Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

Regional comparisons of nano-mechanical properties of the human meniscus; structure and function

Osteoarthritis (OA) is a debilitating disease that is becoming more prevalent in today’s society. OA affects approximately 28 million adults in the United States alone and when present in the knee joint, usually leads to a total knee replacement. Numerous studies have been conducted to determine possible methods to halt the initiation of OA, but the structural integrity of the menisci has been shown have a direct effect on the progression of OA. Menisci are two C-shaped structures that are attached to the tibial plateau and aid in facilitating proper load transmission within the knee. The meniscal cross-section is wedge-like to fit the contour of the femoral condyles and help attenuate stresses on the tibial plateau. While meniscal tears are common, only the outer 1/3 of the meniscus is vascularized and has the capacity to heal, hence tears of the inner 2/3rds are generally treated via meniscectomy, leading to OA. To help combat this OA epidemic, an effective biomimetric meniscal replacement is needed. Numerous mechanical and biochemical studies have been conducted on the human meniscus, but very little is known about the mechanical properties on the nano-scale and how meniscal constituents are distributed in the meniscal cross-section. The regional (anterior, central and posterior) nano-mechanical properties of the meniscal superficial layers (both tibial and femoral contacting) and meniscal deep zone were investigated via nanoindentation to examine the regional inhomogeneity of both the lateral and medial menisci. Additionally, these results were compared to quantitative histological values to better formulate a structure-function relationship on the nano-scale. These data will prove imperative for further advancements of a tissue engineered meniscal replacement.

Human and embodied energy analysis applied to water source protection and household water treatment interventions used in Mali, West Africa

As water quality interventions are scaled up to meet the Millennium Development Goal of halving the proportion of the population without access to safe drinking water by 2015 there has been much discussion on the merits of household- and source-level interventions. This study furthers the discussion by examining specific interventions through the use of embodied human and material energy. Embodied energy quantifies the total energy required to produce and use an intervention, including all upstream energy transactions. This model uses material quantities and prices to calculate embodied energy using national economic input/output-based models from China, the United States and Mali. Embodied energy is a measure of aggregate environmental impacts of the interventions. Human energy quantifies the caloric expenditure associated with the installation and operation of an intervention is calculated using the physical activity ratios (PARs) and basal metabolic rates (BMRs). Human energy is a measure of aggregate social impacts of an intervention. A total of four household treatment interventions – biosand filtration, chlorination, ceramic filtration and boiling – and four water source-level interventions – an improved well, a rope pump, a hand pump and a solar pump – are evaluated in the context of Mali, West Africa. Source-level interventions slightly out-perform household-level interventions in terms of having less total embodied energy. Human energy, typically assumed to be a negligible portion of total embodied energy, is shown to be significant to all eight interventions, and contributing over half of total embodied energy in four of the interventions. Traditional gender roles in Mali dictate the types of work performed by men and women. When the human energy is disaggregated by gender, it is seen that women perform over 99% of the work associated with seven of the eight interventions. This has profound implications for gender equality in the context of water quality interventions, and may justify investment in interventions that reduce human energy burdens.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

Finite element study on fracture patterns in human scaphoid wrist bone due to free fall

Scaphoid is one of the 8 carpal bones found adjacent to the thumb supported proximally by Radius bone. During the free fall, on outstretched hand, the impact load gets transferred to the scaphoid at its free anterior end. Unique arrangement of other carpal bones in the palm is also one of the reasons for the load to get transferred to scaphoid. About half of the total load acting upon carpal bone gets transferred to scaphoid at its distal pole. There are about 10 to 12 clinically observed fracture pattern in the scaphoid due to free fall. The aim of the study is to determine the orientation of the load, magnitude of the load and the corresponding fracture pattern. This study includes both static and dynamic finite element models validated by experiments. The scaphoid model has been prepared from CT scans of a 27 year old person. The 2D slices of the CT scans have been converted to 3D model by using MIMICS software. There are four cases of loading studied which are considered to occur clinically more frequently. In case (i) the load is applied at the posterior end at distal pole whereas in case (ii), (iii) and (iv), the load is applied at anterior end at different directions. The model is given a fixed boundary condition at the region which is supported by Radius bone during the impact. Same loading and boundary conditions have been used in both static and dynamic explicit finite element analysis. The site of fracture initiation and path of fracture propagation have been identified by using max principal stress / gradient and max principal strain / gradient criterion respectively in static and dynamic explicit finite element analysis. Static and dynamic impact experiments were performed on the polyurethane foam specimens to validate the finite element results. Experimental results such as load at fracture, site of fracture initiation and path of fracture propagation have been compared with the results of finite element analysis. Four different types of fracture patterns observed in clinical studies have been identified in this study.

Volcanic processes and human exposure as elements to build a risk model for Volcan de Fuego, Guatemala

The activity of Fuego volcano during the 1999 - 2013 eruptive episode is studied through field, remote sensing and observatory records. Mapping of the deposits allows quantifying the erupted volumes and areas affected by the largest eruptions during this period. A wide range of volcanic processes results in a diversity of products and associated deposits, including minor airfall tephra, rockfall avalanches, lava flows, and pyroclastic flows. The activity can be characterized by long term, low level background activity, and sporadic larger explosive eruptions. Although the background activity erupts lava and ash at a low rate (~ 0.1 m3/s), the persistence of such activity over time results in a significant contribution (~ 30%) to the eruption budget during the studied period. Larger eruptions produced the majority of the volume of products during the studied period, mainly during three large events (May 21, 1999, June 29, 2003, and September 13, 2012), mostly in the form of pyroclastic flows. A total volume of ~ 1.4 x 108 m3 was estimated from the mapped deposits and the estimated background eruption rate. Posterior remobilization of pyroclastic flow material by stream erosion in the highly confined Barranca channels leads to lahar generation, either by normal rainfall, or by extreme rainfall events. A reassessment of the types of products and volumes erupted during the decade of 1970's allows comparing the activity happening since 1999 with the older activity, and suggests that many of the eruptive phenomena at Fuego may have similar mechanisms, despite the differences in scale between. The deposits of large pyroclastic flows erupted during the 1970's are remarkably similar in appearance to the deposit of pyroclastic flows from the 1999 - 2013 period, despite their much larger volume; this is also the case for prehistoric eruptions. Radiocarbon dating of pyroclastic flow deposits suggests that Fuego has produced large eruptions many times during the last ~ 2 ka, including larger eruptions during the last 500 years, which has important hazard implications. A survey was conducted among the local residents living near to the volcano, about their expectations of possible future crises. The results show that people are aware of the risk they could face in case of a large eruption, and therefore they are willing to evacuate in such case. However, their decision to evacuate may also be influenced by the conditions in which the evacuation could take place. If the evacuation represents a potential loss of their livelihood or property they will be more hesitant to leave their villages during a large eruption. The prospect of facing hardship conditions during the evacuation and in the shelters may further cause reluctance to evacuate. A short discussion on some of the issues regarding risk assessment and management through an early warning system is presented in the last chapter.

INNOVATIVE HUMAN-COMPUTER INTERACTIONS TO SUPPORT COGNITIVE COLLABORATIVE GEOSPATIAL ENVIRONMENTS

In the current world geospatial information is being demanded in almost real time, which requires the speed at which this data is processed and made available to the user to be at an all-time high. In order to keep up with this ever increasing speed, analysts must find ways to increase their productivity. At the same time the demand for new analysts is high, and current methods of training are long and can be costly. Through the use of human computer interactions and basic networking systems, this paper explores new ways to increase efficiency in data processing and analyst training.

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.