Anemone coronaria L. (2n = 2x = 16) is a perennial, allogamous, highly heterozygous plant marketed as a cut flower or in gardens. Due to its large genome size, limited efforts have been made in order to develop species-specific molecular markers. We obtained the first draft genome of the species by Illumina sequencing an androgenetic haploid plant of the commercial line “MISTRAL® Magenta”. The genome assembly was obtained by applying the MEGAHIT pipeline and consisted of 2 × 106 scaffolds. The SciRoKo SSR (Simple Sequence Repeats)-search module identified 401.822 perfect and 188.987 imperfect microsatellites motifs. Following, we developed a user-friendly “Anemone coronaria Microsatellite DataBase” (AnCorDB), which incorporates the Primer3 script, making it possible to design couples of primers for downstream application of the identified SSR markers. Eight genotypes belonging to eight cultivars were used to validate 62 SSRs and a subset of markers was applied for fingerprinting each cultivar, as well as to assess their intra-cultivar variability. The newly developed microsatellite markers will find application in Breeding Rights disputes, developing genetic maps, marker assisted breeding (MAS) strategies, as well as phylogenetic studies. Anemone genus belongs to the Ranunculaceae family and the nowadays most cultivated species  originated in the Mediterranean basin. A. coronaria L., also known as poppy anemone, is an herbaceous, perennial crop cultivated both as a cut-flower and garden plant [en plant . It is aen plant . Poppy aen plant . Althougen plant , which pen plant . In previous studies, DNA markers techniques have been applied and adapted mainly for access intra-cultivars genetic variability or to perform varietal fingerprinting, refs. ,6,7 but A. coronaria genome, estimated between 9.08 and 11.93 Gb according to the analyzed genotype [The advances in next-generation sequencing (NGS) techniques and the progressive reduction of sequencing costs facilitated the obtainment of draft sequence genomes in many plant species. However, due to the large size of A. coronaria, and we report on the massive microsatellite loci identification following its genome-wide survey. Microsatellite—alias simple sequence repeats (SSR)-markers, are co-dominantly inherited, ubiquitous, highly polymorphic, and have found large application in plant breeding and phylogenetic studies because of their simple application through conventional PCR protocols [We generated the first draft for genome sequence of rotocols ,14,15,16rotocols ,18,19,20Based on the microsatellites identified, we developed a public dynamic database, which also provides need-based primer designing facilities and represents the first on-line SSR loci resource available for the scientific community and breeders of poppy anemone and related species. Furthermore, a set of the newly developed markers have been validated in commercial cultivars. A. coronaria is a highly heterozygous species, the sequence divergence between alleles in a diploid genotype may hinder a reliable contig assembly of its genome sequence [® Magenta. Overall, 91.24 Gb of cleaned reads were generated and used as input for genome assembly (6 scaffolds (N50 = 5046 bp) for a total genome size of 6.94 Gb. By removing scaffolds shorter than 500 bp, their number was reduced to 2 × 106 (N50 = 6157 bp), for a total genome size of ~6.13 Gb  covering ~56.12 Mb (0.92%) of the estimated genome size. Functional annotation performed through InterProScan domain inspection highlighted about 84% of the predicted proteins with at least one IPR domain. Among the top SUPERFAMILY domains, the most abundant (8.62%) was SSF56112 (protein kinase-like domain), which acts on regulatory and signaling processes in the eukaryotic cell. The second most represented superfamily (6.19%) was SSF52540 (P-loop containing nucleoside triphosphate hydrolase) which is involved in several UniPathways, such as chlorophyll or CoA biosynthesis, followed by SSF48264 (4.10%-Cytochrome P450). These superfamilies have been previously reported as highly abundant in various genomic backgrounds ,28,29.In the assembled poppy anemone genome, a total of 401,822 perfect SSR motifs (density of 65.52 SSR/Mb), which included 42,111 compound SSRs, and 188,987 imperfect SSR motifs were identified .Six classes of perfect SSRs were evaluated (from mono- to hexanucleotide) for their abundance in the assembled genome. Dinucleotides were the most abundant, in accordance with what has been previously reported in literature ,37,38,39The variation of perfect microsatellites repeats was investigated in all SRR classes . As prevBased on the number of motif repeats, 0.95% of SSRs were classified within the hypervariable class I (≥30 motif repeats), 3.71% were assigned to the potentially variable class II (20–30 motif repeats) types, while the remaining 95.34% were included in the variable class III (<20 motif repeats) types a.Compared with our previously published data ,38, in wThe obtained gene annotation made it possible to investigate the distribution of microsatellites across the gene space. Overall, 3223 perfect  and 1261 imperfect SSRs (0.67%) were associated with 3223 and 1261 genes respectively, representing 0.23% of the gene space. These SSRs were estimated to cover a total of 134 Kb, values which translates to a density across the gene space of 57.48 and 22.52 SSRs/Mbp for perfect and imperfect motifs, respectively.We also investigated the perfect SSR motifs detected in the global set of genomic and genic SSRs. The microsatellites were classified in non-triplet repeats , and triplet repeats (tri- and hexanucleotides), and a fair balance between the two classes , and the second most common class were the dinucleotides 29.0%; b. The pr.2%, and The GO categorisation of the genic SSR highlighted 1113 sub-categories of three main GO categories—Biological Process (BP), Molecular Function (MF), and Cellular Component (CC). Thirteen sub-GO categories represented ~33% of the identified entries . The MF sub-categories “protein amino acid binding” GO:0005515) and “ATP binding” (GO:0005524) represented more than the 10% of the overall identified accessions. The occurrence of SSRs within specific gene functions has been previously observed ,55,56,5715 and “AAnCorDB—Available at www.anemone.unito.it, accessed on 9 March 2022). It offers similar features to the CyMSatDB [EgMiDB databases [A public and searchable database of the microsatellites data reported in this paper was developed  values of the polymorphic SSRs varied from 0.13 to 0.85 (mean 0.52 ± 0.025). AnCor49 had the highest PIC, and AnCor71 the lowest . Two major clades were identified, and supported with bootstrap values higher than 90. In Clade I, the two tetraploid cultivars (“BCN” and “Blu”) clustered with an average genetic similarity of 78% and a bootstrap probability of 92%, while among the other three cultivars, Edge resulted more genetically differentiated from “Bordeaux” and “Magenta”, which showed a genetic similarity of 74% and clustered with a bootstrap probability of 94%. In Clade II, “Tigre” and “Tigre Wine”, which in turn resulted highly differentiated, showed an average genetic similarity of 60%.The first two axes of the PCoA scatter plot  explaineAncor33, -36, -49, -59, and -83, applied togheter with the tetranucleotide Ancor177  values ranged from −0.68 to 0.79. As expected from selected genotypes obtained within breeding programs, most the loci showed significant deviation from HWE, with only one marker (Ancor89) showing no significant difference between expected (HE) and observed (HO) heterozygosity values  values for the first coordinate, together with “Tigre” and “Tigre Wine”. “Edge” showed the highest intra-cultivar variability, while “Bordeaux” the lowest . The UPGEach plant of the cultivars “Edge”, “Blu”, and “BCN” showed a unique fingerprinting, while in the other five, some plants shared common alleles. Despite the observed intra-cultivar genetic variability, the application of only six SSRs made it possible to clearly discriminate the diploid cultivars, each of them clustered with bootstrap support from 95 to 100, while no clear genetic differentiation between the tetraploid cultivars “BCN” and “Blu” was detectable, suggesting the application of additional specific markers for their fingerprinting. For this purpose, the sixty-two amplified markers were investigated, leading to the identification of five microsatellites each of which might be individually applied for “BCN” and “Blu” discrimination . ® MAGENTA obtained through “in vitro” androgenesis by applying the regeneration protocol adapted by [®) was used for the genomic DNA extraction following the manufacturer’s instructions. DNA quality was assessed through the NanoDrop™ 2000 spectrophotometer and the Qubit® 2.0 Fluorometer was used for DNA quantification. One microgram of DNA was used for the construction of a 270 bp insertion library , which was sequenced using a NovaSeq Illumina platform  with paired-end chemistry (2 × 150 bp). Raw reads were cleaned with Scythe  for removing contaminant residual adapters and Sickle ) for removing reads with poor quality ends (Q  <  30). De novo assembly was performed with standard parameters using the MEGAHIT assembler ), an ultra-fast and memory-efficient NGS assembler based on succinct de Bruijn graphs that can be applied both for metagenomics and single genome assembly. The quality of the genome assembly  was assessed using the perl script Assemblathon_stats.pl ). Cleaned reads were then used for k-mer-based genome size estimation using the jelly-bean software and applying the formula Genome Size = 19-mers count/peak position of the number of times each 19-mer occurs ) which requires the use of mite hunter, LTRdigest, LTR_harvest , and Repeatmodeler v1.0.11. The new library was then combined with Repbase-viridiplantae to identify transposable elements (TEs). TEs were classified into two main classes: Class I (retrotransposon elements) and Class II (DNA transposons). Gene prediction was performed using Maker-P v2.31.08. Augustus v3.3.2 ), and perfect, compound, and imperfect SSRs were identified in silico using SciRoKo and the misa.pl pipeline ). A minimum of four repetitions together with a minimum length of 15 nt were requested. Any sequence was considered as a perfect SSR when a motif was repeated at least fifteen times (1 nt motif), eight times (2 nt), five times (3 nt), or four times (4–6 nt), allowing for only one mismatch. For compound repeats, the maximum default interruption (spacer) length was set at 100 bp. The coordinates (start/end position) of each SSR were matched with those of the gene space using Bedtools intersect (using the default parameters) with -loj (left outer join) option: where the overlap comprised at least 1 nt, the repeat was designated as a genic SSR. A GO categorization of the three main GO categories—“biological processes” (BP), “molecular functions” (MF), and “cellular components” (CC)—were applied to genes carrying at least one SSR. The un-masked draft assembly of the Ko tool ) was developed to provide browsable access to the SSR data. This web application, based on a LAMP stack, comprises a client tier (client browser), a middle tier (Apache web server with PHP interpreter), and a database tier (MySQL DBMS). A user-friendly interface was developed using PHP, which is an open-source server-side scripting language. The set of in silico detected SSRs were stored in the MySQL database, using PHP scripts to parse the text file from SciRoKo. User need-based customized queries can be generated from the web interface and allow users to search the microsatellite marker information in MySQL database. A stand-alone version of Primer3 has been also provided to design primer pairs for any given SSR: its output lists alternative sets of primer pairs, and the characteristics of the expected amplicon.The A. coronaria cultivars representative of the phenotypic variability of the ones marketed by Biancheri Creazioni. Among them, six cultivars were diploid , while two were tetraploid (“BCN” and “BLU”). The following touchdown PCR protocol was applied: 94 °C for 5 min followed by 13 touchdown cycles with denaturation step at 94 °C for 30 s, a step at 60 °C for 30 s decreasing the annealing temperature of 0.38 °C every cycle, and lastly extension step at 72 °C for 30 s. At last, 35 cycles at 94 °C for 30 s (denaturation), 55 °C for 30 s , and 72 °C for 30 s (extension), and a final extension cycle at 72 °C for 5 min. PCR products were separated using a 2% agarose gel to check their occurred amplification. One hundred and fifty microsatellites were selected among the ones with a number of repetitions between 20 and 30, in line with the overall genome representation of every class and motif. Specifically, di- and tri-nucleotides were selected in the interval ranging from 25 and 30 motif repetitions, while this threshold was lowered to the interval between 20 and 30 motif repetitions for the other classes of microsatellites. These parameters were applied with the aim of obtaining the highest potential polymorphism rate of the selected markers. The primer pairs obtained from the database were used for the DNA amplification of eight ® 310, Applied Biosystems™). M13-Tailed Forward primers were designed for each microsatellite and applied in a three-primers unbalanced PCR reaction with a fluorescent-labelled M13 primer , 1 μL of MgCl_2 (25 mM), 0.4 μL of dNTPs (10 mM), 3 μL of DNA template (5 ng/μL), 1 μL of Reverse and M13-labeled primer (10 μM), 0.2 μL of Forward-M13 Tailed primer (10 μM), and 9.2 μL of ultrapure water. In each reaction, 1 μL of amplification product was pooled with other three products labelled with different fluorophores  and purified using the PEG-precipitation method described by [® 310 according to the GeneScan® Reference Guide (Applied Biosystems™). Results were visualized using Peak Scanner™ Software v1.0 (Applied Biosystems™) and for each microsatellite the amplicons’ length was scored. A binary matrix was generated by scoring the band presence (1) and absence (0), which was used to compute pairwise similarity coefficients [O) and expected (HE) heterozygosity and Wright’s fixation index (FIS) were estimated with the program identity 1.0 [genepop 3.4 [A subset of 62 SSRs  were fur primer . PCR waribed by . Multiplficients  and thenficients  with 100ficients  and Pastficients . The polficients  and usedficients  was perftity 1.0 . Exact tepop 3.4 .Anemone coronaria L. represents the first step toward genomic studies in poppy anemone. Its availability made it possible to identify a wide set of SSR markers and release the comprehensive microsatellite database AnCorDB (www.anemone.unito.it). The latter contains a full set of information regarding both genic and non-genic, perfect and imperfect SSR loci. Its intuitive web interface and its customized primer design offer a highly flexible tool to the scientific community and breeders, exploitable for genetic as well as phylogenetic studies. Our results also demonstrated that the application of a limited number of SSRs might be suitable for varietal discrimination and may contribute to solve Breeding Rights disputes. The development of a draft genome assembly of


In this study, we performed genome-wide association analyses on SARS-CoV-2 genomes to identify genetic mutations associated with pre-symptomatic/asymptomatic COVID-19 cases. Various potential covariates and confounding factors of COVID-19 severity, including patient age, gender and country, as well as virus phylogenetic relatedness were adjusted for. In total, 3021 full-length genomes of SARS-CoV-2 generated from original clinical samples and whose patient status could be determined conclusively as either ‘pre-symptomatic/asymptomatic’ or ‘symptomatic’ were retrieved from the GISAID database. We found that the mutation 11 083G>T, located in the coding region of non-structural protein 6, is significantly associated with asymptomatic COVID-19. Patient age is positively correlated with symptomatic infection, while gender is not significantly correlated with the development of the disease. We also found that the effects of the mutation, patient age and gender do not vary significantly among countries, although each country appears to have varying baseline chances of COVID-19 symptom development. All supplementary information is available with the article as PDF files online. Supplementary material can be found in Figshare: Coronavirus disease 2019 (COVID-19) is a major public health concern, caused by a novel coronavirus called SARS-CoV-2. As of now, more than 240 million cases of COVID-19 with more than 4.9 million deaths have been reported worldwide, and the rapid surge in the number of COVID-19 patients has overwhelmed hospitals’ capacity around the world. It has been reported that up to 80 % of SARS-CoV-2 infection might be asymptomatic, and this probably plays an important part in the rapid global transmission of the virus. To effectively contain the disease, it is thus imperative to understand the disease progression and the factors that drive the process. Here, we performed genome-wide association analyses on all SARS-CoV-2 genomes in the GISAID database, and found that a mutation at genomic position 11 083, namely the 11083G>T mutation, located in the coding region of non-structural protein 6, is significantly associated with asymptomatic COVID-19, adjusted for various confounders and covariates, including virus phylogenetic relatedness, patient age, gender and country. Our results have implications for the development of better and more informative test kits, for example, allowing potentially symptomatic cases to be distinguished from asymptomatic ones, and this could lead to more effective disease management and control.Coronaviridae [Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was first reported in Wuhan, Hubei, China, in late December 2019 [aviridae . It is taviridae .The virus was found to spread around the globe, and as of now (October 2021) has infected more than 240 million people globally , which hhuman leucocyte antigen genes [Several host factors correlated with COVID-19 severity have been identified, including patient age , patienten genes . A numbeen genes , and to en genes . The laten genes . In addien genes . HoweverThere are currently millions of SARS-CoV-2 genomes from around the world made publicly available on the database of the Global Initiative on Sharing All Influenza Data (GISAID) , and somIn total, 18 705 full-length/almost full-length genome sequences of SARS-CoV-2 (>29 000 nt) with patient status were downloaded from the GISAID database on 28 December 2020 together with their metadata. A table of acknowledgements can be found in Table S1 (available in the online version of this article), and the metadata can be found in Table S2. To allow for accurate determination of the genetic factors associated with COVID-19 pathogenicity, we only analysed sequences whose patient status could be unambiguously determined as either ‘pre-symptomatic/asymptomatic’ or ‘symptomatic’. We categorized ‘Asymptomatic/Released’, ‘Asymptomatic’, ‘Asymptomatic, identified as positive during preoperation investigation’, ‘No clinical signs’ and ‘No clinical signs without hospitalization’ as ‘pre-symptomatic/asymptomatic’ (257 sequences). If the patient status was ‘Acute upper respiratory infection, unspecified’, ‘Death’, ‘Deceased’, ‘Hospitalized ’, ‘Hospitalized/Deceased’, ‘Hospitalized, deceased’, ‘Hospitalized in ICU’, ‘Hospitalized (Intensive care unit)’, ‘Hospitalized (Mild)”, ‘Hospitalized (Moderate)’, ‘Hospitalized, oxygenotherapy, diarrhoea’, ‘Hospitalized (Severe)’, ‘Hospsitalized, ICU, fully recovered’, ‘ICD-10 Disease: J00-J06 Acute upper respiratory infections’, ‘ICD-10 Disease: J06.9 Acute upper respiratory infection, unspecified’, ‘ICD-10 Disease: J18.1 Lobar pneumonia, unspecified organism’, ‘ICD-10 Disease: J18.9 Pneumonia, unspecified organism’, ‘ICU’, ‘ICU; Serious’, ‘Intensive Care Unit’, ‘Live, mild symptoms, at home’, ‘Mild’, ‘Mild, at home’, ‘Mild case’, ‘Mild clinical signs without hospitalization’, ‘Mild clinical signs without hospitalization. Diarrhoea’, ‘Mild clinical signs without hospitalization. Distorted ability to smell’, ‘Mild clinical signs without hospitalization. Distorted ability to smell and taste’, ‘Mild clinical signs without hospitalization. Distorted ability to taste’, ‘Mild symptoms ’, ‘Mild symptoms inpatient for observation’, ‘Moderate/Outpatient’, ‘Paucisymptomatic’, ‘Severe/ICU’, ‘Severe’, ‘Symptomatic’ or ‘Symptoms indicative of upper respiratory infection’, we annotated them as ‘symptomatic’ (10 172 sequences). Sequences that were not generated from original clinical samples or human samples were excluded (three asymptomatic samples and 10 symptomatic samples), leaving 10 416 sequences in the whole dataset. Virus genomes associated with symptomatic Japanese cases were subsampled to reduce the data redundancy (see main text). Fifteen sequences with unusually high sequence diversity were also removed. In total, our dataset comprised 3021 sequences, 252 of which were associated with pre-symptomatic/asymptomatic infections, while 2769 sequences were associated with symptomatic cases. Taxonomic and geographical distributions of the sequences can be found in Tables S3 and S4, respectively.P=0.91). A maximum-likelihood phylogeny was estimated by using IQ-TREE [A manually curated full-length multiple sequence alignment of the 3021 SARS-CoV-2 genomes was constructed. Potential recombination within the alignment was checked by using the Phi test implemented in SplitsTree4 , but no  IQ-TREE . ModelFi IQ-TREE  determinUncertCoef function in R (Table S5). Pairs with scores of >0.90 (out of 1) were grouped together as sites with co-varying variants, and were analysed as strongly linked loci. Likewise, for each set of strongly linked loci, a sequence was considered to be a ‘reference’ variant if all of its genetic variations on the sites were those present in the reference genome, and otherwise as a ‘non-reference’ variant.Polymorphic sites with less than 50 % ambiguous bases and aggregated minor allele frequencies of more than 5 % of the collected sequences were identified. For initial screening of candidate sites, genetic variations present in the reference genome (RefSeq accession number: NC_045512.2) were considered ‘reference’ variations, or otherwise as ‘non-reference’ variations, and for each position, a binary profile of genetic variations was constructed. We believed this was reasonable as all positions had only one major alternative variant, with the frequencies of the third most common allele being less than 1 % for all sites except one . Uncertaoddsratio.wald function, implemented in the R software package epitools.TreeWAS  was usedbwa [samtools [Integrative Genomics Viewer [Our initial screening suggested that genetic variations at site 11 083 are associated with COVID-19 pathogenicity, and examination revealed that 18 sequences had either an undetermined (N) or ambiguous (K) base at the position (see Results). To examine the nature of the genetic variations at this site, we were able to obtain raw sequencing data for 14 of them, and mapped them against the reference genome (NC_045512.2) using bwa  and samtsamtools . Crude rs Viewer  , B.1.1 haplogroup GR , B.1.1.214 haplogroup GR , B.1.1.48 haplogroup GR  and A haplogroup S . We thus randomly subsampled the Japanese data so that there were at most 150 sequences from each of these lineages. Preliminary phylogenetic analysis showed that 15 sequences had unusually long terminal branches and had unusually high sequence diversities (>9×10−4 mutations per site) compared to the reference SARS-CoV-2 genome (RefSeq accession number: NC_045512.2), probably due to primer contamination. Thirteen were associated with symptomatic cases, while two were obtained from pre-symptomatic/asymptomatic cases, and they were removed from the dataset. In total, our curated dataset comprised 3021 sequences, 252 of which were associated with pre-symptomatic/asymptomatic infections while 2769 sequences were associated with symptomatic infections.SARS-CoV-2 genomes with patient status data were retrieved from the GISAID database  on 28 DeThe curated dataset covered a wide diversity of SARS-CoV-2, comprising 148 distinct viral lineages and eight GISAID haplogroups (Table S3) sampled from 36 countries/territories and 13 United Nations (UN) geoscheme subregions (Table S4). 2 test: χ2 score=1094.3, degrees of freedom (d.f.)=147, P<2.2×10−16) and GISAID haplogroups  as well as among countries/territories  and broader geographical regions . The majority of the genomes associated with pre-symptomatic/asymptomatic cases were from the Czech Republic (34/252=13.49 %), India (52/252=20.63 %), Italy (69/252=27.38 %), Japan (61/252=24.21 %) and Turkey (21/252=8.33 %), while genomes associated with symptomatic cases were from around the globe (Table S4).The distribution of SARS-CoV-2 genomes associated with pre-symptomatic/asymptomatic and symptomatic infections were significantly different among lineages [χTwenty-six polymorphic sites with less than 50 % ambiguous bases and aggregated minor allele frequencies of more than 5 % of the collected sequences were considered in our analyses, corresponding to sites 241, 313, 1059, 3037, 4346, 8782, 9286, 10 376, 11 083, 14 408, 14 708, 18 167, 18 877, 20 268, 21 518, 23 403, 25 563, 26 730, 26 735, 28 144, 28 725, 28 881, 28 882, 28 883, 28 975 and 29 692 in the reference SARS-CoV-2 genome (RefSeq accession number: NC_045512.2) . Of thesU) were computed (Table S5). We considered pairs with U>0.90 (out of 1) to be sites with co-occurring variations. Five sets of co-varying sites were detected under this criterion, namely (i) sites 241 and 14 408, (ii) sites 8782 and 28 144, (iii) sites 18 167 and 21 518, (iv) sites 28881, 28 882 and 28 883, and (v) sites 4346, 9286, 10376 14 708 and 28 725. Indeed, genetic variations of these five sets of sites were phylogenetically highly correlated, as could been seen pictorially in For each position, a binary profile of genetic variations (reference variation vs. non-reference variation) was constructed, and pairwise uncertainty coefficients . Three-test wide Bonferroni multiple-testing correction was also applied . To account for phylogenetic uncertainty, the analysis was applied to the entire distribution of the 1000 bootstrap trees.Three measurements of association between the observed patient status and virus genotype were computed: ‘terminal score’, ‘simultaneous score’ and ‘subsequent score’. The ‘terminal score’ indicates the degree of sample-wide association across the phylogeny’s leaves, the ‘simultaneous score’ is the number of times that the examined phenotype and genotype change in parallel together, and the ‘subsequent score’ measures the total tree length that the genotype and investigated phenotype are found to co-exist . AncestrOur results showed that site 11 083 had the highest association scores in all of the three tests . ConditiTwo major nucleotide variations were observed at genomic position 11 083, namely thymine  and guanine . The reference genome (RefSeq accession number: NC_045512.2), which is one of the earliest genomes from the COVID-19 outbreak in Wuhan, was identified as a G11 083 variant . One of P-value=2.11×10−58). The association was robust to the inclusion of the Japanese sequences excluded from the dataset due to data redundancy . Altogether, these results suggested that the 11 083G>T mutation is significantly associated with pre-symptomatic/asymptomatic infection.Across the 2769 sequences associated with symptomatic cases, 95.88 % (2655 sequences) were found to be the wild-type G11 083 variants, while only 3.90 % (108 sequences) were found to be the mutant T11 083 variants. By contrast, of the 252 sequences associated with pre-symptomatic/asymptomatic infections, only 56.75 %(143 sequences) were found to be the wild-type G11 083 variants, while 38.49 % (97 sequences) were the T11 083 mutant variants. Based on this dataset, the crude odds ratio for causing a symptomatic infection of the mutant T11 083 variant compared to the reference G11 083 variant was estimated to be 0.060 by the Wald method . In addition, most of these sequences belonged to lineage B.6 (8/15=53.33 %), which is the lineage that has a very high ratio of T11 083 to G11 083 variants (47 : 3 sequences).Regarding the 18 sequences with undetermined or ambiguous bases at position 11 083 , furtherIt is well known that a long homopolymer stretch is difficult to sequence, and is prone to indel sequencing errors , in partOf these 18 sequences, we were able to obtain raw sequence data for 14, and mapped them against the reference genome to examine the underlying nature of the genetic variations at this site . We were able to confirm that, among the three sequences with the long stretches of Ns, one was indeed a result of complete sequencing failure, and for the rest, it was often the case that majority of the raw sequence data (>50 %) would support a deletion at the site. However, considering the remaining reads that resulted in base calling, all of them were either Ts or Ks, and none were Gs. Combining this information, we therefore deemed reasonable to group the remaining 15 sequences with other T11 083 variants for further analyses.One of the limitations of TreeWAS  was thatTo examine if the association detected by TreeWAS  was robu2 test: χ2 score=7.85, d.f.=9, P=0.55), supporting that the effects of the mutation 11 083G>T, patient gender and age on COVID-19 pathogenicity do not vary significantly among countries. However, M2 was found to fit the data significantly better than M3 , suggesting that populations of different counties may have varying baseline chances of developing COVID-19 symptoms. Similarly, M2 was found to better fit than M4 , suggesting that phylogenetic relatedness among viruses plays a significant role in COVID-19 pathogenicity (i.e. closely related viruses tend to cause the same kind of infection). Estimated parameter values of the best-fit model can be found in Table S7, and their corresponding adjusted odds ratios are given in Based on the analysis of the whole dataset, we found that M1 did not significantly better fit the data than M2 , but patient gender does not significantly correlate with the disease outcome . The baseline odds for developing COVID-19 symptoms when getting infected was estimated to be (just) significantly different from 1 (P=4.2×10−2), computed to be 135.56 with an extremely large uncertainty , and the value was estimated to vary substantially among countries (variance=49.66) and also among viruses, although to a much lesser extent (variance=0.38). At face value, this estimate is consistent with the overall baseline chance of developing symptoms being greater than that of not developing symptoms. Nonetheless, it is noteworthy that there might be a tendency for this value to be overestimated, due to the fact that viruses associated with symptomatic infection may be more likely to be sequenced and submitted to the GISAID database than those causing asymptomatic infection given typical healthcare seeking behaviour, making the database systematically biased towards viruses causing symptoms. Thus, this value should be interpreted with care. Nevertheless, taking all of these factors into account, the 11 083G>T mutation was still found to be significantly associated with pre-symptomatic/asymptomatic infection .According to the best-fit model M2 , we foun2 test: score=12.46, d.f.=9, P=0.19), but M2 significantly better fitted the data than M3  and M4 . According to the M2 model , while gender does not significantly correlate with the pathogenicity of the virus . Unlike the results from the whole dataset analysis, the baseline odds was estimated to be insignificantly different from 1 , but the analysis still suggested that the value does vary considerably among countries (variance=2.04) and among viruses (variance=0.32). The overall strength of the random country-specific effect was estimated to be less than that estimated based on the whole dataset (variance=49.66), probably due to fewer countries being included in this dataset. Nonetheless, again, a significant (negative) effect of the 11 083G>T mutation on SARS-CoV-2 pathogenicity could still be detected .Analysis of the subsample data yielded largely consistent results. M1 was not found to significantly better fit than M2 , adjusted for various factors that might also be associated with disease severity, including patient age, gender and country of origin, as well as virus phylogenetic relatedness and structure.In this study, we performed GWAS analyses on 3021 SARS-CoV-2 genomes, and identified variations at genomic position 11 083 to be associated with SARS-CoV-2 pathogenicity. Specifically, we found that the mutation 11 083G>T is associated with pre-symptomatic/asymptomatic cases . In part, this may be because different countries may differ in the way they recorded COVID-19 symptoms and/or how the disease surveillances or treatments were performed, resulting in different distributions of pre-symptomatic/asymptomatic vs. symptomatic cases. This result is also consistent with different human populations having varying degrees of susceptibility to the virus infection. Several studies have revealed that background genetic makeup does, indeed, associate with susceptibility to SARS-CoV-2 infection and COVID-19 severity. For example, a study of two case-control cohorts of Italian and Spanish patients identified a 3p21.31 gene cluster on chromosome 3 to be a genetic susceptibility locus in COVID-19 patients, and showed a higher risk in blood group A than in other blood groups, corresponding to the rs657152 variant at locus 9q34.2 on chromosome 9 . A separ I genes  and TLR7mosome X , for exaP=8.45×10−35) and examination of Pearson’s correlation coefficient  [N=112), and different groupings of the disease outcome , which could potentially mask the effect we observed. Epidemiological data examination showed that, indeed, countries with a high prevalence of the T11 083 variant tended to have lower rates of COVID-19 mortality than those that had low prevalence of the mutation [A study identified the 11 083G>T mutation to be associated with asymptomatic cases by Fisher’s exact test (2×10−56) ; however2×10−56) . This comutation , furtherThis mutation is located in the coding region of non-structural protein 6 , coded by ORF1ab (nt 266–21 555). NSP6 is a multi-functional protein, and can be found in many coronaviruses. It has been demonstrated that, located to the endoplasmic reticulum, SARS-CoV NSP6 can form a protein complex with NSP3 and NSP4 to induce double-membrane vesicles, crucial for the formation of the virus replication/transcription complex . Studiesth position in the NSP6 protein (L37F). In silico 3D structure analyses suggested that the mutation may reduce the stability of the protein structure [The 11 083G>T mutation confers an amino acid change from leucine (L) to phenylalanine (F) at the 37tructure , and at tructure . As discThe mutation 11 083G>T has occurred independently many times over the course of this on-going pandemic. In fact, this genomic position has been quantified as having one of the highest rates of homoplasy . Some prClick here for additional data file.


Blood samples were taken before the exercise test, at maximal intensity and after the volunteers have recovered, and the blood concentration of αCGRP was measured. We found that 2/3 of the volunteers responded to maximal exercise with an increase of their blood αCGRP concentration (responders), while the resting 1/3 did not (non-responders). We also found that VO2max, VCO2, carbohydrate oxidation and performed work were higher in the responders when compared to the non-responders. Therefore, our observations support that αCGRP release during exercise may be associated to physiological responses related to physical performance.αCGRP is a neuropeptide that increases in blood during high-intensity exercise in humans. However, the physiological meaning of this molecular response is unknown. Previous experimental works in rodents have related this neuropeptide to several biological processes in the skeletal muscle tissue and cardiorespiratory physiology. Based on the data from these animal studies we hypothesized that in humans αCGRP release during exercise could be similarly associated to metabolic and cardiorespiratory responses. To test this hypothesis, we subjected a sample of physically active young men to an exercise test up to exhaustion while their oxygen uptake (VO−2 body mass index) performed a graded exercise test. A venous catheter was placed before testing, and blood samples were taken at baseline, maximal effort and recovery. αCGRP was measured in plasma using a commercial double-sandwich enzyme-linked-immunoassay. A two-way repeated measurements ANOVA was used to compare the values obtained at baseline, maximal effort and recovery. In the whole sample, αCGRP increased at maximal effort and its concentration correlated directly, albeit non-significantly, with the muscle mass normalised VO2, VCO2, carbohydrate oxidation and relative power. Two thirds of the participants showed an increase in αCGRP concentration at maximal effort. Post hoc analysis showed that in these individuals, the muscle mass normalised VO2, VCO2, carbohydrate oxidation rate and relative power were higher than in the participants lacking this molecular response. Therefore, our data suggest that (a) a majority of young men respond to exercise with an increase in blood αCGRP concentration; and (b) individuals exhibiting this response also show a higher cardiorespiratory fitness, carbohydrate oxidation and work performed. These findings suggest that this neuropeptide could act as an exerkine with potential effects on physical performance.This study aimed to explore if the acute variations in plasma concentration of α-calcitonin gene-related peptide (αCGRP) induced by a single maximal exercise bout may be associated to cardiorespiratory fitness and carbohydrate oxidation in humans. Twelve young adult Caucasian men (24.3 ± 0.9 years-old; 179.2 ± 1.9 cm of height; 23.9 ± 0.6 kg·m Althoug–37hCGRP . In addi–37hCGRP . In vivo–37hCGRP . For exa–37hCGRP . More re–37hCGRP  with hig–37hCGRP . Therefo–37hCGRP . Presyna–37hCGRP , and add–37hCGRP , thus inase pump , thus in−1) [In resting humans, the blood concentration of αCGRP shows a large inter-individual variability (14.0–132.5 pg·mL−1) , but it −1) . Althoug−1) , several−1) ,26,27,28−1) , the phyTherefore, given the wide range of cardiorespiratory and metabolic effects of αCGRP described in animal models, we hypothesised that exercise-induced αCGRP release would be associated to cardiorespiratory fitness and carbohydrate oxidation in humans, a topic that, to the best of our knowledge, has not yet been addressed. This exploratory study aimed to test this hypothesis by measuring blood αCGRP concentration, cardiorespiratory fitness, carbohydrate oxidation and work performed during a graded exercise test in young, active men.A cross-sectional study was performed with 12 healthy Caucasian young adult men . The weekly time that the individual spends performing each of these activities is also registered. By multiplying the reported time per an assigned number of metabolic equivalents (METs) to each intensity level, the MET-min·week−1 of physical activity of each intensity are obtained. The total MET-min·week−1 is the summation of all the categories. To obtain these data, we used the Excel template that can be downloaded from the instrument’s creators.LTPA was estimated with the Spanish self-administered short version of the International Physical Activity Questionnaire , and expThe exercise test was performed by each participant in a single session in a laboratory with controlled temperature (~23 °C), located 80 m above the sea level, between 17:00 and 19:00, to avoid the circadian baseline changes of αCGRP . The sub2) and CO2 production (VCO2) were measured during a graded exercise test up to exhaustion (see below). For testing, an electromagnetically braked cycle ergometer , a calibrated gas exchange analyser  and an automated blood pressure monitor  were used. Throughout the test, a 12-lead electrocardiogram and pulse-oximetry were continuously monitored. Heart rate was obtained from the electrocardiogram recording. Calorimetry and cardiorespiratory responses were indirectly calculated using the gas analyser software. VO2, VCO2, energy expenditure (EE), carbohydrate oxidation (CHO) as well as the relative power performed by the individual were normalised to his muscle mass (indicated with the sub-index MM throughout the text).Oxygen uptake (VO−1 using a metronome. Test was finished if any of these two conditions of exhaustion were reached: (a) the desire of the subject to stop ; or (b) the inability of the subject to maintain the target pedalling cadence. The criterion to consider the test as maximal was to reach a respiratory exchange ratio (RER) > 1.1 [The test was specifically customised for this study, according to the recommendations of Pettitt et al. . BrieflyR) > 1.1 . TestingR) > 1.1 . The timR) > 1.1 .An intravenous catheter was placed in the right antecubital vein before starting the exercise test. The catheter was filled with sterile physiological saline. Blood samples were withdrawn at baseline (BAS), immediately after the exercise test ended (MAX) and at recovery (REC). On each occasion, the first 2 mL of blood were discarded, and the following 5 mL were collected in EDTA-containing tubes , gently mixed, aliquoted in 2-millilitre polypropylene tubes and centrifuged at 3000 rpm for 10 min. Supernatant plasma was recovered and stored at −80 °C until assayed. For assaying, plasma samples of each subject were slowly thawed at room temperature and homogenised by gentle inversion. According to the enzyme-immuno-assay manufacturer, αCGRP was extracted using Oasis HLB cartridges C18 , recovered in methanol:water  and vacuum centrifuged at 35 °C, until dried. Pellets were afterwards re-suspended in the enzyme-immuno-assay buffer, and subsequently assayed for human αCGRP concentration using a commercial double-sandwich enzyme-immuno-assay kit (SPI-BIO #A05481). The sample of each subject and the CGRP concentration standards were assayed in duplicate, and the mean value was used for statistics. Intra and inter-assay variations were within the limits indicated by the manufacturer. Assays were masked, i.e., the involved researchers did not know any data of the subjects.Plasma volume variations were not expected due to the short duration of the exercise test and the controlled environment conditions. However, to exclude this possibility, some of the initial plasma samples were assayed in parallel for albumin concentration  at the three measurement points. No differences were noted in albumin concentration between them.t-test. A two-way repeated measurements ANOVA (2-way RM ANOVA) was used for between and within group comparison at the different measurement points taken throughout the test. The corresponding non-parametric analyses were applied when appropriate and are indicated in the text. Differences were considered significant for p < 0.05. To calculate the Effect Size (ES), Cohen’s d was used and was interpreted as follows: 0.20–0.50 , 0.50–0.80 (medium), >0.80 (large) [Data were analysed, and graphs were drawn using Sigmaplot 11  or Microsoft Excel™. Unless otherwise indicated, data are expressed as mean ± standard error of the mean. Anthropometric and LTPA data were compared with the Student’s  (large) . ES is pAll the experimental procedures followed a protocol approved by the university Ethics Committee  and attained to the tenets of the Declaration of Helsinki, as well as to the current national and international regulations for research involving human beings.−1, BAS, MAX and REC, respectively; p = 0.138, 2-way RM ANOVA on Ranks; d = 0.59 ). Although not significantly, the αCGRP concentration at maximal effort tended to correlate directly with VO2MM, VCO2MM, CHOMM and relative power ). Therefore, we named them the ‘responders’ group. In contrast, the ‘non-responders’ group ). No differences were found among both groups at baseline, neither in the αCGRP concentration , nor in other variables . Similarly, the CO2 production normalised to the individual’s weight was higher in the responder group at VT1 and MAX (p < 0.05). No other differences were noticed.For further analyses, the data were grouped according to the αCGRP response at MAX. As shown in 2MM, VCO2MM, energy from carbohydrate oxidation and relative power throughout the whole exercise test . Third, αCGRP was tested after a specific exercise test and the effect of other types of exercise or training programs could be different. Nonetheless, the study was designed with the very specific objective to respond to the initial hypothesis.Among young men, a majority of individuals respond to maximal exercise with plasma αCGRP elevations. Individuals with this molecular response exhibit higher cardiorespiratory fitness, carbohydrate oxidation and work performed than individuals in which the response is absent. These findings suggest that αCGRP could be an exerkine with potential effects on physical performance.


Integrin β4 (ITGβ4) is a class of transmembrane adhesion molecules composed of hemidesmosomes (HDs). Its unique long intracellular domain provides intricate signal transduction functions. These signal transduction effects are especially prominent in tumors. Many recent studies have shown that integrin β4 is differentially expressed in various tumors, and it plays a vital role in tumor invasion, proliferation, epithelial–mesenchymal transition, and angiogenesis. Therefore, we categorize the research related to integrin β4, starting from its structure and function in tumor tissues, and provide a basic description. Based on its structure and function, we believe that integrin β4 can be used as a tumor marker. In clinical practice, it is described as a diagnostic marker for the targeted treatment of cancer and will be helpful in the clinical diagnosis and treatment of tumors. The current cancer epidemiological data collected from the official databases of the World Health Organization and the American Cancer Society show that the overall risk of developing cancer for those aged 0–74 years is 20.2% (22.4% in men and 18.2% in women). A total of 18 million new cases were diagnosed in 2018, the most frequent of which were lung (2.09 million cases), breast (2.09 million cases), and prostate (1.28 million cases) cancer. In addition to sex-specific malignancies, the ratio of cancer frequency for men and women is greater than one for all cancers, except thyroid . Regarding mortality, cancer is the second-highest cause of mortality worldwide (8.97 million deaths) after ischemic heart disease, but will likely be ranked first by 2060 (~18.63 million deaths) [Integrins are heterodimeric receptors that consist of paired α and β subunits. In the human genome, 18α and 8β subunits are combined in a limited combination to provide 24 integrin receptors, each with its own specificity for selecting ECM or cellular adhesion proteins . IntegriIntegrin β4 has been widely reported as a prognostic and predictive molecule in patients with various cancers. The aim of this review was to evaluate the results from studies conducted on this subject. Using the search words “integrin β4”, “integrin β4 in tumor”, “diagnostic significance”, “prognostic significance”, and “therapeutic targets”, a search was performed on PubMed. Finally, 105 articles were found. This review regards integrin β4 as a potential tumor marker, providing assistance with the diagnosis and treatment of tumors in the future, and helping to solve major public health problems in the world today.A total of 24 different kinds of integrins have been described . The cytIntegrins are a superfamily of cell adhesion receptors. They mainly recognize extracellular matrix ligands and cell surface ligands. They mainly act as traction receptors and can transmit and detect changes in the mechanical forces acting on the extracellular matrix .Integrin β4 only binds to integrin α6 to form a heterodimer , and itsThrough the intracytoplasmic region of integrin β4, it interacts with ECM molecules to activate many intracellular signal mediators, including FAK, src, PKC, PI3K, and MAPKs, resulting in alterations in the actin cytoskeleton and gene expression . For exaTherefore, integrin β4 can activate intracellular signal transduction in normal tissues and can reorganize the actin cell signal skeleton to maintain the integrity of epithelial cells. Recent studies found that integrin β4 promotes cell proliferation, migration, and invasion and plays a pivotal role in tumorigenesis, leading to poor prognosis and reduced survival rates .Integrin β4 is overexpressed in a variety of human cancers. In many cases documented in studies, it is positively correlated with poor prognosis .Both quantitative mass spectrometry analysis and Western blot analysis showed that integrin β4 is abundantly present in lung cancer cells. Clinical information was available on 21 patients with a median age at diagnosis of 63 years (range: 44–79 years). Survival information was available for 20 patients. The five-year overall survival for MUC5AC-negative patients was 93% , compared to 67% in the MUC5AC-expressing patients . MUC5AC is a class of mucins that are secreted and polymerized to form gels in the airways. It is regulated at the transcriptional, posttranscriptional, and epigenetic levels, and posttranslational modifications play an important role in mucin binding and the clearance of microbes and pollutants . It is oThe role of integrin β4 in breast cancer progression has been well established . StudiesIntegrin β4 is used to identify more aggressive subtypes of mesenchymal cancer cells . Sung etIntegrin β4 can induce an invasive status of breast cancer cells. The acyltransferase DHHC3 transfers palmitate as palmitoyl-CoA to the cysteines of integrin β4, which induces its palmitoylation and then triggers the invasive status of breast cancer cells . Cell viIntegrin β4 also plays a vital role in the occurrence and development of prostate cancer. Studies found that integrin β4 promotes prostate tumorigenesis by co-expressing with ErbB2 and c-Met in tumor progenitor cells . A compeVarious forms of integrin α6β4 can differentially regulate intestinal epithelial cell functions under both normal and pathological conditions . A studyThe expression and function of integrin β4 in the tumors listed above are described in To explore the downstream signaling pathways of integrin β4, cBioPoral was used to detect some genes related to integrin β4. Among them, integrin β4 is strongly correlated with EGFR, which amplifies proliferative and invasive signaling. EGFR-family genes EGF, EGFR, and ErbB3 are also strongly related to integrin β4. In the work map, a number of laminin subunits  connect with integrin β4. This is consistent with the finding that integrin β4 binds laminin-332 in the extracellular matrix, which indicates that integrin β4 plays a vital role in the stabilization of cells, which means that cell invasion and migration can be limited . PhosphoOverexpression of integrin α6β4 is related to aggressive tumor behavior and poor prognosis . Six houIn the process of cancer progression, integrin α6β4 is released from hemidesmosomes, responds to the wounded epithelium or cancer progression, and is located in the F-actin protrusions ,38,39,40Integrin β4 can promote the invasiveness of certain malignant tumors, such as squamous cell carcinoma, breast cancer, and gastric cancer, through the MAPK and NF-κB activation pathways ,42,43,442+/PKC; the Sp1/CaM and Akt/GSK-3β/Snail1 signaling pathways are also activated when glucosamine triggers integrin β4/plectin complex reduction [The extracellular domain of integrin β4 has potential glycosylation sites. A report showed that N-glycan deletion on integrin β4 impaired integrin-β4-dependent cancer cell migration, invasion, and growth in vitro and diminished tumorigenesis in vivo, which means that N-glycosylation is important in cancer progression. It activates the intracellular PI3K pathway to promote cell invasion and migration  and Ca2+eduction .Certain endocrine substances can also affect tumor cell invasion. For example, the N-terminal truncated subtype of the p63 transcription factor ΔNp63 acts as a transcription factor for integrin β4, and estrogen can activate estrogen receptor α (ERα) transcription, thereby inducing ΔNp63 expression; then, ΔNp63 induces the expression of integrin β4, which leads to the phosphorylation of AKT and enhances cell viability and motility . ChangesThe invasive and metastatic phenotype promoted by integrin α6β4 signaling is mediated by the phosphorylation of the cytoplasmic tail of the integrin β4 subunit . As mentA study showed that the proliferation of tumor cells is promoted at a relatively low concentration when integrin β4 interacts with netrins, which are secretory molecules of laminin . For exaEpithelial–mesenchymal transition (EMT) is an important change in cell phenotype. It frees epithelial cells from the structural constraints imposed by the tissue structure. Its core elements include the dislocation of desmosomes and a reduction in intercellular adhesion. More importantly, after EMT, cells show an increase in motor potential. Therefore, EMT is a fundamental process that underlies development and cancer . StudiesTGF-β1 is an important molecule in the initiation of EMT . It is nMoreover, enhanced ECM1 expression facilitates gene expression levels associated with EMT. ECM1 directly interacts with integrin β4 and activates the ITGB4/FAK/SOX2/HIF-1α signal pathway mentioned above .Additionally, a zinc-finger transcription factor, containing KRAB and SCAN domains, ZKSCAN3, directly binds to the integrin β4 promoter and enhances its expression; then, integrin β4 triggers FAK to activate the AKT signaling pathway to promote EMT progression in hepatocellular carcinoma .Tumor angiogenesis is an important condition for tumorigenesis and is crucial for tumor growth ,71. InteDysfunction of the vascular endothelial cell (EC) barrier is regarded as a key feature of tumor angiogenesis, and lipid rafts receptor c-Met is reported to mediate increases in EC barrier integrity. According to Yulia Ephstein et al., integrin β4 is an essential participant in this process . There aFrom the above description of the relationship between integrin β4 and tumors, it is known that integrin β4 is differentially expressed in many tumors. Its extracellular domain constitutes the cytoskeleton and affects the matrix structure. The intracellular domain activates various signaling pathways to produce different cell behaviors. Integrin β4 has an inseparable relationship with tumors. Therefore, integrin β4 is regarded as a potential tumor marker and plays a vital role in the diagnosis and treatment of tumors.Integrin β4 can regulate key signaling pathways related to cancer progression and promote the migration, invasion, and proliferation of cancer cells . StudiesIn malignant tumors, lymphatic vessel infiltration (LVI) and peripheral nerve infiltration (PNI) are two important pathological parameters that require accurate assessment. Studies found that both LVI and PNI are clearly and accurately outlined by integrin β4 immunostaining. Integrin β4 is expressed in most tumor cells, which can identify LVI and PNI that are invaded by small tumor clusters. The applicability of integrin β4 was also confirmed in nine other types of malignant tumors, including colon cancer, prostate cancer, esophageal cancer, lung cancer, renal cancer, uterine cancer, tongue cancer, bladder cancer, and liver cancer. Integrin β4 has therefore become a reliable marker for the simultaneous detection and diagnosis of LVI and PNI .As the upstream transcription factor of integrin β4, miR-21 significantly affects the expression of integrin β4, thereby affecting the migration of colon cancer cells. The tumor suppressor pdcd4 inhibits transformation and invasion and is downregulated in cancer. It is a newly identified tumor suppressor gene involved in the occurrence of colon cancer . miR-21 The aforementioned mucin MUC5AC, which interacts with integrin β4, was also found to affect the expression of focal adhesion kinase (FAK) in the downstream signaling pathway of integrin β4, leading to the migration of lung cancer cells. Therefore, mucin MUC5AC co-localized with integrin β4 is a marker of poor prognosis in lung cancer .Integrin β4 participates in multiple signaling pathways and can also enhance them, including ErbB2 , PI3K 7, FAK/AKTp = 0.004) [Integrin β4 is differentially expressed in tumors and significantly affects the prognosis and survival rate of patients. For example, Kaplan–Meier curves and univariate analysis demonstrated that high ITGB4 expression was significantly associated with unfavorable overall survival in colon cancer  . Integri= 0.004) . Immunoh= 0.004) . Other r= 0.004) .ARRDC3 is a metastasis inhibitor that can induce NEDD4-dependent ubiquitination of ITG β4 and targeting of endosomal integrin β4 into lysosomes, thereby reducing the level of integrin β4 in extracellular vesicles, to reduce the metastasis potential of the extracellular vesicles of breast cancer cells. ARRDC3 can also reduce the metastatic potential of breast cancer cell-derived integrin β4 + EVs, which are mainly detectable from supernatants of TNBC by reducing integrin β4 levels in EVs. Therefore, the ARRDC3/ITG β4 pathway has shown potential for the targeted therapy of TNBC . FAK is In the serum and tissues of gastric cancer patients, the level of extracellular matrix protein (ECM1) is positively correlated with tumor invasion and recurrence. It directly interacts with integrin β4 to activate the integrin β4/FAK/glycogen synthase kinase 3β signaling pathway and to induce the expression of transcription factor SOX2, thereby enhancing the activity of the hypoxia-inducible factor alpha (HIF-1α) promoter to regulate the metastasis of gastric cancer cells. This is significant for the development of therapeutic targets to prevent tumor metastasis and recurrence . RibosomIntegrin β4 and its phosphorylated form can promote cell migration and invasion in pancreatic cancer. p-integrin β4-Y1510 integrin β4 phosphorylated at tyrosine position 1510) can regulate the downstream MEK1-ERK1/2 signaling cascade and affect tumor blood vessel generation, invasion, and metastasis ,91,92,93SEC is a small chiral molecule. By inducing integrin β4 nuclear translocation, nuclear integrin β4 can bind to the ATF3 promoter region to activate ATF3 expression, upregulate downstream pro-apoptotic genes, and promote the apoptosis of cancer cells expressing high levels of integrin β4. It also promotes the binding of annexin A7 (ANXA7) to integrin β4, activates ANXA7, and triggers the phosphorylation of integrin β4 to promote nuclear translocation. Therefore, SEC is a potential target drug to treat integrin-β4-related tumors .Studies showed that integrin β4 is a transcription target of TAp73 . TAp73 iBased on the numerous pathways mediated by integrin β4, blocking the signal pathway is also a reasonable approach to treating cancer. For example, integrin β4 combines with a variety of tyrosine kinases  to enhance its signaling function. Genetic studies showed that integrin β4 signaling promotes both angiogenesis and tumorigenesis. Therefore, some researchers proposed that blocking integrin β4 and receptor tyrosine kinase signaling simultaneously is a potential rational therapy for cancer . NECTIN-Integrin β4 interacts with certain drugs and may be a molecule that induces tumor resistance. Gefitinib is one of the representative drugs of EGF receptor inhibitors (EGFRs), which is a transmembrane protein including an extrinsic ligand-binding domain, a single hydrophobic transmembrane region, and an intrinsic tyrosine kinase domain. It is usually used as an antiproliferative agent and induces cell apoptosis. It is used to treat patients suffering from cancer due to EGFR mutations. However, in clinical treatment with gefitinib, drug resistance appears in most patients . StudiesBerberine is an extract with a long history of use in Chinese herbal medicine. In the past few years, berberine was shown to have therapeutic effects on many types of cancers, such as osteosarcoma, prostate cancer, liver cancer, etc. ,102,103.Integrin β4 palmitoylation is a post-translational modification required for lipid raft positioning and signaling activity, which can enhance the invasive potential of cancer cells ,105. IntStudies showed that after ionizing radiation exposure, cell integrin β4 tyrosine residue 1510 is phosphorylated, which leads to the activation of the integrin α6β4–Src–AKT signaling pathway, and then leads to the disappearance of p21 targeted by p53, prevents the activation of photoproteinase, and causes tumor cells to age during radiation exposure. Therefore, integrin β4 and PI3K/AKT may be important targets for radiotherapy .In the past few years, the prominent differential expression of integrin β4 in various tumors has attracted the attention of researchers. Therefore, research on integrin β4 has concentrated on the field of tumors. Scientists have discovered the differential expression of integrin β4 and its related upstream and downstream molecular pathways in different types of cancer models. As far as the current research status is concerned, the role of integrin β4 in various tumors is relatively clear. Integrin β4 regulates various tumorigenesis processes, such as invasion, migration, proliferation, epithelial–mesenchymal transition, and tumor angiogenesis. With its widespread presence in tumors, we suggest that integrin β4 can be used as a non-specific tumor marker for the diagnosis and treatment of tumors.


Commercial tobacco use is the leading cause of preventable disease, disability, and death in the United States. Most tobacco product use begins during adolescence. In recent years, tobacco products have evolved to include various combusted, smokeless, and electronic products.2021.The National Youth Tobacco Survey (NYTS) is an annual, cross-sectional, school-based, self-administered survey of U.S. middle school (grades 6–8) and high school (grades 9–12) students. A three-stage cluster sampling procedure is used to generate a nationally representative sample of U.S. students attending public and private schools. NYTS is the only nationally representative survey of U.S. middle and high school students that focuses exclusively on tobacco use patterns and associated factors. NYTS provides data to support the design, implementation, and evaluation of comprehensive youth tobacco use prevention and control programs and to guide tobacco regulatory activities. Since 2019, NYTS has been administered electronically via tablet computers. Because of emergency COVID-19 protocols that were in place across the United States during the 2021 NYTS fielding window , the 2021 survey was administered using a web URL to allow participation by eligible students learning under varying instructional models . In total, 50.8% of student respondents reported completing the survey in a school building or classroom and 49.2% at home or some other place. CDC and the Food and Drug Administration (FDA) analyzed data from the 2021 NYTS to assess tobacco product use patterns and associated factors among U.S. middle and high school students. Overall, 20,413 students  completed the questionnaire from 279 schools . The overall response rate, defined as the product of the student and school response rates, was 44.6%. The sample was weighted to represent approximately 11.97 million middle school students and 15.44 million high school students. Students with missing information about grade level were excluded from the school-level analyses (n = 135).In 2021, an estimated 34.0% of high school students (5.22 million) and 11.3% of middle school students (1.34 million) reported ever using a tobacco product . Current (past 30-day) use of a tobacco product was 13.4% for high school students (2.06 million) and 4.0% for middle school students . E-cigarettes were the most commonly currently used tobacco product, cited by 11.3% of high school students (1.72 million) and 2.8% of middle school students , followed by cigarettes, cigars, smokeless tobacco, hookahs, nicotine pouches, heated tobacco products, and pipe tobacco. Current use of any tobacco product was reported by 14.2% of students identifying as lesbian, gay, or bisexual (LGB) ; 18.9% of students identifying as transgender (versus 8.2% of not transgender); and 14.2% of students reporting severe psychological distress (versus 5.5% with no distress). Among students who currently used each respective tobacco product, frequent use (on ≥20 days of the past 30 days) ranged from 17.2% for nicotine pouches to 39.4% for e-cigarettes. Among current users of any tobacco product, 79.1% reported using a flavored tobacco product; by product, e-cigarettes were the most commonly used flavored tobacco product. Among current users of any tobacco product, the most commonly reported source of access was from a friend (32.8%). Among students who currently used e-cigarettes, 53.7% used a disposable device, 28.7% used a prefilled/refillable pod or cartridge device, 9.0% used a tank or mod system (a system that can be customized by the user), and 8.6% did not know the device type. Among students who had ever used e-cigarettes, the most common reason for first trying them was “a friend used them” (57.8%); among current e-cigarette users, the most commonly cited reason for current use was “I am feeling anxious, stressed, or depressed” (43.4%). Among all middle and high school students, 75.2% reported past-year recognition of any antitobacco public education campaign ads. Exposure to marketing or advertising for any tobacco product was reported by 75.7% of students who had contact with an assessed potential source of tobacco product advertisements or promotions . Among students who reported using social media, 73.5% had ever seen e-cigarette–related content. Among all students, perceiving “no” or “little” harm from intermittent tobacco product use was highest for e-cigarettes (16.6%) and lowest for cigarettes (9.6%). Among students who currently used any tobacco product, 27.2% had experienced cravings during the past 30 days; 19.5% reported wanting to use a tobacco product within 30 minutes of waking. Moreover, 65.3% of students who currently used tobacco products were seriously thinking about quitting the use of all products, and 60.2% had stopped using all products for ≥1 day because they were trying to quit during the past 12 months.In 2021, approximately one in 10 U.S. middle and high school students (9.3%) had used a tobacco product during the preceding 30 days. By school level, this represented more than one in eight high school students (13.4%) and approximately one in 25 middle school students (4.0%). E-cigarettes were the most commonly used tobacco product in 2021. Tobacco product use was higher among certain subpopulations, such as those identifying as LGB or transgender, or those reporting psychological distress. Importantly, approximately two thirds of students who currently used tobacco products were seriously thinking about quitting. However, factors that might continue to promote tobacco product use among U.S. youths, such as the availability of flavors, access to tobacco products, exposure to tobacco product marketing, and misperceptions about harm from tobacco product use, remained prevalent in 2021.The continued monitoring of all forms of youth tobacco product use and associated factors through surveillance efforts including NYTS is important to the development of public health policy and action at national, state, and local levels. The 2021 NYTS was successfully administered during the COVID-19 pandemic using a web URL to allow participation by eligible students learning under varying instructional models. As a result of these modifications to the fielding procedures, any comparison of results between 2021 NYTS findings with previous years, including the direct attribution of any potential changes in tobacco product use, is not possible. Parents, educators, youth advocates, and health care providers can help protect youths from the harms of tobacco products, including e-cigarettes. In addition, the comprehensive and sustained implementation of evidence-based tobacco control strategies, combined with FDA’s regulation of tobacco products, is important for reducing all forms of tobacco product use among U.S. youths. TobaccoThe National Youth Tobacco Survey (NYTS), conducted periodically during 1999–2009 and annually since 2011, provides national data on estimates of tobacco product use to support the design, implementation, and evaluation of comprehensive youth tobacco prevention and control programs and to inform tobacco regulatory activities in the United States .Survey administration occurred during January 18, 2021–May 21, 2021. The final sample consisted of 508 schools, of which 279 participated (school response rate: 54.9%); 20,413 student questionnaires were completed out of a sample of 25,149 students (student response rate: 81.2%). Student response rates varied by school instructional model; student response rates were 85.8% among schools with in-person instruction (n = 69 participating schools), 77.9% in schools with exclusive distance learning or virtual instruction (n = 68 participating schools), and 81.4% for schools with hybrid instruction (n = 142 participating schools). Hybrid student instructional models define instances in which some educational instruction happened in person and some happened virtually. This included various scenarios, including all students alternating between in-person and virtual learning or a portion of students receiving in-person instruction at all times and the remaining students receiving virtual instruction at all times. The overall response rate for the 2021 NYTS, defined as the product of the school-level and student-level response rates, was 44.6%. After exclusion of outliers, the average survey completion time was approximately 22 minutes. A weighting factor was applied to each student record to adjust for nonresponse and for varying probabilities of selection. Weights were adjusted to ensure that the weighted proportions of students in each grade matched national population proportions. Additional information on the NYTS sampling design, recruitment procedures, and data weighting is available (Nine tobacco products were assessed: electronic cigarettes (e-cigarettes), cigarettes, cigars , smokeless tobacco , hookahs, pipe tobacco, bidis , heated tobacco products (HTPs), and nicotine pouches . For each product, ever use was defined as ever using the product, and current use was defined as use on ≥1 day during the past 30 days. Any tobacco product use was defined as use of one or more of the nine tobacco products. Use of two or more tobacco products was defined as use of two or more of the nine tobacco products. Any combustible tobacco product use was defined as use of one or more of the following: cigarettes, cigars, hookahs, pipe tobacco, and bidis.Demographic covariates assessed included sex , race and ethnicity , sexual identity , and whether the respondent identified as transgender .Social determinant indicators included academic status in school , and speaking a language other than English at home (yes or no). Additionally, a composite scale made up of four questions was used to assess psychological distress: “During the past two weeks, how often have you been bothered by any of the following problems?” 1) “little interest or pleasure in doing things”; 2) “feeling down, depressed, or hopeless”; 3) “feeling nervous, anxious, or on edge”; and 4) “not being able or stop or control worrying.” For each item, response options were numerically coded , summed (range: 0–12), and categorized as none (0–2), mild (3–5), moderate (6–8), or severe (9–12). Furthermore, a composite scale made up of four questions was used to assess family affluence. Numeric values were assigned to question responses as follows: 1) “Does your family own a vehicle ?” ; 2) “Do you have your own bedroom?” ; 3) “How many computers  does your family own?” ; and 4) “During the past 12 months, how many times did you travel on vacation with your family?” . Responses were summed (range: 0–9) and categorized into approximate tertiles based on the weighted distribution of scores in this sample as low (0–5), medium (6–7), and high (8–9).Respondents who reported ever use of any tobacco product were asked, “During the past 30 days, on how many days did you .” Response options ranged between 0 and 30 days. Response options were categorized as 1–5 days, 6–19 days, and 20–30 days. Frequent use was defined as using a product on ≥20 days of the past 30 days.For each tobacco product (excluding cigarettes), current users were asked, “Were any of the [tobacco product] that you used in the past 30 days flavored to taste like menthol, mint, clove or spice, alcoholic drinks, candy, fruit, chocolate, or any other flavor?” Response options were “yes,” “no,” and “don’t know.” Those who responded “yes” were categorized as a current flavored product user. Current flavored tobacco product users were asked, “What flavors were the [tobacco product] that you have used in the past 30 days? (Select one or more).” Response options were “menthol,” “mint,” “clove or spice,” “fruit,” “chocolate,” “alcoholic drinks ,” “candy, desserts, or other sweets,” and “some other flavor not listed here.” Those who selected “some other flavor not listed here” could provide a write-in response; write-in responses corresponding to an original response option were recoded.For cigarettes, current users were categorized as flavored (menthol) cigarette smokers if they responded “yes” to the question, “Menthol cigarettes are cigarettes that taste like mint. During the past 30 days, were the cigarettes that you usually smoked menthol?” or if they indicated “Kool” or “Newport” as their usual cigarette brand during the past 30 days. Usual cigarette brand was determined based on responses to two questions: “During the past 30 days, what brands of cigarettes did you smoke? (Select one or more)” and “During the past 30 days, what brand of cigarettes did you usually smoke? (Choose only one answer).” If “Kool” or “Newport” was the only brand selected for the first question, or if multiple brands were selected in the first question and “Kool” or “Newport” was selected for the second question, “Kool” or “Newport” was considered the respondent’s usual brand.Respondents who reported current use of e-cigarettes were asked, “Which of the following best describes the type of e-cigarette you have used in the past 30 days? If you have used more than one type, please think about the one you use most often.” Response options were “A disposable e-cigarette ,” “An e-cigarette that uses pre-filled or refillable pods or cartridges ,” “An e-cigarette with a tank that you refill with liquids (including mod systems that can be customized by the user),” and “I don’t know the type.”Respondents who had ever used e-cigarettes were asked, “Why did you first use an e-cigarette?” Respondents who reported current e-cigarette use were further asked, “Why do you currently use e-cigarettes?” For both questions, respondents could select one or more of 14 specified reasons. Respondents who indicated, “I used/use them for some other reasons” to either question could specify a write-in response; analyses of write-in responses were not included in this report.For each tobacco product, access sources were assessed by two questions: “During the past 30 days, how did you get your [tobacco product]?” (respondents could select one or more of eight specified responses) and “During the past 30 days, where did you buy your [tobacco product]?” (respondents could select one or more of 12 specified responses). Respondents could specify a write-in response; analyses of write-in responses were not included in this report.All respondents were asked two questions regarding public education campaigns against tobacco product use: “In the past 12 months, have you seen or heard The Real Cost, on television, the Internet, social media, or radio as part of ads about tobacco?”  and “In the past 12 months, have you seen or heard any other ads against tobacco with the following names or slogans on television, the Internet, social media, or on the radio?” Respondents could select one or more of “Truth,” “Tips or Tips from Former Smokers,” “Fresh Empire,” “This Free Life,” or “some other ad” or could select “I haven’t seen or heard any of these ads.” Those who indicated having seen “some other ad” could specify with a write-in response; analyses of write-in responses were not included in this report. A composite of having recognized at least one ad against tobacco product use from a specified response option also was generated.Exposure to tobacco product marketing (advertisements or promotions) was assessed separately for e-cigarettes and cigarettes or other tobacco products for four sources: retail stores; Internet; television, streaming services, or movies; and newspapers or magazines. Respondents were asked, “When you , how often do you see ads or promotions for ?” Respondents were categorized as exposed if they responded “sometimes,” “most of the time,” or “always” or unexposed if they responded “never” or “rarely.” Those who reported “I do not use the Internet,” “I do not read newspapers or magazines,” “I never go to a convenience stores, supermarket, or gas station,” or “I do not watch TV or streaming services or go to the movies” were excluded from the analysis.All respondents were asked, “How often do you use social media?” Respondents who reported a response other than “never/I don’t use social media” were asked, “When you use social media, how often 1) “do you see posts or content  related to e-cigarettes?”; 2) “do you post pictures or videos of yourself or someone else using e-cigarettes?”; and 3) “have you liked, commented, or shared posts or content  related to e-cigarettes?” For each question, response options were “never,” “less than monthly,” “monthly,” “weekly,” or “daily.”The 2021 NYTS assessed harm perceptions for five tobacco products: e-cigarettes; cigarettes; cigars, cigarillos, or little cigars; smokeless tobacco ; and hookahs. All respondents were asked, “How much do you think people harm themselves when they  some days but not every day?” Response options were “no harm,” “little harm,” “some harm,” and “a lot of harm.”Students who currently used any tobacco product were asked, “During the past 30 days, have you had a strong craving or felt like you really needed to use a tobacco product of any kind?” (yes or no); and “How soon after you wake up do you want to use a tobacco product of any kind?” Response options were dichotomized as wanting to use a tobacco product within 30 minutes  or not .Students who currently used any tobacco product were asked, “Are you seriously thinking about quitting the use of all tobacco products?” Responses were dichotomized as yes  or no . Students who currently used any tobacco product were asked, “During the past 12 months, how many times have you stopped using all tobacco products for one day or longer because you were trying to quit all tobacco products for good?” Responses were dichotomized as making a past-year quit attempt  or not making an attempt .Statistical analyses were conducted by using SAS-callable SUDAAN software  to account for the complex sampling design. Weighted prevalence estimates and 95% CIs were computed for all measures; when applicable, population totals were estimated from probability weights. Results with unweighted denominators <50 or a relative standard error >30% are not reported. Comparisons of estimates from the 2021 NYTS with previous years were not possible because of the modifications to the fielding procedures in 2021 in response to the COVID-19 pandemic. The 20,413 student records were weighted to represent approximately 27.56 million students. On the basis of self-reported grade level, this included 9,763 middle school students (11.97 million) and 10,515 high school students (15.44 million); 135 students with missing information on grade level were excluded from school-level analyses. Overall, 50.8% of student respondents reported completing the survey in a school building or classroom and 49.2% at home or some other place.In 2021, among U.S. middle and high school students, 24.1% (6.6 million) reported ever use of a tobacco product  . Among sOverall, among middle and high school students, 9.3% (2.55 million) reported current (past 30-day) use of any tobacco product . Among sAmong high school students, 13.4% (2.06 million) reported current use of any tobacco product . Among hAmong middle school students, 4.0%  reported current use of any tobacco product. Among middle school students who currently used tobacco products, 40.0%  currently used any combustible tobacco product and 32.5%  currently used two or more tobacco product types. Among middle school students, e-cigarettes were the most commonly used tobacco product , followed by cigarettes (1.0%), cigars and smokeless tobacco (both 0.6%), hookahs and HTPs (both 0.4%), nicotine pouches (0.3%), and pipe tobacco (0.2%).By race and ethnicity, ever use of any tobacco product was reported by 26.7% of students who were non-Hispanic White, 22.4% of students who were Hispanic, 21.9% of students who were non-Hispanic Black, and 16.1% of students who were non-Hispanic other race . Ever usEver use of any tobacco product was reported by 35.4% of students identifying as LGB, 22.8% of those identifying as heterosexual, and 14.4% of those who were not sure  and 37.9For psychological distress, prevalence of ever use of any tobacco product ranged from 16.6% (none) to 37.8% (severe) . PrevaleBy race and ethnicity, current use of any tobacco product was reported by 11.0% of students who were non-Hispanic White, 8.2% of students who were non-Hispanic Black, 7.4% of students who were Hispanic, and 5.4% of students who were non-Hispanic other race . CurrentOverall, current use of any tobacco product was reported by 14.2% of students identifying as LGB, 7.9% of those identifying as heterosexual, and 5.5% of those who were not sure  and 18.9By psychological distress, prevalence of current use of any tobacco product ranged from 5.5% (none) to 14.2% (severe) . CurrentAmong students who currently used each tobacco product, frequent use (on ≥20 of the past 30 days) was 39.4%  for e-cigarettes, 29.5%  for chewing tobacco, snuff, or dip, 26.1%  for snus, 22.1%  for HTPs, 20.7%  for cigars, 19.9%  for hookahs, 18.9%  for cigarettes, and 17.2%  for nicotine pouches . For neaAmong students who currently used any tobacco product, 79.1%  reported using flavored tobacco product(s) in the past 30 days . Among shttps://stacks.cdc.gov/view/cdc/114659); mint was the most commonly reported flavor type for smokeless tobacco (69.2%) and nicotine pouches (53.5%). Menthol use was reported as 50.2% for nicotine pouches, 38.8% for cigarettes, 38.2% for smokeless tobacco, 28.8% for e-cigarettes, 26.5% for HTPs, 21.0% for cigars, and 17.0% for hookahs.Among students who currently used each flavored tobacco product, fruit was the most commonly reported flavor type for e-cigarettes (71.6%), hookahs (73.5%), cigars (65.0%), and HTPs (46.4%)  (Supplemhttps://stacks.cdc.gov/view/cdc/114659).Among students who currently used e-cigarettes, disposable e-cigarettes were the most commonly used device type , followed by prefilled or refillable pods or cartridges , and tanks or mod systems  . EstimatAmong students who ever used e-cigarettes, the most common reasons for first use were “a friend used them” (57.8%), “I was curious about them” (47.6%), “I was feeling anxious, stressed, or depressed” (25.1%), and “to get a high or buzz from nicotine” (23.3%) . The mosAmong students who currently used e-cigarettes, the most common reasons for current use were “I am feeling anxious, stressed, or depressed” (43.4%), “to get a high or buzz from nicotine” (42.8%), “a friend uses them” (28.3%), and “I can use them to do tricks” (20.0%) . The mosAmong students who currently used any tobacco product, during the past 30 days, 32.8% got their products from a friend, 31.3% bought the products themselves, 28.8% had someone else buy the products for them, and 26.3% had someone offer the products to them .By purchase locations, 22.5% of students who currently used tobacco products reported purchasing from another person , 20.2% from vape shops or tobacco shops, and 19.6% from gas stations or convenience stores; 48.6% of current tobacco product users did not purchase the products they used in the past 30 days.Among all students, 75.2%  had seen or heard at least one public education campaign against tobacco product use within the past year . RecogniAmong students who reported contact with a potential source of tobacco product marketing, 75.7%  reported exposure to any tobacco product marketing from one or more of these sources . The preIn total, 91.5% (23.06 million) of U.S. middle and high school students reported using social media. Among all social media users, 73.5%  reported ever seeing e-cigarette-related posts or content; 13.7%  reported seeing e-cigarette–related content daily . An estihttps://stacks.cdc.gov/view/cdc/114659).Among all students, the percentage who reported that intermittent use of tobacco products causes a lot of harm was highest for smokeless tobacco (48.3%), followed by cigarettes (47.0%), hookahs (42.0%), e-cigarettes (41.8%), and cigars (41.5%) . The perAmong students who currently used any tobacco product, 27.2%  reported experiencing cravings for tobacco product of any kind during the past 30 days . OverallAmong students who currently used any tobacco product, 65.3%  reported that they were seriously thinking about quitting all tobacco products. In addition, 60.2%  of current tobacco product users overall reported that they stopped using all tobacco products for ≥1 day during the past 12 months because they were trying to quit.Findings from the 2021 NYTS indicate that approximately one in four students (24.1%), including approximately one in three high school students (34.0%) and one in nine middle school students (11.3%), had ever used a tobacco product. Furthermore, approximately one in 10 students (9.3%), including more than one in eight high school students (13.4%) and one in 25 middle school students (4.0%), had used a tobacco product during the past 30 days. Approximately three in 10 students (29.0%) who currently used any tobacco product reported using two or more tobacco products during the past 30 days; youths who use multiple tobacco products are at higher risk for developing nicotine dependence and might be more likely to continue using tobacco into adulthood , and specifically cigar use (3.1%). While youth use of tobacco products in any form is unsafe .The findings in this report are subject to at least three limitations. First, because of the implementation of emergency COVID-19 protocols across the country during the 2021 NYTS fielding, the survey was administered online to allow participation by eligible students at home, school, or somewhere else. Previous research has shown that the prevalence of tobacco use might differ by interview setting  ever using a tobacco product, and approximately one in 10 students (9.3%) using a tobacco product during the past 30 days. Furthermore, disparities in tobacco product use continue to exist among population subgroups. In 2021, any tobacco product use was higher among students who identified as LGB than heterosexual; among students who identified as transgender than those not transgender; and among students who reported increased symptom severity of psychological distress. Multiple factors continue to promote tobacco product use and initiation among youths, including flavors (such as menthol), marketing, and misperceptions of harm. The comprehensive and sustained implementation of population-level evidence-based tobacco control strategies, combined with FDA’s regulation of tobacco products, is important for preventing and reducing all forms of tobacco product use among all U.S. youths. In addition, as the tobacco product marketplace continues to diversify, surveillance among youths for all forms of tobacco product use and associated factors is important to the development of public health policy and action at the national, state, and community levels.