Background. Populations of African ancestry have greater bone strength and lower osteoporotic fracture risk than other ethnic groups but there is little information about skeletal health among individuals of African heritage.

Methods. Univariate, bivariate and multivariate analytical methods under the variance components framework were employed to dissect the genetic and environment determinants for DXA and pQCT measured bone strength related phenotypes. Our analyses were performed on phenotypic and genotypic data on 471 individuals aged 18+ from 8 large, multigenerational Afro-Caribbean families.

Results. The major conclusions of this study are that (1) compared to Caucasians and African Americans, Afro-Caribbeans have the highest peak areal BMD and slowest bone loss rate, but heritabilities of many bone strength related traits are similar among different populations, and (2) genes and environmental factors differentially affect trabecular versus cortical traits, and also BMD versus bone size. These conclusions are supported by differences in heritability and genetic correlation estimates among these bone categories, differential effects of environmental risk factors, as well as associations with different candidate genes. We also evaluated the capability of two multivariate analysis methods for uncovering underlying genetic factors using both simulated and real family data. We concluded Factor Analysis behaves better for both simulated and real data compare to Principal Component Analysis. The residual strategy increases the probability that composite phenotypes detect underlying genetic components if no gene-environment interaction is involved. And most importantly, composite phenotypes from multivariate analysis demonstrated their capabilities to capture more and stronger association signals in real data analysis.

Public health significance. Our work has identified the facts that environmental risk factors and genetic determinants may differentially affect various bone compartments and types of bone phenotypes. This information will contribute to the understanding of the underlying genetic architecture of osteoporosis and hence lead to better methods of treatment and prevention of the disease.