Estimation of genetic model parameters: Variables correlated with a quantitative phenotype exhibiting major locus inheritance

A major locus that is detected through its effect on one phenotype (a primary trait) may also affect other quantitative phenotypes or qualitative disease endpoints (secondary traits). The pattern of effects for the mutant allele. The effects are directly estimable when “measured genotypes” or a tightly linked marker allow unambiguous assignment of major locus genotypes. When genotype assignments are ambiguous for a major locus detected through its effect on a quantitative primary trait, we propose estimators using genotypic probabilities. Making certain reasonable assumptions, we demonstrate asymptotic unbiasedness of these genotypic probability estimators of the genotypic means and variances for either the quantitative primary or secondary traits, of the covariances between quantitative primary and secondary traits, and of prevalences for the secondary qualitative traits. An important application of genotypic probability estimators is to define an effect of a major locus that cannot be detected upon analysis of the variable; for example, major locus effects may be defined for hypertension or blood pressure as secondary traits, but not detected as primary traits.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101835/1/1370060203_ftp.pd

Indications of Linkage and Association of Gilles de la Tourette Syndrome in Two Independent Family Samples: 17q25 Is a Putative Susceptibility Region

Gilles de la Tourette syndrome (GTS) is characterized by multiple motor and phonic tics and high comorbidity rates with other neurobehavioral disorders. It is hypothesized that frontal-subcortical pathways and a complex genetic background are involved in the etiopathogenesis of the disorder. The genetic basis of GTS remains elusive. However, several genomic regions have been implicated. Among them, 17q25 appears to be of special interest, as suggested by various independent investigators. In the present study, we explored the possibility that 17q25 contributes to the genetic component of GTS. The initial scan of chromosome 17 performed on two large pedigrees provided a nonparametric LOD score of 2.41 near D17S928. Fine mapping with 17 additional microsatellite markers increased the peak to 2.61 (P=.002). The original families, as well as two additional pedigrees, were genotyped for 25 single-nucleotide polymorphisms (SNPs), with a focus on three genes in the indicated region that could play a role in the development of GTS, on the basis of their function and expression profile. Multiple three-marker haplotypes spanning all three genes studied provided highly significant association results (P<.001). An independent sample of 96 small families with one or two children affected with GTS was also studied. Of the 25 SNPs, 3 were associated with GTS at a statistically significant level. The transmission/disequilibrium test for a three-site haplotype moving window again provided multiple positive results. The background linkage disequilibrium (LD) of the region was studied in eight populations of European origin. A complicated pattern was revealed, with the pairwise tests producing unexpectedly high LD values at the telomeric TBCD gene. In conclusion, our findings warrant the further investigation of 17q25 as a candidate susceptibility region for GTS

An application of a model for a genotype-dependent relationship between a concomitant (age) and a quantitative trait(LDL cholesterol)in pedigree data

In most genetic studies in humans the variability in a quantitative trait is adjusted for variability in concomitants (age, sex, etc) using a single regression equation prior to analyses of pedigree data. To illustrate an alternative approach, a single locus genetic model was tested. This model incorporates genotypic effects on the level of the trait, the variability in the trait, and the relationship between a concomitant and the trait. In this study, the model was applied to measures of age and low-density lipoprotein (LDL) cholesterol in a large kindred with familial hypercholesterolemia. The application of this model to 322 individuals in four generations provided evidence that genotypic variation at a single locus influences LDL levels early in life, the rate of increase of LDL with age and the phenotypic variance. A model with genotype-dependent slope and variance fit the data signifcantly better than a model with slope and variance independent of genotype. The inclusion of age-specific genotypic differences contributed to identification of high-risk individuals, to statistical support for a major locus, and to evidence for genetic determination of the tracking of LDL levels. Models that incorporate genotype-specific concomitant effects have the potential to represent more realiscally the relationship between genotypic variability and quantitative phenotypic variation than models that assume that these effects do not exist.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38495/1/1370010403_ftp.pd

Assortative mating for human height: A meta-analysis

OBJECTIVES: The study of assortative mating for height has a rich history in human biology. Although the positive correlation between the stature of spouses has often been noted in western populations, recent papers suggest that mating patterns for stature are not universal. The objective of this paper was to review the published evidence to examine the strength of and universality in assortative mating for height. METHODS: We conducted an extensive literature review and meta-analysis. We started with published reviews but also searched through secondary databases. Our search led to 154 correlations of height between partners. We classified the populations as western and non-western based on geography. These correlations were then analyzed via meta-analytic techniques. RESULTS: 148 of the correlations for partner heights were positive and the overall analysis indicates moderate positive assortative mating (r = .23). Although assortative mating was slightly stronger in countries that can be described as western compared to non-western, this difference was not statistically significant. We found no evidence for a change in assortative mating for height over time. There was substantial residual heterogeneity in effect sizes and this heterogeneity was most pronounced in western countries. CONCLUSIONS: Positive assortative mating for height exists in human populations, but is modest in magnitude suggesting that height is not a major factor in mate choice. Future research is necessary to understand the underlying causes of the large amount of heterogeneity observed in the degree of assortative mating across human populations, which may stem from a combination of methodological and ecological differences

A Copy Number Variant on Chromosome 20q13.3 Implicated in Thinness and Severe Obesity

Background/Objectives. To identify copy number variants (CNVs) which are associated with body mass index (BMI). Subjects/Methods. CNVs were identified using array comparative genomic hybridization (aCGH) on members of pedigrees ascertained through severely obese (BMI ≥ 35 kg/m2) sib pairs (86 pedigrees) and thin (BMI ≤ 23 kg/m2) probands (3 pedigrees). Association was inferred through pleiotropy of BMI with CNV log⁡2 intensity ratio. Results. A 77-kilobase CNV on chromosome 20q13.3, confirmed by real-time qPCR, exhibited deletions in the obese subjects and duplications in the thin subjects (P=2.2×10-6). Further support for the presence of a deletion derived from inference by likelihood analysis of null alleles for SNPs residing in the region. Conclusions. One or more of 7 genes residing in a chromosome 20q13.3 CNV region appears to influence BMI. The strongest candidate is ARFRP1, which affects glucose metabolism in mice