Icahn School of Medicine at Mount Sinai

Aim 1: Optimize power and enhance pathophysiologic insight in clinical areas of unmet need in IBD by 

• Coordinating, standardizing and tracking increased recruitment across the GRCs to substantially increased power to refine allelic effects may be achieved. 

• Integration with multi-omic ATAC + transcriptome single cell data may provide further refinement of association signals between Crohn’s disease and ulcerative colitis and across populations. 

• Complete mapping of sequence data for the NIDDK IBDGC lymphoblastoid lymphocyte repository from over 9000 patients will enable for broad use and dissemination and assist Ancillary studies.

Aim 2: To provide high-quality operational services targeted to the scientific objectives of the IBDGC, including:

• Streamlined data collection, management and distribution;

• Providing guidance in study design and data analysis;

• Supporting Consortium governance, communication and administration.

• Expanding the DCC’s infrastructure to accommodate new recruitment workflows, new GRC(s) and collaborators, and new analytic pipelines to accommodate the scale and richness of newly acquired data.

• Enhance the IBDGC Data Commons and IBDGC website to promote and facilitate discovery and usage of our resources (including those accessible through the NIDDK Central Repository and dbGaP) throughout the IBDGC and IIIBDGC and by the broader research community.

Aim 3: In selected clinical scenarios of unmet medical needs, to enable longitudinal analyses prioritized by the NIDDK IBDGC Steering Committee. To scale and standardize multi-omic cellular data.

• Performing multi-omic integration of the Crohn’s disease ileal resection cohort to predict recurrence and therapeutic response.

• Adapting data collection workflows to capture new clinical priorities for prospective collections (eg. ulcerative colitis flares, and perianal Crohn’s disease)

• Incorporating GRC analytic capacities in innovative endoscopy, radiology and pathology data

New recruitment priorities and approaches

The DCC is piloting methods to facilitate recruitment in non-European populations using single IRBs, alternative reimbursement strategies, biobank-based and direct-to-patient recruitment approaches. The DCC leads a monthly coordinators’ meeting to communicate IBDGC priorities, assess progress and share effective recruiting and sample handling approaches across the Consortium.

New data types and accelerating integration

The DCC is adding to its form-based methods for collecting phenotype data by using electronic medical records and diagnostic imaging and reports. IBDGC investigators are piloting image-based measurements beginning with radiology but likely expanding into both pathology and paraffin-based methods as well. Rapidly developing applications of multi-omic single cell technologies are a high priority, especially for their ability to provide insight into IBD physiology.

Data sharing, data mining, and project acceleration

Common variant, GWAS-based data mapped to traits represents an important, foundation for further studies. Expansions of both chip and sequence-based cohorts will be finalized in 2021-2022 and published via dbGaP and the IBDGC Data Commons. The integration of African-based reference, common variant data substantially improves IBD trait prediction as an important basis for the expansion of non-European cohorts. Tissue-based, bulk RNAseq gene expression linked to important clinical inflection points has provided substantial mechanistic insight, especially when integrated with single cell data. Through the DCC, the IBDGC will utilize the Data Commons to increase the speed of analyses and data sharing in promotion of deeper collaboration.

Training the next generation of IBD researchers

The DCC organizes a rotating schedule of GRC presentations where work from junior investigators is encouraged. In 2020, the DCC initiated a webinar series focusing on data-intensive, translational investigators. Given a) the rapid rate of data expansion in scope and type, and b) the increasingly refined mining capacities of extant clinical collections, the opportunities for training and developing the next generation of translational researchers are highly promising.