A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

Apply response adaptive randomization to group sequential with early stopping

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^

Bayesian estimation of multilevel item response model with missing data

This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

Angiotensin receptor agonistic autoantibody is highly prevalent in preeclampsia: correlation with disease severity.

Preeclampsia (PE), a syndrome affecting 5% of pregnancies, characterized by hypertension and proteinuria, is a leading cause of maternal and fetal morbidity and mortality. The condition is often accompanied by the presence of a circulating maternal autoantibody, the angiotensin II type I receptor agonistic autoantibody (AT(1)-AA). However, the prevalence of AT(1)-AA in PE remains unknown, and the correlation of AT(1)-AA titers with the severity of the disease remains undetermined. We used a sensitive and high-throughput luciferase bioassay to detect AT(1)-AA levels in the serum of 30 normal, 37 preeclamptic (10 mild and 27 severe), and 23 gestational hypertensive individuals. Here we report that AT(1)-AA is highly prevalent in PE ( approximately 95%). Next, by comparing the levels of AT(1)-AA among women with mild and severe PE, we found that the titer of AT(1)-AA is proportional to the severity of the disease. Intriguingly, among severe preeclamptic patients, we discovered that the titer of AT(1)-AA is significantly correlated with the clinical features of PE: systolic blood pressure (r=0.56), proteinuria (r=0.70), and soluble fms-like tyrosine kinase-1 level (r=0.71), respectively. Notably, only AT(1)-AA, and not soluble fms-like tyrosine kinase-1, levels are elevated in gestational hypertensive patients. These data serve as compelling clinical evidence that AT(1)-AA is highly prevalent in PE, and its titer is strongly correlated to the severity of the disease.

Transplantation of human embryonic stem cell-derived alveolar epithelial type II cells abrogates acute lung injury in mice.

Respiratory diseases are a major cause of mortality and morbidity worldwide. Current treatments offer no prospect of cure or disease reversal. Transplantation of pulmonary progenitor cells derived from human embryonic stem cells (hESCs) may provide a novel approach to regenerate endogenous lung cells destroyed by injury and disease. Here, we examine the therapeutic potential of alveolar type II epithelial cells derived from hESCs (hES-ATIICs) in a mouse model of acute lung injury. When transplanted into lungs of mice subjected to bleomycin (BLM)-induced acute lung injury, hES-ATIICs behaved as normal primary ATIICs, differentiating into cells expressing phenotypic markers of alveolar type I epithelial cells. Without experiencing tumorigenic side effects, lung injury was abrogated in mice transplanted with hES-ATIICs, demonstrated by recovery of body weight and arterial blood oxygen saturation, decreased collagen deposition, and increased survival. Therefore, transplantation of hES-ATIICs shows promise as an effective therapeutic to treat acute lung injury.

A pure population of lung alveolar epithelial type II cells derived from human embryonic stem cells.

Alveolar epithelial type II (ATII) cells are small, cuboidal cells that constitute approximately 60% of the pulmonary alveolar epithelium. These cells are crucial for repair of the injured alveolus by differentiating into alveolar epithelial type I cells. ATII cells derived from human ES (hES) cells are a promising source of cells that could be used therapeutically to treat distal lung diseases. We have developed a reliable transfection and culture procedure, which facilitates, via genetic selection, the differentiation of hES cells into an essentially pure (>99%) population of ATII cells (hES-ATII). Purity, as well as biological features and morphological characteristics of normal ATII cells, was demonstrated for the hES-ATII cells, including lamellar body formation, expression of surfactant proteins A, B, and C, alpha-1-antitrypsin, and the cystic fibrosis transmembrane conductance receptor, as well as the synthesis and secretion of complement proteins C3 and C5. Collectively, these data document the successful generation of a pure population of ATII cells derived from hES cells, providing a practical source of ATII cells to explore in disease models their potential in the regeneration and repair of the injured alveolus and in the therapeutic treatment of genetic diseases affecting the lung.

Exploring the role of viral infection in type 2 diabetes

Viral infection is known to play a role in type I diabetes, but there is a paucity of information on the role of viruses in type 2 diabetes. This research examined the seroprevalence of selected viruses in a group of predominantly Mexican-American patients with End Stage Renal Disease (ESRD). Using a case control design, patients with type 2 diabetes were compared with a group of non-diabetic controls. ^ One hundred and thirteen patients, 83 with type 2 diabetes and 30 controls without diabetes, underwent hemodialysis at the same chronic dialysis facility in San Antonio, Texas. AD subjects were tested for IgG, IgM, and neutralizing antibodies against Coxsackie B viruses (CBV), and IgG and IgM antibodies against cytomegalovirus (CMV) and parvovirus B19 (PVB19). Hepatitis B virus antigen (HBVAg), Hepatitis B virus antibody (HBVAb), Hepatitis C virus antibody (HCVAb), and Rubella (IgG) were also measured. A subset of 91 patients, 66 with diabetes and 25 controls, were tested bimonthly for six months. There was a significant difference (P = 0.04) in the seroprevalence of IgG antibodies to CMV between patients with type 2 diabetes (98%) and non-diabetic controls (87%) in the initial sample (OR = 6.2, 95% CI:1.1–36.0). A greater seroprevalence of CMV IgG antibodies was observed over the six month period among patients with type 2 diabetes (M) compared to controls (84%). This difference was also statistically (P < 0.03), with a greater odds ratio (OR = 12.4, 95% CI: 1.3–116.9), but with larger confidence interval related to the small number of subjects. However, when adjusted for age by logistic regression analysis there was no difference between the groups (OR = 1). ^ After one sample, there was a greater seroprevalence of HCVAb in the group without diabetes (28%), compared to those with type 2 diabetes (10%) (P = 0.04). This difference was no longer significant when adjusted for patient age. The prevalence of antibodies to PVB19, HBSAg, HBV, and Rubella was not significantly different in patients with type 2 diabetes and controls. There were significantly more vascular complications (P < 0.02) among patients with diabetes. ^ These results indicate that the significant associations observed in this population between viral infection with CMV, HCV, and type 2 diabetes are confounded by age. Accelerated atherosclerosis has been associated with age, diabetes, as well as CMV. Latent infection may be a factor that links these processes. ^

Tolerance of allografts across MHC barriers by allochimeric class I MHC proteins

Class I MHC proteins have been shown to induce accelerated rejection or prolong survival of allografts in various experimental models. These immunological effects have been attributed to the highly polymorphic alpha helical regions of the extracellular portions of the class I MHC molecule. The present experiments were designed to elucidate the immunomodulatory effects of these polymorphic regions and delineate the mechanisms involved. Soluble allochimeric class I MHC proteins were produced by substituting the PVG class I MHC RT1.Ac amino acid residues within the a 1 helical region with those of the donor BN ( a 1hn-RT1.Ac), the a 2 helical region of BN ( a 2hn-RT1.Ac), and both the a 1 and a 2 helical regions (RT1.An). The class I MHC proteins were produced in an E. coli protein expression system. The a 2hn-RT1.Ac and RT1.An proteins, when administered subcutaneously into PVG hosts 7 days prior to transplantation, resulted in accelerated rejection of BN cardiac allografts. The a 1hn-RT1.Ac construct did not demonstrate such immunogenic effects. Intra-portal administration of a 1hn-RT1.Ac or RT1.An, in combination with perioperative CsA, induced tolerance to BN cardiac allografts. The a 1hn-RT1.Ac protein was able to induce tolerance in a larger majority of the PVG recipients and at a lower dose of protein when compared to the RT1.An protein. RT1.An administered orally to PVG recipients also induced long term survival of cardiac allografts. In vitro analysis revealed that lymphocytes from tolerant hosts were hyporesponsive to donor splenocytes, but responsive to 3rd party splenocytes. Evaluation of T cell cytokine expression patterns revealed that rejector PVG hosts displayed a Type I T-cell response when re-challenged with donor splenocytes, in contrast to tolerant animals that displayed a Type II T-cell response. FACS analysis of the T cells revealed that the ratio of CD4 to CD8 cells was 3:1 and was consistent in the groups tested suggesting a complex interaction between the subsets of T cells, yielding the observed results. Histologic analysis of the cardiac allografts revealed that tolerant PVG hosts maintained BN cardiac allografts without any evidence of acute or chronic rejection after 300 days post transplant. This body of work has demonstrated that the use of soluble donor/recipient allochimeric class I MHC proteins with a short peri-operative course of CsA resulted in transplant tolerance. This treatment regimen proffers a clinically relevant approach to the induction of tolerance across MHC barriers. ^

Collagen I modulates growth and gene expression in prostate cancer cells

Prostate cancer is the second leading cause of male cancer-related deaths in the United States. Interestingly, prostate cancer preferentially metastasizes to skeletal tissue. Once in the bone microenvironment, advanced prostate cancer becomes highly resistant to therapeutic modalities. Several factors, such as extracellular matrix (ECM) components, have been implicated in the spread and propagation of prostatic carcinoma. In these studies, we have utilized the PC3 cell line, derived from a human bone metastasis, to investigate the influence of the predominant bone ECM protein, type I collagen, on prostate cancer cell proliferation and gene expression. We have also initiated the design and production of ribozymes to specific gene targets that may influence prostate cancer bone metastasis. ^ Our results demonstrate that PC3 cells rapidly adhere and spread on collagen I to a greater degree than on fibronectin (FN) or poly-L-lysine (PLL). Flow cytometry analysis reveals the presence of the α1, α2 and α3 collagen binding integrin subunits. The use of antibody function blocking studies reveals that PC3 cells can utilize α2β 1 and α3β1 integrins to adhere to collagen I. Once plated on collagen I, the cells exhibit increased rates of proliferation compared with cells plated on FN or tissue culture plastic. Additionally, cells plated on collagen I show increased expression of proteins associated with progression through G1 phase of the cell cycle. Inhibitor studies point to a role for phosphatidylinositol 3-kinase (PI3K), MAP kinase (MAPK), and p70 S6 kinase in collagen I-mediated PC3 cell proliferation and cyclin D1 expression. To further characterize the effect of type I collagen on prostate cancer bone metastasis, we utilized a cDNA microarray strategy to monitor type I collagen-mediated changes in gene expression. Results of this analysis revealed a gene expression profile reflecting the increased proliferation occurring on type I collagen. Microarray analysis also revealed differences in the expression of specific gene targets that may impact on prostate cancer metastasis to bone. ^ As a result of our studies on the interaction of prostate cancer cells and the skeletal ECM, we sought to develop novel molecular tools for future gene therapy of functional knockdown experiments. To this end, we developed a series of ribozymes directed against the α2 integrin and at osteopontin, a protein implicated in the metastasis of various cancers, including prostate. These ribozymes should facilitate the future study of the mechanism of prostate cancer cell proliferation, and disease progression occurring at sites of skeletal metastasis where a type I collagen-based environment predominates. ^ Together these studies demonstrate the involvement of bone ECM proteins on prostate cancer cell proliferation and suggest that they may play a significant role on the growth of prostate metastases once in the bone microenvironment. ^

Delayed Thrombus Resolution and Fibroproliferative Vascular Wound Healing From Deficiency of Type III Collagen: a Paradoxical Mechanism for Tissue Fragility

Vascular Ehlers-Danlos syndrome is a heritable disease of connective tissue caused by mutations in COL3A1, conferring a tissue deficiency of type III collagen. Cutaneous wounds heal poorly in these patients, and they are susceptible to spontaneous and catastrophic rupture of expansible hollow organs like the gut, uterus, and medium-sized to large arteries, which leads to premature death. Although the predisposition for organ rupture is often attributed to inherent tissue fragility, investigation of arteries from a haploinsufficient Col3a1 mouse model (Col3a1+/-) demonstrates that mutant arteries withstand even supraphysiologic pressures comparably to wild-type vessels. We hypothesize that injury that elicits occlusive thrombi instead unmasks defective thrombus resolution resulting from impaired production of type III collagen, which causes deranged remodeling of matrix, persistent inflammation, and dysregulated behavior by resident myofibroblasts, culminating in the development of penetrating neovascular channels that disrupt the mechanical integrity of the arterial wall. Vascular injury and thrombus formation following ligation of the carotid artery reveals an abnormal persistence and elevated burden of occlusive thrombi at 21 post-operative days in vessels from Col3a1+/- mice, as opposed to near complete resolution and formation of a patent and mature neointima in wild-type mice. At only 14 days, both groups harbor comparable burdens of resolving thrombi, but wild-type mice increase production of type III collagen in actively resolving tissues, while mutant mice do not. Rather, thrombi in mutant mice contain higher burdens of macrophages and proliferative myofibroblasts, which persist through 21 days while wild-type thrombi, inflammatory cells, and proliferation all regress. At the same time that increased macrophage burdens were observed at 14 and 21 days post ligation, the medial layer of mutant arterial walls concurrently harbored a significantly higher incidence of penetrating neovessels compared with those in wild-type mice. To assess whether limited type III collagen production alters myofibroblast behavior, fibroblasts from vEDS patients with COL3A1 missense mutations were seeded into three-dimensional fibrin gel constructs and stimulated with transforming growth factor-β1 to initiate myofibroblast differentiation. Although early signaling events occur similarly in all cell lines, late extracellular matrix- and mechanically-regulated events like transcriptional upregulation of type I and type III collagen secretion are delayed in mutant cultures, while transcription of genes encoding intracellular contractile machinery is increased. Sophisticated imaging of collagen synthesized de novo by resident myofibroblasts visualizes complex matrix reorganization by control cells but only meager remodeling by COL3A1 mutant cells, concordant with their compensatory contraction to maintain tension in the matrix. Finally, administration of immunosuppressive rapamycin to mice following carotid ligation sufficiently halts the initial inflammatory phase of thrombus resolution and fully prevents both myofibroblast migration into the thrombus and the differential development of neovessels between mutant and wild-type mice, suggesting that pathological defects in mutant arteries develop secondarily to myofibroblast dysfunction and chronic inflammatory stimulation, rather than as a manifestation of tissue fragility. Together these data establish evidence that pathological defects in the vessel wall architecture develop in mutant arteries as sequelae to abnormal healing and remodeling responses activated by arterial injury. Thus, these data support the hypothesis that events threatening the integrity of type III collagen-deficient vessels develop not as a result of inherent tissue weakness and fragility at baseline but instead as an episodic byproduct of abnormally persistent granulation tissue and fibroproliferative intravascular remodeling.