The Evidence
What the data revealed
Key biomarkers that told a story—once someone finally looked at them together.
My Function Health Results
Real data showing markers indicating Hashimoto's thyroiditis
TSH: 5.72 mIU/L – Above optimal range
Thyroglobulin Antibodies: 176 IU/mL – Elevated
Pattern Recognition
How Function Health connected the dots
After five years of fragmented care across a dozen specialists, Function Health's comprehensive approach finally revealed what conventional medicine missed. Their panel doesn't just test for symptoms, it systematically screens for patterns across interconnected systems.
When Function Health tested my thyroid antibodies, something never ordered despite family history and clear warning signs, the diagnosis was immediate. Elevated TSH combined with high thyroglobulin antibodies told a clear story: Hashimoto's thyroiditis, quietly causing inflammation for years.
This wasn't a breakthrough in testing technology. These are standard labs. The breakthrough was in integration, running a complete panel proactively, not waiting for symptoms to worsen. Function Health's model proves that comprehensive, data-driven diagnostics can catch what reactive, siloed care misses. That realization changed everything about how I understood both my health journey and the massive opportunity in preventive diagnostics.
7 Years of Physiological Data
Pattern recognition before symptoms became debilitating
Justin's HRV Analysis: 2018-2026
Correlated with Clinical Timeline
Complete HRV timeline with clinical events • Age-based reference ranges shown
In 2018, my Apple Watch began recording heart rate variability data. By 2021, I was experiencing severe autonomic dysfunction, but the warning signs had been in the data all along.
My HRV was chronically low, consistently in the low 30's on average. For comparison, healthy men in their mid-20s to early 30s typically have HRV values of 60-100ms or higher. My values were in the range typically seen in people decades older with cardiovascular disease. The data showed clear autonomic dysfunction years before I developed debilitating symptoms.
The challenge wasn't data availability. It was interpretation. Standard medical care doesn't analyze longitudinal consumer health data. There's no system to flag concerning patterns before they become clinical emergencies. I had to export 7+ years of Apple Health data and analyze it myself to see what had been there the entire time.
Genetic Susceptibilities
Your genome has answers—if you know what to ask
(T-786C + rs1800779)
(R16G)
After years of unexplained POTS symptoms, I used Claude Code to analyze my raw AncestryDNA file directly. The analysis revealed something striking: I carry double homozygous NOS3 variants (both T-786C and rs1800779) plus ADRB2 R16G, a genetic combination that creates a "perfect storm" for autonomic dysfunction.
The NOS3 variants severely reduce nitric oxide production, impairing my blood vessels' ability to dilate properly. The ADRB2 variant causes beta-2 receptor downregulation, meaning my cardiovascular system can't respond appropriately to positional changes. Together, these explain the core pathophysiology of my POTS: impaired vascular tone combined with inadequate compensatory mechanisms.
Here's what matters: this wasn't exotic genetic testing. This was standard consumer DNA data ($99 from Ancestry) that I'd had for years. What was missing wasn't the data, it was the infrastructure to interpret it in clinical context. No doctor I saw had the tools to say "Your symptoms + these variants = high probability autonomic dysfunction, let's test for POTS."
That integration gap, between having data and making it clinically actionable, is exactly what Function Health is solving at scale.
The opportunity: Building the connective tissue
These two datasets—physiological tracking and genetic variants—existed in isolation for years. One lived in my Apple Watch. One lived in an Ancestry DNA file. Neither healthcare provider I saw had access to both, let alone the tools to integrate them.
Function Health is building the infrastructure to close this gap. Comprehensive lab testing plus systematic analysis plus longitudinal tracking. Not reactive medicine, but proactive pattern recognition.
I want to help build that future.
