ß2-Microglobulin deficiency causes a complex immunodeficiency of the innate and adaptive immune system.

BACKGROUND: Most patients with MHC class I (MHC-I) deficiency carry genetic defects in transporter associated with antigen processing 1 (TAP1) or TAP2. The clinical presentation can vary, and about half of the patients have severe skin disease. Previously, one report described ß2-microglobulin (ß2m) deficiency as another monogenetic cause of MHC-I deficiency, but no further immunologic evaluation was performed. OBJECTIVE: We sought to describe the molecular and immunologic features of ß2m deficiency in 2 Turkish siblings with new diagnoses. METHODS: Based on clinical and serologic findings, the genetic defect was detected by means of candidate gene analysis. The immunologic characterization comprises flow cytometry, ELISA, functional assays, and immunohistochemistry. RESULTS: Here we provide the first extensive clinical and immunologic description of ß2m deficiency in 2 siblings. The sister had recurrent respiratory tract infections and severe skin disease, whereas the brother was fairly asymptomatic but had bronchiectasis. Not only polymorphic MHC-I but also the related CD1a, CD1b, CD1c, and neonatal Fc receptor molecules were absent from the surfaces of ß2m-deficient cells. Absent neonatal Fc receptor surface expression led to low serum IgG and albumin levels in both siblings, whereas the heterozygous parents had normal results for all tested parameters except ß2m mRNA (B2M) expression. Similar to TAP deficiency in the absence of a regular CD8 T-cell compartment, CD8(+) γδ T cells were strongly expanded. Natural killer cells were normal in number but not "licensed to kill." CONCLUSION: The clinical presentation of patients with ß2m deficiency resembles that of patients with other forms of MHC-I deficiency, but because of the missing stabilizing effect of ß2m on other members of the MHC-I family, the immunologic defect is more extensive than in patients with TAP deficiency.

Evaluation of frequentist test statistics using constrained statistical inference in the context of the generalized linear model.

When faced with a binary or count outcome, informative hypotheses can be tested in the generalized linear model using the distance statistic as well as modified versions of the Wald, the Score and the likelihood-ratio test (LRT). In contrast to classical null hypothesis testing, informative hypotheses allow to directly examine the direction or the order of the regression coefficients. Since knowledge about the practical performance of informative test statistics is missing in the theoretically oriented literature, we aim at closing this gap using simulation studies in the context of logistic and Poisson regression. We examine the effect of the number of constraints as well as the sample size on type I error rates when the hypothesis of interest can be expressed as a linear function of the regression parameters. The LRT shows the best performance in general, followed by the Score test. Furthermore, both the sample size and especially the number of constraints impact the type I error rates considerably more in logistic compared to Poisson regression. We provide an empirical data example together with R code that can be easily adapted by applied researchers. Moreover, we discuss informative hypothesis testing about effects of interest, which are a non-linear function of the regression parameters. We demonstrate this by means of a second empirical data example.

Overview and evaluation of various frequentist test statistics using constrained statistical inference in the context of linear regression.

Within the framework of constrained statistical inference, we can test informative hypotheses, in which, for example, regression coefficients are constrained to have a certain direction or be in a specific order. A large amount of frequentist informative test statistics exist that each come with different versions, strengths and weaknesses. This paper gives an overview about these statistics, including the Wald, the LRT, the Score, the F ¯ - and the D-statistic. Simulation studies are presented that clarify their performance in terms of type I and type II error rates under different conditions. Based on the results, it is recommended to use the Wald and F ¯ -test rather than the LRT and Score test as the former need less computing time. Furthermore, it is favorable to use the degrees of freedom corrected rather than the naive mean squared error when calculating the test statistics as well as using the F ¯ - rather than the χ ¯ 2 -distribution when calculating the p-values.