Loss of T Cell Progenitor Checkpoint Control Underlies Leukemia Initiation in Rag1-Deficient Nonobese Diabetic Mice

NOD mice exhibit major defects in the earliest stages of T cell development in the thymus. Genome-wide genetic and transcriptome analyses were used to investigate the origins and consequences of an early T cell developmental checkpoint breakthrough in Rag1-deficient NOD mice. Quantitative trait locus analysis mapped the presence of checkpoint breakthrough cells to several known NOD diabetes susceptibility regions, particularly insulin-dependent diabetes susceptibility genes (Idd)9/11 on chromosome 4, suggesting common genetic origins for T cell defects affecting this trait and autoimmunity. Genome-wide RNA deep-sequencing of NOD and B6 Rag1-deficient thymocytes revealed the effects of genetic background prior to breakthrough, as well as the cellular consequences of the breakthrough. Transcriptome comparison between the two strains showed enrichment in differentially expressed signal transduction genes, prominently tyrosine kinase and actin-binding genes, in accord with their divergent sensitivities to activating signals. Emerging NOD breakthrough cells aberrantly expressed both stem cell–associated proto-oncogenes, such as Lmo2, Hhex, Lyl1, and Kit, which are normally repressed at the commitment checkpoint, and post–β-selection checkpoint genes, including Cd2 and Cd5. Coexpression of genes characteristic of multipotent progenitors and more mature T cells persists in the expanding population of thymocytes and in the thymic leukemias that emerge with age in these mice. These results show that Rag1-deficient NOD thymocytes have T cell defects that can collapse regulatory boundaries at two early T cell checkpoints, which may predispose them to both leukemia and autoimmunity

Mamu-A⁎01/Kb transgenic and MHC Class I knockout mice as a tool for HIV vaccine development

AbstractWe have developed a murine model expressing the rhesus macaque (RM) Mamu-A⁎01 MHC allele to characterize immune responses and vaccines based on antigens of importance to human disease processes. Towards that goal, transgenic (Tg) mice expressing chimeric RM (α1 and α2 Mamu-A⁎01 domains) and murine (α3, transmembrane, and cytoplasmic H-2Kb domains) MHC Class I molecules were derived by transgenesis of the H-2KbDb double MHC Class I knockout strain. After immunization of Mamu-A⁎01/Kb Tg mice with rVV-SIVGag–Pol, the mice generated CD8+ T-cell IFN-γ responses to several known Mamu-A⁎01 restricted epitopes from the SIV Gag and Pol antigen sequence. Fusion peptides of highly recognized CTL epitopes from SIV Pol and Gag and a strong T-help epitope were shown to be immunogenic and capable of limiting an rVV-SIVGag–Pol challenge. Mamu-A⁎01/Kb Tg mice provide a model system to study the Mamu-A⁎01 restricted T-cell response for various infectious diseases which are applicable to a study in RM

Three Ways of Combining Genotyping and Resequencing in Case-Control Association Studies

We describe three statistical results that we have found to be useful in case-control genetic association testing. All three involve combining the discovery of novel genetic variants, usually by sequencing, with genotyping methods that recognize previously discovered variants. We first consider expanding the list of known variants by concentrating variant-discovery in cases. Although the naive inclusion of cases-only sequencing data would create a bias, we show that some sequencing data may be retained, even if controls are not sequenced. Furthermore, for alleles of intermediate frequency, cases-only sequencing with bias-correction entails little if any loss of power, compared to dividing the same sequencing effort among cases and controls. Secondly, we investigate more strongly focused variant discovery to obtain a greater enrichment for disease-related variants. We show how case status, family history, and marker sharing enrich the discovery set by increments that are multiplicative with penetrance, enabling the preferential discovery of high-penetrance variants. A third result applies when sequencing is the primary means of counting alleles in both cases and controls, but a supplementary pooled genotyping sample is used to identify the variants that are very rare. We show that this raises no validity issues, and we evaluate a less expensive and more adaptive approach to judging rarity, based on group-specific variants. We demonstrate the important and unusual caveat that this method requires equal sample sizes for validity. These three results can be used to more efficiently detect the association of rare genetic variants with disease

Phase I Study of Pazopanib in Patients with Advanced Solid Tumors and Hepatic Dysfunction: A National Cancer Institute Organ Dysfunction Working Group Study

Pazopanib is a potent, multi-targeted receptor tyrosine kinase inhibitor; however, there is limited information regarding the effects of liver function on pazopanib metabolism and pharmacokinetics (PK). The objective of this study was to establish the maximum tolerated dose (MTD) and PK profile of pazopanib in patients with varying degrees of hepatic dysfunction

Missense Mutations in the MEFV Gene Are Associated with Fibromyalgia Syndrome and Correlate with Elevated IL-1β Plasma Levels

BACKGROUND:Fibromyalgia syndrome (FMS), a common, chronic, widespread musculoskeletal pain disorder found in 2% of the general population and with a preponderance of 85% in females, has both genetic and environmental contributions. Patients and their parents have high plasma levels of the chemokines MCP-1 and eotaxin, providing evidence for both a genetic and an immunological/inflammatory origin for the syndrome (Zhang et al., 2008, Exp. Biol. Med. 233: 1171-1180). METHODS AND FINDINGS:In a search for a candidate gene affecting inflammatory pathways, among five screened in our patient samples (100 probands with FMS and their parents), we found 10 rare and one common alleles for MEFV, a gene in which various compound heterozygous mutations lead to Familial Mediterranean Fever (FMF). A total of 2.63 megabases of genomic sequence of the MEFV gene were scanned by direct sequencing. The collection of rare missense mutations (all heterozygotes and tested in the aggregate) had a significant elevated frequency of transmission to affecteds (p = 0.0085, one-sided, exact binomial test). Our data provide evidence that rare missense variants of the MEFV gene are, collectively, associated with risk of FMS and are present in a subset of 15% of FMS patients. This subset had, on average, high levels of plasma IL-1beta (p = 0.019) compared to FMS patients without rare variants, unaffected family members with or without rare variants, and unrelated controls of unknown genotype. IL-1beta is a cytokine associated with the function of the MEFV gene and thought to be responsible for its symptoms of fever and muscle aches. CONCLUSIONS:Since misregulation of IL-1beta expression has been predicted for patients with mutations in the MEFV gene, we conclude that patients heterozygous for rare missense variants of this gene may be predisposed to FMS, possibly triggered by environmental factors

Complexity and Power in Case-Control Association Studies

A general method is described for estimation of the power and sample size of studies relating a dichotomous phenotype to multiple interacting loci and environmental covariates. Either a simple case-control design or more complex stratified sampling may be used. The method can be used to design individual studies, to evaluate the power of alternative test statistics for complex traits, and to examine general questions of study design through explicit scenarios. The method is used here to study how the power of association tests is affected by problems of allelic heterogeneity and to investigate the potential role for collective testing of sets of related candidate genes in the presence of locus heterogeneity. The results indicate that allele-discovery efforts are crucial and that omnibus tests or collective testing of alleles can be substantially more powerful than separate testing of individual allelic variants. Joint testing of multiple candidate loci can also dramatically improve power, despite model misspecification and inclusion of irrelevant loci, but requires an a priori hypothesis defining the set of loci to investigate

Dental care use by U.S. veterans eligible for VA care

Military veterans eligible for dental care in U.S. Department of Veterans Affairs (VA) facilities cooperated for a mailed survey about their dental care utilization. Subjects were selected because of their eligibility for continuing dental care in VA facilities at no monetary cost. However, only 48% reported the VA as their only or primary source of dental care; this allowed us the oppurtunity to compare dental care frequency by those who received dental care at no monetary cost with those who did not, as well as measure delivery system effects on dental care use. Consequently, we tested respondent-level and delivery system-level hypotheses regarding determinants of veterans' dental care use. Predisposing characteristics (dentate status, usual reason for dental visits, and the importance placed on dental care and oral health) were the strongest determinants of interval since last dental visit. Enabling determinants (current source of dental care, and having a regular source of care) were also significant, but measures of need for dental care (perceived oral health and perceived need for treatment) were not. More recent dental care use by veterans who used the VA delivery system as their source of dental care, even with dental care payment source and other determinants accounted for, suggests that the VA delivery system may have promoted more regular use compared to other systems.dental care utilization delivery systems attitudes dental insurance

Mining Branching Rules from Past Survey Data with an Illustration Using a Geriatric Assessment Survey for Older Adults with Cancer

We construct a fast data mining algorithm that can be used to identify high-frequency response patterns in historical surveys. Identification of these patterns leads to the derivation of question branching rules that shorten the time required to complete a survey. The data mining algorithm allows the user to control the error rate that is incurred through the use of implied answers that go along with each branching rule. The context considered is binary response questions, which can be obtained from multi-level response questions through dichotomization. The algorithm is illustrated by the analysis of four sections of a geriatric assessment survey used by oncologists. Reductions in the number of questions that need to be asked in these four sections range from 33% to 54%

Test size and power using detection in subsets.

1<p>Number cases and controls reduced to 100, so sequencing exhausts cases.</p><p>For each line, except the last, 500 cases and 500 controls are generated in 5,000 simulated samples to estimate test size or power for a nominal 0.05-level test comparing the collective frequency of rare alleles. In each scenario, the baseline disease rate is 1%, so relative risk (RR) of 2.5 implies a penetrance of 2.5%. <b>Rare</b> is the number of unknown rare alleles in the population, all assumed to have the same frequency and penetrance. <b>Freq</b> is the total frequency of all rare alleles (<i>e.g.</i> 20 rare alleles with a combined frequency of 0.2 imply a frequency of 0.01 each). We make the simplifying assumption that rare alleles are mutually exclusive. <b>Seq</b> is the total number sequenced, either concentrated in cases or equally divided (balanced) among cases and controls. All four p-value columns are from Fisher's exact text. The first three count the number of cases and controls with any of the rare alleles detected among the indiduals that are sequenced. In the <b>Naive</b> and <b>Corrected</b> columns, all sequences are from controls, but the number of detected distinct rare alleles is subtracted from the case count in the ‘Corrected’ column. <b>Balanced</b> indicates that the individuals sequenced for allele detection were equally divided between cases and controls. <b>Complete</b> denotes the test based on sequencing all cases and all controls — a much larger sequencing effort. The parenthetic numbers indicate 25th and 75th percentiles of the number of rare alleles detected in the cases-only and balanced detection strategies.</p