Stephen Erickson

Phenotypically concordant and discordant monozygotic twins display different DNA copy-number-variation profiles.

The exploration of copy-number variation (CNV), notably of somatic cells, is an understudied aspect of genome biology. Any differences in the genetic makeup between twins derived from the same zygote represent an irrefutable example of somatic mosaicism. We studied 19 pairs of monozygotic twins with either concordant or discordant phenotype by using two platforms for genome-wide CNV analyses and showed that CNVs exist within pairs in both groups. These findings have an impact on our views of genotypic and phenotypic diversity in monozygotic twins and suggest that CNV analysis in phenotypically discordant monozygotic twins may provide a powerful tool for identifying disease-predisposition loci. Our results also imply that caution should be exercised when interpreting disease causality of de novo CNVs found in patients based on analysis of a single tissue in routine disease-related DNA diagnostics.

Vaccine-Induced Cellular Responses Control Simian Immunodeficiency Virus Replication after Heterologous Challenge

ABSTRACT All human immunodeficiency virus (HIV) vaccine efficacy trials to date have ended in failure. Structural features of the Env glycoprotein and its enormous variability have frustrated efforts to induce broadly reactive neutralizing antibodies. To explore the extent to which vaccine-induced cellular immune responses, in the absence of neutralizing antibodies, can control replication of a heterologous, mucosal viral challenge, we vaccinated eight macaques with a DNA/Ad5 regimen expressing all of the proteins of SIVmac239 except Env. Vaccinees mounted high-frequency T-cell responses against 11 to 34 epitopes. We challenged the vaccinees and eight naïve animals with the heterologous biological isolate SIVsmE660, using a regimen intended to mimic typical HIV exposures resulting in infection. Viral loads in the vaccinees were significantly less at both the peak (1.9-log reduction; P < 0.03) and at the set point (2.6-log reduction; P < 0.006) than those in control naïve animals. Five of eight vaccinated macaques controlled acute peak viral replication to less than 80,000 viral RNA (vRNA) copy eq/ml and to less than 100 vRNA copy eq/ml in the chronic phase. Our results demonstrate that broad vaccine-induced cellular immune responses can effectively control replication of a pathogenic, heterologous AIDS virus, suggesting that T-cell-based vaccines may have greater potential than previously appreciated.

Rank-Based Inverse Normal Transformations are Increasingly Used, But are They Merited?

Many complex traits studied in genetics have markedly non-normal distributions. This often implies that the assumption of normally distributed residuals has been violated. Recently, inverse normal transformations (INTs) have gained popularity among genetics researchers and are implemented as an option in several software packages. Despite this increasing use, we are unaware of extensive simulations or mathematical proofs showing that INTs have desirable statistical properties in the context of genetic studies. We show that INTs do not necessarily maintain proper Type 1 error control and can also reduce statistical power in some circumstances. Many alternatives to INTs exist. Therefore, we contend that there is a lack of justification for performing parametric statistical procedures on INTs with the exceptions of simple designs with moderate to large sample sizes, which makes permutation testing computationally infeasible and where maximum likelihood testing is used. Rigorous research evaluating the utility of INTs seems warranted.

Correlation of microRNA levels during hypoxia with predicted target mRNAs through genome-wide microarray analysis

BackgroundLow levels of oxygen in tissues, seen in situations such as chronic lung disease, necrotic tumors, and high altitude exposures, initiate a signaling pathway that results in active transcription of genes possessing a hypoxia response element (HRE). The aim of this study was to investigate whether a change in miRNA expression following hypoxia could account for changes in the cellular transcriptome based on currently available miRNA target prediction tools.MethodsTo identify changes induced by hypoxia, we conducted mRNA- and miRNA-array-based experiments in HT29 cells, and performed comparative analysis of the resulting data sets based on multiple target prediction algorithms. To date, few studies have investigated an environmental perturbation for effects on genome-wide miRNA levels, or their consequent influence on mRNA output.ResultsComparison of miRNAs with predicted mRNA targets indicated a lower level of concordance than expected. We did, however, find preliminary evidence of combinatorial regulation of mRNA expression by miRNA.ConclusionTarget prediction programs and expression profiling techniques do not yet adequately represent the complexity of miRNA-mediated gene repression, and new methods may be required to better elucidate these pathways. Our data suggest the physiologic impact of miRNAs on cellular transcription results from a multifaceted network of miRNA and mRNA relationships, working together in an interconnected system and in context of hundreds of RNA species. The methods described here for comparative analysis of cellular miRNA and mRNA will be useful for understanding genome wide regulatory responsiveness and refining miRNA predictive algorithms.

Frequent genetic differences between matched primary and metastatic breast cancer provide an approach to identification of biomarkers for disease progression.

Breast cancer is a major cause of morbidity and mortality in women and its metastatic spread is the principal reason behind the fatal outcome. Metastasis-related research of breast cancer is however underdeveloped when compared with the abundant literature on primary tumors. We applied an unexplored approach comparing at high resolution the genomic profiles of primary tumors and synchronous axillary lymph node metastases from 13 patients with breast cancer. Overall, primary tumors displayed 20% higher number of aberrations than metastases. In all but two patients, we detected in total 157 statistically significant differences between primary lesions and matched metastases. We further observed differences that can be linked to metastatic disease and there was also an overlapping pattern of changes between different patients. Many of the differences described here have been previously linked to poor patient survival, suggesting that this is a viable approach toward finding biomarkers for disease progression and definition of new targets useful for development of anticancer drugs. Frequent genetic differences between primary tumors and metastases in breast cancer also question, at least to some extent, the role of primary tumors as a surrogate subject of study for the systemic disease.

Relative impact of insulin resistance and obesity on cardiovascular risk factors in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) affects 5% to 7% of women of reproductive age. Insulin resistance and obesity are components of this important syndrome that may contribute to excess cardiovascular risk. We analyzed data from 69 patients with PCOS who had undergone quantitative assessment of insulin sensitivity, blood pressure, lipid profiles, and androgen levels to determine the impact of insulin resistance and obesity on parameters of cardiovascular risk. Homeostasis model assessment (HOMA) was used to stratify patients in terms of insulin resistance. To obtain a reference population, we used data from the National Health and Nutrition Examination Study (NHANES III, 1988 to 1994). The most insulin-resistant tertile of patients exhibited higher body mass index (BMI), androgen levels, systolic and diastolic blood pressure (DBP), triglyceride (TG) levels, and decreased high-density lipoprotein cholesterol (HDL-C) levels. Insulin resistance, not BMI, was the main determinant of HDL-C and TG levels and systolic blood pressure (SBP) in PCOS. Among normal women, both BMI and insulin resistance influenced cardiovascular risk factors. Insulin resistance was a more significant predictor of TGs in women with PCOS than in normal women (P =.008). In contrast to normal women, insulin resistance in PCOS appears to be the prime determinant of abnormal lipids, blood pressure, and androgens. Thus, early detection of insulin resistance, as well as weight reduction, should be emphasized for all patients with PCOS.

Statistical issues in the analysis of DNA Copy Number Variations.

Approaches to assess copy number variation have advanced rapidly and are being incorporated into genetic studies. While the technology exists for CNV genotyping, a further understanding and discussion of how to use the CNV data for association analyses is warranted. We present the options available for processing and analysing CNV data. We break these steps down into choice of genotyping platform, normalisation of the array data, calling algorithm, and statistical analysis.

A likelihood-ratio test of twin zygosity using molecular genetic markers.

The importance of using multiple polymorphic genetic markers to determine unambiguously whether a twin pair is monozygotic (MZ) or dizygotic (DZ) has long been recognized. Concordance among a set of markers is used as evidence of monozygosity, as it would be improbable for DZ twins to be concordant at a large number of polymorphic loci. Several sources give a formula for the probability of two DZ twins sharing the same genotype at a locus, assuming knowledge of allele frequencies but not of either twins genotype; this probability can be used to determine whether a set of markers will reliably distinguish between MZ and DZ status in a randomly selected twin pair. If the shared genotype is known, however, the likelihood-ratio test (LRT) of the null hypothesis of dizygosity against the alternative hypothesis of monozygosity takes into account the observed genotype and, by the Neyman-Pearson lemma, is the most powerful test of its size. The LRT is equivalent to conditioning on the genotype of one of the twins, and computing the probability, assuming DZ status, of the other twin sharing that genotype. The resulting p values are frequently lower than those produced by the unconditional probability, especially if rare alleles are observed. The unconditional probability can be recapitulated from conditional probabilities by averaging across all of the conditioned siblings possible genotypes. To illustrate properties of the LRT applied to multiple markers, the probability distribution of the LRT p value is computed from allele frequencies of twelve unlinked markers published in Elbaz et al. (2006) and compared with the p value computed from unconditional probabilities.