We have examples of how Neanderthals gave Eurasians individual genetic variants that contribute to traits; however, most medically/evolutionarily relevant traits are complex, with contributions from thousands of parts of the genome. We wanted something more comprehensive...
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We use partitioned heritability to investigate the relationship between introgression and diverse traits. First, we show that genomic regions with Neanderthal ancestry are depleted of heritability for all traits considered, except those related to skin and hair.
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This expands upon previous findings showing that regions with Neanderthal ancestry are depleted for background selection and functional annotations. Not only are these regions depleted for functional annotations, but they are depleted for association with most human traits!
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Then, for the introgressed variants specifically, we ask: how do they contribute to the genetics/heritability of 400+ traits? (thanks @uk_biobank!)
*Enriched for contribution to skin/bone/WBC/respiratory traits
*Depleted for contribution to cognition/procreation
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Partitioned heritability quantifies the overall contribution to variation in traits, but does not consider the direction of effect.
(Think: Do Neanderthal variants contribute to height? VERSUS Are Neanderthal variants more likely to make me taller or shorter?)
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We used two approaches to test for directionality but, overall:
For some traits, Neanderthal variants contribute a directional effect (balding risk, younger menopause, larger FVC, morningness, sunburn risk). 🧑🦲🫁🌞
For other traits, we observed no/little directional bias.
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To contextualize these results, we propose a model that links these above results:
1. observed patterns of heritability and 2. direction of effect
to hypotheses about the history of selective pressures on introgressed haplotypes.
For example, consider the differences in potential pressures on introgressed variants associated with sunburn(skin color) vs. diabetes(glucose homeostasis)
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The relationship between complex trait heritability and evolution/selection is so complicated and interesting! I spent a lot of time trying to envision different scenarios. So for fun/learning, I built an interactive app: neanderthal-heritability.herokuapp.com with @plotlygraphs@heroku
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These models are an oversimplification of a lot of complex environmental/genetic/demographic factors. However, we hope our discussion/model provides useful context for our results and a framework for future work. Feedback and thoughts welcome!
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Notably, our work only quantifies contribution of common variants in European populations. We anticipate more genetic data from non-European populations, new statistical methods, and future simulations will continue to provide a window of understanding into our past! 🌏👩💻
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This work would not have been possible without an amazing community and some really thoughtful reviewers (check out new results since our @biorxivpreprint !) Shout out to:
Reflecting on today's fantastic #iMED2022, I am thrilled to share an app I've been creating to create high-quality🤓, collaborative🗺️, & dynamic 📈diagnostic #MedEd schemas!
By synthesizing topologically associating domain (TAD) maps across 37 diverse cell types with 41 genome-wide association studies (GWASs), we investigate the differences in disease association and evolutionary pressure on variation across the 3D genome landscape.
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We know that TAD boundary disruption by SV can lead to developmental disease and cancers. (Thus, selection acts against these SVs).
But what about the relationship between common human variation in TAD boundaries (eg. SNPs) and associations with complex traits?
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