Commingling and complex segregation analysis of fasting plasma glucose in the Lipid Research Clinics family study

Mixture distributions in human genetics research

The use of mixture distributions in genetics research dates back to at least the late 1800s when Karl Pearson applied them in an analysis of crab morphometry. Pearson's use of normal mixture distributions to model the mixing of different species of crab (or 'families' of crab as he referred to them) within a defined geographic area motivated further use of mixture distributions in genetics research settings, and ultimately led to their development and recognition as intuitive modelling devices for the effects of underlying genes on quantitative phenotypic (i.e. trait) expression. In addition, mixture distributions are now used routinely to model or accommodate the genetic heterogeneity thought to underlie many human diseases. Specific applications of mixture distribution models in contemporary human genetics research are, in fact, too numerous to count. Despite this long, consistent and arguably illustrious history of use, little mention of mixture distributions in genetics research is made in many recent reviews on mixture models. This review attempts to rectify this by providing insight into the role that mixture distributions play in contemporary human genetics research. Tables providing examples from the literature that describe applications of mixture models in human genetics research are offered as a way of acquainting the interested reader with relevant studies. In addition, some of the more problematic aspects of the use of mixture models in genetics research are outlined and addressed.

Family studies of non-insulin-dependent diabetes mellitus in South Indians

Though a genetic basis for non-insulin-dependent diabetes mellitus (NIDDM) is clear, the likely mode of inheritance is not known. The segregation of NIDDM was studied in 64 nuclear South Indian pedigrees (449 individuals) ascertained through an affected proband having both parents and more than 1 sibling alive and available for oral glucose tolerance testing. A high proportion of parents were found to be of abnormal glucose tolerance [89 of 128 (70%) diabetic and 11 of 128 (9%) impaired]. Complex segregation analysis was performed using (1) POINTER which implements the mixed model and distinguishes major gene, multifactorial and non-transmitted environmental contributions to affection and (2) COMDS which implements an oligogenic model with major gene, modifier gene and environmental contributions to a) affection and b) diathesis (an ordered polychotomy amongst non-affected family members, based on 2-h plasma glucose level). Using POINTER, there was no formal support for a major gene and the most parsimonious solutions were achieved with multifactorial models. Using COMDS, we found i) significant improvements in models when information on glucose levels in nondiabetic family members (diathesis) was included, ii) support for segregation of a diallelic gene as well as background familial resemblance, and iii) under the best-supported model, this diallelic locus featured incomplete dominance (d = 0.8) and a disease-predisposing allele frequency of 14%. In South Indians, segregation of NIDDM is inadequately described by simple major gene models: more complex models provide more satisfactory descriptions. This finding, if applicable in other populations, has important implications for the search for diabetes-susceptibility genes.