Comment by Real_S | Hacker News Reader

Comment by Real_S | Hacker News Reader

Parent Full thread

Population structure is controlled through the use of the structure as a co-factor in the analyses. They use a principal component analysis on the genotypes to estimate the structure, and then use the first few principal components (PCs) as cofactors in the analyses.

So if the European population they used consisted of half English and half French participants, then the first PC would likely divide the two. So if British or French ethnicity affected the analysis, this effect would be reduced or eliminated using just the first PC.

How many PCs should be used? Well, ten is a common number chosen. Is it enough? Probably for most studies including this one.

So ancestry and ethnicity in this type of research emerges purely from a PC analysis on the genotypes. They do not use self-reported ethnicity or any other type of common ethnic grouping. To control for population structure, self-reported ethnicity is rarely useful. Its far too unreliable. But these groupings do sometimes loosely correspond to the PCs found in the analysis, supporting the use of PC as a method to control for ethnicity.

Do you believe these findings though?

(original article: http://www.pnas.org/content/111/Supplement_3/10796.full )

To me there are a few things worth highlighting, that are at least tangentially relevant:

1. This article was a PNAS Direct Submission. PNAS Direct Submission, a privilege typically reserved for members of the National Academy of Sciences, is like using trump-card to basically skip peer review. Since NAS members are usually great scientists with a track-record of publishing in high-impact peer reviewed journals, PNAS Direct Submissions are usually saved for pet-projects where the underlying science is... mmmm... of dubious quality. This is not always the case, but when all-star scientists opt for PNAS DS, it's certainly a reason to be speculative.

2. Nick Christakis and James Fowler have teamed up for a number of fancy-ass studies (the type that ensure people will want to write wikipedia pages about them, and lead to TED talk invites); some suggesting personal attributes like obesity, smoking, and happiness arise via 'social contagion', that is, behavioral propensities are transmitted over social networks. And studies like this one, where they find friendship affinities embedded in the genome.

3. I recently read a genome-wide association study (GWAS) with over 400 authors (https://www.ncbi.nlm.nih.gov/pubmed/28714976). I think 400 authors is way above median, but even relatively tame GWAS typically require a group effort just for data QC. Here, somehow these two guys did it all themselves.

4. Not only did they find that some SNPs were positively correlated, they also found some that were negatively correlated... "Across the whole genome, friends’ genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a “friendship score” that predicts the existence of friendship ties in a hold-out sample." So the HN/Nature title might as well be: "Friends are Genetically similar, and Genetically Different".

1. You are perceptive, this is usually something to watch out for. However, it does not always indicate that a study is flawed, just that the research might have met with unwanted resistance, and the authors are in position to avoid that resistance.

2. Yes, these scientists are looking to make their research popular, highlighting an unfortunate conflict of interest present in academia. They do this to get big grants. Important observation, but insufficient to dismiss a finding out of hand.

3. So many authors, such a joke! These people mostly just help collect data, or sometimes simply share data they already have and then give the manuscript a quick read before publishing. But that is actually beside the point. If a lab already had data ready, and isn't pressured to add authors for political reasons, then two authors is not necessarily a red-flag. In fact, these analyses are relatively easy to do with available software. If they have the data, they just plug and chug.

4. The findings of the paper suggest strongly that friends are more genetically similar, on average, akin to fourth cousins. The results have yet to be rebutted to my knowledge. The fact they found some regions were negatively correlated does not conflict with their overall results. I have some doubts that their regional analyses should carry much weight (e.g. olfactory and immune regions). Furthermore, their explanations using natural selection appear to be a stretch. These are possible overstatements of results, allowed because of your points 1 and 2.

My overall impression of the paper is that main results are somewhat interesting and entirely novel. But there is a ton of stretching for just-so stories and "interesting" findings that will be unlikely to hold up. Typical PNAS.

Thanks for these replies. Also, very cool idea you have here: Cryptography for genetic material

You seem to not like the result of the study and making non-arguments to try to discredit it.

I don't feel strongly one way or the other about these results, or their implications. If anything I think they are fairly interesting. You're right, these would be weak arguments if I were trying to discredit the findings (and are fairly ad hominem-y).

I am not a genomics expert, so my comment above was intended to be more of a question directed to Real_S and those versed in genomics analysis (i.e. given this list of concerns, are these findings still legit?).

> 3. I recently read a genome-wide association study (GWAS) with over 400 authors (https://www.ncbi.nlm.nih.gov/pubmed/28714976). I think 400 authors is way above median, but even relatively tame GWAS typically require a group effort just for data QC. Here, somehow these two guys did it all themselves.

This is from Framingham. The QC was all done well before, so not having 400 authors is no more suspicious than a one or two-author paper using UKBB data from 500k people - the point of having a long-running systematic study such as Framingham or UKBB or the twin registries is, among other things, to amortize the cost of data collection and preparation, instead of expecting every paper to collect an entire new sample and build a pipeline and analyze it.

>some suggesting personal attributes like obesity, smoking, and happiness arise via 'social contagion', that is, behavioral propensities are transmitted over social networks.

Don't know about happiness, but regarding smoking and obesity this seems so obvious to not even need a study (excluding pathological causes for obesity of course which are fewer and far between in people compared to the epidemic rates of obesity we see).

And perhaps happiness is quite impacted by living among other "positive looking/happy/chilled out" people as well -- it sure doesn't help if you're into a social network of depressed people, grumpiness and misery.

Reply on news.ycombinator.com