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Review of: The phenotypic legacy of admixture between modern humans and Neandertals

Summary

The study by Simonti et al. (2016) sought to determine whether the introgression of H. neanderthalensis into H.sapiens genome could have an impact on the variation of clinical phenotypes in a modern European-descent population. The research consisted on pairing phenotype data publicly available on electronic health records (EHRs) from the Electronic Medical Records and Genomics (eMERGE) Network, which combines patients’ genetic data from nine cities in the U.S.

28, 416 patients of European descent were pooled from the set, and a set of over 135,000 SNPs most likely derived from Neandertal alleles was filtered. Previous studies had hypothesized a correlation between Neandertal alleles and variation in lipid metabolism,immunity, depression, digestion, hair, and skin. Thus, the cohort used genome-wide complex trait analysis (GCTA) of 1495 Neandertal SNPs, and found that the risk of depression, myocardial infarction, and corns and callosities were significantly explained by the SNPs (and in their replication as well).

The study then focused on finding if there was any correlation between single loci and modern human phenotypes. They performed a phenome-wide association study (PheWAS) of the same 1495 SNPs, and demonstrated four highly significant phenotypic associations (and in their replication as well).

Finally, they also showed that Neandertal SNPs were highly associated with neurological and psychiatric phenotypes, and with fewer digestive phenotypes. The cohort alluded that the Neandertal SNPs were probably advantageous to early modern humans, and these are mismatches due to our current modern environment.

Opinion

In general, the cohort’s methods and structure efficiently established the rationale for their investigation, as well as demonstrated tangible and verifiable results explaining the phenotype association between Neadertal and modern humans. The second phase based on replication of data sets was a sound approach to reduce false discovery rates, and further make their conclusive remarks more significant. Also, I thought that the use of EHR data was interesting aspect of the paper as it opens possibilities for paired meta-analysis with other big data sets available, and could further our understanding on clinical pathologies. However, I had difficulty in grasping that the EHRs were actually integrated through the eMERGE network. At first, it seemed that both were used simultaneously to achieve the Neandertal SNPs data set. Moreover, even though the use of different methods was justified and successful in establish the cohort’s conclusion, the extent to which they were explained was lacking. Additionally, the statistical and computational analyses could have had a more detailed background explanation (without prompting the reader to look at supplementary materials or elsewhere). Lastly, Figure 1 was particularly difficult to interpret and follow the full array of the methodologies used, since their rationale for them is explained in subsequent parts of the text.

Figure Summaries

Figure 1

Overall, the figure demonstrates the array of methods used in this investigation that lead to their various conclusions. Panel A shows the pairing of patients' genotype with EHR in the eMERGE Network in order to look for clinical phenotypes and Neandertal SNPs. Panel B and C shows the genotypic and phenotypic similarity between the patients in all Neandertal SNPs, and the use of GCTA in Neandertal SNPs in order to find the disease-risk associated with them, respectively Panel D shows the PheWAS study to demonstrate the four highly significant SNPs. Panel E focuses in one of the significant SNPs and its expression level.

Table 1

This table shows the results of the GCTA, and demonstrates eight traits that can be associated with Neandertal SNPs in both the discovery and replication sets. Three traits remained significant after a GRM analysis, which accounted for non-Neandertal variation: depression, myocardial infarction, and corns and callosities. The figure demonstrates the verifiability of their methods, and that their remarks about phenotype associations are tangible.

Table 2

This table highlights the four individual significant Neandertal SNP-phenotypic associations with the use of PheWAS method in both the discovery and replication set. The figure highlights the importance of higher scrutiny and replication in order to attain equally verifiable results.

Figure 2

This figure shows the Neandertal SNP enrichment in association with specific phenotypes using the PheWAS method. By comparing phenotype-associations between Neandertal and non-Neandertal, they showed that Neandertal SNPs are more highly associated with neurological and psychiatric phenotypes than digestive ones.  

Reference

Simonti, C, Vernot, B, Bastarache, L, Bottinger, E, Carrell, D, Chisholm, R, Crosslin, D, Hebbring, S, Jarvik, G, Kullo, I, Rongling, L, Pathak, J, Ritchie, M, Roden, D, Verma, S, Tromp, G, Prato, J, Bush, W, Akey, J, & Denny, J. 2016. The phenotypic legacy of admixture between modern humans and Neandertals. Science 351:737-741. http://science.sciencmag.org/content/351/6274/737

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