Mucosal Eosinophil Abundance in Non-Inflamed Colonic Tissue Is Associated with Response to Vedolizumab Induction Therapy in Inflammatory Bowel Disease.

Vedolizumab is used as a treatment for patients with inflammatory bowel disease (IBD), but induction therapy leads to clinical response and remission in approximately 55% and 30% of patients with IBD, respectively. In this study, we aimed to explore the predictive value of mucosal eosinophils and serum eotaxin-1 regarding response to vedolizumab induction therapy. Eighty-four (84) patients with IBD (37 Crohn's disease [CD], 47 ulcerative colitis [UC]) were included. For 24 patients with IBD, histopathology was assessed for eosinophil counts in non-inflamed colonic tissue prior to vedolizumab treatment. For 64 patients with IBD, serum eotaxin-1 levels were quantified prior to (baseline) and during vedolizumab treatment. Serum samples of 100 patients with IBD (34 CD, 66 UC) from the GEMINI 1 and 2 trials were used for external validation. Baseline mucosal eosinophil numbers in non-inflamed colonic tissue were significantly higher in responders to vedolizumab induction therapy when compared to primary non-responders (69 [34−138] vs. 24 [18−28] eosinophils/high-power field, respectively, p < 0.01). Baseline serum eotaxin-1 levels in the discovery cohort were significantly elevated in responders, compared to primary non-responders (0.33 [0.23−0.44] vs. 0.20 [0.16−0.29] ng/mL, p < 0.01). Prediction models based on mucosal eosinophil counts and serum eotaxin-1 showed an area under the curve (AUC) of 0.90 and 0.79, respectively. However, the predictive capacity of baseline serum eotaxin-1 levels could not be validated in the GEMINI cohort. Mucosal eosinophil abundance in non-inflamed colonic tissue was associated with response to vedolizumab induction therapy in patients with IBD. Future studies are warranted to further validate the potential value of mucosal eosinophils and serum eotaxin-1 as biomarkers for response to vedolizumab therapy.

Sapanisertib plus Fulvestrant in Postmenopausal Women with Estrogen Receptor-Positive/HER2-Negative Advanced Breast Cancer after Progression on Aromatase Inhibitor.

PURPOSE: This phase II study investigated daily or weekly sapanisertib (a selective dual inhibitor of mTOR complexes 1 and 2) in combination with fulvestrant. PATIENTS AND METHODS: Postmenopausal women with estrogen receptor-positive (ER+)/HER2-negative (HER2-) advanced or metastatic breast cancer following progression during/after aromatase inhibitor treatment were randomized to receive fulvestrant 500 mg (28-day treatment cycles), fulvestrant plus sapanisertib 4 mg daily, or fulvestrant plus sapanisertib 30 mg weekly, until progressive disease, unacceptable toxicity, consent withdrawal, or study completion. RESULTS: Among 141 enrolled patients, baseline characteristics were balanced among treatment arms, including prior cyclin-dependent kinase-4/6 (CDK4/6) inhibitor treatment in 33% to 35% of patients. Median progression-free survival (PFS; primary endpoint) was 3.5 months in the single-agent fulvestrant arm, compared with 7.2 months for fulvestrant plus sapanisertib daily [HR, 0.77; 95% confidence interval (CI), 0.47-1.26] and 5.6 months for fulvestrant plus sapanisertib weekly (HR, 0.88; 95% CI, 0.53-1.45). The greatest PFS benefits were seen in patients who had previously received CDK4/6 inhibitors. The most common adverse events were nausea, vomiting, and hyperglycemia, all occurring more frequently in the combination therapy arms. Treatment discontinuation due to adverse events occurred more frequently in the two combination therapy arms than with single-agent fulvestrant (32% and 36% vs. 4%, respectively). CONCLUSIONS: Fulvestrant plus sapanisertib daily/weekly resulted in numerically longer PFS in patients with ER+/HER2- advanced or metastatic breast cancer, compared with single-agent fulvestrant. The combination was associated with increased toxicity. Further development of sapanisertib using these dosing schedules in this setting is not supported by these data.

Sapanisertib Plus Exemestane or Fulvestrant in Women with Hormone Receptor-Positive/HER2-Negative Advanced or Metastatic Breast Cancer.

PURPOSE: This open-label, multicenter, phase IB/II study evaluated sapanisertib, a dual inhibitor of mTOR kinase complexes 1/2, plus exemestane or fulvestrant in postmenopausal women with hormone receptor-positive (HR+)/HER2-negative (HER2-) advanced/metastatic breast cancer. PATIENTS AND METHODS: Eligible patients had previously progressed on everolimus with exemestane/fulvestrant and received ≤3 (phase IB) or ≤1 (phase II) prior chemotherapy regimens. Patients received sapanisertib 3 to 5 mg every day (phase IB), or 4 mg every day (phase II) with exemestane 25 mg every day or fulvestrant 500 mg monthly in 28-day cycles. Phase II enrolled parallel cohorts based on prior response to everolimus. The primary objective of phase II was to evaluate antitumor activity by clinical benefit rate at 16 weeks (CBR-16). RESULTS: Overall, 118 patients enrolled in phase IB (n = 24) and II (n = 94). Five patients in phase IB experienced dose-limiting toxicities, at sapanisertib doses of 5 mg every day (n = 4) and 4 mg every day (n = 1); sapanisertib 4 mg every day was the MTD in combination with exemestane or fulvestrant. In phase II, in everolimus-sensitive versus everolimus-resistant cohorts, CBR-16 was 45% versus 23%, and overall response rate was 8% versus 2%, respectively. The most common adverse events were nausea (52%), fatigue (47%), diarrhea (37%), and hyperglycemia (33%); rash occurred in 17% of patients. Molecular analysis suggested positive association between AKT1 mutation status and best treatment response (complete + partial response; P = 0.0262). CONCLUSIONS: Sapanisertib plus exemestane or fulvestrant was well tolerated and exhibited clinical benefit in postmenopausal women with pretreated everolimus-sensitive or everolimus-resistant breast cancer.

Evaluating Responses to Gluten Challenge: A Randomized, Double-Blind, 2-Dose Gluten Challenge Trial.

BACKGROUND & AIMS: Gluten challenge is used to diagnose celiac disease (CeD) and for clinical research. Sustained gluten exposure reliably induces histologic changes but is burdensome. We investigated the relative abilities of multiple biomarkers to assess disease activity induced by 2 gluten doses, and aimed to identify biomarkers to supplement or replace histology. METHODS: In this randomized, double-blind, 2-dose gluten-challenge trial conducted in 2 US centers (Boston, MA), 14 adults with biopsy-proven CeD were randomized to 3 g or 10 g gluten/d for 14 days. The study was powered to detect changes in villous height to crypt depth, and stopped at planned interim analysis on reaching this end point. Additional end points included gluten-specific cluster of differentiation (CD)4 T-cell analysis with HLA-DQ2-gluten tetramers and enzyme-linked immune absorbent spot, gut-homing CD8 T cells, interleukin-2, symptoms, video capsule endoscopy, intraepithelial leukocytes, and tissue multiplex immunofluorescence. RESULTS: All assessments showed changes with gluten challenge. However, time to maximal change, change magnitude, and gluten dose-response relationship varied. Villous height to crypt depth, video capsule endoscopy enteropathy score, enzyme-linked immune absorbent spot, gut-homing CD8 T cells, intraepithelial leukocyte counts, and HLA-DQ2-restricted gluten-specific CD4 T cells showed significant changes from baseline at 10 g gluten only; symptoms were significant at 3 g. Symptoms and plasma interleukin-2 levels increased significantly or near significantly at both doses. Interleukin-2 appeared to be the earliest, most sensitive marker of acute gluten exposure. CONCLUSIONS: Modern biomarkers are sensitive and responsive to gluten exposure, potentially allowing less invasive, lower-dose, shorter-duration gluten ingestion. This work provides a preliminary framework for rational design of gluten challenge for CeD research. ClinicalTrials.gov number, NCT03409796.

Estimating cross-population genetic correlations of causal effect sizes.

Recent studies have examined the genetic correlations of single-nucleotide polymorphism (SNP) effect sizes across pairs of populations to better understand the genetic architectures of complex traits. These studies have estimated ρ g , the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of ρ g depends both on the cross-population correlation of true causal effect sizes ( ρ b ) and on the similarity in linkage disequilibrium (LD) patterns in the two populations, which drive tagging effects. Here, we derive the value of the ratio ρ g / ρ b as a function of LD in each population. By applying existing methods to obtain estimates of ρ g , we can use this ratio to estimate ρ b . Our estimates of ρ b were equal to 0.55 ( SE = 0.14) between Europeans and East Asians averaged across nine traits in the Genetic Epidemiology Research on Adult Health and Aging data set, 0.54 ( SE = 0.18) between Europeans and South Asians averaged across 13 traits in the UK Biobank data set, and 0.48 ( SE = 0.06) and 0.65 ( SE = 0.09) between Europeans and East Asians in summary statistic data sets for type 2 diabetes and rheumatoid arthritis, respectively. These results implicate substantially different causal genetic architectures across continental populations.

Population Structure of UK Biobank and Ancient Eurasians Reveals Adaptation at Genes Influencing Blood Pressure.

Analyzing genetic differences between closely related populations can be a powerful way to detect recent adaptation. The very large sample size of the UK Biobank is ideal for using population differentiation to detect selection and enables an analysis of the UK population structure at fine resolution. In this study, analyses of 113,851 UK Biobank samples showed that population structure in the UK is dominated by five principal components (PCs) spanning six clusters: Northern Ireland, Scotland, northern England, southern England, and two Welsh clusters. Analyses of ancient Eurasians revealed that populations in the northern UK have higher levels of Steppe ancestry and that UK population structure cannot be explained as a simple mixture of Celts and Saxons. A scan for unusual population differentiation along the top PCs identified a genome-wide-significant signal of selection at the coding variant rs601338 in FUT2 (p = 9.16 × 10-9). In addition, by combining evidence of unusual differentiation within the UK with evidence from ancient Eurasians, we identified genome-wide-significant (p = 5 × 10-8) signals of recent selection at two additional loci: CYP1A2-CSK and F12. We detected strong associations between diastolic blood pressure in the UK Biobank and both the variants with selection signals at CYP1A2-CSK (p = 1.10 × 10-19) and the variants with ancient Eurasian selection signals at the ATXN2-SH2B3 locus (p = 8.00 × 10-33), implicating recent adaptation related to blood pressure.

Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia.

Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using the PC-based test for natural selection, we replicate previously known selected loci and identify three new genome-wide significant signals of selection, including selection in Europeans at ADH1B. The coding variant rs1229984(∗)T has previously been associated to a decreased risk of alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents. We also detect selection signals at IGFBP3 and IGH, which have also previously been associated to human disease.

The cytoplasmic prolyl-tRNA synthetase of the malaria parasite is a dual-stage target of febrifugine and its analogs.

The emergence of drug resistance is a major limitation of current antimalarials. The discovery of new druggable targets and pathways including those that are critical for multiple life cycle stages of the malaria parasite is a major goal for developing next-generation antimalarial drugs. Using an integrated chemogenomics approach that combined drug resistance selection, whole-genome sequencing, and an orthogonal yeast model, we demonstrate that the cytoplasmic prolyl-tRNA (transfer RNA) synthetase (PfcPRS) of the malaria parasite Plasmodium falciparum is a biochemical and functional target of febrifugine and its synthetic derivative halofuginone. Febrifugine is the active principle of a traditional Chinese herbal remedy for malaria. We show that treatment with febrifugine derivatives activated the amino acid starvation response in both P. falciparum and a transgenic yeast strain expressing PfcPRS. We further demonstrate in the Plasmodium berghei mouse model of malaria that halofuginol, a new halofuginone analog that we developed, is active against both liver and asexual blood stages of the malaria parasite. Halofuginol, unlike halofuginone and febrifugine, is well tolerated at efficacious doses and represents a promising lead for the development of dual-stage next-generation antimalarials.

Development of a single nucleotide polymorphism barcode to genotype Plasmodium vivax infections.

Plasmodium vivax, one of the five species of Plasmodium parasites that cause human malaria, is responsible for 25-40% of malaria cases worldwide. Malaria global elimination efforts will benefit from accurate and effective genotyping tools that will provide insight into the population genetics and diversity of this parasite. The recent sequencing of P. vivax isolates from South America, Africa, and Asia presents a new opportunity by uncovering thousands of novel single nucleotide polymorphisms (SNPs). Genotyping a selection of these SNPs provides a robust, low-cost method of identifying parasite infections through their unique genetic signature or barcode. Based on our experience in generating a SNP barcode for P. falciparum using High Resolution Melting (HRM), we have developed a similar tool for P. vivax. We selected globally polymorphic SNPs from available P. vivax genome sequence data that were located in putatively selectively neutral sites (i.e., intergenic, intronic, or 4-fold degenerate coding). From these candidate SNPs we defined a barcode consisting of 42 SNPs. We analyzed the performance of the 42-SNP barcode on 87 P. vivax clinical samples from parasite populations in South America (Brazil, French Guiana), Africa (Ethiopia) and Asia (Sri Lanka). We found that the P. vivax barcode is robust, as it requires only a small quantity of DNA (limit of detection 0.3 ng/µl) to yield reproducible genotype calls, and detects polymorphic genotypes with high sensitivity. The markers are informative across all clinical samples evaluated (average minor allele frequency > 0.1). Population genetic and statistical analyses show the barcode captures high degrees of population diversity and differentiates geographically distinct populations. Our 42-SNP barcode provides a robust, informative, and standardized genetic marker set that accurately identifies a genomic signature for P. vivax infections.

COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data.

BACKGROUND: Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. METHODS: COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. RESULTS: COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. CONCLUSIONS: The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.

Diversity-oriented synthesis probe targets Plasmodium falciparum cytochrome b ubiquinone reduction site and synergizes with oxidation site inhibitors.

BACKGROUND: The emergence and spread of drug resistance to current antimalarial therapies remains a pressing concern, escalating the need for compounds that demonstrate novel modes of action. Diversity-Oriented Synthesis (DOS) libraries bridge the gap between conventional small molecule and natural product libraries, allowing the interrogation of more diverse chemical space in efforts to identify probes of novel parasite pathways. METHODS: We screened and optimized a probe from a DOS library using whole-cell phenotypic assays. Resistance selection and whole-genome sequencing approaches were employed to identify the cellular target of the compounds. RESULTS: We identified a novel macrocyclic inhibitor of Plasmodium falciparum with nanomolar potency and identified the reduction site of cytochrome b as its cellular target. Combination experiments with reduction and oxidation site inhibitors showed synergistic inhibition of the parasite. CONCLUSIONS: The cytochrome b oxidation center is a validated antimalarial target. We show that the reduction site of cytochrome b is also a druggable target. Our results demonstrating a synergistic relationship between oxidation and reduction site inhibitors suggests a future strategy for new combination therapies in the treatment of malaria.

An epigenetic antimalarial resistance mechanism involving parasite genes linked to nutrient uptake.

Acquired antimalarial drug resistance produces treatment failures and has led to periods of global disease resurgence. In Plasmodium falciparum, resistance is known to arise through genome-level changes such as mutations and gene duplications. We now report an epigenetic resistance mechanism involving genes responsible for the plasmodial surface anion channel, a nutrient channel that also transports ions and antimalarial compounds at the host erythrocyte membrane. Two blasticidin S-resistant lines exhibited markedly reduced expression of clag genes linked to channel activity, but had no genome-level changes. Silencing aborted production of the channel protein and was directly responsible for reduced uptake. Silencing affected clag paralogs on two chromosomes and was mediated by specific histone modifications, allowing a rapidly reversible drug resistance phenotype advantageous to the parasite. These findings implicate a novel epigenetic resistance mechanism that involves reduced host cell uptake and is a worrisome liability for water-soluble antimalarial drugs.

The malaria parasite Plasmodium vivax exhibits greater genetic diversity than Plasmodium falciparum.

We sequenced and annotated the genomes of four P. vivax strains collected from disparate geographic locations, tripling the number of genome sequences available for this understudied parasite and providing the first genome-wide perspective of global variability in this species. We observe approximately twice as much SNP diversity among these isolates as we do among a comparable collection of isolates of P. falciparum, a malaria-causing parasite that results in higher mortality. This indicates a distinct history of global colonization and/or a more stable demographic history for P. vivax relative to P. falciparum, which is thought to have undergone a recent population bottleneck. The SNP diversity, as well as additional microsatellite and gene family variability, suggests a capacity for greater functional variation in the global population of P. vivax. These findings warrant a deeper survey of variation in P. vivax to equip disease interventions targeting the distinctive biology of this neglected but major pathogen.

Sequence-based association and selection scans identify drug resistance loci in the Plasmodium falciparum malaria parasite.

Through rapid genetic adaptation and natural selection, the Plasmodium falciparum parasite--the deadliest of those that cause malaria--is able to develop resistance to antimalarial drugs, thwarting present efforts to control it. Genome-wide association studies (GWAS) provide a critical hypothesis-generating tool for understanding how this occurs. However, in P. falciparum, the limited amount of linkage disequilibrium hinders the power of traditional array-based GWAS. Here, we demonstrate the feasibility and power improvements gained by using whole-genome sequencing for association studies. We analyzed data from 45 Senegalese parasites and identified genetic changes associated with the parasites' in vitro response to 12 different antimalarials. To further increase statistical power, we adapted a common test for natural selection, XP-EHH (cross-population extended haplotype homozygosity), and used it to identify genomic regions associated with resistance to drugs. Using this sequence-based approach and the combination of association and selection-based tests, we detected several loci associated with drug resistance. These loci included the previously known signals at pfcrt, dhfr, and pfmdr1, as well as many genes not previously implicated in drug-resistance roles, including genes in the ubiquitination pathway. Based on the success of the analysis presented in this study, and on the demonstrated shortcomings of array-based approaches, we argue for a complete transition to sequence-based GWAS for small, low linkage-disequilibrium genomes like that of P. falciparum.

Genomic sequencing of Plasmodium falciparum malaria parasites from Senegal reveals the demographic history of the population.

Malaria is a deadly disease that causes nearly one million deaths each year. To develop methods to control and eradicate malaria, it is important to understand the genetic basis of Plasmodium falciparum adaptations to antimalarial treatments and the human immune system while taking into account its demographic history. To study the demographic history and identify genes under selection more efficiently, we sequenced the complete genomes of 25 culture-adapted P. falciparum isolates from three sites in Senegal. We show that there is no significant population structure among these Senegal sampling sites. By fitting demographic models to the synonymous allele-frequency spectrum, we also estimated a major 60-fold population expansion of this parasite population ∼20,000-40,000 years ago. Using inferred demographic history as a null model for coalescent simulation, we identified candidate genes under selection, including genes identified before, such as pfcrt and PfAMA1, as well as new candidate genes. Interestingly, we also found selection against G/C to A/T changes that offsets the large mutational bias toward A/T, and two unusual patterns: similar synonymous and nonsynonymous allele-frequency spectra, and 18% of genes having a nonsynonymous-to-synonymous polymorphism ratio >1.

Hybrid selection for sequencing pathogen genomes from clinical samples.

We have adapted a solution hybrid selection protocol to enrich pathogen DNA in clinical samples dominated by human genetic material. Using mock mixtures of human and Plasmodium falciparum malaria parasite DNA as well as clinical samples from infected patients, we demonstrate an average of approximately 40-fold enrichment of parasite DNA after hybrid selection. This approach will enable efficient genome sequencing of pathogens from clinical samples, as well as sequencing of endosymbiotic organisms such as Wolbachia that live inside diverse metazoan phyla.

Pathema: a clade-specific bioinformatics resource center for pathogen research.

Pathema (http://pathema.jcvi.org) is one of the eight Bioinformatics Resource Centers (BRCs) funded by the National Institute of Allergy and Infectious Disease (NIAID) designed to serve as a core resource for the bio-defense and infectious disease research community. Pathema strives to support basic research and accelerate scientific progress for understanding, detecting, diagnosing and treating an established set of six target NIAID Category A-C pathogens: Category A priority pathogens; Bacillus anthracis and Clostridium botulinum, and Category B priority pathogens; Burkholderia mallei, Burkholderia pseudomallei, Clostridium perfringens and Entamoeba histolytica. Each target pathogen is represented in one of four distinct clade-specific Pathema web resources and underlying databases developed to target the specific data and analysis needs of each scientific community. All publicly available complete genome projects of phylogenetically related organisms are also represented, providing a comprehensive collection of organisms for comparative analyses. Pathema facilitates the scientific exploration of genomic and related data through its integration with web-based analysis tools, customized to obtain, display, and compute results relevant to ongoing pathogen research. Pathema serves the bio-defense and infectious disease research community by disseminating data resulting from pathogen genome sequencing projects and providing access to the results of inter-genomic comparisons for these organisms.

The comprehensive microbial resource.

The Comprehensive Microbial Resource or CMR (http://cmr.jcvi.org) provides a web-based central resource for the display, search and analysis of the sequence and annotation for complete and publicly available bacterial and archaeal genomes. In addition to displaying the original annotation from GenBank, the CMR makes available secondary automated structural and functional annotation across all genomes to provide consistent data types necessary for effective mining of genomic data. Precomputed homology searches are stored to allow meaningful genome comparisons. The CMR supplies users with over 50 different tools to utilize the sequence and annotation data across one or more of the 571 currently available genomes. At the gene level users can view the gene annotation and underlying evidence. Genome level information includes whole genome graphical displays, biochemical pathway maps and genome summary data. Comparative tools display analysis between genomes with homology and genome alignment tools, and searches across the accessions, annotation, and evidence assigned to all genes/genomes are available. The data and tools on the CMR aid genomic research and analysis, and the CMR is included in over 200 scientific publications. The code underlying the CMR website and the CMR database are freely available for download with no license restrictions.

Comparisons of predicted genetic modules: identification of co-expressed genes through module gene flow.

A question of fundamental importance is the definition and identification of modules from microarray experiments. A wide variety of techniques have been used to gain insight into the elucidation of such modules. One problem, however, is the inability to directly compare results between the different data sets produced due to the inherent parameterizations of their approaches. We first aim to provide a mechanism by which different approaches to module finding can be directly compared. Moreover, the same approach can be used to internally compare the modules predicted by the same technique, but at different parameterizations. We apply this approach to analyze the flow of genes through modules at different module thresholds of the Barkai Signature method, thereby further resolving the modules into sets of co-expressed genes.