SNPs #1 – Obesity Associated Genetic Mutations

SNPs #1 - Obesity Associated Genetic Mutations


Genetics play a significant role in physiology. Yet, as many of you know, your genes do not necessarily dictate your destiny. You can impact the way your genes are being expressed with different interventions, lifestyle and non-lifestyle. This is the field of epigenetics.

To make the best of your physiology, I think it is of great importance to have a good knowledge of both. It’s not one or the other. It’s one and the other – and many other.

As of March 2016, whole genome sequencing (your entire DNA – ~6 billion nucleotides) just got under $1,000; and it can be done in ~24 hours. To appreciate the scale of this, the first human genome took more than a decade to sequence and it cost ~$3 billion.

You don’t need to do whole genome sequencing to get a good grasp of your genetics. You can opt for the cheaper version of genetic testing like the one that 23andme, Ancestry and other companies do for ~$100 (currently).

With this type of test you get your genome checked at a couple of hundreds of thousands (~600,000 – 800,000 as of March 2016) of positions to determine possible mutations. Your genome is compared with a reference genome. 23andme and many other genetic testing companies are basically testing your genome for SNPs (snips), single nucleotide polymorphisms – the technical word for genetic mutation.

What are Single Nucleotide Polymorphisms (SNPs)

The Handbook of Genetics from the NIH explains it better [1]:

Each SNP represents a difference in a single DNA building block, called a nucleotide. For example, a SNP may replace the nucleotide cytosine (C) with the nucleotide thymine (T) in a certain stretch of DNA.

SNPs occur normally throughout a person’s DNA. They occur once in every 300 nucleotides on average, which means there are roughly 10 million SNPs in the human genome.

Some of the SNPs occur in regions between genes and they may have lower association with pathologic and non-pathologic conditions. Others occur within genes and they may have a more direct role in diseases, since they affect the function of the genes.

Most SNPs have no effect on health or development. Some of these genetic differences, however, have proven to be very important in the study of human health. Researchers have found SNPs that may help predict an individual’s response to certain drugs, susceptibility to environmental factors such as toxins, and risk of developing particular diseases. [1]

While many of these SNPs are not determinative by themselves (in isolation), there are various that can heavily impact or characterize a disease state, like the cystic fibrosis – CFTR – associated SNP, the BRCA1 SNP associated with higher risk for developing cancer, the MSH2 SNP associated with Lynch Syndrome and with colorectal cancer, and so on.

Similarly, there are currently various SNPs that have been associated with obesity, and often with type 2 diabetes, putting their carriers at higher risks for developing these disorders.

The purpose of this post is to provide awareness for a few of these SNPs and the research studies associated with them. If you’ve done genetic testing and you have the raw data at hand you can simply check for the specific SNP to see the genotype you have.

You can find the current list (always updating) of obesity associated SNPs at SNPedia. I’m only going to mention a few of them here [2].

Obesity Associated SNPs

  1. APOA2

This is gene that codes for Apolipoprotein A-II, which has an (unclear) role in lipid metabolism, obesity, and atherosclerosis [2]. According to the NIH, defects in APOA2 gene can result in APOAII deficiency and hypercholesterolemia.

An important SNP in APOA2 is:


The risk genotype at this position in the DNA is CC. One of the studies that lead to this association is this [3]:

We studied the association between a functional APOA2 promoter polymorphism (-265T>C) and plasma lipids (fasting and postprandial), anthropometric variables, and food intake in 514 men and 564 women.

They found:

Consistently, after multivariate adjustment, the odds ratio for obesity in CC individuals compared with T allele carriers was 1.70 (95% CI 1.02-2.80, P = 0.039). Interestingly, total energy intake in CC individuals was statistically higher [mean (SE) 9371 (497) vs 8456 (413) kJ/d, P = 0.005] than in T allele carriers.

Likewise, total fat and protein intakes (expressed in grams per day) were statistically higher in CC individuals (P = 0.002 and P = 0.005, respectively). After adjustment for energy, percentage of carbohydrate intake was statistically lower in CC individuals. These associations remained statistically significant even after adjustment for BMI. We found no associations with fasting lipids and only some associations with HDL subfraction distribution in the postprandial state.

Here’s what I see:

CC, the risk genotype, ate more protein and fat and fewer carbohydrates. They had higher plasma lipids, even after adjusting for different variables.

This was an association study, which is why I cannot critique dietary control. It would be interesting to see how CC individuals react to different diets in terms of macro partitioning, though I suspect they would better on a low saturated fat diet, given this mutation in APOA2.

Read the full study here and interpret it yourself.
Read more studies associated with this SNP here.

  1. APOA5

This gene codes for another Apolipoprotein involved in TAG control. According to the NIH, this is a component of HDL and is highly similar to a rat protein that is upregulated in response to liver injury. Mutations in this gene have been associated with hypertriglyceridemia and hyperlipoproteinemia type 5. [4]

There are several mutations (SNPs) associated with the APOA5 gene, including these:


CC is the normal genotype.
Asians with AA or AC genotype at this position have more than 4 times increased risk for higher triglycerides. See study.
For those at risk, it would be wise avoiding a high fat diet.


132 patients of European descent showed severe hypertriglyceridemia (fasting plasma TAGs > 10 mmol/L) compared to 351 patients in the control group (with normal levels). See study.


This one is interesting.
The normal genotype at this position in the human genome is AA.
Those carrying the G allele (AG and GG genotype) are at 1.4x – 2x times more risks of heart attack, though they are less prone to gain weight on a high fat diet. See this study, this one, and this piece of news.

  1. FTO

This is the gene that codes for the Fat-Mass-and-Obesity-Associated protein. According to the NIH, the exact physiologic function of FTO is not know, but [5]:

Studies in mice and humans indicate a role in nervous and cardiovascular systems and a strong association with body mass index, obesity risk, and type 2 diabetes.

There are several mutations (SNPs) in this gene indicating such associations:


The normal genotype at this position is TT and it is associated with lower risks of obesity and T2D.
People who are AA are at 1.6x more risk of developing T2D and higher risk for obesity.
People who are AT are at 1.3x more risk of developing T2D and higher risk for obesity.

See this study, this one, and a few more studies here. If I would detail all of them here this post would turn into a book.


The normal genotype for this position in the human genome is CC.
Those who are CT are at 1.67x increased risk for obesity.
Those who are TT are at 2.76x increased risk for obesity.

The study providing strong associations for this SNP and obesity was done in 929 subjects of Caucasian descent. Another study showed severe obesity for this SNP in 927 Japanese subjects.


The normal genotype is GG.
Those who are AA at this position in the genome are at 1.32x increased risk of melanoma, while those who are AG are at 1.16 increased risk of melanoma. Read the studies here.


The normal genotype is CC.
Those who are AC and AA are at 1.2x – 1.4x increased risk for T2D.
However, this was only seen in some populations. Read the studies here.

  1. MC4R

This is the gene that codes for Melanocortin 4 Receptor. According to the NIH [6]:

The encoded protein interacts with adrenocorticotropic and MSH hormones and is mediated by G proteins. This is an intronless gene. Defects in this gene are a cause of autosomal dominant obesity.

One important SNP in this gene is:


The normal genotype for this position is GG.
However, those who are AG or AA have a decreased risk of developing the metabolic syndrome. A study of 7,888 people of Caucasian descent shows this.

  1. SCG3

This is the gene that codes for Secretogranin III. According to the NIH [7]:

Granins may serve as precursors for biologically active peptides. Some granins have been shown to function as helper proteins in sorting and proteolytic processing of prohormones; however, the function of this protein is unknown.

According to SNPedia, in one study, two SNPs affected the transcriptional activity of SCG3, and subjects with the minor allele seemed to be resistant to obesity. The study was conducted in 94 obese subjects versus 658 controls. See study. If you read the study, you’ll see that certain SNPs in this gene have been associated with resistance to obesity, which is great if you carry that particular genotype, imho.


This is the gene that codes for adiponectin, which is a hormone produced by fat cells. According to the NIH [8]:

The encoded protein circulates in the plasma and is involved with metabolic and hormonal processes. Mutations in this gene are associated with adiponectin deficiency.

From SNPedia and this study:

The -11377 C > G adiponectin gene promoter variant is:
(i) associated with decreased serum adiponectin levels and therefore increased risk of obesity,
(ii) correlated with the presence of coronary atherosclerosis, and
(iii) significantly predictive of vascular events among men undergoing coronary angiography.

  1. rs6971091 is another SNP that affects obesity:

This position refers to an uncharacterized gene on chromosome 7.

The normal genotype for this position is GG.
Those who are AA or AG are at more than twice higher risk for developing obesity (defined by leptin levels and BMI).
The insights have been derived from a study of more than 400 subjects [9]:

We report the results of fine mapping the linkage peak using 1020 single nucleotide polymorphisms (SNPs) to test for association to obesity in families exhibiting linkage to chromosome 7. Association observed in linked families (284 obese cases/381 controls) was examined in an independent set of unrelated FHS participants (172 obese cases/308 controls) to validate the observed association. Two dichotomous obesity phenotypes were studied based on clinical BMI cutoffs and the sex-specific distribution of both BMI and leptin levels.

They adjusted for smoking, exercise and the FTO genotype of the subjects. The adjustment did not affect the results in linked families. However, it improved the results in the unrelated sample [9]:

Carrying a minor allele of the nonsynonymous SNP rs6971091 conferred an odds ratio of at least 2 for obesity defined by both BMI and leptin levels.

Concluding Thoughts

You can test and see your genotype for all these SNPs using different companies. Prices average at $100 currently. It is pretty cheap if you ask me and the error rate is very low, though not inexistent.

However, the amount of information you get for your buck is ungraspable and extremely compelling (big data). If you sequence your entire genome, the issue scales exponentially. Should you want to know your genetics at such a profound level? Well, this is a question that only you have the answer for.

If you decide to do it, you can use these few SNPs as a starting guide. To learn more, you can follow the links to SNPedia and from there the links to the different studies. SNPedia is kindof the Wikipedia of SNPs. The number of outside (external) links and study references is hard, if not impossible, to handle.

When you follow associations between SNPs and different conditions (disease or non-disease), make sure you read the studies and try to view things as critically as possible.

Sadly, I cannot go in an in-depth analysis with this type of post since there so many studies to be read and to be interpreted. In future posts I will use a similar strategy to discuss other diseases and non-disease states associated with different SNPs, with the sole purpose of giving you a starting point if you’re analyzing your genome.

If you think that I can make this post better and if you have suggestions for future similar posts, be sure to leave me a message below, or send me an email and I will do my best to reply.

Please keep in mind:

Knowing your genetics can make a difference. Yet, this is not decisive in your life, physiologically and psychologically speaking.

Epigenetics also plays an important role – you can influence how your genes are being expressed with the lifestyle and non-lifestyle choices you make everyday.

Finding a bridge and connecting the two disciplines is mostly desired, imho.

Personal genomics represents the present and the future, which is why I think that standard dietary recommendations, where one size should fit the majority (high-fat, low-fat, no-fat, etc.), belong to the past.

Sources Mentioned:

  1. NIH Genetics Home Reference (2016). Handbook – Help Me Understand Genetics.
  1. SNPedia (2016). Obesity.
  1. Corella, D., Arnett, D. K., Tsai, M. Y., Kabagambe, E. K., Peacock, J. M., Hixson, J. E., … & Borecki, I. (2007). The− 256T> C polymorphism in the apolipoprotein A-II gene promoter is associated with body mass index and food intake in the genetics of lipid lowering drugs and diet network study. Clinical chemistry, 53(6), 1144-1152.
  1. NCBI at NIH (2016). APOA5 – Apolipoprotein A-V [Homo Sapiens (human)]
  1. NCBI at NIH (2016). FTO – Fat Mass and Obesity Associated [Homo Sapiens (human)]
  1. NCBI at NIH (2016). MC4R – Melanocortin 4 Receptor [Homo Sapiens (human)]
  1. NCBI at NIH (2016). SCG3 – Secretogranin III [Homo Sapiens (human)]
  1. NCBI at NIH (2016). ADIPOQ – Adiponectin, C1Q and Collagen Domain Containing [Homo Sapiens (human)]
  1. Wilk, J. B., Laramie, J. M., Latourelle, J. C., Williamson, S., Nagle, M. W., Tobin, J. E., … & Myers, R. H. (2008). NYD-SP18 is associated with obesity in the NHLBI Family Heart Study. International Journal of Obesity, 32(6), 930-935.

Image: adapted from here

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9 Responses to SNPs #1 – Obesity Associated Genetic Mutations

  1. Jeff Cyr says:

    Cristi Vlad I read your article, not all the studies. First I must say that I agree with you 100% that a ketogenic diet, or a raw vegan diet with no fat, or a high protein diet, is not the right diet for EVERYONE. There is obviously a lot more to it. I have also studied a lot about what you speak of here. And also keep in mind, as you have stated here that you can also change your genetic expression through diet manipulation. I have to give you a lot of credit because you are always digging deeper into the effects how different type diets, fasting, exercise, etc will have on different people for different reasons, of which there are many. I salute you Cristi!

  2. Peter Wojciechowski says:

    Christi, great read. Only 1 day left but how about throwing your hat in the ring for this
    Only 500 words!
    Would love to hear what you would do with the sequencer!
    All the best


  3. David says:

    So I have the GG genotype for the APOA2 . Two variants. It states that saturated fat, will cause weight gain etc. SO ketogenic is a no go ? The study was about CC. Not GG. So a lil confused. Im new to all this genetic stuff. Learning

    • Chris Chris says:

      to be honest, I wouldnt base my decision on a single mutation. To have a better direction I’d look at more genes with known impact on obesity, make appropriate lifestyle changes, and see if they live up to the expectations. We should always be willing to let go of something if it doesnt work.

      If you tried the ketogenic diet and an extensive blood work + other biomarker analyses show nothing out of the ordinary due to the keto diet, and if you have seen positive results with it, I see no reason not to pursue it. I may be wrong though…

      • David says:

        Yeah. I figured looking at one mutation wasn’t enough. Im actually going to be working with someone who analyzes much more to give me a better picture about my own unique makeup. I haven’t gone full keto but very close to it following a Paleo type diet, carbs coming from greens, grass fed fats, but I def eat lots of saturated fats, and haven’t gained any weight. Weight has stayed the same. So it will be interested to see the bigger picture, once I get more blood work, and the dna fully looked into for nutritional etc support.

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