Tag Archives: genetics
At our Quantified Self conferences we focus our show&tell talks on personal, first person narratives of self-tracking and self-knowledge. But what if first person is actually two people instead of one? Well, that’s when things get interesting!
At the upcoming Quantified Self Global Conference we are excited to have Dr. Rosane Oliveira talking about her self-tracking experiments that she’s been conducting with her twin sister. This great talk will include explorations of genetic testing, metabolic biomarkers, gut microbiome and mobile monitoring of diet, weight, sleep, mood, and activity levels.
Lucky for us, we’ve already received a preview of sorts in the form of a wonderful talk Rosane presented at the Bay Area QS meetup group in March of 2012. Watch the video below and come prepared to learn more about what you Rosane was able to learn when she started tracking with her genetic double.
The Quantified Self Global Conference will be held in San Francisco on October 10th and 11th. Registration is now open. As with all our conferences our speakers are members of the community. We hope to see you there!
23andMe, a wonderful annual sponsor of the Quantified Self, has some exciting news to share with us. Check out this letter from 23andMe’s CEO Anne Wojcicki below!
Today we’re announcing some big news. I don’t want this moment to go by without a note of gratitude to our customers and those who have been advocates for 23andMe over the years.
We have come a long way together. Because of you we pioneered the use of personal genetics. You are helping us establish a new medical era that is defined by wellness, disease prevention, and personalized care. You also helped us create a novel research platform. By leveraging online tools, social networking and crowd sourcing, and combining them with genetics, we created a platform that has set the stage to transform the way pharma companies and academics do health and wellness research.
We want to do more.
23andMe has raised more than $50 million in new financing with the goal of reaching one million customers. To help us reach our goal, we are happy to announce today, that we are dropping our price to $99.
One million customers can be the tipping point that moves medicine into the molecular era. Hundreds of you have written to us about how genetic information changed your lives and, in some cases, saved your lives. We believe genetics should be an integral part of health care and we will work hard in the coming year to help genetics become part of everyone’s health and wellness.
A community of one million individuals will also benefit the world. A genetic data resource of this magnitude has enormous potential to address unanswered questions related to the contributions of genes, the environment and your health. Understanding these factors and their interactions could lead to major improvement in diagnostics, preventive medicine and therapeutics [Collins NATURE | VOL 429 | 27 MAY 2004].
This change is not just about a new price point for personal genetic testing. It is about an ambitious plan that could transform medicine for generations to come.
If you have questions about the new pricing please go to our FAQ or email your questions to customercare@23andMe.com.
We talk about very frequently here on the QS website about tools, methods, and systems that help us understand ourselves. When it comes to the self there may be nothing more fundamental to understanding our objective ourness than our basic genetic makeup. Many of you have probably undergone or have thought of using Direct-To-Consumer genetic testing to better understand your phenotypes, disease risk, or even your ancestry. That’s all great, and I’ve spent a lot of valuable time combing through my own genetic data, but like most data true power lies in large datasets that provide observations across many individuals. So how do you participate in that type of sharing and learning? Enter the team at the openSNP.org. Today we talk with Bastian Greshake, one the developers behind the openSNP project.
How do you describe openSNP? What is it?
The too long, didn’t read version: A open platform which allows people to share their genetic information and traits, which are suspected to be at least partially genetically predisposed, which also tries to annotate those genetic variants with primary scientific literature. The data can be exported from openSNP through the website or through APIs, making it easy to re-use the data.
A longer version: openSNP has basically two target groups and users may as well fit in both categories.
First there are customers of Direct-To-Consumer (DTC) genetic testing like 23andMe who want to share their genetic information with the public for various reasons. Those can use openSNP to release their genetic data into the public domain using the Creative Commons license which is applied to the data uploaded and entered in openSNP.
As genetic information is interesting but not very useful to analyze the effect of genetic variants on bodily traits those users can also enter information about traits which might genetically influenced and create new possible categories which all other users then can enter. Those traits range from the more obvious ones, like eye and hair color, to more exotic ones like political ideology. A few weeks ago we also created a method for users to also connect their Fitbit accounts to openSNP to make the collection of data easier and more standardized. The genetic effects on activity, sleep habits and weight loss/gain can more easily be analyzed in this fashion.
We also mine the databases of Mendeley, the Public Library of Science and the SNPedia to annotate the genetic variants users carry. This allows customers of DTC testing to find out what the recent scientific literature is able to tell them about their genetic variants. While the SNPedia is a crowd-curated Wiki, Mendeley and the Public Library of Science link back to primary literature, in the latter case even to Open Access literature which is full text available for everyone.
The second group of users who are interested in openSNP are scientists and citizen scientists who are interested in using the data for their own studies, be it to figure out what genetics can tell us about our ancestry or which effects single variants have on disease risks or other traits. The data can be downloaded from openSNP in bulk or more granularly accessed through a JSON-API and the Distributed Annotation System, a standard in Bioinformatics, which for example is used to visualize the data.
Both groups can profit from the commenting features which allows users to communicate about traits and individual genetic variants. The internal message system of openSNP also facilitates further communication, for example to share details about shared traits and diseases or to allow people who want to use the data to get back in touch with the people who uploaded the data. The latter one enables the direct exchange between those two user-groups in a bidirectional way: Researchers can ask questions about traits and people who have shared their data have a back channel as well and can get notified about the results researchers have made.
What’s the backstory? What led to it?
It more or less began with me getting my genetic information analyzed by 23andMe myself. After I received the results I published the data in a git repository on GitHub to make it available for others who might benefit of having more data. As I started to dig deeper into my own results and the raw data I wanted to have more data sets myself, to be able to compare the results. But unfortunately there wasn’t a single resource for such data. Some people also had published their data on GitHub, others on their own websites, collected publicly available data sets in a Google Spreadsheet or participated in projects like the Personal Genome Project.
This was quite frustrating: Finding the data was hard and it most often there was no additional data about traits attached. And more often than one would expect there was also no way to contact to people who made the data public. So the idea to create a platform to solve this problem grew and I contacted some friends to see if they were interested in doing such a platform, just for fun. We started out with the basic idea of creating a platform where people could upload their genetic data along with some traits they have. A couple of weeks after we started to work on the project we stumbled upon the APIs of Mendeley & the Public Library of Science and thought it might be cool to include additional data about the genetic variants as well. During the development we came up with more and more features, like the openSNP APIs. All in all the project is still growing and we’re working on adding and refining features.
What impact has it had? What have you heard from users?
We submitted the first release of openSNP to the 2011 PLOS/Mendeley Binary Battle, a competition interested in creative ways to use their APIs and won the first prize. We also secured a small grant from the German Wikimedia Foundation, which allowed us to genotype over 20 people, mainly from underrepresented groups, to diversify the available data. Those persons have now released their genetic data on openSNP as well. Right now we have over 250 genetic data sets on openSNP and just short of 600 registered users. Those numbers don’t sound to impressive in the age of one billion people on Facebook. But to put it into perspective: Genetic testing is still a niche thing and before openSNP was released there were about 40-50 of those data sets publicly available.
The feedback of our users has been very positive. Many users come up with new ideas for features they like to see added and we are really open to those suggestions and critiques. Many of the API methods, which are now implemented (and the whole Distributed Annotation System), are only in place because user let us know they wanted them. I know of users who are actively using openSNP to learn more about their test results and are in an active exchange with other users with similar traits. And while the amount of data we have so far doesn’t really allow scientifically sound studies there are already people using the data, for example there are users who run their self-written analysis-tools over the openSNP-data sets and report the results back to the users, which is amazing.
What makes it different, sets it apart?
Of course we’re not really the first to think of such an idea but are more or less a remix. For example 23andMe themselves do use the data of consenting customers for studies. They also provide questionaries about traits which users can take. But this data isn’t available to the public, due to (perfectly reasonable) concerns in terms of privacy, bio-ethics and liability. On the other hand there are projects like the Personal Genome Project, which publishes traits and genetic data of participants into the public domain. But due to similar reasons like with 23andMe the participation in the project isn’t open to everyone.
We feel that informed individuals should be in the position to share their data with the world, like they are already doing on their own websites, in an easy fashion. And of course we’re targeting a slightly different group: Probably over 150,000 people are customers of some DTC genetic testing, this is a huge potential data source which could be used to help us understand new and exciting things.
What are you doing next? How do you see openSNP evolving?
We’re still developing and refining openSNP. One of the biggest problems right now is the quality of the data for the additional traits. We have kept the process of adding data really open on purpose, to make it easy for people to provide additional information about themselves. Unfortunately this has the side-effect that the quality of the descriptions varies wildly. Those problems start of with regional idiosyncrasies: Is it “Eye Color” or “Eye Colour” and are you using the metric or the imperial system of units? And is your eye color blue or “Indeterminate brown-green with a subtle grey caste”? This granular data can be very useful, but for many applications it can be too specific. With the implementation of the Fitbit API we’ve taken a first step to keep the entering of data simple but unified at the same time. And we’re currently looking into other ways of how one could counter problems like this.
We’re also looking in more data sources to annotate the genetic variants listed in openSNP, to provide even more information for customers of DTC testing. And we’re also working on making our APIs more powerful. With the rOpenSci package there is already a great library which makes use of the APIs in the current state, but of course we would like to see more of those libraries.
And it’s hard to say in which direction openSNP will evolve as we are a bit dependent on the DTC genetic testing industry. More and more data, like Whole-Genome or Exome Sequencing, is generated and we are working on reflecting those changes on openSNP as well. And we’re open for any suggestions. So if you find that a feature is missing you should let us know, we will try to work out a way of how this might be usefully implemented.
Anything else you’d like to say?
First of all: We know, genetic information is sensitive and depending on where you are living there might not even be laws to protect you from discrimination based of your genes. Other countries, like the US with the Genetic Information Discrimination Act (GINA), have some mechanisms against this, but even those might not offer total protection in the end. And you should also keep in mind that your genetic information does not only give away details about yourself, but by design also about the next of kin. I think this is really important. If you are thinking about publishing your genetic data please keep those issues in mind. And if you come to the conclusion that this isn’t for you as you have to fear negative repercussions or just have a gut feeling of not really wanting to publish the data: Please don’t do it.
And what I also can’t stress enough is that openSNP is developed and run by a team of about four people and we are all doing this in our spare time as a fun project and as community service, without compensation. Some of us have day jobs, others are still studying and some even do both. So while we are doing our best to keep everything running it might sometimes take a while. But if you feel like contributing to the project please get in touch with us. We’d love to have more people in on this.
Authors note: Data sharing, especially genetic data, is a very sensitive topic in our community. I want to fully disclose my bias towards openness and sharing. I believe that our kindergarden teachers had it right when they taught us that sharing is one of the fundamental human traits we should all cultivate. To this end, I have participated in openSNP and you can view my genetic data here and my Fitbit data here.
This is the 18th post in the “Toolmaker Talks” series. The QS blog features intrepid self-quantifiers and their stories: what did they do? how did they do it? and what have they learned? In Toolmaker Talks we hear from QS enablers, those observing this QS activity and developing self-quantifying tools: what needs have they observed? what tools have they developed in response? and what have they learned from users’ experiences? If you are a “toolmaker” and want to participate in this series, contact Rajiv Mehta or Ernesto Ramirez.
In the last session of the day, we had a few experimental talks on noticing how food changes physical condition. It was also an interesting series of talks that shows the importance of collecting our own subjective data to back up or refute the other technological data that we might also have access to.
I kicked off the session with my talk “Quantifying My Genetics: Why I have been banned from caffeine”. My colleagues and friends helped me quantify my behavior after one, two, or three cups of coffee by giving my agitation a number from 0-10.
I found out that I’m a slow caffeine metabolizer from my genetic results and it seems like there is a correlation between how caffeine affects me and my genes. My genes are not deterministic, I couldn’t have known how caffeine affects me without making my own independent observations.
On a fun note, the crowd guessed that I had one cup of caffeine today, they were right, I had a cup of tea earlier down in the restaurant, away from the conference.
Next we had Martha Rotter who talked about how she experimented with her diet to solve her skin problems after doctors told her there was not much she could do. She did one allergy test where the results said she was allergic to chicken and soy- but after cutting out both of those foods, she did not see any changes but it gave her the idea to test different food groups.
After her experiment with a chicken and soy-less diet, she tried a few other food groups, eventually hitting on cutting out dairy. Her skin cleared up within two weeks of stopping drinking milk, eating cheese.
I think the take away message from our two sessions this afternoon, don’t be afraid to do your own testing, trust in your results.
I led a very interesting discussion at Quantified Self Europe this morning with about 10 attendees with a variety of backgounds. There were entrepreneurs who wanted to start genetic information based companies, a designer, a think tank analyst, and people who are just interested in where the field is and where it was going.
The first thing we did was to create an impromptu community, putting the chairs into a circle and starting the discussion with what brought each of us to the topic of Creating Genetic Communities. This is where the conversation started but the topics ranged from where the industry is going to how to use design to help a non-technical audience understand their genetic data.
There was agreement in the room that the price of DNA sequencing is decreasing exponentially, the discussion then moved to what an individual can do with their own data vs. getting aggregate genetic data. There was an intense debate about open data vs. transparency of who has access vs. private databases. There was also a challenge thrown out by two group members to make genetic information more actionable.
It’s an amazing group of people who have come together in Amsterdam to discuss where we are going as we get more data on ourselves.
Here’s your chance to learn how to live longer, and save money too.
Christine Peterson is hosting the first Personalized Life Extension Conference, October 9-10 at the San Francisco Airport Marriott. She is offering a $100 discount on the $275 registration price to all Quantified Self members who register with the discount code “QS”.
6 months ago, I got my 23andMe genetic test results. They showed mostly what I expected: 30% chance of diabetes, 24% chance of atrial fibrillation, 40x greater risk of Celiac disease than the general population. All of these things are found in my extended family to some degree.
But there was one thing I didn’t expect.
I have double the normal risk of Tourette’s syndrome. Yes, Tourette’s is commonly associated with people walking down the street swearing and thrashing around uncontrollably. That’s not me, but it did get me thinking.
My dad, brother, and I all have tics. They had always bothered me, but I learned to internalize most of them so they aren’t noticeable unless you’re looking very carefully or I let down my guard. They are part of the reason that I can only see people 3 days a week, because I need the other 4 days to recover from the effort. I began to wonder, what if I could address the tics and live life with more ease? So, armed with the new 23andMe information, I started to investigate this part of my health that I hadn’t really looked at in detail before.
The first thing I did was to write down all the different tics I do, which are almost all on my left side. My theory as to why I don’t have many of the vocal tics characteristic of Tourette’s is that perhaps only my right brain is affected – so the right side of my body and my language center, both controlled by my left brain, are mercifully free.
Here are all the things I do, mostly involuntarily, every day (after the jump):
The cheapest commercial genome testing right now is from 23andMe for $400. Prices in this area will continue to drop, while the number of genes sequenced rise. However nothing beats free. You can now get your genome sequenced (partially) for free by participating in a large-scale research program to try to correlate genes with disease. The Coriell Personalized Medicine Collaborative (CPMC) is being funded by charitable foundations, and they have money at present to sequence 10,000 volunteers. To get your genes sequenced for free there are several caveats.
1) You need to be over 18
2) You need to attend an educational session. At the moment these are only offered in Camden, New Jersey (near Philadelphia). They claim to be working on a mail-in version later.
3) You won’t get your gene code back. Instead you will only receive data that is “medically actionable.” In other words you will only get reports about genes that their board of doctors feel you can do something about.
The key phrase here is “board of doctors.” Unlike commercial services which return your full test results and let you do what you want with this data, this survey is run by doctors who feel ethically obligated to offer responsible medical counsel, and so they will not tell you about genes that have no medical value, or about which the science is not certain in their opinion.
For some people this is the doctor priesthood exerting their control over your health options (they would like companies like 23andMe shut down unless they let doctors take control). For others, this is a good deal. Free testing, plus free doctor advice about what is worth paying attention to and what is just fluff.
My long-term prediction has been that pharmaceutical companies will eventually pay for your genome sequencing in full since they can target drugs to specific genetic cohorts and avoid those patients with genes that may produce negative side effects. But again you may not get your full sequence back. But as in the rest of life, there is no such thing as a free lunch.
To clarify what kind of results you get back, here are some excerpts from the CPMC FAQ:
This study will only report back to participants those genetic variants that are potentially “medically actionable.” Potentially medically actionable genetic variants are those for which 1) there is a scientifically valid association between the variant and a specific health condition, 2) there are actions or interventions that can be taken to reduce the risk of the health condition, and 3) the risk of adverse events from these possible interventions is likely small in relation to the risk associated with the genetic variant if no medical action is taken.
You WILL NOT receive results for all genetic variants. Genetic variants associated with medical conditions for which there is no treatment or intervention to reduce the risk of disease WILL NOT be reported back to participants. For example, variants elevating risk for incurable diseases such as Alzheimer’s disease will not be reported. If a new therapy or lifestyle intervention is reported, the ICOB may update a condition to be “potentially medically actionable.”
The technology employed by the CPMC™ is not designed to detect single-gene mutations that cause rare Mendelian disorders such as sickle cell disease, cystic fibrosis and Tay-Sachs; therefore, these are very unlikely to be detected and reported to you.
Ann Turner, co-author of the best book on DNA-based genealogy: Trace Your Roots With DNA, wrote me to say that she too has been comparing results from the two big genetic test companies, 23andMe and deCode. She wrote in response to my earlier posting comparing results between the two vendors.
The big news is that places where errors are showing up are probably not random. Here’s the argument, starting with her post on ancestry.com:
The two companies overlap on 562,532 SNPs. They agreed on 560,128 calls, or 99.6%. 23andMe didn’t make a call on 1,970 SNPs where deCODEme did, and deCODEme didn’t make a call on 399 records where 23andMe did. That leaves a mere 35 records where they actually made different calls [see the list below]. In all of those cases, one company would make a homozygous call while the other company made a heterozygous call — there were no cases where they made a completely discordant call.
Here’s the kicker from Ann’s letter to me:
Four of those (rs11149566, rs4458717, rs4660646, and rs 754499) were also found in Antonio’s list. That’s more than you would expect by chance.
Four out of 23 from Antonio’s list and four out of 35 on Turner’s list of discordant results indicates that these regions (at least) are unreliable.
This is why sharing results is so valuable and a key to great quantified self understanding.
This is a micrograph of the bead array on which these tests are conducted.
Turner’s 35 SNPs with different results, if case you also have done a comparison.
rs10435795 rs1045363 rs10743414 rs10945383 rs11149566 rs11179382 rs11707159 rs11915402 rs1209171 rs1221986 rs12907462 rs1303912 rs13422439 rs161381 rs17328647 rs1961196 rs1966357 rs2016461 rs2064034 rs2290516 rs2853981 rs3952469 rs4336661 rs4423481 rs4458717 rs4572718 rs4660646 rs6531490 rs6942478 rs7102702 rs754499 rs7812884 rs845217 rs9332128 rs9476380