Informal Notes: Additional Research on APOE variants for Increased Risk of Late-Onset Alzheimer's Disease

[this set of notes branched out from this blog post; with 2 similar / partially identical paragraphs] 

I found it hard to find cohorts with individuals greater than 80 years of age in the AlzGene database (and 23andMe was reporting that is the age interval when onset was most likely, and risk was most increased).

To be fair, I also noticed that a recent study by Licher et al. 2019 reported Low-Risk Onset with an average age of 85.5 and High-Risk Onset with an average age of 81.3 (meaning individuals must have been over 80 at some point).  However, they grouped both E3/E4 individuals (like myself) with E4/E4 individuals (who should be at noticeably higher risk) in the "High-Risk" group.  The CDC also provides a short review here.

There is an earlier paper by Corder et al. 1993 reports "mean age at onset decreased from 84 to 68 years," but here were less than a dozen E4/E4 individuals for each gender in that paper (and the maximum risk of 90% seems high compared to other studies).  To be fair, Farrer et al. 1997 also reports an earlier age of onset with more samples (closer to 755 Caucasian E4/E4 individuals from meta-analysis; 14.8% of 5107 cases).  However, with that later study, I would kind of like to see some error bars (and ideally see individual points and/or be able to download an Excel / tab-delimited text / comma-separated text file with APOE genotype, disease status, age of onset, gender, ethnicity, and cohort / batch / family ID).

Myers et al. 1996 report an E4/E4 age of onset closer to 80 years (for 55% of E4/E4 individuals); however, the total percent of individuals developing Alzheimer's Disease is noticeably lower for E3/E4 and E3/E3 (27% and 9%, respectively) as well as having a later onset of closer to 85 years than 80 years.  Unfortunately, I don't have access to that later information, to check additional details.  It also doesn't look like 23andMe directly cites these papers (but I think these are what are discussed in review articles), but they report something more similar to Myers et al. 1996 (and Genin et al. 2011, which I do have access to).

Also, to be fair, my 23andMe Report says "Approximately 40-65% of Alzheimer's patients have one or two copies of the APOE ε4 variant. However, many people with the APOE ε4 variant will not develop late-onset Alzheimer's disease" (citing Alzheimer's Association 2016).  This probably matches the 55% APOE E4/E4 onset (and an indication that E3/E4 individuals like myself are increased risk, but are still more likely not to get the disease).

There are also different genes (such as APP / PSEN1 / PSEN2) which are more associated with early-onset Alzheimer's disease (which I found from this CDC link).

While a slightly different topic, my understanding is that the previous content from the 23andMe forums will be deleted.  So, to copy over some of the main points here, the 23andMe scientific report describes the "General population" risk estimates for individuals over 85 to be 11% for males and 14% from females.  I noticed that the overall risk estimates for individuals over 85 from other sources were numbers like 25%, 50%, and 50%.  Another member of the 23andMe community passed along a link to a PDF of the World Alzheimer Report 2018 from Alzheimer's Disease International; while a bit hard to find that same document, I do see the prevalence values that I mention in this article (which is "3% of people age 65-74, 17% of people age 75-84 and 32% of people age 85 or older have Alzheimer's dementia.").  If you check the reference in this CDC post, then Hebert et al. 2013 indicate previous and projected frequencies of 32% to 37% in Table 1.  I think this leaves some questions unanswered, but I think also the younger age estimates are more similar (and I would guess it is easier to collect data from those younger than 85).  So, I thought the feedback and discussion was helpful.

Change Log:

9/14/2019 - public post date
10/3/2019 - add link for CDC review

8/21/2021 - add overall frequency notes from 23andMe forum

Informal Notes: Pathogenic Variant Risk for BRCA1/2 Mutations

[this set of notes branched out from this blog post] 

I think the estimates of 50% risk for breast cancer and 30% risk of ovarian cancer (in this infographic from the CDC) are in line with that I was expecting (although that doesn't capture mutations in BRCA1 being higher risk than BRCA2).  There is also this page with 60-75% risk for BRCA1 carriers and 50-70% risk for BRCA2 carriers (which I learned about from this Twitter reply).

Importantly, because of that Twitter communication, I read the book "Resurrection Lily" by Amy Byer Shainman.  I think this provides a very poignant perspective of what is like for yourself and/or your friends to go through either breast cancer treatment or prevention strategies (including up to preventive surgeries).  There are also multiple pages for risk estimates at the end of the book (pages 253 and 262-263 in my copy of the book).

Before I learned about that book, I think I would mostly typically refer to the Stanford BRCA Decision Tool (Kurian et al. 2012) that provides the variance of risk with a few options (although I'm not sure about the the intervals of screening, I don't know what is the relative effectiveness of hormonal therapies, and these estimates are at the gene level when I would expect some specific variants are higher risk than others).

While it is probably not going to be a problem in the future, there was a few days when the website was down.  So, I have attached some screenshots below (for BRCA1, and then BRCA2):

There was a recommendation for BRCA screening with a "B" grade in individuals with family histories, but a recommendation against BRCA screening with a "D" grade for individuals that didn't already have an increased risk of getting breast cancer (which I think is shown most clearly on the US Preventive Services website).  While the context is different, I think this figure from Biesecker 2019 shows one example of how filtering for prior risk may help (although not specifically for BRCA1/2).

While the topic of treatment strategies is a little different, I did notice some different number on an NCI Prevention Tweet (going back to topic of the range of risk estimates).  For example, that number seemed noticeably different for BRCA2, and the total risk reduction (particularly if you focus on death from breast cancer) also seemed different that the text in that Tweet (compared to what I see in the BRCA Decision Tool).

I also think I had another interesting conversation on Twitter here, some of which was converted into notes as a blog post (in terms of the overall prevalence of cancers where variants in moderate-to-high risk genes could be found).

There are some NCCN guidelines, although I thought those were more clear for criteria for screening versus recommendation for surgery in a BRCA-positive individual (which supports use on a "case-by-case basis").  Nevertheless, there is a lot of information available if you register for an account in this document, where some details for the "Bilateral Total Mastectomy" are on page MS-24.  Nevertheless, if this implies that people who don't qualify for the NCCN screening criteria (but had a test result, for some reason) are less likely to benefit from surgery, then perhaps that is helpful for making decisions.

The CDC has guidelines to define "average," "moderate," and "high" hereditary breast cancer risk.  I think their guidelines for genetic testing are similar to the NCCN and USPSTF (but you might find that website easier to read, and this page mentions that the USPSTF recommendations may affect health care coverage).  They also have an additional link for mammogram screenings that I didn't previously know about (on this page).

While I think there are some specific things that can be improved (for communication with non-scientists and communicating ranges for estimates of risk for specific variants, for example), I believe free, publicly-available resources like BRCAExchange.org should play an important roles in helping patients learn more about their results.  ClinVar also provides some information, for variants in general.

For example, I believe these are the 3 BRCA1/BRCA2 variants covered by 23andMe: rs386833395, rs80357906, and rs80359550.

The mutation described by the author of "Resurrection Lily" was referred to as "BRCA1 #5385 insC" as well as "BRCA1 #5382".  The book includes some references to ClinVar, but I don't believe I saw the rsID.  However, I believe those names refer to this variant in BRCA Exchange and this variant in ClinVar (based upon this Hamel et al. 2011 paper, and the synonyms in the database listings).  That makes this is second of the 3 variants tested by 23andMe above.

I am not sure about other available estimates.  However, there are selected genes with high (or highest?) lifetime risk variants for 7 cancer types (including breast and ovarian cancer) on this page from JScreen.

You can listen to some personal perspectives from a patient advocate in this podcast from DNA Today.  One statistic that caught my attention was that 1 in 40 Ashkenazi Jewish women have a mutation in the BRCA1 or BRCA2 genes.  I would also find that statistic on this page from the CDC.  I believe that page is combining pathogenic variants from the BRCA1 and BRCA2 genes when reporting "About 50 out of 100 women with a BRCA gene mutation will get breast cancer by the time they turn 70 years old".

There are also various ways to see the influence of ENIGMA on BRCA1 and BRCA2 variant annotations.  For example, BRCA Exchange includes pathogenic variant annotations from ENIGMA and ClinVar.  This page provides information for ENIGMA annotations in ClinVar, and there is also an ENIGMA BRCA1/BRCA2 expert panel in ClinGen (related to "Variant Pathogenicity" for BRCA1 and BRCA2).

Change Log:

9/14/2019 - public post date
11/12/2019 - add link to BRCA decision tool paper; website not currently working, but I will add some screenshots later (to show substantial difference in risk at the gene level for BRCA1 versus BRCA2)
11/20/2019 - add screenshots for BRCA Decision Tool.
12/2/2019 - add prior risk venn diagram link

7/6/2020 - add "breast cancer" label

8/16/2020 - add additional Penn/Basser link for risk estimates

8/22/2020 - add BRCAExchange link

10/25/2020 - add Resurrection Lily link

2/23/2022 - correct typo

12/1/2023 - add JScreen link (after listening to this podcast)

1/21/2024 - add additional DNA Today link as well as CDC Link for BRCA variants in women with Ashkenazi Jewish ancestry.

1/22/2024 - after receiving helpful feedback from GenomeConnect / ClinGen staff, add links for various types of ENIGMA annotations.

Informal Notes: Collection of References Regarding the Frequency of Pathogenic Mutations in Moderate-to-High Cancer Risk Genes

While I typically prefer to keep Twitter responses less formal than blog posts (which in turn are less formal than pre-prints or peer-reviewed journal articles), I feel kind of bad continuing to add citations to an earlier discussion thread.

So, I thought I would copy the notes here, and provide information for those that are interested (without having all the notices go to the person with the original response):

BRCA Exchange tries to provide some variant information (for BRCA1 / BRCA2)

data.color.com also provides some information about specific variants (but counts are often low).  Color also has this page for Breast Cancer Awareness Month (October).

Ambry provides an Interactive Prevalence Tool (in collaboration with Mayo)

Stanford BRCA Decision Tool provides some statistics to guide discussions about risk prevention options (although that relates more to risk than total frequency; however, this with total numbers is essentially what I want to see)

MSKCC lists total inherited breast cancer rate at 5-10%

There is a link from the CDC website listing the BRCA1+BRCA2 rate for hereditary breast cancer as 3% for breast cancer and 10% for ovarian cancer.  If you sum the frequencies, that is somewhat close to LaDuca et al. 2019.

There is also a different source of information from the CDC, mentioning for all hereditary breast and ovarian cancer (which must be greater than the sum of BRCA1+BRCA2), which was 5-10% and 10-15% respectively.

Offit 2006 

• Editorial about BRCA mutation frequency and risk

Hu et al. 2018

• Table 2 shows some percentages per gene

LaDuca et al. 2019

• Learned about from @kristinclift
• GenomeWeb review mentions "13.8 percent of ovarian cancer patients carried germline pathogenic variants in at least one of the 32 genes tested"
• Supplemental Table S7 also shows a higher BRCA1/2 ovarian cancer percent (3-5%, OC) than breast cancer percent (1-2%, BC)
• There are all high-risk patients 
• Total numbers are fairly different: 66,954 BC, 9,106 OC, 1,087 BC+OV.
• Supplemental Table S6 has gnomAD control frequencies, but I think variant calls may need to be more specialized for targeted gene panels.
• In other words, those percentages look low compared to that matched control study, but they do provide those details.
• I also think they used results from the reports from different Ambry panels, rather than obtaining and re-analyzing raw data independently.  So, I wonder how much of an effect that had.

Unpublished (?) CARRIER Study Data

• In a CARRIERS plot (a PDF from a Clinical Cancer Genomics Conference presentation that I don't know if I have permission to post), getting control variants for BRCA1/2 below 0.4% puts BRCA1/2 case mutation rates at under 1.4%.
• I think that is for breast cancer.
• Plots for 14 individual studies (for a total of 10,000s of samples, with matched controls) were shown for 21 genes of with overall case rate of ~6% and control rate of ~2.5%, as well as 17 higher-risk genes with overall case rate of ~5% and control rate of ~2% (which I guess could up to a 30% “false positive” rate either way).

Variability in Variant Calling

• May need more specialized variant calling for targeted gene panels - Warden et al. 2014
• For example, notice the difference in scale for the y-axis in Figure 9, where the relative “novel” variants in controls is a proxy for false positives:
• You may get better concordance between variants with reprocessing (in this case, using a more typical processing strategy for WGS and Exome Data) - blog post on custom scripts and precisionFDA comparisons.
• In addition to data.color.com, I think cBioPortal can be a useful research to look at mutation information across different cancer types and studies
• cBioPortal has some tutorials that can be viewed here
• For example, I think I could see results more similar to what I read elsewhere (with BRCA2 being found at higher frequencies) if I removed variants of unknown significance
• I think 47:45 - 51:55 of this webinar also gives some useful caveats to mutation and copy number calling that might be worth taking into consideration (where a region that is supposed to have a homozygous deletion has a variant with an allele frequency that you would normally consider a match for a heterozgyous variant, when a true homozygous deletion call shouldn't have any variants)

Polygenic Risk Scores

These are arguably more for risk assessment rather than frequency (although the risk estimate vary across the population).

Nevertheless, I would also be interested in seeing more results from Myriad myRisk and AmbryScore-Breast Polygenic Risk Scores (PRS).  This is in part because I haven't been highly satisfied with the polygenic scores that I was able to apply to myself, but I should note that clinical features are included in the calculation for these scores (beyond just the genetic information).

For example, I noticed that some more information Myriad myRisk was provided in these slides, which I believe reference this announcement.  I believe that is a reference to the Hughes et al. 2020 and Gallagher et al. 2020 papers.  However, what caught my eye was this figure, which I don't think it is directly from those publications?

I am not sure if I am correctly understanding that both Myriad myRisk and AmbryScore-Breast use "clinical history" information?

As a possibly separate point, I thought Figure 2 of Fahed et al. 2020 was interesting because of the difference in the range of risk estimates by PRS with versus without a BRCA1 or BRCA2 mutation.  The stratification without being a BRCA1/2 carrier was more limited.  However, I would be interested to get a better sense of how PRS stratification compares to variants in or near the BRCA1 or BRCA2 genomic footprint.  I think the later more along the goals of resources like BRCA Exchange.

Those interested in these notes may also be interested in this post with notes on the range of risk estimates.

Change Log:

9/9/2019 - public post date
9/10/2019 - add "informal note" category, along with link to original response
9/13/2019 - add CDC links, as well as some extra information not previously copied over from earlier Twitter discussion
10/10/2019 - add Color link for BRCA1/2 mutation frequencies
11/12/2019 - add link to other blog post
5/8/2020 - add cBioPortal notes

7/6/2020 - add "breast cancer" label
7/7/2020 - add note about interest in hearing about a range of PRS experiences.

8/14/2020 - add additional PRS links

8/16/2020 - minor change

3/9/2021 - add link for Ambry Prevalence Table

4/23/2021 - move link from earlier blog post to this blog post

6/26/2022 - add link to PRS within BRCA1/2 carriers

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.

Gene Patents and Genetic Testing

NOTE: Getting Advice About Genetic Testing

This week, Angelina Jolie wrote an editorial for the New York Times describing how she underwent a double mastectomy after testing positive for a deleterious BRCA1 mutation.

This article stirred up a lot of discussion because she mentions how "[the] cost of testing for BRCA1 and BRCA2, at more than $3,000 in the United States, remains an obstacle for many women".

Although there have been responses pointing out that insurance can significantly decrease the out-of-pocket costs to the patient (under the right circumstances), the question remains "Why is the test so expensive?".  After all, the true cost to perform the test is much less than $3,000.

The genetic test in question is Myriad's BRACAnalysis test.  This company should sound familar because the Supreme Court recently heard a case from Myriad to decide if human genes can be patented (the BRCA1/2 gene patents are the reason why the Myriad test costs so much).

There are lots of resources to learn more about the court case and BRCA testing.  For example, Chris Mason recently wrote good summary on the topic.  However, I want to re-emphasize a couple important points here:

1) It is possible to provide a genetic test covering a panel of diseases at ~1/10th of the cost.  For example, 23andMe provides carrier status for a variety of diseases (including some BRCA1/2 mutations) for $99.  Likewise, Counsyl offers genetic testing that is less than $100 with insurance or less than $1000 without insurance.  There are also various options for discovering mutations in raw sequencing data, whose cost is continually decreasing.

2) The basis of Myriad's claims to retain its patents is the high development costs to develop the test.  Regardless of the ethical arguements against gene patients (and the high likelihood that genetic tests will be based upon findings from government-funded research), this is no longer a technical concern now that the human genome has been sequenced.  There a multitude of freely available tools to help clone any region of the human genome.  There are certainly still novel discoveries out there (like novel non-coding genes, fusion genes, etc.), but I would argue the tricky part is asking the right question - the production of the cDNA is then trivial.  I see no reason why individuals should have to pay for the costs of a patent for the interpretion of a medical discovery reported in the scientific literature.

Notes on AGBT 2013

I've organized my notes from AGBT, which you can download here.  I know a lot of people were not able to attend the conference, so I hope this is helpful in addition to all the other comments from the twitter feed (HT @Massgenomics for the Google Docs link).

There were a number of interesting talks on clinical genomics, sequencing technology, and bioinformatics.  There were also a few very interesting metagenomics talks.  I don't know a whole lot about this area, but the talks certainly got me interested in learning more about this topic.

Aside from the interesting science, there were some nice features about the conference (catered meals, lots of freebies, etc.), but I also feel like there was some room for improvement.  For example, I wish they ended the conference a little earlier on the last day in order to make it easier to catch a flight out of Florida.  Also, I personally prefer conferences that take place in major cities (that don't require a 1-hour shuttle to get to the airport), although I'm sure there are varying opinions on this matter.

Finally - all minor complaints aside, I am very grateful to be able to attend this conference and present a poster for my new DNA methylation algorithm (COHCAP - City of Hope CpG Island Analysis Pipeline).  For those that couldn't attend the conference, COHCAP is an algorithm that quantifies the consistency of methylation patterns for CpG sites within CpG islands (for Illumina methylation array data and targeted BS-Seq).  The paper is currently under review, but the algorithm is currently available to download and I'd be glad to answer any questions that you have about it.

Should the FDA regulate direct-to-consumer genetic testing?

Last week, Walgreens reversed its decision to provide "spit kits" for Pathway Genomics' genetic tests due to a letter from the FDA requiring Pathway Genomics to either get FDA approval or explain why they are exempt from approval.  This week, CVS also made a similar decision to postpone selling of the Pathway tests.

Recently, I have noticed a number of blog posts that seemed to side with the FDA.  For example, 80beats has criticized the Pathway Genomics tests in terms of usefulness, legality, and unpredictable public response.  Genomeboy has complained that Pathway Genomics is not being very transparent in terms of explaining their analysis (especially in comparison to 23andMe).

I agree that a lack of transparency and usefulness would be serious problems for genetic tests.  As mentioned in my first blog post, there are indeed many problems with the current accuracy of genetic tests (in terms of discrepancies between companies, incorrect prediction of clearly known characteristics such as eye color, etc.).  I think it is also essential that companies provide you with your SNP data so that you can try to seek alternative opinions regarding how to interpret the genetic test.  I was also very disturbed that the CSO of Pathway Genomics claims that "[Pathway Genomics] don't feel that [they are] practicing medicine" even though they wish to sell genetic tests in a drugstores.

That said, I think FDA regulation should only be used as an absolutely last resort.  First, I think many other criticisms are not warranted.  For example, the Wall Street Journal has a nice article about how the negative public response to genetic tests has been exaggerated.  Second, I think it will be valuable for consumers to have access to objective analysis of the accuracy and usefulness of commercially available genetic tests (either conducted through public or private means), but I don't think that necessarily has to be done through FDA regulation.  For example, a large database (perhaps something like PatientsLikeMe) of genetic test results, medical history, and lifestyle changes can help provide the necessary information to consumers.  It will take a significant amount of time to throughly examine these genetic tests, and I think this analysis can be conducted much quicker (and perhaps even better) if the public has direct access to the tests.

I would be ok with some sort of warning label that the tests are not completely accurate and other analysis should taken into consideration when making medical decisions, but I think it would be too extreme to completely remove these tests from the market.