Prematurity is the leading cause of neonatal deaths and high economic costs; it depends on numerous biological and social factors, and is highly prevalent in males. Several factors can affect the metabolome of premature infants. Accordingly, the aim of the present study was to analyze the role played by gestational age (GA), parenteral nutrition (PN), and caffeine treatment in sex-related differences of blood metabolome of premature neonates through a MS/MS-based targeted metabolomic approach for the detection of amino acids and acylcarnitines in dried blood spots. GA affected the blood metabolome of premature neonates: male and female very premature infants (VPI) diverged in amino acids but not in acylcarnitines, whereas the opposite was observed in moderate or late preterm infants (MLPI). Moreover, an important reduction of metabolites was observed in female VPI fed with PN, suggesting that PN might not satisfy an infant’s nutritional needs. Caffeine showed the highest significant impact on metabolite levels of male MLPI. This study proves the presence of a sex-dependent metabolome in premature infants, which is affected by GA and pharmacological treatment . Furthermore, it describes an integrated relationship among several features of physiology and health. Prematurity, defined as childbirth before 37 weeks of gestation, annually affects 9.6% of pregnancies ,2, beingSeveral factors, including gestational age (GA) at birth, can affect qualitatively and quantitatively the metabolites measured in premature infants . It can Moreover, preterm infants often present respiratory symptoms  which aRecently, gender and sex differences have been highlighted in healthy and ill individuals ,18. GendAs a matter of fact, the metabolome of biological fluids of preterm infants collected during the first days after birth shows a specific urinary and blood pattern, with high variability in amino acids, organic acids, and other metabolites ,28,29. Thus, the aim of the present study was to assess the role played by GA in the occurrence of sex-related differences in the blood metabolome of premature neonates through a targeted metabolomic approach for the detection of amino acids and acylcarnitines in dried blood spots (DBS). In addition, it was evaluated whether the sex effect was influenced by feeding condition ) and by caffeine treatment.The population of preterm infants was stratified according to sex, birth weight (BW), GA, and treatment with caffeine or PN. As expected, both male and female very premature infants (VPI) significantly weighted less than male and female MLPI. Moreover, male MLPI fed with PN had lower BW and GA than those exposed to NPN . CaffeinA total of 53 variables were measured  from newThen, partial least squares-discriminant analysis (PLS-DA) was carried out to identify metabolites closely associated with sex-dependent GA according to their variable importance on projection (VIP) score. In the female cohort, Tyr, C12, and C18:1OH differentiated between VPI and MLPI cohorts (VIP > 2.0), whereas in the male cohort, C5, C5OH, and C4 (VIP > 2.0) differentiated between VPI and MLPI .Female and male VPI diverged in their amino acid profile A, with APLS-DA analysis shows that C12 and Asp  were disIn female VPI, PN lowered 9 metabolites  and significantly increased C18:2 of ~73% in comparison with that found in the NPN group . In femaIn male VPI, PN increased only Phe of ~20%, whereas C2, C8, C10:2, C14-OH, total esterified carnitine, and total esterified/C0 ratio were lowered . In malePLS-DA showed that ArgSuc, Glu, Orn, and C12 could discriminate between female VPI fed with NPN and PN , whereasNPN females had higher Gly and Cit concentrations and lower levels of C8, C16, and C18:2 when compared with NPN males . All theFemale VPI treated with caffeine were different only for Glu and C5:1, whose levels were higher when compared with those of non-treated individuals A, whereaIn male VPI, caffeine significantly increased Val and Xle blood levels B. In MLPPLS-DA showed that VIP and MLPI caffeine-treated females were discriminated by ArgSuc, C6:1, Orn, and by C18:2, C16, respectively . VIP andCaffeine-treated females had higher Gly and lower C6 and C18:1 in comparison with those of caffeine-treated males C. In cafPLS-DA showed that C5DC and Asp could differentiate male and female babies treated with caffeine , whereasCluster analysis showed four different clusters: the first one included 57 subjects, whereas the second one included 81 individuals. The third and fourth ones grouped 63 and 109 infants, respectively . ClusterCluster 2 included VPI infants only , with the lowest values of BW, GA, and several acylcarnitines red in . Cluster 3 had the largest percentage (66.7%) of males and grouped almost all subjects treated with caffeine, showing that caffeine highly affects males, in agreement with Kruskall–Wallis analysis. Cluster 4 included most of all late preterm infants , characterized by the highest values of BW and GA and the lowest values of several acylcarnitines red in .Correlations between BW, GA, and parameters are reported in p-value < 0.001 for males; coefficient: 0.503; p-value < 0.001 for females).Furthermore, for both sexes there was a positive correlation between BW and GA  the evidence of quantitative and qualitative sex differences in the blood of premature neonates; (ii) the sex differences are affected by GA, type of nutrition, and caffeine. Prematurity is characterized by sex-specific levels of metabolites: VPI females had higher Tyr, C5:1, and C14:2 when compared with MLPI ones, whereas VPI males had lower Ala and Glu, as well as higher C3, C3DC, and C10:2 than those found in MLPI. Interestingly, GA also affects sex differences, with their onset being closely related to the specific GA. Male and female VPI showed different amino acids levels with the only exception of acylcarnitines; the opposite scenario was observed in MLPI (sex difference found in acylcarnitines but not in amino acids), making infants at different stages of prematurity metabolically distinct, as confirmed by the cluster analysis. This is in agreement with what we previously reported studying term infants: females had higher amino acids concentrations, whereas males had higher acylcarnitines . PreviouPN induced qualitative changes in the blood metabolome when the sex of babies and the grade of prematurity was considered. Preterm infants receive PN, which leads to a reduction in the levels of nine metabolites , ranging from 8% to 52% in female VPI. The decrease is less relevant in male VPI, ranging from 12% to 20% for six metabolites . The dramatic reduction of metabolites in VPI females fed with PN might suggest that PN could not address a female infant’s nutritional needs, indicating the need of sex specific PN. In female MLPI, PN caused an increase (ranged from 10% to 100%) of six metabolites  and a decrease of Glu. In male MLPI, a significant increase (ranged from 17% to 50%) was observed for six metabolites , as well as a decrease of Asp, Glu, and ArgSuc. In Asian preterm infants, it has been reported that leucine, Met, tryptophan, histidine, Arg, Glu, Asp, and serine significantly increase after PN, while Phe, Tyr, Gly, and Ala decrease. However, this study did not consider the sex . In addiPN administration can lead to serious complications, being inappropriate or unsuitable for infants’ metabolic demand ,35,36, sThe sex-specificity of the effect exerted by caffeine on the metabolome is an innovative result, at least in prematures. Caffeine causes relevant metabolic effects, modulating lipid and glucose metabolism ,14. In pThe current study presents some limitations associated with the lack of specific information on maternal nutrition and specific data on mothers , including the reason of premature birth and the mode of birth (cesarean or spontaneous delivery). Furthermore, PN received by preterm infants, even if based on pediatric protocols, was not identical because PN formulations were supplied by different pharmaceutical companies.The recruited sample included 311 preterm infants . It was divided into 2 groups according to the WHO  GA classPreterm infants were characterized by several pathological conditions, requiring the administration of pharmacological therapies. Due to the high variability of pharmacological treatments in preterm infants, subjects treated with dopamine and glucose solutions were excluded, as well as infants with jaundice, those exposed to blood transfusions, and those fed with carnitine solutions. Characteristics of the cohorts stratified by gender and GA are summarized in DBS were collected from hospitals participating in the newborn screening program of Campania Region . All experiments were performed in compliance with national laws and institutional guidelines, approved by Italian Ministry of Health in law no. 167 (19 August 2016).15N,2-13C-Gly; 2H4-Ala; 2H8-Val; 2H3-Leu; 2H3-Met; 13C6-Phe; 13C6-Tyr; 2H3-Asp; 2H3-Glu; 2H2-Orn; 2H2-Cit; 2H4,5-13C-Arg; and 2H9-C0; 2H3-C2; 2H3-C3; 2H3-C4; 2H9-C5; 2H3-C8; 2H9-C14; 2H3-C16) at concentrations of 500–2500 µM and 7.6–152 µM, respectively. Samples were incubated at room temperature for 20 min and dried under nitrogen flow. Metabolites were derivatized using 80 µL n-butanol/3N HCl at 65 °C for 25 min. Samples were dried and resuspended in 300 µL of acetonitrile/water (70:30) containing 0.05% formic acid. A final volume of 40 µL was used for MS analysis.Blood samples were collected from the heel of newborns between 48 and 72 h of life on a special filter paper, dried overnight at room temperature, and processed for tandem mass spectrometry (MS/MS) analysis, as previously described ,44,45,46Metabolites were identified and quantified by MS/MS using an API 4000 triple quadrupole mass spectrometer  coupled with a high performance liquid chromatograph .m/z range (Da): 200–560; declustering potential (DP) range (volts): 55–80; collision energy (CE) range (volts): 34–60. Neutral loss scan was performed according to: neutral loss mass: 102 Da; polarity: positive; m/z range (Da): 130–280; DP (volts): 45; CE (volts): 25. Finally, MRM mode parameters were: positive polarity; Q1/Q3 (m/z): 132.1/76.0 (Gly), 189.1/70.0 (Orn), 231.2/70.0 (Arg), 232.2/113.1 (Cit); DP (volts): 43 (Gly), 33 (Orn), 60 (Arg), 50 (Cit); CE (volts): 14 (Gly), 33 (Orn), 45 (Arg), 28 (Cit). Acylcarnitines and amino acid quantification was performed by precursor ion scan and neutral loss scan, respectively; glycine (Gly), ornithine (Orn), arginine (Arg), and citrulline (Cit) were quantified by multiple reaction monitoring (MRM). Precursor ion scan was performed using the following parameters: precursor ion mass: 85.1 Da; polarity: positive; www.erndimqa.nl).Quantitative analysis of the data was performed with ChemoView v1.2 software  using stable isotope-labeled internal standards to improve matrix correction and compare analyte areas. Quality controls, used to test the mass spectrometry methods’ accuracy and precision, were provided by CDC  and ERNDIM  or medians (interquartile ranges), depending on their normal or non-normal distribution, respectively. Qualitative variables were compared with chi-squared or Fisher exact test, when appropriate. Normal and non-normal quantitative variables were compared with Student http://www.metaboanalyst.ca) [All statistical computations were performed with the statistical software STATA version 16 . Multivariate statistical analysis was performed using MetaboAnalyst 4.0 (lyst.ca) ,48. The Partial least squares-discriminant analysis (PLS-DA) was used, and the corresponding variable importance on projection (VIP) was estimated for each differentially abundant metabolite .This study confirms that metabolomics analysis is a powerful tool in the early characterization of the sexual specificity of perinatal, pediatric, and adulthood status. In preterm infants, the levels of amino acids and acylcarnitines depend on prematurity, PN and caffeine treatment, and on sex. Sex, in fact, induces qualitative changes in all examined conditions . Therefore, sex should be an independent variable in metabolomic studies. Finally, the study shows the importance of intersectionality, considering integrated relationships among the studied parameters.


Les/les) mutants display disease-like spontaneous lesions in the absence of pathogen infection, implying the constitutive activation of defense responses. However, the genetic and biochemical bases underlying the activated defense responses in those mutants remain largely unknown. Here, we performed integrated transcriptomics and metabolomics analysis on three typical maize Les mutants Les4, Les10, and Les17 with large, medium, and small lesion size, respectively, thereby dissecting the activated defense responses at the transcriptional and metabolomic level. A total of 1,714, 4,887, and 1,625 differentially expressed genes (DEGs) were identified in Les4, Les10, and Les17, respectively. Among them, 570, 3,299, and 447 specific differentially expressed genes (SGs) were identified, implying a specific function of each LES gene. In addition, 480 common differentially expressed genes (CGs) and 42 common differentially accumulated metabolites (CMs) were identified in all Les mutants, suggesting the robust activation of shared signaling pathways. Intriguingly, substantial analysis of the CGs indicated that genes involved in the programmed cell death, defense responses, and phenylpropanoid and terpenoid biosynthesis were most commonly activated. Genes involved in photosynthetic biosynthesis, however, were generally repressed. Consistently, the dominant CMs identified were phenylpropanoids and flavonoids. In particular, lignin, the phenylpropanoid-based polymer, was significantly increased in all three mutants. These data collectively imply that transcriptional activation of defense-related gene expression; increase of phenylpropanoid, lignin, flavonoid, and terpenoid biosynthesis; and inhibition of photosynthesis are generalnatures associated with the lesion formation and constitutively activated defense responses in those mutants. Further studies on the identified SGs and CGs will shed new light on the function of each LES gene as well as the regulatory network of defense responses in maize.Disease lesion mimic ( Further studies on related genes indicated that they acted as negative regulators of defense responses via modulating resistance (R) gene SNC1 (Suppressor Of NPR1-1 Constitutive 1) at transcriptional and/or protein level (oscul3a (Oryza sativa cullin3a) is resistant to both Magnaporthe oryzae and Xanthomonas oryzae pv oryzae, and OsCUL3a (Cullin-3a) negatively regulates cell death and immunity by degrading OsNPR1 (Non-Expresser Of PR Genes1) (mlo (mildew resistance locus O) mutant conferred race-non-specific resistance to powdery mildew pathogens (Erysiphe graminis f.sp. hordei) (lesion mimic 3) have enhanced resistance to leaf rust (Puccinia triticina) and powdery mildew (Blumeria graminis f. sp. tritici), respectively  . In barl hordei) . In wheaectively .Les) and recessive disease lesion mimic (les) mutants have been found more than half a century ago  is a les mutant showing elevated resistance to both Cochliobolus heterostrophus and Puccinia sorghi infections at the leaf epidermis (Rp1-D21 (Resistance to P sorghi-D21) mutant, a Les mutant resulting from an aberration in the maize Rp1 disease resistance gene, confers a non-specific resistance to all common rust biotypes tested (P. sorghi)  . These sTranscriptional and metabolic regulations are essential for priming plant defense responses. Previous transcriptomic analysis has identified thousands of genes being upregulated under pathogen invasion , with a Phenylalanine Ammonia Lyase (PAL) and Cinnamyl Alcohol Dehydrogenase (CAD) gene expressions are upregulated after infection of Cercospora zeina or Rhizoctonia solani in maize  confers banded leaf and sheath blight resistance in maize, resulting from the accumulation of lignin and restriction of lesion expansion via ZmCAD activation , Les10 , and Les17  seeds were generously provided by Maize Genetics Cooperation Stock Center. All seeds were planted at the experimental station of Henan Agricultural University in Xinxiang, Henan Province, China. All Les mutant plants from the stock were self-pollinated for two generations. A typical line showing 1:3 segregations of wild type (WT) and mutant phenotypes in the third generation of each Les stock was considered to be heterozygous, and the plants with WT and mutant phenotypes were sampled separately in this generation. Specifically, the putative homozygous plants of Les4 and Les10 showed more intense lesions than the putative heterozygous plants, while for Les17, the lesion phenotype of putative homozygous and/or heterozygous plants were similar  solution for 8 h in the dark (For diaminobenzidine (DAB) staining, the leaf sample harvested above were cut into 3-cm-wide pieces, soaked in 1 mg mlthe dark . After rC. lunata (Wakker) Boed. as previously described with some modifications  (cm2 leaf area)–1 is presented.We performed the pathogen test of ications . The C. ® UltraTM RNA Library Prep Kit for Illumina®  following the manufacturer’s manual and index codes were added to attribute sequences to each sample  using HISAT2 . The subcellular location analysis of CGs was performed with the SUBA43  to remove DNA contamination  and were5; MS, Applied Biosystems 4500 Q TRAP6, the 4-μl sample extracts were injected into a C18 column , which was set to 40°C. The mobile phase was used as follows: A: pure water with 0.04% acetic acid, B: acetonitrile with 0.04% acetic acid. Sample measurements were performed with a gradient program as follows: 0–10 min, 5% B–95% B; 10–11 min, 95% B; 11–11.1 min, 95% B–5% B; 11.1–14 min, 5% B. The effluent was alternatively connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS. The conditions and operation parameters were set as in previous studies (2(FC) ≥ 1 or ≤ -1. The shared DAMs in Les4, Les10, and Les17 were defined as common differentially accumulated metabolites (CMs). KEGG analysis of CMs was performed with the MBROLE 2.07 . The metabolites were extracted using the method of  studies . Metabol studies . PartialOLE 2.07 .Les mutants, we used three representative Les mutants Les4, Les10, and Les17 that have been previously mapped to distinct loci  Boed. strain that causes curvularia leaf spot because the oval-shaped disease lesions are easily distinguishable from that of the big irregularly shaped spontaneous lesions in Les4. At 7 days after inoculation, the WT leaves displayed many disease lesions, while disease lesions observed in Les4 mutant were about 25% that of the WT, indicating significantly enhanced resistance of Les4 to curvularia leaf spot  plots clearly separated the WT samples from the mutant samples and the replicates of both WT and mutants were clustered into distinct patches  were identified in ectively , 3. Of tnd Les17 . Furthernd Les17 . GO termprocess”  in BP-GOGO terms . There wGO terms . In geneLes4, Les10, and Les17 mutants and were defined as specific genes (SGs)  . To lookidation” . SGs of ic acid” . SGs of esponse” . We searectively , suggestLes mutants are in different backgrounds, it is less likely that we could identify many common DEGs. However, 480 DEGs were commonly shared by the Les4, Les10, and Les17 mutants and were designated as CGs  genes. We specifically searched for the 480 CGs in the PRGs database and identified 58 putative PRGs upregulated in all three Les mutants , jasmonic acid (JA), and phenylpropanoid were significantly enriched . Consistative WT , which i mutants .Based on SUBA4 analysis, most proteins encoded by those CGs were estimated to localize in plasma membrane and nucleus . ConsistLes mutants and their relative WT by UPLC-ESI-MS/MS. In this assay, 455 metabolites were collectively identified, including ∼30% flavonoids, 13% phenolic acids, 12% lipid, 11% alkaloids, 11% amino acids and derivatives, 6% organic acids, 5% nucleotides and derivatives, 2% lignans and coumarins, and 10% others   . In thoses (CMs) . Interesin Les10 . Among ain Les10 . While fin Les10 .Based on KEGG and GO enrichment analysis of CGs and CMs, we found that terms of phenylpropanoids and flavonoids were most highly enriched , 9. TherPAL, Cinnamate 4-Hydroxylase (C4H), 4-4-Coumarate: Coenzyme A Ligase (4CL), HCT, CAD, Laccase (LAC), etc., displayed increased expression in Les4, Les10, and Les17 mutant compared to their respective WT , Chalcone Isomerase (CHI), Flavonol Synthase (FLS), UDP-Glucose:Phloretin 2’-O-Glucosyltransferase (P2’GT), Flavanone 3-Hydroxylase (F3H), Flavonoid 3’-Hydroxylase (F3’H), and Dihydroflavonol 4-Reductase (DFR), were greatly increased in Les mutants  1-10 (ZX1-ZX10), were upregulated in all Les mutants (Anther Ear 2 (AN2), Kaurene Synthase-Like (KSL2), Cytochrome P450 (CYP) Z16/18 (CYP71Z16/18), Kauralexin Reductase 2 (KR2), and Kauralexin Oxidase 2 (KO2) were also upregulated in Les mutants  1–6 (BX1–BX6) were mostly downregulated in almost all three Les mutants  and benzoxazinoid since both are very important antibiotic compounds in maize. Because zealexins and kauralexins were not detected due to technical issue in this study, we specifically checked the transcriptional changes of zealexins and kauralexins biosynthetic genes. Surprisingly, all of the zealexins biosynthetic genes,  mutants . Similar mutants . These dlucoside , the dom mutants . In cont mutants . These dLes/les mutants show spontaneous lesion and enhanced disease resistance that are often accompanied by stunted plant growth, implying the constitutive activation of defense responses in those mutants. To make better use of the maize Les/les mutants, it is crucial to systematically understand the molecular bases of commonly and specifically activated defenses leading to those traits. In this study, high-throughput transcriptomics and metabolomics analysis were utilized to explore the specific and common transcriptional and metabolic changes associated with the Les-related traits including necrotic lesions, stunted plant growth, and enhanced disease resistance.Plant Les4, Les10, and Les17, respectively. According to GO enrichment analysis, most of those DEGs were related to defense response and metabolic process . GO enrichment analysis of SGs indicate that LES4’s function may be more directly related to secondary metabolism regulation since lipid, anthocyanin, and flavonoid metabolic processes were most significantly changed in Les4. LES10 is probably involved in the regulation of defense responses to necrotrophic pathogen since wounding and JA-related processes were most significantly changed. LES17, however, is likely involved in the regulation of SA-mediated systemic acquired resistance and hypersensitive responses since representative genes were captured. Using PRG database, we identified 31, 167, and 58 PRGs for Les4, Les10, and Les17, respectively  for all three Les mutants. More interestingly, ∼81% of CGs are shared with the published genes being induced by pathogen infection , which was previously shown to positively regulate zealexins and kauralexins biosynthesis  and the flavonoid biosynthetic genes like CHS, DFR, F3’H, and FLS were upregulated in all three Les mutants  interaction and genetic analysis is provided. In addition, further studies on the identified SGs and CGs will shed new light on the function of each LES gene as well as the general regulatory network of defense responses in maize.Based on our study, a working model is proposed . FirstlyGSE148220).Data of RNA-Seq in this study have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (GEO) database (accession no. MG and XM designed the experiments, interpreted the data, and wrote the article. XM performed most of the experiments and analyzed the data. JL prepared the materials. LX and TF performed the pathogen test. ZD, TJ, and MC worked on the lignin measurement and RNA extraction. All authors contributed to the article and approved the submitted version.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.


The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determining the impact of biological and clinical variables remains critical to understanding potential markers of disease severity and progression. The present large study, including relevant controls, sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831), testing positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples from acutely ill patients while in the emergency department, at admission, and during hospitalization. We then performed additional lipidomics analyses of the 60 subjects with the lowest and highest body mass index, either COVID-19 positive or negative. Omics data were correlated to detailed data on patient characteristics and clinical laboratory assays measuring coagulation, hematology and chemistry analytes. Significant changes in arginine/proline/citrulline, tryptophan/indole/kynurenine, fatty acid and acyl-carnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half yielding ~ 78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for follow-up mechanistic studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses. Our original study aimed to identify metabolic signatures that could help inform prognosis and guide treatment early after the onset of COVID-19, the disease caused by SARS-CoV-2 infection. Indeed, small molecule metabolites provide the building blocks that fuel viral replication, from nucleic acids to proteins and membrane lipids. SARS-CoV-25 – like other viral infections6 – was found to promote the mobilization of free fatty acids to support the formation of viral capsid-associated membranes, a phenomenon that could be explained, at least in part, by activation of phospholipase A2,8 a target amenable to pharmacological intervention.On April 28 2020 we began performing one of the earliest investigations on the impact of SARS-CoV-2 infection on the circulating metabolome.10 which may also escape acquired immunity and/or vaccination.12 Therefore, efforts aimed at identifying strategies to treat SARS-CoV-2, including metabolic interventions or repurposing drugs with potential metabolic targets,13 remain important.Despite public health interventions and the advent of multiple vaccination strategies, the number of cases in the United States has plateaued, rather than continuing to decrease, and COVID-19 cases continue to rise globally. This may be explained by multiple factors, including (i) vaccination rates lagging behind the percentage required to reach herd immunity; (ii) reopening too early, while discontinuing public health mandates; and (iii) the emergence of variants with more efficient transmission,1 like most subsequent studies,21 evaluated small cohorts of COVID-19 patients, with varying severity of disease, and often used healthy individuals as controls. Therefore, some of the reported observations could result from inflammation or infection, in general, rather than COVID-19, in particular. For example, activation of the kynurenine pathway23 could result from inflammatory or interferon-activated responses to viral infection,24 and from downstream activation of indole 2,3-dioxygenase. Based on these observational reports, it was correctly25 predicted that subjects with basal activation of these pathways  may be more susceptible to life-threatening COVID-19.26To this end, herein we collected a large independent data set, including patient characteristics, clinical information, and routine and specialized clinical laboratory results of acutely ill patients, who tested either positive or negative for SARS-CoV-2. This large patient group allowed for verification and expansion of previously published metabolomics studies in COVID-19 and other acute critical illnesses. Our 2020 study,27 age,28 ethnicity,29 body mass index,30 blood group31) and clinical 32 characteristics are necessary to define independent and overlapping metabolic findings in COVID-19 and other acute diseases. To this end, in some cases, we performed sub-analyses focusing on one variable at a time, like sex23 or inflammation  levels).4The published metabolomics studies on COVID-19 were not powered to characterize the effects of other variables critical for disease severity and prognosis. As exsmples, evaluation of biological  and then the development of antibody responses (Stage 2).33 Herein, we expand this approach, as a proof-of-principle, by comparing three mechanically-ventilated COVID-19 patients at up to 21 longitudinal time points; these data suggest a pattern of metabolic changes with relevance to prognosis in severe COVID-19 cases.Another limitation of previous studies, including ours,1 compared the metabolome of COVID-19 patients to healthy controls; this prevented defining a metabolic signature specific to COVID-19 that could be differentiated from other acute illnesses or infections. Therefore, here we enrolled hospitalized patients who were COVID-19-negative (by PCR and/or serology), some of whom had non-COVID-19 respiratory tract infections. Not surprisingly, the metabolic phenotypes of these COVID-19-negative patients partially overlapped with those who were COVID-19-positive   patients, indicated by blood urea nitrogen (BUN) and creatinine levels (39), and negative correlations between BUN and amino acids. As an internal validation of this approach, creatinine measured in the same samples by a CLIA-certified clinical chemistry assay and mass spectrometry correlated extremely well  . Notablye levels . The pospatients –8, inclu22 to be significantly increased in COVID-19 patients as a function of IL-6 levels , markers of mitochondrial dysfunction , with a role in inflammation and thermogenesis via lipid catabolism.44 Consistently, COVID-19 induced increases in levels of long-chain poly- and highly-unsaturated free fatty acids and decreases in acyl-carnitines, although not saturated short and medium-chain ones  ranges, from underweight (BMI 13–20) to severely obese (BMI up to 50), highlighting a positive correlation between BMI and several 18, 20 and 22C series mono- and poly-unsaturated fatty acids in COVID-19-positive, as compared to COVID-19-negative patients  were confirmed6 levels –B. In co6 levels . Indeed,6 levels . IL-6 le6 levels . Positiv6 levels  were obsain ones –E. Poly-ain ones  and negaain ones , but cormbranes6 . Given t46 and given the large size of our cohorts, we tried identifying metabolic and clinical correlates for these variables , and tryptophan and its metabolites, were top correlates to the coagulation parameters  identified clinical and metabolic correlates to coagulation parameters, including D-dimer, APTT, INR , FVIII, TG, VWF:AG, and VWF:Collagen binding activity –F. IL-6,rameters –F.52, were positively correlated with liver transaminases , inflammation (CRP), liver damage , and proteolysis/hemodilution  identified a strong interaction with arginine/proline metabolism, ferritin/hemoglobin/RBC counts, and tryptophan/kynurenine metabolism –L. InterDH, inflaaminases –K.Leveraging the manually-curated clinical records for the enrolled patients, we identified clinical and metabolic markers correlating with mechanical ventilation , stroke 32 Meta-analysis of our cohorts , indicative of progressive mitochondrial dysfunction.59 Given the role of these metabolites in immunometabolism,42 older patients also demonstrated increased inflammation, especially COVID-19 patients, accompanied by poorer outcomes. Similarly, purine catabolism and oxidation products , hallmarks of ischemic44 and hemorrhagic41 hypoxic organ damage, increased with age. Importantly, mitochondria activity, aging, and inflammation are all associated with hypercoagulabiity,49 harmonizing our observational results with the known increased incidence of thromboembolic complications in COVID-19.For example, despite a positive correlation with weight and BMI, aging was accompanied by decreased circulating levels of several poly- and highly-unsaturated fatty acids, consistent with reported age-dependent declines in unsaturated fatty acids in healthy blood donors60 and following the pathological vesiculation of RBC membranes.45 Because obesity also leads to poor outcomes in COVID-19, lipidomics analyses of 60 subjects with the highest and lowest BMIs allowed identification of obesity-related lipid signatures in COVID-19 patients. In particular, neutral lipids  and phospholipids (PC and LPE) were mobilized; the latter may result from release of methyl-groups from LPCs to meet one carbon demands for viral nucleotide synthesis or repair of oxidant-induced isoaspartyl-damage61.In contrast, aging, especially in COVID-19 patients, was accompanied by altered levels of free fatty acids and acyl-carnitines. The former may fuel viral membrane synthesis, which may be sustained by lipid mobilization from adipose tissue and other sources, similar to observations in trauma patients62 and hemodilution. As another example, positive correlations between pro-inflammatory conjugated bile acids and liver transaminases support prior findings of mechanistic interactions of these metabolites with IL-1 beta and hepatic stress.52 Interestingly, these metabolites were also associated with coagulopathy in trauma/hemorrhagic shock,63 and with microbiome dysbiosis related to iron metabolism64, observations informing the correlations in our study between ferritin levels, acute phase response proteins (CRP), and conjugated bile acids.These metabolic observations were exacerbated in COVID-19 patients and were consistent with disease severity, as indicated by clinical records and clinical measurements of markers of inflammation , coagulopathy , and renal dysfunction . Metabolic correlates of these clinical parameters are provided in this study, as part of the efforts aimed at compiling an encyclopedic characterization of metabolism in health and disease. For example, we found strong negative correlations between kidney dysfunction and circulating amino acid levels, as possible indicators of decreased renal reabsorption65 Notably, we confirm4 that arginine/proline/citrulline metabolism is an important pathway affected by COVID-19, which not only depends on kidney function, but also on enterocytes.66 Furthermore, arginase to nitric oxide synthase activity may influence the pro-/anti-inflammatory state of gut resident macrophages.67 In addition, circulating levels of arginine pathway metabolites can be affected by RBC arginase activity45, which is in turn affected by oxidant stress and can contribute to COVID-19-induced endotheliopathy.40Besides aging and inflammation, other factors are also associated with poor outcomes in COVID-19. For example, the expression levels of angiotensin converting enzyme 2 (ACE2) receptor in enterocytes modulate disease severity, in that viral entry into cells is mediated by pairing of ACE2 with the viral spike protein.68 were also significantly decreased in COVID-19 patients, especially in those with the poorest outcomes. These decreases may result from tryptophan depletion as a function of kynurenine pathway activation in COVID-19,23 especially in older males. We confirmed that kynurenine levels correlated with SARS-CoV-2 infection, disease severity, and mortality. Indeed, IL-6 levels and kynurenine/tryptophan ratios were among the top predictors of mortality in COVID-19 patients, confirming previous targeted analyses20 of our larger, independent cohort. However, as activation of interferon responses appear necessary for eliciting adaptive immunity against COVID-19,33 it is interesting that, in our longitudinal blood collections of the COVID-19 patient who died, plasma kynurenine levels did not increase. In contrast, because some metabolites in the kynurenine pathway are neurotoxic 69, uncontrolled activation of this pathway may contribute to some neurological comorbidities of COVID-19 . Interestingly, declines in tryptophan-derived de novo nicotinamide synthesis is associated with aging and inflammation,70 suggesting that nutritionally replenishing NAD reservoirs  may be therapeutic in facilitating recovery from severe COVID-19.71Indole metabolites of microbial origin72 This is relevant given the importance of coagulopathy in COVID-19, with increased plasma levels of FVIII, D-dimers, and VWF , which are among the top correlates of mortality in our cohort. In addition, inflammation negatively correlated with albumin levels, perhaps due to inflammation-induced proteolysis, agreeing with previous reports that albumin predicts all-cause and cardiovascular mortality in chronic kidney disease patients.73 Albumin strongly correlated with total protein and hemoglobin levels, which were also among the top correlates with kidney dysfunction, thereby strengthening the evidence supporting RBC contributions to kidney physiology.38 In contrast, no major effects of ABO blood group were noted in our cohort, except for a link to IL-6 levels . Not surprisingly, ABO blood group was also linked to patient ethnicity in our cohort, which correlated with increased inflammation (IL-6), D-dimers, creatinine, and cystine (oxidant stress) in individuals of African descent.Depleting tryptophan to promote kynurenine synthesis may also lead to serotonin depletion, a key component of platelet dense granules with a role in platelet activation.Finally, as a proof-of-principle, we entered admission data  into machine learning algorithms, randomly selecting approximately half of the COVID-19 patient cohort as a training set and the other half as a test set. The resulting model exhibited high specificity (>95%), but moderate sensitivity (~ 70%). The prediction accuracy of these models may be affected by clinical contributors to the metabolic heterogeneity of hospitalized patients, such as elements of their medical history. Nonetheless, we report here for the first time that metabolic phenotypes of COVID-19 patients were most extreme in patients presenting with a history of hypertension, chronic kidney disease, lung disease, cancer, coronary artery disease, or lung disease.Taken together, the extensively detailed information in this large, prospective, observational study will support future mechanistic studies and data sharing opportunities to enhance understanding of the plasma metabolism in COVID-19 and other acute critical illnesses.This study was approved by the Institutional Review Board of Columbia University Irving Medical Center (CUIMC) (Protocol Number AAAT0680). Data were obtained for patients who were either admitted to the hospital or seen in the Emergency Department from April 14, 2020 through May 31, 2020 , and were evaluated for SARS-CoV-2 by RT-PCR, serology. As part of routine care, hemostasis was evaluated on STAR Evolution and STAR Max analyzers , hematology testing by Sysmex XN900 , and chemistry testing by Roche Cobas c502 . Laboratory values, including antithrombin (AT), prothrombin time (PT)/international normalized ratio (INR), activated partial thromboplastin time aPTT, fibrinogen, d-dimer, white blood cell count (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute monocyte count (AMC), hemoglobin, red blood cell count (RBC), RBC distribution width (RDW), reticulocyte count, platelet count, IL-6, lactate dehydrogenase (LDH), lactic acid, procalcitonin, troponin, blood urea nitrogen (BUN), creatinine, glucose, total-, direct-, and indirect bilirubin, aspartate amino transferase (AST), alanine amino transferase (ALT), albumin, total protein, ferritin, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), creatine kinase (CK), triglycerides, and blood type, were collected. Laboratory data were obtained from the Clinical Data Warehouse at CUIMC after approval from the Tripartite Request Assessment Committee. Clinical and demographic data, including name, medical record number (MRN), sex, date of birth, age, race, ethnicity, weight, body mass index, comorbidities , intubation/ventilator requirement, continuous veno-venous hemofiltration (CVVH) requirement, radiographically-confirmed thrombotic complications , clotting of CVVH, hospitalization course , mortality and date of death) were collected manually by reviewing the electronic medical record. Data were collected retrospectively for patients treated at two New York-Presbyterian Hospital campuses . Residual platelet poor plasma samples were collected for subsequent analyses.74 Briefly, 20 μL of plasma were diluted in 130 μl of LC-MS grade water, 600 μl of ice-cold chloroform/methanol (2:1) was added, and the samples vortexed for 10 seconds. Samples were then incubated at 4°C for 5 minutes, quickly vortexed (5 seconds), and centrifuged at 14,000 x g for 10 minutes at 4°C. The top  phase was transferred to a new tube for metabolomics analysis.Sample processing and metabolite extraction: Plasma samples were extracted via a modified Folch method (chloroform/methanol/water 8:4:3), which completely inactivates other coronaviruses, such as MERS-CoV.75 Solvents were supplemented with 0.1 % formic acid for positive mode runs and 1 mM ammonium acetate for negative mode runs. MS acquisition, data analysis and elaboration was performed as described. 75Analyses were performed using a Vanquish UHPLC coupled online to a Q Exactive mass spectrometer . Samples were analyzed using a 5 and 17 min gradient as described.75 and application papers,76 using a Vanquish UHPLC system coupled online to a high-resolution Q Exactive mass spectrometer . Samples were resolved over a Kinetex C18 column  at 45°C. A volume of 10 ul of sample extracts was injected into the UHPLC-MS. Each sample was injected and run four times with two different chromatographic and MS conditions as follows: 1) using a 5 minute gradient at 450 μL/minute from 5–95% B  and the MS was operated in positive mode and 2) using a 5 minute gradient at 450 μL/minute from 5–95% B  and the MS was operated in negative ion mode. The UHPLC system was coupled online with a Q Exactive  scanning in Full MS mode at 70,000 resolution in the 60–900 m/z range, 4 kV spray voltage, 15 sheath gas and 5 auxiliary gas, operated in negative or positive ion mode (separate runs). These chromatographic and MS conditions were applied for both relative and targeted quantitative metabolomics measurements, with the differences that for the latter targeted quantitative post hoc analyses were performed on the basis of the stable isotope-labeled internal standards used as a reference quantitative measurement, as detailed below.UHPLC-MS metabolomics analyses were performed as described in method45 over an ACQUITY HSS T3 column  using an aqueous phase (A) of 25% acetonitrile and 5 mM ammonium acetate and a mobile phase (B) of 50% isopropanol, 45% acetonitrile and 5 mM ammonium acetate. Samples were eluted from the column using either the solvent gradient: 0–1 min 25% B and 0.3 mL/min; 1–2 min 25–50% B and 0.3 mL/min, 2–8 min 50–90% B and 0.3 mL/min, 8–10 min 90–99% B and 0.3 mL/min, 10–14 min hold at 99% B and 0.3 mL/min, 14–14.1 min 99 – 25% B 1and 0.3 mL/min, 14.1–16.9 min hold at 25% B and 0.4 mL/min, 16.9–17 min hold at 25% B and resume flow of 0.3 mL/min. isocratic elution of 5% B flowed at 250 pl/min and 25°C or a gradient from 0–5% B over 0.5 min; 5–95% B over 0.6 min, hold at 95% B for 1.65 min; 95 – 5% B over 0.25 min; hold at 5% B for 2 min, flowed at 450 μl/min and 35°C53. The Q Exactive mass spectrometer  was operated independently in positive or negative ion mode, scanning in Full MS mode (2 pscans) from 150 to 1500 m/z at 70,000 resolution, with 4 kV spray voltage, 45 shealth gas, 15 auxiliary gas.Samples were resolved as described,77 and applied to similar samples  in D’Alessandro et al. Haematologica 20 2 057.MS2 analyses for untargeted metabolomics For discovery mode untargeted metabolomics, dd-MS2 was performed at 17,500 resolution, AGC target = 1 e5, maximum IT = 50 ms, and stepped NCE of 25, 35 for positive mode, and 20, 24, and 28 for negative mode, as described in Stefeanoni et al. Haematologica 20 20,Calibration was performed prior to analysis using the Pierce™ Positive and Negative Ion Calibration Solutions (Thermo Fisher Scientific). Acquired data was then converted from .raw to .mzXML file format using Mass Matrix . Samples were analyzed in randomized order with a technical mixture  injected every 10 runs to qualify instrument performance. This technical mixture was also injected three times per polarity mode and analyzed with the parameters above, except CID fragmentation was included for unknown compound identification .13C, and 15N isotopes were performed using MAVEN ,78 against an in house library of deuterated lipid standards  and in house libraries of 3,000 unlabeled  and labeled standards (see below for the latter). Discovery mode analysis was performed with standard workflows using Compound Discoverer 2.1 SP1 . From these analyses, metabolite IDs or unique chemical formulae were determined from high-resolution accurate intact mass, isotopic patterns, identification of eventual adducts  and MS2 fragmentation spectra against the KEGG pathway, HMDB, ChEBI, and ChEMBL databases. Additional untargeted lipidomics analyses were performed with the software LipidSearch .Metabolite assignments, isotopologue distributions, and correction for expected natural abundances of deuterium, 79. Briefly, plasma samples were mixed with either thrombin specific substrate, Z-Gly-Gly-Arg-AMC  or plasmin specific substrate, Boc-Glu-Lys-Lys-AMC  and 16 nM of thrombomodulin . The reaction was initiated by adding an activator solution that yielded a final concentration of 1 μM tissue factor , 0.7 Mg/mL of tissue plasminogen activator  and 16 mM CaCl2. Sample wells supplemented with buffer (150 mM NaCl and 20 mM HEPES) and AMC fluorophore instead of activator solution were used for background and calibrator measurements respectively. Calculation of thrombin and plasmin concentration was performed as described previously 80.Simultaneous evaluation of thrombin and plasmin generation  was performed as described previouslyThe antigen and activity measurement of VWF and ADAMTS13 was performed by using commercial ELISA kits. VWF antigen and collagen binding activity levels were measured by using Human Von Willebrand Factor ELISA Kit  and TECHNOZYM® vWF:CBA ELISA Kit  respectively. ADAMTS13 antigen and activity levels were measured by using Human ADAMTS13 ELISA Kit  and TECHNOZYM® ADAMTS13 Activity ELISA  respectively. FVIII antigen levels were measured by using Human Factor VIII total antigen assay ELISA kit . All assays were performed following manufacturer’s recommendations with additional dilution of plasma samples as required.81 In MetaboAnalyst, relative quant data (but not for abs quant), raw values for integrated peak areas for each metabolite were normalized on a pool of day 0 controls and auto-scaled for each species independently prior to margining all the data for multivariate analysis. Analyses through MetaboAnalyst included principal component analysis, partial least square discriminant analysis, hierarchical clustering analyses , calculation of receiver operating characteristic (ROC) curves, correlation analyses (Spearman) and machine learning analyses .Graphs and statistical analyses (either t-test or repeated measures ANOVA) were prepared with GraphPad Prism 5.0 , GENE E , and MetaboAnalyst 4.0.Supplement 1Supplement 2


The OTUD6B and ZMIZ1 genes were recently identified as causes of syndromic intellectual disability (ID) with shared phenotypes of facial dysmorphism, distal limb anomalies, and seizure disorders. OTUD6B- and ZMIZ1-related ID are inherited in autosomal recessive and autosomal dominant patterns, respectively. We report a 5-year-old girl with developmental delay, facial phenotypes resembling Williams syndrome, and cardiac defects. The patient also had terminal broadening of the fingers and polydactyly. Cytogenomic microarray (CMA), whole exome sequencing (WES), and mRNA analysis were performed. The CMA showed a paternally inherited 0.118 Mb deletion of 8q21.3, chr8:92084087–92202189, with OTUD6B involved. The WES identified a hemizygous OTUD6B variant, c.873delA (p.Lys291AsnfsTer3). The mother was heterozygous for this allele. The WES also demonstrated a heterozygous ZMIZ1 variant, c.1491 + 2T > C, in the patient and her father. This ZMIZ1 variant yielded exon 14 skipping, as evidenced by mRNA study. We suggest that Williams syndrome-like phenotypes, namely, periorbital edema, hanging cheek, and long and smooth philtrum represent expanded phenotypes of OTUD6B-related ID. Our data expand the genotypic spectrum of OTUD6B- and ZMIZ1-related disorders. This is the first reported case of a compound heterozygote featuring point mutation, chromosomal microdeletion of OTUD6B, and the unique event of OTUD6B, coupled with ZMIZ1 variants. Multiple congenital anomalies and intellectual disabilities (ID) are common features of many chromosomal and single gene disorders. Owing to the phenotypic and genetic heterogeneity associated with congenital anomalies and ID, establishing a causative diagnosis, based on clinical signs and symptoms, can be challenging. Chromosomal microarray (CMA) has been recommended as the first-tier test in evaluating patients with unexplained ID and multiple congenital anomalies, as endorsed by the American College of Medical Genetics and Genomics (ACMG) ,2. CMA dOTUD6B (ovarian tumor domain-containing 6B) gene, located on chromosome 8q21.3 and consisting of 7 exons, encodes a 323-amino acid protein. OTU6B may play roles in the initiation of protein synthesis, repression of DNA synthesis, and regulation of cell growth and proliferation (uniprot.org/uniprot (accessed on 15 August 2021) [OTUD6B were first described to cause intellectual disability associated with seizure, dysmorphic features, and congenital malformations, including distal limb abnormalities. Some studies propose clinical similarities between OTUD6B-related phenotypes and Rubinstein-Taybi syndrome and Kabuki syndrome [The st 2021) . In 2017syndrome ,10.ZMIZ1 (zinc finger MIZ-domain containing 1), mapped to 10q22.1-q22.3 and containing 21 exons, encodes a 1067-amino acid peptide. ZMIZ1 protein functions as a transcriptional regulator that interacts with other proteins involved in the development of neuronal and glial cells [ZMIZ1 variants have been found to be associated with neurodevelopmental disorder with dysmorphic facies and distal skeletal anomalies (NEDDFSA), including infantile hypotonia, seizures, and ID of varying severity. Since the first description of ZMIZ1 as the cause of ID, in 2019, only a handful of cases have been reported, most of which represented de novo occurrences; only two families were reported with inherited mutations [al cells . Heterozutations ,12.OTUD6B, 8q21.3 microdeletion compounded with a point mutation of the gene, in a patient with ID and Williams syndrome-like phenotypes. We also identify a novel inherited ZMIZ1 variant, resulting in a splicing error. Similarities and differences of clinical manifestations, caused by mutations of the two genes, are also discussed.Herein, we describe novel genetic defects of The patient was a 5-year-old girl who was referred for further genetic investigation owing to her developmental delay, cardiac, and hand anomalies, as well as suspected Williams syndrome (OMIM 194050). Prior investigation included karyotype and fluorescence in situ hybridization (FISH) analysis of 7q11.23, which demonstrated 46, XX, while no deletion was detected by the FISH study.DNA was extracted from peripheral blood, using Gentra Puregene kit . A single nucleotide polymorphism array  was performed and analyzed using BlueFuse Multi software v4.1 (Illumina). The Database of Genomic Variants (DGV) and the Thai CNV database  were useIn an attempt to enroll additional patients into the study, we reviewed curated databases, ClinGen and DECIPHER, searching for patients described as having small (~5Mb or less) microdeletions of the 8q21.3 region.Whole exome sequencing (WES) was performed. All exons of all human genes  were captured by Twist Human Core Exome Kit . The captured genomic regions were sequenced using NovaSeq 6000 (Illumina). The raw genome sequencing data analysis, including alignment to the reference sequence, was found , followed by reverse transcription, using iScript Reverse Transcription Supermix for RT-qPCR , in accordance with the manufacturer’s instructions. PCR and sequencing of the cDNA were performed using primers specific for exons 12 and 17 of the ZMIZ1 gene as follows: forward, 5′-ACCCTGGAGAGCCCAACTAT-3′ and reverse, 5′-GGTCAGACCTCCACATCAGC-3′. The PCR products representing normal and aberrant transcripts were cut out from the agarose gel, then purified using QIAquick Gel Extraction Kit (QIAGEN), before being subjected to Sanger sequencing.Primers were designed using PRIMER3 (frodo.wi.mit.edu (accessed on 9 September 2020)). The reference sequences were NC_000008.10 and NM_016023 for OTUD6B study, as well as NC_000010.10 and NM_020338.3 for ZMIZ1 analysis.This study was approved by the Ramathibodi Hospital Human Research Ethics Committee (COA MURA2020/1273). Genetic analyses were performed following the provision of written informed consent. Consent for the publication of identifiable data of the patient, including photograph, was provided by the parents.The patient was born by cesarean section at a gestational age of 37 weeks, with Apgar scores of 9 and 10 at 1 and 5 min, respectively. Her birth parameters were normal, including weight of 2800 g (50th centile), length of 50 cm (50th–75th centile), and head circumference of 31 cm (3rd–10th centile). She was noted to have respiratory distress right after birth, and was confirmed to have atrial septal defect, ventricular septal defect, and mild pulmonic stenosis. The patient underwent surgical closure of atrial septal defect at 12 months.As an infant, the patient exhibited failure to thrive. At 18 months of age, her growth parameters were at the lowest normal limit, including weight of 8.4 kg (3rd–10th centile), height of 75.5 cm (3rd centile), and head circumference of 44 cm (3rd centile). Her physical growth gradually improved with age, and it has been within the normal range since the age of 3 years.Developmentally, the patient exhibited developmental delay. She could hold to stand up at 18 months, started walking at 24 months, walked independently at 3.6 years, walked up and down stairs at 4 years, and jumped and hopped by 6 years. At 4 years, she was noted to walk on her tiptoe, but without lower limb spasticity. As for language development, she spoke a few single words at 30 months, put 2–3 words together at 3 years and talked in short phrases by 5 years. The patient was able to start toilet training and took part in showering, dressing, and feeding herself at 4 years of age.The patient first developed generalized tonic-clonic (GTC) seizures at 12 and 24 months, preceded by high-graded fever. The third (at 28 months) and fourth episodes (at 29 months) were atonic and tonic-clonic seizures, respectively, with no precipitating cause identified. Her seizures were controlled by phenobarbital, but the medication was discontinued soon after, owing to cutaneous drug reaction, leading to multiple episodes of seizures. Sodium valproate was introduced and controlled her seizures well. At the age of 7 years, there were two episodes of breakthrough seizures, leading to the initiation of topiramate and tailing of valproate.Physical examination at 5 years of age revealed arched and sparse lateral eyebrows, periorbital puffiness, prominent nasal bridge, long philtrum, thin vermillion of the upper lip, hanging cheek, postaxial polydactyly at the left hand, terminal broadening of the fingers, and broad thumbs and great toes A. NeurolOther investigations revealed normal hearing. Ophthalmological examinations at 5 years revealed normal visual acuity and fundoscopic examination, as performed by an ophthalmologist. Ultrasonography of the kidney and urinary system showed normal findings.Family history was negative for consanguinity, seizures, developmental/intellectual problems, and congenital anomalies B. The paAt the time of this writing, the patient is 7.5 years old, weighs 41.4 kg (>97th centile), is 120 cm tall (50th centile), and has a head circumference of 52 cm (75th–90th centile). She communicates in short sentences with good comprehension, being better at the receptive than at the expressive part. She is active in daily life and attends kindergarten.CMA analysis of the patient revealed a 118,100 bps deletion of chromosome 8q21.3  A. The deThe WES analysis of the patient’s specimen identified a hemizygous variant, c.873delA, in exon 6 of the OTUD6B gene (NM_016023). The deletion variant was predicted to cause a frameshift mutation and premature protein truncation (p.Lys291AsnfsTer3). This allele (rs 762934606) is present at an extremely low frequency (0.00003926) in gnomAD (gnomad.broadinstitute.org (accessed on 14 April 2020)) and was classified as likely pathogenic . The motThe segregation of biallelic variants (in trans) of OTUD6B in the patient, and the heterozygous state in the asmptomatic parents, suggests that the 8q21.3: 0.118 Mb deletion and the OTUD6B:c.873delA each respresent a pathogenic recessive allele. A review of curated databases disclosed small 8q21.3 microdeletion, involving OTUD6B in one case, listed in ClinGen, and three cases in DECIPHER. The sizes of the deletions ranged from 3.597 to 5.781 Mb. The phenotypes and genomic locations of these patients were detailed in the Unexpectedly, the WES analysis disclosed a heterozygous nucleotide substitution at the splice donor site of intron 14 of the ZMIZ1 gene, c.1491 + 2T > C. This variant was not present in gnomAD (MAF = 0) or T-REx: Thai Reference Exome Database (trex.nbt.or.th (accessed on 18 September 2021)) (MAF = 0) and was categorized as pathogenic , based on the ACMG/AMP guidelines . Sanger The splicing error of c.1491 + 2T > C mutation was evaluated using in silico analysis software, NNSPLICE 0.9 (fruitfly.org/seq_tools/splice.htm (accessed on 9 September 2020)), which indicated the loss of splicing ability, with the score changed from 0.99 to 0. PCR of the mRNA transcript of coding exons 12–17 yielded both normal sized and aberrant transcripts in the specimens of the patient and her father, but it only yielded normal transcripts in her mother and a control individual B. SangerOTUD6B and heterozygous ZMIZ1 mutations, and that the present patient harbored genetic defects of these two genes, we compared the phenotypes of the present patient to those in previous reports, as summarized in Given clinical similarities of the phenotypes, caused by biallelic mutations of OTUD6B- and ZMIZ1-related disorders share nonspecific phenotypes of ID, global developmental delay, hypotonia, microcephaly, feeding difficulty, and distal limb anomalies in at least two-thirds of the patients. However, some features were relatively prevalent and more specific to those of OTUD6B-linked ID, including substantial epilepsy, characteristic facial dysmorphisms, arched eyebrows/long palpebral fissures, prominent nasal bridge; broad thumb with/without polydactyly . In contrast, facial features and distal limb anomalies found in ZMIZ1-related ID were nonspecific, while ophthalmological abnormalities were more frequently observed in this group.We noticed that both In this study, we demonstrated, for the first time, a genetic compound between a point mutation and a chromosomal structural variant of 8q21.3 as the cause of OTUD6B-linked disorder. We also revealed the unique event of biallelic-OTUD6B mutations coincidental with a ZMIZ1 variant with potential pathogenicity. Both OTUD6B variants and the ZMIZ1 variant were inherited alleles and were not previously reported.Although a genetic compound between a chromosomal defect and a nucleotide change is a rare cause of an autosomal recessive disorder , this poThe hemizygous c.873delA, in exon 6 of the patient, was due to missing exons 3–7, as part of the 8q21.3 deletion of the homologous chromosome.Nine mutations of OTUD6B have been reported in 12 families, all of them were from Hispanic origin or were from Mediterranean countries ,8,9,10. Notably, a recurrent nonsense mutation of OTUD6B, c.433C > T p.Arg145*), has been reported to be consistently associated with severe phenotypes, namely severe ID, restricted ambulation, and absent speech *, has be,9. In coHomozygous Otud6b knockout mice were shown to have low viability, or die shortly after birth, and exhibited growth restriction and congenital heart and hand anomalies, similar to those observed in association with disruption of its human homologue .OTUD6B is a deubiquinating enzyme which reverse the ubiquitination, a process of post-translational protein modification, thus maintaining the homeostasis of cellular functions. This gene is universally expressed in human tissue, including fetal brain and B-and T-cell lineages (uniprot.org/uniprot (accessed on 15 August 2021)). OTUD6B has been experimentally confirmed or predicted to interact with many genes, most of which are involved in cell cycle regulation and apoptosis. Given the global expression of OTUD6B, mutations of this gene could lead to abnormalities of multiple tissues and organs. However, the reasons for some specific findings, such as ID, seizures, intrauterine growth restriction, and hand and cardiac defects, as well as the mechanisms behind them, have remained unclear. Nonetheless, the involvement of proteasome assembly defect has been strongly suggested.The PTK2 gene is one of the top 25 genes interacting with OTUD6B, as described in the protein-protein interaction database, STRING (string-db.org (accessed on 15 August 2021)). PTK2 is a non-receptor protein kinase that plays roles in early embryonic development, placental development, cardiomyocyte migration, normal heart formation, axonal growth, synapse formation, and neuronal cell migration. It is possible that some of the OTUD6B-related features are partly a result of defective interaction between the OTUD6B and PTK2 genes.ZMIZ1 belongs to a group of transcriptional coregulators, the Protein Inhibitor of Activated STAT (PIAS)-like family. It regulates the functions of DNA-binding transcription factors, but it does not directly bind DNA . ZMIZ1 dTo date, 15 pathogenic, or likely pathogenic, ZMIZ1 variants have been described in 18 families, most of which represent de novo events. Two families were reported with dominantly inherited mutations and intra-familial variability ,12.Our patient inherited the ZMIZ1 splice variant, c.1491 + 2T > C, from her asymptomatic father (II-3). As specimens from the paternal relatives were not available for analysis, we could only guess that this allele could have been inherited through one of the paternal grandparents (I-2 and I-3) and might have been passed on to their other child (II-2) and grandchildren (III-1 and III-2).We showed that the ZMIZ1 c.1491 + 2T > C allele resulted in a mutant transcript lacking the entire exon 14. It was predicted to yield a mutant protein with an in-frame deletion of 26 amino acids ; 5 individuals with c.1491 + 2T > A (Latino/Admixed American) in gnomAD. The c.1491 + 1G > A was assigned as pathogenic , whereas c.1491 + 2T > A was judged as benign  based on the ACMG/AMP classification. Functional studies of these variants in animal and cellular models could further elucidate their true pathogenic effects.Taking these findings together, we assume that the OTUD6B mutations were primarily responsible for the phenotypes of our patient because they cause an autosomal recessive disorder that is generally not associated with reduced penetrance. However, it is difficult to entirely rule out the effect of the ZMIZ1 variant, which might be involved in the the patient’s manifestations. The patient’s phenotypes better match OTUD6B-linked characteristics, namely, epilepsy, prominent nasal bridge, arched eyebrows, and broad thumb/polydactyly. Additionally, the father and his blood relatives  were asymptomatic.In conclusion, we suggest that Williams syndrome-like phenotypes, namely, periorbital edema, hanging cheek, and long and smooth philtrum represent an expanded range of phenotypes of OTUD6B-related ID. Our data widen the genotypic spectrum of the OTUD6B- and ZMIZ1-related disorders. Clinical correlation and review of the phenotypes associated with the autosomal recessive gene(s) involved in the rearranged chromosomal segment should not be overlooked when dealing with VUS CNVs in patient(s) with an unrecognizable disorder.


Extranodal NK/T-cell lymphoma is a neoplasm of NK cells or cytotoxic T cells presenting in extranodal sites, most often in the nasal cavity. The typical immunophenotypes are cCD3+, sCD3−, CD4−, CD5−, CD8−, CD16−, and CD56+ with the expression of cytotoxic molecules. Tumor subsets express NK cell receptors, CD95/CD95L, CD30, MYC, and PDL1. Virtually all the tumor cells harbor the EBV genome, which plays a key role in lymphomagenesis as an epigenetic driver. EBV-encoded oncoproteins modulate the host-cell epigenetic machinery, reprogramming the viral and host epigenomes using host epigenetic modifiers. NGS analysis revealed the mutational landscape of ENKTL, predominantly involving the JAK–STAT pathway, epigenetic modifications, the RNA helicase family, the RAS/MAP kinase pathway, and tumor suppressors, which indicate an important role of these pathways and this group of genes in the lymphomagenesis of ENKTL. Recently, three molecular subtypes were proposed, the tumor-suppressor/immune-modulator (TSIM), MGA-BRDT (MB), and HDAC9-EP300-ARID1A (HEA) subtypes, and they are well-correlated with the cell of origin, EBV pattern, genomic alterations, and clinical outcomes. A future investigation into the function and interaction of discovered genes would be very helpful for better understanding the molecular pathogenesis of ENKTL and establishing better treatment strategies. Extranodal NK/T-cell lymphoma (ENKTL) is an EBV-associated NK or cytotoxic T-cell lymphoma occurring at the extranodal site, predominantly in the nasal region . This enThe histologic findings for ENKTL are similar irrespective of whether a lesion is nasal or extranasal . They arThe typical phenotype of ENKTL is CD2+, surface CD3−, cytoplasmic CD3ε+, CD4−, CD5−, CD8−, CD56+, and cytotoxic markers  (+)  [1] but ENKTL is a tumor of either NK cell or cytotoxic T cell lineage. T and NK cells originate from the same lymphoid progenitor cells and develop into different cell lineages with the rearrangement of TCR gene . BecauseThe EBV-positive mature T/NK cell malignancies described in the 2017 WHO classification include ENKTL, EBV-positive T-cell lymphoma of childhood, aggressive NK cell leukemia (ANKL), and EBV-positive nodal T-/NK cell lymphoma  1,54,55,5554,55.Aggressive NK cell leukemia (ANKL) is a rare systemic lymphoproliferative disease of NK cells characterized by an association with EBV, prevalence in Asia, and aggressive clinical course . ANKL isNodal T-/NK cell lymphoma is a primary nodal EBV-positive cytotoxic T- or, uncommonly, NK cell lymphoma without nasal involvement ,55; it iIntravascular lymphoma is rare non-Hodgkin’s lymphoma characterized by the exclusively intraluminal growth of neoplastic lymphoid cells within blood vessels . Most caFOXO3, HACE1, PRDM1, ATG5, and AIM1, were identified in the minimal region in del 6q21 [FOXO3 and PRDM1 in NK cell neoplasms was proven by genomic and functional analyses [ATG5, a gene essential for autophagy [When the entity of ENKTL was introduced in the REAL classification in 1994, studies to explore the genetic alterations in ENKTL were delayed because adequate tissue for analysis was difficult to obtain due to extensive tumor necrosis and the small size of the nasal biopsy. In 1997, cytogenetic analysis by Wong K.F. et al. on recurrent deletion at 6q21–q25 in one nasal, one extranasal, and one leukemic form of NK/T-cell lymphoma provided clues for tracking genetic abnormalities in ENKTL . The subdel 6q21 ,74. The analyses ,76,77. Fanalyses ,76. PRDMutophagy , and AIMutophagy , showingutophagy ,72,74. Tutophagy ,81,82. Autophagy .The development of the NGS technique has accelerated the study of genetic mutations in NK/T-cell lymphoma and aided in examining the genomic landscape from the analysis of individual genes. In 2012, the first data from high-throughput next-generation sequencing analysis came from a Singaporean group . Since tA. JAK/STAT PathwayJanus kinase/signal transducer and activator of transcription (JAK/STAT) signaling is crucial for NK cell development and maturation . When a B. Epigenetic ModifiersMLLs and BCOR are the most commonly mutated, followed by TET2, EP300, and ARID1A [Epigenetic modifiers comprise the largest group among the mutated genes according to the NGS data reported to date . MLLs and ARID1A ,90,91,92d ARID1A . KMT2 fad ARID1A . MLL2/KMd ARID1A ,108,109.d ARID1A ,89,90,91d ARID1A ,91. The d ARID1A . The BCLd ARID1A ,111,112.d ARID1A ,114,115.d ARID1A . The BCOd ARID1A ,94. The d ARID1A ,116. BCOd ARID1A . Other ed ARID1A . The mutd ARID1A ; this wad ARID1A ,87,91. Sd ARID1A . EP300 fd ARID1A . EP300 id ARID1A . The mutd ARID1A  and occud ARID1A ,91. Stopd ARID1A ,123, andd ARID1A ,88,91.C. Tumor SuppressorIn ENKTL, many tumor-suppressor genes are inactivated by promotor hypermethylation and deletion. TP53 mutations were detected in 105 of 242 cases  by Sanger sequencing ,124,125 D. RAS/MAPK PathwayThe Ras/mitogen-activated protein kinase (RAS/MAPK) pathway regulates cellular processes such as proliferation, survival, and migration . The mutE. RNA HelicaseThe RNA helicase family is one of a large group of genes altered in ENKTL, accounting for 8.4% of the mutated genes detected using an NGS platform ,86,89,90F. OthersIKBKB and BIRC3, involved in the NF-kB pathway, are mutated at a low frequency, while the evolutionarily conserved signaling intermediate in Toll pathway (ECSIT) was subject to a hotspot mutation; ECSIT-V140A occurred in 17 of 88 (19%) ENKTLs and was associated with the activation of NF-kappa B, a higher incidence of hemophagocytic syndrome, and poor prognosis . The evoMolecular subtyping is a new way to classify cancers into different groups based on multi-omic data. Xiong J. et al.  performeThe tumor cells of ENKTL consist of either NKs or cytotoxic T cells. ENKTL has few pathological and clinical differences according to cell lineage. The mutational landscapes of NK and T-cell-derived ENKTLs showed no difference in a study by Jiang L. et al. analyzing 105 cases of ENKTL . HoweverGenetic alterations are crucial for the pathogenesis of ENKTL, but epigenetic alterations may be more important during EBV-associated tumorigenesis . EBV plaExtranodal NK/T-cell lymphoma and aggressive NK cell leukemia (ANKL) are the prototypes of EBV-positive T- or NK cell malignancy, with distinct clinical findings. EBV-positive nodal T- or, uncommonly, NK cell lymphoma is a recently recognized tumor characterized by an EBV-positive tumor present in the lymph nodes. All of these three entities share EBV as an important etiologic factor and a cytotoxic phenotype of either T or NK cells, but they are different in clinical presentation.An early aCGH study by Nakashima Y. et al.  reportedIn the NGS era, data from three NGS studies showed more similarities than differences between the two entities. Hussein E. et al.  analyzedEBV-positive nodal T-cell lymphoma is a tumor mainly derived from cytotoxic T cells expressing alpha–beta or gamma–delta receptors or lacking TCR antigen expression ,55,154. Chronic lymphoproliferative disorder of NK cells (CLPD-NK) and T-cell large granular lymphocytic leukemia (T-LGL) are chronic clonal lymphoproliferative disorders with similar indolent clinical features and accumulation of cytotoxic granular lymphocytes of either NK or T-cell lineage . Recent ENKTL is distinct from CLPD-NK and T-LGL in clinical aspects and the presence of EBV in tumor cells but shares a high frequency of STAT3 mutation. Epigenetic modifiers in ENKTL were the largest group affected by the mutations. Although the action mechanism and target genes of epigenetic modifiers have not yet been well elucidated, epigenetics are highly likely to play a central role in tumorigenesis of ENKTL, as demonstrated in TET2 and STAT3 of CLPD-NK.It has been more than 130 years since ENKTL was first described as “ulceronecrotic proliferative lesions of the upper airways”. Since the conception of the disease, it has been established that this tumor mainly consists of NK cells and that EBV infects most of the tumor cells. The recently developed molecular genetic analysis technology allows for exploring the genetic and epigenetic characteristics of ENKTL, as well as the mechanism by which EBV infection in NK cells is involved in tumorigenesis. However, data on the functions and interactions of these genes in the lymphomagenesis of ENKTL are very scarce. More studies in this field would be very helpful in better understanding the molecular genetic pathogenesis of ENKTL and establishing better treatment strategies.


Fasciola gigantica is a parasitic helminth that has been frequently reported to infect mammals, typically involving water buffaloes. In this study, we characterized the tissue transcriptional landscape of buffaloes following infection by F. gigantica. RNAs were isolated from hepatic lymph nodes (hLNs), peripheral blood lymphocytes (pBLs), and spleen at 3-, 42- and 70-days post-infection (dpi), and all samples were subjected to RNA sequencing analyses. At 3 dpi, 2603, 460, and 162 differentially expressed transcripts (DETs) were detected in hLNs, pBLs, and spleen, respectively. At 42 dpi, 322, 937, and 196 DETs were detected in hLNs, pBLs, and spleen, respectively. At 70 dpi, 376, 334, and 165 DETs were detected in hLNs, pBLs, and spleen, respectively. Functional enrichment analysis identified upregulated immune-related pathways in the infected tissues involved in innate and adaptive immune responses, especially in hLNs at 42 and 70 dpi, and pBLs at 3 and 42 dpi. The upregulated transcripts in spleen were not enriched in any immune-related pathway. Co-expression network analysis further identified transcriptional changes associated with immune response to F. gigantica infection. Receiver operating characteristic (ROC) curve analysis showed that 107 genes in hLNs, 32 genes in pBLs, and 36 genes in spleen correlated with F. gigantica load. These findings provide new insight into molecular mechanisms and signaling pathways associated with F. gigantica infection in buffaloes.The tropical liver fluke  Fasciola gigantica is a socioeconomically important tropical liver fluke of mammals, causing fascioliasis–a neglected tropical disease. In the present study, RNA sequencing and bioinformatic approach were employed to explore the global transcriptional changes of hepatic lymph nodes (hLNs), peripheral blood lymphocytes (pBLs), and spleen of water buffaloes during F. gigantica infection at 3-, 42-, and 70-days post-infection (dpi). The results revealed significant transcriptional upregulation of genes associated with innate and adaptive immune responses in infected hLNs (42 and 70 dpi) and pBLs (3 and 42 dpi). However, downregulation of transcripts involved in immune response was detected in pBLs at 70 dpi. The downregulated transcripts were enriched in metabolic pathways, such as drug metabolism-cytochrome P450 in infected hLNs at 3 dpi. These findings provide new insight into the pathogenesis of F. gigantica in its natural mammalian host. Fasciola hepatica and Fasciola gigantica are members of the genus Fasciola. F. hepatica has a worldwide geographical distribution, while F. gigantica is found in tropical regions, including Asia, Africa, and some parts of Europe [Fasciola spp. can infect between 2.4 and 17 million people, and 180 million are at risk of infection. Fasciola spp. also can infect a wide range of livestock animals, of which cattle and water buffalo are the most affected species [F. hepatica infects cattle species (Bos taurus) [F. gigantica in Asia and south China [Fasciola spp. infection mainly takes place in liver, and its severity depends on the parasite burden. The clinical symptoms of fascioliasis is divided into acute  and chronic  phases [f Europe ,2. Fasci species ,4. While taurus) ,6, buffath China . The pat) phases . These sF. gigantica occurs when animals ingest grass and water containing infective metacercariae (encysted juvenile parasites). After ingestion, the metacercariae excyst within the duodenum and develop into newly excysted juveniles (NEJs), which penetrate through the intestinal wall into the peritoneal cavity [Infection with l cavity . After 3l cavity .F. gigantica remains limited. Furthermore, F. gigantica infections are not only limited to the liver of the host but also involve other immune-related tissues. For example, hepatic lymph nodes (hLNs) adjacent to the liver are connected to lymphatic vessels and play important roles in protecting against liver diseases. The spleen, the largest lymphatic organ in the body, produces various immune substances such as immunoglobulins. The peripheral blood lymphocytes (pBLs), including B cells and T cells, counter infection by various pathogens. Previously, we have identified many differentially expressed proteins (DEPs) in F. gigantica-infected buffalo tissues, including hLNs, serum, and spleen, using iTRAQ proteomics [F. gigantica infection in these tissues at the transcriptional level remain largely unknown.Despite significant efforts ,9,12,13,oteomics ,9. HowevF. gigantica-infected buffaloes is not fully known. In addition to Th2 response, mixed Th1/Th2 response, suppression of Th1/Th17 responses, and differential responses of immune cells  have been reported in infected tissues in ruminants or rodents infected by F. hepatica [F. gigantica infection are poorly understood.All helminth infections elicit Th2 regulatory immune response ,15, whichepatica ,18,19. HF. gigantica were examined using RNA-sequencing (RNA-seq). Our comparative analysis revealed significant transcriptomic changes of buffalo tissues at 3, 42, and 70 dpi. We identified hundreds of differentially expressed transcripts (DETs), infection-specific patterns, and genes in different infected tissues that correlated with F. gigantica load.In this study, transcriptomic responses of buffalo’s hLNs, pBLs, and spleen to experimental infection by Water buffaloes were handled in accordance with the Animal Ethics Procedures and Guidelines of the People’s Republic of China, and the study was approved by the Animal Ethics Committee of Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences (Permit number: LVRIAE-2015-08).Fasciola IgG and IgM antibodies using an Enzyme-Linked Immunosorbent Assay (ELISA), as described previously [Eighteen water buffaloes (8-10-months old) were purchased from a local water buffalo farm in Guangxi Zhuang Autonomous Region, China. Buffaloes were randomly assigned into 6 groups , including 3 infected groups and 3 uninfected groups (control group). Buffaloes were kept in a clean shed and provided with enough water and food. The fecal egg counting (FEC) sedimentation method was used to monitor the fluke burden in buffaloes, and serum samples were tested for anti-eviously . AdditioAfter a 4-week of the drug withdrawal period, buffaloes in the three infected groups were inoculated orally with 500 viable metacercariae contained within digestible capsules in 1 mL 0.85% sodium chloride (NaCl) solution; buffaloes in the three control groups were mock-infected with an equal volume of 0.85% NaCl solution contained within digestible capsules but without metacercariae.F. gigantica in infected liver and bile duct was confirmed by examination, as described previously [At 3, 42, and 70 dpi, the presence of eviously ,9 and bu260/280) of the RNA preparation was examined using a NanoPhotometer spectrophotometer , and all RNA preparations had an absorbance ratio OD260/280 > 1.8. The integrity and concentration of RNA were examined using RNA Nano 6000 Assay Kit  and Qubit RNA Assay Kit , respectively. Three micrograms of each RNA sample were used for the construction of RNA libraries according to the protocol of NEBNext Ultra RNA Library Prep Kit . Each library was sequenced on an Illumina HiSeq 2500  resulting in standard pair-end 2 × 150 reads.The RNA of each sample was extracted using TRIzol Reagent  following the manufacturer’s protocols. RNA samples were treated with 20 units of RQ1 RNase-Free DNase  to remove residual genomic DNA. The purity (ODhttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used to process the raw data for quality control analysis. Low-quality reads and adapters were filtered using Trim_Galore  to generate clean reads. The reference genome, annotation information and transcript sequence of swamp buffalo were downloaded from Genome Warehouse of China (http://bigd.big.ac.cn/gwh/) [bona fide mRNA transcript: (i) at least one sample has transcript reads ≥ 30, and the average reads of a transcript in all samples ≥ 3; (ii) a transcript at least has 3 exons, and the sequence length is ≥ 500 bp; (iii) transcript has ≥ 50% sequence encoding a protein and the length of the protein sequence is ≥ 100 aa.FastQC   with acccn/gwh/) . The repcn/gwh/) , and on cn/gwh/)  and Stricn/gwh/)  to identcn/gwh/) , their pcn/gwh/)  and, simBos taurus were used as the input data of BRAKER2 program. The eventual results contained an AUGUSTUS GTF file. Transcript results from StringTie and AUGUSTUS were assembled into a GTF file using EVidenceModeler v1.1.1 [Bos taurus protein using BLASTp .We used BRAKER2 tool to further improve the transcript predictions. BRAKER2  is a newr v1.1.1 , resultiP-value < 0.05 and |log2 fold-change| ≥ 1.5. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses following the strategy of TBtools software [ftp://ftp.pir.georgetown.edu/databases/idmapping/, and considered as the background list of GO enrichment analysis; (iii) based on the calculation principle of the hypergeometric distribution test, GO enrichment analysis of DETs was performed in TBtools program. For KEGG enrichment analysis, there were two steps: (i) online KAAS web-based server (https://www.genome.jp/tools/kaas/) was used to automatically annotate the KEGG orthologs (KO) of buffalo transcripts; (ii) KEGG enrichment analysis of DETs was performed using TBtools based on the principle of hypergeometric distribution test.We quantified the expression of the identified non-redundant transcripts using StringTie v2.1.4 across all samples. The expressed read counts of each transcript were used for differential expression analysis using DESeq2 v1.30.1 package [software  to obtaiF. gigantica-infected tissues. TPM (Transcripts per Million) expression matrix of transcripts was used as the input data. The soft-threshold power for 0.9 was chosen as the correlation coefficient threshold and the minimum number of genes in modules was set to 10. To merge similar modules, we defined 0.2 as the threshold value for cut height. Days post-infection and infection status  were used as input traits in the module-trait correlation analysis. The correlation clusters of interconnected genes that shared similar expression patterns were considered as co-expression modules, and high module groups with significance values greater than 0.5 were selected as predictors that may be correlative with F. gigantica load. In order to test the predictive performance between module hub genes and F. gigantica infection, pROC package v1.66.0 [F. gigantica infection in each tissue were selected out with gene AUC value > 0.6 and TPM > 1.We performed weighted gene co-expression network analysis (WGCNA) to identify the co-expressed gene modules and analyzed the relationship between gene network and phenotype to find the core genes in the network. Briefly, the WGCNA R package v1.0.1  was used v1.66.0  was usedF. gigantica was detected in the infected liver and/or bile duct tissues of the buffalo and the parasite samples from all three infection time points have been collected previously [Fasciola spp. were negative in control groups.At days 3, 42, and 70 after infection, eviously ,34, whicBos taurus via BLASTp to the Uniprot data sets .The RNA integrity numbers (RINs) of each RNA template > 8.0. In this study, we generated 54 high-quality libraries, all of them were subjected to the paired-end Illumina sequencing, and each infected and control group contained 3 biological replicates. The read number (raw and clean reads), Q20, Q30, and GC content of quality control are shown in P-value < 0.05 and Log2FoldChange ≥ 1.5) revealed that: (i) in the infected hLNs, 650, 155, and 248 transcripts were upregulated at 3, 42, and 70 dpi, respectively, whereas 1953, 167, and 128 transcripts were downregulated at 3, 42, and 70 dpi, respectively  inectively ; (iii) iectively . For DETectively , indicatWe performed functional enrichment and pathway analyses of the DETs in infected tissues. The downregulation of transcripts in the infected hLNs at 3 dpi was significantly enriched for GO terms involved in the neuron or cell-related processes, such as neurogenesis, cell communication, neuron differentiation, and neuron projection development, while the upregulation of transcripts for GO terms was mainly involved in eukaryotic cell division, such as mitotic sister chromatid segregation, nuclear chromosome segregation, and mitotic nuclear division. Notably, in the upregulated transcripts in the infected hLNs at 42 and 70 dpi and the infected pBLs at 3 and 42 dpi, most of the enriched transcripts associated with GO terms or pathways were involved in the immune response. Typically, these included complement-mediated attack, mixed innate and adaptive immunity, and inflammatory response . It was P-value < 0.05, the top 10 significantly enriched GO terms are shown in We also performed GO and pathway analysis of all DETs. According to the corrected F. gigantica infection and, with regarding the hLNs, pBLs, and spleen tissue at the three infection time points, the module-trait correlation with value > 0.5 was considered as further analysis. Among these, 3 modules (M1~M3) were from the hLNs group, 7 modules (M4~M10) from the pBLs group, and 2 modules (M11 and M12) from the spleen group , and genes were significantly enriched in the immune system process, immune response, and defense response . HoweverF. gigantica load. The details of these genes including areas under the ROC curve (AUC), chromosome position, differential expression analysis for each time point, and function description are summarized in F. gigantica infection.Results of the ROC analysis revealed the validation of hub genes from the WGCNA modules, of which there were 107 genes in the hLNs, 32 genes in the pBLs, and 36 genes in the spleen that were predicted to be correlated with F. gigantica using RNA-seq approach. Differential expression analysis of transcripts between infected and uninfected tissues revealed significant changes in the number of DETs at 3, 42, and 70 dpi  identified in F. gigantica-infected buffaloes [F. gigantica NEJs from the intestinal wall into the peritoneal cavity are associated with significant transcriptional dysregulation in hLNs.In this study, we performed a comparison of transcriptomic changes in three important immune tissues  of buffaloes following the infection by the liver fluke d 70 dpi . F. gigauffaloes . These rF. gigantica at 3, 42, and 70 dpi [We have previously presented a detailed proteomic analysis of buffalo’s hLNs, global serum, and spleen following the infection of d 70 dpi . By compF. gigantica-infected liver tissue [GSTA2, GSTA3, GSTA4, GSTM1, GSTO2, GSTT3, and MGST1), 4 alcohol dehydrogenases , 1 flavin-containing monooxygenase (FMO1), 1 hematopoietic prostaglandin (HPGDS), 1 glutathione transferase (LOC100295687), and 1 amine oxidase (MAOB)  . Interes animals . Among tIGL-λ, IGL-κ, and IGHM) and two Th2-type cytokines (IL-4 and IL-13) significantly upregulated (> 4-fold) in infected animals. The WGCNA analysis showed that the transcriptional changes of these genes in infected animals are associated with F. gigantica load  at 3 and 70 dpi was significantly upregulated in infected animals, but without any corresponding change in the proteome results. KEGG pathway enrichment analysis suggested that Fc epsilon RI signaling pathway was significantly upregulated (FCER1G) was inhibited in chronic F. hepatica infection (16 weeks) in sheep [FCER1G was not altered in the present study. Because polymorphism of Fc receptor exists in many organisms [Fasciola-infected hosts should be elucidated in further studies.In the hLNs, at 42 and 70 dpi, immune-related processes or pathways such as immunoglobulin response, humoral immune, adaptive immunity, B cell-mediated immunity and cytokine-receptor interaction were significantly upregulated in infected animals . There wica load . Previouola spp. –40. Th2-ola spp. . The exp surface . Fc rece surface . In our egulated . Interesin sheep , but therganisms , the rolIL-17F, IL-17RD, IL-23, and IL23R) were significantly downregulated, which is similar to previous findings on F. hepatica-induced infection in ovine peripheral blood mononuclear cells [GHSR (growth hormone secretagogue receptor) and SFRP1 (secreted frizzled-related protein 1), that are involved in the growth and regulation of immune cells such as macrophages, T cells, and B cells, were also downregulated significantly by 9 and 100-fold, respectively. GHSR can promote the switch of macrophage phenotype to anti-inflammatory M2 in mice [GHSR during early infection stage may not be helpful to the resolution of pro-inflammatory, thereby increasing the helminth impact on host fitness. SFRP1 can respond to IL-1 during the immune response, and negatively regulates the proliferation of B cells. The downregulation of SFRP1 in infected animals indicates that blood cells during early stages of infection preferentially activate humoral immunity to resist the parasite invasion. Interestingly, the new coronavirus disease (COVID-19) related pathway was found activated , and two neutrophil-related chemokines (CXCL3 and CXCL6), and one nitric oxide synthase (NOS2). NOS2 encodes inducible nitric oxide synthase (iNOS) and produces a carbon monoxide (NO) molecule, which has microbicidal and antiparasitic properties [IL-1, IL-6, and IL-8 [NOS2 and inflammatory mediators  in PBMCs of F. hepatica-infected cattle [F. hepatica-infected ovine PBMCs [F. hepatica antigen (fatty acid-binding protein)-induced human macrophages [NOS2 may be species-specific and/or tissue-specific during Fasciola spp. infection.The upregulated transcripts of pBLs at 42 dpi were involved in inflammatory response, and some genes were significantly upregulated, including four cytokines  secrete IL-12 and stimulate natural killer cells (NK) to produce IFN-γ, and then activate STAT1 and promote the differentiation of Th1-type cells thereby mediating innate immunity, however adaptive immunity requires IL-12 to activate STAT4 [IFN-γ, STAT1, and STAT4 in infected tissues were 0.85, 134, and 27, respectively. The expression value of IFN-γ was relatively low, which may play a role in the suppression of Th1-type immunity.The cellular immune response of pBLs at a late stage of infection (70 dpi) exhibited a reverse trend, and anti-pathogen immunity and immune system were downregulated. Previous studies have shown that infections induced by immunity ,56. The te STAT4 . Among tIFCGR1A), 2’-5’ oligoadenylate synthase gene (OAS1Y), RNA helicase gene (DDX58), interferon-induced GTP-binding protein 2 gene (MX2), mannan-binding lectin serine peptidase 1 gene (MASP1), and interferon alpha-inducible protein 6 gene (IFI6). These genes were all downregulated in infected spleen at least by 4-fold. Since the spleen is not the direct target organ of F. gigantica infection, it is speculated that the reason may be related to products of F. gigantica that circulate in the body to the spleen tissue, thereby inhibiting the expression of these immune-related genes. Further research is needed to explore how the fluke effectors influence gene regulation in spleen, and the associated mechanisms of adaptive immune response. At 70 dpi, upregulation and downregulation of spleen transcripts were not enriched in any biological processes, indicating that the effect of F. gigantica on the spleen may be minimal at this phase of infection.Although the spleen is the largest immune organ in the body, upregulation of transcripts during the infection did not fully activate the immune response pathways and the results of our study are very similar to our previous spleen proteomics study . At 3 dpF. gigantica at 3, 42 and 70 dpi. Many differentially expressed transcripts (DETs) were identified in infected tissues, with the largest change occurred in hLNs, especially at 3 dpi . Infection induced significant upregulation of genes and pathways, involved in innate and adaptive immune responses in infected tissues, especially in hLNs at 42 and 70 dpi, and pBLs at 3 and 42 dpi. Consistent with our previous proteomics study, spleen tissue did not exhibit a strong immune response against infection. WGCNA analysis identified many hub genes from co-expression modules that cause differential expression. Validation of the hub genes revealed that 107 hLNs genes, 32 pBLs genes, and 36 spleen genes were correlated with F. gigantica load. These findings improve our understanding of the immunopathology of F. gigantica infection in the buffalo host.In this study, RNA sequencing was used to characterize the transcriptional changes of three important immune-related tissues  of water buffaloes during infection by S1 FigThe yellow bar indicates the number of DETs in tissues of the infected buffaloes, the green bar indicates the number of intersecting DETs, the black circle at the bottom indicates the DETs presented in infected tissue, and the connecting lines indicate the intersecting organs or tissues.(TIF)Click here for additional data file.S2 FigGO functional enrichment analysis demonstrates that six gene modules, i.e., M1 (A), M2 (B), M3 (C), M4 (D), M11 (E) and M12 (F), are significantly enriched in immune-related processes.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.