THE APPLICATION OF PATH ANALYSIS TO ASSESSMENT OF IRON NUTRITIONAL STATUS IN MAN

Path analysis has been applied to components of the iron metabolic system with the intent of suggesting an integrated procedure for better evaluating iron nutritional status at the community level. The primary variables of interest in this study were (1) iron stores, (2) total iron-binding capacity, (3) serum ferritin, (4) serum iron, (5) transferrin saturation, and (6) hemoglobin concentration. Correlation coefficients for relationships among these variables were obtained from published literature and postulated in a series of models using measures of those variables that are feasible to include in a community nutritional survey. Models were built upon known information about the metabolism of iron and were limited by what had been reported in the literature in terms of correlation coefficients or quantitative relationships. Data were pooled from various studies and correlations of the same bivariate relationships were averaged after z- transformations. Correlation matrices were then constructed by transforming the average values back into correlation coefficients. The results of path analysis in this study indicate that hemoglobin is not a good indicator of early iron deficiency. It does not account for variance in iron stores. On the other hand, 91% of the variance in iron stores is explained by serum ferritin and total iron-binding capacity. In addition, the magnitude of the path coefficient (.78) of the serum ferritin-iron stores relationship signifies that serum ferritin is the most important predictor of iron stores in the proposed model. Finally, drawing upon known relations among variables and the amount of variance explained in path models, it is suggested that the following blood measures should be made in assessing community iron deficiency: (1) serum ferritin, (2) total iron-binding capacity, (3) serum iron, (4) transferrin saturation, and (5) hemoglobin concentration. These measures (with acceptable ranges and cut-off points) could make possible the complete evaluation of all three stages of iron deficiency in those persons surveyed at the community level. ^

Immune response to hepatitis B vaccination in drug using populations: A systematic review and meta-regression analysis

Hepatitis B virus (HBV) is a significant cause of liver diseases and related complications worldwide. Both injecting and non-injecting drug users are at increased risk of contracting HBV infection. Scientific evidence suggests that drug users have subnormal response to HBV vaccination and the seroprotection rates are lower than that in the general population; potentially due to vaccine factors, host factors, or both. The purpose of this systematic review is to examine the rates of seroprotection following HBV vaccination in drug using populations and to conduct a meta-analysis to identify the factors associated with varying seroprotection rates. Seroprotection is defined as developing an anti-HBs antibody level of ≥ 10 mIU/ml after receiving the HBV vaccine. Original research articles were searched using online databases and reference lists of shortlisted articles. HBV vaccine intervention studies reporting seroprotection rates in drug users and published in English language during or after 1989 were eligible. Out of 235 citations reviewed, 11 studies were included in this review. The reported seroprotection rates ranged from 54.5 – 97.1%. Combination vaccine (HAV and HBV) (Risk ratio 12.91, 95% CI 2.98-55.86, p = 0.003), measurement of anti-HBs with microparticle immunoassay (Risk ratio 3.46, 95% CI 1.11-10.81, p = 0.035) and anti-HBs antibody measurement at 2 months after the last HBV vaccine dose (RR 4.11, 95% CI 1.55-10.89, p = 0.009) were significantly associated with higher seroprotection rates. Although statistically nonsignificant, the variables mean age>30 years, higher prevalence of anti-HBc antibody and anti-HIV antibody in the sample population, and current drug use (not in drug rehabilitation treatment) were strongly associated with decreased seroprotection rates. Proportion of injecting drug users, vaccine dose and accelerated vaccine schedule were not predictors of heterogeneity across studies. Studies examined in this review were significantly heterogeneous (Q = 180.850, p = 0.000) and factors identified should be considered when comparing immune response across studies. The combination vaccine showed promising results; however, its effectiveness compared to standard HBV vaccine needs to be examined systematically. Immune response in DUs can possibly be improved by the use of bivalent vaccines, booster doses, and improving vaccine completion rates through integrated public programs and incentives.^

Lobe specific Ca2+-calmodulin nano-domain in neuronal spines: a single molecule level analysis.

Calmodulin (CaM) is a ubiquitous Ca(2+) buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca(2+)-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca(2+)-CaM-dependent enzymes: Ca(2+)/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca(2+) and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca(2+) ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca(2+) and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca(2+) signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca(2+)-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca(2+) channels, and to the microscopic injection rate of Ca(2+) ions. We also demonstrate that Ca(2+) saturation takes place via two different pathways depending on the Ca(2+) injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca(2+) sensors that can differentially transduce Ca(2+) influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca(2+)-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

A cladistic analysis of apolipoprotein B gene variation and plasma lipid and apolipoprotein B levels, using familial data

Any functionally important mutation is embedded in an evolutionary matrix of other mutations. Cladistic analysis, based on this, is a method of investigating gene effects using a haplotype phylogeny to define a set of tests which localize causal mutations to branches of the phylogeny. Previous implementations of cladistic analysis have not addressed the issue of analyzing data from related individuals, though in human studies, family data are usually needed to obtain unambiguous haplotypes. In this study, a method of cladistic analysis is described in which haplotype effects are parameterized in a linear model which accounts for familial correlations. The method was used to study the effect of apolipoprotein (Apo) B gene variation on total-, LDL-, and HDL-cholesterol, triglyceride, and Apo B levels in 121 French families. Five polymorphisms defined Apo B haplotypes: the signal peptide Insertion/deletion, Bsp 1286I, XbaI, MspI, and EcoRI. Eleven haplotypes were found, and a haplotype phylogeny was constructed and used to define a set of tests of haplotype effects on lipid and apo B levels.^ This new method of cladistic analysis, the parametric method, found significant effects for single haplotypes for all variables. For HDL-cholesterol, 3 clusters of evolutionarily-related haplotypes affecting levels were found. Haplotype effects accounted for about 10% of the genetic variance of triglyceride and HDL-cholesterol levels. The results of the parametric method were compared to those of a method of cladistic analysis based on permutational testing. The permutational method detected fewer haplotype effects, even when modified to account for correlations within families. Simulation studies exploring these differences found evidence of systematic errors in the permutational method due to the process by which haplotype groups were selected for testing.^ The applicability of cladistic analysis to human data was shown. The parametric method is suggested as an improvement over the permutational method. This study has identified candidate haplotypes for sequence comparisons in order to locate the functional mutations in the Apo B gene which may influence plasma lipid levels. ^

Dielectrophoresis-based analyte separation and analysis

Dielectrophoresis—the tendency of a material of high dielectric permittivity to migrate in an electrical field gradient to a region of maximum field strength—provides an ideal motive force for manipulating small volumes of biological analytes in microfluidic microsystems. The work described in this thesis was based on the hypothesis that dielectrophoresis could be exploited to provide high-resolution cell separations in microsystems as well as a means for the electrically-controllable manipulation of solid supports for molecular analysis. To this end, a dielectrophoretic/gravitational field-flow-fractionation (DEP/G-FFF) system was developed and the separation performance evaluated using various types and sizes of polystyrene microspheres as model particles. It was shown that separation of the polystyrene beads was based on the differences in their effective dielectrophoretic properties. The ability of an improved DEP/G-FFF system to separate genetically identical, but phenotypically dissimilar cell types was demonstrated using mixtures of 6m2 mutant rat kidney cells grown under transforming and non-transforming culture conditions. Additionally, a panel of engineered dielectric microspheres was designed with specific, predetermined dielectrophoretic properties such that their dielectrophoretic behaviors would be controllable and predictable. The fabrication method involved the use of gold-coated polystyrene microsphere cores coated with a self-assembled monolayer of alkanethiol and, optionally, a self-assembled monolayer of phospholipid to form a thin-insulating-shell-over-conductive-interior structure. The successful development of the DEP/G-FFF separation system and the dielectrically engineered microspheres provides proof-of-principle demonstrations of enabling dielectrophoresis-based microsystem technology that should provide powerful new methods for the manipulation, separation and identification of analytes in many diverse fields. ^

Analysis of Mycobacterium tuberculosis in the state of Texas for rifampin resistance using molecular beacons

Mycobacterium tuberculosis, a bacillus known to cause disease in humans since ancient times, is the etiological agent of tuberculosis (TB). The infection is primarily pulmonary, although other organs may also be affected. The prevalence of pulmonary TB disease in the US is highest along the US-Mexico border, and of the four US states bordering Mexico, Texas had the second highest percentage of cases of TB disease among Mexico-born individuals in 1999 (CDC, 2001). Between the years of 1993 and 1998, the prevalence of drug-resistant (DR) TB was 9.1% among Mexican-born individuals and 4.4% among US-born individuals (CDC, 2001). In the same time period, the prevalence of multi-drug resistant (MDR) TB was 1.4% among Mexican-born individuals and 0.6% among US-born individuals (CDC, 2001). There is a renewed urgency in the quest for faster and more effective screening, diagnosis, and treatment methods for TB due to the resurgence of tuberculosis in the US during the mid-1980s and early 1990s (CDC, 2007a), and the emergence of drug-resistant, multidrug-resistant, and extremely drug-resistant tuberculosis worldwide. Failure to identify DR and MDR-TB quickly leads to poorer treatment outcomes (CDC, 2007b). The recent rise in TB/HIV comorbidity further complicates TB control efforts. The gold standard for identification of DR-TB requires mycobacterial growth in culture, a technique taking up to three weeks, during which time DR/MDR-TB individuals harboring resistant organisms may be receiving inappropriate treatment. The goal of this study was to determine the sensitivity and specificity of real-time quantitative polymerase chain reaction (qPCR) using molecular beacons in the Texas population. qPCR using molecular beacons is a novel approach to detect mycobacterial mutations conferring drug resistance. This technique is time-efficient and has been shown to have high sensitivity and specificity in several populations worldwide. Rifampin (RIF) susceptibility was chosen as the test parameter because strains of M. tuberculosis which are resistant to RIF are likely to also be MDR. Due to its status as a point of entry for many immigrants into the US, control efforts against TB and drug-resistant TB in Texas is a vital component of prevention efforts in the US as a whole. We show that qPCR using molecular beacons has high sensitivity and specificity when compared with culture (94% and 87%, respectively) and DNA sequencing (90% and 96%, respectively). We also used receiver operator curve analysis to calculate cutoff values for the objective determination of results obtained by qPCR using molecular beacons. ^

A qualitative analysis of leadership styles and the selection of quality improvement in primary care practice

In the Practice Change Model, physicians act as key stakeholders, people who have both an investment in the practice and the capacity to influence how the practice performs. This leadership role is critical to the development and change of the practice. Leadership roles and effectiveness are an important factor in quality improvement in primary care practices.^ The study conducted involved a comparative case study analysis to identify leadership roles and the relationship between leadership roles and the number and type of quality improvement strategies adopted during a Practice Change Model-based intervention study. The research utilized secondary data from four primary care practices with various leadership styles. The practices are located in the San Antonio region and serve a large Hispanic population. The data was collected by two ABC Project Facilitators from each practice during a 12-month period including Key Informant Interviews (all staff members), MAP (Multi-method Assessment Process), and Practice Facilitation field notes. This data was used to evaluate leadership styles, management within the practice, and intervention tools that were implemented. The chief steps will be (1) to analyze if the leader-member relations contribute to the type of quality improvement strategy or strategies selected (2) to investigate if leader-position power contributes to the number of strategies selected and the type of strategy selected (3) and to explore whether the task structure varies across the four primary care practices.^ The research found that involving more members of the clinic staff in decision-making, building bridges between organizational staff and clinical staff, and task structure are all associated with the direct influence on the number and type of quality improvement strategies implemented in primary care practice.^ Although this research only investigated leadership styles of four different practices, it will offer future guidance on how to establish the priorities and implementation of quality improvement strategies that will have the greatest impact on patient care improvement. ^

Factors that affect non-adherence to first line antiretroviral medications among HIV infected children and adolescents in Botswana

The aims of the study were to determine the prevalence of and factors that affect non-adherence to first line antiretroviral (ARV) medications among HIV infected children and adolescents in Botswana. The study used secondary data from Botswana-Baylor Children's Clinical Center of Excellence for the period of June 2008 to February 10th, 2010. The study design was cross-sectional and case-comparison between non-adherent and adherent participants was used to examine the effects of socio-demographic and medication factors on non-adherence to ARV medications. A case was defined as non-adherent child with adherence level < 95% based on pill count and measurement of liquid formulations. The comparison group consisted of children with adherence levels ≥95%.^ A total of 842 participants met the eligibility criteria for determination of the prevalence of non-adherence and 338 participants (169 cases and 169 individuals) were used in the analysis to estimate the effects of factors on non-adherence. ^ Univariate and multivariable logistic regression were used to estimate the association between non-adherence (outcome) and socio-demographic and medication factors (exposures). The prevalence of non-adherence for participants on first line ARV medications was 20.0% (169/842).^ Increase in age (OR (95% CI): 1.10 (1.04–1.17) p = 0.001) was associated with nonadherence, while increase in number of caregivers (OR (95% CI): 0.72 (0.56–0.93) p = 0.01) and increase in number of monthly visits (OR (95% CI): 0.92 (0.86–0.99) p = 0.02), were associated with good adherence in both the unadjusted and the adjusted models. For the categorical variables, having more than two caregivers (OR (95% CI): 0.66 (0.28–0.84), p = 0.002) was associated with good adherence even in the adjusted model. ^ Conclusion. The prevalence of non-adherence to antiretroviral medicines among the study population was estimated to be 20.0%. In previous studies, adherence levels of ≥ 95% have been associated with better clinical outcomes and suppression of virus to prevent development of resistance. Older age, fewer numbers of caregivers and fewer monthly visits were associated with non-adherence. Strategies to improve and sustain adherence especially among older children are needed. The role of caregivers and social support should be investigated further.^

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.^

Secondary data analysis of lead screening compliance in high-risk children

Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^

AN ATTEMPT TO MEASURE FOOD SAFETY STATUS

The main objective of this study was to attempt to develop some indicators for measuring the food safety status of a country. A conceptual model was put forth by the investigator. The assumption was that food safety status was multifactorily influenced by medico-health levels, food-nutrition programs, and consumer protection activities. However, all these in turn depended upon socio-economic status of the country.^ Twenty-six indicators were reviewed and examined. Seventeen were first screened and three were finally selected, by the stepwise multiple regression analysis, to reflect the food safety status. Sixty-one countries/areas were included in this study.^ The three indicators were life expectancy at birth with multiple correlation coefficient (R2 = 34.62%), adult literacy rate (R2 = 29.66%), and child mortality rate for ages 1-4 (R2 = 9.99%). They showed a cumulative R2 of 57.79%. ^

Policy analysis of iron micronutrient programs at USAID: The FANTA program in East Africa and the micronutrient initiative in Bihar region of India, using comparative cost effective and cost benefit analysis

It is the aim of this paper to examine iron supplementation programs which receive funding from United States Agency for International Development (USAID) but approach combating iron deficiency anemia in two vastly different ways. A brief literature review and background information on iron deficiencies and the differences between supplementation programs and micronutrient fortification were reviewed. Two non-governmental organizations (NGO's) were examined for this paper: the Food and Nutrition Technical Assistance II (FANTA) and the MicroNutrient Initiative. The FANTA program included an educational component to their supplementation program while the MicroNutrient Initiative solely used supplementation of micronutrients to their population. Methods used were cost-benefit analysis and cost-effectiveness analysis to determine the overall effectiveness of each program in reducing iron deficiency anemia in each population, if the added costs of the incentives in the FANTA program changed the cost-effectiveness of the program compared to the MicroNutrient Initiative program and to determine which program imparted the greatest benefit to each population by reducing the disease burden in Disability Adjusted Life Years (DALY). Results showed that the unit cost of the FANTA program per person was higher than the MicroNutrient Initiative program due to the educational component. The FANTA program reduced iron deficiency anemia less overall but cost less for each percentage point of anemia decreased in their respective populations. The MicroNutrient Initiative program had a better benefit cost ratio for the populations it served. The MicroNutrient Initiative's large scale program imparted many advantages by reducing unit cost per person and decreasing iron deficiency anemia. The FANTA program was more effective at decreasing iron deficiency anemia with less money: $5,660 per 1% decrease in iron deficiency anemia versus $18,450 per 1% decrease in iron deficiency anemia for the MicroNutrient Initiative program. ^ In conclusion, economic analysis cannot measure all of the benefits associated with programs that contain an educational component or large scale supplementation. More information needs to be gathered by NGOs and reported to USAID, such as detailed prevalence rates of iron deficiency anemia among the populations served. Further research is needed to determine the effects an educational supplementation program has on compliance rates of participants and motivation to participate in supplementation programs whose aim is to decrease iron deficiency anemia in a targeted population.^

Pathway analysis of genome-wide association study data in primary biliary cirrhosisa

Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^