Mixture SNPs effect on phenotype in genome-wide association studies

© 2015 Wang et al.; licensee BioMed Central. Background: Recently mixed linear models are used to address the issue of "missing" heritability in traditional Genome-wide association studies (GWAS). The models assume that all single-nucleotide polymorphisms (SNPs) are associated with the phenotypes of interest. However, it is more common that only a small proportion of SNPs have significant effects on the phenotypes, while most SNPs have no or very small effects. To incorporate this feature, we propose an efficient Hierarchical Bayesian Model (HBM) that extends the existing mixed models to enforce automatic selection of significant SNPs. The HBM models the SNP effects using a mixture distribution of a point mass at zero and a normal distribution, where the point mass corresponds to those non-associative SNPs. Results: We estimate the HBM using Gibbs sampling. The estimation performance of our method is first demonstrated through two simulation studies. We make the simulation setups realistic by using parameters fitted on the Framingham Heart Study (FHS) data. The simulation studies show that our method can accurately estimate the proportion of SNPs associated with the simulated phenotype and identify these SNPs, as well as adapt to certain model mis-specification than the standard mixed models. In addition, we analyze data from the FHS and the Health and Retirement Study (HRS) to study the association between Body Mass Index (BMI) and SNPs on Chromosome 16, and replicate the identified genetic associations. The analysis of the FHS data identifies 0.3% SNPs on Chromosome 16 that affect BMI, including rs9939609 and rs9939973 on the FTO gene. These two SNPs are in strong linkage disequilibrium with rs1558902 (Rsq =0.901 for rs9939609 and Rsq =0.905 for rs9939973), which has been reported to be linked with obesity in previous GWAS. We then replicate the findings using the HRS data: the analysis finds 0.4% of SNPs associated with BMI on Chromosome 16. Furthermore, around 25% of the genes that are identified to be associated with BMI are common between the two studies. Conclusions: The results demonstrate that the HBM and the associated estimation algorithm offer a powerful tool for identifying significant genetic associations with phenotypes of interest, among a large number of SNPs that are common in modern genetics studies.published_or_final_versio

Genomic Assortative Mating in Marriages in the United States

Assortative mating in phenotype in human marriages has been widely observed. Using genome-wide genotype data from the Framingham Heart study (FHS; number of married couples = 989) and Health Retirement Survey (HRS; number of married couples = 3,474), this study investigates genomic assortative mating in human marriages. Two types of genomic marital correlations are calculated. The first is a correlation specific to a single married couple “averaged” over all available autosomal single-nucleotide polymorphism (SNPs). In FHS, the average married-couple correlation is 0.0018 with p = 3×10−5; in HRS, it is 0.0017 with p = 7.13×10−13. The marital correlation among the positively assorting SNPs is 0.001 (p = .0043) in FHS and 0.015 (p = 1.66×10−24) in HRS. The sizes of these estimates in FHS and HRS are consistent with what are suggested by the distribution of the allelic combination. The study also estimated SNP-specific correlation “averaged” over all married couples. Suggestive evidence is reported. Future studies need to consider a more general form of genomic assortment, in which different allelic forms in homologous genes and non-homologous genes result in the same phenotype

Design and Experiment of a Lifting Tool for Hoisting Offshore Single-Pile Foundations

Experiments with a cam-type clamp tool were carried out to overcome the difficulty of transporting and installing large-diameter mono-piles for offshore wind turbines. Using the experiments method to design a small wedge-type clamping mechanism and using cam teeth made of 40Cr material resulted in the maximum friction for the mechanism. A single clamping design was created for the cam-type clamp tool to hoist mono-piles for offshore wind turbines. Through force analysis and Automatic Dynamics Analysis of Mechanical System (ADAMS) dynamic simulation of the lifting tool, it was calculated that the clamping force of the lifting tool meets application requirements. A prototype was built in order to carry out an experiment in which the lifting tool hoisted a mono-pile. It was concluded from the experiment that the proposed design of the lifting tool is feasible in practical applications

Elastographic imaging of pancreatic cancer tumor microenvironment

Thesis (Ph. D.)--University of Rochester. Department of Electrical and Computer Engineering, 2019.Pancreatic ductal adenocarcinoma (PDAC) is a common and aggressive malignancy with a 5-year survival rate of less than 5%. Surgical resection with targeted neoadjuvant therapy remains the most effective treatment plan available. Despite extensive research, targeted therapies have made incremental improvement in efficacy for PDAC patients. The unique abnormal PDAC tumor microenvironment has been postulated to promote tumor growth and inhibit drug delivery. The role of the dense stroma contents and high interstitial pressure are under active investigation regarding their role in vascular compression. An imaging technique that can measure the tumor stroma stiffness would provide crucial information on how the tumor microenvironment changes during different therapies. Contrast agent-based computed tomography, and magnetic resonance imaging modalities are faced with contrast pooling and poor contrast delivery, also a result of the abnormal tumor microenvironment. The objective of this thesis is to establish shear modulus as a surrogate biomarker for tissue pressure in pancreatic tumors using ultrasound elastography including model-based iterative reconstruction schemes and shear wave elasticity imaging. To achieve this goal, the following objectives are to be satisfied: (1) establish the relationship between shear modulus and stromal components of the pancreatic cancer tumor microenvironment; (2) investigate how shear modulus impacts drug delivery and vascular patency in pancreatic tumors; (3) assess the effects of radiotherapy and immunotherapy on shear modulus and the underlying tissue components. The results of these studies showed that the shear modulus is an excellent surrogate imaging biomarker for tissue pressure in pancreatic tumors. We demonstrated through three animal studies that shear modulus is inversely related to drug delivery in pancreatic adenocarcinoma tumors. Shear modulus also changes in response to modifications in tumor stroma attributes due to emerging treatment regimens such as immunotherapy and stereotactic body radiation therapy

Research on Airflow distribution in Internet Data Center

With the rapid growth of IDC (Internet Data Center) construction, the energy consumption is also increasing gradually. It is extremely important to design a reasonable air distribution to reduce the energy consumption of IDC. The research object is an IDC Plant in Beijing. Airpak software is used to conduct DeST ( Building energy consumption analysis software) simulation of the air flow organization in IDC room. Under the same cooling load conditions, through the simulation of the three types of diffuse air supply, closed cold aisle and closed hot aisle in the IDC room, it is concluded that the air flow organization after the closed cold and hot aisle is excellent. The energy consumption analysis of the enclosure structure of the three air flow organizations of IDC room shows that the energy consumption of the closed cold aisle is lower than that of the closed hot aisle air-conditioning system

Equalized shape feature enhancement method for multiple ferromagnetic objects

When magnetic measuring instruments are used to measure the shape of ferromagnetic objects, the objects far away from the observation plane are likely to have blurred shape features because the magnetic field decays rapidly with distance. A bigger challenge is to measure multiple objects at the same time. When the relative positions of multiple measured objects and the observation plane are inappropriate, it is easy to have problems that the shape features of the deeper measured objects are not obvious and the magnetic signals of multiple measured objects are aliased, which usually leads to shape feature measurement failed. To address this issue, we propose an equalized shape feature enhancement method for multiple ferromagnetic objects. The method enhances shape features by evaluating the trends of the total horizontal derivative and vertical derivative of the magnetic field within the measurement area using the standard deviation. Meanwhile, the method combines the theory of ratio equalization and normalization to improve the shape features convergence of deeper objects and balance the signal aliasing interference between objects of different depths. Model simulation and experimental results show that the shape feature measurement results of the proposed method are clear and in good agreement with the ideal model. The method can effectively balance the magnetic anomaly amplitudes of the measured objects with different depths, and improve the accuracy and stability of shape feature measurement. We compare and analyze the processing effects of the proposed method and the traditional normalized standard deviation method (NSTD). It is calculated that the standard deviations of the results obtained by the proposed method and the NSTD method are 0.146 and 0.136, and the average peak-to-trough differences are 0.368 and 0.352, respectively. Therefore, the proposed method can better enhance the shape characteristics of ferromagnetic objects and has more practical application value

The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period

© 2015 Population Association of America In this analysis, guided by an evolutionary framework, we investigate how the human genome as a whole interacts with historical period, age, and physical activity to influence body mass index (BMI). The genomic influence is estimated by (1) heritability or the proportion of variance in BMI explained by genome-wide genotype data, and (2) the random effects or the best linear unbiased predictors (BLUPs) of genome-wide association studies (GWAS) data on BMI. Data were used from the Framingham Heart Study (FHS) in the United States. The study was initiated in 1948, and the obesity data were collected repeatedly over the subsequent decades. The analyses draw analysis samples from a pool of >8,000 individuals in the FHS. The hypothesis testing based on Pitman test, permutation Pitman test, F test, and permutation F test produces three sets of significant findings. First, the genomic influence on BMI is substantially larger after the mid-1980s than in the few decades before the mid-1980s within each age group of 21–40, 41–50, 51–60, and >60. Second, the genomic influence on BMI weakens as one ages across the life course, or the genomic influence on BMI tends to be more important during reproductive ages than after reproductive ages within each of the two historical periods. Third, within the age group of 21–50 and not in the age group of >50, the genomic influence on BMI among physically active individuals is substantially smaller than the influence on those who are not physically active. In summary, this study provides evidence that the influence of human genome as a whole on obesity depends on historical period, age, and level of physical activity.Link_to_subscribed_fulltex

FHS data – the empirical density distribution of couple correlation for married-couples (N = 989), opposite-sex random pairs from permuted individuals in FHS (N = 200,000), opposite-sex random pairs from permuted individuals among married couples (N = 246,870), parent-child pairs (N = 6,958), and full sibling pairs (N = 5,713), with each mixed-model regression estimating a within-a-single-pair correlation “averaged” over 287,294 SNPs.

<p>FHS data – the empirical density distribution of couple correlation for married-couples (N = 989), opposite-sex random pairs from permuted individuals in FHS (N = 200,000), opposite-sex random pairs from permuted individuals among married couples (N = 246,870), parent-child pairs (N = 6,958), and full sibling pairs (N = 5,713), with each mixed-model regression estimating a within-a-single-pair correlation “averaged” over 287,294 SNPs.</p

A Method for Detecting and Analyzing Facial Features of People with Drug Use Disorders

Drug use disorders caused by illicit drug use are significant contributors to the global burden of disease, and it is vital to conduct early detection of people with drug use disorders (PDUD). However, the primary care clinics and emergency departments lack simple and effective tools for screening PDUD. This study proposes a novel method to detect PDUD using facial images. Various experiments are designed to obtain the convolutional neural network (CNN) model by transfer learning based on a large-scale dataset (9870 images from PDUD and 19,567 images from GP (the general population)). Our results show that the model achieved 84.68%, 87.93%, and 83.01% in accuracy, sensitivity, and specificity in the dataset, respectively. To verify its effectiveness, the model is evaluated on external datasets based on real scenarios, and we found it still achieved high performance (accuracy &gt; 83.69%, specificity &gt; 90.10%, sensitivity &gt; 80.00%). Our results also show differences between PDUD and GP in different facial areas. Compared with GP, the facial features of PDUD were mainly concentrated in the left cheek, right cheek, and nose areas (p &lt; 0.001), which also reveals the potential relationship between mechanisms of drugs action and changes in facial tissues. This is the first study to apply the CNN model to screen PDUD in clinical practice and is also the first attempt to quantitatively analyze the facial features of PDUD. This model could be quickly integrated into the existing clinical workflow and medical care to provide capabilities