Category Archives: Transhuman News

A team of scientists led by the University of Michigan Health Rogel Cancer Center has found that a class of United States Food and Drug Administration-approved drugs can effectively stop a highly aggressive type of uterine cancer in its tracks, paving a quick path toward new treatment strategies for a deadly cancer with limited therapeutic options.

Collaborating with researchers from Case Western Reserve University and Memorial Sloan Kettering Cancer Center, the team showed that ribonucleotide reductase, or RNR, inhibitors target two mutations in the gene that encodes the tumor suppressor PP2A, present in up to 40% of uterine serous carcinomas.

The team reported its findings in Cancer Research.

Uterine cancer is the most common gynecologic cancer with more than 60,000 cases diagnosed each year in the U.S. The endometrioid subtype is most common and in general responds well to targeted immunotherapies. By contrast, the uterine serous subtype has few genetic mutations that would make it a candidate for targeted therapies, and patients face rapid disease progression and a dire prognosis.

While uterine serous carcinoma represents only 10% of uterine cancers, it accounts for the majority of deaths. We showed that the PP2A mutation is common in uterine serous carcinoma, and we found a potential new treatment option for these patients, said first author Caitlin OConnor, Ph.D., a research fellow in the Division of Genetic Medicine at Michigan Medicine. We can rapidly translate this bench work to patients.

PP2A is a tumor suppressor, stopping cancer growth much like the brakes on a car. In previous studies, the team showed that about a third of uterine serous carcinomas harbor two mutations that disable the brake, said senior author Goutham Narla, M.D., Ph.D., chief of genetic medicine at Michigan Medicine. We asked ourselves, how can we take advantage of these mutations?

To start, the researchers ran a high-throughput screen of 3,200 drug compounds against uterine serous cell samples from patients with recurrent cancer. The results showed that a family of anti-cancer drugs called ribonucleic reductase inhibitors killed cancer cells that harbored the mutations.

Researchers then narrowed their focus to one of the drug screen hits, the RNR inhibitor clofarabine, and tested it in a mouse model of uterine serous carcinoma. RNR inhibitors interfere with the growth of tumor cells by blocking the formation of DNA. Consistent with the cell-based data from the drug screen, clofarabine shrank the tumors in mice.

To further explore RNR inhibition as a potential therapeutic strategy for uterine serous carcinoma, the team did a retrospective analysis of patients treated with the RNR inhibitor gemcitabine as a later-line therapy for this subtype, compared to patients with the endometrioid subtype. We found that the uterine serous carcinoma-type patients actually did better than the endometrioid patients, OConnor said.

There is currently only one first-line chemotherapy for uterine serous carcinoma: carboplatin, Narla noted. This type of uterine cancer has a short progression, and its a particularly lethal form, so we want to find a drug that will work earlier on in disease progression and find a molecular way to target the cancer. We believe we may have that here, he said.

The research team is now planning to begin a clinical trial of gemcitabine in patients with uterine serous carcinoma. They also plan to extend this work to other cancers that harbor the PP2A mutations, including lung, colon and ovarian cancer.

Additional authors include Sarah E. Taylor of Case Western Reserve University; Kathryn M. Miller and Dmitriy Zamarin of Memorial Sloan Kettering Cancer Center; Fallon K. Noto of Hera BioLabs, Inc.; Lauren Hurst, Terrance J. Haanen, Tahra K. Suhan, Kaitlin P. Zawacki, Jonida Trako, Arathi Mohan, Jaya Sangodkhar and Analisa DiFeo of the University of Michigan.

The research was supported by grants from the National Institutes of Health (R01 CA-181654, R01 CA-240993, T32 CA-009676), and funding provided by the Rogel Cancer Center.

OConnor and Narla are named inventors on a U.S. provisional patent application concerning compositions and methods for treating high grade subtypes of uterine cancer. OConnor, Suhan, Zawacki and Sangodkar are consultants for RAPPTA Therapeutics. Narla is chief scientific officer of, reports receiving commercial research support from and has ownership interest in RAPPTA Therapeutics and is an adviser to Hera BioLabs. Zamarin reports research support to his institution from Astra Zeneca, Plexxikon, and Genentech, and personal/consultancy fees from Synlogic Therapeutics, GSK, Genentech, Xencor, Memgen, Immunos, Celldex, Calidi, and Agenus, and is an investor on a patent related to use of oncolytic Newcastle Disease Virus for cancer therapy.

Paper cited: Targeting ribonucleotide reductase induces synthetic lethality in PP2A-deficient uterine serous carcinoma, Cancer Research. DOI: 10.1158/0008-5472.CAN-21-1987

Link:
Researchers zero in on therapeutic target for aggressive uterine cancer - Michigan Medicine

Generation Bios shares were briefly halted Tuesday morning on the release of mouse data that complicated its search for a viable target for hemophilia A to take into the clinic.

The biotech, which joined the public markets with an IPO that had proceeds of $230 million in June 2020, announced in a Securities and Exchange Commission filing that data from early preclinical mouse studies did not translate into nonhuman primates.

This one is in the weeds, but Generation's previous research in mouse models found that their candidate demonstrated peak mean human factor VIII expression of 205% of normal. Factor VIII is an essential blood-clotting protein and a key biomarker for patients with hemophilia. New gene therapies are trying to correct deficiency of that protein to prevent bleeding episodes.

However, once the candidate was administered to nonhuman primates, that peak mean human factor VIII expression dropped to just 2%. That result is now sending Generation back to the drawing board to come up with a new candidate that might work in humans.

RELATED:Generation Bio tees up $125M IPO to push next-gen gene therapies

After trading on Generations shares resumed, the price plummeted more than 55% to $6.22, compared to a prior close of $13.60.

Generation had promised to pick its clinical candidates over the course of 2020, with IND-enabling studies planned for this year. Applications to the FDA for human testing were expected in 2022.

That timeline will be pushed backway back. The company now plans to provide updates to its pipeline program sometime in 2022 and timing for IND submissions will come in the future.

This is a cautionary tale for the hot IPO arena that has seen biotechs leap to the public markets based purely on preclinical data.

Nevertheless, Chief Scientific Officer Matthew Stanton, Ph.D., said the company has learned plenty about its platform in collecting the animal study data, specifically around manufacturing capabilities and production processes.

RELATED:Generation Bio grabs a $110M round to ramp up work on next-gen gene therapies

We are working to translate the improved potency and decreased variability that we have observed in mice to [nonhuman primates], Stanton said.

Back in January, Generation said its candidate had been successfully delivered to the liver of nonhuman primates. At the time, Stanton referred to data on the demonstration of translation from mice to nonhuman primates as important proof points for our platform.

Generation is aiming to exceed the limits of conventional gene therapies, CEO Geoff McDonough, M.D., said in a Tuesday statement. The companys gene therapy technology is based on a non-viral genetic medicine platform.

More here:
Generation Bio shares halved as hemophilia gene therapy hunt goes back to square one - FierceBiotech

The carbon nanotube device could streamline some cancer therapies like CAR T-cell therapy.

Researchers at the University of Rochester Del Monte Institute for Neuroscience and Rochester Institute of Technology have received a U.S. patent for technology designed to accelerate development of cell therapies for cancer and other bio-therapies. The technique provides a less toxic alternative to standard gene transfer techniques by using an array of carbon nanotubes to deliver DNA into primary neurons, immune cells, and stem cells.

Our goal is to provide a technology that can lower the cost and increase speed and the range of cell types that can be adapted for therapeutic use, said Ian Dickerson, Ph.D., associate professor of Neuroscience. Many new cell-based therapies depend on changing the gene expression of primary cells. These approaches range from stem cells for production of patient-specific repair tissues, to CAR T-cells used for focused cancer therapy.

Dickerson and Michael Schrlau, Ph.D., associate professor of mechanical engineering in RITs Kate Gleason College of Engineering, were recently awarded a patent for this technology. It delivers biomolecules into cells through carbon nanotube arrays. Their honeycomb of nanotubes device was first described in a 2016 study published in the journal Small.

A scanning electron micrograph (SEM) of a macrophage cell sitting on top of the bed of carbon nanotubes.

The carbon nanotubes aim to be an alternative to conventional gene transfer methods that have a number of limitations including expensive equipment, low efficiency, and results in high toxicity that damages the cells. These methods limit the types of experiments that can be done and many cells like stem cells, primary cells, and immune T-cells. With Dickersons and Schrlaus device cells are able to grow on the carbon nanotube, genes are then transferred through the tubes and taken up by the cells through endocytosis. It has been successful at culturing a number of cell types, including immune cells, stem cells, and neurons, all are typically difficult to grow and keep alive.

The initial research that lead to this device was supported in part by a $50-thousand SchmittProgram in Integrative Neuroscience pilot award from the Del Monte Institute for Neuroscience. It funded Dickersons project entitled High Efficiency Injection of Biomolecules into Uticle Cells by Carbon Nanotube Arrays. This funding enabled us to begin manufacturing these carbon nanotube devices, and test the function on cell lines, which provided preliminary data that proved the concept of carbon nanotube-mediated gene transfer would work, said Dickerson.

The researchers are now collaborating with investigators at Wilmot Cancer Institute to further explore using this device for cancer therapies like CAR T-cells. "Currently CART-cells are manufactured using a viral vector to accomplish gene transfer, said Patrick Reagan, M.D., assistant professor of Medicine at the Wilmot Cancer Institute.Gene transfer via carbon nanotubules represents a novel method of gene transfer that could make the manufacturingprocess more efficient. This is important given that many of the patients treated with CAR T-cell therapy for lymphoma and leukemia have aggressive disease and the time delays associated with CAR T-cell manufacturing can lead to adverse outcomes."

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URMC & RIT faculty awarded patent for gene transfer technology that could transform cancer therapies - URMC

Introduction

The use of drugs should be different among diverse ethnic groups because of differences in ethnicity, age, sex, environmental factors and genetic factors. If these differences are ignored, then drug sensitivity, metabolic rate, and adverse reactions are affected, which influences the curative effect of drugs and aggravates the illness of patients.

Genetic factors can explain up to 2095% of the variability in drug response.1 Variations in genes can affect the pharmacokinetics/pharmacodynamics of drugs, as well as their absorption and metabolism. Pharmacogenes are genes that decide the fate of drug pharmacology in a biological system. In general, pharmacogenes correspond to specific gene superfamilies. Among numerous gene superfamilies, the cytochrome P450 superfamily is the most widely researched in pharmacogenomics studies. It has been reported that polymorphisms of cytochrome P450 account for the most frequent variations in the phase-I metabolism of drugs.2 Variations in most gene superfamilies can affect the metabolism of drugs and disease risk.

The single-nucleotide polymorphism (SNP) is the most common variation of very important pharmacogenes (VIPs). Usually, SNPs are employed to analyze the pharmacogenomic information in different populations.3,4 Pharmacogenomics is an emerging approach to precision medicine. Pharmacogenomics plays a major part in precision medicine by tailoring the selection and dosing to the patients genetic features.5 The Pharmacogenomics Knowledge Base (PharmGKB; http://www.pharmgkb.org/) is one of the most commonly used databases on primary pharmacogenomics. PharmGKB contains information on gene-variant annotations, drug-centered pathways, VIPs and diverse diseases. PharmGKB aims to share genotype, phenotype, or other data on genetic variations among researchers.6

It has been demonstrated that pharmacogenomic analysis of a specific population can aid the efficacious, accurate use of drugs in a population.7,8 For example, Bader et al found that variants of the vitamin K epoxide reductase complex gene (VKORC) and cytochrome P450 family 2 subfamily C member 9 gene (CYP2C9), which encode enzymes for warfarin metabolism, were the strongest predictors of variability in the warfarin dose among different populations in Middle East and North Africa.7 In addition, Kim et al demonstrated that adverse drug reactions could be avoided if preemptive genotyping was employed in a South Korean population.8

The US Food and Drug Administration (www.fda.gov/) have recognized >250 biomarkers with known pharmacogenomic value, and provided recommendations for therapeutic management.9 Recently, pharmacogenomics information on increasing numbers of ethnic minorities in China has been explored. For example, Liu et al found that, compared with 11 populations in a dataset from the International HapMap Project (www.genome.gov/), differences in expression between the rs2070676 of the cytochrome P450 family 2 subfamily E member 1 gene (CYP2E1) and rs1065852 of cytochrome P450 family 2 subfamily D member 6 gene (CYP2D6) in people of Zhuang nationality were the greatest according to genotyping of samples of 105 people of Zhuang nationality.3 Besides, He et al concluded that expression of rs4291 of the angiotensin I-converting enzyme gene (ACE), rs1051296 of the solute carrier family 19 member 1 gene (SLC19A1) and rs1065852 of CYP2D6 differed significantly in a Tibetan population compared with that of 26 other populations after genotyping of 200 samples from a Tibetan population. They also found that the allele frequency in this Tibetan population differed least from that of an East Asian population, and differed most from that of a North American population.4

China has 56 ethnic groups. The Blang ethnic group is found in Yunnan Province in China. According to the Sixth National Census in 2010, the total number of people of Blang ethnicity was 119,639. Among them, >30,000 people live in Mount Blang, Xiding, Bada, Daluo, Mengman, Menggang and other towns in Menghai County in Xishuangbanna Dai Autonomous Prefecture.10 People of Blang ethnicity live in mountainous areas with a mild climate and abundant rainfall, which is very conducive to plant growth. The area in which Blang populations live is one of the main raw material-producing areas of Puer tea and Mengku tea. Even though genetic studies on Blang populations have been conducted,1012 pharmacogenomics information of the Blang population is lacking. Cheng et al explored the pharmacogenomics information of a Blang population.13

Here, we shed light on the pharmacogenomic information of a Blang population by genotyping 55 different loci of 27 VIPs using 200 samples from Yunnan Province. These samples are different from those investigated by Cheng and collaborators. We also compared the distribution of genotype frequency and minor allele frequency (MAF) differences (55 loci of 27 VIPs) with a Blang population and 26 other populations. The genetic variations of the 15 gene superfamilies involved in the present study were related mainly to changes in drug metabolism and disease risk.2,1427 We wished to enrich the pharmacogenomics information of a Blang population and provide a theoretical foundation for promoting the development of personalized precise medication for Blang populations in the future.

The study protocol was approved by the Clinical Research Ethics Committee of Xizang Minzu University (Xianyang, China). Written informed consent was obtained from each study participant before a blood sample was given.

Two-hundred randomly selected healthy, unrelated individuals of Blang ethnicity from Yunnan Province were recruited. Whole-blood samples were collected according to the study protocol. Candidate participants were healthy individuals and had exclusive Blang ancestry for 3 previous generations. People suffering from cancer, infectious diseases, drug/alcohol addiction, severe dysfunction of the heart, liver, or kidney or immune disorders were excluded, as were women who were pregnant or lactating. Thus, the recruited individuals were representative of a Blang population.

PharmGKB was used for selection of genetic variants from published polymorphisms associated with VIP variants. Assays for the loci of 55 genetic variants in 27 VIPs were designed. Loci that could not be designed for an assay were excluded.

We extracted the genomic DNA from the peripheral blood of participants using the GoldMag-Mini Whole Blood Genomic DNA Purification Kit (GoldMag. Xian, China) according to manufacturer protocols. The DNA concentration was measured using the NanoDrop 2000C spectrophotometer (Thermo Scientific, Waltham, MA, USA). MassARRAY Assay Design 3.0 (Sequenom, San Diego, CA, USA) was employed to design multiplexed SNP MassEXTEND assays.28 SNP genotyping was done using MassARRAY RS1000 (Sequenom) according to manufacturer protocols. Sequenom Typer 4.0 was employed to manage and analyze the data on SNP genotyping.29 The basic information on the selected 55 loci related to 27 VIPs of the Blang population are listed in Table 1. The polymerase chain reaction (PCR) primers designed for the selected SNPs are shown in Supplemental Table 1. The basic information comprised the gene name, SNP ID, positions, functional consequence, genotype frequencies and MAF in the Blang population. All samples from the Blang population were genotyped with respect to these variants. PharmGKB was also used for the clinical and variant annotations for seven significantly different SNPs in the Blang population compared with 26 other populations.

The genotype data of individuals from 26 populations was obtained from the International HapMap Project Internet website (www.genome.gov/10001688/international-hapmap-project/). The 26 populations were as follows: 1) Chinese Dai in Xishuangbanna, China (CDX); 2) Han Chinese in Beijing, China (CHB); 3) Southern Han Chinese, China (CHS); 4) Japanese in Tokyo, Japan (JPT); 5) Kinh in Ho Chi Minh City, Vietnam (KHV); 6) African Caribbeans in Barbados (ACB); 7) African Ancestry in Southwest USA (ASW); 8) Esan in Nigeria (ESN); 9) Gambian in Western Divisions, The Gambia (GWD); 10) Luhya in Webuye, Kenya (LWK); 11) Mende in Sierra Leone (MSL); 12) Yoruba in Ibadan, Nigeria (YRI); 13) Colombian in Medellin, Colombia (CLM); 14) Mexican Ancestry in Los Angeles, Colombia (MXL); 15) Peruvian in Lima, Peru (PEL); 16) Puerto Rican in Puerto Rico (PUR); 17) Utah residents with Northern and Western European ancestry (CEU); 18) Finnish in Finland (FIN); 19) British in England and Scotland (GBR); 20) Iberian populations in Spain (IBS); 21) Toscani in Italy (TSI); 22) Bengali in Bangladesh (BEB); 23) Gujarati Indian in Houston, Texas (GIH); 24) Indian Telugu in the UK (ITU); 25) Punjabi in Lahore, Pakistan (PJL); 26) Sri Lankan Tamil in the UK (STU).

An exact test was used to test the frequency validity of each VIP variant by assessing the departure from the HardyWeinberg equilibrium. The comparison of genotype frequencies between the Blang population and 26 other populations was conducted using the 2 test. SPSS 17.0 (Armonk, NY, USA) and Excel (Microsoft, Redmond, WA, USA) were used to analyze the distribution of genotypes and MAFs. The Bonferroni correction was applied to p < 0.05 (two-sided).

The VIPs corresponding to 55 loci could be classified into 15 gene superfamilies (Table 1): cytochrome P450 superfamily; dihydropyrimidine dehydrogenase; prostaglandin-endoperoxide synthase; calcium voltage-gated channel; ryanodine receptor; alcohol dehydrogenase; potassium voltage-gated ion channel; N-acetyltransferase; angiotensin I-converting enzyme; potassium inwardly rectifying channel; G-protein coupled receptor family; solute carrier organic anion transporter family; nuclear receptor family; sulfotransferase family; solute carrier family. The sequence function of these 55 loci was classified mainly into eight types: intron variant; upstream transcript variant; downstream transcript variant; coding sequence variant; missense; 3 untranslated region (UTR) variant; non-coding transcript variant; 5 UTR variant.

All selected loci met the HardyWeinberg equilibrium (p>0.05) with a call rate >99.9%. Among the 26 populations studied, GWD, YRI, GIH, ESN, MSL, TSI, PJL, ACB, FIN and IBS were the top-10 populations which showed significant differences compared with the Blang population (>35 loci) (Table 2). Conversely, CHB, JPT, CDX, CHS and KHV populations showed the most similarities with the Blang population (genotype distribution <20 loci). The genotype distribution of 2734 loci in the Blang population showed a significant difference from that of 11 other populations, (LWK, CEU, ITU, STU, PUR, CLM, GBR, ASW, BEB, MXL and PEL). On the one hand, among 26 populations, the GWD population had the greatest number of significantly different loci after Bonferroni correction compared with that in the Blang population, indicating that GWD was the most different population from the Blang population. This significant difference may have resulted from a difference in the genetic background between them. On the other hand, the KHV population showed the least number of different loci after Bonferroni correction. The relatively greater number of similar loci was probably caused by a similar geographic location (East Asian) between them. The distribution of genotypes and allele frequencies of the seven significantly different SNPs are shown in Supplemental Table 2 and Supplemental Figures 17.

Table 2 The Genotype Distribution Difference Between Blang and 26 Other Populations After Bonferronis Multiple Adjustments

Among 55 loci, after Bonferroni correction between the Blang population and 26 other populations, the distribution of genotype frequencies was significantly different in five loci: rs750155 of sulfotransferase family 1A member gene (SULT1A1), rs4291 of ACE, rs1051298, rs1131596 and rs1051296 of SLC19A1. Besides, the genotype distribution of rs1800764 (ACE) and rs1065852 (CYP2D6) was different in all populations except for PEL and LWK, respectively. Conversely, the genotype distribution of rs1801028 of the dopamine receptor D2 gene (DRD2) was significantly different only in the GIH population compared with that in the Blang population. In addition to the eight loci mentioned above, the genotype distribution of the remaining loci in the Blang population also showed a significant difference compared with that in the other 26 populations, but to different degrees.

The MAF distribution of seven significantly different SNPs is shown in Table 3 and Figure 1. The MAFs of rs1065852 (CYP2D6) and rs750155 (SULT1A1) showed the greatest similarities among SAS, EUR, AFR and AMR populations, but also showed the largest fluctuation between the Blang population and SAS, EUR, AFR and AMR populations. The MAFs of rs1800764 (ACE) and rs1131596 (SLC19A1) among the seven subpopulations of AFR showed distinct differences when compared with those of the Blang population. However, the MAFs of rs4291 (ACE), rs1051298 (SLC19A1), and rs1051296 (SLC19A1) showed relatively less fluctuation between the Blang population and the other 26 populations. Besides, the MAFs of rs1800764 (ACE) and rs750155 (SULT1A1) in the Blang population were close to those of the PEL population, even though most of other populations showed distinct differences on it. To better observe the phenotypes of these seven significantly different SNPs in the Blang population, their clinical and variant annotations were retrieved from PharmGKB (Supplemental Table 3 and Supplemental Table 4, respectively).

Table 3 The Minor Allele Frequency Distribution of Seven SNPs Among 27 Populations

Figure 1 The minor allele frequency (MAF) distribution of seven significantly different SNPs between Blang population and other 26 populations. The value of the Y axis represents the MAF.

We genotyped 55 VIP variants from PharmGKB and compared the genotype distribution and MAF of variants in a Blang population with those of 26 other populations. Among 55 loci, the genotype distribution of five SNPs (rs750155 (SULT1A1), rs4291 (ACE), rs1051298 (SLC19A1), rs1051296 (SLC19A1) and rs1131596 (SLC19A1)) was significantly different in the Blang population compared with that in the other 26 populations. Two SNPs (rs1800764 (ACE) and rs1065852 (CYP2D6)) showed a significantly different genotype distribution in the Blang population compared with that in the other 25 populations but, compared with PEL and LWK populations, respectively, a significant difference was not observed. In addition, the MAFs of rs1065852 (CYP2D6) and rs750155 (SULT1A1) showed the greatest fluctuation between the Blang population and SAS, EUR, AFR and AMR populations.

SULT1A1, encoded by SULT1A1, is an isoform of sulfotransferases. The latter are phase-II detoxification enzymes and have a crucial role in the metabolism of several xenobiotics and endogenous compounds (eg, tamoxifen).30,31 High polymorphism of SULT1A1 has been reported among Caucasian, Chinese, AfricanAmerican and Korean populations.32,33 Moyer et al reported that the genetic variation in SULT1A1, including rs750155, which is located in the promoter region (the short arm of chromosome 16) of SULT1A1, could explain (at least in part) the interindividual variability in the onset of menopause and symptoms before initiation of hormone therapy, and may represent a step towards individualizing decisions for hormone therapy.34 Besides, Innocenti et al demonstrated that allele T of rs750155 is not associated with the pharmacokinetic parameters of ABT-751 (novel anticancer agent) in people with neoplasms as compared with allele C.35 In our study, the genotype frequency distribution of rs750155 (SULT1A1) in the Blang population was significantly different from that of the other 26 populations. Also, the MAF distribution of rs750155 (SULT1A1) showed the greatest difference between the Blang population and SAS, EUR, AFR and AMR populations. Besides, the allele T frequency of rs750155 was far higher than that of allele C [T (76.7%) vs C (23.3%)], which indicated that the T allele of rs750155 in members of the Blang population with neoplasms could metabolize ABT-751 more readily.

ACE, encoded by ACE, is an enzyme that can affect the reninangiotensin system and regulation of blood pressure.36,37 ACE inhibitors are first-line treatment for hypertension. They can favorably affect the vascular remodeling of patients with myocardial infarction and heart failure, and reduce its risk and mortality.38 The functional SNPs rs1800764 (ACE) and rs4291 (ACE) are located in the promoter region (chromosome 17) of ACE.39 Linkage disequilibrium has been identified between these two SNPs in ACE in multiple populations.40,41 These two SNPs possess the same pharmacokinetic characteristics and are associated with the risk of breast cancer, end-stage renal disease and Alzheimers disease.4244 The SNPs rs1800764 (ACE) and rs4291 (ACE) show different drug responses in different populations.4547 In the present study, the genotype frequency distribution of SNPs rs1800764 (ACE) and rs4291 (ACE) in the Blang population was different from that of the other populations studied, even though rs1800764 (ACE) was not significantly different in the Blang population compared with that in the PEL population. Besides, the MAF of rs1800764 (ACE) in the AFR population showed a distinct difference compared with that in the Blang population. However, rs4291 (ACE) showed relatively less fluctuation of MAF between the Blang population and the other 26 populations. Although the association between SNPs rs1800764 (ACE) and rs4291 (ACE) and the risk of breast cancer, end-stage renal disease and Alzheimers disease have not been elucidated in the Blang population, our pharmacogenomics study of the SNPs rs1800764 (ACE) and rs4291 (ACE) in the Blang population is important for disease prevention and safe use of drugs.

Reduced folate carrier protein 1 (RFC1), encoded by SLC19A1, is a high-capacity, bidirectional transporter of 5-methyl-tetrahydrofolate and thiamine monophosphate. RFC1 is involved in the uptake, homeostasis, folate deficiency as well as the transportation and sensitivity of antifolate chemotherapeutic agents, such as methotrexate.4850 The SNPs rs1051298 and rs1051296 are intron variants, and rs1131596 is the missense variant of SLC19A1. Scholars have postulated genotype (AA + AG) of rs1051298 to be associated with reduced overall survival upon treatment with pemetrexed in people with non-small-cell lung cancer or mesothelioma compared with that with genotype GG.51 In addition, allele G of rs1051298 has been reported to be associated with longer progression-free survival after treatment with bevacizumab and pemetrexed in patients with lung neoplasms compared with that with allele A of rs1051298.52 Besides, the SNP rs1051296 is associated with higher plasma concentrations of methotrexate in pediatric patients with acute lymphoblastic leukemia.53 Evidence suggests that rs1131596 variants have a positive effect on methotrexate toxicity.54 Research has shown that the SNP rs1131596-G is not associated with alteration of the concentration or side-effects of methotrexate treatment compared with that of the SNP rs1131596-A in Chinese children with precursor cell lymphoblastic leukemia/lymphoma and people with rheumatoid arthritis.55 In our study, the genotype distribution of rs1051298, rs1051296, and rs1131596 in the Blang population was significantly different from that of the other 26 populations. MAF analyses showed that rs1051298 (SLC19A1), and rs1051296 (SLC19A1) showed relatively less fluctuation between the Blang population and the other 26 populations, even though the MAF of rs1131596 (SLC19A1) in the AFR population showed a distinct difference when compared with that of the Blang population. These observations suggested that pharmacogenomic research of variants of rs1051298, rs1051296 and rs1131596 may help to provide guidance for individualized drug use for the Blang population.

CYP2D6, encoded by CYP2D6, is an enzyme of the cytochrome P450 superfamily. It is involved in the metabolism of 25% of drugs in common use in the clinic.56 Debrisoquine and sparteine are CYP2D6 variation-related drugs.57 The genetic variation of CYP2D6 has been reported to be closely related to the metabolism of antipsychotic, antiarrhythmic and antiepileptic drugs.5860 The SNP rs1065852 is an intron variant of CYP2D6. It is related to alteration of the encoded amino acids of CYP2D6 protein, reduction of CYP2D6 activity and to have a poor metabolizer phenotype.61 In addition, the genotype GG of rs1065852 (CYP2D6) is a factor of increased corrected QT (QTc) interval after treatment with iloperidone in people suffering from schizophrenia.61 The distribution of rs1065852 (CYP2D6) has been shown to be significantly different in a Zhuang population as compared with that in 11 other ethnic groups by Liu et al.3 In the present study, the genotype distribution of rs1065852 (CYP2D6) was different in the Blang population when compared with that in all other ethnic groups except for the LWK population, and the MAF distribution showed the largest fluctuation between the Blang population and SAS, EUR, AFR and AMR populations. Hence, the different corrected QTc interval may occur in schizophrenia patients of Blang ethnicity upon treatment with iloperidone. All the above evidence indicated the non-negligible roles of CYP2D6 (rs1065852) in effective drug usage and normal drug metabolism in Blang individuals.

We provided information on the genetic polymorphisms of VIP variants in the Blang population from Yunnan Province. Nevertheless, the sample size was small: a much larger sample size is needed to verify our results.

The genotype distribution of five SNPs (rs750155 (SULT1A1), rs4291 (ACE), rs1051298 (SLC19A1), rs1051296 (SLC19A1) and rs1131596 (SLC19A1)) was significantly different in the Blang population compared with that in the other 26 populations tested. Two SNPs (rs1800764 (ACE) and rs1065852 (CYP2D6)) showed a significantly different genotype distribution in the Blang population as compared with all other populations tested except for PEL and LWK populations, respectively. The MAF of rs1065852 (CYP2D6) and rs750155 (SULT1A1) showed the largest fluctuation between the Blang population and SAS, EUR, AFR and AMR populations. Our data can provide theoretical guidance for safe and efficacious personalized drug use in the Blang population.

VIPs, very important pharmacogenes; BP, Blang population; GD, genotype distribution; CDX, Chinese Dai in Xishuangbanna, China; CHB, Han Chinese in Beijing, China; CHS, Southern Han Chinese, China; JPT, Japanese in Tokyo, Japan; KHV, Kinh in Ho Chi Minh City, Vietnam; BEB, Bengali in Bangladesh; GIH, Gujarati Indian in Houston, Texas; ITU, Indian Telugu in the UK; PJL, Punjabi in Lahore, Pakistan; STU, Sri Lankan Tamil in the UK; CEU, Western European ancestry; FIN, Finnish in Finland; GBR, British in England and Scotland; IBS, Iberian populations in Spain; TSI, Toscani in Italy; ACB, African Caribbeans in Barbados; ASW, African Ancestry in Southwest USA; ESN, Esan in Nigeria; GWD, Gambian in Western Divisions, The Gambia; LWK, Luhya in Webuye, Kenya; MSL, Mende in Sierra Leone; YRI, Yoruba in Ibadan, Nigeria; CLM, Colombian in Medellin, Colombia; MXL, Mexican Ancestry in Los Angeles, Colombia; PEL, Peruvian in Lima, Peru; PUR, Puerto Rican in Puerto Rico; LD, linkage disequilibrium; MTX, methotrexate; SULT1A1, sulfotransferase family 1A member 1; ACE, angiotensin I-converting enzyme; SLC19A1,solute carrier family 19 Member 1; CYP2D6, cytochrome P450 family 2 subfamily D member 6; VKORC, vitamin K epoxide reductase complex; CYP2C9, cytochrome P450 family 2 subfamily C member 9; DRD2, dopamine receptor D2; RFC1, reduced folate carrier protein 1; PCR, polymerase chain reaction; MAF, minor allele frequency; SNP, single-nucleotide polymorphism; PharmGKB, Pharmacogenomics Knowledge Base; SAS, South Asian; EUR, European; AFR, African; AMR, American.

All relevant data are available within the manuscript. Scholars interested in other information from this study should contact the corresponding author.

All experiments were conducted in accordance with the Declaration of Helsinki 1964 and its later amendments. Each participant provided written informed consent before study commencement. The study protocol was approved (2019-12) by the Ethics Committee of Xizang Minzu University.

We express our thanks to all study participants. We also thank the clinicians and hospital staff who worked on sample/data collection in this study.

This work was performed in collaboration between all authors. YLW and LNP carried out the draft and improvement of the manuscript. HYL, ZHZ and SSX designed the tables and figures. DDL and CJH performed the SNP genotyping analysis. TBJ and LW conceived of the study, worked on associated data collection and statistical analysis, participated in the coordination and funded of the study. All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work. YLW and LNP contributed equally to this article. Yuliang Wang and Linna Peng are co-first authors.

The study was supported by the Talent Development Supporting Project entitled Tibet-Shaanxi Himalaya of Xizang Minzu University (2020 Plateau Scholar), Major Science and Technology Research Projects of Xizang (Tibet) Autonomous Region (2015XZ01G23), and Natural Science Foundation of Tibet Autonomous Region (2015ZR-13-19).

The authors declare that they have no competing interests.

1. Kalow W, Tang BK, Endrenyi L. Hypothesis: comparisons of inter- and intra-individual variations can substitute for twin studies in drug research. Pharmacogenetics. 1998;8(4):283289. doi:10.1097/00008571-199808000-00001

2. Zhou SF, Liu JP, Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug Metab Rev. 2009;41(2):89295. doi:10.1080/03602530902843483

3. Liu Y, Li H, Cao K, et al. Genetic variation of pharmacogenomic VIP variants in Zhuang nationality of southern China. Pharmacogenomics J. 2021;21(1):6068. doi:10.1038/s41397-020-0177-y

4. He C, Peng L, Xing S, Li D, Wang L, Jin T. Population genetic difference of pharmacogenomic VIP variants in the Tibetan population. Pharmgenomics Pers Med. 2021;14:10271040. doi:10.2147/PGPM.S316711

5. Cecchin E, Stocco G. Pharmacogenomics and personalized medicine. Genes. 2020;11(6):679683. doi:10.3390/genes11060679

6. Barbarino JM, Whirl-Carrillo M, Altman RB, Klein TE. PharmGKB: a worldwide resource for pharmacogenomic information. Wiley Interdiscip Rev Syst Biol Med. 2018;10(4):113.

7. Bader LA, Elewa H, Novelli G. The impact of genetic and non-genetic factors on warfarin dose prediction in MENA region: a systematic review. PLoS One. 2016;11(12):115. doi:10.1371/journal.pone.0168732

8. Kim GJ, Lee SY, Park JH, Ryu BY, Kim JH. Role of preemptive genotyping in preventing serious adverse drug events in south Korean patients. Drug Safe. 2017;40(1):6580. doi:10.1007/s40264-016-0454-5

9. Arbitrio M, Scionti F, Di Martino MT, et al. Pharmacogenomics biomarker discovery and validation for translation in clinical practice. Clin Transl Sci. 2021;14(1):113119. doi:10.1111/cts.12869

10. Wang B, Hu W, Wang J, et al. HLA-DPB1 polymorphism in Blang and Puyi ethnic groups of southwest China inferred from sequence-based typing. Tissue Antigens. 2008;71(1):8184. doi:10.1111/j.1399-0039.2007.00963.x

11. Zeng WM, Yang J, Dong YL, et al. The frequency distribution of flavin-containing monooxygenase 3 mutant alleles in 28 populations from Yunnan. Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2003;20(4):318321.

12. Li L, Zhang Y, Wang W, et al. Allele frequencies of 20 autosomal STR loci for 207 unrelated individuals of the Blang people in China. Int J Legal Med. 2020;134(3):987988. doi:10.1007/s00414-019-02192-0

13. Zhang C, Guo W, Cheng Y, et al. Genetic analysis of pharmacogenomic VIP variants in the Blang population from Yunnan Province of China. Mol Genet Genom Med. 2019;7(5):117. doi:10.1002/mgg3.574

14. Rosmarin D, Palles C, Pagnamenta A, et al. A candidate gene study of capecitabine-related toxicity in colorectal cancer identifies new toxicity variants at DPYD and a putative role for ENOSF1 rather than TYMS. Gut. 2015;64(1):111120. doi:10.1136/gutjnl-2013-306571

15. Fritsche E, Baek SJ, King LM, Zeldin DC, Eling TE, Bell DA. Functional characterization of cyclooxygenase-2 polymorphisms. J Pharmacol Exp Ther. 2001;299(2):468476.

16. Pan R, Qi X, Wang F, Chong Y, Li X, Chen Q. Correlations of calcium voltage-gated channel subunit alpha1 A (CACNA1A) gene polymorphisms with benign paroxysmal positional vertigo. Med Sci Monit. 2019;25:946951. doi:10.12659/MSM.912359

17. Klein A, Lillis S, Munteanu I, et al. Clinical and genetic findings in a large cohort of patients with ryanodine receptor 1 gene-associated myopathies. Hum Mutat. 2012;33(6):981988. doi:10.1002/humu.22056

18. Saloner R, Paolillo EW, Kohli M, et al. Genetic variation in alcohol dehydrogenase is associated with neurocognition in men with HIV and history of alcohol use disorder: preliminary findings. J Neurovirol. 2020;26(2):214225. doi:10.1007/s13365-019-00825-z

19. Li L, Shen C, Yao Z, Liang J, Huang C. Genetic variants of potassium voltage-gated channel genes (KCNQ1, KCNH2, and KCNE1) affected the risk of atrial fibrillation in elderly patients. Genet Test Mol Biomarkers. 2015;19(7):359365. doi:10.1089/gtmb.2014.0307

20. Song Y, Qi X, Liu X. N-acetyltransferase 2 polymorphism is associated with bladder cancer risk: an updated meta-analysis based on 54 case-control studies. Gene. 2020;757:139.

21. Stoffel M, Espinosa R, Powell KL, Philipson LH, Le Beau MM, Bell GI. Human G-protein-coupled inwardly rectifying potassium channel (GIRK1) gene (KCNJ3): localization to chromosome 2 and identification of a simple tandem repeat polymorphism. Genomics. 1994;21(1):254256. doi:10.1006/geno.1994.1253

22. Parry DA, Smith CE, El-Sayed W, et al. Mutations in the pH-sensing G-protein-coupled receptor GPR68 cause amelogenesis imperfecta. Am J Hum Genet. 2016;99(4):984990. doi:10.1016/j.ajhg.2016.08.020

23. Collins KS, Metzger IF, Gufford BT, et al. Influence of uridine diphosphate glucuronosyltransferase family 1 member A1 and solute carrier organic anion transporter family 1 member B1 polymorphisms and efavirenz on bilirubin disposition in healthy volunteers. Drug Metab Dispos. 2020;48(3):169175. doi:10.1124/dmd.119.089052

24. Zimmer V, Liebe R, Lammert F. Nuclear receptor variants in liver disease. Dig Dis. 2015;33(3):415419. doi:10.1159/000371695

25. Arslan S, Silig Y, Pinarbasi H. Sulfotransferase 1A1 Arg(213)His polymorphism and prostate cancer risk. Exp Ther Med. 2011;2(6):11591162. doi:10.3892/etm.2011.334

26. Muminovic Umihanic M, Babic R, Kravic N, et al. Associations between polymorphisms in the solute carrier family 6 member 3 and the myelin basic protein gene and posttraumatic stress disorder. Psychiatr Danub. 2019;31(2):235240. doi:10.24869/psyd.2019.235

27. Cambien F, Evans A. Angiotensin I converting enzyme gene polymorphism and coronary heart disease. Eur Heart J. 1995;16(Suppl K):1322. doi:10.1093/eurheartj/16.suppl_K.13

28. Gabriel S, Ziaugra L, Tabbaa D. SNP genotyping using the Sequenom massARRAY iPLEX platform. Curr Protocols Human Genet. 2009;Chapter 2:Unit2.12.

29. Thomas RK, Baker AC, Debiasi RM, et al. High-throughput oncogene mutation profiling in human cancer. Nat Genet. 2007;39(3):347351. doi:10.1038/ng1975

30. Nowell S, Falany CN. Pharmacogenetics of human cytosolic sulfotransferases. Oncogene. 2006;25(11):16731678. doi:10.1038/sj.onc.1209376

31. Daniels J, Kadlubar S. Pharmacogenetics of SULT1A1. Pharmacogenomics. 2014;15(14):18231838. doi:10.2217/pgs.14.134

32. Carlini EJ, Raftogianis RB, Wood TC, et al. Sulfation pharmacogenetics: SULT1A1 and SULT1A2 allele frequencies in Caucasian, Chinese and African-American subjects. Pharmacogenetics. 2001;11(1):5768. doi:10.1097/00008571-200102000-00007

33. Kim KA, Lee SY, Park PW, Ha JM, Park JY. Genetic polymorphisms and linkage disequilibrium of sulfotransferase SULT1A1 and SULT1A2 in a Korean population: comparison of other ethnic groups. Eur J Clin Pharmacol. 2005;61(10):743747. doi:10.1007/s00228-005-0989-3

34. Moyer AM, de Andrade M, Weinshilboum RM, Miller VM. Influence of SULT1A1 genetic variation on age at menopause, estrogen levels, and response to hormone therapy in recently postmenopausal white women. Menopause (New York, NY). 2016;23(8):863869. doi:10.1097/GME.0000000000000648

35. Innocenti F, Ramrez J, Obel J, et al. Preclinical discovery of candidate genes to guide pharmacogenetics during Phase I development: the example of the novel anticancer agent ABT-751. Pharmacogenet Genomics. 2013;23(7):374381. doi:10.1097/FPC.0b013e3283623e81

36. de Oliveira FF, Bertolucci PH, Chen ES, Smith MC. Brain-penetrating angiotensin-converting enzyme inhibitors and cognitive change in patients with dementia due to Alzheimers disease. JAD. 2014;42(Suppl 3):S3214. doi:10.3233/JAD-132189

37. Rahimi Z. ACE insertion/deletion (I/D) polymorphism and diabetic nephropathy. J Nephropathol. 2012;1(3):143151. doi:10.5812/nephropathol.8109

38. Jeffrey LP. Progression of cardiovascular damage: the role of renin-angiotensin system blockade. Am J Cardiol. 2010;1(Suppl105):111.

39. de Oliveira FF, Chen ES, Smith MC, Bertolucci PHF. Pharmacogenetics of angiotensin-converting enzyme inhibitors in patients with Alzheimers disease dementia. Curr Alzheimer Res. 2018;15(4):386398. doi:10.2174/1567205014666171016101816

40. Reba M, Kharrat N, Ayadi I, Reba A. Haplotype structure of five SNPs within the ACE gene in the Tunisian population. Ann Hum Biol. 2006;33(3):319329. doi:10.1080/03014460600621977

41. Kharrat N, Abdelmouleh W, Abdelhedi R, Alfadhli S, Rebai A. The linkage disequilibrium pattern of the angiotensin converting enzyme gene in Arabic and Asian population groups. Ann Hum Biol. 2012;39(6):538540. doi:10.3109/03014460.2012.713509

42. Ding P, Yang Y, Ding S, Sun B. Synergistic association of six well-characterized polymorphisms in three genes of the renin-angiotensin system with breast cancer among Han Chinese women. JRAAS. 2015;16(4):12321239. doi:10.1177/1470320314542828

43. Su SL, Yang HY, Wu CC, et al. Gene-gene interactions in renin-angiotensin-aldosterone system contributes to end-stage renal disease susceptibility in a Han Chinese population. Sci World J. 2014;2014:110.

44. Miners S, Ashby E, Baig S, et al. Angiotensin-converting enzyme levels and activity in Alzheimers disease: differences in brain and CSF ACE and association with ACE1 genotypes. Am J Transl Res. 2009;1(2):163177.

45. Kim TH, Chang HS, Park SM, et al. Association of angiotensin I-converting enzyme gene polymorphisms with aspirin intolerance in asthmatics. Clin Exp Allergy. 2008;38(11):17271737. doi:10.1111/j.1365-2222.2008.03082.x

46. Ezzidi I, Mtiraoui N, Kacem M, Chaieb M, Mahjoub T, Almawi WY. Identification of specific angiotensin-converting enzyme variants and haplotypes that confer risk and protection against type 2 diabetic nephropathy. Diabetes Metab Res Rev. 2009;25(8):717724. doi:10.1002/dmrr.1006

47. Ferreira de Oliveira F, Berretta JM, Suchi Chen E, Cardoso Smith M, Ferreira Bertolucci PH. Pharmacogenetic effects of angiotensin-converting enzyme inhibitors over age-related urea and creatinine variations in patients with dementia due to Alzheimer disease. Colombia medica (Cali, Colombia). 2016;47(2):7680. doi:10.25100/cm.v47i2.2188

48. Dixon KH, Lanpher BC, Chiu J, Kelley K, Cowan KH. A novel cDNA restores reduced folate carrier activity and methotrexate sensitivity to transport deficient cells. J Biol Chem. 1994;269(1):1720. doi:10.1016/S0021-9258(17)42301-5

49. Westerhof GR, Schornagel JH, Kathmann I, et al. Carrier- and receptor-mediated transport of folate antagonists targeting folate-dependent enzymes: correlates of molecular-structure and biological activity. Mol Pharmacol. 1995;48(3):459471.

50. Ifergan I, Jansen G, Assaraf YG. The reduced folate carrier (RFC) is cytotoxic to cells under conditions of severe folate deprivation. RFC as a double edged sword in folate homeostasis. J Biol Chem. 2008;283(30):2068720695. doi:10.1074/jbc.M802812200

51. Corrigan A, Walker JL, Wickramasinghe S, et al. Pharmacogenetics of pemetrexed combination therapy in lung cancer: pathway analysis reveals novel toxicity associations. Pharmacogenomics J. 2014;14(5):411417. doi:10.1038/tpj.2014.13

52. Adjei AA, Mandrekar SJ, Dy GK, et al. Phase II trial of pemetrexed plus bevacizumab for second-line therapy of patients with advanced non-small-cell lung cancer: NCCTG and SWOG study N0426. J Clin OIncol. 2010;28(4):614619. doi:10.1200/JCO.2009.23.6406

53. Wang SM, Sun LL, Wu WS, Yan D. MiR-595 suppresses the cellular uptake and cytotoxic effects of methotrexate by targeting SLC19A1 in CEM/C1 cells. Basic Clin Pharmacol Toxicol. 2018;123(1):813. doi:10.1111/bcpt.12966

54. Chatzikyriakidou A, Georgiou I, Voulgari PV, Papadopoulos CG, Tzavaras T, Drosos AA. Transcription regulatory polymorphism 43T>C in the 5-flanking region of SLC19A1 gene could affect rheumatoid arthritis patient response to methotrexate therapy. Rheumatol Int. 2007;27(11):10571061. doi:10.1007/s00296-007-0339-0

55. Liu SG, Gao C, Zhang RD, et al. Polymorphisms in methotrexate transporters and their relationship to plasma methotrexate levels, toxicity of high-dose methotrexate, and outcome of pediatric acute lymphoblastic leukemia. Oncotarget. 2017;8(23):3776137772. doi:10.18632/oncotarget.17781

56. Ingelman-Sundberg M, Sim SC, Gomez A, Rodriguez-Antona C. Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacol Ther. 2007;116(3):496526.

57. Evans DA, Harmer D, Downham DY, et al. The genetic control of sparteine and debrisoquine metabolism in man with new methods of analysing bimodal distributions. J Med Genet. 1983;20(5):321329. doi:10.1136/jmg.20.5.321

58. Jrgens G, Andersen SE, Rasmussen HB, et al. Effect of routine cytochrome P450 2D6 and 2C19 genotyping on antipsychotic drug persistence in patients with schizophrenia: a randomized clinical trial. JAMA Netw Open. 2020;3(12):112. doi:10.1001/jamanetworkopen.2020.27909

59. Hamm BS, Rosenthal LJ. Psychiatric aspects of chloroquine and hydroxychloroquine treatment in the wake of Coronavirus disease-2019: psychopharmacological interactions and neuropsychiatric sequelae. Psychosomatics. 2020;61(6):597606. doi:10.1016/j.psym.2020.06.022

60. Lpez-Garca MA, Feria-Romero IA, Serrano H, et al. Influence of genetic variants of CYP2D6, CYP2C9, CYP2C19 and CYP3A4 on antiepileptic drug metabolism in pediatric patients with refractory epilepsy. Pharmacolog Rep. 2017;69(3):504511. doi:10.1016/j.pharep.2017.01.007

61. Potkin SG, Preskorn S, Hochfeld M, Meng X. A thorough QTc study of 3 doses of iloperidone including metabolic inhibition via CYP2D6 and/or CYP3A4 and a comparison to quetiapine and ziprasidone. J Clin Psychopharmacol. 2013;33(1):310. doi:10.1097/JCP.0b013e31827c0314

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Very important pharmacogene variants in the Blang population | PGPM - Dove Medical Press

DUBLIN--(BUSINESS WIRE)--The "Gene Editing Global Market Report 2021: COVID-19 Growth and Change to 2030" report has been added to ResearchAndMarkets.com's offering.

The global gene editing market is expected to grow from $4.25 billion in 2020 to $4.53 billion in 2021 at a compound annual growth rate (CAGR) of 6.6%. The market is expected to reach $7.27 billion in 2025 at a CAGR of 12.6%.

Major players in the gene editing market are CRISPR, GenScript USA Inc., Horizon Discovery Group plc, Integrated DNA Technologies and New England Biolabs.

The gene editing market consists of sales of gene editing technology such as CRISPR/CAS9, zinc finger nucleus, and talens and related services. Gene editing technology allows genetic material to change genetic code at particular location in a genome. It involves cell line engineering, animal genetic engineering and plant genetic engineering.

The gene editing market covered in this report is segmented by technology into CRISPR, TALEN, ZFN. It is also segmented by end users into biotechnology, pharmaceutical, contract research organization and by application into animal genetic engineering, plant genetic engineering, cell line engineering.

Infectious diseases are constantly on the rise. For instance, according to the World Health Organization (WHO), infectious diseases kill more than 17 million people per year. In addition to that, according to the AP-NORC (a research initiative by the Associated Press and the University of Chicago) survey, out of 1,067 adults in the US surveyed, 71% are in favor of gene editing for the treatment of incurable, hereditary diseases such as Huntington's disease and 67% of Americans support the use of gene editing to prevent diseases such as cancer.

Ethical issues in general public with respect to gene editing is one of the major restraining factors for the market. Many researchers and ethicist have argued against gene editing due to different reasons such as off-target effect (edits in the wrong place), mosaicism (when only some of the cells carry the edits) and safety concerns. Some even argued that gene editing will lead to the creation of classes of individuals who will be genetically modified to be able to do things that a normal human being is not supposed to do according to the laws of nature. Due to these reasons, gene editing is still not considered to be safe and effective by many nations and international organizations.

Gene editing (also called genome editing) is a group of technologies that allow the researchers to change an organism's DNA by adding, removing or altering genetic material at particular locations in the genome. The emergence of advanced genome editing techniques is one of the major trend in the gene editing market.

The new techniques in genome editing are relatively inexpensive and can be used in a variety of application areas such as improving the food supply in agriculture, rectifying specific genetic mutations in the human genome and preventing the spread of diseases. For instance, CRISPR-Cas9 is a gene editing technique and stands for Clustered Regularly Interspace Short Palindromic Repeats.

The technique uses a strand of DNA as molecular scissors used to make cuts in DNA at specific points to make space to add new genomes. This technique is faster, cheaper, more accurate and efficient than other existing genome editing methods. Companies investing in CRISPR technology are Crispr therapeutics (CRSP), Intellia Therapeutics (NTLA), and Editas medicine.

The rising infectious diseases acts as one of the major drivers of the gene editing market. Gene editing techniques are used for detection of infectious diseases such as HIV. Infectious diseases are caused by microorganisms like bacteria, viruses, fungi, and parasites. Gene therapy treats the infectious diseases by blocking the replication of the infectious agent that causes the disease at the extracellular level. Gene editing introduces new genetic material into the cells of living organisms with the intention of treating the diseases.

European regulatory framework divided gene therapy into two categories, germline gene therapy, and somatic gene therapy. In germ line gene therapy, modified genes will be passed on to next generations whereas its not the same case with somatic gene therapy. Current regulation by the EU has only allowed somatic gene therapy, therefore, germline gene therapy is banned.

The European Medical Association provides guidelines on gene therapy for preparing market authorization application to obtain approval from the authority to carry on research and development activities in gene therapy. For instance, the EU provides guidance note on gene therapy medicinal product which is intended for use in humans, defines scientific principles and provide guidance for development and evaluation of gene therapy products.

Key Topics Covered:

1. Executive Summary

2. Gene Editing Market Characteristics

3. Gene Editing Market Trends and Strategies

4. Impact Of COVID-19 On Gene Editing

5. Gene Editing Market Size and Growth

5.1. Global Gene Editing Historic Market, 2015-2020, $ Billion

5.1.1. Drivers Of the Market

5.1.2. Restraints On the Market

5.2. Global Gene Editing Forecast Market, 2020-2025F, 2030F, $ Billion

5.2.1. Drivers Of the Market

5.2.2. Restraints On the Market

6. Gene Editing Market Segmentation

6.1. Global Gene Editing Market, Segmentation by Technology, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

6.2. Global Gene Editing Market, Segmentation by End Users, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

6.3. Global Gene Editing Market, Segmentation by Application, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

7. Gene Editing Market Regional and Country Analysis

7.1. Global Gene Editing Market, Split by Region, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

7.2. Global Gene Editing Market, Split by Country, Historic and Forecast, 2015-2020, 2020-2025F, 2030F, $ Billion

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/ns9rjy

with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

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Global Gene Editing Market Research Report 2021 Featuring CRISPR, GenScript, Horizon Discovery Group, Integrated DNA Technologies and New England...

A2Z Market Research announces the release of the Gene Sequencing market research report. It is a comprehensive and in-depth analysis of the global market. It covers a wide range of market potential and restrictions. The market is predicted to grow at a healthy pace in the coming years.When compiling this all-encompassing Gene Sequencing research report, each and every market parameter is taken into account, resulting in precise and accurate market data.

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Gene Sequencing Market is growing at a 11% of CAGR during the forecast period. The research report also focuses on the evolving facts in the Gene Sequencing market that affect market, demand, and supply. This report provides an in-depth review of the current state of the Gene Sequencing market, daring its growth and all other essential elements in all of the major markets of the county.

The report includes information on the Gene Sequencing markets most prominent key players. It presents a gigantic amount of market data, compiled using myriad primary and secondary research practices. The data in this report has been reduced on a business basis using various systematic methods. Players enlisted in report are Roche, Johnson & Johnson, Illumina, Thermo Fisher Scientific, Beckman Coulter, Pacific Biosciences, Oxford Nanopore, GE Healthcare Life Sciences, Abbott Laboratories

Overview of the market :

For a comprehensive analysis, the Gene Sequencing market is segmented by product type, region, and application. Due to its regional focus, the market is alien to North America, Europe, Asia-Pacific, the Middle East, and Africa as well as Latin America. Major companies are working on distributing their products and services across different regions. In addition, procurements and associations from some of the leading organizations. All of the factors intended to drive the global marketplace are examined in depth. Finally, the research findings and conclusion are thoroughly addressed.

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The report offers the segmentation of the market on the basis of the type and applications.

The segmentation research conducted in this report aids market players in boosting productivity by focusing their organizations efforts and assets on Gene Sequencing market segments that are most beneficial to their goals.

By Type

Emulsion PCRBridge AmplificationSingle-molecule

By end-users

Molecular BiologyEvolutionary BiologyMetagenomicsMedicineOther

Regional coverage:

The report covers global as well as regional Gene Sequencing market focusing on the regions:

? North America

? South America

? Asia and Pacific region

? Middle east and Africa

? Europe

Key Factors Impacting Market Growth:

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Gene Sequencing Market Research, Analysis and Global Study |Roche, Johnson & Johnson, Illumina, Thermo Fisher Scientific - Digital Journal

1Department of Respiratory and Critical Care Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322000, Zhejiang, Peoples Republic of China; 2Department of Respiratory Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua Municipal Central Hospital, Jinhua, 321000, Zhejiang, Peoples Republic of China

Correspondence: Saibin WangDepartment of Respiratory Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua Municipal Central Hospital, Jinhua, 321000, Zhejiang Province, Peoples Republic of ChinaTel +86 579 82552278Fax +86 579 82325006Email [emailprotected]

Purpose: Sleep duration is associated with aging. However, the relationship between sleep duration and the concentration of the protein klotho in the serum remains unknown in the general population of the United States. Hence, this study aimed at exploring the association between them.Methods: Participants whose data included klotho protein and sleep duration variables in the National Health and Nutrition Examination Survey data from 2007 to 2016 were utilized for this analysis.Results: Sleep duration was non-linearly associated with the level of klotho protein in the serum, with a negative association between sleep duration and serum klotho concentration after adjusting for confounding variables ( = 7.6; 95% CI: 11.3, 4.0; P 7.5 hours) revealed that the serum klotho of the participants in the highest tertile (> 7.5 hours) was 21.9 pg/mL lower (95% CI: 38.6, 5.2; P = 0.01) than those in the lowest tertile (Conclusion: Our results revealed that people who sleep more than 7.5 hours per night have decreased levels of the anti-aging protein klotho in their serum, thus being more at risk of aging-related syndromes.

The sleep duration recommended by the National Sleep Foundation in 2015 was as follows: 79 hours in young people and adults, and 78 hours in elderly people. Excessive or insufficient sleep duration is disadvantageous for health. Previous studies have shown that sleep duration is associated with cardiovascular disease, cognitive decline, and metabolic syndrome,13 and aging.4

Klotho protein is a multifunctional protein encoded by the klotho gene, and its expression level is associated with aging.5 Kuro-o found that mice lacking klotho suffer from premature aging syndrome,6 the lack of klotho in serum is also associated with heart aging,7,8 and decreased klotho levels are found in patients with various aging-related diseases, such as metabolic syndrome, cancer, and hypertension.911 In contrast, high level of klotho prolongs lifespan.6

Aging is an inevitable process for human beings. Although there is a fixed limit to human life span,12 the speed of aging is affected by many factors. Aging is affected by environmental, genetic, and epigenetic factors.13 On the other hand, the expression level of klotho may be potentially involved in the relationship between sleep duration and aging. Sleep disorders and aging are common public health problems, and the potential association between sleep duration and the anti-aging protein klotho is largely unexplored. Therefore, the purpose of this study was to investigate the potential association between them using the data of the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2016, performed in the population of the United States. Our hypothesis is that sleep duration is associated with the serum anti-aging protein klotho concentration.

The NHANES contains the data related to the anti-aging protein klotho for the following 5 cycles: 20072008, 20092010, 20112012, 20132014, 20152016. In this study, the National Center for Health Statistics was used to merge the publicly available documents of the 5 cycles of NHANES.

A total of 13,765 participants included in the NHANES database who had klotho in the serum measured from 2007 to 2016 were included in this study. Sleep indicators were considered for those participants who measured klotho.

The serum klotho concentration in the participants was measured using a commercially available Enzyme Linked Immunosorbent Assay (ELISA) kit produced by Immuno-Biological Laboratories international in Japan. The serum samples of the participants were received on dry ice and stored at 80C until analysis. The samples were analyzed in duplicate, and the mean of the two values was used to calculate the final value. Two quality control samples containing low and high concentrations of klotho protein were also analyzed in duplicate by ELISA. Samples with more than 10% repeated results were considered as repeated analysis. If the values of the quality control samples were not within the 2SD range of the specified value, the entire analysis was discarded, and the sample analysis was repeated.

The following self-reported outcomes related to sleep such as sleep duration and trouble sleeping were collected. These questions were asked at home by trained interviewers using the computer-assisted personal interview system.

Sleep duration: According to the questionnaire about the sleeping habits of the participants, the mean sleep duration per night was asked. The range of sleep duration was 112 hours, and the value of more than 12 hours was defined as 12 hours.

Trouble sleeping: Participants were asked whether they informed the doctor about their trouble sleeping. The answer to this question was divided into Yes or No.

Information about age (years), gender, race, education level, marital status, and income level was obtained from the demographic documents. Race was divided into Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black, and other races. Education was divided into <9th grade, 911th grade, high-school grade, college, and college graduate. The marital status was classified as follows: married, widowed, divorced, separated, never married, living with partner. The income level was based on the poverty income ratio, which was considered as a continuous variable in this study. Body mass index (BMI) was obtained from the examination document. Participants who smoke at least 100 cigarettes in their lifetime were considered as smokers. Alcohol use was defined as the consumption of at least 12 cups of alcoholic beverages in the last 12 months. The information regarding the presence of diabetes, hypertension, coronary heart disease, stroke, liver disease, and cancer were obtained from the questionnaire.

Detailed information about klotho, sleep-related variables and covariates is available at http://www.cdc.gov/nchs/nhanes/.

Statistical analysis was performed using R software (The R Foundation; https://www.r-project.org). The factors that influence the levels of klotho in the serum were detected using the univariate analysis. The association between sleep duration and serum klotho levels was assessed using multiple regression model. The threshold effect of sleep duration on serum klotho levels and the smoothing function were calculated using piecewise linear regression. The potential bias of the results due to the use of indicator variables with missing data was assessed by multiple imputation analysis.14

Two adjustment models were evaluated for the levels of klotho in the serum: the adjusted model I, which included variables in which the regression coefficients changed >10% after the basic model was introduced or removed from the full model (age, race); the model II, which included variables in the model I and the regression coefficient of covariable to dependent variable of P < 0.1 (age, race, gender, education level, marital status, smoking, alcohol use, hypertension, coronary heart disease, stroke, liver disease, cancer).15 A value of P < 0.05 was considered to be statistically significant.

The baseline characteristics of the study population are listed in Table 1. The mean age of the participants was 57.7 10.9 years, and 51.6% were females. The mean sleep duration of the participants was 6.9 1.5 hours, and 29.5% of them had trouble sleeping. The mean serum klotho concentration was 854.3 308.2 pg/mL.

Table 1 Baseline Characteristics of the Study Participants

A univariate analysis of the potential influencing factors of the serum klotho level shown in Table 2 revealed that the concentration of klotho protein in the serum decreased when sleep duration increased (P<0.001). In addition, trouble sleeping, age, gender, race, education level, marital status, smoking, alcohol use, hypertension, coronary heart disease, stroke, liver disease, and cancer were associated with the levels of klotho in the serum.

Table 2 Univariate Analysis of Influencing Factors of the Serum Klotho Level

The correlation of the smooth curve fitting suggested a non-linear association between sleep duration and the level of klotho in the serum (Figure 1), and a two-piece linear regression model revealed an inflection point of 5.5 hours (Table 3). The multiple regression analysis shown in Table 4 after adjustment for model I and model II revealed a negative association between sleep duration and the concentration of klotho in the serum in the non-adjustment model ( =11.1; 95% CI: 14.5, 7.6; P<0.001), adjustment model I ( =7.3; 95% CI: 10.8, 3.8; P<0.001) and adjustment model II ( =7.6; 95% CI: 11.3, 4.0; P<0.001). The conversion of the sleep duration from a continuous variable to a categorical variable (tertile: T1: <5.5 hours; T2: 5.57.5 hours; T3: >7.5 hours) revealed that the level of klotho in the serum of the participants in the highest tertile (>7.5 hours) was 21.9 pg/mL (95% CI: 38.6, 5.2; P=0.010) lower than that in the lowest tertile (<5.5 hours). No statistical difference on the concentration of klotho in the serum of the participants was observed between the middle tertile (5.57.5 hours) and the lowest tertile (<5.5 hours) ( = 3.9; 95% CI: 12.1, 20.0; P=0.633). Substitution analysis yielded consistent results, including multiple imputation of missing variables.

Table 3 Threshold Effect Analysis of Sleep Duration on Serum Klotho Using the Two-Piecewise Regression Model

Table 4 Multivariate Regression Analysis of the Association Sleep Duration (Hours) and Serum Klotho (pg/mL)

Figure 1 The fitted smooth curve showed the association between sleep duration and serum klotho levels after adjusting the relative confounding factors (age, race, gender, education level, marital status, smoking, alcohol use, hypertension, coronary heart disease, stroke, liver disease, cancer). The area between the dotted lines represents the 95% confidence interval.

To our knowledge, this work is the first reporting on the association between sleep duration and serum anti-aging protein klotho concentration in the general population of the United States. A nonlinear association between sleep duration and serum klotho level was found. The levels of klotho protein in the serum of the participants whose sleep duration was more than 7.5 hours showed a downward trend as the duration of sleep increased.

Klotho protein is a one-way transmembrane protein, mainly including -klotho and -klotho forms performing different functions.5,16 -Klotho is a multifunctional protein regulating the metabolism of phosphate, calcium and vitamin D,5 while -klotho is involved in key metabolic processes in various tissues.16 Although klotho gene expression is tissue specific,17,18 klotho gene defects cause systemic phenotypes,17 while klotho protein inhibits aging,19 suggesting that klotho protein may be involved in the regulation of the endocrine system. Mice lacking the klotho gene or fibroblast growth factor 23 show phosphate retention and premature aging syndrome, revealing that phosphate metabolism disorders may be the mechanism between klotho gene and aging.20 This evidence was used in this study as a basis to evaluate klotho protein in the serum as an aging-related marker.

Inappropriate sleep duration mainly determines the imbalance between the two sympathetic nervous systems and the hypothalamicpituitaryadrenal axis.21 Moderate sleep duration is crucial for health.22 Insufficient sleep is a public health epidemic as revealed by the United States Centers for Disease Control (www.cdc.gov/features/dssleep/). Insomnia and excessive sleep duration are both involved in the risk of inflammatory and infectious diseases, which in turn cause all-cause mortality.2326 In addition, sleep duration is also associated with some diseases related to aging, and an inverted U-shaped association exists between sleep duration and cognitive aging.27 Insufficient sleep time is independently associated with an increased risk of atherosclerosis,1 and both insufficient and excessive sleep duration are related to an increased risk of cardiovascular disease.28,29 Elderly people with excessive sleep duration have a higher prevalence of stroke compared with elderly people with a sleep duration less than 9 hours.30 These studies revealed that inappropriate sleep duration is a very common and critical public health problem, but it is still overlooked, despite being easy to diagnose and treat. Our study demonstrated that excessive sleep duration (>7.5 hours) was associated with a significant decrease in the anti-aging protein klotho, which is consistent with the previous evidence that excessive sleep duration causes aging.

In a randomized controlled study of 74 participants, Mochn-Benguigui et al report that sleep duration adjusted for fat mass and lean mass index was positively associated with soluble klotho levels.31 In comparison, the results of 13,765 American general population included in our work showed that serum klotho levels increased with sleep duration when sleep duration was within 5.5 hours after adjusting for confounding factors. This is consistent with the conclusion of Mochn-Benguigui et al. However, serum klotho levels were negatively correlated with sleep duration when sleep duration exceeded 7.5 hours. It revealed that excessive sleep duration may be detrimental to the level of serum anti-aging protein klotho. Although previous studies have already demonstrated that sleep duration is related to aging, no studies have reported the relationship between sleep duration and serum anti-aging protein klotho as we did in this work. Our research offers an additional evidence of sleep duration on aging by providing for the first time the relationship between sleep duration and the levels of klotho protein in the serum in the general population of the United States.

This study had several limitations. First of all, this analysis lacked participants sleep details and sleep perception, which may influence the relationship between sleep duration and the concentration of klotho protein in the serum. Secondly, this study was a cross-sectional study. The causal association between sleep duration and serum klotho levels was not evaluated because of time constraints. Thus, the sleep duration was reported by the participants, with inevitable reported bias. Thirdly, this study may also be disturbed by other uncontrollable factors. For example, Pk et al pointed out that lower plasma klotho levels were observed in patients with obstructive sleep apnea (OSA).32 In addition, Oliveira et al found that the concentration of klotho decreased in the cerebrospinal fluid of narcolepsy patients.33 In our study population, whether the participants suffered from these diseases (eg, OSA, narcolepsy) and the proportion of these patients were unknown because such information was not available in the raw data. However, the evaluation was adjusted for several possibly important confounding factors (age; race; gender; education level; marital status; smoking; alcohol use; hypertension; coronary heart disease; stroke; liver disease; cancer). Moreover, this study used data from a large national survey in the United States (NHANES) from 2007 to 2016, which has a large sample size and random sampling, and a good representation of the general population in the United States.

Our study revealed that sleep duration was non-linearly related to the serum anti-aging protein klotho. Indeed, the level of the anti-aging protein klotho in the serum showed a significant downward trend when sleep duration exceeded 7.5 hours, thus being more at risk of aging-related syndromes. Therefore, these people should monitor the level of the anti-aging protein klotho in the serum. Further well-designed prospective studies are needed to evaluate the effect of sleep duration on the anti-aging protein klotho to better understand the impact of the results obtained in this work on health, considering the enormous influence of sleep disorders on public health.

NHANES, National Health and Nutrition Examination Survey; U, Uranium; OR, Odds ratio; CI, Confidence interval; GINA, Global Initiative for Asthma; US, United States; U, uranium; Pb, Lead; Hg, Mercury; As, Arsenic; BMI, Body mass index; ICP-MS, Inductively coupled plasma mass spectrometry; PIR, Poverty-to-income ratio; TP. Total protein; ALT, Alanine aminotransferase; AST, Aspartate aminotransferase; BUN, Blood urea nitrogen; Scr, Serum creatinine; TB, Total bilirubin; SUA, Serum uric acid; Ba, Barium; Cd, Cadmium; Co, Cobalt; Cs, Cesium; Mo, Molybdenum; Sb, Antimony; Tl, Thallium; Tu, Tungsten; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; GFR, Glomerular filtration rate; OSA, Obstructive sleep apnea.

All analyses were performed using R (The R Foundation; https://www.r-project.org) software and Empower (X&Y solutions, Inc., Boston, MA; http://www.empowerstats.com).

The data used in this study are publicly available on the Internet. https://www.cdc.gov/nchs/nhanes/.

Data analyzed in this study were from NHANES. Protocols involved were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board (ERB), and consent from all participants was documented. This study was a secondary analysis of the data, which was deemed exempt from review by the Ethics Committee of the Fourth Affiliated Hospital of Zhejiang University School of Medicine.

All authors consented for publication.

All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval for the version to be published, and agree to be accountable for all aspects of the work.

This study was supported by the Medical and Health Science and Technology Plan Project of Zhejiang Province (No. 2020KY627).

The authors declare that they have no competing interests.

1. Domnguez F, Fuster V, Fernndez-Alvira JM, et al. Association of sleep duration and quality with subclinical atherosclerosis. J Am Coll Cardiol. 2019;73:134144. doi:10.1016/j.jacc.2018.10.060

2. Suh SW, Han JW, Lee JR, et al. Sleep and cognitive decline: a prospective nondemented elderly cohort study. Ann Neurol. 2018;83:472482. doi:10.1002/ana.25166

3. Smiley A, King D, Bidulescu A. The association between sleep duration and metabolic syndrome: the NHANES 2013/2014. Nutrients. 2019;11:2582. doi:10.3390/nu11112582

4. Duffy JF, Zitting KM, Chinoy ED. Aging and circadian rhythms. Sleep Med Clin. 2015;10:423434. doi:10.1016/j.jsmc.2015.08.002

5. Xu Y, Sun Z. Molecular basis of Klotho: from gene to function in aging. Endocr Rev. 2015;36:174193. doi:10.1210/er.2013-1079

6. Klotho KM. Pflugers archives. Eur J Physiol. 2010;459:333343. doi:10.1007/s00424-009-0722-7

7. Chen K, Wang S, Sun QW, et al. Klotho deficiency causes heart aging via impairing the Nrf2-GR pathway. Circ Res. 2021;128:492507. doi:10.1161/circresaha.120.317348

8. Wang Y, Sun Z. Current understanding of klotho. Ageing Res Rev. 2009;8:4351. doi:10.1016/j.arr.2008.10.002

9. Luo L, Hao Q, Dong B, Yang M. The Klotho gene G-395A polymorphism and metabolic syndrome in very elderly people. BMC Geriatr. 2016;16:46. doi:10.1186/s12877-016-0221-6

10. Mencke R, Olauson H, Hillebrands JL. Effects of Klotho on fibrosis and cancer: a renal focus on mechanisms and therapeutic strategies. Adv Drug Deliv Rev. 2017;121:85100. doi:10.1016/j.addr.2017.07.009

11. Wang HL, Xu Q, Wang Z, et al. A potential regulatory single nucleotide polymorphism in the promoter of the Klotho gene may be associated with essential hypertension in the Chinese Han population. Clin Chim Acta. 2010;411:386390. doi:10.1016/j.cca.2009.12.004

12. Dong X, Milholland B, Vijg J. Evidence for a limit to human lifespan. Nature. 2016;538:257259. doi:10.1038/nature19793

13. Khan SS, Singer BD, Vaughan DE. Molecular and physiological manifestations and measurement of aging in humans. Aging Cell. 2017;16:624633. doi:10.1111/acel.12601

14. Melamed A, Margul DJ, Chen L, et al. Survival after minimally invasive radical hysterectomy for early-stage cervical cancer. N Engl J Med. 2018;379:19051914. doi:10.1056/NEJMoa1804923

15. Wang S, Zhang J, Lu X. Non-linear association of plasma level of high-density lipoprotein cholesterol with endobronchial biopsy bleeding in patients with lung cancer. Lipids Health Dis. 2019;18:17. doi:10.1186/s12944-019-0966-y

16. Lee S, Choi J, Mohanty J, et al. Structures of -klotho reveal a zip code-like mechanism for endocrine FGF signalling. Nature. 2018;553:501505. doi:10.1038/nature25010

17. Kuro-o M, Matsumura Y, Aizawa H, et al. Mutation of the mouse klotho gene leads to a syndrome resembling ageing. Nature. 1997;390:4551. doi:10.1038/36285

18. Ben-Dov IZ, Galitzer H, Lavi-Moshayoff V, et al. The parathyroid is a target organ for FGF23 in rats. J Clin Invest. 2007;117:40034008. doi:10.1172/jci32409

19. Kurosu H, Yamamoto M, Clark JD, et al. Suppression of aging in mice by the hormone Klotho. Science. 2005;309:18291833. doi:10.1126/science.1112766

20. Razzaque MS, Sitara D, Taguchi T, St-Arnaud R, Lanske B. Premature aging-like phenotype in fibroblast growth factor 23 null mice is a vitamin D-mediated process. FASEB J. 2006;20:720722. doi:10.1096/fj.05-5432fje

21. Irwin MR. Why sleep is important for health: a psychoneuroimmunology perspective. Ann Rev Psychol. 2015;66:143172. doi:10.1146/annurev-psych-010213-115205

22. Buysse DJ. Sleep health: can we define it? Does it matter? Sleep. 2014;37:917. doi:10.5665/sleep.3298

23. Dew MA, Hoch CC, Buysse DJ, et al. Healthy older adults sleep predicts all-cause mortality at 4 to 19 years of follow-up. Psychosom Med. 2003;65:6373. doi:10.1097/01.psy.0000039756.23250.7c

24. Kripke DF, Garfinkel L, Wingard DL, Klauber MR, Marler MR. Mortality associated with sleep duration and insomnia. Arch Gen Psychiatry. 2002;59:131136. doi:10.1001/archpsyc.59.2.131

25. Mallon L, Broman JE, Hetta J. Sleep complaints predict coronary artery disease mortality in males: a 12-year follow-up study of a middle-aged Swedish population. J Intern Med. 2002;251:207216. doi:10.1046/j.1365-2796.2002.00941.x

26. Vgontzas AN, Fernandez-Mendoza J, Liao D, Bixler EO. Insomnia with objective short sleep duration: the most biologically severe phenotype of the disorder. Sleep Med Rev. 2013;17:241254. doi:10.1016/j.smrv.2012.09.005

27. Leng Y, Yaffe K. Sleep duration and cognitive aging-beyond a U-shaped association. JAMA Netw Open. 2020;3:e2014008. doi:10.1001/jamanetworkopen.2020.14008

28. Tobaldini E, Fiorelli EM, Solbiati M, et al. Short sleep duration and cardiometabolic risk: from pathophysiology to clinical evidence. Nat Rev Cardiol. 2019;16:213224. doi:10.1038/s41569-018-0109-6

29. Cappuccio FP, Cooper D, DElia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. Eur Heart J. 2011;32:14841492. doi:10.1093/eurheartj/ehr007

30. Fang J, Wheaton AG, Ayala C. Sleep duration and history of stroke among adults from the USA. J Sleep Res. 2014;23:531537. doi:10.1111/jsr.12160

31. Mochn-Benguigui S, Carneiro-Barrera A, Castillo MJ, Amaro-Gahete FJ. Is sleep associated with the S-Klotho anti-aging protein in sedentary middle-aged adults? The FIT-AGEING study. Antioxidants. 2020;9. doi:10.3390/antiox9080738

32. Pk J, Kunos L, Mszros M, et al. Decreased levels of anti-aging Klotho in obstructive sleep apnea. Rejuvenation Res. 2020;23(3):256261. doi:10.1089/rej.2019.2183

33. da Paz Oliveira G, Elias RM, Peres Fernandes GB, et al. Decreased concentration of klotho and increased concentration of FGF23 in the cerebrospinal fluid of patients with narcolepsy. Sleep Med. 2021;78:5762. doi:10.1016/j.sleep.2020.11.037

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Seven passengers from Nigeria have been admitted to the Kings Institute of Preventive Medicine in Chennai for suspected Omicron variant, Tamil Nadu Health Minister Ma Subramanian said on Tuesday.

The Nigerians, according to health department officials, had landed at the Chennai airport a couple of days ago and were tested for Covid -19 and the RT-PCR test revealed that their test had 'S' gene dropout.

However, the health department said that all are asymptomatic and under observation.

The Nigerians had landed at Chennai international airport via Doha, Qatar, and one of them was subjected to a random RT- PCR test which revealed the presence of 'S' gene dropout, which is an early indicator of Omicron variant.

After the 47-year-old man tested the presence of 'S' gene dropout, all the six family members who had accompanied him were also subject to RT-PCR test and found that all had the presence of 'S' gene dropout.

The minister said that all the passengers are asymptomatic and that the health department is waiting for the final test report regarding the presence of Omicron variant.

He said that the samples have been sent to a Bengaluru testing facility and is expecting the results either by Tuesday evening or Wednesday day time. The state has so far sent the samples of 29 people for testing at Bengaluru laboratory for gene sequencing of which four were identified with Delta variant.

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Covid-19: 7 Nigeria returnees admitted to Chennais Kings Institute of Preventive Medicine for suspected - Free Press Journal