Study of isolated populations require an understanding of the unique population history and admixture, which has led to unique genomic structure both in terms of long 'runs' of homozygosity (due to inbreeding), as well as extensive stretches of locus-specific admixture (heterozygosity introduced via population admixture). Genomic structure in populations has the potential to influence genetic associations with disease, and is therefore important to consider in future study design. This knowledge can then be used appropriately as a valuable tool in disease mapping and association studies. This work increases the accuracy of previous estimates of inbreeding and documents for the first time runs of HBD in the NI population. Additionally, this study identified significant correlations between these unique structural components and disease risk traits for Metabolic Syndrome and CVD. Importantly both increased prevalence and underlying population/genetic based association with Metabolic Syndrome in the NI pedigree has been identified. This provides strong justification for further examination of the NI population in the context of Metabolic Syndrome risk and prevalence. Future research should focus in on the identified area's of locus-specific admixture and HBD in light of the correlations with MetS and related traits.

The authors have no competing interests to declare.

Contributions here....

This research was supported by funding from a National Health and Medical Research Council of Australia (NHMRC) Project Grant. It was also supported by infrastructure purchased with Australian Government EIF Super Science Funds as part of the Therapeutic Innovation Australia - Queensland Node project. MCB was supported by a Corbett Postgraduate Research Scholarship. The SOLAR statistical genetics computer package is supported by a grant from the US National Institute of Mental Health (MH059490). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

We would like to acknowledge Amanda Miotto and also QUT for providing computational support for this project. Additionally, we extend our appreciation to the Norfolk Islanders who volunteered for this study.