PROJECT SUMMARY / ABSTRACT
The funds requested in this R13 application are for partial support of “Systems Immunology in Aging and Chronic
Diseases of Aging” annual meetings to be offered each September from 2020 through 2022 at The Jackson
Laboratory for Genomic Medicine (JAX-GM) in Farmington, Connecticut. This meeting builds on its very
successful first instance in 2019 and will bring together up to 150 interdisciplinary scientists including molecular
biologists, immunologists, computational biologists, and geriatricians, who share a common interest in
understanding aging and aging-associated disease at the systems level. Many aging-associated diseases, such
as cancer and cardiovascular disease, are influenced by dysfunctions in the immune system. Recent advances
in genomic profiling techniques (e.g., single cell transcriptomics) provide an opportunity to uncover aging-related
changes in human cells/tissues and to link these changes to health and lifespan. The wealth and complexity of
data produced using these technologies is ever increasing, as is the need to develop advanced computational
methods to mine and integrate these data. Despite this need, there are currently no formal venues at which
scientists, specifically those in the aging field, can be trained in the basics and application of data mining
techniques (i.e., machine learning algorithms). Furthermore, current conferences on aging are not aimed at
specifically bringing together computational biologists, immunologists and basic and clinical aging researchers.
Therefore, the objectives of this meeting are: (1) to recognize and emphasize the highly interdisciplinary nature
of the aging field and to promote and accelerate collaborations and cross-pollination of ideas across the three
disciplines: aging, immunology, and computational biology; (2) to provide trainees (students and postdoctoral
fellows) an opportunity to closely interact with, and gain feedback from, more senior investigators to advance
their projects and establish connections to help build their careers; and (3) to provide an opportunity for
researchers in the field of aging to learn the basics of machine learning techniques, which they will be able to
immediately apply to their own research upon return to their home institutions. We will reach these objectives
through carrying out the following Aims. In Aim 1, we will organize an interdisciplinary meeting and hands-on
workshop focused on aging and aging-related diseases. The meeting will include a 2-day seminar session
featuring talks by leading scientists, followed by a 1-day hands-on workshop on the basics of machine learning.
In Aim 2, we will promote interactions to foster collaborative research and career advancement, including through
a poster session. In Aim 3, we will recruit diverse attendees. Our proposed speaker list features several female
scientists, and we will use our partnership networks to specifically recruit attendees from nationally
underrepresented racial and ethnic groups. The ultimate goal of the meeting is to advance the aging research
field through expediting collaborations and the understanding of aging-related genomic data via application of
advanced data mining approaches.