Angela
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There's been a number of papers out on the subject of height in the last couple of years, and now we have two more. It seems that the impact of selection was overestimated because of the samples used in earlier papers.
Here are the two papers:
Reich and Patterson are involved with this one: "Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies".
Mashaal Sohail, Robert M. Maier, Andrea Ganna, Alexander Bloemendal, Alicia R. Martin, Michael C. Turchin, Charleston W. K. Chiang, Joel N. Hirschhorn, Mark Daly, Nick Patterson, Benjamin Neale, Iain Mathieson, David Reich, Shamil R. Sunyaev
https://www.biorxiv.org/content/biorxiv/early/2018/06/25/355057.full.pdf
"Genetic predictions of height differ significantly among human populations and these differences are too large to be explained by random genetic drift. This observation has been interpreted as evidence of polygenic adaptation, natural selection acting on many positions in the genome simultaneously. Selected differences across populations were detected using single nucleotide polymorphisms (SNPs) that were genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of sub-significant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection for diverse traits, the introduction of methods to do this, and claims of polygenic adaptation for multiple traits. All of the claims of polygenic adaptation for height to date have been based on SNP ascertainment or effect size measurement in the GIANT Consortium meta-analysis of studies in people of European ancestry. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. While we replicate most previous findings when restricting to genome-wide significant SNPs, when we extend the analyses to large fractions of SNPs in the genome, the differences across groups attenuate and some change ordering. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure, a more severe problem in GIANT and possibly other meta-analyses than in the more homogeneous UK Biobank. Therefore, claims of polygenic adaptation for height and other traits, particularly those that rely on SNPs below genome-wide significance, should be viewed with caution."
The other one is by Graham Coop, whose work is always extremely reliable and cutting edge, imo.
Jeremy J. Berg et al (inc. Graham Coop),
"Reduced signal for polygenic adaptation of height in UK Biobank"
https://www.biorxiv.org/content/early/2018/06/27/354951
"There is considerable variation in average height across European populations, with individuals in the northwest being taller, on average, than those in the southeast. During the past six years, a series of papers reported that polygenic scores for height also show a north to south gradient, and that this cline results from natural selection. These polygenic analyses relied on external estimates of SNP effects on height, taken from the GIANT consortium and from smaller replication studies. Here, we describe a new analysis based on SNP effect estimates from a large independent data set, the UK Biobank (UKB). We find that the signals of selection using UKB effect-size estimates for height are strongly attenuated, though not entirely absent. Because multiple prior lines of evidence provided independent support for directional selection on height, there is no single simple explanation for all the discrepancies. Nonetheless, our current view is that previous analyses were likely confounded by population stratification and so the conclusion of strong polygenic adaptation in Europe now lacks clear support. Moreover, these discrepancies highlight (1) that current methods for correcting for population structure in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of polygenic differences between populations should be treated with caution until these issues are better understood."
Razib Khan has also opined on the matter:
https://www.gnxp.com/WordPress/2018...ss-effected-by-selection-than-we-had-thought/
"Like an Old Testament prophet of yore Graham Coop has been prophesying that cryptic population stratification may be a major confounder in analyses for as long as I’ve known him with any degree of familiarity. So it’s no surprise he’s an author on one of two preprints which have rocked the genomics world:"
"Finally, recall that population structure within Europe is relatively weak and the distances between the groups low. It reminds you of how difficult polygenic traits are to analyze due to the small and subtle effects, and how they might be overwhelemed even by subtle population structure. And recall, even the British population has some of that… (albeit, an order of magnitude or so less than what you can find across Europe)."
However, as Khan points out, no one has answered the question as to how within family association studies can be so affected by population structure.
Here are the two papers:
Reich and Patterson are involved with this one: "Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies".
Mashaal Sohail, Robert M. Maier, Andrea Ganna, Alexander Bloemendal, Alicia R. Martin, Michael C. Turchin, Charleston W. K. Chiang, Joel N. Hirschhorn, Mark Daly, Nick Patterson, Benjamin Neale, Iain Mathieson, David Reich, Shamil R. Sunyaev
https://www.biorxiv.org/content/biorxiv/early/2018/06/25/355057.full.pdf
"Genetic predictions of height differ significantly among human populations and these differences are too large to be explained by random genetic drift. This observation has been interpreted as evidence of polygenic adaptation, natural selection acting on many positions in the genome simultaneously. Selected differences across populations were detected using single nucleotide polymorphisms (SNPs) that were genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of sub-significant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection for diverse traits, the introduction of methods to do this, and claims of polygenic adaptation for multiple traits. All of the claims of polygenic adaptation for height to date have been based on SNP ascertainment or effect size measurement in the GIANT Consortium meta-analysis of studies in people of European ancestry. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. While we replicate most previous findings when restricting to genome-wide significant SNPs, when we extend the analyses to large fractions of SNPs in the genome, the differences across groups attenuate and some change ordering. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure, a more severe problem in GIANT and possibly other meta-analyses than in the more homogeneous UK Biobank. Therefore, claims of polygenic adaptation for height and other traits, particularly those that rely on SNPs below genome-wide significance, should be viewed with caution."
The other one is by Graham Coop, whose work is always extremely reliable and cutting edge, imo.
Jeremy J. Berg et al (inc. Graham Coop),
"Reduced signal for polygenic adaptation of height in UK Biobank"
https://www.biorxiv.org/content/early/2018/06/27/354951
"There is considerable variation in average height across European populations, with individuals in the northwest being taller, on average, than those in the southeast. During the past six years, a series of papers reported that polygenic scores for height also show a north to south gradient, and that this cline results from natural selection. These polygenic analyses relied on external estimates of SNP effects on height, taken from the GIANT consortium and from smaller replication studies. Here, we describe a new analysis based on SNP effect estimates from a large independent data set, the UK Biobank (UKB). We find that the signals of selection using UKB effect-size estimates for height are strongly attenuated, though not entirely absent. Because multiple prior lines of evidence provided independent support for directional selection on height, there is no single simple explanation for all the discrepancies. Nonetheless, our current view is that previous analyses were likely confounded by population stratification and so the conclusion of strong polygenic adaptation in Europe now lacks clear support. Moreover, these discrepancies highlight (1) that current methods for correcting for population structure in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of polygenic differences between populations should be treated with caution until these issues are better understood."
Razib Khan has also opined on the matter:
https://www.gnxp.com/WordPress/2018...ss-effected-by-selection-than-we-had-thought/
"Like an Old Testament prophet of yore Graham Coop has been prophesying that cryptic population stratification may be a major confounder in analyses for as long as I’ve known him with any degree of familiarity. So it’s no surprise he’s an author on one of two preprints which have rocked the genomics world:"
"Finally, recall that population structure within Europe is relatively weak and the distances between the groups low. It reminds you of how difficult polygenic traits are to analyze due to the small and subtle effects, and how they might be overwhelemed even by subtle population structure. And recall, even the British population has some of that… (albeit, an order of magnitude or so less than what you can find across Europe)."
However, as Khan points out, no one has answered the question as to how within family association studies can be so affected by population structure.