Estimation of the incidence of a rare genetic disease through a two-tier mutation survey.

Recent attempts to detect mutations involving single base changes or small deletions that are specific to genetic diseases provide an opportunity to develop a two-tier mutation-screening program through which incidence of rare genetic disorders and gene carriers may be precisely estimated. A two-tier survey consists of mutation screening in a sample of patients with specific genetic disorders and in a second sample of newborns from the same population in which mutation frequency is evaluated. We provide the statistical basis for evaluating the incidence of affected and gene carriers in such two-tier mutation-screening surveys, from which the precision of the estimates is derived. Sample-size requirements of such two-tier mutation-screening surveys are evaluated. Considering examples of cystic fibrosis (CF) and medium-chain acyl-CoA dehydrogenase deficiency (MCAD), the two most frequent autosomal recessive disease in Caucasian populations and the two most frequent mutations (delta F508 and G985) that occur on these disease allele-bearing chromosomes, we show that, with 50-100 patients and a 20-fold larger sample of newborns screened for these mutations, the incidence of such diseases and their gene carriers in a population may be quite reliably estimated. The theory developed here is also applicable to rare autosomal dominant diseases for which disease-specific mutations are found.

CSF from Parkinson disease patients differentially affects cultured microglia and astrocytes.

BACKGROUND: Excessive and abnormal accumulation of alpha-synuclein (α-synuclein) is a factor contributing to pathogenic cell death in Parkinson's disease. The purpose of this study, based on earlier observations of Parkinson's disease cerebrospinal fluid (PD-CSF) initiated cell death, was to determine the effects of CSF from PD patients on the functionally different microglia and astrocyte glial cell lines. Microglia cells from human glioblastoma and astrocytes from fetal brain tissue were cultured, grown to confluence, treated with fixed concentrations of PD-CSF, non-PD disease control CSF, or control no-CSF medium, then photographed and fluorescently probed for α-synuclein content by deconvolution fluorescence microscopy. Outcome measures included manually counted cell growth patterns from day 1-8; α-synuclein density and distribution by antibody tagged 3D model stacked deconvoluted fluorescent imaging. RESULTS: After PD-CSF treatment, microglia growth was reduced extensively, and a non-confluent pattern with morphological changes developed, that was not evident in disease control CSF and no-CSF treated cultures. Astrocyte growth rates were similarly reduced by exposure to PD-CSF, but morphological changes were not consistently noted. PD-CSF treated microglia showed a significant increase in α-synuclein content by day 4 compared to other treatments (p ≤ 0.02). In microglia only, α-synuclein aggregated and redistributed to peri-nuclear locations. CONCLUSIONS: Cultured microglia and astrocytes are differentially affected by PD-CSF exposure compared to non-PD-CSF controls. PD-CSF dramatically impacts microglia cell growth, morphology, and α-synuclein deposition compared to astrocytes, supporting the hypothesis of cell specific susceptibility to PD-CSF toxicity.

Mutations in myosin light chain kinase cause familial aortic dissections.

Mutations in smooth muscle cell (SMC)-specific isoforms of α-actin and β-myosin heavy chain, two major components of the SMC contractile unit, cause familial thoracic aortic aneurysms leading to acute aortic dissections (FTAAD). To investigate whether mutations in the kinase that controls SMC contractile function (myosin light chain kinase [MYLK]) cause FTAAD, we sequenced MYLK by using DNA from 193 affected probands from unrelated FTAAD families. One nonsense and four missense variants were identified in MYLK and were not present in matched controls. Two variants, p.R1480X (c.4438C>T) and p.S1759P (c.5275T>C), segregated with aortic dissections in two families with a maximum LOD score of 2.1, providing evidence of linkage of these rare variants to the disease (p = 0.0009). Both families demonstrated a similar phenotype characterized by presentation with an acute aortic dissection with little to no enlargement of the aorta. The p.R1480X mutation leads to a truncated protein lacking the kinase and calmodulin binding domains, and p.S1759P alters amino acids in the α-helix of the calmodulin binding sequence, which disrupts kinase binding to calmodulin and reduces kinase activity in vitro. Furthermore, mice with SMC-specific knockdown of Mylk demonstrate altered gene expression and pathology consistent with medial degeneration of the aorta. Thus, genetic and functional studies support the conclusion that heterozygous loss-of-function mutations in MYLK are associated with aortic dissections.

Detection of enterotoxigenic Escherichia coli in foods by polymerase chain reaction

Enterotoxigenic Escherichia coli (ETEC) causes significant morbidity and mortality in infants of developing countries and is the most common cause of diarrhea in travelers to these areas. Enterotoxigenic Escherichia coli infections are commonly caused by ingestion of fecally contaminated food. A timely method for the detection of ETEC in foods would be important in the prevention of this disease. A multiplex polymerase chain reaction (PCR) assay which has been successful in detecting the heat-labile and heat-stable toxins of ETEC in stool was examined to determine its utility in foods. This PCR assay, preceded by a glass matrix and chaotropic DNA extraction, was effective in detecting high numbers of ETEC in a variety of foods. Ninety percent of 121 spiked food samples yielded positive results. Samples of salsa from Guadalajara, Mexico and Houston, Texas were collected and underwent DNA extraction and PCR. All samples yielded negative results for both the heat-labile and heat-stable toxins. Samples were also subjected to oligonucleotide probe analysis and resulted in 5 samples positive for ETEC. Upon dilution testing, it was found that positive PCR results only occurred when 12,000 to 1,000,000 bacteria were present in 200 mg of food. Although the DNA extraction and PCR method has been shown to be both sensitive and specific in stool, similar results were not obtained in food samples. ^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Molecular Mechanisms of Vascular Disease in Patients with Rare Variants in MYH11

Thoracic aortic aneurysms and dissections (TAAD) are the primary disease affecting the thoracic ascending aorta, with an incidence rate of 10.4/100,000. Although about 20% of patients carry a mutation in a single gene that causes their disease, the remaining 80% of patients may also have genetic factors that increase their risk for developing TAAD. Many of the genes that predispose to TAAD encode proteins involved in smooth muscle cell (SMC) contraction and the disease-causing mutations are predicted to disrupt contractile function. SMCs are the predominant cell type in the ascending aortic wall. Mutations in MYH11, encoding the smooth muscle specific myosin heavy chain, are a rare cause of inherited TAAD. However, rare but recurrent non-synonymous variants in MYH11 are present in the general population but do not cause inherited TAAD. The goal of this study was to assess the potential role of these rare variants in vascular diseases. Two distinct variants were selected: the most commonly seen rare variant, MYH11 R247C, and a duplication of the chromosomal region spanning the MYH11 locus at 16p13.1. Genetic analyses indicated that both of these variants were significantly enriched in patients with TAAD compared with controls. A knock-in mouse model of the Myh11 R247C rare variant was generated, and these mice survive and reproduce normally. They have no structural abnormalities of the aorta or signs of aortic disease, but do have decreased aortic contractility. Myh11R247C/R247C mice also have increased proliferative response to vascular injury in vivo and increased proliferation of SMCs in vitro. Myh11R247C/R247C SMCs have decreased contractile gene and protein expression and are dedifferentiated. In fibroblasts, myosin force generation is required for maturation of focal adhesions, and enhancers of RhoA activity replace enhancers of Rac1 activity as maturation occurs. Consistent with these previous findings, focal adhesions are smaller in Myh11R247C/R247C SMCs, and there is decreased RhoA activation. A RhoA activator (CN03) rescues the dedifferentiated phenotype of Myh11R247C/R247C SMCs. Myh11R247C/R247C mice were bred with an existing murine model of aneurysm formation, the Acta2-/- mouse. Over time, mice carrying the R247C allele in conjunction with heterozygous or homozygous loss of Acta2 had significantly increased aortic diameter, and a more rapid accumulation of pathologic markers. These results suggest that the Myh11 R247C rare variant acts as a modifier gene increasing the risk for and severity of TAAD in mice. In patients with 16p13.1 duplications, aortic MYH11 expression is increased, but there is no corresponding increase in smooth muscle myosin heavy chain protein. Using SMCs that overexpress Myh11, we identified alterations in SMC phenotype leading to excessive protein turnover. All contractile proteins, not just myosin, are affected, and the proteins are turned over by autophagic degradation. Surprisingly, these cells are also more contractile compared with wild-type SMCs. The results described in this dissertation firmly establish that rare variants in MYH11 significantly affect the phenotype of SMCs. Further, the data suggests that these rare variants do increase the risk of TAAD via pathways involving altered SMC phenotype and contraction. Therefore, this study validates that these rare genetic variants alter vascular SMCs and provides model systems to explore the contribution of rare variants to disease.