Genetic Makeup Can Exacerbate Effects of Fried Food Diet, published today, summarizes the findings in Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies, an Open Access article in the British Medical Journal by Qi et al, a group of Harvard professors. In this article, the authors reused a genetic risk of obesity score that they had previously published in Sugar-Sweetened Beverages and Genetic Risk of Obesity in the New England Journal of Medicine. Unfortunately, the latter article is not Open Access. So, I'll describe the Qi et al Genetic Risk of Obesity score (which I'll call QiGRO for short) in this post.
The information needed to compute QiGRO is presented in Table 1 of the Supplementary Appendix to Sugar-Sweetened Beverages and Genetic Risk of Obesity. This lists 32 SNPs (single-nucleotide polymorphisms) contributing to risk of increased BMI (body mass index), along with a β-coefficient describing the relative effect size for each. Here are the relevant columns from the table:
The information needed to compute QiGRO is presented in Table 1 of the Supplementary Appendix to Sugar-Sweetened Beverages and Genetic Risk of Obesity. This lists 32 SNPs (single-nucleotide polymorphisms) contributing to risk of increased BMI (body mass index), along with a β-coefficient describing the relative effect size for each. Here are the relevant columns from the table:
| SNP | Nearest Gene | Chromosome | Effect | Other | Beta |
| rs543874 | SEC16B | 1 | G | A | 0.22 |
| rs1514175 | TNNI3K | 1 | A | G | 0.07 |
| rs1555543 | PTBP2 | 1 | C | A | 0.06 |
| rs2815752 | NEGR1 | 1 | A | G | 0.13 |
| rs2890652 | LRP1B | 2 | C | T | 0.09 |
| rs887912 | FANCL | 2 | T | C | 0.1 |
| rs713586 | RBJ | 2 | C | T | 0.14 |
| rs2867125 | TMEM18 | 2 | C | T | 0.31 |
| rs13078807 | CADM2 | 3 | G | A | 0.1 |
| rs9816226 | ETV5 | 3 | T | A | 0.14 |
| rs13107325 | SLC39A8 | 4 | T | C | 0.19 |
| rs10938397 | GNPDA2 | 4 | G | A | 0.18 |
| rs4836133 | ZNF608 | 5 | A | C | 0.07 |
| rs2112347 | FLJ35779 | 5 | T | G | 0.1 |
| rs987237 | TFAP2B | 6 | G | A | 0.13 |
| rs206936 | NUDT3 | 6 | G | A | 0.06 |
| rs10968576 | LRRN6C | 9 | G | A | 0.11 |
| rs3817334 | MTCH2 | 11 | T | C | 0.06 |
| rs4929949 | RPL27A | 11 | C | T | 0.06 |
| rs10767664 | BDNF | 11 | A | T | 0.19 |
| rs7138803 | FAIM2 | 12 | A | G | 0.12 |
| rs4771122 | MTIF3 | 13 | G | A | 0.09 |
| rs11847697 | PRKD1 | 14 | T | C | 0.17 |
| rs10150332 | NRXN3 | 14 | C | T | 0.13 |
| rs2241423 | MAP2K5 | 15 | G | A | 0.13 |
| rs7359397 | SH2B1 | 16 | T | C | 0.15 |
| rs1558902 | FTO | 16 | A | T | 0.39 |
| rs12444979 | GPRC5B | 16 | C | T | 0.17 |
| rs571312 | MC4R | 18 | A | C | 0.23 |
| rs29941 | KCTD15 | 19 | G | A | 0.06 |
| rs3810291 | TMEM160 | 19 | A | G | 0.09 |
| rs2287019 | QPCTL | 19 | C | T | 0.15 |
If you subscribe to 23andMe, you can get some idea about your QiGRO score. Not all of the above SNPs are included in the 23andMe data at this time, so you can't compute it exactly. You can compute the contribution to your QiGRO score from the SNPs that 23andMe does include. We'll call this the modified QiGRO score for short. Here's how to compute it.
Sign in to the service, click on the downward arrow next to your name in the upper right, and click "Browse Raw Data". This brings you to a page where you can "Jump to a gene" "or a SNP".
Copy the first SNP from the table above, rs543874, into the "or a SNP" box (the righthand one) on the "Browse Raw Data" page and click Go. 23andMe will list a result with your genotype at this SNP: it might be AA, AG, or GG. Since the above table lists G as the Effect allele, count the number of Gs in your genotype. If your genotype is AA, AG, or GG, you will get 0, 1, or 2, respectively. Multiply the number you get by the Beta coefficient, 0.22, from the first row of the above table. So if your genotype is AA, AG, or GG, you will get 0.0, 0.22, or 0.44, respectively. Start a running tally for your score using this number. Also start another running tally of the Beta coefficients, 0.22. Keep track of the number of SNPs you've checked. This is now 1.
In case you're curious, here's what this means. You got two copies of this locus (a site on a chromosome), one from your mother and one from your father. The above table says that there are two possible variants, or alleles, at this locus: A (the DNA nucleotide alanine) or G (the DNA nucleotide guanine). Here G is the effect allele, meaning that each G increases the risk of a higher BMI. The Beta coefficient describes how much it increases the risk.
Continuing, copy the second SNP from the table above, rs1514175, into the "or a SNP" box and click Go. In this case again your genotype at this SNP might be AA, AG, or GG. However, this time A is the Effect allele, so count the number of As in your genotype. If your genotype is AA, AG, or GG, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.07, from the second row of the above table. So if your genotype is AA, AG, or GG, you will get 0.14, 0.07, or 0.0, respectively. Add this to your running tally for your score. For instance, if your genotype at rs543874 was AG, and your genotype at rs1514175 was AA, your running tally for your score would be 0.22 + 0.14 = 0.36. Also add the Beta coefficient, 0.07 to your running tally of the Beta coefficients, yielding 0.22 + 0.07 = 0.39. The number of SNPs you've checked is now 2.
Copy the third SNP from the table above, rs1555543, into the "or a SNP" box and click Go. Currently, 23andMe tells me: “No SNPs matching 'rs1555543' found in the data from your chip.” I deliberately did not include this information in the table above since 23andMe updates their chips and reruns samples from time to time, so by the time you read this post the data may be present. Try it and see. If there is no data, skip adding anything either to the running tally for your score or the running tally using the Beta coefficients.
Copy the fourth SNP from the table above, rs2815752, into the "or a SNP" box and click Go. In this case your genotype at this SNP might be AA, AG, or GG. Here A is the Effect allele, so count the number of A's in your genotype. If your genotype is AA, AG, or GG, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.13, from the fourth row of the above table. So if your genotype is AA, AG, or GG, you will get 0.26, 0.13, or 0.0, respectively. Add this to your running tally for your score. For instance, if your running tally for your score was 0.36 as in the example above, and your genotype at rs2815752 is AA, your running tally for your score will now be 0.36 + 0.26 = 0.62. Add the Beta coefficient 0.13 to your running tally of the Beta coefficients, yielding 0.39 + 0.13 = 0.52. The number of SNPs you've checked is now 3.
Currently, rs2890652, rs887912, and rs713586 are not included in the 23andMe data. Just to be completely clear, I'll write out one more step.
Copy the eighth SNP from the table above, rs2867125, into the "or a SNP" box and click Go. In this case your genotype at this SNP might be CC, CT, or TT. Here C is the Effect allele, so count the number of C's in your genotype. If your genotype is CC, CT, or TT, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.31, from the eighth row of the above table. So if your genotype is CC, CT, or TT, you will get 0.62, 0.31, or 0.0, respectively. Add this to your running tally for your score. For instance, if your running tally for your score was 0.62 as in the example above, and your genotype at rs2867125 is CT, your running tally for your score will now be 0.62 + 0.31 = 0.93. Add the Beta coefficient 0.31 to your running tally of the Beta coefficients, yielding 0.52 + 0.31 = 0.83. The number of SNPs you've checked is now 4.
Continue in this way until you've checked all 32 SNPs in the table. Currently there's no data for rs9816226, rs4836133, rs2112347, rs3817334, rs4929949, rs10767664, rs4771122, rs11847697, rs10150332, or rs7359397. So the number of SNPs you've checked would end up at 18, and your running tally of the Beta coefficients would end up at 2.84, assuming the same set of SNPs are included. Your running tally for your score will be some number between 0 and twice the sum of the Beta coefficients, i.e., 5.68 currently.
To get your modified QiGRO score, take your running tally for your score, divide it by your running tally of the Beta coefficients, and multiply it by the number of SNPs you've checked. You will get a number between 0 and twice the number of SNPs you've checked, i.e., between 0 and 36 currently.
Your actual QiGRO score includes the contributions of the other (currently 14) SNPs you weren't able to check, so it lies between your modified QiGRO score and your modified QiGRO score plus twice the number of SNPs you weren't able to check, i.e., currently your modified QiGRO score plus 28. Unfortunately this range is too large to provide useful information. According to Figure S1 in the Supplementary Appendix to Sugar-Sweetened Beverages and Genetic Risk of Obesity, almost the entire cohorts studied fall between a QiGRO score of 19 and a QiGRO score of 39, a range of only 20. In the absence of any other information, you might look at the middle of the range, i.e., your modified QiGRO score plus 14. To get a better estimate we would need to know the distribution of these SNPs in the population.
In Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies, all study participants had a QiGRO score between 13 and 43. Qi et al divided their study participants into thirds by increments of 10 risk alleles, i.e., the lower third with scores between 13 and 23, the middle third with scores between 24 and 33, and the upper third with scores between 34 and 43. (They did not publish the exact cutoffs in their paper, so the intermediate boundaries may be off by one.) Qi et al found in these two studies that fried foods and sugar sweetened beverages increase BMI more among those with a higher QiGRO score. So, if it appears that your QiGRO score is on the high side, it may be more beneficial for you to cut back on sugar sweetened beverages and fried foods.
You might also note your genotype at rs1558902 in particular (which is currently included in the 23andMe data). Qi et al found that the association between BMI and this variant alone was significant, and strengthened as more fried foods were consumed.
Sign in to the service, click on the downward arrow next to your name in the upper right, and click "Browse Raw Data". This brings you to a page where you can "Jump to a gene" "or a SNP".
Copy the first SNP from the table above, rs543874, into the "or a SNP" box (the righthand one) on the "Browse Raw Data" page and click Go. 23andMe will list a result with your genotype at this SNP: it might be AA, AG, or GG. Since the above table lists G as the Effect allele, count the number of Gs in your genotype. If your genotype is AA, AG, or GG, you will get 0, 1, or 2, respectively. Multiply the number you get by the Beta coefficient, 0.22, from the first row of the above table. So if your genotype is AA, AG, or GG, you will get 0.0, 0.22, or 0.44, respectively. Start a running tally for your score using this number. Also start another running tally of the Beta coefficients, 0.22. Keep track of the number of SNPs you've checked. This is now 1.
In case you're curious, here's what this means. You got two copies of this locus (a site on a chromosome), one from your mother and one from your father. The above table says that there are two possible variants, or alleles, at this locus: A (the DNA nucleotide alanine) or G (the DNA nucleotide guanine). Here G is the effect allele, meaning that each G increases the risk of a higher BMI. The Beta coefficient describes how much it increases the risk.
Continuing, copy the second SNP from the table above, rs1514175, into the "or a SNP" box and click Go. In this case again your genotype at this SNP might be AA, AG, or GG. However, this time A is the Effect allele, so count the number of As in your genotype. If your genotype is AA, AG, or GG, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.07, from the second row of the above table. So if your genotype is AA, AG, or GG, you will get 0.14, 0.07, or 0.0, respectively. Add this to your running tally for your score. For instance, if your genotype at rs543874 was AG, and your genotype at rs1514175 was AA, your running tally for your score would be 0.22 + 0.14 = 0.36. Also add the Beta coefficient, 0.07 to your running tally of the Beta coefficients, yielding 0.22 + 0.07 = 0.39. The number of SNPs you've checked is now 2.
Copy the third SNP from the table above, rs1555543, into the "or a SNP" box and click Go. Currently, 23andMe tells me: “No SNPs matching 'rs1555543' found in the data from your chip.” I deliberately did not include this information in the table above since 23andMe updates their chips and reruns samples from time to time, so by the time you read this post the data may be present. Try it and see. If there is no data, skip adding anything either to the running tally for your score or the running tally using the Beta coefficients.
Copy the fourth SNP from the table above, rs2815752, into the "or a SNP" box and click Go. In this case your genotype at this SNP might be AA, AG, or GG. Here A is the Effect allele, so count the number of A's in your genotype. If your genotype is AA, AG, or GG, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.13, from the fourth row of the above table. So if your genotype is AA, AG, or GG, you will get 0.26, 0.13, or 0.0, respectively. Add this to your running tally for your score. For instance, if your running tally for your score was 0.36 as in the example above, and your genotype at rs2815752 is AA, your running tally for your score will now be 0.36 + 0.26 = 0.62. Add the Beta coefficient 0.13 to your running tally of the Beta coefficients, yielding 0.39 + 0.13 = 0.52. The number of SNPs you've checked is now 3.
Currently, rs2890652, rs887912, and rs713586 are not included in the 23andMe data. Just to be completely clear, I'll write out one more step.
Copy the eighth SNP from the table above, rs2867125, into the "or a SNP" box and click Go. In this case your genotype at this SNP might be CC, CT, or TT. Here C is the Effect allele, so count the number of C's in your genotype. If your genotype is CC, CT, or TT, you will get 2, 1, or 0, respectively. Multiply this by the Beta coefficient, 0.31, from the eighth row of the above table. So if your genotype is CC, CT, or TT, you will get 0.62, 0.31, or 0.0, respectively. Add this to your running tally for your score. For instance, if your running tally for your score was 0.62 as in the example above, and your genotype at rs2867125 is CT, your running tally for your score will now be 0.62 + 0.31 = 0.93. Add the Beta coefficient 0.31 to your running tally of the Beta coefficients, yielding 0.52 + 0.31 = 0.83. The number of SNPs you've checked is now 4.
Continue in this way until you've checked all 32 SNPs in the table. Currently there's no data for rs9816226, rs4836133, rs2112347, rs3817334, rs4929949, rs10767664, rs4771122, rs11847697, rs10150332, or rs7359397. So the number of SNPs you've checked would end up at 18, and your running tally of the Beta coefficients would end up at 2.84, assuming the same set of SNPs are included. Your running tally for your score will be some number between 0 and twice the sum of the Beta coefficients, i.e., 5.68 currently.
To get your modified QiGRO score, take your running tally for your score, divide it by your running tally of the Beta coefficients, and multiply it by the number of SNPs you've checked. You will get a number between 0 and twice the number of SNPs you've checked, i.e., between 0 and 36 currently.
Your actual QiGRO score includes the contributions of the other (currently 14) SNPs you weren't able to check, so it lies between your modified QiGRO score and your modified QiGRO score plus twice the number of SNPs you weren't able to check, i.e., currently your modified QiGRO score plus 28. Unfortunately this range is too large to provide useful information. According to Figure S1 in the Supplementary Appendix to Sugar-Sweetened Beverages and Genetic Risk of Obesity, almost the entire cohorts studied fall between a QiGRO score of 19 and a QiGRO score of 39, a range of only 20. In the absence of any other information, you might look at the middle of the range, i.e., your modified QiGRO score plus 14. To get a better estimate we would need to know the distribution of these SNPs in the population.
In Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies, all study participants had a QiGRO score between 13 and 43. Qi et al divided their study participants into thirds by increments of 10 risk alleles, i.e., the lower third with scores between 13 and 23, the middle third with scores between 24 and 33, and the upper third with scores between 34 and 43. (They did not publish the exact cutoffs in their paper, so the intermediate boundaries may be off by one.) Qi et al found in these two studies that fried foods and sugar sweetened beverages increase BMI more among those with a higher QiGRO score. So, if it appears that your QiGRO score is on the high side, it may be more beneficial for you to cut back on sugar sweetened beverages and fried foods.
You might also note your genotype at rs1558902 in particular (which is currently included in the 23andMe data). Qi et al found that the association between BMI and this variant alone was significant, and strengthened as more fried foods were consumed.
Excellent!!
ReplyDeleteThis needs a script to automate the steps ;) ;) ;)
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