular Disease Knowledge Portals (KPs), we're launching an entirely new Portal: the Sleep Disorder Knowledge Portal, for the genetics of sleep and circadian traits.

We'll also present an interactive workshop on Friday that will go over the basics of navigating the Knowledge Portal Network. Download the flyer here, and find more details below.

Here's the schedule of events for the week:

Tuesday, October 16
2:05-2:30 pm: Jason Flannick will present a talk, "Infrastructure for analyzing and disseminating large-scale genetic data for type 2 diabetes and other complex diseases," in the ASHG/IGES/ISCB Joint Symposium.
Room 6C - Upper Level/San Diego Convention Center

Wednesday, October 17
The Knowledge Portal team will be at our booth, #219, in the exhibit hall from 10am-4:30pm.
We'll also be at the Broad Institute Genomic Services booth, #1634, from 10:30-11:30am.
At 2:30pm, Richa Saxena, the P.I. for the Sleep Disorder Knowledge Portal, will be at our booth to talk about the SDKP.

Thursday, October 18
The team will again be at our booth, #219, in the exhibit hall from 10am-4:30pm.

Friday, October 19
We'll again be at our booth, #219, in the exhibit hall from 10am- 4:30pm, but today the booth will be closed around lunchtime so that we can present a special tutorial session on the Knowledge Portals. See details and sign up below. After the session, we'll be back at our booth until 4:30pm and will also be at the Broad Institute Genomic Services booth, #1634, from 2:30 - 3:30pm.

At lunchtime on Friday, grab your laptop and come to a workshop on the Knowledge Portals:

Navigating complex disease genetics: using the Knowledge Portal Network to move from SNPs to functional insights
Room 28C, Upper Level, San Diego Convention Center

We'll go over some basics, illustrate workflows, and answer questions about how you can use KPs to investigate SNPs, genes, or regions of interest and turn genetic data into insights about complex diseases.

Please sign up so we can plan for refreshments. We'll send you a reminder a few days beforehand. We look forward to seeing you there! Please contact us with any questions or suggestions for topics you'd like to discuss.

Monday, October 8, 2018

DIAMANTE GWAS dataset adds close to a million samples along with fine-mapping to the T2DKP

In a groundbreaking paper published today, Anubha Mahajan and colleagues (Mahajan et al., Nature Genetics 2018) report on a meta-analysis of unprecedented size for genetic associations with type 2 diabetes (T2D) along with fine-mapping analyses to identify causal variants that can suggest new therapeutic targets. We are pleased to provide access to the summary results as well as the results of the fine-mapping today in the T2D Knowledge Portal (T2DKP).

Working as part of the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) and DIAMANTE (DIAbetes Meta-ANalysis of Trans-Ethnic association studies) consortia, the researchers aggregated and meta-analyzed genome-wide association studies for about 900,000 individuals of European ancestry (about 74,000 T2D cases and 824,000 controls). The studies were imputed using the most comprehensive reference panels possible, and in all, the analysis considered about 27 million genotyped or imputed variants.

After performing T2D association analysis (both unadjusted and adjusted for body mass index) 243 loci were seen to be associated with T2D at genome-wide significance or better (p-value for association ≤ 5 x 10-8). Of these, 135 were novel--not detected previously in any T2D association analysis to date.

Within these loci, each of which included multiple significantly associated variants, the researchers performed approximate conditional analysis to determine whether the associations were independent of each other. They found surprising complexity within some loci; for example, the well-known TCF7L2 locus appears to include as many as 8 distinct association signals!

All of the T2D associations from this study may be viewed in the T2DKP. They are represented in two datasets, named "DIAMANTE (European) T2D GWAS" and "UK Biobank T2D GWAS (DIAMANTE-Europeans Sept 2018)."  Manhattan plots showing the distribution of the associations across the genome may be seen by selecting either the "Type 2 diabetes" or "Type 2 diabetes adj BMI" phenotypes from the phenotype selection menu on the T2DKP home page. On Gene pages of the T2DKP, the results may be viewed in tables of variant associations and in the interactive LocusZoom visualization (see below). Results from this study are also displayed on Variant pages of the T2DKP.

LocusZoom plot on the PPARG Gene page

The credible set analysis performed in this study is also incorporated into the T2DKP. On the "Credible sets" tab of Gene pages, you may choose to visualize any of the credible sets available for the region. Epigenomic annotations that overlap the positions of the variants in the credible set are presented in an interactive display that allows you to select particular chromatin states or tissues to view. In the example shown below, one of the credible sets in the TCF7L2 region includes just two variants, and the one with the highest posterior probability overlaps active enhancer regions in adipose and liver tissue--both of which are important for T2D.

Detail of the Credible sets tab of the TCF7L2 Gene page

The multiple causal variants identified in this study support previous investigations on the biological mechanisms behind T2D and suggest new hypotheses that will likely lead to therapeutic insights. After reading the paper and a blog post from the authors, we invite you to explore the results in the T2DKP and to contact us with any suggestions or questions!

Wednesday, September 26, 2018

New datasets and many new phenotypes in the T2DKP

Today we release several new datasets, including associations for many new phenotypes and individual-level data for secure interactive analysis, to the Type 2 Diabetes Knowledge Portal.

The AAGILE GWAS dataset, from the African American Glucose and Insulin Genetic Epidemiology (AAGILE) Consortium, brings more diversity of ancestry to the T2DKP, with meta-analysis of fasting glucose and BMI-adjusted fasting insulin associations from over 20,000 African American individuals. These results were combined with associations for over 57,000 individuals of European ancestry from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) in a trans-ethnic meta-analysis.

This release also adds two new diabetic kidney disease datasets from the SUMMIT (SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools) consortium. All of the more than 40,000 subjects in the "Diabetic Kidney Disease GWAS: subjects with T1D or T2D" dataset had either type 1 or type 2 diabetes. The study measured seven different renal phenotypes in these subjects, including four that are new to the T2DKP. Summary association results are available for the entire group and for sub-cohorts that separate T1D from T2D and European from Asian ancestry. A separate dataset from SUMMIT, "Diabetic Kidney Disease GWAS: subjects with T1D or T2D, ESRD vs. controls" is comprised of more than 5,600 diabetics, nearly 1,200 of whom had end-stage renal disease. These two datasets greatly expand the range of diabetic complications for which genetic association data are available in the T2DKP.

The T2DKP is federated, meaning that in addition to the Data Coordinating Center at the Broad Institute, some results are drawn from a sister site at the European Bioinformatics Institute (EMBL-EBI). This system allows data that may not leave Europe to be represented in the T2DKP. Six of the new datasets in this release are housed at the T2DKP Federated Node at EMBL-EBI.

The Hoorn Diabetes Care System (DCS) dataset includes associations for 12 different anthropometric, blood lipid, blood pressure, and liver and kidney function measures for a cohort of over 3,400 type 2 diabetics in the Netherlands.

The GoDarts project (Genetics of Diabetes Audit and Research in Tayside Scotland) recruits type 2 diabetics and matching controls in the Tayside region of Scotland. This release includes five new datasets from GoDarts, representing experiments performed using different arrays. Each experiment determined genetic associations for a wide variety of phenotypes, including two that are new to the T2DKP: levels of adiponectin and leptin, hormones that are associated with risk of T2D and obesity.

Results from all of these datasets may be searched using the Variant Finder tool and may be browsed:

• On Gene Pages in the Common variants and High-impact variants tables and in LocusZoom plots;

• On Variant Pages in the Associations at a glance section, the Associations across all datasets section, and in LocusZoom plots;

• From the View full genetic association results for a phenotype search on the home page: first select a phenotype, then select a dataset on the resulting page.

Individual-level data from the Hoorn DCS and GoDarts datasets also power secure interactive analyses using the Genetic Association Interactive Tool (GAIT) on Variant Pages. With the new additional data, nearly 61,000 individual-level samples are now available for custom association analysis.

Please take a look at the new results and contact us any time with questions or suggestions!