Transmission ratio distortion in families from the Framingham Heart Study

BACKGROUND: One implicit assumption in most linkage analysis is that live-born siblings unselected for a phenotype do not share alleles greater than the Mendelian expectation at any particular locus. However, since most families are recruited for genetic studies because of the presence of disease, there is little data available to confirm that this is the case. We hypothesized that loci that behave in a non-Mendelian fashion could be identified using genotype data from the Framingham Heart Study families. We tested the hypothesis that live-born sibs, either stratified by or irrespective of gender, demonstrate excess sharing of alleles on the autosomes, i.e., transmission ratio distortion. Multipoint linkage analysis of siblings either according to gender or not was performed using an allele-sharing method. Such observations may have implications for the mapping of loci for complex disease and quantitative traits in human pedigrees. RESULTS: No results that reached genome-wide significance were observed. However, four regions demonstrated excess sharing of alleles at p < 0.002 when sibships were stratified by gender-three of which were present in males. Of note, a female-specific locus co-localized with region that is linked to mean systolic blood pressure in the same families. In addition, three other regions demonstrated excess sharing of alleles in sibships irrespective of gender, including a region on chromosome 10p14-p15 (p = 7.5 × 10(-4)). CONCLUSION: Although no loci meeting genome-wide significance were detected to demonstrate transmission ratio distortion, loci with suggestive evidence for linkage were detected. These may have implications for the mapping of susceptibility loci for complex disease in human pedigrees

Evaluating outlier loci and their effect on the identification of pedigree errors

Homozygosity outlier loci, which show patterns of variation that are extremely divergent from the rest of the genome, can be evaluated by comparison of the homozygosity under Hardy-Weinberg proportions (the sum of the squares of allele frequencies) with the expected homozygosity under neutrality. Such outlier loci are potentially under selection (balancing selection or directional selection) when genome-wide effects (such as bottleneck and rapid population growth) are excluded. Outlier loci show skewed allele frequencies with respect to neutrality and may therefore affect the identification of pedigree errors. However, choosing neutral markers (excluding outlier loci) for the identification of pedigree errors has been neglected thus far. Our results showed that 4.1%, 5.5%, and 1.5% of the microsatellite markers, Illumina single-nucleotide polymorphisms (SNPs), and Affymetrix SNPs, respectively, on the autosomes appear to be under balancing selection (p ≤ 0.01) while 0.8% of the Affymetrix SNPs are consistent with directional selection. On the X-chromosome, 7.7%, 3.2%, and 0.4% of the microsatellite markers, Illumina SNPs, and Affymetrix SNPs, respectively, appear to be under balancing selection. 9.3% of Illumina SNPs and 6.7% of Affymetrix SNPs which have high minor allele frequency (≥40%) appear to be under balancing selection. Pedigree structure errors in 15 of 143 pedigrees were detected using microsatellite markers from the autosomes and/or selected SNPs from chromosomes 1 to 18 of the Illumina and/or selected SNPs from chromosomes 1 to 16 of the Affymetrix. Outlier loci did not make a major difference to the identification of pedigree errors. The Collaborative Study on the Genetics of Alcoholism data has pedigree errors and some of them may be due to sample mix up

Genetic analysis of common factors underlying cardiovascular disease-related traits

BACKGROUND: Cardiovascular disease-related traits, such as body mass index (BMI), systolic blood pressure (SBP), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and glucose levels (GLUC), have moderate to high correlations with each other. We hypothesized that there might be some common factors underlying the correlations of these traits, and attempted to identify these factors and their genetic structures. Cross-sectional measurements from the 330 extended Framingham Heart Study families were used in this study. Principal component factor analysis was applied to obtain the factors that were then analyzed using variance components linkage analysis. RESULTS: With the above six traits three factors were generated: BMI-SBP-GLUC, HDL-TG, and TC-TG. The heritabilities for these factors were 32%, 45%, and 49%, respectively. Comparing the linkage results of the factors with the results of their component traits, evidence for linkage was observed for the TC-TG factor to a locus on chromosome 2p23 with a two-point LOD score 2.73 (marker GATA8F07) and a multipoint LOD score 1.81 (at 54 cM), while the LOD scores for TC and TG did not exceed 1 at this region. CONCLUSION: Our analysis showed a locus on chromosome 2 might have a pleiotropic effect on the cardiovascular disease-related traits TC and TG

Beyond apples and pears: sex-specific genetics of body fat percentage

IntroductionBiological sex influences both overall adiposity and fat distribution. Further, testosterone and sex hormone binding globulin (SHBG) influence adiposity and metabolic function, with differential effects of testosterone in men and women. Here, we aimed to perform sex-stratified genome-wide association studies (GWAS) of body fat percentage (BFPAdj) (adjusting for testosterone and sex hormone binding globulin (SHBG)) to increase statistical power.MethodsGWAS were performed in white British individuals from the UK Biobank (157,937 males and 154,337 females). To avoid collider bias, loci associated with SHBG or testosterone were excluded. We investigated association of BFPAdj loci with high density cholesterol (HDL), triglyceride (TG), type 2 diabetes (T2D), coronary artery disease (CAD), and MRI-derived abdominal subcutaneous adipose tissue (ASAT), visceral adipose tissue (VAT) and gluteofemoral adipose tissue (GFAT) using publicly available data from large GWAS. We also performed 2-sample Mendelian Randomization (MR) using identified BFPAdj variants as instruments to investigate causal effect of BFPAdj on HDL, TG, T2D and CAD in males and females separately.ResultsWe identified 195 and 174 loci explaining 3.35% and 2.60% of the variation in BFPAdj in males and females, respectively at genome-wide significance (GWS, p&lt;5x10-8). Although the direction of effect at these loci was generally concordant in males and females, only 38 loci were common to both sexes at GWS. Seven loci in males and ten loci in females have not been associated with any adiposity/cardiometabolic traits previously. BFPAdj loci generally did not associate with cardiometabolic traits; several had paradoxically beneficial cardiometabolic effects with favourable fat distribution. MR analyses did not find convincing supportive evidence that increased BFPAdj has deleterious cardiometabolic effects in either sex with highly significant heterogeneity.ConclusionsThere was limited genetic overlap between BFPAdj in males and females at GWS. BFPAdj loci generally did not have adverse cardiometabolic effects which may reflect the effects of favourable fat distribution and cardiometabolic risk modulation by testosterone and SHBG

Assessing models for genetic prediction of complex traits:a comparison of visualization and quantitative methods

BACKGROUND: In silico models have recently been created in order to predict which genetic variants are more likely to contribute to the risk of a complex trait given their functional characteristics. However, there has been no comprehensive review as to which type of predictive accuracy measures and data visualization techniques are most useful for assessing these models. METHODS: We assessed the performance of the models for predicting risk using various methodologies, some of which include: receiver operating characteristic (ROC) curves, histograms of classification probability, and the novel use of the quantile-quantile plot. These measures have variable interpretability depending on factors such as whether the dataset is balanced in terms of numbers of genetic variants classified as risk variants versus those that are not. RESULTS: We conclude that the area under the curve (AUC) is a suitable starting place, and for models with similar AUCs, violin plots are particularly useful for examining the distribution of the risk scores

Genome-wide association analysis of cardiovascular-related quantitative traits in the Framingham Heart Study

Multivariate linear growth curves were used to model high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), and systolic blood pressure (SBP) measured during four exams from 1659 independent individuals from the Framingham Heart Study. The slopes and intercepts from each of two phenotype models were tested for association with 348,053 autosomal single-nucleotide polymorphisms from the Affymetrix Gene Chip 500 k set. Three regions were associated with LDL intercept, TG slope, and SBP intercept (p < 1.44 × 10-7). We observed results consistent with previously reported associations between rs599839, on chromosome 1p13, and LDL. We note that the association is significant with LDL intercept but not slope. Markers on chromosome 17q25 were associated with TG slope, and a single-nucleotide polymorphism on chromosome 7p11 was associated with SBP intercept. Growth curve models can be used to gain more insight on the relationships between SNPs and traits than traditional association analysis when longitudinal data has been collected. The power to detect association with changes over time may be limited if the subjects are not followed over a long enough time period

ANKH variants associated with ankylosing spondylitis: gender differences

The ank (progressive ankylosis) mutant mouse, which has a nonsense mutation in exon 12 of the inorganic pyrophosphate regulator gene (ank), exhibits aberrant joint ankylosis similar to human ankylosing spondylitis (AS). We previously performed family-based association analyses of 124 Caucasian AS families and showed that novel genetic markers in the 5' flanking region of ANKH (the human homolog of the murine ank gene) are modestly associated with AS. The objective of the present study was to conduct a more extensive evaluation of ANKH variants that are significantly associated with AS and to determine whether the association is gender specific. We genotyped 201 multiplex AS families with nine ANKH intragenetic and two flanking microsatellite markers, and performed family-based association analyses. We showed that ANKH variants located in two different regions of the ANKH gene were associated with AS. Results of haplotype analyses indicated that, after Bonferroni correction, the haplotype combination of rs26307 [C] and rs27356 [C] is significantly associated with AS in men (recessive/dominant model; P = 0.004), and the haplotype combination of rs28006 [C] and rs25957 [C] is significantly associated with AS in women (recessive/dominant model; P = 0.004). A test of interaction identified rs26307 (i.e. the region that was associated in men with AS) as showing a difference in the strength of the association by gender. The region associated with AS in women only showed significance in the test of interaction among the subset of families with affected individuals of both genders. These findings support the concept that ANKH plays a role in genetic susceptibility to AS and reveals a gender–genotype specificity in this interaction

A genome scan for parent-of-origin linkage effects in alcoholism

BACKGROUND: Alcoholism is a complex disease in which genomic imprinting may play an important role in its susceptibility. OBJECTIVE: To conduct a genome-wide search for loci that may have strong parent-of-origin linkage effects in alcoholism; to compare the linkage results between the microsatellites and the two single-nucleotide polymorphism (SNP) platforms. METHODS: Nonparametric linkage analyses were performed using ALLEGRO with the three sets of markers provided by the Genetic Analysis Workshop 14 for the Collaborative Study on the Genetics of Alcoholism Problem 1 data. Both sex-averaged and sex-specific genetic maps were used. We also provided a valid statistical test to determine whether the parental allele sharing differed significantly. RESULTS: Significant maternal linkage effects (paternal imprinting) were observed on chromosome 12 using either the microsatellite markers or the two SNP panels. The two SNP sets did not improve the linkage signals compared to the results from the microsatellite markers on chromosome 12. Possible paternal linkage effects (maternal imprinting) on chromosome 7 and maternal linkage effects (paternal imprinting) on chromosome 10 were found using the two SNP panels. CONCLUSION: For diseases which may have parent-of-origin effects, linkage analysis looking at parental sharing separately may reduce locus heterogeneity and increase the ability to identify that which can not be identified with usual linkage analysis