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1. Genome-wide association meta-analysis identifies 17 loci associated with nonalcoholic fatty liver disease

Author

Chen, Yanhua, Du, Xiaomeng, Kuppa, Annapurna, Feitosa, Mary F, Bielak, Lawrence F, O’Connell, Jeffrey R, Musani, Solomon K, Guo, Xiuqing, Kahali, Bratati, Chen, Vincent L, Smith, Albert V, Ryan, Kathleen A, Eirksdottir, Gudny, Allison, Matthew A, Bowden, Donald W, Budoff, Matthew J, Carr, John Jeffrey, Chen, Yii-Der I, Taylor, Kent D, Oliveri, Antonino, Correa, Adolfo, Crudup, Breland F, Kardia, Sharon LR, Mosley, Thomas H, Norris, Jill M, Terry, James G, Rotter, Jerome I, Wagenknecht, Lynne E, Halligan, Brian D, Young, Kendra A, Hokanson, John E, Washko, George R, Gudnason, Vilmundur, Province, Michael A, Peyser, Patricia A, Palmer, Nicholette D, and Speliotes, Elizabeth K

Subjects
Biochemistry and Cell Biology, Genetics, Biological Sciences, Human Genome, Hepatitis, Liver Disease, Chronic Liver Disease and Cirrhosis, Digestive Diseases, Prevention, 2.1 Biological and endogenous factors, Aetiology, Humans, Non-alcoholic Fatty Liver Disease, Genome-Wide Association Study, Liver Cirrhosis, Acyltransferases, Phospholipases, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Liver, Protein Serine-Threonine Kinases, Intracellular Signaling Peptides and Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Nonalcoholic fatty liver disease (NAFLD) is common and partially heritable and has no effective treatments. We carried out a genome-wide association study (GWAS) meta-analysis of imaging (n = 66,814) and diagnostic code (3,584 cases versus 621,081 controls) measured NAFLD across diverse ancestries. We identified NAFLD-associated variants at torsin family 1 member B (TOR1B), fat mass and obesity associated (FTO), cordon-bleu WH2 repeat protein like 1 (COBLL1)/growth factor receptor-bound protein 14 (GRB14), insulin receptor (INSR), sterol regulatory element-binding transcription factor 1 (SREBF1) and patatin-like phospholipase domain-containing protein 2 (PNPLA2), as well as validated NAFLD-associated variants at patatin-like phospholipase domain-containing protein 3 (PNPLA3), transmembrane 6 superfamily 2 (TM6SF2), apolipoprotein E (APOE), glucokinase regulator (GCKR), tribbles homolog 1 (TRIB1), glycerol-3-phosphate acyltransferase (GPAM), mitochondrial amidoxime-reducing component 1 (MARC1), microsomal triglyceride transfer protein large subunit (MTTP), alcohol dehydrogenase 1B (ADH1B), transmembrane channel like 4 (TMC4)/membrane-bound O-acyltransferase domain containing 7 (MBOAT7) and receptor-type tyrosine-protein phosphatase δ (PTPRD). Implicated genes highlight mitochondrial, cholesterol and de novo lipogenesis as causally contributing to NAFLD predisposition. Phenome-wide association study (PheWAS) analyses suggest at least seven subtypes of NAFLD. Individuals in the top 10% and 1% of genetic risk have a 2.5-fold to 6-fold increased risk of NAFLD, cirrhosis and hepatocellular carcinoma. These genetic variants identify subtypes of NAFLD, improve estimates of disease risk and can guide the development of targeted therapeutics.

Published
2023

16. Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer’s disease and myocardial infarction

Author

Palmer, Nicholette D, Kahali, Bratati, Kuppa, Annapurna, Chen, Yanhua, Du, Xiaomeng, Feitosa, Mary F, Bielak, Lawrence F, O’Connell, Jeffrey R, Musani, Solomon K, Guo, Xiuqing, Smith, Albert V, Ryan, Kathleen A, Eirksdottir, Gudny, Allison, Matthew A, Bowden, Donald W, Budoff, Matthew J, Carr, J Jeffrey, Chen, Yii-Der I, Taylor, Kent D, Correa, Adolfo, Crudup, Breland F, Halligan, Brian, Yang, Jian, Kardia, Sharon LR, Launer, Lenore J, Fu, Yi-Ping, Mosley, Thomas H, Norris, Jill M, Terry, James G, O’Donnell, Christopher J, Rotter, Jerome I, Wagenknecht, Lynne E, Gudnason, Vilmundur, Province, Michael A, Peyser, Patricia A, and Speliotes, Elizabeth K

Subjects
Biological Sciences, Genetics, Digestive Diseases, Brain Disorders, Prevention, Aging, Chronic Liver Disease and Cirrhosis, Obesity, Neurosciences, Alzheimer's Disease, Liver Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Neurodegenerative, Human Genome, Hepatitis, Dementia, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Alanine Transaminase, Alleles, Alzheimer Disease, Apolipoproteins E, Databases, Genetic, Exome, Gene Frequency, Genome-Wide Association Study, Humans, Liver, Liver Cirrhosis, Myocardial Infarction, Non-alcoholic Fatty Liver Disease, Phenotype, Polymorphism, Single Nucleotide, Prognosis, Risk Factors, Triglycerides, Medical and Health Sciences, Genetics & Heredity
Abstract

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P

Published
2021

24. Brassinosteroids Mediate Endogenous Phytohormone Metabolism to Alleviate High Temperature Injury at Panicle Initiation Stage in Rice

Author

Chen Yanhua, Wang Yaliang, Chen Huizhe, Xiang Jing, Zhang Yikai, Wang Zhigang, Zhu Defeng, and Zhang Yuping

Subjects
rice, high temperature, panicle initiation stage, phytohormone metabolism, physiological and biochemical indices, Plant culture, SB1-1110
Abstract

High temperatures cause physiological and biochemical changes and significantly affect young panicle development of rice (Oryza sativa L.). Brassinosteroids play important roles in enhancing crop stress resistance. In this study, we subjected rice cultivars Huanghuazhan (heat-resistant) and IR36 (heat-sensitive) to high temperature (HT, 40 ºC) or normal temperature (NT, 33 ºC) for 7 d at the panicle initiation stage, in conjunction with application of 24-epibrassinolide [EBR, a synthetic brassinolide (BR)] or brassinazole (BRZ, a BR biosynthesis inhibitor) at the beginning of the treatments. HT exacerbated spikelet degeneration and inhibited young panicle growth, which were partially prevented by EBR application, while BRZ application aggravated the reduction in spikelet number. HT decreased the contents of BR, active cytokinins (aCTK), active gibberellins (aGA) and indole-3-acetic acid (IAA), but increased the content of abscisic acid (ABA) in young panicles. The activities of key enzymes involved in sucrose hydrolysis, glycolysis and the tricarboxylic acid cycle in young panicles were decreased with the change of endogenous hormone levels under HT. In addition, the contents of H2O2 and malondialdehyde (MDA) were increased and the activities of antioxidant enzymes were decreased in young panicles. Exogenous application of EBR induced the expression of phytohormone biosynthesis-related genes and down-regulated the expression of phytohormone catabolism-related genes to increase the contents of endogenous BR, aCTK, aGA and ABA, thus promoting the decomposition and utilization of sucrose in young panicles, enhancing the activities of superoxide dismutase, catalase and peroxidase, and reducing the accumulation of H2O2 and MDA in young panicles, whereas application of BRZ had the opposite physiological effects. These results showed that brassinosteroids mediate endogenous phytohormone metabolism to alleviate HT injury at the panicle initiation stage in rice.

Published
2023
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27. A Multilayer Neural Network Merging Image Preprocessing and Pattern Recognition by Integrating Diffusion and Drift Memristors

Author

Tang, Zhiri, Zhu, Ruohua, Hu, Ruihan, Chen, Yanhua, Wu, Edmond Q., Wang, Hao, He, Jin, Huang, Qijun, and Chang, Sheng

Subjects
Computer Science - Emerging Technologies
Abstract

With the development of research on novel memristor model and device, neural networks by integrating various memristor models have become a hot research topic recently. However, state-of-the-art works still build such neural networks using drift memristor only. Furthermore, some other related works are only applied to a few individual applications including pattern recognition and edge detection. In this paper, a novel kind of multilayer neural network is proposed, in which diffusion and drift memristor models are applied to construct a system merging image preprocessing and pattern recognition. Specifically, the entire network consists of two diffusion memristive cellular layers for image preprocessing and one drift memristive feedforward layer for pattern recognition. Experimental results show that good recognition accuracy of noisy MNIST is obtained due to the fusion of image preprocessing and pattern recognition. Moreover, owing to high-efficiency in-memory computing and brief spiking encoding methods, high processing speed, high throughput, and few hardware resources of the entire network are achieved., Comment: Accepted by IEEE Transactions on Cognitive and Developmental Systems

Published
2019

28. Fully Memristive Spiking-Neuron Learning Framework and its Applications on Pattern Recognition and Edge Detection

Author

Tang, Zhiri, Chen, Yanhua, Ye, Shizhuo, Hu, Ruihan, Wang, Hao, He, Jin, Huang, Qijun, and Chang, Sheng

Subjects
Computer Science - Emerging Technologies
Abstract

Fully memristive spiking-neuron learning framework, which uses drift and diffusion memristor models as axon and dendrite respectively, becomes a hot topic recently with the development of memristor devices. Normally, some other devices like resistor or capacitor are still necessary on recent works of fully memristive learning framework. However, theoretically, one neuron needs axon and dendrite only, which makes technique process simpler and learning framework more similar to biologic brain. In this paper, a fully memristive spiking-neuron learning framework is introduced, in which a neuron structure is just built of one drift and one diffusion memristive models. To verify it merits, a feedforward neural network for pattern recognition and a cellular neural network for edge detection are designed. Experiment results show that compared to other memristive neural networks, our framework's the processing speed is much faster and the hardware resource is saved in pattern recognition due to its simple structure. Further due to the dynamic filtering function of diffusion memristor model in our learning framework, its peak signal noise ratio (PSNR) is much higher than traditional algorithms in edge detection., Comment: Accepted by Neurocomputing

Published
2019
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44. Modelling financial market based on econometric and complex network analysis

Author

Chen, Yanhua, Pantelous, Athanasios A., and Zuev, Konstantin M.

Subjects
620
Abstract

The complex network theory, especially, the economic and financial networks have offered a new approach that emphasizes the complexities and interdependencies in the financial market. In this thesis, I am interested in combining the complex network theory and econometric measures, namely, cointegration and error correction models (ECM) to reveal the internal connectedness structure of the financial market and their dynamic characteristics evolution over time. The initial Chapters 1–2 present an introduction, background knowledge as well as the methodology has been applied throughout the thesis. Chapters 3–5 introduce corresponding specific problems leading up to their solutions. Specifically, in Chapter 3, we examine the dynamic evolution of short-term correlation, long-term cointegration and ECM-based long-term Granger causality between each pair of US, UK, and Eurozone stock markets from 1980 to 2015 using the rolling-window technique. A comparative analysis of pairwise dynamic integration and causality of stock markets, measured in common and domestic currency terms, is conducted to evaluate comprehensively how exchange rate fluctuations affect the time-varying integration among the S&P 500, FTSE 100 and EURO STOXX 50 indices. Chapter 4 seeks to incorporate the long-run cointegration and short-run error correction mechanisms to build up the financial networks to quantify the connectedness across 46 stock markets worldwide from January 2007 to June 2017. By constructing the static ECM-based global stock market network, the topological structure reflects the regional integrated and segmented stock markets. The dynamic international stock market further reveals the time-varying properties of both error correction effects and long-run equilibrium relations amongst 46 stock markets during periods of financial turmoil and implementation of the QEs in the Fed, BoE, BoJ, and ECB, respectively. In Chapter 5, we analyze the financial effects of Brexit-vote on the stocks traded on the London Stock Exchange (FTSE 100 and FTSE Mid250 Index). Specifically, we construct corresponding British stock networks using the ECM models to investigate the short-run self-correction mechanisms as well as long-run equilibrium amongst stocks from sectoral-level before and after the Brexit-vote. To extract most strongly related interactions from the British stock networks, the minimal spanning tree (MST) and hierarchical clustering analysis are applied for filtering network and to detect the taxonomy and hierarchical topological structure based our proposed Jaccard distance metric. Each chapter is followed by a mini-conclusion. In the end, we summarize our results and conclude the thesis by presenting some research directions based on our findings in Chapter 6.

Published
2018
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45. Phosphorus Distribution within Aggregates in Long-Term Fertilized Black Soil: Regulatory Mechanisms of Soil Organic Matter and pH as Key Impact Factors.

Author

Zhang, Naiyu, Wang, Qiong, Chen, Yanhua, Zhang, Shuxiang, Zhang, Xianmei, Feng, Gu, Gao, Hongjun, Peng, Chang, and Zhu, Ping

Subjects
BLACK cotton soil, SOIL structure, ORGANIC compounds, PHOSPHORUS in soils, SOIL acidity, POTASSIUM
Abstract

Understanding soil phosphorus (P) distribution and its key drivers is fundamental for sustainable P management. In this study, a 21-year fertilization experiment on black soil was carried out, setting up five fertilization treatments: unfertilized control (CK), nitrogen and potassium (NK), nitrogen, P and potassium (NPK), NPK plus straw (NPKS), and NPK plus manure (NPKM). The distribution and effecting factors of P pools within soil aggregates were investigated. Compared to CK, the NK and NPK treatments decreased calcium-associated P concentration in all aggregate fractions. Meanwhile, the NPK treatment significantly increased the organic P extracted from NaOH in unaggregated particles (<0.053 mm). This was mainly due to the reduction in soil pH. The NPKS and NPKM treatments increased almost all P forms in aggregates, especially Ca-P. For the NPKM treatment, inorganic P extracted from resin, NaHCO3, and NaOH increased as aggregate size increased. This was mainly because straw or manure addition promoted soil organic carbon (SOC) storage in aggregates, creating more sorption sites via association with amorphous metallic minerals, and, thus, facilitating P accumulation. In conclusion, decreasing soil pH by chemical fertilizers is an effective strategy for mobilizing soil P, whereas increasing SOC by straw or manure facilitates P accumulation. [ABSTRACT FROM AUTHOR]

Published
2024
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