M. catarrhalis, a recent study suggested otherwise. Next generation sequence based comparative genomics has revolutionized the mining of potential novel drug resistant mechanisms. In this study, two pairs of resistant and susceptible M. catarrhalis isolates with different multilocus sequence types, were investigated for potential differential genes or informative single nucleotide polymorphisms (SNPs). The identified genes and SNPs were evaluated in 188 clinical isolates. From initially 12 selected differential genes and 12 informative SNPs, 10 differential genes  and 6 SNPs  were identified as possibly linked to macrolide resistance in M. catarrhalis. Most of the identified differential genes and SNPs are related to methylation of ribosomal RNA (rRNA) or DNA, especially MCR_0020 and rrmA. Further studies are needed to determine the function and/or evolution process, of the identified genes or SNPs, to establish whether some novel or combined mechanisms are truly involved in M. catarrhalis macrolide resistance mechanism.Although previous studies have confirmed that 23S rRNA gene mutation could be responsible for most of macrolide resistance in  M. catarrhalis is a prominent pathogen that causes acute otitis media in children and lower respiratory tract infections in adults (such as exacerbations of chronic obstructive pulmonary disease)1M. catarrhalis isolates, macrolide initially appeared to provide a safe alternative to β-lactam antibiotics for the treatment of respiratory illnesses with a low risk of serious side effects, especially for childrenM. catarrhalis isolates are still susceptible to macrolide in many countries4590 of 0.25 g/L, macrolide-resistant M. catarrhalis have been reported in several studies worldwide78M. catarrhalis, and that A2330T  mutation was related to high-level macrolide-resistance111213M. catarrhalis strains with high level macrolide resistance also exhibit mutations in ribosomal proteins L4 (V27A and R161C) and L22 (K68T)M. catarrhalis, mutation of the 23S rRNA gene is usually not the main reason for macrolide-resistance in other bacterial species , we studied in detail 2 macrolide resistant and 2 susceptible M. catarrhalis isolates using genomic sequencing. The aim was to screen for other possible resistance genes or mutations (apart from 23S rRNA gene mutation) responsible for macrolide resistance in M. catarrhalis, and to further confirm the findings in a large collection of clinical isolates.In order to investigate potential novel mechanisms involved in macrolide resistance by M. catarrhalis, or whether other mechanisms, including methylase, efflux pump, or other genes or mutationsM. catarrhalis are so different from other macrolide resistant cocci, we assumed that macrolide resistance in M. catarrhalis may be associated with the distinct genomic background of this organism.Firstly, we intended to gain further insights into whether A2330T mutation is solely responsible for macrolide resistance in M. catarrhalis.In order to answer the two questions above, comparative genomics and multiple molecular typing methods for genetic population were used in this study. Based on the genome-wide data of two pairs of macrolide susceptible and resistant isolates (n = 4), and further evaluation in 188 clinical isolates, we found that six informative SNPs and ten differently expressed genes, possibly contribute to macrolide-resistance in All the authors confirm that all experiments were performed in accordance with relevant guidelines and regulations. Study materials involved in our study are clinical isolates, no human subjects (including the use of tissue samples) were included in the present study, so informed consent was not required in this study which has been approved by the Human Research Ethics Committee of Peking Union Medical College Hospital (No. S-424).M. catarrhalis isolates (2 susceptible and 2 resistant) arbitrarily chosen. The details of the two susceptible isolates are as follows:M. catarrhalis isolated in 2013 from a purulent sputum of a 33 year old outpatient woman with lower respiratory tract infection. The erythromycin and azithromycin MIC of this organism was 0.125 g/L each.Strain 13R13726 was M. catarrhalis isolate with erythromycin and azithromycin MICs of 0.125 g/L each, and was isolated in 2011 from a 40-year-old woman admitted in hospital with lower respiratory tract infection.Strain 11XR1696 was an Genome sequencing was performed on two pairs of M. catarrhalis with erythromycin and azithromycin MICs of >256 g/L each. This organism was isolated in 2013 from the purulent sputum of a 61-year-old outpatient man with chronic obstructive pulmonary disease.Strain 13R13685 was M. catarrhalis with erythromycin and azithromycin MICs of >256 g/L each, and was isolated from the purulent sputum of a 62-year-old inpatient with lower respiratory tract infection.Isolate 11XR4410 was Details of the two resistant isolates are as follows:M. catarrhalis (including 11XR4410 and 13R13685) and 167 macrolide-susceptible M. catarrhalis (including 11XR1696 and 13R13726) isolates from our previous studyIn addition, 21 macrolide-resistant M. catarrhalis isolates were confirmed by E-test  method to get the minimum inhibitory concentrations (MICs). Staphylococcus aureus ATCC 25923 was used for quality control.As previously published, all the isolates n = 188) were tested for susceptibility to erythromycin and azithromycin using the disc diffusion  method according to CLSI 2010 guideline8 were teIsolates were grown overnight at 35 °C on blood agar plates and DNA extracted using the QIAamp DNA Mini Kit  following the manufacturer’s instructions.http://mlst.warwick.ac.uk/mlst/dbs/Mcatarrhalis), which was performed on the 2 pairs of macrolide-susceptible and resistant M. catarrhalis isolates, was inferred from the best hit homologs of abcZ (ATP-binding protein), adk (adenylate kinase), efp (elongation factor P), fumC (fumarate hydratase), glyRS (glycyl-tRNA synthetase beta subunit), mutY (adenine glycosylase), ppa (pyrophosphate phospho-hydrolase), and trpE (anthranilate synthase component I) genes present in each genome, in accordance with the M. catarrhalis MLST scheme developed previously (Multilocus sequence typing (MLST) (eviously  19.copB polymerase chain reaction–restriction fragment length polymorphisms were performed on the four isolates as previously describedPulsed-field gel electrophoresis (PFGE) and M. catarrhalis isolates (one pair susceptible and the other resistant). DNA libraries were constructed with genomic DNA using kits provided by Illumina Inc. according to the manufacturer’s instructions. Libraries with an insert size of 500-bp were prepared for each isolate. Methods for DNA manipulation, including formation of single-molecule arrays, cluster growth and paired-end sequencing, were performed on an Illumina Hiseq 2500 sequencer according to standard protocols. The Illumina base-calling pipeline was used to process the raw fluorescent images and call sequences. Raw reads of low quality from paired-end sequencing (those with consecutive bases covered by fewer than five reads) were discarded. The bioproject accession number for the four isolates  is PRJNA338378.Genome sequencing was performed on the two pairs of M. catarrhalis reference genome, the BBH18 reference genome (GenBank accession number: CP002005.1) and M. catarrhalis isolate E22 plasmid pLQ510 (GenBank accession number: NC_011131.1) using Burrows-Wheeler Alignment (BWA) software. Nucleotide base coverage of each gene from each of the isolates on the BBH18 and plasmid pLQ510 genomes was assessed using Samtools mpileup packages (http://samtools.sourceforge.net/). Based on the Samtools mpileup results, the average coverage for each gene was calculated. If the gene coverage was different between the resistant and susceptible groups by either being present or absent, or if present, by significantly (P < 0.05) different levels of gene coverage, those genes were considered as differential genes.The paired-end reads from each of the four genome sequenced isolates were mapped to a previously published For SNPs, the number of genome nucleotide bases of a test isolate that were similar to those of the reference genome (ref) were determined. Likewise the number of test isolate genome nucleotide bases that were different  to the reference genome were also determined for each isolate. High quality SNPs were defined as SNPs that satisfied the following criteria: alt/ >0.95 (which means to be different from the reference genome nucleotide base) or alt/ ≤M. catarrhalis isolates  derived from Peking Union Medical College Hospital (PUMCH): 2010–2013, to detect the following identified differential genes as per definition above; mboIA, mcbC, mcbI, mboIB, MCR_1794, MCR_1795, lgt2B/C, dpnI, mcbB, MCR_0360, MCR_0361, and mcbA . A standard PCR protocol was used for all PCRs. The PCR protocol for rumA, MCR_0016, MCR_0020, MCR_1465, copB and rrmA genes used an initial annealing temperature of 94 °C for 5 min, followed by 35 cycles of 94 °C for 30 sec, 55 °C for 30 sec, 72 °C for 90 sec, and a final extension step of 72 °C for 7 min. For the rpIF gene, a standard PCR protocol comprising 94 °C for 5 min, followed by 35 cycles of 94 °C for 30 sec, 50 °C for 30 sec, 72 °C for 90 sec, and an extension time of 7 min at 72 °C, was used. We further investigated the 23S rRNA gene sequence changes in a 934-bp region in all the 73 M. catarrhalis isolates as per our previous studyPCR was performed to detect M. catarrhalis strain, BBH18; GenBank accession number. NR_103214.1).DNA sequencing was performed on the 73 isolates using the same primers used for PCR amplification, providing bidirectional coverage. The obtained sequences were aligned to those of the wild type GenBank reference M. catarrhalis isolates from sputum of patients treated at PUMCH. The genome sizes of the four M. catarrhalis isolates that were studied in detail (2 susceptible and 2 resistant) ranged from 1.85 to 1.96 Mbp, with a mean size of 1.91 Mbp , including NP-ST-4 , NP-ST-5 , ST312, and ST327. Furthermore, 2 novel sequence variants for the abcZ (abcZ 61) and efp (efp 34) alleles were present in strains 13R13726 and 11XR1696, respectively (abcZ and ppa). All the four isolates belonged to copB II. We utilized PFGE analysis to determine the clonal relationship of the 4 isolates, and four pulsotypes were found (data not shown), suggesting origination from different clones.MLST analyses of the 2 pairs of susceptible and resistant ectively . HoweverM. catarrhalis isolate E22 plasmid pLQ510 (GenBank accession number: NC_011131.1) using BWA. When compared to the BBH18 reference genome, 96 differential genes were detected, including 88 hypothetical protein genes and 8 annotated genes . For the M. catarrhalis E22 plasmid pLQ510 comparison, 4 differential genes  belonging to annotated genes, were detected  were mapped to the BBH18 reference genome (GenBank accession number: CP002005.1) and detected .M. catarrhalis, there are four identical copies of rRNA  operons in which the 16S and 23S rRNA genes are interspersed with genes encoding tRNAs for isoleucine and alanineM. catarrhalis isolates (11XR4410 and 13R13685), A2330T and C2480T mutations could be detected in all the four different operons of these isolates, while A2144T mutation was only detected in four operons of strain 11XR4410.The paired-end reads from each isolate  were mapped to the BBH18 reference genome (GenBank accession number: CP002005.1) using BWA. SNPs occurring in at least one isolate were considered. A total of 19489 SNPs were detected when each of the four isolates was compared to BBH18 reference genome, and 4770 SNPs were found to be unique to susceptible (13R13726 and 11XR1696) or resistant isolates (11XR4410 and 13R13685). Considering that different non-synonymous mutations may cause the same alternation of amino acid, all the 4770 SNPs analyzed in this study were confirmed after assessment for both synonymous and non-synonymous mutations. In mboIA, mcbC, mcbI, mboIB, MCR_1794, MCR_1795, lgt2B/C, dpnI, mcbB, MCR_0360, MCR_0361, and mcbA) and 12 informative candidate SNPs  were considered relevant for macrolide resistance. The 12 selected annotated genes and 12 candidate SNPs were further tested in 188 M. catarrhalis isolates of clinical origin (21 macrolide resistant and 167 macrolide susceptible) and 73 isolates , respectively , mcbC (p < 0.0001), mcbI (p < 0.0001), mboIB (p = 0.0003), MCR_1794 (p = 0.0039), MCR_1795 (p = 0.0039), lgt2B/C (p < 0.0001), dpnI (p = 0.0476), mcbB (p < 0.0001), and mcbA (p < 0.0001) genes was statistically different between the two groups, while the presence of MCR_0360 (p = 0.4640) and MCR_0361 (p = 0.5844) was very similar in the two groups (The frequency distribution of the 12 annotated genes between the macrolide resistant (n = 21) and susceptible (n = 167) clinical isolates was compared using a χ2-test. The presence of o groups .rumA, T140C of rplF, G643A of MCR_0020, T270G of MCR_1465, C1348A of copB, and G238A of rrmA, was statistically different between the two groups (p < 0.05). In contrast, the presence of A1249G mutation of MCR_0016, G695A of MCR_1465, and A1205C of copB genes, was very similar in the two groups (p > 0.05)  using a χ2-test, indicated that the presence of the A2144T, A2330T, and C2480T mutation of 23S rRNA, C619T of  > 0.05) . DiagramM. catarrhalis macrolide resistance. In most studies, 23S rRNA gene mutation is singled out as being responsible for the majority of cases of macrolide resistance10M. catarrhalis remains unknown, though the presence of macrolide-resistant strains without any 23S rRNA gene mutations seem to suggest otherwise.Based on our literature review, we found that very few studies have examined the molecular mechanisms involved in M. catarrhalis isolates with the same MLST or pulsed field gel electrophoresis types, as there was considerable genetic diversity among the isolates. As such, it is clear that not all the SNPs and genes identified in this study can be considered to be highly associated with macrolide resistance, hence had to confirm some of them in a large collection of clinical isolates.Comparative genomics is a practical tool which has been widely used in the study of drug resistance mechanismsMCR_0020 and rrmA  (rumA and T140C of rplF)   and infoof rplF)  identifiMCR_0020_G643A, MCR_1465_T270G) were only detected in the resistant group, whilst among the differential genes, only one gene (lgt2B/C) was identified in the susceptible group. The remaining SNPs and differential genes were detected in both groups. In addition, among the remaining SNPs, C619T of rumA, T140C of rplF, and G238A of rrmA mutations, were always found together in the resistant group, and no definite pattern was obvious in the susceptible group. Moreover, the distribution frequency of the mcbB, mcbC and mcbI genes was similar between the two groups, and so was that of mboIA and mboIB, MCR_1794 and MCR_1795 genes. These findings suggest that these genes are associated with each other when they function in the cell.Furthermore, we analyzed the distribution of the identified 12 differential genes and 12 SNPs in the two groups , in order to find possible gene combinations associated with macrolide resistance . Among tInterestingly, the identified 12 SNPs and 12 differential genes could also be used to differentiate individual isolates even between two isolates which shared the same MLST type, such as strain xm21 (NP-ST-3) and c17 (NP-ST-3).MCR_0020 and rrmA) might be involved in this process. Many of the identified genes are related to the methylation of ribosomal RNA (rRNA) or DNA, and may solely, or in combination, with one another or with 23S rRNA gene mutation, be responsible for macrolide resistance in M. catarrhalis. However, the functions of these identified genes or SNPs, and the crystal structure of their translated proteins, are still unknown. We consider these findings as hypothesis generating and exploratory, requiring confirmation in the future to fully elucidate some of these findings.Based on the above results, we surmise that the molecular mechanism of macrolide resistance might not be as simple as previously thought10111213M. catarrhalis isolates would have yielded different candidate differential genes or informative SNPs. Second, Samtools pileup pipeline can yield less SNPs than other pipelines, therefore some SNPs potentially related to macrolide resistance might have been missed. Third, the selection of candidate differential genes and informative candidate SNPs was mainly based on reviewing relevant literature and further evaluation in 188 clinical isolates; it is possible that some relevant genes and SNPS may have been overlooked due to limited bioinformatic analysis. Fourth, none of the 10 annotated differential genes were assessed for expression under normal cultural conditions and/or in the presence of macrolides. And finally, it is not possible to rule out that the other 88 hypothetical proteins and 1862 SNPs not mentioned are not involved as they could have hidden some potentially important macrolide resistance genes. More studies are needed to fully understand the mechanism of macrolide resistance by M. catarrhalis. Our limited budget was a hindrance to carrying out more detailed studies.This study has several limitations. First, the four isolates used as the main anchor of the study were chosen arbitrarily. It’s possible that a different set of How to cite this article: Liu, Y.-L. et al. Use of next generation sequence to investigate potential novel macrolide resistance mechanisms in a population of Moraxella catarrhalis isolates. Sci. Rep.6, 35711; doi: 10.1038/srep35711 (2016).


Rosa sericea complex distributed in alpine regions of the temperate and subtropical zones in eastern Asia. We used three chloroplast (cp) DNA fragments  approximately 3,100 bp and nuclear microsatellite (nSSR) on eight sites to determine whether cold tolerant plants experienced expansion during the Pleistocene. The neutral test and mismatch distribution analysis (MDA) indicated that whole populations and major lineages of the Qinghai-Tibet Plateau (QTP) underwent expansion during the middle to late Pleistocene. Environmental niche modeling (ENM) indicates more suitable habitats during the Last Glacial Maximum (LGM) than at present. We concluded that the demographic history of R. sericea, which diverged in the middle Pleistocene, was mostly affected by climatic oscillations instead of by geographical barriers. The low genetic divergence, as well as the weak phylogenetic structure in the R. sericea complex both support treating this complex as a single taxon.While most temperate plants probably underwent glacial constriction to refugia and interglacial expansion, another type of interglacial refugia might have existed to maintain alpine plants during warm periods. To test this hypothesis, we applied phylogeographic methods to 763 individuals (62 populations) which belong to 7 taxonomically difficult species of the  Geographic changes, such as the uplifting of the Qinghai-Tibet Plateau and Rocky mountain systems, result in habitat fragmentation that forms barriers to gene flow, further leading to genetic diversification, accelerated variation and even speciation1234Two theories, named the pioneer model and the phalanx model, have been advanced to address the consequences of population expansion on genetic legacy791011Dryas integrifoliaPicea glaucaPinus kwangtungensis17Lagopus muta)In recent years, phylogeographic research has shown that glaciation may not only force population contractions in plants, but also promote expansion or persistence of cold adapted or cold tolerant species. For example, studies in Although recent phylogeographic studies have been conducted on various plant groups and many geographic regions21222324Rosa sericea complex comprises a group of shrubs in section Pimpinellifoliae DC. Ser. Sericeae (Crep.) Yu et Ku27R. sericea complex is a monophyletic group most closely related to R. hugonis Hemsl. and contains seven species: R. sericea, R. omeiensis, R. zhongdianensis, R. sikangensis, R. morrisonensis, R. taronensis, R. mairei or infraspecific taxaR. sericea complex has a broader eastward distribution. The complex may have had a continuous distribution in southeastern China in the past, and is a good candidate for a demographic study of cold adapted species.The R. sericea complex. In particular, we wanted to answer these questions: 1) Did range expansion exist in the demographic history of R. sericea? If it did, which factors  contributed to this expansion? 2) How were southwestern China – Taiwan disjunctions formed? Did continuous distributions once exist in eastern China? If so, then which part served as a bridge between the two areas? In addition, we also aimed to determine suitable species delimitations for the R. sericea complex.In this study, we used DNA sequences and a phylogeographic approach as well as niche modeling to determine the mechanism of range expansion and disjunction within the The three cpDNA-IGS surveyed across 691 individuals (belonging to 62 populations) were aligned. Of the 3057 bp, nucleotide substitutions occurred at 32 sites and 10 indels (from 1 to 24 bp) were present . After iπ) and haplotype (Hd) diversity across all populations was 0.00056 and 0.815. The QTP group exhibited the highest haplotype diversity (Hd = 0.779) while the largest group in Hengduan Mountains (region II in Hd = 0.522). Genetic diversity calculated for all populations (HT = 0.823) was higher than the average intra-population diversity (HS = 0.267). Relative high levels of genetic differentiation were observed . Permutation tests showed that NST was greater than GST in all groups and in the metapopulation  revealed a total of 254 alleles across the eight nSSR loci surveyed, along with high mean per-locus estimates of allele and gene diversity  was significant at each locus (P< 0.05) and averaged 0.298 across all loci , STRUCTURE yielded the highest likelihood when samples were clustered into three groups . The pre-defined taxa and the recognized clusters in detected . Three mdetected . Contactdetected .FCT increased with partitioning of species into 2 to 20 groups , and a large level of variation was due to differentiations between populations within geographic regions  and among geographical regions    . The AMO < 0.05) .Rosa sericea complex presented a radiation-shaped relationship, with a weak phylogeographic pattern (The tree topologies generated by Neighbor-joining (NJ) and Bayesian inference (BI) were congruent in terms of major clades, thus only the NJ tree is presented in Figure S2. Overall, 37 chlorotypes were clustered into three major lineages: 1) northern Hengduan Mountains and QTP, 2) southern Hengduan Mountains and Yungui Plateau, and 3) eastern China, named CPA to CPC, respectively . This wa pattern . We sepa−9 s/s/y, the divergence time for the Rosa sericea complex was estimated to be 0.482 Ma, with a 95% confidence interval (95% CI) of 0.281–0.722 Ma  and 0.352 Ma (95% CI 0.175–0.469 Ma), also espectively. Overall, all our results indicate a mid-Pleistocene divergence of populations within this complex.Assuming substitution rates of 2.0 × 100.722 Ma . We usedRosa sericea complex using a sudden demographic expansion model. The results showed that the whole populations and CPA lineage were unimodal, while lineages CPB and CPC were bimodal and multimodal, respectively. Accordingly, the two statistics –SSD and HRag – that assessed the fitness of the model only rejected the expansion model in lineage CPC. In neutrality tests, the whole group, lineage CPA and CPB showed negative values in Tajima’s D and Fu’s Fs test, which indicated population expansion. Only the whole lineage, however, showed significant negative value for Fu’s Fs , based on 10 replicates]. The model predicted suitable habitat for the species that was mostly coincident with its natural geographic distribution  except tf Taiwan . ObviousCercidiphyllumRosa sericea complex comprises no distinct geographic lineages as inferred from the chlorotype network and phylogenetic analysis Generally, if deep divergence occurred through paleogeological events, then a phylogeographic study should detect strong geographic clustering that coincides with known geographic boundaries. This scenario appears in some relict plants or relatively old species , and its major lineages diversified not earlier than the middle of Pleistocene  predicts rapid colonization of an area during glacial periods and fragmentation during interglacials accompanied by genetic drift and range expansions from interglacial refugia over short distances involving limited gene flow during glacial periodsAlthough the phalanx model may best explain the overall distributional patterns of the Rosa sericea complex is disjunct between southwest China and Taiwan   (R. sericea.We attempted to use our phylogenetic and population genetic data to delimit species within the  < 0.05) , compare 0.0001) . It is cR. sericea complex is comprised of a single species that underwent rapid geographic radiation during the LGM. The phylogeographic structure of modern populations is consistent with a phalanx model-type expansion during the LGM and subsequent pioneer model-type population histories. Our work supports the recognition of a single R. sericea species.In summary, our results show that the cold-tolerant Rosa sericea complex during 2010–2011 . Based on the results of amplify efficiency and amount of polymorphism, three IGS, ndhJ-trnFtrnL-trnFndhF-rpl32Rosa sericea were deposited in GenBank under accession numbers KF850715 – KF850751, KF850756 – KF850792, KF851050 – KF851086, and for three chloroplast sequences for four outgroup accessions, i.e. R. hugonis (2 accessions), R. banksiae and R. cymosa .Total genomic DNA was extracted from the dried leaf tissue by a modified cetyltrimethyl ammonium bromide (CTAB) methodRosaAll DNA samples were genotyped at eight nSSR loci using primers and amplification protocols developed for To verify the existence of significant heterogeneity in the phylogenetic signal among the three cpDNA fragments, we carried out a partition-homogeneity testπ) and haplotype (h) diversityNST) and unordered (GST) chlorotypes, both in the overall cpDNA data set and within population groups, using PERMUT1.0. The result of this program and the significant test by 1000 permutation were then employed to examine if NST > GST, which is a test for the presence of phylogeographic structure. The phylogenetic relationships among chlorotypes were investigated using the statistical parsimony procedure for phylogenetic network estimations implemented in TCS 1.21, with a 95% criterion for a parsimonious connection.Sequence variation was analyzed using MEGA 4, whereas nucleotide (FCT) as a result of differences between groups of populations. We set the number of initial condition to 100 with K = 2–20. To verify its consistency, we ran the analysis five times for each K value with 1000 independent annealing processes. Afterwards, analyses of the molecular variance (AMOVA)et al.Flora of ChinaTo identify population groups and genetic barriers, a spatial analysis of molecular variance (SAMOVA) was performed using SAMOVA 1.0. Based on a simulated annealing procedure, the SAMOVA algorithm iteratively seeks the composition of a user-defined number of groups (K) of geographically adjacent populations that maximizes the proportion of total genetic variance , allelic richness (RS), and gene diversity (HS). Differentiation between populations  was computed using FSTR. hugonis, R. cymosa and R. banksiae, as outgroups based on the framework of Rosa phylogenyThe phylogeny reconstruction based on haplotype was performed in both Neighbor-joining (NJ) and Bayesian inference (BI) using four accessions of three species, RosaRosa sericea is unknown, three different cpDNA substitution rates for angiosperms [the slowest (1.1 × 10−9 substitution/site/year), fastest (2.9 × 10−9 s/s/y) and mean (2.0 × 10−9 s/s/y)62Using the same matrix as above, tree topologies and node ages were determined in BEAST version 1.61 using a GTR+I substitution model, selected by jModelTest, and an uncorrelated lognormal relaxed clockSSD) between observed and expected mismatch distributions and Harpending’s raggedness index (HRag)For a single expanding subclade identified (see the Results section), demographic history was initially explored using mismatch distribution analysis (MDA), which represented the frequency distribution of pair-wise nucleotide differences among all chlorotypes in the population(s)Rosa sericea complex. First, the expansion time was estimated directly from the mismatch distribution with the statistic τ (tau) and translated into absolute time in years (t), using the equation T = τ/2u , where u is the neutral mutation rate for the entire sequence per generation and is calculated as u = μkg, where μ is the substitution rate in substitutions per site yr−1 (s/s/y), k is the average sequence length of the cpDNA region under study (k = 2974 in this study), and g is the generation time in yr . The substitution rate range of the three combined cpDNA-IGS regions was assumed as minimum and maximum mutation rates of 1.1 × 10−9 s/s/y and 2.9 × 10−9 s/s/y62R. sericea complex were inferred from Bayesian skyline plot (BSP) analyses using BEAST 1.6.1D testFS testIn such a context, two methods were used to estimate the time of expansion of the R. sericea complex during cold periods, species distribution models for the R. sericea complex were generated using MAXENT 3.3.3k. MAXENT is a program for maximum entropy modeling of the geographical distributions of species; it combines presence only data with ecological climatic layers to predict species occurrence in areas where data points are unavailable. We used MAXENT to predict species occurrence under both present day and LGM conditions. Although potentially useful for this study, we avoided making predictions for the last interglacial phase (about 135 000–115 000BP), because of a lack of detailed bioclimatic data for this period. Information on the geographic distribution of the R. sericea complex was based on present collection and herbarium specimens from the herbaria A, BM, CDBI, E, HNWP, IBSC, K, KATH, KUN, PE, TUCH and WUK. In total, 317 presence records of members of the R. sericea complex were obtained from throughout the species range, after removal of duplicate records within each pixel . Six bioclimatic variables  at 2.5 arc-min resolution were used to model the species’ niche: (i) annual mean temperature, (ii) mean temperature of the warmest quarter, (iii) mean temperature of the coldest quarter, (iv) annual precipitation, (v) precipitation of the wettest quarter and (vi) precipitation of the driest quarter. Model validation was performed using default settings with 100 replicates of cross-validation procedures with 25% of the data used for model testing. The area under the ROC curve (AUC) was then calculated for each run, which is an indicator of the accuracy of the model predictionTo reconstruct the past distribution of the http://www.worldclim.org). LGM paleo climate layers in 2.5 arc-min resolution were then prepared from these data following Sakaguchi et al.The established model was then projected onto the reconstructed climatic conditions during the LGM simulated by Community Climate System Model 3.0How to cite this article: Gao, Y.-D. et al. Pleistocene glaciations, demographic expansion and subsequent isolation promoted morphological heterogeneity: A phylogeographic study of the alpine Rosa sericea complex (Rosaceae). Sci. Rep.5, 11698; doi: 10.1038/srep11698 (2015).


A total of 4338 high-quality single nucleotide polymorphisms were identified using the genotyping-by-sequencing technique and were subsequently used to construct a high-density genetic map spanning 1942.9 cM. Thereafter, QTL analysis identified five, two, four, and four QTLs for bark thickness, bark weight, fiber output ratio, and fiber yield, respectively. A 5.1 cM region that corresponded to a QTL for bark thickness (qBT4a) contained 106 candidate genes, and the Zhongzhu 1 allele of one of the genes, a putative MYB gene (evm.model.scaffold7373.133_D1), included a 760-bp insertion that caused premature termination, thereby producing a protein that lacked part of the MYB domain. Because MYB transcription factors play central roles in regulating the development of secondary cellular walls and fiber biosynthesis, we propose evm.model.scaffold7373.133_D1 as a likely candidate gene for qBT4a.Ramie fiber extracted from ramie stem bark (RSB) is a highly important natural fiber, and therefore, RSB is an economically important plant organ. The genetic basis of RSB traits is poorly understood. In the present study, fiber yield and three RSB traits  were subject to quantitative trait locus (QTL) analysis using an F Boehmeria nivea L. Gaud), which is commonly known as China grass, is a perennial and diploid (2n = 28) herbaceous plant that belongs to the Urticaceae and is one of the most important natural fiber crops. Ramie fibers are vegetative and are extracted from the plant’s stem bark. Therefore, fiber yield (FY) is markedly influenced by ramie stem bark (RSB) traits, like bark thickness (BT), bark weight (BW), and the output ratio of fiber from the bark (RFB), and understanding the genetic basis of these traits will facilitate molecular designing of the traits, as well as breeding programs for FY.Ramie . Owing to the development of molecular marker and QTL analysis methods during the past 20 years, a great number of quantitative traits have been characterized for important crop species, and thousands of corresponding QTLs have been identified8, some of which have also been fine-mapped and cloned13. In recent years, numerous SSR markers have also been developed in ramie, based on expressed sequence tags (ESTs) from the de novo assembled transcriptome of species15. However, only one expanded, low-resolution genetic map has been constructed2, and only 33 and 29 QTLs have been detected for yield- and flowering time-related traits, respectively8. Therefore, it is likely that many QTLs have yet to be identified, because of the QTL regions without markers observed in this low-resolution map, and a high-resolution genetic map of ramie is needed.Many of ramie agronomic traits, including FY and RSB traits, are complex and are inherited in a quantitative manner2, and no RSB development-related genes or QTLs have been cloned or functionally characterized. Therefore, the genetic and molecular mechanisms for the RSB traits remain completely unknown.Ramie breeding programs often focus on RSB-related traits, owing to their effects on FY. However, only BT was included in the previous analysis that only identified six QTLs2 agamous line (FAL) population that consisted of 134 lines derived from two ramie varieties, Qingdaye (QDY) and Zhongzhu 1 (ZZ1). Thereafter, QTL analysis for FY and three RSB traits was performed; and based on the QTL region sequences of two the parents, candidate gene for one of the BT QTLs (qBT4a) was further investigated. The present study provides a basis for understanding the genetic and molecular mechanisms of RSB development and will facilitate future breeding programs improving ramie fiber yield.A major objective of this study is to characterize the genetic basis of RFB traits. To achieve this aim, whole-genome single nucleotide polymorphism (SNP) was identified, and used to construct a high-density genetic linkage map of ramie, using a genotyping-by-sequencing (GBS) technique and an F2 agamous lines (FALs) and were deposited in the NCBI-short read archive (SRA) database under accession number SRX2830696. Most of the sequence reads were uniquely aligned to the ramie genome, with an average mapping rate of 85.5% among 136 families , except RFB and BT, and RFB and BW in 2015 (Table The FY and RSB traits of the two parent varieties ZZ1 and QDY) were significantly different .The estimated LOD threshold (1000 permutations) indicated that the values for the four traits ranged from 4.6 to 5.5 Table . Based oqBT4a was chosen for further candidate gene analysis. In case of a wave in the QTL location by statistical mapping, an enlarged 5.1-cM region  that contained 614 kb genome sequence was used to identify the candidate gene of the qBT4a. Finally, 106 genes, including genes for a cellulose synthase , a glycosyltransferase (XP_010091051.1_D2), a MYB protein (evm.model.scaffold7373.133_D1), and a galactosyltransferase (XP_010091820.1_D1), were identified  and two thin-bark varieties  technologies have provided a powerful and cost-effective tool for high-throughput sequence determination and SNP discovery, and as a result, large numbers of high-density linkage maps have been successfully developed for many organisms, including non-model species28. In the present study, we developed a SNP-based genetic linkage map using GBS technology. Although the total length of this map (1942.9 cM) was shorter than the previously reported SSR-based map (2265.1 cM), the SNP-based map included a far greater number of markers (n = 4338) than the previous SSR-based map (n = 142), thereby reducing the average genetic distance between neighboring markers from 17.1 to 0.66 cM. Accordingly, the high-quality SNP-based map had a greater resolution than the previous one and will serve as a unique tool for molecular-assisted breeding and genomic studies that will contribute to the improvement of ramie.The construction of useful genetic linkage maps and identification of agronomic trait-related QTLs will facilitate future genetic and breeding studies in ramie. However, until now, only a single low-resolution genetic linkage map, based on SSR markers, has been available2. In this study, the RSB traits were systemically dissected, and a total of 15 QTLs identified. Of them, 6 QTLs constituted 3 clusters, i.e., qBW2 and qFY2 formed a cluster, qBT4c and qFY4b made up of another cluster, whereas qBT4a and qRFB4b built up another one. The presence of many QTL clusters indicated that these four traits had a close correlation. Among these three QTL clusters, the cluster constituted by qBW2 and qFY2 increased traits by QDY alleles, whereas the other two improved the phenotypes by ZZ1 alleles. Therefore, these QTL clusters can be easily applied in ramie improvement by marker-assisted selection.There were only 6 RSB QTLs reported in previous studyqBT4a region of the two parents revealed a putative MYB-like gene (evm.model.scaffold7373.133_D1), the ZZ1 allele of which included a 760-bp insertion that causes premature termination. The textile fiber from ramie consists of bast cell walls, so the formation and thickening of secondary cellular walls are important for fiber biosynthesis. Furthermore, secondary wall biosynthesis is regulated by a transcriptional network that includes NAC and MYB master switches and their downstream transcription factors29. Indeed, at least 16 MYB transcription factors are reportedly involved in regulating secondary wall biosynthesis in Arabidopsis16. Among them, MYB46 and MYB83 are regulated by the NAC protein and function as master switches that activate a battery of downstream transcription factors, including a large number of other MYB genes31. Therefore, MYB genes clearly play important roles in secondary wall biosynthesis, and because secondary wall development contributes to fiber biosynthesis in ramie stem bark, thereby improving stem bark thickness, and because of the large fragment-insertion identified in the MYB gene of the ZZ1 allele of the qBT4a region, we deduce that the MYB gene evm.model.scaffold7373.133_D1 is a candidate gene for the qBT4a locus. We also compared its putative protein sequences in three thick-bark and three thin-bark varieties, and found that an identical amino acids sequence in MYB domain was observed in three thin-bark varieties, whereas in three thick-bark varieties, either a truncation or a change of amino acids in the MYB domain was observed, which further validate our deduction.Sequence comparison of the 2. The 134 FALs and the two parents were planted on the experimental farm of the Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China, in 2014. Field experiments were performed using a randomized complete block design with two replicates. For each FAL, 10 cuttage seedlings were planted into a two-row plot, with a within-row distance of 70 cm between plants and a between-row distance of 45 cm. Boundary effect was eliminated by planting with two-row ramie in the area around the population. In June of 2015 and 2016, when more than two-thirds leaves had shattered, the ramie was harvested, and the traits of RSB were investigated. The bark was ripped from the stems and weighed, after which BT was measured using a vernier caliper and bark from the middle of the stems, and BW was calculated as the mean bark weight per stem. Fibers were harvested from stem bark of individual plants and dried, and FY was calculated as the mean weight of fiber per stem. Finally, the RFB was calculated for each FAL as the ratio of FY to BW. Additionally, four varieties  from the National Ramie Germplasm Resource Garden located in the Wangcheng experimental farm of the Institute of Bast Fiber Crops were used for investigating the BT trait in 2017.An FAL population that consisted of 134 lines derived from two ramie varieties, QDY and ZZ1, was developed using a previously described strategyYoung leaf samples were individually collected from the 134 FALs and two parents for DNA extraction, and stem bark was collected from 40-day-old ZZ1 and QDY seedlings for RNA extraction. All the samples were immediately frozen in liquid nitrogen and preserved at −80 °C until extraction. The total genomic DNA and total RNA were extracted using a DNA extraction kit  and E.Z.N.A. Plant RNA Kit , respectively, according to the manufacturers’ instructions.MseI and EcorI was selected for constructing the GBS libraries. GBS libraries were constructed for each line by incubating 0.1–1 μg genomic DNA at 37 °C with MseI , T4 DNA ligase (NEB), ATP (NEB), and MseI Y adapter N, which contained barcodes, and then heat-inactivating the reaction mixtures at 65 °C. EcoRI (NEB) was then added to the MseI digests and incubated at 37 °C. Thereafter, the fragments of each sample were purified using Agencourt AMPure XP (Beckman) and subject to PCR amplification using Phusion Master Mix (NEB), universal primer, and index primer. The resulting PCR products of each sample were purified using Agencourt AMPure XP (Beckman), pooled, and visualized on a 2% agarose gel, and fragments of 400–450 bp (including indexes and adaptors) were excised from the gel and purified using a gel extraction kit . The purified fragments were cleaned further using Agencourt AMPure XP (Beckman) prior to sequencing. Finally, paired-end sequencing was performed on the selected tags by Novogene Bioinformatics Institute  using an Illumina 2500 platform .Restriction enzyme selection for the GBS was performed by predicting fragment sizes that would result from various enzyme combinations, according to the previously described ZZ1 genome, and eventually, the combination of 32 (settings: mem –t − 4 –k 32 –MR), and the alignment files were converted to bam files using SAMtools33 (settings: –bS –t). If multiple read pairs had identical external coordinates, only the pair with the highest mapping quality was retained.Sequence data from each FAL were sorted from the raw reads using their barcodes. To ensure that the reads were reliable, the raw reads were filtered using three stringent filtering criteria that removed: (1) reads with ≥10% unidentified nucleotides, (2) reads with >50% of bases having Phred quality scores of <5, and (3) reads with >10 nucleotides aligned to the adapter, allowing ≤10% mismatches. The resulting clean, filtered reads from each individual were aligned to the ramie genome (genome accession ID: NHTU00000000) using the Burrows-Wheeler Aligner (BWA) software33. Because the two parents were heterozygous, the polymorphic markers between them were classified into eight segregation patterns 28, according to the CP model in JoinMap 4.034. The numbers of SNPs, transitions, and transversions were also counted, and then, a Perl script was used to filter out the SNPs with more than two genotypes, retaining only polymorphic markers with the ‘aa × bb’ segregation pattern.SNP identification was performed for the two parents and 134 FALs using SAMtools32. The regression algorithm, three times circulation sequence, and Kosambi mapping function were used for marker distance calculation35, and the linkage map was drawn using Perl SVG.Markers that contained abnormal bases or exhibited significantly distorted segregation (P < 0.001) or non-integrity (missing data in > 30% progenies) were filtered out using JoinMap 4.036. Window size was set at 10 cM, and forward stepwise regression was used to identify significant markers as cofactors. The experiment-wise LOD threshold significance level was determined by computing 1000 permutations (P < 0.05) using a permutation test program in MapQTL37. These permutations can account for non-normality in marker distribution and trait values. The heritability for four traits was estimated in the population according to the description of Liu et al.2.QTLs for FY and the three RSB traits in two environments were detected using composite interval mapping with Windows QTL CARTOGRAPHER2.5evm.model.scaffold7373.133_D1 cDNA from the two parents, using gene-specific primers (Table ExoI (NEB) and 0.13 U shrimp alkaline phosphatase (Fermentas) and sequenced using a 3730xl DNA Analyzer . Sequence contigs were assembled using SEQUENCHER 4.1.2 (Gene Codes Co.), and the resulting ZZ1 and QDY evm.model.scaffold7373.133_D1 cDNA sequences were submitted to GeneBank with the accession numbers MF100996 and MF100997, respectively. DNA and protein sequences were aligned using CLUSTAL × 2.138, and the intron and exon were identified by comparing the cDNA with the corresponding genomic sequence  and subsequently used as templates to reverse-transcribe first-strand cDNAs using M-MuLV Reverse Transcriptase (Fermentas), according to the manufacturer’s instructions. For each sample, 2-μg total RNA was reverse-transcribed in 20 μL reactions. A standard PCR protocol was then performed to amplify rs Table . For seqSupplementary materials


Human Immuno-deficiency Virus (HIV) associated non-Hodgkin’s lymphoma (NHL) was a special group of disease, which manifests distinct clinical features and prognosis as compared with NHLs in patients without HIV. We performed this study to describe the clinical features of the disease and investigated the potential prognostic factors.HIV-infected patients who were newly diagnosed with NHL were enrolled in this study. The selection of anti-lymphoma treatment regimen was mainly dependent on the pathological subtypes of NHLs. Tumor response was reviewed and classified according to the International Workshop Criteria.P = 0.004) and poor Eastern cooperative oncology group (ECOG) score (P = 0.038). The estimated 2-year overall survival (OS) and progression free survival (PFS) rate was 74.3 ± 8.1%, 28.9 ± 11.0%, and 54.2 ± 8.1%, 19.2 ± 7.5% for DLBCL and BL, respectively. In multivariate analysis, international prognostic index (IPI) score was an independent prognostic factor for predicting both OS  and PFS .A total of 78 patients were enrolled, among whom, 42 (53.8%) were with Diffuse large B cell Lymphoma (DLBCL), and 29 (37.2%) were with Burkitt lymphoma (BL). BL patients presented with higher risk features as compared with DLBCL in terms of numbers of extranodal diseases (HIV associated NHLs represents a group of heterogeneous aggressive diseases with poor prognosis. IPI parameters were still effective in predicting the prognosis of HIV associated NHLs.The online version of this article (doi:10.1186/s13027-017-0120-2) contains supplementary material, which is available to authorized users. Non-Hodgkin’s Lymphoma (NHL) is one of the most common types of malignancies with high morbidity and mortality in the patients who were infected by Human Immune-deficiency Virus (HIV) . GeneralThe International Prognostic Index (IPI) , which iAnother important issue is the complexity of the background of the HIV associated NHLs, such as more aggressive phenotype, immune-deficiency status. What even worse is that treatment factors (cART) also intervene the clinical outcome and prognosis –11. ChroIn China, with the increasing of incidence of HIV infection in recent years, acquired immunodeficiency syndrome (AIDS) associated NHL became more and more frequently. This subset of the patients might present distinct clinical behavior and treatment outcome as compared with their western counterpart. Hence, we performed this study to describe the clinical features and evaluate the potential prognostic factors of the Chinese AIDS patients with NHLs.The HIV-infected patients who were newly diagnosed NHL were consecutively entered in this study from Jan.2002 to May.2015 in Shanghai Public Health Clinical Center. The subtypes of the lymphoma were defined according to the WHO 2008 classification system.etc.), CD4 cell count, bone marrow and radiological examinations, was performed to stage the disease and assess the general and disease status.Systemic evaluation of the patients including complete blood cell count (CBC), biochemical parameters, LDH, viral panel  and B regimen  were given alternatively to the patients. For DLBCL, CHOP regimen  was initially designed for the patients, initiated from Dec.2014, to enhance the efficacy of young high risk patients . DA-EPOCH  was also given to this subgroup of the patients  300 mg/mpatients . The pat2 was designed to give to the patients with a suitable CD4 cell count (>50 cells/μl) to prevent the deep suppression of both B and T cell immunity. Since rituximab usage is not covered by medical insurance in most provinces in China, the application of treatment with rituximab also depended on patients’ willing. Fifty patients had a CD4 count greater than 50 (2 with PBL without CD20 expression), and 20 patients (40%) received rituximab.Rituximab 375 mg/mThe first line treatment regimen was discontinued if patients experienced any severe adverse event or lymphoma progressing. The initiation of the second line or salvage treatment regimen for relapsed and refractory patients was dependent on the decision of the physicians according to the condition of the patients.n = 1) or with a non-nucleoside reverse transcriptase inhibitor (n = 70), or with an integrase inhibitor (n = 2).ART was given immediately after the diagnosis of HIV with the exception of 5 patients due to rapid progression of lymphoma . They weEvaluation of the efficacy was performed one month after completion of all the treatment. Thoracic, abdominal, and pelvic computed tomography scans were performed even if those areas were not initially affected , 18. IntFisher’s Exact P test and one way ANOVA test were used to compare the clinical parameters in different subtypes of lymphoma. All patients entered into the study were followed up. Overall survival (OS) was measured from the date of disease diagnosis to death (failure) or alive at last follow-up (censored). Progression free survival (PFS) was defined as time from disease diagnosis to treatment failure such as relapse, progressive disease, any new anti-lymphoma treatment, and death of any reasons, or alive in CR at last follow-up (censored). Kaplan-Meier analysis was used to calculate the distribution of OS and PFS. Binary logistic regression was used for the multivariate analysis of prognostic parameters for response, while Cox model was used to identify prognostic variables for OS and PFS. A limited backward selection procedure was used to exclude redundant or unnecessary variants. To provide quantitative information on the relevance of results, 95% confidence intervals (95% CIs) of odds ratios (ORs) was calculated. All above statistical procedures were performed with the SPSS statistical software package, version 16.0.P = 0.004) and poor ECOG score (P = 0.038), while age (P = 0.151), gender (P = 0.692) and CD4 cell count (P = 0.526) were distributed equally in the two groups.A total of 78 patients were enrolled, among whom, 42 (53.8%) were with DLBCL, 29 (37.2%) were with Burkitt lymphoma (BL), 5 (6.4%) were with plasmablastic lymphoma (PBL) and 1 (1.3%) was with follicular lymphoma (FL) and angioimmunoblastic lymphoma (IBL), respectively. The median age of the patients was 48 (24–74). A strong tendency of male patients was observed (89.7% vs. 10.3%). The clinical characteristics of the patients were shown in Table 33% 25/78) of the patients was confirmed to be infected with HIV before lymphoma diagnosis. 22% (17/78) of them received ART with a median treatment exposure of 12 months before the diagnosis of lymphoma, whereas 78% (61/78) of the patients were ART-naïve. 67% (53/78) of the patients were simultaneously diagnosed of lymphoma and HIV. Notably, 14% (11/78) of the patients had a plasma HIV-1 RNA viral load below 40 copies/ml at the time of lymphoma diagnosis. Table 5/78 of tAmong 35 DLBCL patients, 22 (62.9%) and 26 patients (74.3%) achieved CR and OR, respectively. For 23 patients with BL, 5 (21.7%) achieved CR while 8 patients (34.8%) achieved OR. One patient with FL achieved PR. None of the patients with PBL and IBL obtained any response.P = 0.003). Ann Arbor stage (P < 0.001), number of extranodal disease (P = 0.001), ECOG performance status (P = 0.001), LDH (P = 0.008) and IPI (P < 0.001) were proved to be significantly associated the CR induction results.Further prognostic analysis for CR induction was performed in 58 patients with DLBCL or BL after anti-lymphoma treatment. As shown in Additional file P = 0.038, OR = 0.240, 95% CI 0.063–0.925) and IPI score  were independent prognostic factors of CR , number of extranodal diseases , ECOG performance status , and IPI score  were all significantly associated the survival (OS and PFS) of the patients. LDH as continuous variable, could predict OS  and PFS , while CD4 cell count at diagnosis was not associated with the treatment outcome . The estimated 2-year OS and PFS rates were shown in Table Since a survival plateau could be observed in DLBCL and BL patients Fig. , furtherP < 0.001) and PFS   among this population. Compared to NHL in general population, AIDS patients with NHL presents with a more aggressive features including advanced Ann Arbor stage, significantly elevated LDH, and poor ECOG performance status, and a high IPI score eventually [P = 0.004) but poorer ECOG scores (P = 0.038).Very similar to the normal HIV negative population, the most common subtype of lymphoma observed in HIV-infected patients was also DLBCL  . As an ientually . AccordiIn this study, it was observed that the Chinese NHL patients presented with the characteristics of very low rate of ART exposure prior to the lymphoma diagnosis. Its negative impact on the anti-tumor treatment outcome could not be excluded. The severe immunosuppression status as well as the more aggressive disease phenotypes of these patients all strongly challenged the health care providers. One of the main reasons for the late ART initiation is that most of AIDS patients in China are from low income class, or so called “grass roots”, who are often less educated, single or separated from their family to work outside to strive. Although Chinese government have made great efforts to provide the basic education of AIDS, making the free ART publicly available, especially to this population, it seemed that a long way still needs to be run to popularize contemporary knowledge of HIV in such a large country with a huge population. The ignorance of the HIV infection of the patients and the prejudice from their family members should be firstly diminished. In this study, most of the patients came to the hospital not for suspicion of HIV infection, but for the complications, including but not limited to fever, unexplained symptoms and signs, or even hematological events like tumor or pancytopenia.AIDS patients with DLBCL or BL could still achieve a survival plateau. However, it seemed that this plateau is significantly lower than that of the HIV negative counterpart, especially for BL patients . In thisVarious prognostic parameters have been used for predicting the treatment outcome of NHL , 11, 24.HIV associated NHLs represents a group of heterogeneous aggressive diseases with poor prognosis. Current anti-lymphoma treatment should be improved in this special group of patients in future clinical practice. IPI still works in the HIV-infected NHL patients in predicting the prognosis during the cART era. However, this study was a retrospective one and the treatment outcome of the patients, especially for BL, need to be further monitored. And the potential usefulness of existing clinical prognostic factors in AIDS patients should be further addressed in future studies.


For every 1-unit increase of RDW, there is an increased risk of occurrence of ACM  and MACEs . This study indicates RDW may be a prognostic indicator for CVD outcomes.Red blood cell distribution width (RDW) is the coefficient of variation of red blood cell size, considered to be associated with cardiovascular disease (CVD). This study aimed to comprehensively synthesize previous studies on RDW and CVD outcomes through an overall and dose-response meta-analysis. PubMed, Embase and Web of Science were searched systematically for English and Chinese language publications up to November 30, 2015. We extracted data from publications matching our inclusion criteria for calculating pooled hazard ratio (HR), which was used to assess prognostic impact of RDW on CVD. Twenty-seven articles, consisting of 28 studies and 102,689 participants  were included in the present meta-analysis. The pooled HRs are 1.12 (95% CI = 1.09–1.15) for the association of all-cause mortality (ACM) per 1% increase of RDW, 1.12(95% CI = 1.08–1.17) for major adverse cardiac events (MACEs) per 1% increase of RDW. A dose-response curve relating RDW increase to its effect on CVD outcomes was established ( Red blood cell distribution width (RDW) is a quantitative parameter in routine hematologic analysis for representing the variation of red blood cell size. RDW is numerically expressed as the coefficient of variation for red blood cell size  and has been used to differentiate the causes of anemia for a long time13457591011121414As shown in flowchart , our litp = 0.000) per 1% increase of RDW among CVD patients. The heterogeneity test showed that statistical significance existed across all the studies . The subgroup analysis was conducted based on specific disease category. The pooled HRs (and 95% CIs) of ACM were 1.11(1.07–1.14), 1.11(1.00–1.21), 1.21(1.11–1.32) among HF, MI and CAD patients, respectively. In addition, the results of subgroup analyses stratified by subject ethnicity, study design and follow-up duration were presented in As shown in 169111718192021222324252627282930p = 0.000) indicated that increased RDW also facilitated MACEs among CVD populations . Then, we performed subgroup analyses based on disease classification, subject ethnicity, study design and follow-up duration. As shown in Eleven studies5172022262829313233ulations . The het2 = 48.57, p = 0.000). The pooled HR was 1.03(95% CI = 1.02–1.04) for every 1-unit increase of RDW among CVD patients.Twelve original studies within 11 articles2820232728353637382 = 10.25, p = 0.001), with the pooled HR being 1.04 (95% CI = 1.01–1.06) for every 1-unit increase of RDW.Five studies21220282 = 34.87, p = 0.000). The pooled HR was 2.03(95% CI = 1.60–2.57) for every 1-unit increase of the RDW/Hb ratio. For the relationship between RDW/Hb and MACEs, a significant curve of dose-response relationship exists , with the pooled HR being 1.58(95% CI = 1.09–2.29) for every 1-unit increase of RDW/Hb  for ACM and 1.04 for MACEs  in clinical settings, may be a confounder in this study. Therefore we conducted a sensitivity analysis by excluding the original studies of Poludasu or MACEs . FurtherThe funnel plot is used to explore potential publication bias of the current meta-analysis. In this systematic review, we included 27 articles consisting of 28 original studies and 102,689 subjects. The pooled results demonstrated that baseline RDW level was remarkably associated with CVD outcomes. We found a 0.12-fold elevation for all-cause mortality risk in CVD patients per 1% increase of RDW. Increased RDW is also an effective predictor for MACEs with a HR of 1.12. The novel approach of dose-response meta-analysis identified the curve of dose-response relationship between RDW and CVD outcomes.Red blood cell distribution width (RDW) is a parameter of the heterogeneity of circulating erythrocytes size, which was reported to be associated with CVD12612283719434445et al., may play a role in association of RDW with CVDHemodynamic status, reported by Salvagno Many clinical studies and several meta-analyses have been conducted to explore the application measures of the easily acquired routine blood index, and to study the prognostic significance of RDW among CAD or HF patients14Although RDW is a recognized parameter associated with anemia, no study has provided an explicit baseline for anemia with exception to hemoglobin (Hb) levels in subjects. In the present study, we calculated the pooled HR, for which Hb and other confounding factors were adjusted with multiple statistical model. A recently publication verified that RDW was an independent risk factor related to mortality of post-PCI non-anemia patientMoreover, the treatment of PCI plays a crucial role in post-PCI anemia because of arterial vessel wall injury and further antiplatelet or antithrombotic medication during the PCI procedure. Post-PCI anemia is also reported to increase the risk of CVD in patientsenter model should be applied to include each variable in multivariate statistical analysis.The present study has certain limitations. Firstly, the heterogeneity across individual studies was not avoided completely. Secondly, we did not conduct subgroup analyses based on gender and age stratifications because no original articles reported the detailed HRs stratified by age and gender. Thirdly, the potential publication bias might disturb the quality of meta-analysis. Publication bias is a disadvantage in systematic reviews and meta-analyses, which needs to be mitigated as much as possible at the onset of original studies. When researchers evaluate the risks of RDW and other variables on CVD outcomes, the COX proportional hazards regression model would be utilized to calculate the adjusted HRs, which then presented the independent risk degrees. However, the non-significant HRs were not included in the original publications. This is problematic for us to further systematic reviews and meta-analyses referring to these studies, as only the significant adjusted HRs were included in synthesized HRs. Undoubtedly, this induced a publication bias into our studies. In order to avoid this kind of bias in the future, the following methods should be implemented: (1) all results of statistical analysis should be reported, (2) when employing a stepwise method for COX regression analysis, the variables in the multivariate model equation and those not in the equation should be involved simultaneously; otherwise, the In spite of the afore-mentioned limitations, this study presents new comprehensive evidence for the association between RDW and CVD outcomes. We might conclude that increased RDW is a prognostic indicator for CVD outcomes with a dose-response manner.This meta-analysis is conducted according to the published criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)14We identified relevant studies on the association between RDW and adverse outcomes among CVD patients . The search approach was performed to retrieve articles from PubMed, Embase and Web of Science databases published in English and Chinese up to November 30, 2015. The search strategy was designed with the following terms: “red cell distribution width” or “red blood cell distribution width” or “RDW”, “mortality”, “CVD events”, “cardiovascular disease” or “CVD”, “coronary artery disease” or “CAD”, “myocardial infarction” or “MI”, and “heart failure” or “HF”. Further manual collection of references attached on retrieved papers was performed to screen potential relevant studies.We included studies that fulfilled the following inclusion criteria: (1) the baseline or admission serum RDW level was reported; (2) prospective study or retrospective study that evaluated the prognostic value of RDW for CVD patients; (3) one of the following outcomes was reported: all-cause mortality (ACM), fatal CVD events (cardiovascular death), non-fatal CVD events ; (4) studies performed in participants aged ≥18 years. We excluded studies that matched any of the following exclusion criteria: (1) duplicated data; (2) researches based on animal or cell line design; (3) no full data can be obtained.Two authors independently reviewed relevant articles. The quality of each study was assessed with the scale for quality assessment  generateThe following data for eligible studies were extracted independently: year of publication, name of first author, duration of follow-up, location of study population, number of participants, characteristics of patients or controls, definition of outcome, adjusted HR for per 1% increase of RDW for CVD risk, adjusted HR for each RDW classification compared to reference level. We also checked the online Supplementary Data of published articles when necessary.2 and Q-test was performed to detect the heterogeneity across included studies. The fixed effects model was used to combine the original data when the heterogeneity was not statistically significant. Otherwise, the random effects model analysis was used when heterogeneity was considered to be significant (p was < 0.10 and I2 was >50%). Furthermore, subgroup analyses were performed to explore the sources of heterogeneity according to study characteristics in terms of study design, type of disease, follow-up duration and ethnicity of subject. Sensitivity analyses were conducted to evaluate the stability of results in the current meta-analysis. Funnel plot analysis was implemented to detect potential publication biasThe STATA 14.0 software  was utilized to analyze data. We combined HR values to identify the prognostic risk of per 1% increase of RDW for CVD based on the original studies reporting quantitative RDW levels. For other studies which addressed ordinal classification of RDW levels, the dose-response meta-analysis was performed to synthesize pooled HRs and the curve of dose-response relationship with the method of Greenland and LongneckerHow to cite this article: Hou, H. et al. An overall and dose-response meta-analysis of red blood cell distribution width and CVD outcomes. Sci. Rep.7, 43420; doi: 10.1038/srep43420 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Onabotulinum toxin A (OnabotA) cyclic treatment is approved for the prophylactic treatment of chronic migraine (CM), a highly disabling disorder. Although treatment response varies among patients, current guidelines suggest to stop treatment after cycle 2 if no response is achieved. This prospective study aimed to define, in real-life setting, the evolution of the response to OnabotA over five cycles of treatment among patients non-responding to cycle 1. The results of this study might help in decision-making, in particular whether prosecuting OnabotA further or not, when facing a patient not responding to cycle 1.Patients failing to respond at cycle 1 were recruited to complete five cycles. Key outcomes were: (i) a ≥50% reduction in headache days, (ii) a ≥50% reduction in total cumulative hours of headache on headache days and (iii) a ≥5-point improvement in Headache Impact Test-6 (HIT-6) scores.p < 0.001). During 12 months (5 cycles), migraine days per month progressively abated , days with symptomatic medications intake/month consistently decreased , and mean HIT-6 score lowered .Overall, 56 patients were included. Mean age was 45.7 years . Severe (≥60) HIT-6 score was reported at baseline by 95.8% of patients. Responders (headache days reduction of more than 50%) progressively increased cycle after cycle, doubling from cycle 2 to cycle 5 (from 27 to 48%). In addition, patients regressed from CM to episodic migraine moving on with each cycle, with 78% of them reaching less than nine migraine days/month after cycle 5. The headache days per month decreased significantly from cycle 1 to cycle 5 (overall from 23.3 ± 5.7 to 9.2 ± 3.6; The positive effect of OnabotA treatment spreads over the course of the treatment and might also manifest late in treatment course among patients with no benefit after the first two cycles. Thus, the results of this real-life study suggest to extend OnabotA treatment further, beyond cycle 2, to avoid premature withdrawal in patients who would have become responders at cycle 3, 4, or 5. Chronic migraine (CM) is the most disabling migraine headache disorder, involving 2% of the general population, with an estimated incidence of about 2.5% per year , 2. CM cOnabotulinum toxin A (OnabotA) is the only preventive treatment approved for CM based on efficacy and safety data from randomized controlled trials, with efficacy being also confirmed in patients with MOH , 7–10. OUsing pooled data from PREEMPT trial, Silberstein and colleagues defined the probability of non-responders to cycle 1 to improve after cycle 2 and 3. Specifically, more than 10% of patients were reported to respond to cycle 2 and 3 after having failed to respond to cycle 1 (late responders), suggesting an improvement in the short-term period with repeated treatment , as wellTo date, no studies are available, in real-life setting, regarding the proportion of patients non-responding to cycle 1 who first respond to OnabotA in the following cycles. Moreover, few data are available regarding the evolution of CM during the five cycles in the sub-population of non-responders to the first cycle of treatment. In this prospective real-life setting study, we report the evolution in response to OnabotA repeated cycles among patients non-responding to cycle 1. The results of this study might help clinicians in decision-making about continuing OnabotA treatment under such specific circumstances.This open-label, single-arm, prospective, observational study has been conducted in accordance with the principles of the Helsinki Declaration. The study was approved by the Internal Advisory Board. Participants admitted to the Headache Centre of Neurologic Clinic of Perugia between January 2014 and September 2016 were enrolled, after obtaining a written informed consent, according to the following inclusion criteria: (a) 18–65 years of age; (b) diagnosed with CM according to ICHD-III-beta criteria ; (c) recU test was used for testing hypotheses of changes of continuous variables. Fisher exact test was used for testing hypotheses of difference in the distribution of categorical data. A 0.05 level of significance was assumed for all the hypotheses tests.Descriptive statistics are presented as means and SDs for continuous variables. The categorical variables were reported as counts and percentages. Mann–Whitney Seventy-one patients were selected according to specified criteria; 56 accepted and were recruited to complete a five-cycle 1 year) OnabotA treatment period. Fifteen patients did not participate to the study: seven refused to undergo further invasive treatment, two refused to be included in the study but continued OnabotA cycles, and six refused to prosecute the treatment because of the lack of short-term guaranteed results. Non-participants had baseline characteristics similar to participants. Among participants, follow-the-pain strategy with up to 195 U of OnabotA was used in 59 cases (21.0%), due to shortening of response persistence. Demographic and headache characteristics at baseline and after cycle 1 are reported in Table  year Onap < 0.001). Moreover, significant improvements in all other key outcomes were found. Migraine days per month progressively abated during the five cycles , as well as days with acute medications intake .Variations of all outcome measures from baseline to OnabotA cycle 5 are reported in Table p < 0.001), with a severe impact on the rate of patients with severe (≥60) HIT-6 score, decreasing by nearly 60% moving from cycle 2 to cycle 5  or partial responders (n = 4) after cycle 5. Similarly, three non-responders and three partially responders after cycle 4 became responders at cycle 5.The proportion of non-responders to treatment dramatically decreased over time, reaching its half at the end of treatment protocol Figure . On the A significant positive trend with treatment cycles was observed also for other outcome measures, such as migraine days per month Figure . In partConsidering different intervals of migraine days per month (0–4 vs 5–9 vs 10–14 days), OnabotA showed a positive progressive impact among late responders . Since these patients with frequent EM are likely to progress to CM , one mayvia SNARE complex cleavage, inhibiting the release of CGRP, substance P and glutamate. Such effects, together with the regulation of the expression of the transient receptor potential vanilloid type 1, localized within C-fibers and participating in pain transmission, directly limit peripheral sensitization. Moreover, once peripheral sensitization is reduced, central sensitization indirectly decreases, leading do pain relief (Several factors are known to influence the response of CM to OnabotA, including peripheral and central sensitization mechanisms . OnabotAn relief . All of n relief . This men relief . This stn relief , 21, mign relief . Thus, tn relief . NeverthThis observational study received approval from the Internal Advisory Board. Informed consent was obtained from all patients for data collection, analysis, and publication.PS performed and took full responsibility for data collection and analysis, interpretation of data and results, manuscript drafting and revision. MR revised the manuscript. IC, LB, AV, EB, SC, and PC revised the manuscript. PE performed statistical analysis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Besides, it is yet uncertain that TFs are useful for estimation of histopathologic markers, prediction of response to neoadjuvant chemotherapy (NAC), or prognostic ability in breast cancer. To depart from the traditional approach, we evaluated the clinical usefulness of integrated metabolic radiomics using unsupervised clustering with 109 TFs measured from pretreatment 18F-FDG PET/CT scans of 73 patients with locally advanced breast cancer (LABC) underwent NAC before surgery. Our study shows that metabolic radiomics patterns of LABC are associated with Ki67 expression, achievement of pathologic complete response after NAC, and risk of recurrence. Integrated metabolic radiomics has potential for clinically relevant pretreatment biomarker with predictive and prognostic ability for personalized management in LABC.Radiomics has been spotlighted as imaging biomarker for estimation of intratumoral heterogeneity (ITH) which is regarded as the main reason for resistance to tumor treatment. Although a number of studies has shown clinical evidences that separate measurement of metabolic ITH by texture features (TFs) on  There is much evidence that uptake on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) scans correlates with histopathologic markers, response to treatment, and prognosis in breast cancer4. The usefulness of decrease in PET parameters between pretreatment and interim 18F-FDG PET/CT in early prediction of a pCR has been reported in LABC treated by NAC6. However, pCR can only be predicted after the start of NAC and additional radiation exposure is involved.Neoadjuvant chemotherapy (NAC) allows complete surgical resection by downstaging tumors and is now a standard treatment strategy in patients with locally advanced breast cancer (LABC). A pathologic complete response (pCR) after NAC indicates a better prognosis for patients with LABC7. Radiomics contains all mineable data from medical images for clinical decision support. There have been reports that certain texture features (TFs) indicating metabolic intratumoral heterogeneity (ITH) are good prognostic markers of the likely response of the tumor to treatment and of patient survival10. Recently, success has been achieved in decoding tumor phenotypes by combining hundreds of features on CT images12.Texture analysis, developed for image pattern recognition, has been identified as a tool for “radiomics” on medical images in recent years18F-FDG PET/CT scans was applied to LABC tumors as part of an integrated approach to metabolic radiomics. We then investigated the relationship between tumor clusters (TCs), histopathologic characteristics, tumor response to NAC, and risk of recurrence.We hypothesized that tumors with distinctive metabolic radiomics patterns may have certain clinical characteristics. To test this theory, unsupervised clustering on pretreatment in situ hybridization results. Seventeen cases (23.2%) achieved a pCR. Recurrences were observed in 4 cases (6.1%), and median DFS was 25 (16–57) months.Seventy-three patients with LABC who satisfied inclusion and exclusion criteria were included in this retrospective study Fig. . The patmax) and metabolic tumor volume (MTV) were correlated with 68 TFs (62.3%) and 45 TFs (41.3%), respectively. Only 17 TFs (15.6%) were correlated with neither SUVmax nor MTV. When disregarding multiple comparison correction (P < 0.05), only five TFs (4.6%) were correlated with neither SUVmax nor MTV.Correlations between TFs were expressed in an intuitive way, with the correlogram considering multiple comparison correction Fig.  or not . Maximummax, MTV, total lesion glycolysis (TLG), coefficient of variation (CV), normalized entropy measured from gray level co-occurrence matrix (NL_EntropyGLCM), normalized homogeneity from gray level co-occurrence matrix (NL_HomogeneityGLCM), zone percentage from gray level size zone matrix (ZPGLSZM), and skewness (Table P ≤ 0.001). TC 1 had a large tumor size , high SUVmax (13.2 [5.0–22.1]), and high ITH as high CV (0.42 [0.19–0.66]) and high NL_EntropyGLCM (5.4 [3.4–5.9]). Like TC I, although TC II had a medium tumor size , it had a high SUVmax (13.3 [9.2–24.6]), and high ITH . TC III had a small tumor size , low SUVmax (5.8 [3.7–9.7]), and low ITH , and NL_EntropyGLCM (3.7 [2.5–5.0]). Representative cases of TC I-III groups can be found as Supplementary Fig. We assessed TCs by metabolic radiomics patterns via unsupervised clustering. Unsupervised clustering resulted in 3 TCs Fig. . There wss Table . The TFsP = 0.006). The ER and PgR were expressed at relatively higher levels in TC III than in TC I and TC II, but the difference was only statistically significant before multiple comparison correction . There was no statistically significant difference in HER2 expression between the unsupervised TCs (P = 0.688).To characterize the unsupervised TCs, we investigated the expression of histopathologic factors, i.e., estrogen receptor (ER), progesterone receptor (PgR), HER2, and Ki67 Table . The onlP < 0.001). Univariate analysis revealed that the TC II , ER-negative , PgR-negative , and high Ki67  groups were significantly associated with achievement of a pCR. The TC II  and ER-negative  groups were still significant in multivariate analysis. High Ki67 expression  had intermediate significance. Table The pCR rates were significantly different between the TC I, II, and III groups  were in the TC I group (n = 10); the other one (2.9%) was in the TC III group (n = 35). No recurrences occurred in the TC II group (n = 21) during follow-up. All recurrences were non-pCRs. Mean DFS was 35.3 months  in the TC I group, 55.0 months (95% CI 55.0–55.0) in the TC II group, and 39.2 months (95% CI 37.7–40.7) in the TC III group. There was a statistically significant difference in DFS between the unsupervised TC I, II, and III groups (P = 0.010) was identified as a prognostic factor for recurrence in univariate Cox regression analysis . Further, the histopathologic parameters of ER, PgR, HER2, and Ki67 were not found to be prognostic factors in univariate Cox regression analysis  was an independent prognostic factor regardless of stage or achievement of a pCR.The TC I  and non-pCR.We evaluated metabolic radiomics patterns in tumors and their clinical usefulness in patients with LABC. In this study, breast tumors were clustered into 3 TCs in an unsupervised manner according to their metabolic radiomics patterns. TC II, which had a moderate MTV, high SUV13. Biological ITH is suspected to be the main reason for resistance to treatment14. Image-based assessment of metabolic ITH is based on the hypothesis that it may be a projection of underlying tumor biology, including glucose metabolism, necrosis, oxygenation, vascularization and angiogenesis15. With the heightened interest in measurement of metabolic ITH by texture analysis, a number of clinical studies have reported that TFs from PET images have more prognostic ability than conventional SUV parameters in various cancers17. However, investigators cannot interpret TFs in an intuitive way, because TFs merely offer a mathematical explanation of images that can be interpreted as not only heterogeneous, but also smooth, coarse, rough, or grainy18. Further, it has not been easy to reach a consensus regarding the parameter that best represents ITH. Therefore, an integrated radiomics approach that departs from the traditional approach is needed.A cancerous tumor is composed of a heterogeneous cell population rather than a homogeneous one, with distinct molecular and phenotypic characteristics20. A recent study has reported that a TF of High-Gray-level Run Emphasis (HGRE) was significantly higher in groups of ER-negativity and PR-negativity regardless to SUVmax19. However, given relatively small sample size (n = 54) and multiple comparison problem, the relationship of HGRE and hormonal receptor expression looks uncertain. Another recent study with a larger cohort (n = 171) has reported that there were not only limited relationship of TFs with hormone receptor expression, but also no additive effect of TFs discriminating breast cancer subtypes compared to SUVmax20. While the previous two studies used same resampling methods of equally divided SUV ranges of tumor by 64 bins (variable bin width of SUV) and analyzed relationship of individual TFs with hormonal receptor expression, our study used a different resampling method maintaining a constant intensity resolution (fixed bin width of SUV 0.4) and integrated radiomics approach for analysis. Nonetheless, our study suggested concordant results to the latter previous study that there were no sufficient evidences that TFs are associated with hormone receptor expression. Meanwhile, our data provided concordant results to previous studies that HER2 status is not associated with TFs20. On the other hand, Ki67, a proliferative marker, was significantly associated with unsupervised TCs in our results, which makes sense because there has been an observation of high dependency of TFs on MTV22. In this study, our congruent results also suggest that a number of TFs were significantly correlated with MTV and/or SUVmax, meaning that each TF should be interpreted comprehensively with consideration of MTV and/or SUVmax.Previous PET studies in breast cancer cohorts have yielded conflicting results regarding the relationship between TFs and the histopathologic parameters of ER, PgR, and HER2Our data suggest that integrated metabolic radiomics has considerable potential for personalized management in LABC. For example, unsupervised TCs from metabolic radiomics can help to identify patients at higher risk for recurrence in addition to the established prognostic factors of stage and achievement of a pCR. Patients with tumors clustered as TC I might also be at high risk of recurrence. Physicians may actively consider NAC in TC II cases because of the good chance of a pCR, whereas TC III cases are less likely to achieve a pCR so are less likely to benefit NAC before surgery. In summary, use of metabolic radiomics may help in the appropriate management of individual patients and avoid the side effects of unnecessary systemic chemotherapy.23. Genomic profiling of tumors from tissue samples is being used increasingly to tailor the management strategy at the level of the individual patient. Radiomics is expected to have a role complementary to that of genomic profiling, because it has an advantage of being able to provide a non-invasive comprehensive tumor assessment that overcomes sampling error and the invasiveness of repeated biopsies7. Radiomics could be used as a cross-validation tool and provide information over and above that obtained from genomic profiling24.The rapid development of applications for omics data means that personalized medicine is now one step closer to becoming a reality25. The other method is using a fixed bin width, which provides a constant intensity resolution to all analyzed cases26. In this study, we adopted a fixed bin width of SUV 0.4 in range SUV 0–25. A recent study has reported that a constant intensity resolution is more meaningful for inter- and intra-patient comparison of TFs27. Much validation is needed to evaluate the comparison of both two methods. Regardless, our integrated radiomics analysis method is expected to be able to use combination of both TFs obtained by the two fully different resampling methods for comparison of tumor textures on images.SUV resampling is one of remaining issues in texture analysis, which is apparently an important methodological factor affecting the results of texture analysis. There has been two ways generally used to resample images. The most widely used method is using a fixed number of bins to divide the tumor SUV range, which results in varying intensity resolution to each case28. Given that clustering is not an inferential technique, an adequate sample size for clustering is important. To avoid finding patterns in noise, we included biological validation by prediction of the likelihood of a pCR and evaluated the risk of recurrence. Not only were the results of clustering reasonably explained by several meaningful parameters , but the biological validation suggests a clinical rationale for clustering. A multicenter trial containing much larger study cohorts is now needed to validate our results. Second, we used unsupervised clustering for this radiomics study. Supervised learning can optimize prediction of certain outcomes like histopathologic markers, response to NAC, and prognosis. Third, our results should be interpreted carefully because of the exclusion of the least metabolically active tumors. However, it should be borne in mind that delineation of tumors with little metabolic activity is usually difficult because of surrounding physiologic uptake in the breast parenchyma. In addition, we used a fixed cutoff method of SUV 2.5 can cause inaccurate tumor segmentation especially in high ITH cases. Although there was one inaccurately tumor-segmented case ; inflammatory breast cancer (n = 4); and occult breast cancer or a tumor with so little metabolic activity that it could not be delineated with a SUV cut-off of 2.5 (n = 15). One further patient was excluded because delineation of her cancer was not possible as the primary tumor was abutting the metastatic axillary nodes too closely. Finally, 73 patients with stage LABC IIA–IIIC were enrolled for metabolic radiomics analysis. Six patients who were censored or had a recurrence before 6 months of disease-free survival (DFS) were excluded from survival analysis. One patient who did not fit into any TC was also excluded from survival analysis  HER2 staining on IHC. The breast cancer subgroups were classified as: ER-positive or PgR-positive/HER2-negative; HER2-positive; or triple-negative. Staging was defined according to the American Joint Committee on Cancer (AJCC) system. A pCR was defined as no residual invasive cancer (AJCC ypT0/Tis ypN0). The patients were followed up for recurrence until December 2015.This retrospective study was approved by the Institutional Review Board at our institution. The need for written informed consent was waived. Inclusion criteria were female sex, Korean ethnicity, pretreatment 18F-FDG PET/CT on a Discovery VCT scanner . The blood sugar level was <120 mg/dL after at least 6 hours of fasting, and 5.18 MBq/kg of 18F-FDG were administered intravenously in each patient 1 hour before PET/CT scanning. CT scanning was performed at 120 kVp for attenuation correction and to obtain anatomic information. PET scans were obtained from the skull base to the upper thigh level with a 128 × 128 matrix size. The voxel size was 3.91 × 3.91 × 3.27 mm3. Images were reconstructed with an ordered subset expectation maximization iterative algorithm (2 iterations and 8 subsets).Patients underwent 29. Primary tumors were delineated by a fixed SUV cut-off of 2.530. Next, for calculation of TFs, the gray level was resampled by a fixed bin width method with 0.4 SUV units which was calculated from 64 grey levels of 0 to 25, to minimize the error due to variation of contrast and to improve reproducibility27. Of all the methods available to compute TFs, we chose a statistics-based methodology based on the spatial distribution of gray levels31. Multiple matrixes were used as follows: a gray level co-occurrence matrix32, gray level run-length matrix33, gray level neighborhood intensity-difference matrix34, gray level size zone matrix35, SUV statistics, texture spectrum36, texture feature coding37, texture feature coding co-occurrence matrix37, and neighboring gray level dependence38. Finally, 109 TFs were calculated from the matrices. The matrix parameters were expressed next to the parameter name to avoid mimicking28. Detail on these parameters are provided in Supplementary Table 29. We chose NL_EntropyGLCM and CV, which are generally used for measurement of ITH, to classify the extent of metabolic ITH21. MTV (cm3) was defined as the volume of the tumor delineated with an SUV cut-off of 2.5. TLG (g·cm3/mL) was defined as the mean SUV (SUVmean) multiplied by the MTV of the delineated tumor. The CV was defined as the standard deviation of SUVs divided by the SUVmean in a delineated tumor.CGITA ver.1.4  based on MATLAB v.2014a  was used for analysis of the three-dimensional textures on PET images39, along with the parameters that were statistically significant in the univariate analysis were included in the multivariate analysis. PgR was excluded from the multivariate analysis because of its strong association with ER status. Kaplan-Meier survival analysis and the log rank test were used to compare DFS between the unsupervised TCs. A univariate Cox regression survival analysis with binary TC parameters (TC I compared with the other TC groups), including age, clinical stage, pCR, and ER, PgR, HER2, and Ki67 status, was applied to identify predictors of recurrence. Multivariate Cox regression analysis was conducted for binary TCs, disease stage, and pCRs. A P-value less than 0.05 (two tailed) was considered to be statistically significant. Bonferroni’s correction was applied for multiple comparison correction. Continuous values are expressed as the median and range.We used MedCalc version 14.8.1  for the statistical analysis. R version 3.2.3  was used to construct the correlograms and heat maps. The correlations among all the 109 TFs were evaluated by Pearson correlation analysis and displayed by correlogram with hierarchical clustering. Radiomics heat maps in red to green coloring were constructed for the TF cases normalized Z-score using the Euclidean method and hierarchical clustering. Kruskal-Wallis test was used to compare representative TF values among the unsupervised TCs. The proportions of ER-positive, PgR-positive, and HER2-positive tumors, tumors with high Ki67 expression, and pCRs were compared between the unsupervised TCs using the chi-square test. The parameters included in univariate logistic regression analysis for prediction of a pCR were age, clinical AJCC stage, T stage, nodal metastasis, ER, PR, HER2, and Ki67 status, and TC. The established parameters of nodal metastasis, ER status, and HER2 statusSupplementary table and figures