Self-Research Project - Investigating Undiagnosed Condition Through Longitudinal Health & Genetic Data

Hi everyone,

I wanted to share the self-research project I’ll be
working on as part of the Keating Memorial group
and hopefully get feedback as I go.

Background

I am currently dealing with ongoing health issues
that have not yet been fully explained or
diagnosed. Over time, I’ve started collecting a large
amount of personal data, including medical
records, lab results, symptom patterns, and
genetic data. My goal is to better understand what
may be underlying these issues and to build a more
complete picture that could eventually support
clinical evaluation or programs like the
Undiagnosed Diseases Network.

Research Focus
My current focus is identifying patterns across:
. Longitudinal lab values (including values within
“normal” ranges that may still show trends)

· Symptom tracking over time

. Genetic variants (especially variants of uncertain
significance)
. Family-level data to explore shared traits and
variability

I am particularly interested in:

. Variable expressivity and incomplete penetrance
. Correlations between symptoms and lab
fluctuations

. How genetic findings may (or may not) align with
real-world presentation

What I Plan to Do
. Organize and centralize my existing data (labs,
symptoms, genetics)
. Track ongoing symptoms and relevant variables
more consistently

. Compare patterns across time and across related
individuals where possible

.Identify potential clusters or trends that could guide further investigation.

Where I’d Appreciate Feedback
. Best practices for structuring and organizing
multi-source health data

. Approaches to interpreting variants of uncertain
significance

. Methods for identifying meaningful patterns vs
noise

. Any tools or workflows that could improve
analysis or visualization

Goal

My overall goal is to move from scattered
information to a structured, interpretable dataset
that can help guide next steps-both for my own
understanding and for potential clinical or research
collaboration.

I’m looking forward to learning from others here
and sharing updates as I make progress.