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Laboratory techniques to study the cellular and molecular processes of disorders
Published in Louis-Philippe Boulet, Applied Respiratory Pathophysiology, 2017
The advance of PCR with high throughput platforms played a tremendous role in realizing the Human Genome Project that documented the entire human genome sequence [24]. The project led to the identification and documentation of genetic variations. These variations in turn become landmarks on the map of the human genome and allow genetic studies to be carried out. Genotyping, the determination of the alleles present in an individual, becomes the aim of many genetic studies. In asthma research, genotyping enables linkage studies to detect chromosomal regions housing asthma or asthma-trait–related genes (e.g., 5q31–33, 6p21, 12q13–q24, and 17q12–q21) [25] and genetic association studies (both genome-wide or candidate genes) to identify asthma or as, thma-trait–related genes (e.g., ADAM33, ADRB2, CD14, GSTP1, HLA-DRB1, HLA-DQB1, IL4, IL4R, IL10, IL13, LTA, MS4A2, STAT6, and TNFA) (PMID:18301422). It can be insightful to group disease-associated genes into classes according to biological functions. For example, the grouping of 65 asthma-associated genes revealed that more than half of the genes (54%) have an immune response function and 18% of the genes are involved in tissue remodeling. Finally, 17 genes (28%) fall into the “other” category suggesting that diverse biological pathways are also involved in asthma pathogenesis (Figure 3.7) [26]. More research is needed to identify and understand how these biological pathways underlie asthma pathogenesis.
What is the gold standard model for Alzheimer’s disease drug discovery and development?
Published in Expert Opinion on Drug Discovery, 2021
Ramón Cacabelos, Iván Carrera, Olaia Martínez-Iglesias, Natalia Cacabelos, Vinogran Naidoo
Transgenic models are created to reproduce in the brain of different animals an overexpression of genes associated with the EOAD and LOAD phenotypes. Over 600 different genes distributed across the human genome are potentially involved in AD pathogenesis [1,24]. Some of these genes are primarily pathogenic (e.g. APP, PSEN1, PSEN2, MAPT, APOE) while others may confer vulnerability following a probabilistic golden rule in complex disorders: the larger the number of defective genes, the earlier the onset of the disease, the faster the clinical course and the poorer the response to conventional treatments [6,25]. In a recent meta-analysis, about 20 LOAD risk loci were confirmed (CR1, BIN1, INNPP5D, HLA-DRB1, TREM2, CD2AP, NYAP1g, EPHA1, PTK2B, CLU, SPI1h, MS4A2, PICALM, SORL1, FERMT2, SLC24A4, ABCA7, APOE, CASS4) [26] and 5 new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, WWOX) have been identified, together with the haplotype HLA-DR15 (HLA-DQA1*01:02/HLA-DQB1*06:02(HLA-DBR1*15:01) of the human leukocyte antigen (HLA) region [24]. Among the most relevant 24 signals, APOE, ABCA7, BIN1, TREMs, SORL1, ADAM10, SPI1 and CR1 are true AD risk genes, with potential multiple causative genes at a single genome-wide association study (GWAS) locus [27]. Excluding APOE, of the most important risk factors for AD, only 2% of 1,073 variants in 24 loci are exonic and 58% are intronic. Most genetic pathways implicate Aβ metabolism, Tau binding proteins, lipid metabolism, and the immune system [24].
Pharmacology mechanism of Flos magnoliae and Centipeda minima for treating allergic rhinitis based on pharmacology network
Published in Drug Development and Industrial Pharmacy, 2019
Yulin Liang, Xiaofei Zhang, Junbo Zou, Yajun Shi, Yu Wang, Jia Tai, Yanjun Yang, Xiao Zhou, Dongyan Guo, Jing Wang, Jiangxue Cheng, Ming Yang
The pink node represents the target of the disease, and the green represents the target protein of the CM component, component target proteins and disease targets consist of 416 nodes and 673 edges. Among them, 37 nodes and 135 edges directly reflect the interaction between the component target and disease target. The small circle in the middle represents a common target for component and disease, including MS4A2, CHRM3, PLAT, AHR, NR3C1, IL13, SPP1, PIK3CG, ICAM1, HIF1A, SERPINE1, IL2, IL1A, IL4, MMP9, CXCL8, IFNG, TGFB1, BCL2, IL1B, IL10, IL6, TNF, CHRM1, CHRM2, CHRM4, CHRM5, SLC6A4, SLC6A2, CYP1A2, PTGS1, SLC6A3, CYP3A4, PLA2G4A, PGR, NR3C2, ABCG2, and PTGS2 (Figure 2(B)).
A pilot study of differential gene expressions in patients with cough variant asthma and classic bronchial asthma
Published in Journal of Asthma, 2022
Guanghong Zhou, Qingcui Zeng, Wei Wei, Hong Teng, Chuntao Liu, Zhongwei Zhou, Binmiao Liang, Huaicong Long
The DEGs related to the signaling pathway described above included IL4, MS4A2, FCER1A, IL5RA and CLC. All of them were upregulated in the CVA group, but we only identified IL4 and FCER1A. In the future, we will continue to identify the other genes. The DEGs EGR1, G0S2, DEFA4, LTF, TFF3, CTSG and CAMP were not validated by real-time PCR, but we could not confirm that the difference among the seven genes was not statistically significant between the groups.