Outline:
Project description
Plans during funding
Future perspectives
Challenges
MELD Project Description
Brief introduction
Early life influences risk for diabetes
How metabolic processes mediate link? 🤷🤷
Difficult to study due to long timespans
Easier now with:
- Long term registers
- Cohort with registers
- Powerful mediation methods
Research questions:
- Aim: To quantify and understand impact of early life conditions on adult metabolic capacity and risk for T2D.
Objectives
- Investigate how specific early life conditions affect risk of T2D nationally
- Extend and generalise NetCoupler algorithm
(github.com/NetCoupler)
- Estimates direct and mediating pathways in high dimensional metabolic data
- Identify mediating pathways of metabolic capacity between early life adversity and T2D using NetCoupler
Methods: Population
Methods: Variables
Methods: Analysis process
Analyzing data that looks like:
NetCoupler: A causal structure learning algorithm that...
Finds most likely network structure
Allows inclusion of exposure and outcome
Identifies causal links between and within network
NetCoupler algorithm was developed by Clemens Wittenbecher.
Infer (potentially) causal pathways with graphical model
General timeline
(Some) Plans
Adhere even more to open scientific practices
- E.g. developing protocol to register study[1]
Research stays in Boston to work with Clemens
[1] MELD Project Protocol: lwjohnst.gitlab.io/meld-protocol
Future Perspectives
For project
Potential for other research s
- Cohort with registers
- Application of causal learning algorithm
Gain expertise in working with registers
Potential to get to expand project
For career
Develop and expand my network in Europe
Get more 👨💻👩💻 to work with
Co-mentor PhD student
Challenges:
Navigating Statistics Denmark website and documentation
Translating Danish words for variables and registers
- ... and knowing what to look for
Finding other datasets to use for linkage
Balancing my time with other projects