An autosome-wide search using longitudinal data for loci linked to type 2 diabetes progression

A genome-wide screen was conducted for type 2 diabetes progression genes using measures of elevated fasting glucose levels as quantitative traits from the offspring enrolled in the Framingham Heart Study. We analyzed young (20–34 years) and old (≥ 35 years) subjects separately, using single-point and multipoint sibpair analysis, because of the possible differential impact of progression on the groups of interest. We observed significant linkage with change in fasting glucose levels on 1q25-32 (p = 5.21 × 10(-8)), 3p26.3-21.31 (p = 1 × 10(-11)), 8q23.1-24.13 (p = 2.94 × 10(-6)), 9p24.1-21.3 (p = 7 × 10(-7)), and 18p11.31-q22.1 (p < 10(-11)). The evidence for linkage on chromosomes 8 and 18 was consistent for the subset of study participants aged 43 through 55 years

Optimizing the evidence for linkage by permuting marker order

We developed a new marker-reordering algorithm to find the best order of fine-mapping markers for multipoint linkage analysis. The algorithm searches for the best order of fine-mapping markers such that the sum of the squared differences in identity-by-descent distribution between neighboring markers is minimized. To test this algorithm, we examined its effect on the evidence for linkage in the simulated and the Collaborative Studies on Genetics of Alcoholism (COGA) data. We found enhanced evidence for linkage with the reordered map at the true location in the simulated data (p-value decreased from 1.16 × 10(-9 )to 9.70 × 10(-10)). Analysis of the White population from the COGA data with the reordered map for alcohol dependence led to a significant change of the linkage signal (p = 0.0365 decreased to p = 0.0039) on chromosome 1 between marker D1S1592 and D1S1598. Our results suggest that reordering fine-mapping markers in candidate regions when the genetic map is uncertain can be a critical step when considering a dense map

Structural equation model-based genome scan for the metabolic syndrome

BACKGROUND: The metabolic syndrome is characterized by the clustering of several traits, including obesity, hypertension, decreased levels of HDL cholesterol, and increased levels of glucose and triglycerides. Because these traits cluster, there are likely common genetic factors involved. RESULTS: We used a multivariate structural equation model (SEM) approach to scan the genome for loci involved in the metabolic syndrome. We found moderate evidence for linkage on chromosomes 2, 3, 11, 13, and 15, and these loci appear to have different relative effects on the component traits of the metabolic syndrome. CONCLUSION: Our results suggest that the metabolic syndrome components, diabetes, obesity, and hypertension, are under the pleiotropic control of several loci

Studying genetic determinants of natural variation in human gene expression using Bayesian ANOVA

Standard genetic mapping techniques scan chromosomal segments for location of genetic linkage and association signals. The majority of these methods consider only correlations at single markers and/or phenotypes with explicit detailing of the genetic structure. These methods tend to be limited by their inability to consider the effect of large numbers of model variables jointly. In contrast, we propose a Bayesian analysis of variance (ANOVA) method to categorize individuals based on similarity of multidimensional profiles and attempt to analyze all variables simultaneously. Using Problem 1 of the Genetic Analysis Workshop 15 data set, we demonstrate the method's utility for joint analysis of gene expression levels and single-nucleotide polymorphism genotypes. We show that the method extracts similar information to that of previous genetic mapping analyses, and suggest extensions of the method for mining unique information not previously found

Small Drusen and Age-Related Macular Degeneration: The Beaver Dam Eye Study

We tested the hypothesis that large areas of small hard drusen (diameter \u3c63 μm) and intermediate drusen (diameter 63-124 μm) are associated with the incidence of age-related macular degeneration (AMD). Eyes of 3344 older adults with at least 2 consecutive visits spaced 5 years apart over a 20-year period were included. A 6-level severity scale including no drusen, 4 levels of increasing area (from minimal (\u3c2596 μm2) to large (\u3e9086 μm2)) of only small hard drusen, and intermediate drusen was used. The 5-year incidence of AMD was 3% in eyes at the start of the interval with no, minimal, small, and moderate areas of only small drusen and 5% and 25% for eyes with large area of only small drusen and intermediate drusen, respectively. Compared to eyes with a moderate area of small drusen, the odds ratio (OR) of developing AMD in eyes with a large area of only small drusen was 1.8 (p \u3c 0.001). Compared to eyes with large area of only small drusen, eyes with intermediate drusen had an OR of 5.5 (p \u3c 0.001) of developing AMD. Our results are consistent with our hypothesis that large areas of only small drusen are associated with the incidence of AMD

Effect of genotyping error in model-free linkage analysis using microsatellite or single-nucleotide polymorphism marker maps

Errors while genotyping are inevitable and can reduce the power to detect linkage. However, does genotyping error have the same impact on linkage results for single-nucleotide polymorphism (SNP) and microsatellite (MS) marker maps? To evaluate this question we detected genotyping errors that are consistent with Mendelian inheritance using large changes in multipoint identity-by-descent sharing in neighboring markers. Only a small fraction of Mendelian consistent errors were detectable (e.g., 18% of MS and 2.4% of SNP genotyping errors). More SNP genotyping errors are Mendelian consistent compared to MS genotyping errors, so genotyping error may have a greater impact on linkage results using SNP marker maps. We also evaluated the effect of genotyping error on the power and type I error rate using simulated nuclear families with missing parents under 0, 0.14, and 2.8% genotyping error rates. In the presence of genotyping error, we found that the power to detect a true linkage signal was greater for SNP (75%) than MS (67%) marker maps, although there were also slightly more false-positive signals using SNP marker maps (5 compared with 3 for MS). Finally, we evaluated the usefulness of accounting for genotyping error in the SNP data using a likelihood-based approach, which restores some of the power that is lost when genotyping error is introduced

Identification of nephropathy candidate genes by comparing sclerosis-prone and sclerosis-resistant mouse strain kidney transcriptomes

Abstract Background The genetic architecture responsible for chronic kidney disease (CKD) remains incompletely described. The Oligosyndactyly (Os) mouse models focal and segmental glomerulosclerosis (FSGS), which is associated with reduced nephron number caused by the Os mutation. The Os mutation leads to FSGS in multiple strains including the ROP-Os/+. However, on the C57Bl/6J background the mutation does not cause FSGS, although nephron number in these mice are equivalent to those in ROP-Os/+ mice. We exploited this phenotypic variation to identify genes that potentially contribute to glomerulosclerosis. Methods To identify such novel genes, which regulate susceptibility or resistance to renal disease progression, we generated and compared the renal transcriptomes using serial analysis of gene expression (SAGE) from the sclerosis-prone ROP-Os/+ and sclerosis resistant C57-Os/+ mouse kidneys. We confirmed the validity of the differential gene expression using multiple approaches. We also used an Ingenuity Pathway Analysis engine to assemble differentially regulated molecular networks. Cell culture techniques were employed to confirm functional relevance of selected genes. Results A comparative analysis of the kidney transcriptomes revealed multiple genes, with expression levels that were statistically different. These novel, candidate, renal disease susceptibility/resistance genes included neuropilin2 (Nrp2), glutathione-S-transferase theta (Gstt1) and itchy (Itch). Of 34 genes with the most robust statistical difference in expression levels between ROP-Os/+ and C57-Os/+ mice, 13 and 3 transcripts localized to glomerular and tubulointerstitial compartments, respectively, from micro-dissected human FSGS biopsies. Network analysis of all significantly differentially expressed genes identified 13 connectivity networks. The most highly scored network highlighted the roles for oxidative stress and mitochondrial dysfunction pathways. Functional analyses of these networks provided evidence for activation of transforming growth factor beta (TGFβ) signaling in ROP-Os/+ kidneys despite similar expression of the TGFβ ligand between the tested strains. Conclusions These data demonstrate the complex dysregulation of normal cellular functions in this animal model of FSGS and suggest that therapies directed at multiple levels will be needed to effectively treat human kidney diseases.http://deepblue.lib.umich.edu/bitstream/2027.42/112491/1/12882_2011_Article_362.pd

Genome-wide analyses demonstrate novel loci that predispose to drusen formation

PURPOSE. To test whether genes for drusen formation are independent of age-related macular degeneration (AMD) pathogenesis. METHODS. A genome-wide model-free linkage analysis was performed, using two semiquantitative drusen traits, size and type, on two sets of data: (1) 325 individuals (225 sib pairs) from the Beaver Dam Eye Study (BDES), and (2) 297 individuals (346 sib pairs) from the Family Age Related Maculopathy Study (FARMS). Apolipoprotein E (APOE) genotypes were used as a covariate in a multipoint sibpair analysis. RESULTS. The authors found evidence of linkage on 19q13.31 (D19S245), with size of drusen in both the BDES (P ϭ 0.0287) and the FARMS (P ϭ 0.0013; P ϭ 0.0005, combined). In the BDES, type showed linkage evidence on 3p24.3 (D3S1768; P ϭ 0.0189) and 3q25.1 (D3S2404; P ϭ 0.0141); the linkage on 3p24.3 was also found with size (D3S1768; P ϭ 0.0264). In the FARMS, size showed evidence of linkage at 5q33.3 (D5S820; P ϭ 0.0021), 14q32.33 (D14S1007; P ϭ 0.0013), and 16p13.13 (D16S2616; P ϭ 0.0015) and type at 21q21.2 (D21S2052; P ϭ 0.0070). For size in the FARMS, there was a small increase in P-value at marker D19S245 from 0.0044 to 0.0111, and from 0.0044 to 0.0064, when the 4-carrier and the 3-carrier genotype were the covariates, respectively. CONCLUSIONS. The results show that APOE effects may be mediated early in the progression of ARM to AMD and thus may not be detected by standard genome scans for more severe disease. (Invest Ophthalmol Vis Sci. 2005;46:3081-3088

Meta-analysis of genome-wide linkage scans for renal function traits

Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance