Robert C. Elston

Purpose. Diabetic retinopathy (DR) and diabetic nephropathy (DN) are serious microvascular complications of diabetes mellitus. Correlations between severity of DR and DN and computed heritability estimates for DR were determined in a large, multiethnic sample of diabetic families. The hypothesis was that (1) the severity of DR correlates with the presence and severity of nephropathy in individuals with diabetes mellitus, and (2) the severity of DR is under significant familial influence in members of multiplex diabetic families. methods. The Family Investigation of Nephropathy and Diabetes (FIND) was designed to evaluate the genetic basis of DN in American Indians, European Americans, African Americans, and Mexican Americans. FIND enrolled probands with advanced DN, along with their diabetic siblings who were concordant and discordant for nephropathy. These diabetic family members were invited to participate in the FIND-Eye study to determine whether inherited factors underlie susceptibility to DR and its severity. FIND-Eye participants underwent eye examinations and had fundus photographs taken. The severity of DR was graded by using the Early Treatment Diabetic Retinopathy Study Classification (ETDRS). Sib–sib correlations were calculated with the SAGE 5.0 program FCOR, to estimate heritability of retinopathy severity. results. This report summarizes the results for the first 2368 diabetic subjects from 767 families enrolled in FIND-Eye; nearly 50% were Mexican American, the largest single ethnicity within FIND. The overall prevalence of DR was high; 33.4% had proliferative DR; 7.5%, 22.8%, and 9.5% had severe, moderate, and mild nonproliferative DR, respectively; 26.6% had no DR. The severity of DR was significantly associated with severity of DN, both by phenotypic category and by increasing serum creatinine concentration (χ² = 658.14, df = 20; P < 0.0001). The sib–sib correlation for DR severity was 0.1358 in the total sample and 0.1224 when limited to the Mexican-American sample. Broad sense heritabilities for DR were 27% overall and 24% in Mexican-American families. The polygenic heritability of liability for proliferative DR approximated 25% in this FIND-Eye sample. conclusions. These data confirm that the severity of DR parallels the presence and severity of nephropathy in individuals with diabetes mellitus. The severity of DR in members of multiplex diabetic families appears to have a significant familial connection.

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.

In the Haseman-Elston approach the squared phenotypic difference is regressed on the proportion of alleles shared identical by descent (IBD) to map a quantitative trait to a genetic marker. In applications the IBD distribution is estimated and usually cannot be determined uniquely owing to incomplete marker information. At Genetic Analysis Workshop (GAW) 13, Jacobs et al. [BMC Genet 2003, 4(Suppl 1):S82] proposed to improve the power of the Haseman-Elston algorithm by weighting for information available from marker genotypes. The authors did not show, however, the validity of the employed asymptotic distribution. In this paper, we use the simulated data provided for GAW 14 and show that weighting Haseman-Elston by marker information results in increased type I error rates. Specifically, we demonstrate that the number of significant findings throughout the chromosome is significantly increased with weighting schemes. Furthermore, we show that the classical Haseman-Elston method keeps its nominal significance level when applied to the same data. We therefore recommend to use Haseman-Elston with marker informativity weights only in conjunction with empirical p-values. Whether this approach in fact yields an increase in power needs to be investigated further.

The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewidep-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates.

We present a new method for fine‐mapping a disease susceptibility locus using a case‐control design. The new method, termed the ‘weighted average (WA) statistic’, averages the Cochran–Armitage (CA) trend test statistic and the difference between the Hardy Weinberg disequilibrium test statistics (the HWD trend) for cases and controls. The main features of the WA statistic are that it mitigates against the weaknesses, and maintains the strong points, of both the CA trend test and the HWD trend test. To allow for the extra variance induced by population structure and cryptic relatedness, the WA statistic can be adjusted for variance inflation. Based on the results of a simulation study, when there is no population structure the WA test statistic shows good performance under a variety of genetic disease models. When there is population structure, the adjusted WA statistic maintains the correct probability of type I error. Under all genetic disease models investigated, the adjusted WA statistic has better power than the adjusted CA trend test, the HWD trend test or the product of the adjusted CA trend test and the HWD trend test statistics. Copyright © 2005 John Wiley & Sons, Ltd.

Background: Maximum likelihood estimates of haplotype frequencies can be obtained from pooled DNA using the expectation maximization (EM) algorithm. Through simulation, we investigate the effect of genotyping error on the accuracy of haplotype frequency estimates obtained using this algorithm. We explore model parameters including allele frequency, inter-marker linkage disequilibrium (LD), genotyping error rate, and pool size. Results: Pool sizes of 2, 5, and 10 individuals achieved comparable levels of accuracy in the estimation procedure. Common marker allele frequencies and no inter-marker LD result in less accurate estimates. This pattern is observed regardless of the amount of genotyping error simulated. Conclusion: Genotyping error slightly decreases the accuracy of haplotype frequency estimates. However, the EM algorithm performs well even in the presence of genotyping error. Overall, pools of 2, 5, and 10 individuals yield similar accuracy of the haplotype frequency estimates, while reducing costs due to genotyping.

Juvenile rheumatoid arthritis (JRA) comprises a group of chronic systemic inflammatory disorders that primarily affect joints and can cause long-term disability. JRA is likely to be a complex genetic trait, or a series of such traits, with both genetic and environmental factors contributing to the risk for developing the disease and to its progression. The HLA region on the short arm of chromosome 6 has been intensively evaluated for genetic contributors to JRA, and multiple associations, and more recently linkage, has been detected. Other genes involved in innate and acquired immunity also map to near the HLA cluster on 6p, and it is possible that variation within these genes also confers risk for developing JRA. We examined the TPSN gene, which encodes tapasin, an endoplasmic reticulum chaperone that is involved in antigen processing, to elucidate its involvement, if any, in JRA. We employed both a case–control approach and the transmission disequilibrium test, and found linkage and association between the TPSN allele (Arg260) and the systemic onset subtype of JRA. Two independent JRA cohorts were used, one recruited from the Rheumatology Clinic at Cincinnati Children's Hospital Medical Center (82 simplex families) and one collected by the British Paediatric Rheumatology Group in London, England (74 simplex families). The transmission disequilibrium test for these cohorts combined was statistically significant (χ² = 4.2, one degree of freedom; P = 0.04). Linkage disequilibrium testing between the HLA alleles that are known to be associated with systemic onset JRA did not reveal linkage disequilibrium with the Arg260 allele, either in the Cincinnati systemic onset JRA cohort or in 113 Caucasian healthy individuals. These results suggest that there is a weak association between systemic onset JRA and the TPSN polymorphism, possibly due to linkage disequilibrium with an as yet unknown susceptibility allele in the centromeric part of chromosome 6.

Background: Although many years of genetic epidemiological studies have demonstrated that genetics plays a significant role in determining smoking behavior, little information is available on genomic loci or genes affecting nicotine dependence. Several susceptibility chromosomal regions for nicotine dependence have been reported, but few have received independent confirmation. To identify susceptibility loci for nicotine dependence, 313 extended pedigrees selected from the Framingham Heart Study population were analyzed by both the GENEHUNTER and S.A.G.E. programs. Results: After performing linkage analyses on the 313 extended Framingham Heart Study families, the EM Haseman-Elston method implemented in GENEHUNTER provided evidence for significant linkage of smoking rate to chromosome 11 and suggestive linkage to chromosomes 9, 14, and 17. Multipoint sib-pair regression analysis using the SIBPAL program of S.A.G.E. on 1389 sib pairs that were split from the 313 extended families identified suggestive linkage of smoking rate to chromosomes 4, 7, and 17. Of these identified positive regions for nicotine dependence, loci on chromosomes 7, 11, and 17 were identified by both GENEHUNTER and S.A.G.E. programs. Conclusion: Our genome-wide scan results on the Framingham Heart Study data provide evidence for significant linkage of smoking rate to chromosome 11 and suggestive linkage to chromosomes 4, 7, 9, 14, and 17. These findings suggest that some of these regions may harbor susceptibility loci for nicotine dependence, and warrant further investigation in this and other populations.

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.

Only one genome scan to date has attempted to make use of the longitudinal data available in the Framingham Heart Study, and this attempt yielded evidence of linkage to a gene for mean systolic blood pressure. We show how the additional information available in these longitudinal data can be utilized to examine linkages for not only mean systolic blood pressure (SBP), but also for its trend with age and its variability. Prior to linkage analysis, individuals treated for hypertension were adjusted to account for right-censoring of SBP. Regressions on age were fitted to obtain orthogonal measures of slope, curvature, and residual variance of SBP that were then used as dependent variables in the model-free linkage program SIBPAL. We included mean age, gender, and cohort as covariates in the analysis. To improve power, sibling pairs were weighted for informativity using weights derived from both the marker and trait. The most significant results from our analyses were found on chromosomes 12, 15, and 17 for mean SBP, and chromosome 20 for both SBP slope and curvature.