Control of the COVID-19 pandemic will rely on SARS-CoV-2 vaccine-elicited antibodies to protect against emerging and future variants; an understanding of the unique features of the humoral responses to infection and vaccination, including different vaccine platforms, is needed to achieve this goal.The epitopes and pathways of escape for Spike-specific antibodies in individuals with diverse infection and vaccination history were profiled using Phage-DMS. Principal component analysis was performed to identify regions of antibody binding along the Spike protein that differentiate the samples from one another. Within these epitope regions we determined potential escape mutations by comparing antibody binding of peptides containing wildtype residues versus peptides containing a mutant residue.Individuals with mild infection had antibodies that bound to epitopes in the S2 subunit within the fusion peptide and heptad-repeat regions, whereas vaccinated individuals had antibodies that additionally bound to epitopes in the N- and C-terminal domains of the S1 subunit, a pattern that was also observed in individuals with severe disease due to infection. Epitope binding appeared to change over time after vaccination, but other covariates such as mRNA vaccine dose, mRNA vaccine type, and age did not affect antibody binding to these epitopes. Vaccination induced a relatively uniform escape profile across individuals for some epitopes, whereas there was much more variation in escape pathways in in mildly infected individuals. In the case of antibodies targeting the fusion peptide region, which was a common response to both infection and vaccination, the escape profile after infection was not altered by subsequent vaccination.The finding that SARS-CoV-2 mRNA vaccination resulted in binding to additional epitopes beyond what was seen after infection suggests protection could vary depending on the route of exposure to Spike antigen. The relatively conserved escape pathways to vaccine-induced antibodies relative to infection-induced antibodies suggests that if escape variants emerge, they may be readily selected for across vaccinated individuals. Given that the majority of people will be first exposed to Spike via vaccination and not infection, this work has implications for predicting the selection of immune escape variants at a population level. Current surges in the Delta variant coupled with reports of reduced potency of vaccine elicited antibodies against this variant highlight this concerning ongoing dynamic9. Evidence from related endemic coronaviruses indicates that evolution in the Spike protein results in escape from neutralizing antibodies elicited by prior infection10, potentially contributing to why endemic coronaviruses can reinfect the same host13. Without immunity that is robust in the face of antigenic drift, continual updates of the vaccine to combat new SARS-CoV-2 variants will likely be necessary to provide optimal protection against symptomatic infection.The future of the COVID-19 pandemic will be determined in large part by the ability of vaccine-elicited immunity to protect against current and future variants of the SARS-CoV-2 virus. Several vaccines have now been approved for use in multiple countries, including two that are based on mRNA technology: BNT162b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna). In the United States, over half of adults are now vaccinated against SARS-CoV-2, the majority of whom have received one of these mRNA vaccines. While these vaccines have been shown to effectively guard against infection, severe disease, and death related to SARS-CoV-218. It is currently unknown whether SARS-CoV-2 infection and vaccination result in antibodies that bind to similar epitopes, an important point to consider given that most people have acquired antibodies through immunization and not infection. The Spike protein encoded by the mRNA in both SARS-CoV-2 vaccines is stabilized in the prefusion conformation by addition of two proline substitutions19. This change in sequence and fixed conformation of the Spike protein could result in altered antibody targeting when compared to antibodies elicited during infection, where Spike undergoes several conformational changes. It is also possible that differences in antibody specificity could be due to the amount of antigen or type of immune response stimulated in the context of infection versus vaccination. We know that vaccines drive higher neutralization titers and more Spike binding IgG antibodies than infection22, indicating some differences in the B cell response compared to infection. A recent study showed that antibodies against the receptor binding domain (RBD) of Spike differ between infected and vaccinated individuals; they are generally less sensitive to mutation and bind more broadly across the domain in the context of vaccination as compared to infection23.Prior infection with SARS-CoV-2 also provides some immunity against subsequent re-infection, and several studies have characterized the epitopes targeted by convalescent sera25, few studies have examined the prevalence and escape pathways of these antibodies, especially in the setting of vaccination. Antibodies to linear epitopes in the S2 domain of Spike overlapping the fusion peptide (FP), and in the stem helix region just upstream of heptad repeat 2 (SH-H) region are found in serum from COVID-19 patients, and some studies suggest these antibodies may be neutralizing27. These non-RBD responses may also be important contributors to non-neutralizing antibody activities, which have been associated with protection and therapeutic benefit in experimental SARS-CoV-2 models and with vaccine protection31. Importantly, these epitopes lie in more conserved regions of Spike than RBD where functional constraints on variation may counter the selective pressure for viral escape.Although the majority of the serum binding response in SARS-CoV-2 infected and vaccinated people is directed towards regions of the protein outside of the RBD epitopesTo compare antibody immunity elicited by SARS-CoV-2 infection and vaccination, we used a high-resolution Spike-specific deep mutational scanning phage display library to profile the epitopes and sites of escape for serum antibodies from people who had been infected, vaccinated, or a combination of both. This approach, called Phage-DMS, identified four non-RBD antibody binding epitopes across all samples: the FP and SH-H region in the S2 subunit, and the N-terminal and C-terminal domains  in the S1 subunit of Spike. Antibodies to NTD and CTD were uniquely present in the setting of mRNA vaccination or severe infection, but mostly absent in mild COVID-19 cases. In vaccinated individuals, the magnitude of the response varied over time both to the CTD and SH-H epitopes. Other covariates, such as age, dose, and vaccine type had no significant differences in the binding profiles observed. Of particular relevance to protection against emerging variants, infection and vaccination appear to shape the pathways of escape differently in different epitopes. In the FP epitope, which is a dominant response after infection, the escape pathway was maintained after subsequent vaccination; in the SH-H epitope, infection resulted in antibodies with diverse pathways of escape, whereas vaccination induced a highly uniform escape profile across individuals. Overall, these findings indicate that vaccination induced a broader antibody response across the Spike protein but induced a singular antibody response at the SH-H epitope, which could favor variants that emerge with these mutations.32. The Moderna Trial Cohort were participants in a Phase 1 trial and consisted of 49 individuals, 34 who received the 100 μg dose of mRNA-1273 (Moderna) and 15 who received the 250 μg dose. Serum samples were taken at days 36 and 119 post first dose 32. The HAARVI Cohort included 64 individuals, 44 who had confirmed SARS-CoV-2 infection and 20 who had no reported infection; among this group, 44 were also vaccinated. Those with infection history were stratified by severity based on hospitalization status  and serum was sampled at timepoints ranging from 8 to 309 days post symptom onset. Of these 44 individuals, 24 were also sampled after vaccination with two doses of either mRNA-1273  or BNT162b2 , with 23 from the non-hospitalized group and 1 from the hospitalized group. All 20 SARS-CoV-2 naïve individuals were sampled post-vaccination, with 18 having an additional sample taken pre-vaccination (0 to 98 days). Post-vaccination timepoints for all naïve and convalescent individuals ranged from 23 to 65 days after the first dose . We collected serum samples from two cohorts, termed the Moderna Trial Cohort and the Hospitalized or Ambulatory Adults with Respiratory Viral Infections (HAARVI) Cohort24. This library consists of peptides displayed on the surface of T7 bacteriophage that are 31 amino acids long, tiling across the length of Spike in one amino acid increments. Peptides in the library correspond to the wild-type Wuhan Hu-1 Spike sequence as well as sequences that contain every possible single amino acid mutation at the central position of the peptide. Serum samples were screened with this library by performing immunoprecipitation (IP) followed by sequencing of the pool of phage enriched by the serum antibodies as previously described34.We used a previously described Spike Phage-DMS library to profile the epitopes bound by serum antibodies in the samples described above24. Samples from hospitalized/severe COVID-19 cases and vaccinated individuals also bound to the FP and SH-H regions, but additionally bound to epitopes within the NTD and CTD regions. In naïve serum samples there were antibodies that occasionally bound to the FP and SH-H peptides. These findings likely reflect that some individuals have preexisting cross-reactive antibodies that bind to these conserved regions between SARS-CoV-2 and endemic coronaviruses, as suggested by previous studies18.We first examined the wild-type peptides in the Spike Phage-DMS library that were enriched by each serum sample to determine the epitopes bound by antibodies in each sample from these cohorts . The majA Principal Component Analysis (PCA) was used to further investigate differences between the infected and/or vaccinated groups. This analysis indicated that binding to epitopes in the NTD, CTD, FP, and SH-H regions were driving differences between samples . To quanIn order to determine if there were covariates that contributed to differences in antibody binding, we examined the effect of participant age, vaccine dose and type, and timepoint post infection or vaccination on binding to the four epitopes identified above . For samIn infected individuals, the effect of time post symptom onset on epitope binding was examined using non-hospitalized infected individuals in the HAARVI Cohort, who were sampled between 26 and 309 days post symptom onset . Samples33. Site mutations that cause a loss of binding when compared to the wild-type peptide centered at that same site are reported as having negative differential selection values, whereas those that bind better than the wild-type peptide have positive differential selection values. In order for differential selection to be meaningful, however, we must ensure that we do not include weak or sporadic signals that may be due to non-specific binding. Accordingly, we set a threshold of summed wild-type peptide binding in any one region. By doing so, we lose samples in the analysis but can be confident in the results presented by samples passing this curation step , vaccine type (BNT162b2 or mRNA-1273), and participant age did not significantly affect the specificity of the antibody response.35. This hints that a singular antibody clonotype could be elicited when exposed to a stabilized Spike protein, dominating the response in the SH-H region.We explored the pathways of escape for antibodies binding to these key regions in infected and vaccinated people. We defined for the first time the escape pathways for NTD and CTD-N binding antibodies, epitopes that were commonly found in vaccinated individuals but not in infected individuals. In the case of the NTD epitope, which was located at the C-terminal end of the NTD, escape mutations were uniform and consistent amongst vaccinees, while pathways of escape were more diverse for CTD-N antibodies. Individuals with antibodies that strongly bound the FP epitope had focused escape profiles, with the majority of escape occurring at sites 819, 820, 822, and 823, although the sample size of this group is small (N=3). Vaccination did not greatly alter the escape profile in previously infected individuals, nor did vaccination alone induce a strong or uniform response at the FP epitope. In contrast, antibodies that bind in the SH-H epitope region after infection have diverse pathways of escape, while after vaccination they appear to converge on a more uniform pathway of escape that includes mutations at sites 1148, 1152, 1155 and 1156. Interestingly, these are also the sites of contact for a cross-reactive HR2-specific antibody isolated from a mouse sequentially immunized with the MERS and SARS Spike proteins23. Together these results suggest that the B cell response after vaccination with Spike mRNA continues to evolve over time. Multiple studies have demonstrated that SARS-CoV-2-specific B cells undergo continued somatic hypermutation in the months after infection, likely due to antigen persistence37. Spike antigen has been detected in the lymph nodes at least 3 months after vaccination with BNT162b2, and continued maturation of germinal center B cells could be a possible explanation for the changes in epitope binding we observed38. Alternatively, turnover of short-term plasma cells and memory B cells could account for loss of antibody binding to certain epitopes.We also observed some drift in the pathways of escape within a single person over time after vaccination. This mirrors findings from a recent study that examined sites of escape for RBD-specific antibodies in serum samples from the same Moderna Trial Cohort as used in this study23. Finally, we only have 5 individuals within the hospitalized group and this small sample size limits our ability to make conclusions about epitope binding in those with severe infection.Our study has important limitations worth noting. Because the Spike Phage-DMS library displays 31 amino acid peptides, we are unable to detect antibodies that bind to conformational epitopes and/or glycosylated epitopes. This is demonstrated by the lack of observable binding to the RBD region, a domain with complex folding and known target of antibodies from infected and vaccinated individuals. However, prior studies of RBD epitopes have already been reported using an overlapping set of samples from the HAARVI Cohort, however, and together these results paint a more complete picture of epitopes across the Spike protein39. Thus, the polyclonal response to vaccination may provide greater protection from infection than the more focused response after infection. However, the number of epitopes targeted provides just one benchmark and the ability to escape at the population level could also be influenced by the diversity of individuals’ antibody responses at each epitope and thus the likelihood that a single escape mutation could be widely selected. At one S2-domain epitope region (SH-H) vaccination induced uniform sites of escape that may be due to a singular type of antibody that would allow escape by the same mutations for all vaccinated people. However, epitopes in the S2 domain tend to be in highly conserved regions with important functions that constrain the virus’ ability to mutate, making escape from these antibodies less likely than for RBD, where escape is already common. Indeed, mutations in the FP and SH-H epitopes are not arising in the global population of SARS-CoV-224, providing some suggestion that these regions may be constrained41. Overall, further studies of the functional capacity of these vaccine-elicited antibodies targeting epitopes outside of RBD are warranted, to provide a path towards a polyclonal response to epitopes across the full Spike protein. This comprehensive view may further the goal of a more universal coronavirus vaccine that eliminates the need for continual updates of the SARS-CoV-2 vaccine strain due to mutations in variable regions on Spike.Our finding that vaccinated individuals have a broader response across the Spike protein than infected individuals may have important implications for immune durability against future SARS-CoV-2 variants. Evidence suggests that a polyclonal antibody response that is resistant in the face of multiple mutations is necessary for long-lasting immunity against a mutating viral pathogenNCT04283461)32. All samples were de-identified and thus all work was approved by the Fred Hutchinson Cancer Research Center Institutional Review Board as nonhuman subjects research. Trial participants were given either 100 ug or 250 ug doses of the mRNA-1273 vaccine, and serum was sampled from all trial participants at 36 days and 119 days post vaccination. See Table 1 for detailed metadata related to each participant and serum sample.We obtained post-vaccination serum samples via the National Institute of Allergy and Infection Disease that were taken as part of a phase I clinical trial testing the safety and efficacy of the Moderna mRNA-1273 vaccine  or mRNA-1273 (Moderna). See Table 1 for detailed metadata related to each participant and plasma sample. For convenience, all plasma and serum samples in this study are referred to as serum. This study was approved by the University of Washington Institutional Review Board.We obtained plasma samples from individuals enrolled in the Hospitalized or Ambulatory Adults with Respiratory Viral Infections (HAARVI) study conducted in Seattle24. Following this method, the Spike Phage-DMS library was diluted in Phage Extraction Buffer  to a concentration of 2.964 × 109 plaque forming units/mL, which corresponds to approximately 200,000-fold coverage of each peptide. 10 uL of serum or plasma was added to 1 mL of the diluted library and incubated in a deep 96-well plate overnight at 4°C on a rotator. 40uL of a 1:1 mixture of Protein A and Protein G Dynabeads (Invitrogen) were added to each well and then incubated at 4°C for 4 hours on a rotator. Beads bound to the antibodyphage complex were magnetically separated and washed 3x with 400 uL wash buffer . Beads were resuspended in 40 uL of water and lysed at 95°C for 10 minutes. The diluted Spike Phage-DMS library was also lysed to capture the starting frequencies of peptides. All samples were run twice, once each with two independently generated Spike Phage-DMS libraries.The Spike Phage-DMS library used in this study contained 24,820 designed peptides that tile across the length of the Spike protein. Peptides are each 31 amino acids long and tile by 1 amino acid increments, and correspond to either the wild-type sequence or a sequence containing a single mutation. Serum samples were profiled using the Spike Phage-DMS library as previously described24. Two rounds of PCR were performed using Q5 High-Fidelity 2X Master Mix (NEB). For the first round of PCR, 10uL of lysed phage was used as the template in a 25 uL reaction using primers described in24. For the second round of PCR, 2 uL of the round 1 PCR product was then used as the template in a 50 uL reaction, with primers that add dual indexing sequences on either side of the insert. PCR products were then cleaned using AMPure XP beads (Beckman Coulter) and eluted in 50 uL water. DNA concentrations were quantified via Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen). Equimolar amounts of DNA from the samples, along with 10X the amount of the input library samples, was pooled, gel purified, and the final library was quantified using the KAPA Library Quantification Kit (Roche). Pools were sequenced on an Illumina HiSeq 2500 machine using the rapid run setting with single end reads.DNA from lysed samples were amplified and sequenced as previously describedAll sample IP’s and downstream analysis were run in duplicate across two separate phage display library batches to ensure reproducibility, with the exception of the four acute samples from hospitalized HAARVI participants which were run in singlicate. All results were cross checked with the set of batch replicates to ensure significance fell within one order of magnitude where applicable. For brevity, we present only figures resulting from the single complete set of batch-specific replicates, however, all figures using the second set of library batch replicates are available see . AdditioNextflow pipeline to process the peptide counts as well as alignment stats for all samples42. The tools and parameters describing the workflow are as follows. The index creation and short-read alignment step were done using Bowtie2. During alignment we allowed for zero mismatches in the default seed length of each read  after trimming 32 bases from the 3’ end of each 125bp read to match the 93 bp peptides in our reference library43. Samtools was subsequently used to gather sequencing statistics as well as produce the final peptide counts using the stats and idxstats modules. Finally, the pipeline collected all reference peptide alignment counts and merges them into a single xarray dataset coupling sample and peptide metadata with their respective count. Alignment stats for all replicates are seen in Samples were aliquoted and sequenced targeting 10X coverage of total sample reads to the peptide library reference. We demultiplexed samples using Illumina MiSeq Reporter software. Post sample demultiplexing, we used a Each of the processing steps described here, as well as downstream analysis and plotting, were run using static and freely available Docker containers for reproducibility. We provide an automated workflow and the configuration scripts defining exact parameters. See 44. We first subset our dataset to only include wildtype peptide count enrichments from either infected or vaccinated individuals as input. This curation resulted in the matrix, X of size n × p with n biologically distinct replicates and p enrichment features across the spike protein. All enrichment values were calculated as a fold change in the frequency for any one sample enrichment over the library control enrichment at the same sites. Each feature was mean centered before performing the PCA such that the covariance matrix of X is equivalent to XTX/(n – 1). We can then use the eigendecomposition, X = USVT, to describe the data. The principal axes in feature space are then represented by the columns of V and represent the direction of maximum variance in the data. Principal Component Analysis (PCA) via Singular Value Decomposition (SVD) was performed on each set of batch replicates using the scikit-learn packageIn order to ensure reliable measurements of differential selection of single AA variants compared to the ancestral sequence variant, we threw out samples whose respective sum of wild-type enrichment was below a threshold set for each of the defined binding regions . Once cuphippery and phip-flow described in the https://github.com/matsengrp/phage-dms-vacc-analysis.We provide a fully reproducible automated workflow which ingests raw sequencing data and performs all analyses presented in the paper. The workflow defines and runs the processing steps within publicly available and static Docker software containers, including https://github.com/matsengrp/phip-flow. A template and documentation for the alignment pipeline configuration is available at https://github.com/matsengrp/phip-flow-template. Finally, we provide a python API, phippery, to query the resulting dataset post-alignment that can be found at https://github.com/matsengrp/phippery.The generalized PhIP-Seq alignment and count generation pipeline script can be found at https://github.com/matsengrp/vacc-dms-view-host-repo.All raw sequencing data was submitted to the NCBI SRA under PRJNA765705. Pre-processed enrichment data is available upon request. Additionally, differential selection data and more can be explored interactively using the dms-view toolkit available at jgallowa@fredhutch.org. For original data from the NIH Moderna trial please see Jackson et al32, and for information on the HAARVI cohort please contact HYC.For more information regarding code and data availability, please email Mann-Whitney Wilcoxon test with the exception of analysis that included only paired longitudinal samples - such as the comparison of 36-and-119 Days post-vaccination - in this case we used a Wilcoxon signed-rank test. Bonferroni correction was applied where applicable and adjusted P values < 0.05 were presented as significant. All statistical analysis were done using Python 3.6 and plotted using the statannot package found here https://github.com/webermarcolivier/statannot. The static Docker container used for all statistical analysis is publicly hosted at https://quay.io/repository/matsengrp/vacc-ms-analysis.Estimates of significance presented between group continuous distributions of wild-type enrichment were reported using a 1


ABO gene. The genetic-phenotypic mechanism underneath the four mutually exclusive and collectively exhaustive types of O, A, B and AB could theoretically be elucidated. However, genetic polymorphisms in the human populations render the link elusive, and importantly, past studies using genetically determined rather than biochemically determined ABO types were not and could not be evaluated for the inference errors. Upon both blood-typing and genotyping a cohort of 1008 people of the Han Chinese population, we conducted a genome-wide association study in parallel with both binomial and multinomial log-linear models. Significant genetic variants are all mapped to the ABO gene, and are quantitatively evaluated for binary and multi-class classification performances. Three single nucleotide polymorphisms of rs8176719, rs635634 and rs7030248 would together be sufficient to establish a multinomial predictive model that achieves high accuracy (0.98) and F1 scores (micro 0.99 and macro 0.97). Using the set of identified ABO-associated genetic variants as instrumental variables, we demonstrate the application in causal analysis by Mendelian randomization (MR) studies on blood pressures (one-sample MR) and severe COVID-19 with respiratory failure (two-sample MR).ABO blood system is an inborn trait determined by the  ABO gene, consists of seven exons located on chromosome 9q34.2 and encodes a glycosyltransferase that catalyzes the transfer of carbohydrates to the H antigen to form the antigenic structures of the ABO blood groups [ABO gene differ minimally, and they catalyze the transfer of different carbohydrates  to form the A or B antigen, respectively; in comparison, the ABO gene in individuals with blood type O does not produce A or B antigens due to a single-base nonsense deletion [ABO gene displays a substantial spectrum of single nucleotide polymorphisms (SNPs): over 100 unique alleles have been curated for the ABO gene in the Leiden Open Variation Database [Discovered earliest in 1901 by Karl Landsteiner, the ABO system classifies human blood into exclusive types of O, A, B and AB based on the presence or absence of specific A and B antigens on the surface of red blood cells [Database . For exaDatabase . HoweverABO gene is expressed not only in red blood cells but also in body fluids and tissues surfaces , suggesting the extension of the ABO system in clinical importance beyond immunohematology and transfusion/transplantation medicine [ABO locus [rs579459 in ABO was associated with the risk of coronary artery disease [rs657152 at the ABO gene (the other is rs11385942 at the LZTFL1 gene) [The medicine ,7. The PBO locus . A genet disease , ranking disease . Several disease ,13,14. IGenome-wide association study (GWAS) is a high-throughput method sequencing genomic variants and mapping SNPs associated with the phenotype-of-interest . Hit SNPA group of healthy adult residents of the Han ethnicity in China were recruited as a cohort based on multi-stage sampling from the China Multi-Ethnic Cohort (CMEC) . For GWAFor this study, serological testing of the ABO blood system was conducted for each individual by means of a routine blood test: 2 mL of blood sample were collected, transported cold back to a certified clinical laboratory within 24 h and assayed for agglutination using antisera reagents to identify blood group antigens (ABO blood types as the outcome-of-interest). In parallel, genotyping of single nucleotide polymorphisms (SNPs) was carried out for each individual: 1–2 mL of saliva sample were collected, transported back to a certified genetic laboratory within 24 h, subjected to genomic DNA purification and finally genotyped on a high-throughput multi-channel platform  using Affymetrix Axiom Precision Medicine Array chips (genomic SNPs as the predictors). Other related health and personal information of the participants was collected on site through face-to-face surveys by trained staff . The methods were carried out in accordance with the relevant guidelines and regulations.For one-sample MR analysis, individuals’ blood pressures (systolic and diastolic) were measured by certified medical staff; for two-sample MR analysis, genomic associations with COVID-19 phenotype were retrieved from published literature .The study design and procedure were reviewed and approved by the Research Ethics Committee at West China School of Public Health of Sichuan University. All participants in the cohort were informed of the research design, and have signed the Informed Consent Form. The phenotype and genetic data were subjected to anonymization for the protection of personal privacy. In observance of the Regulatory Articles of Human Genetic Resources of P.R. China, population-based summary statistics are reported for GWAS but no individual’s raw genotypes were published.−8 (−log10(p) of 7.3) was used exclusively for screening hit SNPs  avoidance of linkage disequilibrium (r2 < 0.8). In these tables, # suffix in SNP annotates the subset of hit variants selected and to be evaluated for binary classification performances in rs529565 is the top ranked SNP for O vs. non-O and selected for binary classification evaluation  to rs529565 would not be selected for binary classification evaluation (thus no # suffix: rs657152 with r2 = 0.94 to rs529565). Iterating the above analysis for all hit SNPs leads to the selection of # suffix genetic variants to be evaluated  was assembled by the completion of routine blood tests, lab genotyping experiments and on-site surveys. SNPs on the autosomes were used in association analysis. The raw genetic dataset was pre-processed for quality checks at both sample and SNP levels. For GWAS, two respective models were fit: (1) binomial logistic regression model with the ABO blood types dichotomized into a binary phenotype , and (2) multinomial log-linear model with the ABO blood types treated as a quaternary phenotype . For two-allele SNP settings, the major allele was defined as the reference allele, and the minor allele was thus selected as the effect allele. Locus genotypes were coded as the copies of minor allele, accordingly assuming an additive effect. The top ten principal components (PCs) from principal component analysis (PCA) on SNPs in linkage equilibrium were included in modeling for the adjustment of any remaining genetic substructures. In accordance with common GWAS practice, sex and age were included as covariates in modeling, but in the case of ABO blood types, inclusion or omission of sex and age would not lead to significant differences because the ABO blood types for individuals are determined from birth (do not change as the age grows), and are inherited in an autosomal rather than sex-dependent manner (no association with the sex). We include sex and age in the linear models as covariates to match the general practice of published GWAS for many diseases or traits , but in parallel, we have conducted GWAS analysis without adjusting sex and age, and the top hit SNPs remain the same . With a commonly used significance level of 0.05 adjusted by one million , a conservative Bonferroni corrected threshold of 5 × 10SNPs see , the selvaluated . The invStatistical analysis and data visualization were conducted using version 4.0.0 of the R statistical environment  and PLINK 1.07 . Single-https://github.com/westchinabiomedicaldatascience-Wang-lab/GWAS-ABO (accessed on 6 November 2020). The authors have provided the relevant information  for hit SNPs in The core codes of binomial and multinomial models used in this study are available from the following public GitHub repository: GWAS-ABO An initial cohort of 1008 individuals fully participated in blood-typing, genotyping and on-site surveys. Upon sequential steps of data pre-processing, a final dataset of 921 independent individuals was ready for GWAS analysis . The cohort was summarized for baseline characteristics that are comparable across the four levels of ABO blood system . In addiABO gene and its nearby regions  to avoid the most notable redundant variants, a subset of hit SNPs are selected in each binomial model  are associated with higher probability of type A and type B for single copy of minor alleles but of type AB for dual copies; (3) rs9919007 is associated with higher probability of type B for single copy but of type A and type AB for dual copies; (4) rs7030248 is predominantly associated with type B. These distinct patterns reveal hit SNPs associated with the respective type of the ABO blood system.Dichotomizing ABO blood types into a binary phenotype is a common practice in previous studies, but such an operation leads to the loss of information and would reduce statistical power. In addition, predicted probabilities for each blood type from the four binomial models do not add up to one, leading to the difficulty in appropriately assigning un-blood-typed but genotyped individuals to a specific predicted blood type. To overcome such issues, we treat ABO blood types as a quaternary phenotype (with type O defined as the reference level), perform a multinomial analysis for GWAS and consistently uncover associated variants mapped exclusively to the  regions . There a regions , and som regions . Predict regions : (1) 10 rs8176719 and rs7030248 are among the 19 common hit SNPs  as instrumental variables in one-sample MR, two methods of inverse-variance weighted (IVW) and weighted median argue against a potential causal relationship between the exposure of ABO blood types and the outcome of blood pressures in the Han Chinese population  and a protective effect in blood group O (OR of 0.65) [p < 0.001, The COVID-19 GWAS project not only discovers ABO-mapped ABO gene. Therefore, perfect prediction of ABO blood types based on genetic variants is theoretically possible. We demonstrate that while dichotomizing ABO blood system into a set of binary phenotypes is capable of identifying key genetic variants, treating the phenotype as a quaternary trait and applying a multinomial model would confer higher statistical power and simultaneously evaluate the probabilities of an individual for all four types. A key contribution of our study lies in the simultaneous genotyping and blood-typing of the cohort members so the genetics-based model could be evaluated and optimized for predictive performances. In contrast, past studies subjectively infer blood types from genotypes without quantifying the potential error rate. To make the practice more error-prone, past genetic association studies on ABO blood types generally use individuals’ self-reported rather than biochemically determined ABO blood types, raising concerns for the identity and strength of the hit SNPs used for ABO inference.Our extensive characterization of the ABO genomics validates the ABO blood system as a classical Mendelian phenotype determined exclusively by a single rs8176719, rs635634 and rs7030248 leads to strong performances in multi-class classification, suggesting these three SNPs combined would be sufficient to explain a major proportion of the diversity in the ABO blood system within the Han Chinese population. Given that the allele frequencies of the hit SNPs are comparable but still disparate among different ethnicities . Such efforts combined with larger sample size and populations of different ethnicities should deepen our understanding of the ABO genomics and also optimize a predictive model that precisely or even perfectly determines blood types solely based on genetics.In this study, a predictive model based on nicities , the prep value or highest odds ratio are not necessarily those missense variants that confer structural changes to the glycosyltransferase encoded by the ABO gene. This raises an unverified issue if the ABO blood system could be solely determined by the exons of the ABO gene, or would be dependent on genetic variants both in the exons and introns. Undoubtedly, we only genotyped a subset of all possible missense genetic variants, and there also exists high LD in the region. Therefore, it would be meaningful for future research to conduct whole-gene-sequencing-based association studies to appropriately resolve this issue.An interesting observation from GWAS is that the top hit SNPs with the lowest ABO variants are discovered in large-scale GWAS for association with an increasing number of traits and diseases naturally leads to the necessity to differentiate causality from non-causal association. MR is a fast-developing field to address such causal inferences, but certain key concerns exist. First, the exposure of ABO blood types is treated as a binary variable, which is uncommon but not impossible in MR [ABO gene or variants could be pleiotropic. Finally, there is always a potential but hard-to-evaluate issue regarding ethnicity confounding in two-sample MRs, which could have profound consequences when the p value is marginally significant or insignificant . For the above reasons, the causal inference results from our two-sample MR study between ABO and COVID-19 should be viewed as preliminary rather than conclusive.The involvement of the ABO blood system in biology and health has been ever increasing. Historically, ABO blood-typing is widely applied in paternity testing in an “exclusion” basis before being replaced by the genotyping-based “confirmation” methods . ABO blole in MR . Second,


In the west, survival following treatment of childhood acute lymphoblastic leukaemia (ALL) approaches 90%. Outcomes in India do not exceed 70%. To address this disparity, the Indian Collaborative Childhood Leukaemia group (ICiCLe) developed in 2013 a contemporary treatment protocol for uniform risk-stratified management of first presentation ALL based on cytogenetics and minimal residual disease levels (MRD). A multicentre randomised clinical trial opened in 2016 (ICiCLe-ALL-14) and examines the benefit of randomised interventions to decrease toxicity and improve outcomes.9/L) and no high-risk features. Intermediate risk includes BCP-ALL patients with no high-risk features but are older and have high presentation leucocyte counts and/or bulky disease. High risk includes BCP-ALL patients with any high-risk feature, including high-risk genetics, central nervous system leukaemia, poor prednisolone response at treatment day 8 and high MRD (≥ 0·01%) at the end of induction. Patients with T-lineage ALL constitute the fourth risk group. All patients receive four intensive treatment blocks  followed by 96 weeks of maintenance. Treatment intensity varies by risk group. Clinical data management is based on a web-based remote data capture system. The first randomisation examines the toxicity impact of a shorter induction schedule of prednisolone (3 vs 5 weeks) in young non-high-risk BCP-ALL. The second randomisation examines the survival benefit of substituting doxorubicin with mitoxantrone in delayed intensification for all patients. Primary outcome measures include event-free survival , sepsis rates in induction (first randomisation) and event-free survival rates following second randomisation.Patients 1–18 years with newly diagnosed ALL are categorised into four risk groups based on presentation features, tumour genetics and treatment response. Standard risk includes young (< 10 years) B cell precursor ALL (BCP-ALL) patients with low presentation leucocyte count  The online version contains supplementary material available at 10.1186/s13063-022-06033-1. The order of the items has been modified to group similar items  approach 90% in high-income countries . This isOutcomes in childhood ALL lag behind In India, with survival rates of around ~ 65% –5. The fTo address these issues, five major paediatric oncology centres came together in 2012 to form the Indian Collaborative Childhood Leukaemia (ICiCLe) study group. Geographically, the centres are located in the main metropolises of India, where families often travel to for treatment. The group developed a risk-stratified treatment protocol for children (1–18 years) with newly diagnosed ALL. Patients are categorised into four risk groups: B cell precursor ALL (BCP-ALL) patients with standard (SR), intermediate (IR) and high (HR) risk disease and patients with T-ALL. Age and the white blood cell (WBC) count at presentation collectively determine the National Cancer Institute (NCI) risk groups . All patThe ICiCLe initiative is based on the hypothesis that uniform risk-adapted therapy of paediatric ALL, based on a contemporary treatment protocol and use of standardised investigations of disease genetics and minimal residual disease, will identify patients at lower risk of relapse who require lower-intensity therapy to obtain cure, while intensifying therapy appropriately in patients predicted to be at higher risk of treatment failure. This approach seeks to decrease treatment-related toxicity and deaths, treatment costs and improve outcomes. Uniform standardised treatment at treatment centres located in all four regional zones of the country will enable patients to obtain contemporary treatment more locally, obviating the need for travel to distant centres and alleviating the financial hardship of families.A pre-trial phase was initiated in 2013, providing the opportunity for centres to establish collaborative practice, evaluate the feasibility of uniform protocol-based treatment, enrol and monitor patients, collect and record data, standardise the specialised tests required for risk stratification, develop a remote customised web-based electronic data capture system and obtain funding to run a multi-centre clinical trial. The ICiCLe-ALL-14 randomised trial opened three years later (2016) and is currently underway. The trial includes randomised interventions to decrease toxicity (shorter course of induction prednisolone) and improve survival (mitoxantrone in place of doxorubicin in delayed intensification).Decrease treatment-related toxicity and mortality and improve survival outcomes using a risk-stratified approach to ALL therapy based on disease genetics and levels of minimal residual disease (MRD)Decrease toxicity and mortality in induction by shortening the duration of prednisolone therapy in patients with non-high risk ALLImprove event-free survival (EFS) in risk groups by replacing doxorubicin with mitoxantrone in delayed intensificationStandardisation of risk stratified therapy across participating centres, establishing a standard of care for children with ALL in IndiaImprove overall survival (OS) of children with ALL in IndiaICiCLe-ALL-14 is an investigator-initiated, institution-led, multicentre, open-label, parallel-group randomised, phase III/IV study in children aged 1–18 years with newly diagnosed ALL. Following registration, eligible children are enrolled in the clinical trial after informed consent. Patients are categorised into four risk groups. The initial risk classification is based on lymphoblast lineage, presentation clinical features , leukaemia cytogenetics and prednisolone response at treatment day 8. The final risk stratification is determined at the end of the induction treatment phase and is based on treatment response, including remission status and the level of bone marrow MRD. All risk groups receive sequential blocks of chemotherapy that includes 6–7 months of intensive therapy  and 24 months of maintenance therapy. A web-based remote data entry system (RDES) supports data management, randomisations and study notifications. Parallel-arm 1:1 permuted block randomisation is performed centrally through the RDES and is stratified by trial centre. The first randomisation in induction examines the toxicity impact of a shorter pulsed course of the corticosteroid prednisolone versus the standard 4-week continuous prednisolone schedule in younger patients (< 10 years old) with non-high-risk B cell precursor ALL. The second randomisation examines the survival impact of substituting three doses of the anthracycline doxorubicin with one dose of mitoxantrone during delayed intensification in all risk groups. Trial events include treatment-related deaths, relapses and trial withdrawals . In the absence of events, follow-up is continued for minimum 5 years from diagnosis.The study is conducted at 6 participating sites in 5 hospitals. These centres are major paediatric oncology centres in India, three of which have participated in the previous MCP-841 study . DetailsDiagnosis of ALL confirmed by microscopy and flow cytometry studiesAge ≥ 1 year and ≤ 18 years at the time of enrolmentPreviously untreated patients, with the following exceptionsPrior treatment with prednisolone as sole agent, provided (i) has completed less than 7 days of prednisolone treatment or (ii) if has completed more than 7 days of prednisolone treatment, information on prednisolone response is availablePrior treatment with no more than one dose of vincristine or one dose of intrathecal methotrexate (IT-MTX)Inclusion criteria are evaluated prior to study enrolment, with decision support provided by the RDES. The inclusion criteria are as follows:Previously treated patients who do not meet the criteria as stated abovec-myc rearranged B cell precursor ALLPatients with mature B cell leukaemia or Patients with the Down syndromeMixed phenotype acute leukaemia The exclusion criteria are as follows:Informed consent is obtained from the parents of patients or from authorised surrogates. Assent is obtained in children ≥ 8 years old. Following diagnosis of ALL, patients are registered for study enrolment and treatment is initiated after consent has been obtained for clinical management. All patients receive oral prednisolone alone as treatment for the first 7 days (prednisolone prophase). During this time, patients and families are provided written and verbal information about the clinical trial. Following completion of the 7-day prednisolone prophase, patients undergo initial risk stratification. Consent to participate in the clinical trial is obtained at day 8, or at any time from registration to initial risk stratification. In young patients (Age at diagnosis < 10 years) with initial risk stratification as standard or intermediate risk ALL, consent is also obtained for the first randomisation (R1). The second randomisation (R2) in the delayed intensification phase of treatment is open to all enrolled patients, and informed consent for participation in this randomisation is obtained prior to the start of the delayed intensification treatment phase. Patients / authorised guardians may opt to participate in the study alone, or in either or both randomisations (wherever applicable). Signed consent and assent (where applicable) are obtained by designed clinical staff assigned to this responsibility and designated as such in the trial delegation log. Exemplar consent form and patient information sheets are provided in supplementary data.All patients who consent to participate in the study are also approached for consent for the collection and use of anonymised data relevant to the study objectives. Collection of biological material is not mandated in the study and is specific to each centre. Centres that collect biological samples as part of independent research studies obtain consent separately for the collection and banking of pseudonymised clinical samples as part of peer-reviewed ethics-approved research projects.2/day) either as a pulsed 3-week schedule (days 1–14 and days 22–28) or a continuous 4-week schedule with taper. The second randomisation is in delayed intensification, where all patients are eligible to be randomised to receive either one dose of intravenous mitoxantrone  or 3 doses of intravenous doxorubicin  . The North American Children’s Oncology Group (COG) administers prednisolone at the same dose for 4 weeks, equating to a total 1680 mg/m2. Complications from prolonged corticosteroid treatment include infection, hypertension, myopathy, hyperglycaemia, weight gain, adrenal axis suppression and osteonecrosis. Older children (age ≥ 10 years) appear to be more susceptible to steroid-associated toxicities ; TCF3-HLF) and screening for aneuploidies  by DNA ploidy analysis (flow cytometry) and/or conventional karyotyping. Treatment response is assessed by evaluating the prednisolone response  non-high risk BCP-ALL patients) and decrease rates of relapse . Uniformity of practice across the five major participating paediatric cancer centres enables access to contemporary treatment more locally, decreasing delays in diagnosis and treatment, reducing treatment-related costs and contributing additionally to improved outcomes.Event-free survival, overall and in all risk groups.Event-free survival will be estimated three years from diagnosis and the estimates will be compared with survival outcomes in patients treated in the pre-trial phase. Events include treatment-related deaths (including deaths in induction), relapses and trial withdrawals 2/day, pulsed schedule, days 1-14 and days 22–28) versus the standard induction prednisolone schedule .Incidence rates of severe sepsis (NCI CTCAE grade 3 and higher) and deaths in younger (< 10 years) non-high risk BCP-ALL patients randomised to receive a shorter induction course of prednisolone  versus the standard 3 doses of doxorubicin  in delayed intensification. Event-free survival will be estimated at 3 years from randomisation.Event-free survival in patients randomised to receive 1 dose of mitoxantrone , overall, by treatment phase, by risk groups and by first and second randomisationsProportion of events including treatment-related deaths, relapse and trial withdrawal , overall, by treatment phase, within risk groups and by randomisationsOverall survival, 3 years from diagnosis, in all patients, by risk groups and by randomisationsAnalysis of variations in patient and disease characteristics, treatment response, treatment-related toxicities and deaths, event rates and survival outcomes among participating centres, as a representation of geographical variations in patient populations and disease featuresAnalysis of cumulative incidence of relapse and long-term survival outcomes (at a median 5 years from diagnosis) to examine patterns of relapse and late treatment-related effectsThe ICiCLe-ALL-14 protocol follows the SPIRIT guidelines for interventional trials . Figure General remarks2.First randomisationSample size determinations for the randomised interventions have been powered to observe a clinically meaningful difference of 5% or greater with the experimental treatments. An extended pre-trial pilot at participating centres indicated that loss to follow-up is uncommon (less than 5%), and this has therefore not been factored into the estimations of sample size.3.Second randomisationAn estimated 50% of enrolled patients will be eligible for the first randomisation. At an estimated baseline rate of 39 ± 2% for severe infection-related toxicity in induction and after accounting for drop-outs and refusal to participate (< 5%), a projected enrolment of 3056 patients over an accrual period of 4–5 years is estimated to provide the required sample size, (764 patients in each arm) to detect a 7% difference in rates of severe infection (grades 3 and higher) between the randomised arms, with an alpha error of 5% and at a power of 80%.An estimated 20% of enrolled patients will experience an event prior to entering the delayed intensification phase and will not be eligible for the second randomisation. At an estimated baseline 3-year EFS estimate of 70% and after accounting for randomisation drop-outs and refusal to participate (< 5%), a projected enrolment of 2004 patients (1002 patients in each arm) over an accrual period of 4–5 years will provide the required sample size to detect a 6% difference in event-free survival between the randomised groups, with an alpha error of 5% and at a power of 80%.Within the context of the clinical trial, a 5% difference is taken to be clinically significant. The targeted recruitment numbers are powered to detect this difference.The standard arms of the trial represent standard-of care interventions, minimising the probability of consent refusal. Participating centres have well-established arrangements to provide material and financial support for patients and families, resulting in low rates of treatment abandonment and loss to follow-up. The pre-trial phase additionally provided the opportunity for study centres to strengthen processes for study enrolment and monitoring of patients. The experience gained through the pre-trial phase at study centres has also resulted in low refusal rates for participation in the randomised interventions (≤ 5%).The study uses a permuted block randomisation design with variable block sizes and 1:1 allocation, stratified by treatment centre. Randomisation is performed centrally through the secure web-based RDES. The first (R1) randomisation is performed on treatment day 8 and involves an open label two-arm randomised design comparing experimental arm R1B  against standard arm R1A (4 weeks of induction prednisolone as a continuous schedule followed by taper) in younger (< 10 years) non-high risk BCP-ALL patients. The second open-label randomisation (R2) is performed in delayed intensification and compares 1 dose of mitoxantrone  against 3 doses of doxorubicin (standard arm R2A) in all risk groups.Concealment is achieved by randomisation allocations through the RDES.The entire process from enrolment to assignment of randomisation in the different intervention arms is performed by the web-based RDES.ICiCLe-ALL-14 is an open label study. While participants and clinicians will be aware of what treatment is received, the data centre responsible for analyses of the trial is blinded to the actual allocation. Randomisation allocation is done through the RDES and is visible to the centre only at the time of randomisation. This is recorded in the database visible to the trial centre as R1A/B and R2A/B.The randomised data will be unblinded once recruitment is complete. Alternatively, if the trial statistician reports a significant difference in events between the two arms, accepted by the DSMC, then the data will be unblinded.All trial and treatment-related data are recorded in electronic case report forms (e-CRFs) against unique patient trial numbers. The web-based RDES allows trial registration, enrolment and randomisation in real-time and contemporaneous recording of toxicities and events. Staff at each centre have been trained to use the RDES for trial data management. Data queries raised by the RDES are addressed jointly by the coordinating trials unit and participating trial centres. The coordinating trials unit also organises regular database trawls to evaluate the quality and completeness of data.Trial centres have developed institution-specific approaches to monitor and promote adherence of patients to treatment and follow-up . These pAll data are recorded electronically by centres. To verify accuracy of the data, range, validity and consistency checks are performed automatically by the database. Implausible or missing data are corrected or added only after consulting trial investigators, and all corrections are documented. The database will be closed after termination of the study and following completion of all entries with appropriate documentation of the process.Data from each patient is recorded under a unique identifier number instead of patient name so that patient identity remains undisclosed and confidentiality is maintained.This activity is not part of the clinical trial.p values less than 0·05 will be considered significant. Randomised interventions will be analysed primarily as modified intention-to-treat (modified to exclude ineligible patients who were randomised). Secondary analyses will include as-treated  and per-protocol  approaches. These secondary analyses will be performed as part of sensitivity analysis to examine the influence of protocol deviations on study observations, and in the case of as-treated analyses, to evaluate treatment-related toxicities. Cox regression analyses of potential determinants of survival outcomes will be accompanied by tests of the proportional hazards assumption. Poisson regression analysis will be accompanied by testing for dispersion.Two-sided tests of significance will be used in all analyses. Unless specified, For the trial cohort: event-free survival at 3 years from diagnosisPrimary outcomes measures include the following:2.For the first randomisation: Infection and deaths in inductionThe Kaplan-Meier method will be used to estimate EFS and to plot survival curves. Diagnosis will be from time of trial registration. Events include treatment-related death, relapse and trial withdrawal . EFS will be estimated for the entire cohort and will be stratified by risk group. Survival estimates between groups will be compared by the log-rank test. The influence of risk variables on EFS outcomes will be examined using Cox regression. Risk variables will include patient characteristics , disease features , treatment response  and treatment centre.3.For the second randomisation: EFS at 3 years from second randomisationRates of severe infection (NCI CTCAE Grade 3 and higher) and deaths in induction will be used as measures of steroid-related toxicity during the induction treatment phase. These will be examined separately  and as a composite endpoint. Incidence rates between the randomised arms will be compared using the Fisher exact test. Association with potential risk variables  will be examined by Poisson regression.The Kaplan-Meier method will be used to estimate EFS and to plot survival curves. EFS will be estimated for all randomised patients and within risk groups. EFS estimates will be compared using the log-rank test. A Cox regression model will be used to examine the influence of risk variables (as outlined above) on EFS outcomes. The influence of the randomised intervention on the risk of relapse and treatment-related death will be examined using a competing-risks model (Fine-Gray), treating relapse and treatment-related death as competing events. Cumulative incidence plots of relapse and treatment-related death will be compared using the Gray test.Treatment responseSecondary outcome measures include the following:2.Treatment-related toxicityThe proportion of patients with good prednisolone response; complete remission at end of induction; low levels of MRD at end of induction; and non-remission at end of consolidation will be reported for all patients, within risk groups and by first randomisation. The Fisher exact test will be used to compare proportions. Logistic regression will be used to examine the influence of presentation risk factors  on measures of treatment response (induction remission and MRD levels at end of induction).3.Trial eventsTreatment-related toxicity includes severe non-fatal (NCI CTCAE grades 3–4) and fatal toxicities, consequent to infection or otherwise. Recurring non-infection treatment-related toxicities of interest include complications associated with corticosteroid, vincristine and L-asparaginase treatment and select organ-specific toxicities . Incidence rates of severe treatment-related toxicities  will be examined for each treatment phase, stratified by risk group, and by second randomisation. The Fisher exact test will be used to compare toxicity rates. The influence of potential risk variables (as outlined above) on incidence rates of toxicity will be examined using Poisson regression.4.Overall survivalTreatment-related death, relapse and trial withdrawal  are recorded as events. Patients are withdrawn from the trial when managed off-protocol  and when non-adherent to treatment . Proportion of events overall and for each of the three categories will be reported for the entire trial cohort, within risk groups, by randomisations and by treatment centres. Proportions will be compared by the Fisher exact test.Estimated using the Kaplan-Meier method at 3 years from diagnosis, for the entire cohort, stratified by risk groups, second randomisation and by treatment centre. The log rank test will be used to compare survival estimates between groups.p value of 0·001 or less on the Fisher exact test. Event-free survival following second randomisation will also be analysed although here, the number of events will be insufficient to observe a treatment effect and will require the hazard ratio from Cox regression analysis to have a significance level of < 0·00034 to trigger consideration of early termination of the second randomisation.A single interim analysis is planned 4 years from start of enrolment, when a minimum 30% of events is expected in enrolled patients. The duration of treatment is 2·5 years. As the bulk of relapses occurs ~ 6 months or more following completion of treatment, the major outcome measure at the interim analysis timepoint will be estimation of treatment-related deaths overall and between the randomised arms. The interim analysis will examine the incidence rate of treatment-related deaths and severe non-fatal toxicities between the randomised interventions and determine whether the observed difference exceeds or is within the boundary of tolerable differences on a two-sided Fisher exact test. The boundary of tolerable difference is estimated at 3 standard deviations of the incidence rate overall for treatment-related deaths and severe non-fatal toxicities; surpassing this boundary will be indicated by a Patterns of treatment failure following remission-inductionThe following additional analyses will be performed:very early within 18 months of diagnosis, early between 18 months from diagnosis to within 6 months from end of treatment, late more than 6 months from end of treatment) will be reported as proportions overall, within risk groups and by second randomisations. The Fisher exact test will be used to compare proportions.2.Influence of select covariates on survival outcomesThe cumulative incidence of relapse will be examined overall, in risk groups and by treatment centre using a competing-risks model (Fine-Gray), with treatment-related death and trial withdrawal as competing risks. Cumulative incidence curves will be compared using the Gray test. Site of relapse (any bone marrow versus non-marrow sites) and timing of relapse  and cytogenetic subtypes  on survival outcomes will be examined by Cox regression.4.Analysis of steroid-related weight gain in inductionThe first and second randomisations will combine to generate four arms . The Kaplan-Meier method will be used to determine estimates of EFS in all four arms and the findings will be compared by the log-rank test.z-score and z-score categories  using standard age- and sex-matched reference growth charts. Aggregate percentage changes in median weight, weight percentile, z-score and z-score categories will be determined for each risk group and stratified by first randomisation. Changes among groups will be compared by one-way analysis of variance.5.Treatment delays and relapseFor each patient, changes in weight and body mass index (BMI) will be determined prior to treatment (baseline) and at the end of induction. Weight and BMI values will be reported as percentile, 6.Long-term survival outcomesDelays in treatment during the intensive treatment phase (induction to delayed intensification), the maintenance phase and for the entire duration of chemotherapy will be determined for each patient. Logistic regression will be used to examine the influence of treatment delay on remission status.Estimates of event-free and overall survival at a median 60 months from diagnosis will be examined using the Kaplan-Meier method to examine late relapses and late treatment effects. The association of risk variables on survival outcomes, including findings from biological sub-studies  will be analysed using Cox regression.Robust measures are in place to ensure completeness of data elements critical for analyses of primary and secondary outcomes. The data flow from case report forms in the electronic data capture system ensures capture of all relevant information required for diagnosis, risk stratification, drug treatment, toxicity and treatment response. Completion of data entry in these forms is necessary to progress through trial registration, enrolment, risk stratification and randomisation. Data in the RDES is reviewed, cleaned and updated periodically, both as part of regular data management and in the course of preparing 6-monthly trial reports for review by the data and safety monitoring committee. The objective is to ensure less than 5% missingness in data. For the randomised interventions, the robustness of observations from the primary modified intention-to-treat analysis will be examined using per-protocol and as-treated approaches as secondary analyses. Measures for handling missing data may be required for the exploratory analyses (e.g. association of cytogenetic subtypes with EFS outcomes) and will be addressed using multivariate imputation by chained equations (MICE), assuming data to be missing at random (MAR). For a given variable, missing data will be imputed randomly using the appropriate regression model and iterated to create multiple datasets with imputed values, followed by a pooled estimate derived from statistical analyses performed on each of these imputed datasets.Immediately following publication of the results of the study and on reasonable request to the corresponding author, the following information will be made available and will be accessed from the institutional server at the coordinating trial centre: the latest version of the complete trial protocol, the dataset related to the reported study results with appropriate de-identification of study participants, and the accompanying statistical analysis plan.The organisational structure of the trial is shown in Fig. The independent data and safety monitoring committee (DSMC) includes two international clinical trialists and a statistician with expertise in collaborative multicentre trials in childhood acute lymphoblastic leukaemia. The DSMC receives 6-monthly updates on trial enrolment and randomisation, data recording status, trial events, treatment-related toxicity and serious adverse events (SAE). The trial recruitment committee and the coordinating clinical trials unit responsible for analysing data are blinded to the randomisation allocations. The role of the DSMC is to review data produced by the clinical trials unit, comment on the observations, request additional information, make recommendations regarding the trial and data collection and report back to the trial coordinating centre and the institutional review boards on their observations and recommendations. Based on the periodic trial reports, the DSMC may advise continuation of the trial, scheduling of an early interim analysis, trial modification, closure of the randomisation or closure of the trial. The trial management committee will then take a decision based on these recommendations and report to the institutional review boards.https://evs.nci.nih.gov/ftp1/CTCAE/CTCAE_4.03/) has been used to grade toxicity. Trial specific toxicity data collection is based on a priori knowledge of known toxicities that are expected with the administration of the protocol drugs at each phase. Specific CTCAE grade 3–5 toxicities (listed in Supplementary Table The common terminology criteria for adverse events (NCI CTCAE) version 4.03  guidelines for clinical trials and adheres to institutional procedural standards for conduct of clinical trials. The monitor verifies that all adverse events are documented appropriately and are consistent with protocol definitions; reviews the source  documents and determines whether the data reported in the RDES are complete and accurate. The monitor confirms that the regulatory binder is complete and that all associated documents are up to date. The monitor also advises centres on measures to ensure adherence to ICH-GCP guidelines. At the end of each visit, the monitor shares a report of identified deficiencies and assists the site in resolving these issues.Protocol amendments are reviewed by the trial management committee. The clinical trials unit then submits to the institutional review board of the coordinating centre, an amended protocol version bearing a new version number that contains the tracked changes accompanied by a cover letter listing the changes in the protocol and their rationale. Once approved, the amended protocol version is shared with participating centres for approval by the respective institutional review boards. The amended version is then adopted for use at centres and recorded as the version in use in the trial master file; earlier versions of the protocol are then removed from use and archived.The decision to publish results of the trial will be taken by the trial management committee. Papers will be produced by a writing group and approved by the trial management committee prior to publication. The study outcomes will be circulated to all participating centres and presented to the community regardless of the magnitude or direction of the results.ICiCLe-ALL-14 is the first risk-stratified multi-centre randomised clinical trial in ALL in India. The benefits include modernisation and standardisation of ALL diagnosis and treatment across the major Indian paediatric oncology centres. The resulting uniformity in care serves to reassure patients and families that they will receive the best available standard of treatment irrespective of the treatment centre they choose to travel to. Furthermore, for patients and families who relocate to continue care at the cancer centre closest to home, the transfer of care would be seamless. A uniform treatment protocol also enables specialty centres to develop shared care arrangements with smaller centres. Contemporaneous recording of information using the RDES has enabled capture of high-quality study data. The sharing of knowledge and experience through the multicentre collaboration has allowed continuous refinement of clinical management through sharing of best practice, improving the quality of care at all centres using an evidence-based approach. The risk stratification and treatment strategies have been designed to reduce morbidity associated with treatment and to facilitate outpatient management, decreasing the burden of treatment for patients and families. At all centres, financial support for hospitalisation, treatment, travel and residential stay are facilitated by a number of government and non-governmental agencies. These measures have been shown to reduce treatment abandonment in low-middle income countries –35. Our The trial seeks to improve outcomes in childhood ALL in India. There are a number of limitations. Trial eligibility may favour enrolment of patients with better outcomes and may not reflect real-world experience. Absence of centralised standardisation of genetic and MRD testing results in inconsistencies in risk stratification across centres. Treatment centres also vary by catchment areas, hospital accessibility and inpatient capacity, resulting in variations in treatment practice that potentially influence the outcomes of acute treatment-related toxicities such as sepsis. Finally, the quality and availability of key chemotherapy drugs are variable. In the absence of therapeutic drug monitoring, this variability in drug quality may result in suboptimal dosing or excessive drug toxicity.The trial is underway. Study recruitment began on 24 October 2016 and is projected to be completed on 31 March 2022. As of 10 December 2021, 2301 patients have been enrolled in the trial. The current approved version of the trial protocol is version 5.1 .Additional file 1: Supplementary Table 1. List of centres participating in the ICiCLe-ALL-14 trial. Supplementary Table 2. The Indian Collaborative Childhood Leukaemia (ICiCLe) study group protocol for risk-stratified treatment of patients aged 1-18 years with first diagnosis of acute lymphoblastic leukaemia (ALL). Supplementary Table 3. SPIRIT item 3. Supplementary Figure 1. Schema of randomisation in the ICiCLe-ALL-14 protocol.


Different polymorphisms of the catechol-O-methyltransferase (COMT) gene affect the COMT enzyme activity. The COMT enzyme plays a major role in the pathophysiology of various neurological and psychiatric disorders. This review article aims to discuss what recent research has discovered about the association of COMT genotype polymorphism with neurological and psychiatric disorders and the scope for the knowledge to be applied for advancement in therapeutics. We searched PubMed and Google Scholar databases and found 1656 articles. We included observational studies, clinical trials, and meta-analyses in the English language published between 2019 and 2021. We screened the articles based on the title and the abstract and found 26 relevant articles. Diseases or conditions studied primarily were schizophrenia, Parkinson’s disease, Alzheimer’s disease, substance use, and depression. This article highlights how genetics influences the susceptibility of an individual to neurological and psychiatric diseases and the variations in the specific symptoms of those diseases. The review showed that the variability in individual response to therapeutic interventions stems from the gene level. This knowledge can contribute towards the dawn of a new era of personalized medicine. Globally, there is a great burden of neurological and mental disorders. In 2005, neurological disorders contributed to 92 million disability-adjusted life years (DALYs), and this number is projected to rise by around 12% to 103 million in 2030, according to a report by the World Health Organization (WHO). Alzheimer’s disease and other dementias are expected to increase by 66% from the year 2005 to 2030. In 2005, out of the total global burden of disease, neurological disorders contributed to 10.9% in high-income countries, 6.7% in upper-middle, 8.7% in lower-middle, and 4.5% in low-income countries. Years of healthy life lost as a result of disability (YLDs) associated with Alzheimer’s disease and other dementias are expected to rise by 38% in 2030 [Catechol-O-methyltransferase (COMT) is an enzyme that catalyzes the methylation of catechol substrates during the metabolism of catecholamines (mainly norepinephrine and epinephrine) within the body, as shown in Figure A methyl group from S-adenosyl-L-methionine (SAM) is transferred to a catechol substrate with the help of COMT and Mg2+. O-methylated catechol and S-adenosyl-L-homocysteine (SAH) are formed as by-products of this reaction. COMT is an intracellular enzyme that has two isoforms - soluble COMT (S-COMT), which is soluble in the cytoplasm, and membrane-bound COMT (MB-COMT), which is associated with membranes ,4. COMT The association between COMT genotype polymorphism with neurological and psychiatric disorders has been actively researched in the last few decades. A recent meta-analysis comprehensively studied the association between COMT Val158Met genotype and psychiatric disorders . A few nWe searched PubMed and Google Scholar databases using the keywords ‘catechol-O-methyltransferase, ‘COMT’, ‘COMT genotype’, ‘polymorphism’, ‘neurological disorders’, ‘psychiatric disorders’, and ‘mental health disorders’ and found a total of 1656 articles. We included observational studies, clinical trials, and meta-analysis studies in the English language published between 2019 and 2021. We excluded animal studies, gray literature, and all studies involving subjects below 18 years of age. After screening articles with the help of titles and abstracts, we ended up with 26 articles that were relevant to our research question. Out of these, two studies were clinical trials, 23 articles were observational studies, and one article was a meta-analysis. Out of the total number, 17 studies, including 8638 subjects, explored the association between COMT genotype polymorphism and neurological and psychiatric disorders, and nine studies were drug-based or pharmacogenetic studies that included a total of 5115 subjects. Diseases or conditions studied primarily were schizophrenia, Parkinson’s disease, Alzheimer’s disease, substance use, and depression.Variants of COMT genotype have been extensively studied in association with various neurological and psychiatric disorders. Additionally, much focus has been seen on COMT gene variants and cognitive function. In the last few years, scientists have embarked on a journey to discover more about this association with respect to newer concepts in various neurological and psychiatric diseases and how their findings translate to advancement in therapeutic strategies moving towards personalized medicine.Association of catechol-O-methyltransferase genotype polymorphism with psychiatric disordersIt has been long established that the dopaminergic system is involved in the pathogenesis of schizophrenia. COMT enzyme takes part in the dopamine degradation pathway and plays a vital role in schizophrenia. In the last few decades, several studies have shown an association between schizophrenia and COMT genotype polymorphisms. Recently, researchers have undertaken studies involving schizophrenia patients and COMT genotype variants, associating them with newer concepts. In 2021, a study was conducted to assess the effect of interaction between genotype polymorphisms of COMT  and IL-10 (IL-10 -592A/C or rs1800872) on cognition in 244 patients with chronic schizophrenia and in 396 healthy controls. The study found that IL-10 did not have any effect on cognition if measured alone; however, COMT alone had an impact on language and schizophrenia. Additionally, the study confirmed more significant interactive effects of genotypes of COMT and IL-10 on cognition in schizophrenia patients than in controls. The study revealed that the findings could be valuable for further discussion about the interactive effects of different systems on cognition in schizophrenia patients as well as for drug administration . AnotherThere are multiple phenotypes of heroin use disorder, which might be associated with COMT genetic polymorphism. In a study done in 2021, 801 heroin users were included and divided into groups with four different phenotypes. The findings of the study suggested that subjects having the G (guanine) allele of rs769224 COMT variant were prone to consuming higher dosages of heroin every day and concluded that the findings could be helpful in the precise treatment of heroin use disorder . A similIn 2021, a study was done on 329 subjects from Lithuania that assessed the effect of Ankyrin Repeat and Kinase Domain Containing 1 - Dopamine Receptor D2 complex (ANKK1-DRD2) and COMT SNP on the risk of alcohol abuse. Having both genetic polymorphisms of COMT and ANKK1-DRD2 was associated with an elevated risk of hazardous use of alcohol . AnotherMethamphetamine increases dopamine levels in the prefrontal cortex, and its dependence affects executive function (EF) in individuals. In 2020, a study was done to assess how the different COMT genotypes alter the effects of methamphetamine dependence on EF. The study recruited 75 men with methamphetamine dependence (METH+) and 47 men with no dependence (METH-) and checked their cerebrospinal fluid (CSF) levels of dopamine and its metabolites. Lower dopamine levels were found in Met/Met METH+ men with a worse performance of EF. Among METH- men with Met/Met, the highest dopamine levels were seen, and these individuals performed EF better than Val/Met and Val/Val variants. It was concluded that slow clearance of dopamine worsens dopamine dysregulation associated with methamphetamine . A similTable Association of catechol-O-methyltransferase genotype polymorphism with neurological disordersDopamine plays a role in the pathophysiology of Parkinson's disease, and the COMT enzyme degrades dopamine. A study done in 2020 stated that the Val(158)Met variant of the COMT gene has recently been associated with a decline in cognition in Parkinson’s disease (PD). The study assessed the gray matter volume (GMV) in 120 PD patients with Val(158)Val variant of the COMT gene who had preserved cognition and found a widespread reduction in the GMV with atrophy in fronto-subcortical as well as the parieto-temporal regions of the cerebrum. A four-year follow-up showed cognitive decline associated with some of these regions and the study concluded that PD patients with a reduced GMV and a Val homozygous genotype are predisposed to a decline in cognition . These sThe Val(158)Met (rs4680) variant of the COMT gene has been associated with Alzheimer’s disease (AD). In a research study conducted in 2020, scientists assessed the association of this variant with the levels of cerebrospinal fluid (CSF) biomarkers of AD in 233 subjects. Amyloid-β42 (Aβ42) levels were significantly decreased in AD patients with GG in comparison to the AG COMT Val158Met variant. The levels of t-tau and p-tau181 were found to be increased in AD patients with AA (adenine-adenine) in comparison to the AG (adenine-guanine) COMT Val158Met genotype. The study concluded that the COMT Val158Met genotype could be investigated as a genetic marker of AD . This stPharmacogenetic studies on the effect of COMT genotype polymorphism in neurological and psychiatric disordersAripiprazole is an atypical antipsychotic drug used in the treatment of schizophrenia. In a research study done in 2021, 98 patients with recent-onset schizophrenia were administered aripiprazole long-acting injectable (LAI) for three months, and genetic polymorphism of COMT along with two other genes was determined. Symptom severity was assessed, and it was found that usage of aripiprazole LAI improved cognitive functions. COMT Met/Met genotype and COMT interaction with methylenetetrahydrofolate reductase (MTHFR) gene were found to have a positive association with attention and executive functioning. The study concluded that COMT has the potential to be a biomarker of cognition in schizophrenic patients . A longiA study conducted in 2020 investigated the association of gene polymorphisms with motor levodopa-induced complications (MLIC) in Parkinson’s Disease (PD). The study recruited 133 subjects and genotyped them for brain-derived neurotrophic factor (BDNF), dopamine transporter (DAT), and COMT genes. The study found a positive association between a combination of AG (adenine-guanine) BDNF, AG (adenine-guanine) DAT, and GG (guanine-guanine) COMT genotypes with MLIC and concluded that genetic biomarkers could help determine which PD patients are more prone to the long-term side effects of therapy with levodopa . Most ofPatients have been found to show varied responses to the same antidepressive treatment. A meta-analysis was done in 2020 that included 11 studies involving 2845 subjects studied the association of COMT rs4680 variant with antidepressive treatment response and found that patients with the G allele of the COMT rs4680 gene responded better to electroconvulsive therapy (ECT). COMT rs4680 variant was significantly associated with antidepressive treatment, but this association varied amongst the individual studies. Patients with the GG or AG + GG variants responded better to ECT than patients with the AA (adenine-adenine) genotype. Only a small number of studies used ECT, and the authors saw this as a limitation of the study, which prompted them to suggest the need for further research to verify these findings . A randoMethadone is a drug used for maintenance treatment in patients dependent on opioids to reduce withdrawal symptoms. A study in 2020 investigated the association of COMT genotype variants with response to methadone maintenance treatment (MMT) in 820 Chinese opioid-dependent patients. Three polymorphisms of COMT were genotyped. The study found that patients with the TC (thymine-cytosine) or CC (cytosine-cytosine) genotypes of rs933271 variant had a higher chance of responding to MMT than patients with TT (thymine-thymine) allelic variant and the other two genotypes of COMT - rs4680 and rs737866 did not have an association with MMT response. These results could shed new light on methadone treatment in individuals and their sensitivity to methadone treatment, thus paving the way for a more effective therapeutic approach. However, the study lacked an assessment of multiple gene interactions and acknowledged the possibility of coexistence of more than one mental disorder . FurtherThis review focused on the association of the various COMT genotype polymorphisms in neurological and psychiatric disorders, emphasizing its therapeutic implications, especially towards personalized medicine. We have explored how the susceptibility to neurological and psychiatric diseases, their specific symptoms, and therapeutic interventions is dependent on genetics. In schizophrenia patients, significant interactive effects of genotypes of COMT and IL-10 were seen, and the COMT rs4680 variant was associated with tardive dyskinesia. COMT gene polymorphism influenced working memory in Parkinson’s disease. Individuals with the Met/Met variant were more likely to use opioids than those with the Val/Met variant of the COMT gene. Having both genetic polymorphisms of COMT and ANKK1-DRD2 was associated with an elevated risk of hazardous use of alcohol. We also reviewed several pharmacogenetic studies. A significant therapeutic response to olanzapine was found in schizophrenia patients with the COMT rs4680 A allele and rs4680-rs4818 CA haplotype. COMT rs4680 variant was found to be significantly associated with antidepressive treatment. Patients with the TC or CC genotypes of rs933271 variant had a higher chance of responding to methadone maintenance treatment among opioid-dependent patients. These findings prove that there is a huge variation in individual response to disease pathophysiology and therapeutic strategies based on genetic polymorphisms, which paves the way for personalized medicine. It is a well-known fact that the prognosis of various neurological and psychiatric disorders is poor. Focusing on targeted therapeutic strategies can improve the quality of life of patients and decrease the cost of care of patients. Most of the studies we included in this review were newer observational studies with small sample sizes, and we also excluded studies with subjects below the age of 18. We recommend future researchers conduct more randomized control trials (RCTs) to investigate the therapeutic role of COMT genotype polymorphism in neurological and psychiatric disorders.