Questions About Genetic Testing

NOTE: Getting Advice About Genetic Testing

I've recently been asked some questions about genetic testing, some of which I think are worth mentioning in a public discussion (although please see the note above if you are interested in getting specific recommendations):

1) How can I use my DNA sequence to inform my decision making about reducing my risk of getting a disease?

In many cases, I think the actions that you can take to reduce disease risk are relatively generic (exercise, eat lots of fruits and vegetables, etc.), and these are things that you should do regardless of your genotype.

That said, there certainly are some circumstances where very specific action can be taken, based upon your genome sequence.  I am not personally aware of all such examples, and I would recommend talking to a medical professional (such as a genetic counselor) for more information.  If this is the only type of information that you wish to learn about your genome, then you may only benefit from determining the sequence for a small portion of your genome (and your family history can guide the likelihood of needing to perform any genetic tests in a clinical setting).

2) How does Promethease compare to the health reports from 23andMe?  Does Promethease mostly focus on rare mutations?

Promethease is based upon annotations that come from SNPedia (similar to wikipedia, but specifically for mutation annotations).  So, I would expect the content would depend on whatever information is entered by volunteers.  Given the amount of information that I see from by 23andMe data (which is mostly common variants), I would say it contains a large amount of information on common variants.

When I first ran Promethease, I remembered mostly seeing risk annotations (which you can see in my old post, comparing my top 23andMe risk associations), and I didn't remember seeing anything like the carrier status report.  For example, I didn't remember seeing anything reporting me as a carrier for cystic fibrosis, which is an example of a 23andMe result that was in good concordance with my family history.  However, I went back to check my specific mutation (394delTT), with a probe ID i4000313.  This particular probe ID makes it a bit harder to match the mutation.  However, if I Google the probe ID, I can see that is is included in SNPedia but without a detailed description.  If I look up 394delTT in ClinVar, then I can get more information about this variant and I can see that it corresponds to rs121908769.  If I then look this variant up in SNPedia, I can see that it provides some information from ClinVar (although there is nothing in the brief main text for mentioning cystic fibrosis), but I don't see it among any of the "cystic fibrosis" variants in my old Promethease report.

However, to be fair, I wanted to re-run my sample through Promethase to see if the reporting system has changed and/or confirm that it now recognizes this mutation in my data.  It appears that a many new features have been added within the last 3+ years, such as a more interactive interface (viewed by clicking "UI version 2" in the downloadable report). Additionally, I can tell that the "medicines" and "medical conditions" have been expanded to include more SNPs.   However, it still don't recognize my cystic fibrosis carrier status, so it can't simply considered a replacement for the old 23andMe report.

Also, in general, the information available in Promethease tends to be terse, and it won't contain the same level of detail for explaining basic concepts as would have been provided by the old 23andMe health report.

3) More specifically, I do not wish to see a doctor in order to obtain my genetic information.  Also, I want something clear and easy to understand, which doesn't require doing any additional research.  What are my options, now that 23andMe no longer offers health reports?

I am not aware of any direct-to-consumer test that provides information that is comparable to the old 23andMe health reports, and I am not aware of any tool to analyze your raw 23andMe data that will reproduce your the old 23andMe health report (especially not with all the details to help make the results easier to understand).  I believe that even Illumina's Understand Your Genome program requires meeting with a doctor to draw your blood, conduct a predisposition screen, and discuss your results.

Perhaps more importantly, I think it is worth emphasizing that the health reports previously offered by 23andMe were not really a single report: they were updated periodically as new findings were published in the genomics literature, so your estimated risk would change over time for many traits.  This should be generally true for any tool connecting you to the genomics literature, as also demonstrated for the Promethease example above.

If you were only interested in the subset of results that are unlikely to change, I think you would probably have been most interested in the carrier status reports (and a handful of the other reports).  There are tests like Counsyl that I would expect to probably be similar to the the 23andMe carrier status results (and it is something that I would want to check out, if I was planning on having a child), but I believe that you can only get that test through your doctor.  However, this is just one example: I would recommend talking to a doctor or genetic counselor if you want more specific guidance.

In my opinion, I am most uncomfortable with the request to get a result that "doesn't require doing any additional research".  Critical thinking and being able to synthesize your own opinion from multiple sources of information are important skills that should be part of everyday life, and I think "additional research" is especially important for tools designed for "research and educational purposes" (including 23andMe, Promethease, Interpretome, etc.).  For example, clinical action may be limited because 1) all the genetic influences of disease risk are not known, 2) ways to mitigate genetic risk may not be known, and 3) one current limitation to low-cost options like SNP chips is that you aren't measuring your entire genome sequence (so, some important sequences may not be covered).  This might be a problem for some people, but I think it is still OK for many people.

In other words, there certainly have been some cases where people discovered important findings from their 23andMe reports that were worth verifying in a clinical setting, but I think most 23andMe customers took no medical action based upon their reports.  Most importantly, "no medical action" need not equate to "dissatisfied": I would personally fall the category of a customer who was "very satisfied" yet has not changed by behavior because of any of the results.  I think trying to understand how your biology is influenced by your genome sequence is a life-long goal that will probably never be fully realized, but I think there is value in being able to understand on-going genome research through the context of your own genome.

My 23andMe Results: Getting a (Free) Second Opinion

NOTE: Getting Advice About Genetic Testing

In order to get an idea about how well the 23andMe risk calculator agrees with other algorithms (when using the same exact same SNP data), I searched for other tools that I could use to analyze my genetic data.

For this post, I have compared my risk assessments from 23andMe to those provided by Promethease (which uses the information available in SNPedia).  I also played around with the free version of Enlis Genome (Personal Edition), but I found the GUI to be a little buggy and they didn’t automatically prioritize risk assessments (unlike 23andMe and Promethease).  So, this post will focus only on comparing my 23andMe assessment with my Promethease assessment.

To be fair, I should point out that I would not necessarily expect 100% concordance between my 23andMe and Promethease results for various reasons.  For example, the “magnitude” score from promethease is a subjective measure, and the curation methods are different for these two tools.  However, I think such a comparison will still be useful because it will still be encouraging to see any predictions that are shared by both tools, and I think both of these tools provide useful information since there is no “standard” way to combine all possible associated SNPs associated with a particular disease.

I will focus on my increased disease risks, but the same principles could be applied to decreased disease risk, drug response, or any other trait.

All Diseases with Increased Risk

NOTE: Percentages refer to percent of individuals with my genotype that have a particular disease, and the relative risk compared to average percentage is given in parentheses.  Percentages are not given for Promethease results because the percentage provided in the summary report refers to the population frequency of the SNP and not the percent of individuals with that SNP that will have a particular disease. Only Promethease results with clearly defined disease names and relative risk values were considered.   Promethease cutoff chosen based upon change in color from pink to red in summary report (and also the number of associations listed at this threshold).  23andMe risk assessment was recorded on 2/26/2011.  Promethease report was generated on 1/27/2011.  Multiple values are provided for Promethease but not 23andMe because promethease provides risk assessments for individual SNPs whereas 23andMe provides a single risk value for each disease.

Overall, I thought that there was pretty good agreement between the two methods.  This may not be apparent from the table above, but that is because my list of “higher importance” SNPs is considerably smaller but with greater overlap.  For example, I would have ideally preferred to look at SNPs with a 1.5x increase in risk and an absolute risk greater than 50%. The absolute cut-off of 50% is because I would prefer to look at SNPs where I am more likely to get the disease than not get the disease.  The 1.5x (or 50% increase in risk) is a somewhat arbitrary cutoff that is loosely based upon my microarray data analysis experience.  Since no SNPs meet both of these criteria, I chose to look at those with a greater than 1.5x relative risk and greater than 5% absolute risk (which, in my opinion, is still quite low).  Now, take a look at my more subjective SNP list.

 “Higher Priority” SNPs

Now, 2 out of the 3 SNPs have similar predictions.  Although there wasn’t a high magnitude SNP in promethease for venous thromboembolism, this could be because I subjectively considered this disease to be less well known than arthritis or diabetes, so I figured less popular diseases may have lower magnitude scores.  For this reason, I decided to look into what SNPs are used by 23andMe and promethease to determine venous thromboembolism risk.  I also checked the Genome-Wide Association (GWAS) Catalog to try and get a idea which SNPs are the best established (according to the US National Human Genome Institute).

SNPs Associated with Venous Thromboembolism Risk

	23andMe	Promethease	GWAS Catalog
rs6025	Yes	Yes	No
i3002432	Yes	No	No
rs505922	No	Yes	Yes

NOTE: Promethease lists 19 SNPs associated venous thrombembolism.  In order to simplify the table (and avoid listing some potentially inaccurate and/or low-confidence associations), I have only listed SNPs listed by 23andMe or the GWAS Catalog.

Now there is agreement between the 23andMe and Promethease results because both tools indicate that I have a mutation in rs6025, which results in an increased risk of developing venous thromboembolism.  However, I think it is worth pointing out that the results are not quite as clean as they could be.  For example, this SNP was not listed in the GWAS Catalog, and I couldn’t determine the dbSNP annotation for i3002432 (so it was relatively hard for me to cross-reference this result with other databases).

Another topic that is worth considering is family history.  Before I saw my results, there were 3 diseases that I wanted to check due to family history: type I diabetes, type II diabetes, and macular degeneration.  Thus, it was interesting to see type I diabetes come up in both reports.  Although I doubt that I will get type I diabetes (since the absolute risk is low and this disease usually appears during childhood), this information may still be useful if these mutations have other affects and/or increase the likelihood of children inheriting type I diabetes.

On the other hand, I didn’t see results indicating a increase in risk for type II diabetes and there were some conflicting results about macular degeneration.  Of course, family history is not a gold standard, and I may very well never develop type II diabetes or macular degeneration.  However, I think it is important to think carefully about ambiguous or uncertain results.  For example, this could be done by comparing SNP association to family history as well as considering both genetic and non-genetic risk factors for disease (the later is the topic of my second post).