Tau-66: evidence for a novel tau conformation in Alzheimer's disease

We have characterized a novel monoclonal antibody, Tau-66, raised against recombinant human tau. Immunohistochemistry using Tau-66 reveals a somatic-neuronal stain in the superior temporal gyrus (STG) that is more intense in Alzheimer's disease (AD) brain than in normal brain. In hippocampus, Tau-66 yields a pattern similar to STG, except that neurofibrillary lesions are preferentially stained if present. In mild AD cases, Tau-66 stains plaques lacking obvious dystrophic neurites (termed herein 'diffuse reticulated plaques') in STG and the hippocampus. Enzyme-linked immunosorbent assay (ELISA) analysis reveals that Tau-66 is specific for tau, as there is no cross-reactivity with MAP2, tubulin, Abeta(1-40), or Abeta(1-42), although Tau-66 fails to react with tau or any other polypeptide on western blots. The epitope of Tau-66, as assessed by ELISA testing of tau deletion mutants, appears discontinuous, requiring residues 155-244 and 305-314. Tau-66 reactivity exhibits buffer and temperature sensitivity in an ELISA format and is readily abolished by SDS treatment. Taken together these lines of evidence indicate that the Tau-66 epitope is conformation-dependent, perhaps involving a close interaction of the proline-rich and the third microtubule-binding regions. This is the first indication that tau can undergo this novel folding event and that this conformation of tau is involved in AD pathology.     

Regression models for disease prevalence with diagnostic tests on pools of serum samples

Whether the aim is to diagnose individuals or estimate prevalence, many epidemiological studies have demonstrated the successful use of tests on pooled sera. These tests detect whether at least one sample in the pool is positive. Although originally designed to reduce diagnostic costs, testing pools also lowers false positive and negative rates in low prevalence settings and yields more precise prevalence estimates. Current methods are aimed at estimating the average population risk from diagnostic tests on pools. In this article, we extend the original class of risk estimators to adjust for covariates recorded on individual pool members. Maximum likelihood theory provides a flexible estimation method that handles different covariate values in the pool, different pool sizes, and errors in test results. In special cases, software for generalized linear models can be used. Pool design has a strong impact on precision and cost efficiency, with covariate-homogeneous pools carrying the largest amount of information. We perform joint pool and sample size calculations using information from individual contributors to the pool and show that a good design can severely reduce cost and yet increase precision. The methods are illustrated using data from a Kenyan surveillance study of HIV. Compared to individual testing, age-homogeneous, optimal-sized pools of average size seven reduce cost to 44% of the original price with virtually no loss in precision.     

Random effects modeling of multiple binomial responses using the multivariate binomial logit-normal distribution

The multivariate binomial logit-normal distribution is a mixture distribution for which, (i) conditional on a set of success probabilities and sample size indices, a vector of counts is independent binomial variates, and (ii) the vector of logits of the parameters has a multivariate normal distribution. We use this distribution to model multivariate binomial-type responses using a vector of random effects. The vector of logits of parameters has a mean that is a linear function of explanatory variables and has an unspecified or partly specified covariance matrix. The model generalizes and provides greater flexibility than the univariate model that uses a normal random effect to account for positive correlations in clustered data. The multivariate model is useful when different elements of the response vector refer to different characteristics, each of which may naturally have its own random effect. It is also useful for repeated binary measurement of a single response when there is a nonexchangeable association structure, such as one often expects with longitudinal data or when negative association exists for at least one pair of responses. We apply the model to an influenza study with repeated responses in which some pairs are negatively associated and to a developmental toxicity study with continuation-ratio logits applied to an ordinal response with clustered observations.     

Testing equality of survival functions based on both paired and unpaired censored data

We introduce two test procedures for comparing two survival distributions on the basis of randomly right-censored data consisting of both paired and unpaired observations. Our procedures are based on generalizations of a pooled rank test statistic previously proposed for uncensored data. One generalization adapts the Prentice-Wilcoxon score, while the other adapts the Akritas score. The use of these particular scoring systems in pooled rank tests with randomly right-censored paired data has been advocated by several researchers. Our test procedures utilize the permutation distributions of the test statistics based on a novel manner of permuting the scores. Permutation versions of tests for right-censored paired data and for two independent right-censored samples that use the proposed scoring systems are obtained as special cases of our test procedures. Simulation results show that our test procedures have high power for detecting scale and location shifts in exponential and log-logistic distributions for the survival times. We also demonstrate the advantages of our test procedures in terms of utilizing randomly occurring unpaired observations that are discarded in test procedures for paired data. The tests are applied to skin graft data previously reported elsewhere.     

Regression analysis when covariates are regression parameters of a random effects model for observed longitudinal measurements

We consider regression analysis when covariate variables are the underlying regression coefficients of another linear mixed model. A naive approach is to use each subject's repeated measurements, which are assumed to follow a linear mixed model, and obtain subject-specific estimated coefficients to replace the covariate variables. However, directly replacing the unobserved covariates in the primary regression by these estimated coefficients may result in a significantly biased estimator. The aforementioned problem can be evaluated as a generalization of the classical additive error model where repeated measures are considered as replicates. To correct for these biases, we investigate a pseudo-expected estimating equation (EEE) estimator, a regression calibration (RC) estimator, and a refined version of the RC estimator. For linear regression, the first two estimators are identical under certain conditions. However, when the primary regression model is a nonlinear model, the RC estimator is usually biased. We thus consider a refined regression calibration estimator whose performance is close to that of the pseudo-EEE estimator but does not require numerical integration. The RC estimator is also extended to the proportional hazards regression model. In addition to the distribution theory, we evaluate the methods through simulation studies. The methods are applied to analyze a real dataset from a child growth study.     

The FTDP-17-linked mutation R406W abolishes the interaction of phosphorylated tau with microtubules

The recent finding that several point mutations in the gene encoding for the microtubule-binding protein tau correlate with neurological disorders has heightened interest in the mechanisms of destabilization of this protein. In this study the functional consequences of the tau mutation R406W on the interaction of the protein with microtubules have been analyzed. Mutated tau is less phosphorylated than its normal counterpart at serines 396 and 404. Furthermore, the phosphorylated mutant protein is unable to bind to microtubules, and, as a consequence, microtubules assembled after transient nocodazole treatment in the presence of this tau variant contain only unmodified tau and appear to form more and longer bundles than those assembled in the presence of wild-type tau. We propose that phosphorylated tau, unbound to microtubules, could accumulate in the cytoplasm.     

Semiparametric maximum likelihood for measurement error model regression

This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural model is used in which probability distributions are specified for (a) the response and (b) the measurement error. A distribution is also assumed for the true explanatory variable but is left unspecified and is estimated by nonparametric maximum likelihood. For various types of extra information about the measurement error distribution, the proposed algorithm makes use of available routines that would be appropriate for likelihood analysis of (a) and (b) if the true x were available. Simulations suggest that the semiparametric maximum likelihood estimator retains a high degree of efficiency relative to the structural maximum likelihood estimator based on correct distributional assumptions and can outperform maximum likelihood based on an incorrect distributional assumption. The approach is illustrated on three examples with a variety of structures and types of extra information about the measurement error distribution.     

Abnormal tau-containing filaments in neurodegenerative diseases

It has been known for some time that the neurofibrillary pathology in Alzheimer's disease consists of so-called paired helical and straight filaments made up of the microtubule-associated protein tau. The degree of dementia observed in the disease correlates better with the extent of neurofibrillary pathology than with the Abeta amyloid deposits, the other characteristic defining pathological fibrous deposit in Alzheimer's disease. However, no familial cases of Alzheimer's disease have been genetically linked to the tau protein locus. Recently a group of frontotemporal dementias with parkinsonism linked to chromosome 17 has been shown to be caused by mutations in the tau gene. Some are missense mutations giving altered tau proteins, whereas others affect the splicing of the pre-mRNA and change the balance between different tau isoforms. Histologically these diseases are all characterised by various kinds of filamentous tau protein deposits, mostly in the complete absence of Abeta deposits. The abnormal tau filaments show different morphologies, depending on the nature of the tau mutation. These diseases show that tau mutations can be a prime cause of inherited dementing illness and may throw some light on the pathological process in the much larger number of sporadic cases of Alzheimer's disease.     

Fibers of tau fragments, but not full length tau, exhibit a cross beta-structure: implications for the formation of paired helical filaments

We have used X-ray fiber diffraction to probe the structure of fibers of tau and tau fragments. Fibers of fragments from the microtubule binding domain had a cross beta-structure that closely resembles that reported both for neurofibrillary tangles found in Alzheimer's disease brain and for fibrous lesions from other protein folding diseases. In contrast, fibers of full-length tau had a different, more complex structure. Despite major differences at the molecular level, all fiber types exhibited very similar morphology by electron microscopy. These results have a number of implications for understanding the etiology of Alzheimer's and other tauopathic diseases. The morphology of the peptide fibers suggests that the region in tau corresponding to the peptides plays a critical role in the nucleation of fiber assembly. The dramatically different structure of the full length tau fibers suggests that some region in tau has enough inherent structure to interfere with the formation of cross beta-fibers. Additionally, the similar appearance by electron microscopy of fibrils with varying molecular structure suggests that different molecular arrangements may exist in other samples of fibers formed from tau.     

糖元合成酶激酶3β对微管相关蛋白tau的磷酸化作用

tau蛋白是中枢神经系统中重要的微管相关蛋白,其功能受磷酸化调节.异常过度磷酸化的tau蛋白是阿尔茨海默病患者脑中神经纤维缠结的主要组成部分.糖元合成酶激酶3β(glycogen synthase kinase-3β,GSK-3β)是重要的tau蛋白激酶之一,它虽可催化tau蛋白多个位点的磷酸化,但对不同位点,其催化效率不同.通过位点特异性、磷酸化依赖的tau蛋白抗体,用免疫印迹技术,检测GSK-3β对tau蛋白位点特异性的磷酸化作用及动力学.用双倒数作图,计算GSK-3β催化tau磷酸化以及各个位点磷酸化的Km值,并结合培养细胞中的实验,研究GSK-3β对tau蛋白磷酸化作用的位点特异性.结果显示,GSK-3β催化tau蛋白多个位点的磷酸化,其中包括Thr181、Ser199、Ser202、Thr205、Thr212、Thr217、Thr231、Ser396和Ser404,对不同的位点磷酸化作用,其Km值不同,GSK-3β对Ser396的Km值最低,即对Ser396位点的亲和性最高,催化其磷酸化的能力最强.在培养的细胞中,也显示了GSK-3β的表达引起Ser396位点的磷酸化最明显.