Of the 5742 individuals in the main pedigree, 1503 were inbred. The average F of the inbred individuals was 0.044, with a maximum of 0.16 (0.16 indicates slightly more inbreeding than would result from an avuncular marriage). Of the 337 individuals with phenotypes/genotypes, 60 are inbred – the average inbreeding in these individuals was 0.026, with a maximum of 0.081.

Figure 3 shows the relationship between marker-derived homozygosity and F for the 60 inbred individuals. The gradient is 1.05 (SE 0.15); this is not significantly different from the prediction of 1–0.21=0.79. For individuals who are (based on the available pedigree information) not inbred (F=0), there is some variability in their marker-derived homozygosity but the mean value in the non-inbred individuals is 0.21 – this is the same as the intercept derived from the inbred individuals. A small number of individuals from outside the main pedigree had marker homozygosity values much higher than expected if they were not inbred – it is likely that some of these individuals are in fact related to the main pedigree but the available marker data were not sufficient to allow these individuals to be explicitly connected to the main pedigree (using the program GRR).

Figure 3 Marker-derived homozygosity and inbreeding coefficient. Full size image

The average proportion of the genome from initial founders obviously decreases over time (as more new founders are ‘married-in’), but the contribution of the initial founders remains reasonably high. There are 295 non-founder individuals in the main pedigree with phenotypes. On average, these individuals carry 18% of their genome from the male original founders and 14% of their genome from the female initial founders – histograms are in Figure 4. The present-day individual from Figure 2 is on the right-hand side of the histograms – she is expected to have inherited 61% of her genome from founder males and 39% from founder females and has F=0.029. The female-specific histogram in Figure 2 can also be interpreted as showing the degree of Polynesian/Caucasian admixture in the Norfolk Island population (assuming that all new founders were Caucasian). Considering each initial founder separately, some of the original founders contribute much more to present-day phenotyped individuals than others (range: 0.2–3.1%).

Figure 4 Contribution of ‘original’ founders: (a) males, (b) females. Full size image

There is a strong relationship between inbreeding and ancestry – individuals with ancestors who intermarried with others from small group of founders will be inbred and also carry a large proportion of the original founder individuals’ DNA. The correlation between F and Polynesian ancestry was 0.78. Graphs showing the relationship between proportion of genome from initial founders (ie, ancestry) and inbreeding coefficient are in Figure 5. The correlation between marker-derived homozygosity and Polynesian ancestry was much lower (0.19).

Figure 5 Relationship between ancestry and inbreeding: (a) males, (b) females. Full size image

Heritabilities (h2) for each trait were estimated using the mixed model (Table 1). The mixed model was also used to estimate the effect of Polynesian ancestry, taking into account the known relationships between individuals. Polynesian founder ancestry significantly increased total triglycerides, body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP) for individuals with more Polynesian ancestry (Table 1). There was also an indication that Polynesian ancestry increased total cholesterol. Although the effects of ancestry on the other traits were non-significant, the effect direction was always consistent with Polynesian ancestry leading toward less favorable outcomes with respect to CVD risk (increases in all traits with the exception of HDL and height). It seems likely that having greater Polynesian ancestry generally increased individuals susceptibility to traits associated with CVD when those individuals were ‘exposed’ to a Western diet.

Table 2 shows the effect of GWH and inbreeding (F) on each trait. For GWH, N=593; for F, N is only 60 because only individuals from the main pedigree can be assessed for their F-value, and only a subset of individuals in the main pedigree are inbred. The only trait significantly affected by marker-derived homozygosity was height and this result was also confirmed in the small set of inbred individuals. Total cholesterol and SBP were significantly related to F, although interpretation of this is made difficult by the strong correlation between F and ancestry. The individuals who have high levels of Polynesian ancestry tend to maintain that high level as a result of their being inbred descendants of the small number of Polynesian founders. Owing to the strong correlation between F and ancestry in the pedigreed individuals in the main pedigree, it is difficult to fully disentangle their effects. Fiting both F in the model after ancestry resulted in F becoming non-significant (and vice versa). For GWH and ancestry, the correlation was substantially lower (0.19).

Table 2 Effect of homozygosity and inbreeding on CVD-related traits Full size table

The mixed-model results shown are for the main pedigree together with the additional individuals (N=593). The results were similar if the analysis was restricted to just the N=295 non-founder individuals in the main pedigree.

We attempted to fit dominance components of variance in the mixed model but with little success. For some of the traits, including a dominance component in the model led to convergence problems. For other traits, estimates of the dominance variance were estimated but (1) our confidence that these results were correct and were not convergence artefacts was low and (2) the estimated SE of the dominance components were very large. Such problems were not entirely surprising because our pedigree has somewhat limited information to estimate dominance variance because dominance variance can only be estimated from a limited number of (phenotyped) relative pairs such as full sibs. Convergence problems are common when there is only limited information to estimate a parameter in the mixed model.