Thickness of renal glomerular capillary basement membrane in the offspring of diabetic rats fed a regular or high-sucrose diet

Numerous animal model studies of diabetes mellitus have been reported. Diabetes-induced vascular damage is a common cause of systemic organ damage in humans and animals. Many investigations have been made of human and animal offspring of diabetic mothers. The present report documents the sequential glomerular basement membrane (GBM) thickness in fetuses and infants of diabetic rats. The postnatal increase in GBM thickness was similar in the offspring of control and diabetic rats, and was not related to the sucrose concentration in the diet.     

Alteration of ethanol self-administration by naltrexone

The effect of naltrexone HC1 (NLTRX) on the reinforcing properties of ethanol (EtOH) was evaluated with intravenous self-administration (IVSA). Eight drug-naive, male, 3.5–5.0 Kg rhesus monkeys ($\text{M. mulatta}$) were selected for: spontaneous acquisition of EtOH IVSA, consumption of at least 1.0 gm/Kg/day of EtOH during daily 4 hr. IVSA test sessions, and extremely low daily variability (10%) of EtOH intake during a 30 day control period. The selected subject group received intramuscular injections of either saline (SAL) (1.0 ml) or NLTRX (1, 3, 5 mg/Kg) 30 minutes before each test session. SAL was administered for 10 consecutive days and each NLTRX dose for 15 consecutive days. SAL phases were alternated with the NLTRX phases. NLTRX pretreatment produced lower levels of EtOH IVSA than those observed during SAL pretreatment phases. The magnitude of the suppression of EtOH IVSA corresponded to the NLTRX dose and was statistically significant following both 3 mg/Kg (p<0.05) and 5 mg/Kg (p<0.01) doses. NLTRX pretreatment produced transient increases in EtOH IVSA during the first 5 days of treatment, followed by significant decreases for the next 10 days. These data suggest that the blockade of opiate receptors by NLTRX in rhesus monkeys apparently decreases the reinforcing effects of EtOH measured with IVSA techniques.     

Modeling and E-M estimation of haplotype-specific relative risks from genotype data for a case-control study of unrelated individuals

The US National Cancer Institute has recently sponsored the formation of a Cohort Consortium (http://2002.cancer.gov/scpgenes.htm) to facilitate the pooling of data on very large numbers of people, concerning the effects of genes and environment on cancer incidence. One likely goal of these efforts will be generate a large population-based case-control series for which a number of candidate genes will be investigated using SNP haplotype as well as genotype analysis. The goal of this paper is to outline the issues involved in choosing a method of estimating haplotype-specific risk estimates for such data that is technically appropriate and yet attractive to epidemiologists who are already comfortable with odds ratios and logistic regression. Our interest is to develop and evaluate extensions of methods, based on haplotype imputation, that have been recently described (Schaid et al., Am J Hum Genet, 2002, and Zaykin et al., Hum Hered, 2002) as providing score tests of the null hypothesis of no effect of SNP haplotypes upon risk, which may be used for more complex tasks, such as providing confidence intervals, and tests of equivalence of haplotype-specific risks in two or more separate populations. In order to do so we (1) develop a cohort approach towards odds ratio analysis by expanding the E-M algorithm to provide maximum likelihood estimates of haplotype-specific odds ratios as well as genotype frequencies; (2) show how to correct the cohort approach, to give essentially unbiased estimates for population-based or nested case-control studies by incorporating the probability of selection as a case or control into the likelihood, based on a simplified model of case and control selection, and (3) finally, in an example data set (CYP17 and breast cancer, from the Multiethnic Cohort Study) we compare likelihood-based confidence interval estimates from the two methods with each other, and with the use of the single-imputation approach of Zaykin et al. applied under both null and alternative hypotheses. We conclude that so long as haplotypes are well predicted by SNP genotypes (we use the Rh2 criteria of Stram et al. [1]) the differences between the three methods are very small and in particular that the single imputation method may be expected to work extremely well.     

Consistent Association of Type 2 Diabetes Risk Variants Found in Europeans in Diverse Racial and Ethnic Groups

It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10⁻⁴) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; P_het = 3.8×10⁻⁴). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.     

Testing for an unusual distribution of rare variants

Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.     

The use of duplex-specific crab nuclease for rapid analysis of single-nucleotide polymorphisms and the detection of DNA targets in complex PCR products

A rapid method for single-nucleotide polymorphism analysis and the detection of target clones after cloning of complex PCR products based on the use of duplex-specific crab nuclease and a universal fluorescent probe has been developed. The method is an alternative to the labor-intensive procedures of clone screening employing radioactively labeled probes, gel-based restriction analysis, and costly sequencing. The efficiency of the novel method has been demonstrated in a range of model systems.     

Genetic variation in the HSD17B1 gene and risk of prostate cancer

Steroid hormones are believed to play an important role in prostate carcinogenesis, but epidemiological evidence linking prostate cancer and steroid hormone genes has been inconclusive, in part due to small sample sizes or incomplete characterization of genetic variation at the locus of interest. Here we report on the results of a comprehensive study of the association between HSD17B1 and prostate cancer by the Breast and Prostate Cancer Cohort Consortium, a large collaborative study. HSD17B1 encodes 17β-hydroxysteroid dehydrogenase 1, an enzyme that converts dihydroepiandrosterone to the testosterone precursor Δ5-androsterone-3β,17β-diol and converts estrone to estradiol. The Breast and Prostate Cancer Cohort Consortium researchers systematically characterized variation in HSD17B1 by targeted resequencing and dense genotyping; selected haplotype-tagging single nucleotide polymorphisms (htSNPs) that efficiently predict common variants in U.S. and European whites, Latinos, Japanese Americans, and Native Hawaiians; and genotyped these htSNPs in 8,290 prostate cancer cases and 9,367 study-, age-, and ethnicity-matched controls. We found no evidence that HSD17B1 htSNPs (including the nonsynonymous coding SNP S312G) or htSNP haplotypes were associated with risk of prostate cancer or tumor stage in the pooled multiethnic sample or in U.S. and European whites. Analyses stratified by age, body mass index, and family history of disease found no subgroup-specific associations between these HSD17B1 htSNPs and prostate cancer. We found significant evidence of heterogeneity in associations between HSD17B1 haplotypes and prostate cancer across ethnicity: one haplotype had a significant (p < 0.002) inverse association with risk of prostate cancer in Latinos and Japanese Americans but showed no evidence of association in African Americans, Native Hawaiians, or whites. However, the smaller numbers of Latinos and Japanese Americans in this study makes these subgroup analyses less reliable. These results suggest that the germline variants in HSD17B1 characterized by these htSNPs do not substantially influence the risk of prostate cancer in U.S. and European whites.