Category Archives: Transhuman News

Introduction

Coronary artery disease (CAD) is the major cause of death throughout the world.1 As reported by GBD 2017 Causes of Death Collaborators, the estimated years of life lost (YLLs) increased for CAD (ranked first in 2017).2 During the past decade, a marked rising trend of atherosclerosis-related burden (especially for CAD) in Eastern Asia was observed.3 Although endothelial dysfunction contributes essentially to the atherosclerosis, the molecular pathways underlying disease occurrence are not fully understood.

MicroRNAs (miRNAs) play important roles in the pathophysiology of cardiovascular diseases through the posttranscriptional control of gene networks.4,5 Among them, miR-217 was reported to aggravate atherosclerosis and promote cardiovascular dysfunction through downregulating a network of endothelial NO synthase (eNOS) activators, including vascular endothelial growth factor (VEGF).6 VEGF, a signal protein stimulating the formation of blood vessels, acted as a potential biomarker to predict the occurrence of CAD, and increased VEGF level was associated with poor coronary collateralization in patients with stable CAD.7 Besides, inhibition of miR-217 could protect against myocardial ischemia-reperfusion injury through inactivating NF-kappaB and MAPK pathways by targeting DUSP14.8 These findings highlighted a potential role of miR-217 in pathogenesis of CAD. Whether genetic variants of the miR-217 gene contributed to the occurrence of CAD was still undetermined and worthy to be explored. Thus, we aimed to conduct a casecontrol study among Chinese population to evaluate the associations of genetic variants of the miR-217 gene with CAD risk, as well as plasma level of VEGF.

In the current casecontrol study, we totally recruited 498 CAD patients and 499 healthy controls (frequency-matched by age, gender, and living areas). CAD diagnosis of any major coronary artery with diameter stenosis of more than 50%, or previous angioplasty, coronary bypass surgery, or myocardial infarction (MI) history verified by electrocardiogram (ECG) changes was evaluated by two cardiologists.9 This study has been approved by the institute committee of Jinan peoples Hospital. All participants in the study received informed consent and followed the guidelines set out in the Helsinki declaration.

Fasting venous blood was collected into plasma tubes containing 0.1% ethylenediaminetetraacetic acid (EDTA) and stored at 80C prior to analysis. Total RNAs were isolated using the miRNeasy kit (Qiagen) according to the manufacturers protocol. TaqMan miRNA assay kits (Applied Biosystems) were used for miRNA amplification, and real-time polymerase chain reaction (RT-PCR) was performed to detect miR-217, while cel-miRNA-39 was added as a spike-in control. Plasma VEGF level among the healthy controls was determined by multiplex analysis using Bioplex suspension arrays (Bio-Rad, Veenendaal, The Netherlands) according to the manufacturers specifications. All samples were thawed only once and measured three times.

TagSNPs were selected among the 1kb flanking region of the miR-217 gene according to 1000 genome CHB data (phase 3, minor allele frequency 5%, pairwise r20.8) using the Haploview 4.2 software.10 Finally, four tagSNPs, including rs6724872, rs4999828, rs10206823, and rs41291177, were determined. Genomic DNA was extracted from peripheral blood samples using QIAamp DNA blood Mini Kit (Qiagen, Hilden, Germany). Genotyping was performed by TaqMan analysis (Applied Biosystems [ABI], Foster City, CA) according to the manufacturers instructions. A randomly selected group of 10% of the samples was tested twice by different individuals with 100% concordance of results.

Statistical analyses were carried out using IBM SPSS Statistics version 22.0, while two-tailed P-values <0.05 were considered significant. All the demographic data were presented as proportions. Deviation of candidate SNPs from Hardy-Weinberg equilibrium in the control group was assessed by the goodness-of-fit 2 test. Allele frequencies and demographic variables between the two groups were assessed with chi-square tests. Odds ratios (ORs), 95% confidence levels (CIs), and corresponding P values were calculated for each SNP using logistic regression analysis, adjusted for age, gender, smoking status, drinking status, diabetes, and hypertension.

Table 1 lists the comparison of clinical features between 498 CAD cases and 499 controls. The results showed that there was no significant difference in age, gender, drinking status, diabetes and hypertension (P > 0.05). However, compared with the control group, the patients have higher percentage of smokers (controls vs cases: 26.7% vs 42.4%; P < 0.001).

Table 1 Clinical Characteristics of CAD Cases and Controls

We first evaluated the association between plasma level of miR-217 and CAD risk to validate the role of miR-217 in CAD development. As shown in Figure 1, plasma level of miR-217 was analyzed in 50 randomly selected patients with CAD and controls. We found plasma level of miR-217 in CAD cases was significantly higher than that in controls (P < 0.001).

Figure 1 Plasma level of miR-217 and CAD risk. Plasma level of miR-217 was analyzed in 50 randomly selected patients with CAD and controls, and plasma level of miR-217 in CAD cases was significantly higher than that in controls (P < 0.001).

As shown in Table 2, all four tagSNPs (rs6724872, rs4999828, rs10206823, and rs41291177) were in Hardy-Weinberg equilibrium in healthy controls, which indicated that the sampled subjects were representative of the population without any deviation of genotype frequencies (P>0.05). Of the four tagSNPs in the miR-217 gene region, rs6724872 and rs4999828 were significantly associated with increased risk of CAD (P value was smaller than 0.05 even after Bonferroni multiple adjustment). Compared with the G allele, C allele of rs6724872 was significantly associated with 1.73-fold increased risk of CAD (95% CI: 1.252.39; P=0.001). While C allele of rs4999828 was significantly associated with 1.75-fold increased risk of CAD, compared with T allele (95% CI: 1.342.29; P=4105).

Table 2 Associations Between Genetic Variations and Risk of CAD

To further evaluate the influence of susceptibility SNPs upon plasma level of VEGF, we compared the VEGF level among healthy controls with different genotypes of rs6724872 and rs4999828. As shown in Figure 2, with the increase in number of minor alleles, the plasma level of VEGF increased significantly for both rs6724872 and rs4999828 (P < 0.001). This means rs6724872 and rs4999828 were significantly associated with higher level of VEGF.

Figure 2 Circulating level of VEGF in subjects with different miR-217 genotypes. Plasma VEGF level among the healthy controls were determined by multiplex analysis using Bioplex suspension arrays. With the increasement of number of minor alleles, the plasma level of VEGF increased significantly for both rs6724872 and rs4999828 (P < 0.001).

Coronary heart disease is a common and frequent disease, which brings serious trouble to peoples quality of life.2,11 The exploration of the etiology of CAD is a complex and systematic project, and researchers have explored multiple aspects and perspectives.12,13 The current study explored associations between the associations of genetic variants of the miR-217 gene with CAD risk, as well as plasma level of VEGF, using a casecontrol study design. We found plasma level of miR-217, rs6724872 and rs4999828 were significantly associated with increased risk of CAD, as well as higher level of VEGF. These findings highlighted the important role of miR-217 in the pathogenesis of CAD and potential targets for intervention.

MiRNAs are implicated in the regulation of proliferation and apoptosis of endothelial cells, induction of immune responses and different stages of plaque formation, which finally results atherosclerosis and CAD.5,14,15 A previous meta-analysis identified that a total of 48 dysregulated miRNAs were confirmed for their role in CAD development, while MiR-122-5p and miR-133a-3p may be valuable biomarkers for CAD.16 Another two studies confirmed that predictive value of miRNA-21 and miRNA-126 on coronary restenosis after percutaneous coronary intervention (PCI) in patients with CAD.17,18 Previously, miR-217 was most studied in the field of cancer biology.1923 Zhao et al reported that downregulated miR-217 could regulate KRAS and function as a tumor suppressor in pancreatic ductal adenocarcinoma (PDAC).19 Further, Menghini et al pinpointed miR-217 as an endogenous inhibitor of SirT1 was potentially amenable to the prevention of endothelial dysfunction.24 Recently, Yebenes then reported that miR-217 could aggravate atherosclerosis and promote cardiovascular dysfunction.6 Taking the findings above together, it is important to extensively explore the role of miR-217 in the pathogenesis of CAD and to investigate the association of its genetic variants with the risk of disease development.

Genetic variants in miRNAs have been widely explored for their functions among pathophysiological mechanism of cardiovascular diseases, and offer new insight into the causal role of microRNAs in CAD.2531 Glinsky et al revealed identifies a consensus disease phenocode through a SNP-guided microRNA map of fifteen common human disorders.31 Ghanbari et al systematically evaluated 230 variants located within miRNA-binding sites in the 3-untranslated region of 155 cardiometabolic genes, and 37 were functional in their corresponding genomic loci.28 In the current study, rs6724872 and rs4999828 were significantly associated with increased risk of CAD, as well as higher level of VEGF, which means the important role in CAD development. Using RegulomeDB 2.0, we found both rs6724872 and rs4999828 were located in the TF binding and DNase peak region.32 The findings of HaploReg v4.1 also validated their functions in gene regulation.33

Conclusively, We found rs6724872 and rs4999828 were significantly associated with increased risk of CAD, as well as higher level of VEGF. Although these findings need further validation in larger cohorts for definitive results, they reveal new mechanisms by which genetic variations in miR-217 gene may coordinate the development of CAD. The gathered evidence could be further exploited in prevention strategies or screening protocols for CAD.

This study was supported by medical and health science and technology development planning project of Shandong Province (No. 202003011008) and the second batch of science and technology projects of Jinan Health Committee (2020-03-55).

The authors declare that they have no conflict of interest.

1. Hata J, Kiyohara Y. Epidemiology of stroke and coronary artery disease in Asia. Circ J. 2013;77(8):19231932. doi:10.1253/circj.CJ-13-0786

2. Collaborators GBDCoD. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 19802017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):17361788.

3. Wong MC, Zhang DX, Wang HH. Rapid emergence of atherosclerosis in Asia: a systematic review of coronary atherosclerotic heart disease epidemiology and implications for prevention and control strategies. Curr Opin Lipidol. 2015;26(4):257269. doi:10.1097/MOL.0000000000000191

4. Widmer RJ, Lerman LO, Lerman A. MicroRNAs: small molecule, big potential for coronary artery disease. Eur Heart J. 2016;37(22):17501752. doi:10.1093/eurheartj/ehw067

5. Ghafouri-Fard S, Gholipour M, Taheri M. Role of MicroRNAs in the pathogenesis of coronary artery disease. Front Cardiovasc Med. 2021;8:632392. doi:10.3389/fcvm.2021.632392

6. de Yebenes VG, Briones AM, Martos-Folgado I, et al. Aging-associated miR-217 aggravates atherosclerosis and promotes cardiovascular dysfunction. Arterioscler Thromb Vasc Biol. 2020;40(10):24082424. doi:10.1161/ATVBAHA.120.314333

7. Sun Z, Shen Y, Lu L, et al. Increased serum level of soluble vascular endothelial growth factor receptor-1 is associated with poor coronary collateralization in patients with stable coronary artery disease. Circ J. 2014;78(5):11911196. doi:10.1253/circj.CJ-13-1143

8. Li Y, Fei L, Wang J, Niu Q. Inhibition of miR-217 protects against myocardial ischemia-reperfusion injury through inactivating NF-kappaB and MAPK pathways. Cardiovasc Eng Technol. 2020;11(2):219227. doi:10.1007/s13239-019-00452-z

9. Li J, Zhang Y, Guo X, Wu Y, Huang R, Han X. Circulating level of monocyte chemoattractant protein-1 and risk of coronary artery disease: a case-control and Mendelian randomization study. Pharmgenomics Pers Med. 2021;14:553559.

10. Barrett JC. Haploview: visualization and analysis of SNP genotype data. Cold Spring Harb Protoc. 2009;2009(10):pdbip71. doi:10.1101/pdb.ip71

11. Benjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and stroke statistics-2017 update: a report from the American Heart Association. Circulation. 2017;135(10):e146e603.

12. Manfrini O, Yoon J, van der Schaar M, et al. Sex differences in modifiable risk factors and severity of coronary artery disease. J Am Heart Assoc. 2020;9(19):e017235. doi:10.1161/JAHA.120.017235

13. Lonnebakken MT. Cardiometabolic risk factors and coronary artery disease in women. J Womens Health (Larchmt). 2020;29(12):14891490. doi:10.1089/jwh.2020.8755

14. Sanlialp M, Dodurga Y, Uludag B, et al. Peripheral blood mononuclear cell microRNAs in coronary artery disease. J Cell Biochem. 2020;121(4):30053009. doi:10.1002/jcb.29557

15. Zhang X, Cai H, Zhu M, Qian Y, Lin S, Li X. Circulating microRNAs as biomarkers for severe coronary artery disease. Medicine (Baltimore). 2020;99(17):e19971. doi:10.1097/MD.0000000000019971

16. Wang -S-S, Wu L-J, Li -J-J-H, Xiao H-B, He Y, Yan Y-X. A meta-analysis of dysregulated miRNAs in coronary heart disease. Life Sci. 2018;215:170181. doi:10.1016/j.lfs.2018.11.016

17. Dai H, Wang J, Shi Z, Ji X, Huang Y, Zhou R. Predictive value of miRNA-21 on coronary restenosis after percutaneous coronary intervention in patients with coronary heart disease: a protocol for systematic review and meta-analysis. Medicine (Baltimore). 2021;100(10):e24966. doi:10.1097/MD.0000000000024966

18. Qiu X, Wang J, Shi Z, Ji X, Huang Y, Dai H. Predictive value of miRNA-126 on in-stent restenosis in patients with coronary heart disease: a protocol for meta-analysis and bioinformatics analysis. Medicine (Baltimore). 2021;100(22):e25887. doi:10.1097/MD.0000000000025887

19. Zhao WG, Yu SN, Lu ZH, Ma YH, Gu YM, Chen J. The miR-217 microRNA functions as a potential tumor suppressor in pancreatic ductal adenocarcinoma by targeting KRAS. Carcinogenesis. 2010;31(10):17261733. doi:10.1093/carcin/bgq160

20. Deng S, Zhu S, Wang B, et al. Chronic pancreatitis and pancreatic cancer demonstrate active epithelial-mesenchymal transition profile, regulated by miR-217-SIRT1 pathway. Cancer Lett. 2014;355(2):184191. doi:10.1016/j.canlet.2014.08.007

21. Nishioka C, Ikezoe T, Yang J, Nobumoto A, Tsuda M, Yokoyama A. Downregulation of miR-217 correlates with resistance of Ph(+) leukemia cells to ABL tyrosine kinase inhibitors. Cancer Sci. 2014;105(3):297307. doi:10.1111/cas.12339

22. Popov A, Szabo A, Mandys V. Small nucleolar RNA U91 is a new internal control for accurate microRNAs quantification in pancreatic cancer. BMC Cancer. 2015;15:774. doi:10.1186/s12885-015-1785-9

23. Xi S, Inchauste S, Guo H, et al. Cigarette smoke mediates epigenetic repression of miR-217 during esophageal adenocarcinogenesis. Oncogene. 2015;34(44):55485559. doi:10.1038/onc.2015.10

24. Menghini R, Casagrande V, Cardellini M, et al. MicroRNA 217 modulates endothelial cell senescence via silent information regulator 1. Circulation. 2009;120(15):15241532. doi:10.1161/CIRCULATIONAHA.109.864629

25. Borghini A, Andreassi MG. Genetic polymorphisms offer insight into the causal role of microRNA in coronary artery disease. Atherosclerosis. 2018;269:6370. doi:10.1016/j.atherosclerosis.2017.12.022

26. Joehanes R, Zhang X, Huan T, et al. Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies. Genome Biol. 2017;18(1):16. doi:10.1186/s13059-016-1142-6

27. Kaudewitz D, Skroblin P, Bender LH, et al. Association of MicroRNAs and YRNAs with platelet function. Circ Res. 2016;118(3):420432. doi:10.1161/CIRCRESAHA.114.305663

28. Ghanbari M, Franco OH, de Looper HW, Hofman A, Erkeland SJ, Dehghan A. Genetic variations in MicroRNA-binding sites affect MicroRNA-mediated regulation of several genes associated with cardio-metabolic phenotypes. Circ Cardiovasc Genet. 2015;8(3):473486. doi:10.1161/CIRCGENETICS.114.000968

29. Li L, He M, Zhou L, et al. A solute carrier family 22 member 3 variant rs3088442 G>A associated with coronary heart disease inhibits lipopolysaccharide-induced inflammatory response. J Biol Chem. 2015;290(9):53285340. doi:10.1074/jbc.M114.584953

30. Miller CL, Haas U, Diaz R, et al. Coronary heart disease-associated variation in TCF21 disrupts a miR-224 binding site and miRNA-mediated regulation. PLoS Genet. 2014;10(3):e1004263. doi:10.1371/journal.pgen.1004263

31. Glinsky GV. An SNP-guided microRNA map of fifteen common human disorders identifies a consensus disease phenocode aiming at principal components of the nuclear import pathway. Cell Cycle. 2008;7(16):25702583. doi:10.4161/cc.7.16.6524

32. Boyle AP, Hong EL, Hariharan M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22(9):17901797. doi:10.1101/gr.137323.112

33. Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40(Databaseissue):D930934. doi:10.1093/nar/gkr917

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Association of Genetic Variants in miR-217 Gene with Risk of Coronary | PGPM - Dove Medical Press

How often do we look for medicines that are commonly used to treat a particular disease? What if we looked for medicines to treat a particular individual instead? Transitioning from the current one-cure-fits-all treatment model to a holistic approach that tailors the medical interventions to a particular individual is what precision medicine is all about.

At the launch of the US Precision Medicine Initiative in 2015, Barack Obama had said, You can match a blood transfusion to a blood type that was an important discovery. What if matching a cancer cure to our genetic code was just as easy, just as standard? Personalised treatments benefit health by avoiding wrong treatment and reducing the financial burden for those who cant afford it. With an almost 72 million rare disease population in India, the right therapy or preventing the occurrence itself will go a long way to reduce the countrys health burden.

The Human Genome Project started in 1990. Sequencing the human genome for the first time took 13 years, costing about $3 billion. Since then, sequencing technologies have undergone revolutionary changes, from sequencing one gene to a panel of genes by next-generation sequencing (NGS). The speed and cost-efficiency of sequencing a whole human genome, a major driver of precision medicine, has improved manifold from $10,000 in 2011 to about $1,000 today.

Cancer, largely a genetic disease, has been the first and most widely studied disease area in precision medicine, where diagnostics serves not as a one-time tool, but rather an ongoing process to assess the biology of the tumour as it changes and evolves. About 5-10% of all cancers are hereditary and occur due to inheritance of a genetic variation, mutation within families.

In 2018, World Health Organisation (WHO) projected that 1 in 10 Indians will develop cancer during their lifetime, and 1 in 15 will die of the disease. Identifying genetic predispositions can have significant implications for treatment decisions, interventions for patients and testing for close relatives.

Personalised cancer medicine also involves targeted therapy, which targets specific genes and proteins that allow certain cancers to grow and survive. Majority of cancers are also being successfully treated by immunotherapy, which boosts the bodys natural defences to fight cancer, though it remains very costly.

Another breakthrough liquid biopsy has opened doors to a new era in precision oncology. A simple blood test can detect cancer much earlier, reduce the burden on the limited cancer hospitals, while saving many more lives at much lower costs.

While we cant change our genes (yet), we can change the environment we put them in, and make healthier lifestyle choices. Wellness-based genomic tests combined with the analysis of other risk factors can help tailor specific nutritional and lifestyle choices. With pharmacogenomics, it is now possible to identify how genetic variations affect a persons ability to metabolise a drug and prescribe the right dosage.

Research in precision medicine has been responsible in bringing many targeted therapeutics to the market. For a diverse country like India with over 4,000 population groups, and a significant percentage of consanguineous (descended from the same ancestor) marriages there is high prevalence of inherited genetic disorders that require attention for early diagnosis, right treatment and management. This opportunity to get access to data and understand disease-wise genetic variations will help develop better treatment, although managing this data will be just as critical.

With the Covid-19 pandemic, mutants and variants have become household names. It highlights the role genomics plays in infections disease management at the individual and population levels. Point-of-care molecular tests tailored to individual pathogens have dramatically increased the speed and specificity of infectious disease diagnosis, such as tuberculosis and other non-communicable diseases.

Embedding precision medicine principles at research, clinical, industry and regulatory levels, creating awareness, educating the general population, and making these tests affordable are the immediate challenges.

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Transitioning from the current one-cure-fits-all: Medicines for each other, precisely - Economic Times

BOSTON--(BUSINESS WIRE)--Vertex Pharmaceuticals Incorporated (Nasdaq: VRTX) today announced publication in The New England Journal of Medicine (NEJM) of results from a Phase 3 study of TRIKAFTA (elexacaftor/tezacaftor/ivacaftor and ivacaftor) in people with cystic fibrosis (CF) ages 12 years and older who have one copy of the F508del mutation and one gating (F/G) or residual function (F/RF) mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The manuscript includes data on primary and key secondary endpoints, which were previously reported and showed statistically significant and clinically meaningful improvements in lung function and sweat chloride, when compared to active control (either ivacaftor or tezacaftor/ivacaftor), as well as more detailed efficacy and safety data, including subgroup efficacy analyses.

This study is the third of three Phase 3 clinical trials in the TRIKAFTA program in the 12 years and older age group. Consistent with the prior outcomes, these results show clinically meaningful improvements in pulmonary function, sweat chloride and Cystic Fibrosis Questionnaire-Revised (CFQ-R) respiratory domain scores," said Carmen Bozic, M.D., Executive Vice President and Chief Medical Officer, Vertex. These results are especially notable given that all patients were treated with a CFTR modulator prior to initiating TRIKAFTA.

The outcomes within this study, in particular those from the subgroup efficacy analysis by F/G and F/RF, are remarkable because they demonstrate additional benefit on top of standard of care and build further confidence for clinicians to treat people with CF who may have these mutations, said Steven Rowe, M.D., Director, Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham.

Study 445-104

The data published today are from a global Phase 3, randomized, double-blind, parallel-group study. All patients had a 4-week run-in period of either ivacaftor or tezacaftor/ivacaftor. Following the run-in, 258 patients were randomized to receive TRIKAFTA or to remain on their prior regimen of ivacaftor or tezacaftor/ivacaftor for 8 weeks. Baseline was measured at the end of the run-in period, prior to the start of the 8-week treatment period. TRIKAFTA improved the percent predicted forced expiratory volume in 1 second (ppFEV1) by 3.7 percentage points (95% CI, 2.8 to 4.6; P<0.001) from baseline and by 3.5 percentage points (95% CI, 2.2 to 4.7; P<0.001) vs. active control and improved sweat chloride concentration by 22.3 mmol/liter (95% CI, 24.5 to 20.2; P<0.001) from baseline and by 23.1 mmol/liter (95% CI, 26.1 to 20.1; P<0.001) vs. active control. The change in the CFQ-R respiratory domain score was +10.3 points from baseline (95% CI, 8.0 to 12.7) and +8.7 points vs. active control (95% CI, 5.3 to 12.1). Subgroup analyses of patients with F/G and F/RF genotypes are also included in the manuscript. Safety data were consistent with those observed in previous Phase 3 studies with TRIKAFTA.

About Cystic Fibrosis

Cystic Fibrosis (CF) is a rare, life-shortening genetic disease affecting more than 80,000 people globally. CF is a progressive, multi-system disease that affects the lungs, liver, GI tract, sinuses, sweat glands, pancreas and reproductive tract. CF is caused by a defective and/or missing CFTR protein resulting from certain mutations in the CFTR gene. Children must inherit two defective CFTR genes one from each parent to have CF. While there are many different types of CFTR mutations that can cause the disease, the vast majority of all people with CF have at least one F508del mutation. These mutations, which can be determined by a genetic test, or genotyping test, lead to CF by creating non-working and/or too few CFTR proteins at the cell surface. The defective function and/or absence of CFTR protein results in poor flow of salt and water into and out of the cells in a number of organs. In the lungs, this leads to the buildup of abnormally thick, sticky mucus that can cause chronic lung infections and progressive lung damage in many patients that eventually leads to death. The median age of death is in the early 30s.

INDICATION AND IMPORTANT SAFETY INFORMATION FOR TRIKAFTA (elexacaftor/tezacaftor/ivacaftor and ivacaftor) TABLETS

What is TRIKAFTA?

TRIKAFTA is a prescription medicine used for the treatment of cystic fibrosis (CF) in patients aged 6 years and older who have at least one copy of the F508del mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene or another mutation that is responsive to treatment with TRIKAFTA. Patients should talk to their doctor to learn if they have an indicated CF gene mutation. It is not known if TRIKAFTA is safe and effective in children under 6 years of age.

Patients should not take TRIKAFTA if they take certain medicines or herbal supplements, such as: antibiotics such as rifampin or rifabutin; seizure medicines such as phenobarbital, carbamazepine, or phenytoin; St. Johns wort.

Before taking TRIKAFTA, patients should tell their doctor about all of their medical conditions, including if they: have kidney problems; have or have had liver problems; are pregnant or plan to become pregnant because it is not known if TRIKAFTA will harm an unborn baby; or are breastfeeding or planning to breastfeed because it is not known if TRIKAFTA passes into breast milk.

TRIKAFTA may affect the way other medicines work, and other medicines may affect how TRIKAFTA works. Therefore, the dose of TRIKAFTA may need to be adjusted when taken with certain medicines. Patients should especially tell their doctor if they take antifungal medicines such as ketoconazole, itraconazole, posaconazole, voriconazole, or fluconazole; antibiotics including telithromycin, clarithromycin, or erythromycin.

TRIKAFTA may cause dizziness in some people who take it. Patients should not drive a car, operate machinery, or do anything that requires alertness until they know how TRIKAFTA affects them.

Patients should avoid food or drink that contains grapefruit while they are taking TRIKAFTA.

TRIKAFTA can cause serious side effects, including:

High liver enzymes in the blood, which is a common side effect in people treated with TRIKAFTA. These can be serious and may be a sign of liver injury. The patient's doctor will do blood tests to check their liver before they start TRIKAFTA, every 3 months during the first year of taking TRIKAFTA, and every year while taking TRIKAFTA. Patients should call their doctor right away if they have any of the following symptoms of liver problems: pain or discomfort in the upper right stomach (abdominal) area; yellowing of the skin or the white part of the eyes; loss of appetite; nausea or vomiting; dark, amber-colored urine.

Abnormality of the eye lens (cataract) has happened in some children and adolescents treated with TRIKAFTA. If the patient is a child or adolescent, their doctor should perform eye examinations before and during treatment with TRIKAFTA to look for cataracts.

The most common side effects of TRIKAFTA include headache, upper respiratory tract infection (common cold) including stuffy and runny nose, stomach (abdominal) pain, diarrhea, rash, increase in liver enzymes, increase in a certain blood enzyme called creatine phosphokinase, flu (influenza), inflamed sinuses, and increase in blood bilirubin.

These are not all the possible side effects of TRIKAFTA. Please click the product link to see the full Prescribing Information for TRIKAFTA.

About Vertex

Vertex is a global biotechnology company that invests in scientific innovation to create transformative medicines for people with serious diseases. The company has multiple approved medicines that treat the underlying cause of cystic fibrosis (CF) a rare, life-threatening genetic disease and has several ongoing clinical and research programs in CF. Beyond CF, Vertex has a robust pipeline of investigational small molecule medicines in other serious diseases where it has deep insight into causal human biology, including pain, alpha-1 antitrypsin deficiency and APOL1-mediated kidney diseases. In addition, Vertex has a rapidly expanding pipeline of cell and genetic therapies for diseases such as sickle cell disease, beta thalassemia, Duchenne muscular dystrophy and type 1 diabetes mellitus.

Founded in 1989 in Cambridge, Mass., Vertex's global headquarters is now located in Boston's Innovation District and its international headquarters is in London. Additionally, the company has research and development sites and commercial offices in North America, Europe, Australia and Latin America. Vertex is consistently recognized as one of the industry's top places to work, including 11 consecutive years on Science magazine's Top Employers list and a best place to work for LGBTQ equality by the Human Rights Campaign. For company updates and to learn more about Vertex's history of innovation, visit http://www.vrtx.com or follow us on Facebook, Twitter, LinkedIn, YouTube and Instagram.

Special Note Regarding Forward-Looking Statements

This press release contains forward-looking statements as defined in the Private Securities Litigation Reform Act of 1995, including, without limitation, statements made by Dr. Carmen Bozic and Dr. Steven Rowe in this press release and statements regarding the potential benefits of TRIKAFTA and our anticipated efforts to expand the indication for TRIKAFTA globally. While Vertex believes the forward-looking statements contained in this press release are accurate, these forward-looking statements represent the company's beliefs only as of the date of this press release and there are a number of risks and uncertainties that could cause actual events or results to differ materially from those expressed or implied by such forward-looking statements. Those risks and uncertainties include, among other things, that data from a limited number of patients may not be indicative of final clinical trial results, that data from the company's development programs, including its programs with its collaborators, may not support registration or further development of its compounds due to safety, efficacy, or other reasons, and other risks listed under the heading Risk Factors in Vertex's most recent annual report filed with the Securities and Exchange Commission at http://www.sec.gov and available through the company's website at http://www.vrtx.com. You should not place undue reliance on these statements or the scientific data presented. Vertex disclaims any obligation to update the information contained in this press release as new information becomes available.

(VRTX-GEN)

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Vertex Announces Publication in The New England Journal of Medicine of Phase 3 Results for TRIKAFTA (elexacaftor/tezacaftor/ivacaftor and ivacaftor)...

Key Message

Chronic kidney disease (CKD) has a global prevalence of 816%, with serious morbidity and mortality.1 CKD is a direct risk factor for cardiovascular diseases, end-stage renal disease (ESRD)/CRF, and mortality.2 While replacement therapy with regular dialysis represents a temporary solution, renal transplantation is the permanent solution.3 Anaemia is one of the most important CRF complications, which develops early and worsens during the long-term progression of the disease.4 Coresh et al showed the association between lower Hb levels, the severity of anaemia and kidney function reduction.5 Erythropoietin (Epo), iron therapy, and continuous patient response monitoring provide a good tool for treating CKD-associated anaemia6 that helps to minimize transfusions and improve CKD patient survival.7 Although the response to rHuEpo is mostly good, resistance to Epo therapy among these cases ranges from 10% to 20%.8

Many factors may affect patients responses to replacement therapy with rHuEPO, including genetic factors, eg, ACE gene polymorphism that has an important impact on hematopoiesis. ACE gene is located at 17q23. It contains 26 exons and 25 introns.9 It has several single-nucleotide polymorphisms (SNPs). ACE G2350A (rs4343) SNP is located in exon 17 of the ACE gene and results in silent Thr 776 Thr (NP_000780.1) change. ACE gene SNPs may affect the patients response to Epo and could be useful genetic markers in assessing the required dose of Epo in such patients.10 ACE SNPs effect on CKD response to Epo therapy was evaluated with conflicting results. Varagunam et al reported a predictive role for it in determining Epo dosage in continuous ambulatory peritoneal dialysis English patients,11 while in another study in Korean HD patients, it was found to be associated with Epo resistance.10 ACE G2350A (RS4343) was selected for the present study based on a genome-wide-analysis study that reported the ACE G2350A (RS4343) is a good predictor of ACE activity12 due to the absence of wide genomic mapping in Arabian Countries, so our hypothesis that it may affect HD patients response to rHuEPO.

Although it was investigated concerning other clinical conditions, to the best of our knowledge, none of the international reports studied the effect of ACE G2350A (RS4343) gene polymorphisms on haematological markers of response to rHuEpo in CRF patients on HD. The current study aims to study the effect of ACE G2350A (RS4343) I/D gene polymorphisms on the response to rHuEpo, anaemia biomarkers, ACE content, inflammatory biomarkers, serum Epo and soluble Epo receptor (sEpoR) among CRF patients on HD.

Observational cross-sectional study.

Nephrology department and Biochemistry and molecular biology department, faculty of medicine, Cairo University.

Our cross-sectional study enrolled 256 CRF patients on HD for six months receiving rHuEpo therapy. They included 162 males and 103 females and aged 51.3 11.9 years. They were recruited from the nephrology unit, Internal Medicine Department, Cairo University, Cairo, Egypt, from April 2019 to June 2020. Matching 160 normal healthy control subjects were recruited from those accompanying outpatients and comprised 122 males and 38 females ageing 36.1 12.8 years (Table 1). Each participant had a five-minute interview to discuss the current studys objectives and aims before signing the informed consent and enrollment.

Table 1 General Characteristics and Laboratories of HD Patients versus Controls

Patients excluded from the study if age 18 years, acute renal failure, non-CKD-related anaemia, recent blood transfusion within the previous three months, a history of hepatitis B (HBV) or C (HCV) or HIV or other active acute or chronic infections, decompensated liver cirrhosis, pregnancy, and malignancy.

10 mL peripheral venous blood was collected on heparin. The recovered plasma by centrifugation (1000 x g for 10 min at 4 C) was aliquot stored at 40 C till used for assessment of ferritin, Transferrin (TF), soluble transferrin receptor (sTfR), EPO, sEpoR, ACE, and cytokines (IL-1, IL-6, and IL-10) content, iron workup (iron and total iron-binding capacity; TIBC). Iron (g/dL) and TIBC (g/dL) were assayed using colorimetric kits (Stanbio Laboratory, Boerne, TX, USA). Transferrin saturation (%) was calculated from iron and TIBC. Plasma proteins and cytokines were assayed using specific quantitative commercially available ELISA kits as instructed; ferritin in ng/mL and sTfR in nmol/L (Diagnostic Automation/Cortez Diagnostics Inc, CA, USA; cat#1601-16 and 3126-15), TF in mg/dL (Abcam, Cambridge, MA, USA, USA cat#ab187391), ACE in ng/mL and sEpoR in ng/mL (MyBioSource, Inc., San Diego, CA, USA; cat#MBS494753 and MBS702997), IL-1, IL-6, and IL-10 in pg/mL (RayBiotech, Inc., Peachtree Corners, GA, USA; cat# ELH-IL1b, ELH-IL6, and ELH-IL10), and Epo in mIU/mL (BioVision, Inc., Milpitas, CA, USA; cat# E4720-100). An aliquot of whole blood was also used to assess Hb, TLC count using a cell counter (Sysmex XT-4000i Automated Haematology Analyzer Lincolnshire, IL, USA). Hb level was measured in the 6th month three times, one week apart, the mean of these three readings was recorded. Half of the whole blood sample collected was used for genomic DNA extraction and real-time PCR analysis of ACE genes polymorphism.

Total DNA was isolated from whole blood mononuclear cells (MNC) using the extraction kit (Zymo Research, Irvine, CA, USA; cat# D302 Quick-DNA Microprep Kit) instructed. The DNA purity (A260/A280 ratio) and concentration were assessed spectrophotometrically (dual-wavelength Beckman, Spectrophotometer, USA). GAPDH house-keeping gene was assessed in all PCR reactions as an internal control and for DNA integrity. The extracted and purified DNA samples were stored at 80 C till used. ACE polymorphism genotyping and allelic discrimination was assessed using TaqMan Analysis. DNA was genotyped for ACE G/A at rs4343. PCRs were carried out in reaction volumes of 25 L containing 50 ng DNA, 10 L TaqMan Universal PCR Master Mix (Applied Biosystems, ThermoFisher Scientific Inc., Waltham, MA, USA) with the passive reference ROX (Perkin Elmer), 280 nmol/L of each primer and 200 nmol/L VIC-labeled probes for ACE G > A. Primers and minor groove binder probes were synthesized by Applied Biosystems. The primer sequence was forward: 5-GTGAGCTAAGGGCTGGA-3 and reverse: 5-CCAGCCCTCCCATGCCCATAA-3. PCR thermal cycler conditions included an initial incubation at 50 C for 2 minutes, 95 C for 10 minutes, followed by 35 cycles of 15 seconds at 92 C and 1 minute at 6062 C. Allele discrimination was accomplished by running endpoint detection using the StepOne and SDS 2.0 software. ACE AA = ACE Insertion/Insertion (I/I), ACE GA = ACE Insertion/Deletion (I/D) while ACE GG = ACE Deletion/Deletion (D/D).

Data were collected, tabulated, and analyzed using SPSS version 21 (IBM SPSS Statistics for Windows, Armonk, NY: IBM Corp). Deviation of genotype frequencies of the studied group of patients from Hardy-Weinberg equilibrium (HWE) was assessed by Chi-squared test with one degree of freedom (df) using the Michael H. Courts (20052008) calculator.13 If P 0.05, then the population is in HWE. For categorical data like gender was presented as frequency and percentage. Scale data like age, haematological parameters were presented as mean Standard Error of Mean (SEM). ShapiroWilk test was applied to determine the distribution of data. Chi-square test/ Fischer exact test was applied to measure the difference among categories. Independent samples t-test was used to measure the mean difference across two categories. Levenes test was applied to ascertain equal variance among the groups. One-way ANOVA with LSD posthoc analysis was applied to determine the difference in scale data among more than two categories. Correlations between ACE level and haematological parameters were using Pearsons correlation coefficient. The stepwise regression test was used to determine the independent parameters that may affect Hb or Hct values. A p-value < 0.05 was considered significant.

The current study protocol was approved by the Bioethics Committee, Medical College, Cairo University (Approval Number CU III F 40 20) and conducted following the Helsinki declaration.

Comparing HD patients vs healthy controls showed significant differences in plasma potassium, urea, creatinine, iron, TIBC, % TF Saturation, TF, sTfR, Hb, Hct, TLC, platelets count IL-6, IL-10 and IL-1, EPO, ACE and sEpoR (Table 1).

The prevalence of ACE G2350A (rs4343) I/D genotype among HD patients and healthy controls showed that the I/D genotype is the most prevalent while the I/I genotype is the least one. ACE G2350A (rs4343) I/D genotype distribution showed a significant difference in the gene allele distribution between HD patients compared to normal controls: I/D (n = 174 vs 85), I/I (n = 41 vs 6) and D/D (n = 50 vs 69) (p = 0.001). D allele is the most prevalent one either in HD patients (0.52) or among the control group (0.7) (Table 2).

Table 2 Patients and Control Group ACE Rs4343 Genotype and Allele Distributions

The mean Hb was highest in D/D genotype patients (11.120.19), followed by I/I (11.110.2) n I/D (10.470.1).

The effect of ACE G2350A (rs4343) genotypes on different parameters among CRF patients was evaluated using one-way ANOVA; a significant difference between the three categories was found, F= 5.9, P=0.003. Differences were significant between I/I and I/D genotype (mean difference=.63, P = 0.012), D/D and I/D genotype (mean difference =.65, P = 0.005). no significant difference was noted between I/I and D/D (P=0.956) Table 3.

Table 3 Comparison of Hb & Serum Iron in Different HD Patient Genotypes of ACE Gene Rs4343

The mean serum iron was highest in I/D genotype patients (44.53 .87), followed by I/I (40.951.3 n DD (40.61.05). A one-way ANOVA found a significant difference between three categories, F= 4.062, P=0.018. Differences were significant between I/D and II (mean difference=3.58. P =0.045), I/D and D/D (mean difference=3.93, P =0.018). I/I and D/D had not shown a significant difference (P= 0.871) Table 3.

There were insignificant differences among patients with I/I, D/D, or I/D genotypes regarding TLC (Figure 1A) or the inflammatory biomarkers (IL-6, IL-10, and IL-1) (Figure 1B).

Figure 1 Comparison of WBC (A), IL6 & IL10 & IL1 (B) regarding the ACE G2350A (rs4343) genotypes. Data presented as mean SEM. Evaluated by ANOVA test followed by LSD as a post hoc.

Figure 2 Comparison of Transferrin Saturation or sTfR (soluble transferrin receptor) (A), TIBC (Total Iron Binding Capacity), ferritin, and Transferrin (B) regarding the ACE G2350A (rs4343) genotypes. Data presented as mean SEM. Evaluated by ANOVA test followed by LSD as a post hoc.

There were insignificant differences among patients with I/I, D/D, or I/D genotypes regarding % TF Saturation and sTfR (Figure 2A), TIBC, Ferritin, or TF level (Figure 2B).

Figure 3 Comparison of Epo (erythropoietin), ACE (angiotensin-converting enzyme) and sEpoR (Soluble erythropoietin receptors) regarding the ACE G2350A (rs4343) genotypes. Data presented as mean SEM. Evaluated by ANOVA test followed by LSD as a post hoc.

The effect of ACE G2350A (rs4343) genotypes on levels of ACE, EPO, and sEpoR levels was evaluated among CRF patients. Our results showed insignificant differences between patients with different genotypes in that regard (Figure 3).

The D allele is the most prevalent allele among patients in the current study (Table 2). Analysis of the genotype correlation in a recessive mode of inheritance of the risk of D allele between Non-DD (II+ID) vs (DD) was done using an independent t-test. Our results showed a significant difference between the two groups regarding iron status (43.9.7, 40.61.1, respectively, F: 6.946, t: 2.529, CI: 0.7019:5.8004, P=0.013) and Hb level (10.6.1, 11.1.19, respectively, F: 0.261, t: 2.308, CI: 0.9797:0.0776, P=0.013) (Table 4).

Table 4 Comparison of Different Parameters Between Non-DD (ID+II) and DD Genotype Among HD Patients

Using Pearsons correlation coefficient, the correlation between the ACE level and haematological parameters among HD patients showed a significant positive correlation between the ACE level and Epo (r: 0.244, P=0.0001) and a significant negative correlation between the ACE level and HCT (r: 0.131, P=0.033) (Table 5).

Table 5 Correlations Between ACE Level and Haematological Parameters Using Pearsons Correlation Coefficient

Linear regression analysis revealed that among all parameters tested, ACE G2350A (rs4343) (R.194, P=0.001), TLC (R 0.282, P=0.001), and sEpoR (R 0.312, P=0.024) were independent predictors of Hb level (Table 6). While the ACE content (R. 0.292, P= 0.017), TLC (R. 0.255, P=0.015), and iron (R 0.209, P=0.001) were independent predictors of the Hct level (Table 7).

Table 6 Hb Stepwise Regression Test

Table 7 HCT Stepwise Regression Test

The current study is the first report that studied the effect of ACE G2350A (rs4343) gene polymorphism on the haematological indicators of response to rHuEpo therapy. It is well-established that genetic factors play an essential role in determining the efficacy and response to drug treatment.14 Pharmacogenomics analyses such relationships towards the personalization of medicine. Our lab showed the importance of such an approach in predicting the patients response to different drug therapy.15,16

The present study showed that HD patients with the ACE G2350A (rs4343) D/D and I/I genotype respond better to rHuEpo therapy than those with the I/D genotype as evidenced by the higher Hb level among the former group. This higher Hb level among D/D and I/I genotypes were not related to iron level. Our results showed that patients with the I/D allele had higher iron than patients with each of the D/D and I/I genotypes, despite the lower Hb level of the I/D allele holders. The better Hb response was recently partially reasoned to higher plasma angiotensin II (Ang II) levels in D/D and I/D genotypes compared to the II genotype.17

Ang II is the main effector member of the renin-angiotensin system acting through the AT1 receptor and is generated from Ang. I by an ACE-induced proteolytic cleavage.18 The Renin-angiotensin system plays a vital role in hematopoiesis and other diseases.19,20 However, the exact mechanism by which ACE may affect erythropoiesis and Hb level is still not well elucidated. Among the other plausible explanations is ACE inhibition of Ang IIinduced Epo release and prevention of the induction of pluripotent hematopoietic stem cells.21 ACE directs stem cell differentiation to erythroid progenitors synthesis.22 ACE may affect the Ang II level, directly increasing erythroid progenitors in vitro proliferation.23

Savin et al showed that the ACE D/D genotype is associated with higher Hb levels.24 Patients with the D/D genotype were shown to require less Epo dose than the I/I genotype.11

In a study that included 112 ambulatory peritoneal dialysis patients, Sharples et al25 showed that the ACE DD genotype requires less rHuEpo than other ACE genotypes, I/I or I/D. This result seems to be in line with our conclusion, albeit we could not identify the exact ACE SNPs that Sharples and his colleagues had examined. Similarly, Hatano et al26 showed that HD patients with D/D-allele require low rHuEPO.

The ACE rs4646994 D/D genotype was associated with a poor response to rHuEpo in HD Korean patients, suggesting that it could be a useful genetic tool in predicting Epo requirement and responsiveness in HD patients.10 Kiss et al,27 working on Hungarian and Al-Radeef et al,28 working on Iraqi HD patients, reported that ACE polymorphism had a non-significant effect on the Hb level. These variations may arise from the exact SNPs tested; we explored the ACE G2350A (rs4343) effect while they examined rs1799752 and rs4646994, respectively. Also, the small sample size of these studies compared to ours might have affected their conclusions.

Our results showed a higher iron store among the heterozygous ID genotype than II or DD genotype patients assuming a heterozygous advantage for the ACE G2350A (rs4343) ID genotype among HD patients included in the present study.

Heterozygote advantage or overdominant refers to better fitness of heterozygous genotype patients over both homozygous. It firstly appeared in 1922 to maintain polymorphism stability.29 Major histocompatibility complex (MHC) gene represent one of the prominent examples for the heterozygote advantage, in which MHC heterozygotes genetic diversity is abundant. Heterozygote genotype patients have better recognition of pathogen antigen and resist infections effectively than homozygous.30,31 Heterozygote advantage provides a protective effect against malaria for the sickle-cell anaemia allele carriers.32

Recently, A genome-wide association study revealed that heterozygous individuals were significantly healthy-aged compared to other individuals with other genotypes. Moreover, in the same age group population, a 10-year higher survival was associated with individuals with higher heterozygosity rates; the association is more likely to be explained by heterozygote advantage.33 Previous observations noted heterozygous advantages on ACE genotype patients among cardiovascular diseases; because of high linkage disequilibrium (LD) between the polymorphisms, ACE haplotypes needed to be determined in different populations with different evolutionary histories search for additional ancestral breakpoints. The phenotypes complexity also includes the possibility of multiple interactions between genes or genes and environmental factors. The high frequency of I/D, ie, 56.61%, could be because of heterozygote advantages against the two homozygotes D/D and I/I in cardiovascular diseases9 and kidney diseases; individuals with I/D genotype have the least levels of ACE. The DD genotype has the highest levels, followed by I/I34 or having lower plasma ACE levels,35 although these studies may differ from our study in its design, ethnicity, and allele distributions.

A 287-bp insertion/deletion (I/D) polymorphism in intron 16 of the ACE gene (17q22-q24, 26 exons, and 25 introns) in humans may control serum ACE levels. Many SNPs in linkage disequilibrium (LD) with the I/D polymorphism, including T5941C, A262T, T93C, T1237C, C4656T, and A11860G (rs 4343; exon 16),36,37 are known to influence serum ACE.38

Furthermore, rs1799752 is one of four SNPs that may be the most well-studied ACE SNP. It is an insertion/deletion of an Alu repetitive element in an ACE genes intron rather than a single nucleotide polymorphism.

ACE G2350A (rs4343) gene polymorphism is associated with increased ACE enzyme activity in physiological and pathological states.39 It increases ACE levels in subjects with a high-saturated-fat diet that enhances diet-dependent hypertension.40

Our data showed insignificant differences among the tested three ACE G2350A (rs4343) I/I, I/D, and D/D genotypes regarding the circulating ACE protein content. On the contrary, Mizuiri et al and Elshamaa et al demonstrated an opposite conclusion. ACE I/D genotype is associated with renal ACE gene expression in healthy Japanese subjects41 and plasma and tissue ACE levels.42 Nand et al showed D allele positively affects ACE serum level.43

Endogenous or rHuEpo binds to EPOr resulting in stimulation of erythropoiesis.44 sEpoR is generated from mRNA alternative splicing, and since it lacks the transmembrane domain, it is released into extracellular fluids. sEpoR buffers rHuEpo because of its high affinity to EPO; therefore, it acts as a potent antagonist to EPO, resulting in decreased response to rHuEpo treatment. sEpoR high level was correlated to a high need for rHuEpo dose.45,46

In the current work, there was an insignificant difference between ACE G2350A (rs4343) I/I, I/D, or D/D genotypes regarding plasma Epo and sEpoR content in the present study. This notion contradicts the finding of Al-Radeef et al, who showed that another rs1799752 I/D and D/D genotypes had a higher serum Epo level compared to the I/I genotype.28

Our patients were free of active infection, and the measured proinflammatory cytokine levels, IL-6, IL-1, and IL-10, were insignificant differences among the three ACE G2350A (rs4343) genotypes; I/I, I/D, or DD.

Increases in the inflammatory mediator, such as IL-6 and TNF-, lead to increases in the sEpoR level that would hinder erythropoiesis.46 sEpoR stabilizes proinflammatory cytokine ligand and modulates cytokine interaction to its membrane-bound receptor, leading to variation in its concentration.47 Inflammatory cytokines accompanying CRF and HD decrease rHuEpo efficacy. TNF-, IL-1, and IL-6 induce resistance against rHuEpo in erythroid progenitor cells reducing iron release from the reticuloendothelial system and decreasing Hb production.48,49 Betjes et al reported a lack of response to rHuEpo among CKD patients with cytomegalovirus infection mainly due to IFN- and TNF- production.50

Although our HD patients showed higher levels of % TF saturation and sTfR, TIBC, Ferritin, or TF, there were insignificant differences among patients with I/I, D/D, and I/D genotypes regarding these parameters.

Various tissues obtain their iron need via TF binding to its receptor, endocytosis of the complex, and iron download.51,52 The expression rate of the cell surface TF receptor is directly proportional to its iron need.53 The transmembrane glycoprotein TF receptor is formed of two disulfide-linked monomers; each polypeptide subunit comprises three major domains: a large C-terminal extracellular domain and a transmembrane and an N-terminal cytoplasmic domain. sTfR is the cleaved extracellular domain of the high-affinity iron-sensor TF receptor released soluble in extracellular fluids. Circulating levels of sTfR reflect the number of cells with receptors (erythropoietic activity) and the receptor density on cells (tissue iron status).54 Ferritin is used for diagnosing iron deficiency anaemia, but it could be falsely elevated in inflammation giving the erroneous impression of normal iron stores.55 sTfR is insensitive to inflammatory states and inflammatory biomarkers. It could detect anaemia even in subjects with the inflammatory condition; moreover, it could differentiate between anaemia due to iron deficiency or chronic diseases.56

Finally, we tested for independent factors that may affect the patients response to rHuEPO. Among all parameters tested, ACE protein level, TLC, and sEpoR were the independent predictors of Hb level. Simultaneously, ACE protein content, TLC, and iron are the independent predictors for the Hct level.

Previous works measured Hb level at the beginning, 3rd, and 6th months of treatment with rHuEpo [24, 28]. In the present study, we measured the Hb level after six months of the treatment with rHuEpo to allow more precision and avoid fluctuation of patient response to treatment. We took the mean of the three Hb levels in the 6th month. We could not retrieve accurate data considering the use of ACE inhibitors (ACEIs) or ARBs among our patients. We measured circulating ACE level as a protein rather than an activity that revealed insignificant differences among the three genotypes assessed to avoid any related confusion. We did not evaluate angiotensin II (Ang II) level in the current study and iron intake status, but we estimate Hct, iron, ferritin, TF, % TF saturation, sTfR, and TIBC. Many other ACE gene SNPs may affect the HD patients response to rHuEPOs as rs1799752, rs429, and rs4341 which may be in linkage disequilibrium with studied rs4343; however, the only studied here is the ACE G2350A (rs4343). These limitations of the current study are highly acknowledged and will be considered in our future studies.

Patients with either ACE G2350A (rs4343) I/I or D/D genotype showed better response to rHuEpo than those with I/D genotype. ACE protein content, TLC, and sEpoR may represent independent predictors for the HD patients response to rHuEPOs. Screening for ACE G2350A (rs4343) gene polymorphisms in the HD patients on HD before rHuEpo administration may predict patients response.

This project was funded by The Deanship for Scientific Research, Jouf University, Sakaka, Saudi Arabia (Grant # 40/345). The authors express their deepest thanks to Prof. Dr Dina Sabry (The Molecular Biology Lab, Faculty of Medicine, Cairo University, Cairo, Egypt) for facilitating the gene analysis and biochemical investigations.

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

The authors stated that they have no conflicts of interest for this work.

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33. Xu K, Kosoy R, Shameer K, et al. Genome-wide analysis indicates association between heterozygote advantage and healthy aging in humans. BMC Genet. 2019;20(1):52. doi:10.1186/s12863-019-0758-4

34. Pincus MR, Abraham NZ Jr, Carty RP. 20 Clinical enzymology. In: Henrys Clinical Diagnosis and Management by Laboratory Methods E-Book. Saunders; 2011:273. ISBN-10:1437709745

35. Kumari S, Sharma N, Thakur S, Mondal PR, Saraswathy KN. Beneficial role of D allele in controlling ACE levels: a study among Brahmins of north India. J Genet. 2016;95(2):291295. doi:10.1007/s12041-016-0649-7

36. Paillard F, Chansel D, Brand E, et al. Genotype-phenotype relationships for the renin-angiotensin-aldosterone system in a normal population. Hypertension. 1999;34(3):423429. doi:10.1161/01.HYP.34.3.423

37. Williams AG, Rayson MP, Jubb M, World M, Woods D, Hayward M. The ACE gene and muscle performance. Nature. 2000;403(6770):614. doi:10.1038/35001141

38. Zhu X, Bouzekri N, Southam L, et al. Linkage and association analysis of angiotensin Iconverting enzyme (ACE)gene polymorphisms with ACE concentration and blood pressure. Am J Hum Genet. 2001;68(5):11391148. doi:10.1086/320104

39. Firouzabadi N, Shafiei M, Bahramali E, Ebrahimi SA, Bakhshandeh H, Tajik N. Association of angiotensin-converting enzyme (ACE) gene polymorphism with elevated serum ACE activity and major depression in an Iranian population. Psychiatry Res. 2012;200(23):336342. doi:10.1016/j.psychres.2012.05.002

40. Schler R, Osterhoff MA, Frahnow T, et al. High-saturated-fat diet increases circulating angiotensin-converting enzyme, which is enhanced by the rs4343 polymorphism defining persons at risk of nutrient-dependent increases of blood pressure. J Am Heart Assoc. 2017;6(1):e004465.

41. Mizuiri S, Hemmi H, Kumanomidou H, et al. Angiotensin-converting enzyme (ACE) I/D genotype and renal ACE gene expression. Kidney Int. 2001;60(3):11241130. doi:10.1046/j.1523-1755.2001.0600031124.x

42. Elshamaa MF, Sabry SM, Bazaraa HM, et al. Genetic polymorphism of ACE and the angiotensin II type1 receptor genes in children with chronic kidney disease. J Inflamm. 2011;8(1):20. doi:10.1186/1476-9255-8-20

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Haematological Indicators of Response to Erythropoietin Therapy in Chr | PGPM - Dove Medical Press

Introduction

Klebsiella pneumoniae (K. pneumoniae) is an opportunistic pathogen and the leading cause of healthcare-associated infections.1 Multidrug-resistant (MDR) K. pneumoniae isolates are rapidly spreading, thus limiting the choice of antimicrobial agents for empiric treatment of infections caused by these microorganisms; hence, this is a public health challenge.2

Polymyxins are last-resort antibiotics used to treat infections caused by carbapenem-resistant K. pneumoniae (CRKP).3 The two polymyxins currently in clinical use are polymyxin B and colistin (polymyxin E). They have similar antibacterial activity, but their structures differ by only one amino acid.4

The antibacterial effect of polymyxins on gram-negative bacteria is mainly a two-step mechanism comprising initial binding to and permeabilization of the outer membrane, followed by the destruction of cytoplasmic membrane.5 Notably, with the increase in the clinical use of polymyxins, polymyxin resistance has emerged and is rising rapidly. Polymyxin-resistant K. pneumoniae often spread in different hospital wards, making clinical treatment more difficult.6 The previously reported mechanisms of polymyxin resistance are chromosomally mediated and involve the regulation of two-component regulatory systems (eg, pmrAB, phoPQ, and its negative regulator, mgrB, in the case of K. pneumoniae), leading to the modification of lipid A (phosphoethanolamine or 4-amino-4-arabinose) or in rare cases, the complete loss of the lipopolysaccharide.7

Researchers reported the first plasmid-mediated polymyxin resistance mechanism, mcr-1, in Enterobacteriaceae in China. This warranted immediate worldwide attention, and mcr-1 has since been detected in Enterobacteriaceae from animals, food, and healthy people outside of China, including in Europe and the USA.8 Recently, some countries have also reported that mcr-1 and blaNDM-5 genes coexist in Escherichia coli strains,9,10 which is a serious challenge to treatment efforts.

This study assessed the current status of polymyxin resistance in CRKP isolates and investigated the possible coexistence of mcr-1 and -lactamase genes in K. pneumoniae in Nanchang, China.

From January 2018 to June 2019, a total of 107 nonduplicate CRKP isolates were isolated from hospitalized patients in different clinical departments in a tertiary teaching hospital in Nanchang, China. Different specimens were collected, and the K. pneumoniae isolates were identified using a VITEK-2 automated platform (bioMerieux, Marcy lEtoile, France). E. coli ATCC 25922 was used as a control strain.

The susceptibility of the K. pneumoniae clinical isolates to antimicrobials was determined using gram-negative susceptibility cards (AST-GN-16) on the VITEK system (bioMerieux, Marcy lEtoile, France) following the manufacturers instructions; the results were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) standards.11 The MICs of polymyxin B for CRKP were further determined using the microdilution broth method according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines.12 A total of 16 antimicrobial agents were tested, including carbapenems (imipenem), -lactam/-lactamase inhibitor complexes (amoxicillin/clavulanic acid and piperacillintazobactam), monocyclic -lactam (aztreonam), cephalosporins (cefoxitin, cefepime, cefazolin, and ceftriaxone), aminoglycosides (gentamicin and amikacin), fluoroquinolones (levofloxacin and ciprofloxacin), folate metabolic pathway inhibitors (sulfamethoxazole), tetracyclines (tobramycin and tigecycline), and polymyxin B. E. coli ATCC 25922 was used as a control.

The carbapenemases produced by CRKP isolates were determined using a modified carbapenem inactivation test (mCIM) recommended by CLSI.11 In addition, a double-disc synergy test was performed to confirm the presence of metallo--lactamases (MBLs).11 The carbapenemase (blaKPC, blaGES, blaNDM, blaIMP, blaVIM, blaOXA-48, blaSIM, blaSPM, blaSME, and blaGIM), extended-spectrum -lactamase (ESBLs; blaTEM, blaDHA, blaSHV, blaCMY-II, and blaCTX-M), and polymyxin B (mcr-1 to mcr-8) resistance genes were detected using polymerase chain reaction (PCR) and DNA sequencing as described previously.2,13

Multilocus sequence typing (MLST) was performed on the polymyxin B-resistant K. pneumoniae isolates by amplifying and sequencing seven housekeeping genes (gapA, infB, mdh, pgi, phoE, rpoB, and tonB) according to a previously described protocol. Sequence types (STs) were assigned using the online database.

Pulsed-field gel electrophoresis (PFGE) was performed to analyze the phylogenetic relatedness of the polymyxin B-resistant K. pneumoniae isolates. Genomic DNA was digested by XbaI for 4 h at 37 C. Electrophoresis was performed for 19 h at 14 C, at an angle of 120, with switch times of 4 and 40 s at 6 V/cm using the CHEF III system (Bio-Rad Laboratories, Hercules, CA, USA). The Salmonella H9812 strain was used as the size marker. Analysis of the PFGE patterns using the Dice similarity coefficient was performed using the Bionumerics software (Applied Maths, Sint-Martens-Latem, Belgium). Clusters were defined as DNA patterns sharing more than 80% similarity.

A donor isolate, N816, was cultured in lysogeny broth (LB), and an azide-resistant E. coli J53 strain was used as the recipient. Transconjugants were selected on LB agar plates with 2 mg/L of polymyxin B or imipenem and 150 mg/L of sodium azide. Multiple attempts to transfer blaNDM-5 plasmid failed. Plasmid DNA was extracted from N816, transferred to competent E. coli DH5, and screened on LB agar plates with 2 mg/L imipenem. After the experiment, the transconjugant (JN816) and transformant (ZN816) were obtained and verified using PCR with previously described primers. Antimicrobial susceptibility testing was subsequently performed on JN816 and ZN816.

Genomic DNA was extracted from JN816 and ZN816 with the Qiagen Midi kit (Qiagen, Hilden, Germany) and sequenced with an Illumina HiSeq 2000 sequencer following a paired-end 2100-bp protocol.14 The raw data were mapped to a reference sequence found on the CLC genomics workbench version 8.0. Sequence comparison and alignment were performed using MEGA 5.01.15

Among the 107 K. pneumoniae isolates, 15 (14.0%) were resistant to polymyxin B according to EUCAST 7.0 guidelines.12 The antimicrobial resistance rates of these isolates are shown in Table 1. These isolates were resistant to imipenem, aztreonam, cefazolin, cefepime, cefoxitin, ceftriaxone, ciprofloxacin, and sulfamethoxazole. The resistance rates of isolates for amikacin, gentamicin, tobramycin, and tigecycline were 46.7, 60.0, 53.3, and 13.3%, respectively.

Table 1 Antimicrobial Resistance Profiling of 15 Carbapenem-Resistant Klebsiella pneumoniae Isolates

Twelve of the 15 polymyxin B-resistant isolates were confirmed as carbapenemase producers as determined using the mCIM assay, among which two isolates had a positive result for the double-disc synergy test, indicating that they also produced an MBL. In addition, 10 CRKP isolates were positive for blaKPC-2, and two were positive for blaNDM. Other carbapenemase genes including blaGES, blaIMP, blaVIM, blaOXA-48, blaSIM, blaSPM, blaSME, and blaGIM were not detected in any of the tested isolates. In addition to blaKPC-2, all isolates were positive for blaSHV, and eight (53.3%) were positive for the ESBL gene, blaCTX-M-65. Only one CRKP isolate was positive for mcr-1, blaNDM-5, blaCTX-M-55, and blaSHV-27 (Figure 1).

Figure 1 Pulsed-field gel electrophoresis results for 15 carbapenem-resistant Klebsiella pneumoniae isolates.

Among the 15 CRKP isolates, five STs were identified, including ST11 (11 isolates), and one isolate each in ST34, ST334, ST485, and a novel ST. The PFGE results showed that the 15 isolates were divided into nine different PFGE clusters; cluster A (4; 26.7%), cluster C (3; 20.0%), and cluster D (2; 13.3%). Each of the remaining six isolates were classified as singletons (Figure 1).

The two CRKP N816 plasmids harboring mcr-1 and blaCTX-M-55, designated as pMCR-1-N816 and pCTX-M-55-N816, respectively, were successfully transferred into the recipient strain (J53) via filter mating conjugation. We confirmed the presence of mcr-1 and blaCTX-M-55 genes in these plasmids. The antimicrobial resistance patterns of CRKP N816 and its transconjugant are shown in Table 2. The blaNDM-5-harboring plasmid of CRKP N816, designated as pNDM-5-N816, was electroporated into E. coli DH5 as described previously. Growth was observed only on plates with imipenem 2 mg/L, and the transformants were screened for the presence of blaNDM-5 using PCR, and blaNDM-5 was located on the plasmid. The antimicrobial resistance patterns of CRKP N816 and its transformants are shown in Table 2.

Table 2 Minimum Inhibitory Concentrations of Antimicrobials Against N816, JN816, ZN816, J53, and DH5

pMCR-1-N816 is 33309 base pairs (bp) long, with an average guanine-cytosine (GC) content of 41.84%. It has 41 predicted open reading frames (ORFs) and belongs to the IncX4 incompatibility group. A BLAST search of the plasmid sequences against the GenBank database showed that pMCR-1-N816 is similar (with 100% query coverage and >98.0% nucleotide identity) to pKP15450-MCR-1, an IncX4-type plasmid carrying mcr-1 among K. pneumoniae isolates in China (Figure 2). Plasmid pCTX-M-55-N816 is 76526-bp in length, with an average GC content of 51.93%. It has 105 predicted ORFs, and a BLAST search of the plasmid sequences against the GenBank database showed that pCTX-M-55-N816 is similar to pKP32558-4, with 89% query coverage and >98.0% nucleotide identity (Figure 3). Furthermore, pNDM-5-N816 is 46286-bp in length, with an average GC content of 46.63%, 59 predicted ORFs, and belongs to the IncX3 incompatibility group. A BLAST search showed that pNDM-5-N816 is similar to pNDM5-LDR, an IncX3-type plasmid carrying blaNDM-5 among K. pneumoniae isolates in China, with 100% query coverage and >99.9% nucleotide identity (Figure 4).

Figure 2 Structure of plasmid pMCR-1-N816 carrying mcr-1 from Klebsiella pneumoniae N816.

Figure 3 Structure of plasmid pCTX-M-55-N816 carrying blaCTX-M-55 from Klebsiella pneumoniae N816.

Figure 4 Structure of plasmid pNDM-5-N816 carrying blaNDM-5 from Klebsiella pneumoniae N816.

Carbapenems are the choice of treatment for infections caused by MDR K. pneumoniae. However, with the emergence of carbapenemase-producing bacteria, carbapenem resistance is increasing. The most common carbapenemase gene is blaKPC-2.16 Since the first discovery of the carbapenem resistance gene, blaNDM-1, in New Delhi, India,17 this gene and its multiple subtypes have been gradually discovered and reported worldwide. Moreover, the emergence of MBL-producing drug-resistant bacteria poses a great challenge for the treatment of drug-resistant bacterial infections. China reported a CRKP strain carrying the blaNDM-1 gene in 2013.18

Polymyxins have been used for many years in veterinary medicine, and nowadays, in human medicine, as a last resort for the treatment of MDR infections, especially CRKP. Thus, the increase in carbapenemase-producing Enterobacteriaceae has resulted in increased use of polymyxins with the inevitable risk of emerging polymyxin resistance.19,20 In this study, 107 CRKP isolates were tested for antimicrobial susceptibility; 15 (14.0%) of them were resistant to polymyxin B. The resistance rates of CRKP isolates to polymyxin B reported in Brazil and other European countries are 15.5% and 36%, respectively.20,21 The differences in antimicrobial resistance rates may be related to the different levels of antimicrobial usage in different countries.22

We found that 15 isolates were resistant to broad-spectrum antibiotics. Sequencing analysis showed that in addition to the blaKPC-2 gene, one or more other kinds of -lactamase genes (such as blaCTX-M, blaSHV, and blaTEM) were identified in these KPC-producing K. pneumoniae strains, with 53% (8/15) of the strains carrying the ESBL gene, blaCTX-M; this is consistent with previous reports.23 Consistent with other studies, the isolates were also more resistant to quinolones and trimethoprim/sulfamethoxazole. Quite often, plasmids carrying ESBL genes also carry other drug-resistant genes including quinolone and trimethoprim/sulfamethoxazole resistance genes.24

The drug susceptibility results of this study showed CRKP has a low resistance to amikacin, possibly because amikacin has only been used for a short time in this region or owing to the presence of restorative mutations. It may also be because of the aminoglycoside-modifying enzymes produced when amikacin is used to treat CRKP; the 16S rRNA gene targeted by amikacin is prone to mutations, resulting in a decrease in the activity of the enzyme to hydrolyze it.25 Although the resistance rate of CRKP to tigecycline is also low in this study, Its FDA approved uses include complicated skin/skin structure infections, complicated intra-abdominal infections, and community-acquired bacterial pneumonia, treatment of these infections limits its use.26 Studies have shown that polymyxin combined with amikacin has obvious synergistic and additive effects, and the MICs of this combination therapy are significantly lower than those of monotherapy.27 Polymyxin and amikacin may be sensitive to each other and as they target multiple proteins through different mechanisms to inhibit biofilm formation and increase membrane permeability, a synergistic effect to inhibit CRKP isolates is exhibited.28

Among the 15 polymyxin B-resistant CRKP isolates, most of the strains carried the blaKPC-2 gene, which is primarily responsible for carbapenem resistance, and this is consistent with our previous report.16 Among these strains, we only detected one isolate positive for mcr-1 gene. This strain was isolated from a blood culture specimen of a 71-year-old male patient and was resistant to multiple drugs, including polymyxin B, but not amikacin. This isolate also had blaCTX-M-55, blaNDM-5 and blaSHV-27 genes. Our experiments and sequencing results show that these mcr-1, blaCTX-M-55, and blaNDM-5 genes do not appear to be on the same plasmid, and the blaSHV-27 gene was found on the bacterial chromosome. Consistent with the above experimental results, the MICs of the corresponding antibiotic of the conjugants and transformants were altered accordingly (Table 2). The other 14 isolates did not harbor the mcr-1 gene. Other drug resistance mechanisms may be related to specific mutations within the genes encoding LPS-modifying enzymes, resulting in increased levels of the intrinsic regulator RamA and hyperproduction of CPS.29,30 However, this needs further testing. Unlike reports in other countries where the mcr-1 and blaNDM-5 genes were found to coexist in E. coli,9,10 this is the first time that K. pneumoniae has been reported to harbor both mcr-1, blaNDM5, and blaCTX-M-55 genes. What is even more worrying is that the plasmids in which these three genes are located have the ability to transfer horizontally. Thus, the bacteria may develop more serious drug resistance and lead to a state where there will be no treatment options. However, PFGE and MLST results of this isolate indicated that it had a different homology from the other 14 polymyxin B-resistant K. pneumoniae isolates, indicating that this type of bacteria did not have an outbreak. This isolate is not part of the most common ST (ST11) in China,16 but is a rare ST485 isolate. There is no report of an outbreak caused by K. pneumoniae ST485 at home and abroad. The patient had no history of foreign travel in the inquiry; thus, we infer that the occurrence of this isolate is a rare phenomenon in this area, but continuous monitoring to prevent the spread of this type of bacteria, which may cause more serious drug resistance, is warranted.

It has long been believed that polymyxin is mediated by chromosomes.19 Until 2015, Chinese scholars reported that the plasmid-mediated polymyxin resistance gene mcr-1 was found in Enterobacteriaceae isolated from humans and animals.3 Since then, people have a new understanding of the mechanism of polymyxin resistance. The emergence of a new type of drug resistance mechanism immediately set off a research boom among microbiologists worldwide. After sequencing and analysis of the plasmid obtained in this study, it was found that the isolate contained three plasmids of different sizes (33, 46, and 76 kb), which carried the mcr-1, blaCTX-M-55, and blaNDM-5 genes, which also verified the results of our previous conjugation, transformation, and drug susceptibility experiments. Further analysis of the data obtained using sequencing revealed that the similarity between the plasmid carrying mcr-1 and the plasmid pKP15450-MCR-1 was 98.77%. The mcr-1 gene at the starting point of the plasmid is approximately 3826 to 5451 bp, which encodes 541 amino acids. Analysis of its upstream and downstream genes showed that there are no common insert elements, indicating that the mcr-1 gene on this type of plasmid is more prone to horizontal transfer. The plasmid carrying the blaCTX-M-55 gene has a similarity of 99.96% with the plasmid pKP32558-4. The start site of the blaCTX-M-55 gene is approximately 2052 to 2927 bp, which encodes 291 amino acids and has an inserted transposon IS431 around the gene. The above two plasmids can be successfully joined to the same strain at the same time, indicating that they are compatible with each other. The plasmid carrying the blaNDM-5 gene has a similarity of 98.4% with the plasmid pNDM5-LDR. The start site of the blaNDM-5 gene is approximately 5783 to 6595 bp, which encodes 270 amino acids and has an inserted transposon, IS1086 and IS5H, upstream of the gene. The IS1086 and IS5H sequences indicate that the plasmid can transfer horizontally and confirm the results of previous experimental research. The resistance gene expression and transferability of this isolate have been further verified, which may lead to serious drug resistance.

In conclusion, the present study demonstrated for the first time the coexistence of mcr-1, blaNDM5, and blaCTX-M-55 in a K. pneumoniae ST485 isolate. Therefore, treatment strategies and monitoring should be implemented to limit the widespread of isolates containing mcr-1, blaNDM5, and blaCTX-M-55.

As the Klebsiella pneumoniae clinical isolate in this study was part of the routine hospital laboratory procedure, we have confirmed that the isolate has no identifiable patient data, the Second Affiliated Hospital of Nanchang University Medical Research Ethics Committee exempted this research for review.

This study was supported by a grant from the Department of Science and Technology of Jiangxi Province (20181BBG70030), the Jiangxi Natural Science Foundation (No.20181BAB205066), Science and Technology Plan of Jiangxi Provincial Health Commission (NO.20195211).

All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

The authors declare that they have no conflict of interest.

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2. Zhan L, Wang S, Guo Y, et al. Outbreak by hypermucoviscous Klebsiella pneumoniae ST11 isolates with carbapenem resistance in a tertiary hospital in China. Front Cell Infect Microbiol. 2017;7:182. doi:10.3389/fcimb.2017.00182

3. Chavda B, Lv J, Hou M, et al. Coidentification of mcr-4.3 and blaNDM-1 in a clinical Enterobacter cloacae isolate from China. Antimicrob Agents Chemother. 2018;62(10):e0064918. doi:10.1128/AAC.00649-18

4. Hussein M, Han ML, Zhu Y, et al. Metabolomics study of the synergistic killing of polymyxin B in combination with amikacin against polymyxin-susceptible and -resistant pseudomonas aeruginosa. Antimicrob Agents Chemother. 2019;64(1):e0158719. doi:10.1128/AAC.01587-19

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10. Zhang Y, Liao K, Gao H, et al. Decreased fitness and virulence in ST10 Escherichia coli harboring blaNDM-5 and mcr-1 against a ST4981 strain with blaNDM-5. Front Cell Infect Microbiol. 2017;7:242. doi:10.3389/fcimb.2017.00242

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19. Mendes AC, Novais A, Campos J, et al. mcr-1 in carbapenemase-producing Klebsiella pneumoniae with hospitalized patients, Portugal, 20162017. Emerg Infect Dis. 2018;24(4):762766. doi:10.3201/eid2404.171787

20. Wang R, van Dorp L, Shaw LP, et al. The global distribution and spread of the mobilized colistin resistance gene mcr-1. Nat Commun. 2018;9(1):19. doi:10.1038/s41467-018-03205-z

21. Di Tella D, Tamburro M, Guerrizio G, et al. Molecular epidemiological insights into colistin-resistant and carbapenemases-producing clinical Klebsiella pneumoniae. Infect Drug Resist. 2019;Volume 12:37833795. doi:10.2147/idr.s226416

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23. Liu H, Lin H, Sun Z, et al. Distribution of beta-lactamase genes and genetic context of bla KPC-2 in clinical carbapenemase-producing Klebsiella pneumoniae Isolates. Infect Drug Resist. 2021;14:237247. doi:10.2147/IDR.S290434

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Emergence of the Coexistence of mcr-1, blaNDM-5, and blaCTX-M-55 in Kl | IDR - Dove Medical Press

Background: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

Methods: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

Results: We identified a multi-ethnic set-based rare-variant association (p = 3.48 10-8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

Conclusions: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Keywords: GWAS; Genome-wide association study; Sleep apnea; Sleep-disordered breathing; WGS; Whole-genome sequencing.

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Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program - NCBI