Tag Archives: 23andMe

Big data: From medical imaging to genomics

Pickard-KT-and-Kimberly

KT & Kimberly Pickard

In 2006, a Scientific American article written by George Church, “Genomics for All,” rekindled my interest in genomics. I went back to school in 2009 to contemplate the business of genomic medicine, and celebrated my MBA by writing a Wikipedia entry for the word, “Exome.” I was hooked.

We started our odyssey by genotyping our family using 23andMe, and later my wife and I had our whole genomes sequenced. Realizing that genomics were starting to yield clinically useful information, we crowdsourced the sequencing of our kid’s genomes to look for genetic clues in their autism. We found interesting results, gave talks and wrote papers.

imaging-to-genomics-2014-03-06

 

Along the way, I realized that medical imaging and genomics are highly complementary: genomics informs or identifies conditions, and radiology localizes them. Sarah-Jane Dawson pointed this out at a Future of Genomic Medicine conference in 2014.

After working in medical imaging for over twenty years, I am moving into the world of clinical genomics and precision medicine. For the past two-and-a-half years, I have had the good fortune to run an enterprise medical imaging startup, but it is time to turn my passion into action.

Now, I am looking for new opportunities, and welcome your introductions to connect us to our next chapter.

Trust, but verify

Working with 23andMe exome data: my CF allele and the need for verification

This informative blog post from Dr. Jung Choi at Georgia Tech discusses how to use free, publicly available bioinformatics tools to interpret new exome sequence data from 23andMe. The post includes a response from 23andMe in the comments.

Some of the bioinformatics tools that Dr. Choi uses are:

The post highlights the challenges of mapping gene-protein interactions when reporting results.

Jc_cftr_rpt

Self-Tracking Presentation at Quantified Self Meetup in San Francisco

I presented results from my self-tracking study at the Quantified Self San Francisco meetup at WellnessFX in San Francisco.

Experiment

By participating in this crowd-sourced study on Genomera, I tested niacin supplementation as a potential treatment for Restless Legs Syndrome (RLS).

Methods

The protocol is based on ramping up from 0mg to 1000mg of niacin over one month. I had to taper off my current medication that I have taken for 10 years, clonazepam, for a week and then take nothing for a control week.

RLS_Study_Pickard.xlsx

I recorded some sliding scale measurements of RLS sensation, leg jerks, sleep, etc. in a spreadsheet (above), and worked with Genomera to create an “instrument,” a web page for data entry. I used Tonic to remind me to take niacin with meals, and Fitbit to record my sleep.

Results

Two weeks after taking niacin (500 mg/day), I did not see any improvement so I stopped taking niacin. Afterwards, I saw my doctor and we had a great discussion about the genetic factors that contribute to the disease. He also suggested that I check my ferritin level, since some people with RLS have this hidden iron deficiency. I learned that my ferritin level is very low, so I am starting an iron supplement. With luck, I will be able to report some improvement in my RLS in a future post.

Quantified Self video presentation (5:24)

Link to slides on slideshare.net