copies between two individuals to evaluate whether genetic evidence supported putative relationships reported in the Kosrae pedigree. A complete list of putative first-degree relative pairs (parent-child, sibling, half-sibling) was extracted from the pedigree. For each putative first-degree relative pair, we examined genetic evidence supporting or refuting that relationship and corrected relationships in the Kosrae pedigree accordingly. For example, in a set of individuals forming a putative nuclear family, we verified that all combinations of parent-child relationships and sibling relationships met our criteria for genetic relatedness. ‘‘Placehold- er’’ individuals were added to the pedigree as necessary to reflect genetic relationships, such as the addition of a ‘‘placeholder’’ father for a newly-discovered maternal half-sibling. The correction of numerous relationship pairs and our ability to detect cryptic relationships enabled consolidation or elimination of over 70 non- genotyped ancestors, resulting in ‘‘tightening’’ of the Kosrae family tree. Thirteen pairs of monozygotic twins and thirty-five duplicate sample pairs were identified by genotype similarity. Sample identity was confirmed from patient records (name, birth date) and one subject from each pair was included in the association analyses. We identified 58 offspring from consanguineous matings, where a common ancestor could be identified in the extended Kosrae pedigree; these consanguineous offspring were excluded from association analyses. An additional nine individuals were excluded from the dataset, as they self-reported non-Micronesian ethnicities and could not be connected to the pedigree. Breaking the Pedigree Three approaches were considered to break the extended pedigree into smaller units. Founders consist of a filtered subset of sibships-without-parents, such that any genotyped offspring of a founder sibship are removed from the dataset. Founder sibships are drawn primarily from the upper levels of the Kosrae family tree. For example, 582 ‘‘founders’’ in 247 sibships were identified for the BMI phenotype. Sibships without parents consist of two or more individuals known to share both parents. Since the Kosrae cohort spans multiple generations, members of one family group are frequently parents or cousins of other family groups. Information about parents is used to define a sibship; however, any genotyped parents are considered only in the context of their own siblings. For BMI, 1,871 individuals were included in 467 sibships of size $2. Nuclear families consist of two genotyped parents and one or more offspring. Where one genotyped parent is available, offspring are included as a sibship without parents and the genotyped parent is included in the context of its own siblings. Where no genotyped parents are available, individuals contribute as members of a sibship without parents. ‘‘Sibships of size one’’ and ‘‘Unrelateds’’. Genome-wide estimates of identity-by-descent (pihat) were used to select a subset of distantly related individuals. Genotyped individuals were randomly ordered, and individuals were selected if they were related to every other member of the group below a set threshold. A threshold of pihat #0.125 was used for individuals included in the association analyses (‘‘sibships of size one’’), corresponding to a relationship of first cousin or less. This selection process was repeated for 1,000 iterations, after which the largest set of individuals was identified for further use. These individuals contribute in the Between-family association score. For example, 202 ‘‘sibships of size one’’ contribute to the analysis for BMI. A more stringent threshold of pihat #0.08, applied to the entire dataset of 2,906 study participants, resulted in n = 133 individuals GWAS on the Island of Kosrae related as less than first cousins. These individuals are treated as independent observations (‘‘unrelateds’’), suitable for use in any analysis requiring unrelated individuals (e.g., calculating allele frequencies, LD). Selection of a scheme to break the extended pedigree. In selecting a method to break the extended Kosrae pedigree, we considered three factors: maximum use of genotyped individuals (a rough proxy for power); minimal inflation of the association test statistic; and the practical consideration of retaining similar family structures across multiple traits. ‘‘Founders’’ (n = 582) have the fewest relationships with other individuals in the complete pedigree and were expected to minimize association score inflation due to excess relatedness between families. However, the exclusion of over 2,300 genotyped individuals from the analysis and concomitant loss of power persuaded us against this family configuration. Sibships-without-parents and nuclear families include similar numbers of individuals for a given trait. We note that the optimal configuration of nuclear families varies across phenotypes, whereas sibships-without-parents minimize differences in family structure across multiple traits. Individuals lacking a phenotype are simply omitted from a sibship and do not radically change the number of sibships available for analysis. The extended Kosrae pedigree was broken into sibships-without-parents separately for each trait and analyzed for association. ‘‘Spiked’’ Datasets for Data Simulations We performed empirical evaluations of power for each association method using simulated datasets. We ‘‘spiked’’ an effect of known size (explaining an additional 0.5%, 1% or 2% variance) into an existing Kosraen phenotype (BMI) and analyzed this modified phenotype with observed Kosraen genotypes, thereby retaining the true genotype-phenotype correlation be- tween related study subjects. A subset of 1,000 SNPs across the genome were randomly selected and filtered to retain SNPs with MAF.0.01. The remaining 770 SNPs were analyzed for association with the spiked phenotype. A total of 770 spiked phenotypes were generated, in which each phenotype was altered to reflect association to a different SNP of the random subset. These 770 phenotypic datasets were analyzed for association to the spiked SNP using FBAT and PLINK/QFAM under an additive model [13,40]. Calculating Effective Sample Size We used empirical power estimates from the BMI ‘‘spiking’’ experiment and the module for variance components QTL association for sibships in the Genetic Power Calculator [20] to estimate the effective sample size of our cohort, or the number of unrelated individuals required to obtain power equivalent to that provided by the Kosraen sibships. Power calculations were performed assuming no dominance, minor allele frequency of 0.2, and direct genotyping of the causal variant. For BMI, the 2,073 individuals included in the association analysis have power equivalent to ,840 unrelated individuals. Association Analyses Quantitative trait data were analyzed under an additive model using the QFAM module of PLINK [13]. Nominal scores were permuted to obtain an empirical p-value while maintaining familial correlation between genotype and phenotype. The permutation procedure employed by QFAM corrects for related- ness within families. Between-family relatedness is not addressed in QFAM and is the major source of score inflation (see Dataset S1, PLoS Genetics | www.plosgenetics.org 15 February 2009 | Volume 5 | Issue 2 | e1000365