After filtering for FASTQ files greater than 1 MB, I found there were 77 American Gut subjects that suffered from migraines (at least a few times a year). I calculated abudance levels for phylum, class, and species using MG-RAST (with alignments to RDP). You can see my previous post for more details.
First, I wanted to see what other variables were correlated with migraine status (in order to make sure I was characterizing metagenomic changes that are specifically associated with migraines and not secondary factors). I found two factors significantly associated with migraine status: BMI (and other weight-related factors: migraine subjects had a higher BMI) and sex (migraine subjects were more likely to be women).
| METADATA | t-test p-value |
| CARBOHYDRATE_PER | 0.46 |
| AGE | 0.79 |
| TOT_MASS | 0.039 |
| PROTEIN_PER | 0.16 |
| PLANT_PER | 0.97 |
| BMI | 0.017 |
| HEIGHT_IN | 0.23 |
| SEX | 0.0039 |
| FAT_PER | 0.93 |
| HEIGHT_OR_LENGTH | 0.23 |
| WEIGHT_LBS | 0.039 |
| ANIMAL_PER | 0.95 |
| LATITUDE | 0.55 |
| LONGITUDE | 0.82 |
So, I then collected normal controls matched for BMI and sex. There were a few migraine subjects missing gender and/or BMI information, so I only included 70 matched controls. To be fair, this might have not mattered too much: for example, the preliminary American Gut report noted that profiles didn't seem very different between genders. However, I thought it was best to err on the side of safety.
Unsurprisingly, there were not any substantial clustering between migraine and non-migraine subjects (otherwise, I would have expected this to be included in the American Gut preliminary report):
Unfortunately, I also didn't see any strong clustering based upon migraine frequency either:
FYI, I am showing PCA plots based upon species-level abundances for species with an average abundance of at least 100 counts per sample, but you can also view the case-vs-control phylum and class distributions as well as the migraine frequency phylum and class distributions.
Although I didn't see any major differences in the PCA plots, I went ahead and looked for any differences that occurred with a false-discovery rate (FDR) less than 0.05. I used the sRAP package for analysis, treating the 16S rRNA abundances like gene expression values. Although most of these results looked like artifacts from only having one subject that had migraines on a daily basis, I did consider Lactococcus lactis (p=0.00088, FDR = 0.042) to be an interesting candidate:
I double-checked the frequency of migraine subjects with lactose intolerance: the frequency was qualitatively higher compared to subjects with less frequent migraines (50% versus 28.6%), but this difference was not statistically significant (Fisher's exact p-value = 0.28). Additionally, I'm not sure about the interpreation if this Lactococcus lactis trend is found to be reproducible in other independent cohorts. For example, it seems like Lactococcus lactis can regulate riboflavin production (Burgess et al. 2004), which has supposedly been used in the treatment of migraines. In other words, causality may be hard to distinguish: perhaps subjects with severe migraine problems are taking probiotic supplements. For example, the majority of American Gut participants reported taking some sort of supplement (I couldn't find a metadata variable specific for probiotics). In fact, it has been reported that Lactococcus lactis might alleviate symptoms from lactose intolerance (Li et al. 2012), and the individual with daily migraine occurrences was lactose intolerant.
I certainly applaud the work done by the American Gut project: from what I could tell, they were the only major metagenomic consortium that collected migraine metadata. However, I would feel more confident about these results if there were more subjects who commonly experienced migraines and/or if there was longitudinal data (to track metagenomic profiles during intervals when migraine subjects did or did not experience a migraine).
Of course, I should also point out that I wouldn't consider the analysis presented in this post to be comprehensive. I would certainly be interested in seeing what other conclusions could be drawn from this data. In fact, the processed data is publicly available in MG-RAST:
Migraine Subjects: http://metagenomics.anl.gov/metagenomics.cgi?page=MetagenomeProject&project=6547
Matched Control Subjects: http://metagenomics.anl.gov/metagenomics.cgi?page=MetagenomeProject&project=6594
If desired, you can also download by tables (normalized to counts per thousand) for phylum, class, and species distributions.
Unsurprisingly, there were not any substantial clustering between migraine and non-migraine subjects (otherwise, I would have expected this to be included in the American Gut preliminary report):
Unfortunately, I also didn't see any strong clustering based upon migraine frequency either:
FYI, I am showing PCA plots based upon species-level abundances for species with an average abundance of at least 100 counts per sample, but you can also view the case-vs-control phylum and class distributions as well as the migraine frequency phylum and class distributions.
Although I didn't see any major differences in the PCA plots, I went ahead and looked for any differences that occurred with a false-discovery rate (FDR) less than 0.05. I used the sRAP package for analysis, treating the 16S rRNA abundances like gene expression values. Although most of these results looked like artifacts from only having one subject that had migraines on a daily basis, I did consider Lactococcus lactis (p=0.00088, FDR = 0.042) to be an interesting candidate:
 |
| y-axis is abundance (count-per-thousand) on a log2 scale |
I double-checked the frequency of migraine subjects with lactose intolerance: the frequency was qualitatively higher compared to subjects with less frequent migraines (50% versus 28.6%), but this difference was not statistically significant (Fisher's exact p-value = 0.28). Additionally, I'm not sure about the interpreation if this Lactococcus lactis trend is found to be reproducible in other independent cohorts. For example, it seems like Lactococcus lactis can regulate riboflavin production (Burgess et al. 2004), which has supposedly been used in the treatment of migraines. In other words, causality may be hard to distinguish: perhaps subjects with severe migraine problems are taking probiotic supplements. For example, the majority of American Gut participants reported taking some sort of supplement (I couldn't find a metadata variable specific for probiotics). In fact, it has been reported that Lactococcus lactis might alleviate symptoms from lactose intolerance (Li et al. 2012), and the individual with daily migraine occurrences was lactose intolerant.
I certainly applaud the work done by the American Gut project: from what I could tell, they were the only major metagenomic consortium that collected migraine metadata. However, I would feel more confident about these results if there were more subjects who commonly experienced migraines and/or if there was longitudinal data (to track metagenomic profiles during intervals when migraine subjects did or did not experience a migraine).
Of course, I should also point out that I wouldn't consider the analysis presented in this post to be comprehensive. I would certainly be interested in seeing what other conclusions could be drawn from this data. In fact, the processed data is publicly available in MG-RAST:
Migraine Subjects: http://metagenomics.anl.gov/metagenomics.cgi?page=MetagenomeProject&project=6547
Matched Control Subjects: http://metagenomics.anl.gov/metagenomics.cgi?page=MetagenomeProject&project=6594
If desired, you can also download by tables (normalized to counts per thousand) for phylum, class, and species distributions.
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