The main features of any organism’s life cycle are defined by traits such as size at birth, growth rate, age and size at maturity, age-specific reproductive investment, offspring size and quantity, and its lifespan. Life-history (LH) theory has been used across taxa to explain co-variation in these traits as evolutionary tradeoffs in physiological resource allocation reflecting resource availability and extrinsic mortality risk: Low risk, resource rich environments favour investment into the future while in high mortality risk, low resource environments the value of the future is discounted, leading to decreased investment into growth and maintenance and increased investment into earlier reproduction being adaptive. Anthropological and epidemiological studies have found strong correlations between anthropometric and reproductive traits at the core of LH tradeoffs, such as adult height and weight and age at menarche and menopause in humans. Twin and other family studies of these traits show significant genetic effects on the traits independent of the environment (i.e. high heritability)4, suggesting strong genetic links between them. However, despite several well-powered genome-wide association studies (GWASs) conducted to map their genetic architecture, very few variants with significant effect on multiple LH traits have been found.
This may be due to challenges in combining associated variants from separate GWASs – stemming from confounding environmental, parental, and indirect genetic effects – that are expected to obscure any shared signal, hindering the discovery of shared genetic pathways. As a result, the proximate biological mechanisms connecting reproductive and anthropometric traits are poorly understood. Furthermore, epidemiological studies have found that LH traits are linked to susceptibility to cardiovascular disease, type 2 diabetes, and certain types of cancers, independent of risk factors such as smoking, alcohol consumption, and socioeconomic status, raising the question: Can epistatic genetic variants in shared gene regulatory pathways and networks also explain variation in susceptibility to these diseases?
What is more, LH theory predicts that past changes in extrinsic mortality and resource availability would result in natural selection on reproductive and anthropometric traits. The transition from a hunting and gathering to a farming subsistence strategy starting around 10,000 years ago, and the subsequent increases in population densities, warfare, urbanisation, and infectious disease loads, have had an impact on both mortality risk and resource availability in Holocene Europe. Analysis of long bones and genetic data from human fossils in West Eurasia suggest that human stature has changed considerably over this period, but life history traits have not been analysed together as a package to understand the extent to which recent natural selection on human life-histories has shaped present day variation in anthropometric and reproductive traits as well as affected susceptibility to certain diseases through pleiotropic
effects.
This project has 3 main Research objectives (ROs):
RO1: Leverage data from two large biobanks, the Estonian Biobank (EstBB) and the UK Biobank (UKBB), with multi-trait GWAS to identify genes and regulatory regions that affect LH traits individually and jointly and map how these variants segregate across cell types and tissues. This WP will deliver the first systematic map of pleiotropic interactions in genes and gene regulatory regions for reproductive and anthropometric traits.
RO2: Construct a gene regulatory network, informed by biological pathways, pleiotropic genetic variants and epigenetic effects across cell types and tissues, that connect LH traits and associated disease outcomes. This WP will provide a comprehensive understanding of how different LH traits are biologically linked to each other and disease outcomes, and the biological mechanisms that enable external (environmental) factors to exert influence on many of LH traits jointly.
RO3: To leverage ancient DNA data and powerful methods for inference of recent selection from whole genome sequences (WGS) to investigate the extent to which evolution has shaped different LH traits and affected susceptibility to disease in present-day populations. Furthermore, to test the hypothesis that genes in the core parts of the LH trait network are highly conserved across taxa, whereas the genes that connect the core of this network to loci associated with diseases have a younger evolutionary origin and are less conserved.
Originality: The project is original in its multi-angled and highly interdisciplinary approach to a question that bridges ecology, evolution, and human medical genomics. It is innovative in integrating epidemiological and genomic data with evolutionary analysis. The project is also ambitious in its scope, answering big questions yet delivering tangible results using data from two of the worlds’ most comprehensive biobanks (EstBB and UKBB) in terms of both genetic and phenotypic data, as well as combining population-level and family-level data with state-of-the-art statistical tools to discover and connect biologically relevant genetic variants.
