20 research outputs found

    Evidence for a heritable predisposition to Chronic Fatigue Syndrome

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    <p>Abstract</p> <p>Background</p> <p>Chronic Fatigue Syndrome (CFS) came to attention in the 1980s, but initial investigations did not find organic causes. Now decades later, the etiology of CFS has yet to be understood, and the role of genetic predisposition in CFS remains controversial. Recent reports of CFS association with the retrovirus xenotropic murine leukemic virus-related virus (XMRV) or other murine leukemia related retroviruses (MLV) might also suggest underlying genetic implications within the host immune system.</p> <p>Methods</p> <p>We present analyses of familial clustering of CFS in a computerized genealogical resource linking multiple generations of genealogy data with medical diagnosis data of a large Utah health care system. We compare pair-wise relatedness among cases to expected relatedness in the Utah population, and we estimate risk for CFS for first, second, and third degree relatives of CFS cases.</p> <p>Results</p> <p>We observed significant excess relatedness of CFS cases compared to that expected in this population. Significant excess relatedness was observed for both close (p <0.001) and distant relationships (p = 0.010). We also observed significant excess CFS relative risk among first (2.70, 95% CI: 1.56-4.66), second (2.34, 95% CI: 1.31-4.19), and third degree relatives (1.93, 95% CI: 1.21-3.07).</p> <p>Conclusions</p> <p>These analyses provide strong support for a heritable contribution to predisposition to Chronic Fatigue Syndrome. A population of high-risk CFS pedigrees has been identified, the study of which may provide additional understanding.</p

    Antibody Responses against Xenotropic Murine Leukemia Virus-Related Virus Envelope in a Murine Model

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    Xenotropic murine leukemia virus-related virus (XMRV) was recently discovered to be the first human gammaretrovirus that is associated with chronic fatigue syndrome and prostate cancer (PC). Although a mechanism for XMRV carcinogenesis is yet to be established, this virus belongs to the family of gammaretroviruses well known for their ability to induce cancer in the infected hosts. Since its original identification XMRV has been detected in several independent investigations; however, at this time significant controversy remains regarding reports of XMRV detection/prevalence in other cohorts and cell type/tissue distribution. The potential risk of human infection, coupled with the lack of knowledge about the basic biology of XMRV, warrants further research, including investigation of adaptive immune responses. To study immunogenicity in vivo, we vaccinated mice with a combination of recombinant vectors expressing codon-optimized sequences of XMRV gag and env genes and virus-like particles (VLP) that had the size and morphology of live infectious XMRV.Immunization elicited Env-specific binding and neutralizing antibodies (NAb) against XMRV in mice. The peak titers for ELISA-binding antibodies and NAb were 1:1024 and 1:464, respectively; however, high ELISA-binding and NAb titers were not sustained and persisted for less than three weeks after immunizations.Vaccine-induced XMRV Env antibody titers were transiently high, but their duration was short. The relatively rapid diminution in antibody levels may in part explain the differing prevalences reported for XMRV in various prostate cancer and chronic fatigue syndrome cohorts. The low level of immunogenicity observed in the present study may be characteristic of a natural XMRV infection in humans

    3,4-Methylenedioxymethamphetamine (MDMA) neurotoxicity in rats: a reappraisal of past and present findings

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    RATIONALE: 3,4-Methylenedioxymethamphetamine (MDMA) is a widely abused illicit drug. In animals, high-dose administration of MDMA produces deficits in serotonin (5-HT) neurons (e.g., depletion of forebrain 5-HT) that have been interpreted as neurotoxicity. Whether such 5-HT deficits reflect neuronal damage is a matter of ongoing debate. OBJECTIVE: The present paper reviews four specific issues related to the hypothesis of MDMA neurotoxicity in rats: (1) the effects of MDMA on monoamine neurons, (2) the use of “interspecies scaling” to adjust MDMA doses across species, (3) the effects of MDMA on established markers of neuronal damage, and (4) functional impairments associated with MDMA-induced 5-HT depletions. RESULTS: MDMA is a substrate for monoamine transporters, and stimulated release of 5-HT, NE, and DA mediates effects of the drug. MDMA produces neurochemical, endocrine, and behavioral actions in rats and humans at equivalent doses (e.g., 1–2 mg/kg), suggesting that there is no reason to adjust doses between these species. Typical doses of MDMA causing long-term 5-HT depletions in rats (e.g., 10–20 mg/kg) do not reliably increase markers of neurotoxic damage such as cell death, silver staining, or reactive gliosis. MDMA-induced 5-HT depletions are accompanied by a number of functional consequences including reductions in evoked 5-HT release and changes in hormone secretion. Perhaps more importantly, administration of MDMA to rats induces persistent anxiety-like behaviors in the absence of measurable 5-HT deficits. CONCLUSIONS: MDMA-induced 5-HT depletions are not necessarily synonymous with neurotoxic damage. However, doses of MDMA which do not cause long-term 5-HT depletions can have protracted effects on behavior, suggesting even moderate doses of the drug may pose risks

    Statistical properties of methods based on the Q-statistic for constructing a confidence interval for the between-study variance in meta-analysis

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    The effect sizes of studies included in a meta‐analysis do often not share a common true effect size due to differences in for instance the design of the studies. Estimates of this so‐called between‐study variance are usually imprecise. Hence, reporting a confidence interval together with a point estimate of the amount of between‐study variance facilitates interpretation of the meta‐analytic results. Two methods that are recommended to be used for creating such a confidence interval are the Q‐profile and generalized Q‐statistic method that both make use of the Q‐statistic. These methods are exact if the assumptions underlying the random‐effects model hold, but these assumptions are usually violated in practice such that confidence intervals of the methods are approximate rather than exact confidence intervals. We illustrate by means of two Monte‐Carlo simulation studies with odds ratio as effect size measure that coverage probabilities of both methods can be substantially below the nominal coverage rate in situations that are representative for meta‐analyses in practice. We also show that these too low coverage probabilities are caused by violations of the assumptions of the random‐effects model (ie, normal sampling distributions of the effect size measure and known sampling variances) and are especially prevalent if the sample sizes in the primary studies are small

    Examining workgroup diversity effects: does playing by the (group-retention) rules help or hinder?

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    Group diversity researchers are often faced with the problem of calculating diversity indices for groups that are incomplete due to participant nonresponse. Because participant nonresponse may attenuate the correlations that are observed between group diversity scores and outcome variables, some researchers use group-retention rules based on within-group response rates. With this approach, only those groups that have a within-group response rate at, or higher than, the rate prescribed by the group-retention rule are retained for subsequent analyses. We conducted two sets of experiments using computer simulations to determine the usefulness of group-retention rules. We found that group-retention rules are not a substitute for a high response rate and may decrease the accuracy of observed relations, and consequently, we advise against their use in diversity research. Over the past two decades, researchers and practitioners have shown considerable interest in understanding the impact that workgroup diversity has on group-level process variables (e.g., conflict, communication) and outcome variables (e.g., viability, innovation, performance). Some theoretical perspectives, such as the information-processing/decision-making approach (Ancona & Caldwell, 1992; De Dreu & West, 2001; Gruenfeld, Mannix, Williams, & Neale, 1996), predict that diversity will enhance processes and outcomes, whereas others, in particular the social identity, self-categorization, and similarity attraction perspectives (e.g., Byrne, 1971; Hogg & Abrams, 1988; Tajfel & Turner, 1986), predict that diversity will disrupt processes and impede outcomes. As various reviewers have concluded, the overall pattern of findings examining the effects of diversity is quite mixed (e.g., Horwitz & Horwitz, 2007; King, Hebl, & Beal, 2009; Mannix & Neale, 2005; Riordan, 2001; van Knippenberg, De Dreu, & Homan, 2004; Williams & O’Reilly, 1998). In their review, Mannix and Neale argued that these mixed results will only be clarified “by carefully considering moderators such as context, by broadening our view to include new types of diversity such as emotions and networks, and by focusing more carefully on mediating mechanisms” (p. 32). More recently, King et al. expressed a similar sentiment and emphasized the need, in future diversity research, to examine group processes and outcomes with greater specificity. We agree with these observations, but would add that methodological issues associated with diversity research also need careful scrutiny. Specifically, we contend that clarifying the mixed results within the diversity literature requires attention to how, and from whom, researchers collect the data on which diversity variables are based (e.g., Riordan, 2001), how well researchers’ conceptualizations of diversity match their operationalizations of diversity (e.g., Harrison & Klein, 2007), and how researchers handle the ubiquitous missing-data problem that hampers the accurate assessment of workgroup diversity (e.g., Allen, Stanley, Williams, & Ross, 2007b; Newman & Sin, 2009). The latter issue is the focus of the present research; specifically, we examine the effectiveness of rules that govern the decision to drop or retain groups based on within-group response rates. We do this in the context of diversity research, where diversity is operationalized using the standard deviation
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