PMS, Genetics, and Solutions (Patrons Only)

A lot of women know the moodiness and brain fog that comes with premenstrual syndrome (PMS).  It can range from simply feeling irritable and icky to being something that really interferes with our lives.

What role do genes play in PMS?  It has been shown in the past few years that there is a genetic component, especially for a severe form of PMS called premenstrual dysphoric disorder (PMDD). PMS is thought to affect about 30-40% of women, while PMDD is rarer and affects only 3-8%.[ref] One 2011 study of twins estimated that heritability of PMS was around 95%.[ref]

Neurotransmitters cause some of the symptoms of PMS and PMDD. Serotonin is an important neurotransmitter involved in mood stability.

Estrogen is a serotonin agonist, and fluctuations in estrogen levels also affect serotonin levels. GABA, another neurotransmitter, is also involved in PMS symptoms for some.

Genes involved in PMS and PMDD

 

The rest of this article is available to Patrons via Patreon.  Thank you to all of you who support Genetic Lifehacks on Patreon!

 

Ancestry.com vs 23andMe: Comparing the raw data files

I recently picked up an AncestryDNA kit out of curiosity to find out how well the data matched up to the 23andMe test that I did a few years ago.  Quick answer: It matched up better than I expected.

First, a couple of caveats:  
I’m not a genealogy expert and was not comparing the two tests as far as accuracy of determining my ancestry.  I’m also not a statistician, so the mathematical comparisons of the raw data files are just the basics.

Taking the test:
Both companies are fairly similar in the simplicity of getting the testing done.  You order the kit — either through the company websites or through Amazon.com — and it comes in the mail.  The box contains a vial to spit into, instructions on how to register the kit, and a small pre-paid shipping box to mail the vial back to the company.

Both 23andMe and Ancestry.com advertise that it takes 4 – 6 weeks to get the test results back after they receive your vial of spit.  It was faster than advertised (about 2 weeks for AncestryDNA) when I did the tests, but I think the times can vary depending on how busy the lab is when you send in your test.

The privacy policies:
Privacy policies: 23andMe.com Privacy Policy, AncestryDNA Privacy Policy  Read the terms of service and the full privacy policy.  Make sure you understand and are ok with them before you order your kit.

Once you have taken the test, you also have the option of answering research survey questions on 23andMe and on Ancestry.com.  Be sure that you understand that you are giving your survey information to the companies to use for their own purposes.

Downloading the raw data:
Both companies allow you to download and keep your raw data file.  I highly recommend that you do so as soon as you get the results.  The information is yours, and you should keep it safe.
Here are directions on how to download the raw data:
Download your genetic data from 23andMe.com
Download your genetic data from AncestryDNA

Both companies also have a clearly stated way to delete your data from their records if you choose to close your account with them. Here are the directions:  Deleting your 23andMe account; for AncestryDNA, there is a button to delete data right under the download link on your settings page.

Searching your raw data online:
23andMe.com has a convenient interface for searching through your raw data on their website.  It is in their Tools section, under Raw Data.   You can search by rs id number or by gene name.  AncestryDNA does not seem to have this option.

Using your raw data file:
The raw data file for both companies comes as a zipped text file.  Both files include the rs id #, chromosome, position, and your genotype.  AncestryDNA’s data is formatted a little bit differently in that the genotype is given separately as “allele 1” and “allele 2”, where 23andMe combines the information into a “genotype” column.

You can simply open up the text file on your computer and do a “Find” to search for a rs id number.  Everyone should have the ability to open a text file on their computer, no matter the operating system.

A better option (in my opinion) is to import the text file into Excel.  To do so, open a new Excel Workbook and click on the Data tab.  There should be an icon there labeled “Text” that will let you import a text file.  Both the 23andMe and AncestryDNA files are tab delimited.  Simply accept all of the default setting in Excel for the text import.

Importing it into Excel then gives you the option of using a second worksheet to make notes on what you learn from your genetic data.

23andMe raw data imported into Excel.

Comparing the raw data files:
I decided to compare my 23andMe (v. 4) data file with the AncestryDNA file.  23andMe gives data for over 600,000 nucleotide base pairs, and AncestryDNA’s raw data covers over 650,00 base pairs.  Comparing the two files, there were over 303,000 rs ids in common between the two.  (This isn’t a completely accurate comparison since 23andMe reports some of the chromosome positions in a proprietary i-number format instead of as a rs id, but it is close enough for my purposes.)

Of the ~303,000 rs id’s in common, for my data, there were just over 1,000 for which the genotypes did not match.  This comes out to 0.3% that did not match — or, alternatively, 99.7% that did match.

Which test is more accurate?
Knowing that for my data the two data files matched for 99.7% of the data actually doesn’t tell me anything as far as which one is ‘correct’ for the ~1,000 genotypes that differed.  Neither company guarantees that their testing is accurate, and both companies are very up-front about it with disclaimers stating that it isn’t being offered as a medical test.

I was actually expecting the mismatch percentage to be higher between the two tests.  While I’m not an expert on error rates in genetic sequencing, several studies that I had read lead me to expect that there would be more variation in the tests.

Final thoughts:
Everyone who is doing either AncestryDNA testing or 23andMe testing needs to read the privacy policies and also understand that the data shouldn’t be used as the only basis for making major medical decisions.  I’m fine with a little uncertainty in looking at my genetic data for something like deciding that I should eat more foods that are high in choline or add in more leafy greens for folate.  Any major health decisions should always be double checked with a test ordered through a lab certified for that test.

Enjoy this comparison and planning on buying a test kit?  I would appreciate you using my referrer link, which will cost you nothing but help me keep on blogging.

Review of Genos – Whole Exome Sequencing

Screen Shot 2017-03-13 at 3.40.18 PM

UPDATE:  Genos was bought out by another company…  Good reminder to read through privacy policies!  The company that bought them now owns customer’s data but said they would abide by the Genos privacy policy.  I did ask for my data to be deleted and account to be removed out of an abundance of caution.

————

Genos is a fairly new company in the direct-to-consumer genetic sequencing market.  They offer sequencing of the whole exome, instead of just the specific locations that are covered by services such as 23andMe or AncestryDNA. Moreover, they are bringing in research study partners that then will pay their clients for participating in the studies.  It is definitely an interesting business model and one that may end up being a game changer for the genetic sequencing market.

I was intrigued enough to go ahead and try it out and will share what I have learned from the experience. (Yep – this was my birthday present this year!)

First off, sending off the saliva sample was similar to the way 23andMe does it — spit in a tube, register online, and send it off.  Nice and simple process.  The Genos website was easy to use as far as ordering and registering the sample.  The wait time was a little over two months to get the results back, which is a bit longer than 23andMe, but Genos is brand new and was still in beta when I ordered.

Screen Shot 2017-03-13 at 3.40.00 PM
Genos Website – www.genos.co

When my data finally came in, I was eager to dig in and geek out with it. The Genos website offers a variant viewer that compares my results with ClinVar, which is an NIH-funded database of genetic variants that have been submitted by various sources.  The database marks the variants as pathogenic, benign, or somewhere in between, and it is a good source of information about rare genetic diseases.

While the Genos variant viewer was interesting, there seems to be a lot of information submitted to ClinVar showing a variant to be both benign and pathogenic. And for me, personally, it didn’t show me a lot that I didn’t already know from 23andMe testing. I would imagine that it may be useful for some people in terms of carrying rare genetic diseases.  Keep in mind, though, that Genos is only sequencing the exome.

So what is an exome?  Of the 3 billion plus nucleotide base pairs in our DNA (the A, C, G, and T’s), only a small portion actually make up the coding part of genes.  On each of our 23 pairs of chromosomes, there are sequences that code for genes and then sections that are called non-coding, which have to do RNAs, telomeres, regulatory elements, etc.  Basically, in DNA, genes code for proteins which are made up of amino acids. Most genes have portions of the DNA sequences that code for amino acids (the exons) and then portions that don’t code for part of the protein (introns).  The whole exome is then the sum of all the coding parts of the gene.  While a lot of the serious, rare genetic diseases are a result of variations in the exome, the non-coding parts of our DNA not sequenced by Genos also play a big role in our health as well.

Screen Shot 2017-03-13 at 3.39.42 PM
Genos Website

Genos offers a download of your data as a VCF file.  This is where it got complicated for me.  I was under the impression from their website copy that I would be getting 50 million rows of data, and I thought I would need to figure out how to dig through that big of a file with lots of rsIDs and my genotype.  What I downloaded was about 300,000 rows of data with just the HGSV nomenclature and no rsID’s included. Hmmm….  After several emails back and forth with their customer support and bioinformatics department, I finally got a bit of a grasp on what was contained in the VCF file.  Basically, it is everything in my exome that is different from the reference data.  This doesn’t mean that it is everything that is heterozygous or homozygous for the minor allele (a bad assumption on my part), but it is just everything that is different from a reference file.  So I’m going to have to spend some time this summer learning more about bioinformatics and VCF file types in order to get anything out of my whole exome file.  Definitely not an easy way to unlock my curiosity.

The other file that Genos offers for download is a Promethease formatted file.  This allows you to use Promethease (for $5) to compare all of your data against the SNPedia database.  The file is formatted similarly to the raw data file you can download from 23andMe.  Again, I personally learned a lot more from my 23andMe results than I did from my Genos results in Promethease, but your mileage may vary on this as well.

Since I have all my 23andMe data imported into an Excel spreadsheet, I imported in my Genos “Promethease” file to compare the two.  This is where it got interesting for me!

Screen Shot 2017-03-13 at 3.39.32 PM
Genos website

The Genos genotype file (Promethease file) had about 43,000 rsIDs in it, and I compared those to the 600,000+ rsIDs from 23andMe. A few formatting tweaks, merging of the data and I was on my way to seeing how closely the data matched.  Out of the 600,000 data points from 23andMe and 43,000 data points from Genos, only 4,433 were common to both.  (Granted, 23andMe uses “i” numbers instead of rsID’s sometimes, so there could be more in common between the two files than what I could easily count.)  Of those 4433 rsID’s in common, 25 were different between

Of those 4433 rsID’s in common, 25 were different between Genos and 23andMe which is about a 0.5% error/difference rate.  I have my parents’, my husband’s, and my children’s 23andMe data (in a nice spreadsheet, of course), and looking at the inheritance pattern there were 2 spots where 23andMe is probably wrong on my variants (and Genos is probably right).  There were several more spots where Genos was probably wrong and some heterozygous calls that I couldn’t determine which was correct.

I emailed Genos customer support about the differences between the files, and the head of the bioinformatics department pointed me towards a study showing the accuracy of the sequencing.  A 0.5% error rate was actually about average…  This was eye-opening to me.  Even though I knew that there was a possibility for errors, realizing that 1 out of every 200 could be wrong drives home the point that no one should make major health decisions based on this data.

To sum it all up…

  • I like the goals of Genos and that they recognize that customers should be compensated for participating in research studies.  This is a big contrast to 23andMe asking customers to give away information for free.
  • I personally didn’t find the information received from Genos, though, to be worth the price.   The variant viewer on the Genos website was somewhat interesting, but the information out of ClinVar is too narrow in its scope.  It would be great to have something like the gene lookup function that 23andMe has to really be able to know what your genotype is for a specific rsID without the need to conquer the VCF file format.
  • Keeping in mind that Genos is new to the game, things may change on their website and with what they offer to their customers.  Do check with them if you have questions.  Their customer support response sometimes took a day or two, but they were good at patiently answering my many questions.

 

How to Download Your 23andMe Data

How to download your raw data file from 23andMe
How to download your raw data file from 23andMe

Someone asked me recently how to download their data from 23andMe.   So, here is a quick tutorial if anyone else is searching for their raw data file on the 23andMe website.

Why download your data? It is yours, and it may be something you need in the future.  23andMe could change their policy on allowing downloads, or they could go out of business at some point.  Seriously – everyone should go ahead and download their genetic data file and keep it in a safe place.

Downloading Your Raw Data from 23andMe

Step 1: Go to www.23andMe.com and log in with your password.

Step 2: On the top navigation bar, put your mouse pointer over the word Tools.  A drop-down appears with a link to go to Browse Raw Data.

download

 

Step 3: Click on the Download link.

download2

Step 4: Scroll down to the bottom of the download page (yes, read it as you scroll :-).  There you will click the button to request to download your data.

 

Step 5:  It takes several minutes for the download to be ready.  23andMe will send you an email, or you can just refresh the download page again in a few minutes.

Step 6: Get geeky with your info and put it into an Excel spreadsheet.

Checking Your Carrier Status for Genetic Diseases

Carrier StatusThe term “carrier status” when applied to a genetic disease usually means looking at whether or not you are heterozygous (have one copy) for a mutation that causes a Mendelian genetic disease. Generally, these are the rare diseases that you would need two copies of the variant to have the disease.

Take cystic fibrosis as an example…  the Cystic Fibrosis Foundation explains that “People with CF have inherited two copies of the defective CF gene — one copy from each parent.  Both parents must have at least one copy of the defective gene.  People with only one copy of the defective CF gene are called carriers, but they do not have the disease.”

A word of caution before you go any further!  While genetic information from 23andMe or a similar DNA test is generally accurate, always re-confirm with a more accurate test before making a major health decision.  Also, the information from studies that I’ve listed below could be inaccurate.  Check and double check before you do anything with the information below.  Seriously!  There are companies out there that do genetic testing and counseling if you are looking for information before having a baby.

It is also important to know that researchers are discovering new things all the time about rare genetic diseases, such as this Nature article that looked at over 500,000 people’s genes and found that there are people have that have a mutation for a genetic disease without symptoms.  This is a fairly new science, and researchers are still making discoveries all the time.

So with all the caveats above, why even look into your carrier status for genetic diseases?  If you have kids already, it may be important to let them know if they are possibly a carrier for a genetic disease.  Others in your family may also be affected.

For most of the diseases listed below, being a carrier generally means you are not affected by the disease, but for some diseases, it is possible to be mildly affected. In general, when someone is heterozygous, the normal, healthy allele (version from one parent) can compensate for the allele (version from the other parent) that isn’t working. But take hemochromatosis as an example– it is possible for someone who is heterozygous to have issues with iron overload, and men especially should keep an eye on their iron levels.

For more information on inheritance, www.yourgenome.org has a nice explanation.

The list below is in no way complete and is for informational purposes only.  23andMe data only covers a small percentage (less than 1%) of your genome, and this is just a list of SNPs that I’ve compiled along the way.  I highly suggest putting them into an Excel file or installing the SNPtips extension for Firefox as an easy way to see your data.  Some of these are also on the 23andMe health report, if you have purchased that, but there are several listed below that aren’t included in their reports.  All of the information can also be found on SNPedia.com.

Thinking that it is not worth your time to look at rare diseases?  If you consider that there are more than 7,000 rare diseases and that they affect 1 in 10 people in the US, it really isn’t out of the realm of possibility to be a carrier or affected by a rare disease.  Learn more at Global Genes or the National Organization for Rare Disorders.

If you know of other SNPs to add to this list, please add them in the comments below.

Condition Gene SNP Risk Allele (fwd) Notes/References
Agenesis of the Corpus Callosum with Peripheral Neurophathy SLC12A6 i5012573 D rs515726215  more
Agenesis of the Corpus Callosum with Peripheral Neurophathy SLC12A6 i5012575 A
Alpha-1 Antitrypsin Deficiency SERPINA1 rs17580 A Homozygous has 60% of enzyme function.   More of a problem in conjunction with another variant.  more… 
Alpha-1 Antitrypsin Deficiency SERPINA1 rs28929474 T Homozygous usually leads to severe alpha-1-antitrypsin deficiency. Heterozygous may also have increased rate of lung or liver problems. more
Argininosuccinate lyase deficiency ASL rs28941472 G There is both a neonatal form and a late onset form more
Argininosuccinate lyase deficiency ASL rs201523601 T
Autosomal recessive spastic ataxia of Charlevoix-Saguenay SACS i5012578 D rs281865117, more
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5000043 G rs200511261,  (huge list)
Autosomal Recessive Polycystic Kidney Disease PKHD1 i6016630 T rs794727819, classified as likely pathogenic
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5007345 G rs137852948
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5000045 G rs760222236, i6016633
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5000047 C rs369925690
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5012610 D rs398124502
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5000042 G rs137582950
Autosomal Recessive Polycystic Kidney Disease PKHD1 i5012612 A rs137852949
Autosomal Recessive Polycystic Kidney Disease PKHD1 rs28939383 A rs28939383
Beta Thalassemia HBB rs11549407 A  Heterozygous variants can cause a milder form of the disease. more…
Bardet-Biedl Syndrome MKKS rs28937875 T more
Bardet-Biedl Syndrome BBS10 rs148374859 C
Bardet-Biedl Syndrome BBS12 rs121918327 T
Bardet-Biedl Syndrome BBS1 rs113624356 G
Bardet-Biedl Syndrome BBS1 rs35520756 A Though this one is listed as pathogenic, it is fairly common and looks to only add risk with other variants.
Beta Thalassemia / Sickle Cell Anemia HBB i3003137 A rs334, homozygous AA is pathogenic for sickle cell anemia, heterozygous leads to reduced risk of malaria
Beta Thalassemia HBB rs33915217 G
Beta Thalassemia HBB rs33944208 T
Beta Thalassemia HBB rs33960103 G
Beta Thalassemia HBB rs33971440 T
Beta Thalassemia HBB rs33985472 C
Beta Thalassemia HBB rs33986703 G
Beta Thalassemia HBB rs34451549 A
Beta Thalassemia HBB rs34598529 C
Beta Thalassemia HBB rs34690599 C
Beta Thalassemia HBB rs35004220 T
Beta Thalassemia HBB rs35724775 G  read more
Beta Thalassemia HBB rs63750783 T
Bloom’s Syndrome BLM i4000396 I rs113993962
Canavan Disease ASPA rs28940279 C read more
Canavan Disease ASPA rs28940574 A
Congenital Disorder of Glycosylation Type 1a PMM2 i5012679 A read more
Congenital Disorder of Glycosylation Type 1d PMM2 rs28940588 T
Congenital Disorder of Glycosylation Type 1a PMM2 i5012680 A rs28936415
Connexin 26-Related Nonsyndromic Sensorineural Hearing Loss GJB2 i4000434 D rs80338939
Connexin 26-Related Nonsyndromic Sensorineural Hearing Loss GJB2 rs72474224 T may cause only mild hearing loss in some populations
Connexin 26-Related Nonsyndromic Sensorineural Hearing Loss GJB2 i4000435 D rs80338942
Cystic Fibrosis CTFR i3000001 D rs11399360, most common cause of cystic fibrosis
Cystic Fibrosis CTFR rs75961395 A more…
Cystic Fibrosis CTFR rs78655421 A
Cystic Fibrosis CTFR rs121909011 T
Cystic Fibrosis CTFR i4000297 A
Cystic Fibrosis CTFR i4000291 A
Cystic Fibrosis CTFR i4000299 T
Cystic Fibrosis CTFR rs113993959 T
Cystic Fibrosis CTFR i4000301 A
Cystic Fibrosis CTFR rs75527207 A i4000305
Cystic Fibrosis CTFR i4000306 T
Cystic Fibrosis CTFR i4000307 C
Cystic Fibrosis CTFR i4000308 T
Cystic Fibrosis CTFR i4000309 A
Cystic Fibrosis CTFR i4000311 G
Cystic Fibrosis CTFR i4000313 D
Cystic Fibrosis CTFR i4000314 T
Cystic Fibrosis CTFR rs77188391 T i4000315
Cystic Fibrosis CTFR i4000316 D
Cystic Fibrosis CTFR rs76713772 A i4000317
Cystic Fibrosis CTFR i4000318 A
Cystic Fibrosis CTFR i4000319 D
Cystic Fibrosis CTFR rs80224560 A i4000320
Cystic Fibrosis CTFR rs75096551 A i4000321
Cystic Fibrosis CTFR i4000322 D
Cystic Fibrosis CTFR i4000323 D
Cystic Fibrosis CTFR i4000324 I
Cystic Fibrosis CTFR rs75039782 T i4000325
D-Bifunctional Protein Deficiency HSD17B4 i5007145 A Heterozygous carriers may also have problems with the breakdown of fatty acids.
D-Bifunctional Protein Deficiency HSD17B4 i5007146 T
Deglycosylation Disorder NGLY1 rs201337954 A
Denys-Drash syndrome WT1 rs28941778 T
Dihydrolipoamide Dehydrogenase Deficiency DLD DLD i5003700 T more
Factor VIII Deficiency – Hemophilia F8 rs28933681 T
Factor VIII Deficiency – Hemophilia F8 rs28933679 C
Factor IX – Hemophilia F9 i5007022 G Very rare (possibly extinct) form of Hemophilia
Factor XI Deficiency – Hemophilia F11 i4000397 A
Factor XI Deficiency – Hemophilia F11 rs121965063 T i4000398
Factor XI Deficiency – Hemophilia F11 rs121965064 C i4000399
Familial Dysautonomia IKBKAP rs111033171 G i4000334
Familial Dysautonomia IKBKAP i4000400 G
Familial Hypercholesterolemia Type B APOB rs144467873 A i4000339
Familial Hypercholesterolemia Type B APOB rs12713559 A
Familial Hypercholesterolemia Type B APOB rs5742904 T
Fanconi Anemia FANCC rs104886456 A i4000336
Fanconi Anemia FANCC rs104886457 A i4000412
Fanconi Anemia FANCC i4000413 D
Gaucher Disease GBA rs421016 G
Gaucher Disease GBA rs80356773 T i4000386
Gaucher Disease GBA i4000415 C rs76763715
Gaucher Disease GBA i4000417 I rs387906315
Gaucher Disease GBA i4000419 A rs80356769
Glutaric Aciduria GCDH rs121434369 T
Glycogen Storage Disease Type 1a G6PC rs1801175 T i3002486
Gracile Syndrome BCS1L rs28937590 G i5012660
Hemochromatosis HFE rs1800562 A Known as C282Y.
Hemochromatosis HFE rs1799945 G Known as H63D, can cause milder form of hemochromatosis or when combined with rs1800562
Hemochromatosis HFE rs1800730 T Known as s65C, possible causes milder form of hemochromatosis
Hereditary Fructose Intolerance ALDOB i5012664 C rs78340951
Hereditary Fructose Intolerance ALDOB i5012665 D
Hereditary Fructose Intolerance ALDOB rs76917243 T
Hereditary Fructose Intolerance ALDOB rs1800546 G
Kindler Syndrome FERMT1 rs121918293 A
LAMB3-Related Junctional Epidermolysis Bullosa LAMB3 i5012669 A rs80356680
LAMB3-Related Junctional Epidermolysis Bullosa LAMB3 i5012671 A rs80356681
LAMB3-Related Junctional Epidermolysis Bullosa LAMB3 i5012672 A rs80356682
Limb-girdle Muscular Dystrophy SGCA rs28933693 T
Limb-girdle Muscular Dystrophy SGCB rs28936383 C
Limb-girdle Muscular Dystrophy FKRP rs28937900 A
Maple Syrup Urine Disease Type 1B BCDKDHB i3002808 C more
Maple Syrup Urine Disease Type 1B BCDKDHB i4000422 A Known as G278S
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM rs121434282 C i5003116
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM rs121434281 T i5003117
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM i5012755 T
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM rs121434280 C
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM rs77931234 G
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM i5012760 T rs373712782
Medium-Chain Acyl-CoA Dehydrogenase Deficiency ACADM rs121434274 A
Mucolipidosis IV MCOLN1 rs104886461 G i4000425
Mucolipidosis IIIa GNPTAB rs34159654 C pseudo-hurler polydystrophy
Neuronal Ceroid Lipofuscinosis CLN5 i5012678 D rs386833969
Neuronal Ceroid Lipofuscinosis PPT1 i5012622 G more
Neuronal Ceroid Lipofuscinosis PPT1 rs137852695 A
Neuronal Ceroid Lipofuscinosis PPT1 i5012624 A
Niemann-Pick Disease Type A i4000381 C more…
Niemann-Pick Disease Type A i4000383 D
Niemann-Pick Disease Type A rs120074117 T
Nijmegen Breakage Syndrome NBN i5012770 D
Pendred Syndrome SLC26A4 rs121908362 G hearing loss
Pendred Syndrome SLC26A4 rs111033244 G
Pendred Syndrome SLC26A4 rs111033199 T
Pendred Syndrome SLC26A4 i5000696 G
Pendred Syndrome SLC26A4 i5012616 C
Pendred Syndrome SLC26A4 i5012618 C
Phenylketonuria PAH rs5030843 A more…
Phenylketonuria PAH rs5030846 T
Phenylketonuria PAH rs5030847 A
Phenylketonuria PAH rs5030850 A
Phenylketonuria PAH i3003401 A rs5030851
Phenylketonuria PAH rs5030856 C
Phenylketonuria PAH rs5030859 T
Phenylketonuria PAH rs5030860 C
Phenylketonuria PAH i4000467 A
Phenylketonuria PAH i4000470 C
Phenylketonuria PAH rs75193786 G
Phenylketonuria PAH rs76296470 A
Phenylketonuria PAH rs62642932 T
Phenylketonuria PAH rs62642933 C
Phenylketonuria PAH rs62516092 C
Phenylketonuria PAH rs62514953 T
Phenylketonuria PAH i4000478 T
Phenylketonuria PAH i4000479 C
Phenylketonuria PAH rs62508588 T
Phenylketonuria PAH rs28934899 G
Phenylketonuria PAH rs5030841 G
Phenylketonuria PAH rs5030849 T
Phenylketonuria PAH rs5030852 A
Phenylketonuria PAH rs5030853 A
Phenylketonuria PAH rs5030855 T
Phenylketonuria PAH rs5030857 A
Phenylketonuria PAH rs5030858 A
Phenylketonuria PAH rs5030861 T
Primary Hyperoxaluria Type 2 GRHPR i5012628 D rs80356708
Primary Hyperoxaluria Type 3 GRHPR i5012629 D rs180177309
Rhizomelic Chondrodysplasia Punctata PEX7 rs61753238 G more…
Rhizomelic Chondrodysplasia Punctata PEX7 rs1805137 A
Salla Disease SLC17A5 i5012634 A
Sjogren-Larsson Syndrome ALDH3A2 rs72547571 T
Tay-Sachs Disease HEXA i4000391 I
Tay-Sachs Disease HEXA rs147324677 T
Tay-Sachs Disease HEXA rs121907954 T
Tay-Sachs Disease HEXA rs76173977 T
Torsion Dystonia TOR1A i4000446 D deltaE302
TTR-Related Cardiac Amyloidosis TTR rs76992529 A more…
TTR-Related Familial Amyloid Polyneuropathy TTR i3002758 A rs28933979
TTR-Related Familial Amyloid Polyneuropathy TTR rs121918070 G
Tyrosinemia Type I FAH rs80338899 A
Tyrosinemia Type I FAH rs80338898 T
Tyrosinemia Type I FAH i5012865 A
Tyrosinemia Type I FAH i5012867 T
Tyrosinemia Type I FAH rs121965075 T

 

Dyslexia – Genetic Connections

Genetics of Dyslexia

While dyslexia is known to run in families, the role of genetics in dyslexia is still being determined.  Here is a quick look at some of the genes thought to be involved in dyslexia, which affects around 10% of the population.

Two of the genes (KIAA0319 and DCDC2) identified as probably playing a role in dyslexia are involved in neuron migration.  A recent study (Oct. 2016) points to a connection between these genes and cilia, hair-like structures which are present on most neurons.  [ref]

A recent study looked at the interactions between genetics and environment when it comes to dyslexia being combined with ADHD.  The study found that one of the DCDC2 gene variants was associated with both dyslexia and ADHD, with smoking in the environment adding to the correlation.  [ref]

Genes Involved in Dyslexia:

KIAA0319 is involved in cell to cell interactions.  In animal models, knocking out KIAA0319 causes animals to have impaired, rapid auditory processing and spatial learning problems.  Most of these are fairly common variants and are found in a quarter of the population or more.

  • rs4504469 (T) – found to be protective against dyslexia in Asian populations, but linked to higher risk of dyslexia in European populations.  [ref] [ref]
  • rs9461045 (T) – reduced expression of the KIAA0319 gene, associated with a risk for dyslexia [ref]
  • rs2038137 (T)  – slightly increased risk of dyslexia for homozygous [ref]
  • rs6935076 (T) – slightly increased risk of dyslexia (OR = 1.25) [ref]

DCDC2 gene – from Genetics Home Reference “This gene encodes a doublecortin domain-containing family member. The doublecortin domain has been demonstrated to bind tubulin and enhance microtubule polymerization. This family member is thought to function in neuronal migration where it may affect the signaling of primary cilia. Mutations in this gene have been associated with reading disability (RD) type 2, also referred to as developmental dyslexia.”

  • rs793862 (A) – 3 to 5x greater risk of dyslexia [ref]
  • rs807701 (G) – 2 to 5x increased risk of dyslexia if homozygous; even great risk if combined with rs793862 [ref] [ref]
  • rs7765678  (C) – protective against dyslexia [ref]
  • rs807724 (C) – A Chinese study found this to be significantly associated with reading comprehension and fluency. [ref]

More to read: 

Recent studies have looked into the differences between the types of dyslexia caused by these two genes.  A study from April 2016, Knockdown of Dyslexia-Gene Ccd2 Interferes with Speech Sound Discrimination in Continuous Streams, gives details on the differences.

Visual motion discrimination has been linked to DCDC2 polymorphisms.

A rabbit trail to go down:

A recent study found that an mTor inhibitor can differentially regulate DCDC2 (in podocytes – kidney cells).

Creating your own genetics “reports” for free

Reading through some Facebook questions the other day, it hit me that most people are not keeping track of their genetic information for themselves.  There are so many recommendation for ‘reports’ that you can order for $19 or $50 or much more.  A lot of these reports just color your SNPs red or green, which isn’t necessarily meaningful. Some polymorphisms will make an impact on your health and some have no impact.  So I’ve decided to explain how I personally keep track of information on my own genes (and for family and friends).

Short answer: I simply created an Excel spreadsheet, imported all of my raw data file, and use a separate sheet to look up my genetic info.

The spreadsheet isn’t beautiful, but it contains way more information than any of the paid reports that I’ve seen.  Plus it has all of my notes that are pertinent just to me! It is important to me that I know the source of the information and to read through studies myself rather than just relying on what someone else might say.  (There is a lot of speculation,  misinformation, and wacky stuff floating around on the internet – especially on Facebook!)

A final advantage of creating your own spreadsheet to keep track of your genetic information is that it is private.  I always worry a little bit about the security of sharing my 23andme data on another website.

Step-By-Step for Excel Gene Report using 23andMe Raw Data

Step 1: Download your raw data file from 23andMe. Log into the 23andMe website and go to the Tools section.  Click on Raw Data, and the click on Download.  That will take you to a page with instructions on how to download the file.  After downloading it, you will need to un-zip the compressed file, and then I really recommend saving it in a place where you won’t lose it (i.e. don’t leave it in your downloads folder!).

Step 2: Importing text fileOpen up Excel and start a blank workbook.  Import your raw data file by going to File, Import, and choosing to import a Text File. (Or your version may have a Data tab and an icon for importing Text.)  Find your .txt file that you just downloaded from 23andMe.  It is a “Delimited file” that is tab delimited.  It may take a minute to import all the data since your raw data file is over 600,000 rows.

 

 

 

Step 3: Open a new sheet by clicking on Sheet 2 at the bottom of your Excel screen.  This new sheet is where you will make your genetic ‘report’.

I set up mine to have headings across the top of Gene Name, SNP id, Risk Allele, person’s name (yours!), and Notes.  Here is an example with some made up data:  example Excel gene report

 

Step 4: Here is where the real magic comes in!  For each SNP id and risk allele, your alleles will be looked up and automatically included.

Go ahead and put in some data:   put in MTHFR C677T under your Gene Name column and rs1801133 under your SNPid column.  The risk allele for MTHFR C677T is  A.

Then in the column for your gene data you will use the following formula to look up your information from your raw data sheet.

=VLOOKUP(TRIM($B2),Sheet1!$A$16:$D$610564,4,FALSE)

What this formula does is looks at what is in B2 (the SNP id) and compares it to everything on your raw data sheet (Sheet1) in all of the rows.  Then when it finds a match, it returns your genotype for that SNP id.

Step 5: Excel copyAdd in some more Genes and SNP ids (read the rest of my blog posts to find more), and then copy the formula down under your gene data column by clicking on the little box in the lower right corner of the cell and dragging it down the columns that you want to fill.  (You can copy and paste the normal way as well if you don’t like the ‘fill handle’ shortcut.)

Double check that you have copied correctly by checking that the VLOOKUP formula is always referring to the row that you are on (e.g. $B3).

Also, the “Risk Allele” always needs to be in the same orientation that 23andMe uses (referred to as forward or plus).

Step 6: Finally, add in some color to make it easy to read.  Use whatever color coding system makes sense to you — this is YOUR spreadsheet.  I did end up setting up Conditional Formatting to automatically color code my spreadsheets, but that is a more complicated tutorial for another day.

Genetics of Grinding Your Teeth

The Genetic Polymorphisms involved in Teeth Grinding (Bruxism)
The Genetic Polymorphisms involved in Teeth Grinding (Bruxism)

It never fails to amaze me how many of our quirks and traits have a genetic basis.  A study that came out last week caught my eye. Bruxism, teeth grinding, is linked to a genetic variant.

The study, Genetic polymorphisms in the serotoninergic system are associated with circadian manifestations of Bruxism, looked into several polymorphisms in neurotransmitters such as serotonin.  For some people, SSRI’s are effective in helping  control teeth grinding.

The September 2016 study found that a variant in the HTR2A gene, which codes for a 5-HT2 serotonin receptor, is associated with bruxism.  Those with a C allele in rs2770304  were found to have twice the normal risk for bruxism.[ref]

Another study from 2012 of bruxism in a Japanese population found a different variant in HTR2A to be significant.  In that study, a G allele for rs6313 gave a 4 times greater risk for grinding your teeth in your sleep.  [ref]

Both variants are very common and have many other studies associated with them. [ref]

Check your 23andMe results for rs2770304

  • CC: 2X increased risk of bruxism (teeth grinding)
  • CT: increased risk of bruxism
  • TT: wildtype/normal

 

Check your 23andMe results for rs6313

  • GG: 4X increased risk of bruxism
  • AG: increased risk of bruxism
  • AA: wildtype/normal

 

So what can you do with this information? Logically, if you are grinding your teeth and have these variants, you could look into the serotonin system.   Be cautious and read up on serotonin before starting supplements that could affect your neurotransmitter levels.  Honestly, it is not clear to me whether it would be better to try to stimulate more serotonin or to try to decrease serotonin for bruxism.  Tryptophan is an amino acid that may increase serotonin, as well as 5-HTP. [ref]  So talk with your doctor and get your serotonin levels checked.

Mono and genetics

Ever wonder why some people get mono and others don’t?  Almost 95% of adults carry antibodies to the Epstein Barr virus that causes mono, but less than 30% of people are estimated to get mono.  [CDC.gov]   Turns out that there may be a genetic susceptibility to mono as well as environmental factors.  Twin studies, one way of determining heritability of a condition,  show that identical twins are twice as likely to both have mono as fraternal twin siblings.  [ref]

There aren’t a lot of studies seeking to determine exactly where the genetic susceptibility of a person to mono lies.  My guess is that there isn’t any money in knowing that answer, but as a parent of a teen who has been exposed, I would like to know if he will get it!

A 2007 study with approximately 200 participants determined that certain HLA polymorphisms “may predispose patients to development of IM [infectious mononucleosis] upon primary EBV [Epstein Barr virus] infection.”  The study found that for rs253088, the A/A genotype was less frequent in the infectious mononucleosis group.  It also found that for rs6457110 the T allele was found less frequently in the mono group. [ref]

A 2001 study found that for the IL10 gene, a haplotype of ATA (TAT in 23and me orientation) on rs1880896, rs1800871, and rs1800872 is protective against Epstein Barr infection.  [ref]

More studies have been done on the link between having had mono and later developing multiple sclerosis.  HLA-DRB1*1501 serotype is highly correlated with the rs3135388 T-allele of HLA-DRA.  Studies have found that those with the HLA-DRB1*1501 (look at rs3135388 T allele) are at a higher risk of multiple sclerosis, especially if they have had mono. [ref]

If you have mononucleosis, there is a 2014 study showing that high doses of vitamin C may help shorten the duration of the disease. [ref]

 

 

 

Ear wax and body odor – it’s genetic

The ABCC11 gene determines both the type of earwax a person has and their armpit odor. A change in a single base in the code for this gene can cause the gene not to function.

Check your 23andMe results to see if you produce body odor. Or just do a sniff test…

People with a functioning ABCC11 gene have wet earwax and body odor, while those with the gene variant causing loss of function have dry earwax and little or no body odor. Loss of function of the ABCC11 gene is very common among East Asian populations (80-90% of the population!), but fairly rare in other populations (1 – 3% of Caucasians).

So what exactly does this gene do? The ABCC11 gene (ATP-binding cassette transporter sub-family C member 11) codes for a protein that is involved in transporting molecules across cellular membranes.  It is involved in the transport of lipophilic compounds, bile acids, conjugated steroids, and the substance that is in apocrine sweat and in earwax, thus causing body odor and wet earwax.

Variants of this gene are also involved in resistance to antiviral and anticancer drugs.[ref]  The wet earwax allele was also associated with a higher risk of breast cancer in Japanese women, but not in women of European descent.[ref] [ref]

Check your 23andMe results for rs17822931 (v.4 and v.5):

  • CC: wet earwax, body odor, and normal colostrum[ref] [ref]
  • CT: wet earwax, somewhat less body odor
  • TT: dry earwax, no body odor, and less colostrum

There was an interesting article in Scientific American a few years ago looking into the fact that those who genetically don’t have smelly pits often unnecessarily still wear deodorant. Other research showed that those with the ‘no body odor’ variant sometimes had other sources of body odor or social reasons for wearing deodorant.[ref]