Neutrophil-to-lymphocyte ratio and all-cause mortality with and without myeloproliferative neoplasms-a Danish longitudinal study.

The neutrophil-to-lymphocyte ratio(NLR) is increased in chronic inflammation and myeloproliferative neoplasms (MPN). We hypothesize that NLR is associated with all-cause mortality and mortality by comorbidity burden in the general population and individuals with MPN. We included 835,430 individuals from The Danish General Suburban Population Study, general practitioners, and outpatient clinics. We investigated NLR on mortality stratified by prevalent and incident MPN, essential thrombocythemia (ET), polycythemia vera (PV), myelofibrosis (MF), comorbidity burden (CCI-score), and the Triple-A risk score using hazard ratio (HR) and 95% confidence interval (95%CI). NLR 1-1.9 was the reference level. During a median follow-up of 11.2 years, 197,802 deaths were recorded. All-cause mortality increased for a stepwise increasing NLR with a HR (95%CI) for NLR ≥ 6 of 2.06(2.03-2.09) for the whole population and 2.93(2.44-3.50) in prevalent MPN. ET, PV, and MF had a HR (95%CI) for NLR ≥ 2 of 2.14(1.71-2.69), 2.19(1.89-2.54), and 2.31(1.91-2.80). Results were similar for incident MPN. Mortality was higher for stepwise increasing NLR and CCI-score(pinteraction < 2×10-16), with a HR for NLR ≥ 6 of 2.23(2.17-2.29), 4.10(4.01-4.20), and 7.69(7.50-7.89), for CCI-score 0, 1-2, or ≥3. The Triple-A risk score demonstrated alignment with NLR. Increasing NLR and comorbidity burden were associated with lower survival in individuals without MPN but were even worse in prevalent and incident MPN, ET, PV, and MF.

Transformative Materials for Interfacial Drug Delivery.

Drug delivery systems (DDS) are designed to temporally and spatially control drug availability and activity. They assist in improving the balance between on-target therapeutic efficacy and off-target toxic side effects. DDS aid in overcoming biological barriers encountered by drug molecules upon applying them via various routes of administration. They are furthermore increasingly explored for modulating the interface between implanted (bio)medical materials and host tissue. Herein, an overview of the biological barriers and host-material interfaces encountered by DDS upon oral, intravenous, and local administration is provided, and material engineering advances at different time and space scales to exemplify how current and future DDS can contribute to improved disease treatment are highlighted.

Transformative Materials to Create 3D Functional Human Tissue Models In Vitro in a Reproducible Manner.

Recreating human tissues and organs in the petri dish to establish models as tools in biomedical sciences has gained momentum. These models can provide insight into mechanisms of human physiology, disease onset, and progression, and improve drug target validation, as well as the development of new medical therapeutics. Transformative materials play an important role in this evolution, as they can be programmed to direct cell behavior and fate by controlling the activity of bioactive molecules and material properties. Using nature as an inspiration, scientists are creating materials that incorporate specific biological processes observed during human organogenesis and tissue regeneration. This article presents the reader with state-of-the-art developments in the field of in vitro tissue engineering and the challenges related to the design, production, and translation of these transformative materials. Advances regarding (stem) cell sources, expansion, and differentiation, and how novel responsive materials, automated and large-scale fabrication processes, culture conditions, in situ monitoring systems, and computer simulations are required to create functional human tissue models that are relevant and efficient for drug discovery, are described. This paper illustrates how these different technologies need to converge to generate in vitro life-like human tissue models that provide a platform to answer health-based scientific questions.

Case Report: First longitudinal study of a patient with CALR positive clonal hematopoiesis of indeterminate potential developing into pre-fibrotic myelofibrosis.

Initial diagnosis of overt myeloproliferative neoplasms (MPNs) represents the juncture during clonal evolution when symptoms or complications prompt an afflicted individual to seek medical attention. In 30-40% of the MPN subgroups essential thrombocythemia (ET) and myelofibrosis (MF), somatic mutations in the calreticulin gene (CALR) are drivers of the disease resulting in constitutive activation of the thrombopoietin receptor (MPL). In the current study, we describe a healthy CALR mutated individual during a 12 year follow-up from initial identification of CALR clonal hematopoiesis of indeterminate potential (CHIP) to the diagnosis of pre-MF. The pre-diagnostic exponential development dynamics of the malignant clone demonstrated close correlation with the platelet counts, neutrophil-to-lymphocyte (NLR) ratio, and inversely correlated to hemoglobin and erythrocyte counts. Backward extrapolation of the growth rate indicated the potential for discovery of the malignant clone many years prior to presentation of overt disease, opening a window of opportunity for early treatment intervention. We did not find any additional mutations associated with MPNs and the current case report provides novel information regarding the development of a driver mutation and the association with blood cell counts prior to clinical manifestation of symptoms suggesting that pre-diagnostic dynamics may supplement future diagnostic criteria for early diagnosis and intervention in MPN patients.

HSC Niche Dynamics in Regeneration, Pre-malignancy, and Cancer: Insights From Mathematical Modeling.

The hematopoietic stem cell (HSC) niche is a crucial driver of regeneration and malignancy. Its interaction with hematopoietic and malignant stem cells is highly complex and direct experimental observations are challenging. We here develop a mathematical model which helps relate processes in the niche to measurable changes of stem and non-stem cell counts. HSC attached to the niche are assumed to be quiescent. After detachment HSC become activated and divide or differentiate. To maintain their stemness, the progeny originating from division must reattach to the niche. We use mouse data from literature to parametrize the model. By combining mathematical analysis and computer simulations, we systematically investigate the impact of stem cell proliferation, differentiation, niche attachment, and detachment on clinically relevant scenarios. These include bone marrow transplantation, clonal competition, and eradication of malignant cells. According to our model, sampling of blood or bulk marrow provides only limited information about cellular interactions in the niche and the clonal composition of the stem cell population. Furthermore, we investigate how interference with processes in the stem cell niche could help to increase the effect of low-dose chemotherapy or to improve the homing of genetically engineered cells.

Clonal haematopoiesis of indeterminate potential and impaired kidney function-A Danish general population study with 11 years follow-up.

The myeloproliferative neoplasms are associated with chronic kidney disease but whether clonal haematopoiesis of indeterminate potential (CHIP) is associated with impaired kidney function is unknown. In the Danish General Suburban Population Study (N = 19 958) from 2010 to 2013, 645 individuals were positive for JAK2V617F (N = 613) or CALR (N = 32) mutations. Mutation-positive individuals without haematological malignancy were defined as having CHIP (N = 629). We used multiple and inverse probability weighted (IPW)-adjusted linear regression analysis to estimate adjusted mean (95% confidence interval) differences in estimated glomerular filtration rate (eGFR; ml/min/1.73 m2 ) by mutation status, variant allele frequency (VAF%), blood cell counts, and neutrophil-to-lymphocyte ratio (NLR). We performed 11-year longitudinal follow-up of eGFR in all individuals. Compared to CHIP-negative individuals, the mean differences in eGFR were -5.6 (-10.3, -0.8, p = .02) for CALR, -11.9 (-21.4, -2.4, p = 0.01) for CALR type 2, and -10.1 (-18.1, -2.2, p = .01) for CALR with VAF ≥ 1%. The IPW-adjusted linear regression analyses showed similar results. NLR was negatively associated with eGFR. Individuals with CALR type 2 had a worse 11-year longitudinal follow-up on eGFR compared to CHIP-negative individuals (p = .004). In conclusion, individuals with CALR mutations, especially CALR type 2, had impaired kidney function compared to CHIP-negative individuals as measured by a lower eGFR at baseline and during 11-year follow-up.

Genetic barcoding systematically compares genes in del(5q) MDS and reveals a central role for CSNK1A1 in clonal expansion.

How genetic haploinsufficiency contributes to the clonal dominance of hematopoietic stem cells (HSCs) in del(5q) myelodysplastic syndrome (MDS) remains unresolved. Using a genetic barcoding strategy, we performed a systematic comparison on genes implicated in the pathogenesis of del(5q) MDS in direct competition with each other and wild-type (WT) cells with single-clone resolution. Csnk1a1 haploinsufficient HSCs expanded (oligo)clonally and outcompeted all other tested genes and combinations. Csnk1a1-/+ multipotent progenitors showed a proproliferative gene signature and HSCs showed a downregulation of inflammatory signaling/immune response. In validation experiments, Csnk1a1-/+ HSCs outperformed their WT counterparts under a chronic inflammation stimulus, also known to be caused by neighboring genes on chromosome 5. We therefore propose a crucial role for Csnk1a1 haploinsufficiency in the selective advantage of 5q-HSCs, implemented by creation of a unique competitive advantage through increased HSC self-renewal and proliferation capacity, as well as increased fitness under inflammatory stress.

Kynurenine pathway activation and deviation to anthranilic and kynurenic acid in fibrosing chronic graft-versus-host disease.

Fibrosing chronic graft-versus-host disease (cGVHD) is a debilitating complication of allogeneic stem cell transplantation (alloSCT). A driver of fibrosis is the kynurenine (Kyn) pathway, and Kyn metabolism patterns and cytokines may influence cGVHD severity and manifestation (fibrosing versus gastrointestinal [GI] cGVHD). Using a liquid chromatography-tandem mass spectrometry approach on sera obtained from 425 patients with allografts, we identified high CXCL9, high indoleamine-2,3-dioxygenase (IDO) activity, and an activated Kyn pathway as common characteristics in all cGVHD subtypes. Specific Kyn metabolism patterns could be identified for non-severe cGVHD, severe GI cGVHD, and fibrosing cGVHD, respectively. Specifically, fibrosing cGVHD was associated with a distinct pathway shift toward anthranilic and kynurenic acid, correlating with reduced activity of the vitamin-B2-dependent kynurenine monooxygenase, low vitamin B6, and increased interleukin-18. The Kyn metabolite signature is a candidate biomarker for severe fibrosing cGVHD and provides a rationale for translational trials on prophylactic vitamin B2/B6 supplementation for cGVHD prevention.

Computational Reconstruction of Clonal Hierarchies From Bulk Sequencing Data of Acute Myeloid Leukemia Samples.

Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.

High throughput screening of novel AAV capsids identifies variants for transduction of adult NSCs within the subventricular zone.

The adult mammalian brain entails a reservoir of neural stem cells (NSCs) generating glial cells and neurons. However, NSCs become increasingly quiescent with age, which hampers their regenerative capacity. New means are therefore required to genetically modify adult NSCs for re-enabling endogenous brain repair. Recombinant adeno-associated viruses (AAVs) are ideal gene-therapy vectors due to an excellent safety profile and high transduction efficiency. We thus conducted a high-throughput screening of 177 intraventricularly injected barcoded AAV variants profiled by RNA sequencing. Quantification of barcoded AAV mRNAs identified two synthetic capsids, peptide-modified derivative of wild-type AAV9 (AAV9_A2) and peptide-modified derivative of wild-type AAV1 (AAV1_P5), both of which transduce active and quiescent NSCs. Further optimization of AAV1_P5 by judicious selection of the promoter and dose of injected viral genomes enabled labeling of 30%-60% of the NSC compartment, which was validated by fluorescence-activated cell sorting (FACS) analyses and single-cell RNA sequencing. Importantly, transduced NSCs readily produced neurons. The present study identifies AAV variants with a high regional tropism toward the ventricular-subventricular zone (v-SVZ) with high efficiency in targeting adult NSCs, thereby paving the way for preclinical testing of regenerative gene therapy.

Dynamical properties of feedback signalling in B lymphopoiesis: A mathematical modelling approach.

Haematopoiesis is the process of generation of blood cells. Lymphopoiesis generates lymphocytes, the cells in charge of the adaptive immune response. Disruptions of this process are associated with diseases like leukaemia, which is especially incident in children. The characteristics of self-regulation of this process make them suitable for a mathematical study. In this paper we develop mathematical models of lymphopoiesis using currently available data. We do this by drawing inspiration from existing structured models of cell lineage development and integrating them with paediatric bone marrow data, with special focus on regulatory mechanisms. A formal analysis of the models is carried out, giving steady states and their stability conditions. We use this analysis to obtain biologically relevant regions of the parameter space and to understand the dynamical behaviour of B-cell renovation. Finally, we use numerical simulations to obtain further insight into the influence of proliferation and maturation rates on the reconstitution of the cells in the B line. We conclude that a model including feedback regulation of cell proliferation represents a biologically plausible depiction for B-cell reconstitution in bone marrow. Research into haematological disorders could benefit from a precise dynamical description of B lymphopoiesis.

Mathematical modelling of the hematopoietic stem cell-niche system: Clonal dominance based on stem cell fitness.

Human blood cell production is maintained by hematopoietic stem cells (HSC) which give rise to all types of mature blood cells. Experimental observation of HSC in their physiologic bone-marrow microenvironment, the so-called stem cell niche, is challenging. Therefore, the details of HSC dynamics and the cellular interactions in the stem cell niche remain elusive. Mutations that lead to a competitive advantage are the cause of clinical challenges when treating HSC-derived malignancies such as acute myeloid leukemia or the myeloproliferative neoplasms (MPNs). To investigate the significance of the interaction between the HSC and the stem cell niche in these malignancies, we propose and analyse a mechanism-based mathematical model of HSC dynamics within the bone-marrow microenvironment. The model is based on the central hypothesis that HSC self-renewal depends on the niche. In the model, the interaction of HSC with specific niches located in the bone marrow are key to the indefinite HSC renewal necessary for long-term maintenance of blood cell production. We formulate a general model of n distinct clones that differ with respect to cell properties. We identify an attractive trapping region and compute and classify all steady states. A concept of HSC fitness naturally arises from the model analysis. HSC fitness is found to determine the asymptotic behaviour of the model, as the HSC clone with the highest fitness is related to the unique locally stable steady state. Based on biological assumptions about HSC, we propose two reduced models of different complexity. A thorough mathematical analysis reveals that both reduced models have the same asymptotic behaviour as the full model. We compare the simpler of the two models, a logistic equation of the disease burden, to clinical data of MPN-patients. The reduced model is found to agree well with data and suggests a simple interpretation and possible prediction of patient prognosis. The proposed mathematical model and the reduced forms have the potential to provide insights into the regulation of HSC dynamics and blood cell formation, and ultimately for future advances in treatment of hematologic malignancies.

Coordinated changes in cellular behavior ensure the lifelong maintenance of the hippocampal stem cell population.

Neural stem cell numbers fall rapidly in the hippocampus of juvenile mice but stabilize during adulthood, ensuring lifelong hippocampal neurogenesis. We show that this stabilization of stem cell numbers in young adults is the result of coordinated changes in stem cell behavior. Although proliferating neural stem cells in juveniles differentiate rapidly, they increasingly return to a resting state of shallow quiescence and progress through additional self-renewing divisions in adulthood. Single-cell transcriptomics, modeling, and label retention analyses indicate that resting cells have a higher activation rate and greater contribution to neurogenesis than dormant cells, which have not left quiescence. These changes in stem cell behavior result from a progressive reduction in expression of the pro-activation protein ASCL1 because of increased post-translational degradation. These cellular mechanisms help reconcile current contradictory models of hippocampal neural stem cell (NSC) dynamics and may contribute to the different rates of decline of hippocampal neurogenesis in mammalian species, including humans.

Using mathematical models to improve risk-scoring in acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aggressive cancer of the blood forming (hematopoietic) system. Due to the high patient variability of disease dynamics, risk-scoring is an important part of its clinical management. AML is characterized by impaired blood cell formation and the accumulation of so-called leukemic blasts in the bone marrow of patients. Recently, it has been proposed to use counts of blood-producing (hematopoietic) stem cells (HSCs) as a biomarker for patient prognosis. In this work, we use a non-linear mathematical model to provide mechanistic evidence for the suitability of HSC counts as a prognostic marker. Using model analysis and computer simulations, we compare different risk-scores involving HSC quantification. We propose and validate a simple approach to improve risk prediction based on HSC and blast counts measured at the time of diagnosis.

Mathematical Modeling Provides Evidence for Niche Competition in Human AML and Serves as a Tool to Improve Risk Stratification.

Acute myeloid leukemia (AML) is a stem cell-driven malignant disease. There is evidence that leukemic stem cells (LSC) interact with stem cell niches and outcompete hematopoietic stem cells (HSC). The impact of this interaction on the clinical course of the disease remains poorly understood. We developed and validated a mathematical model of stem cell competition in the human HSC niche. Model simulations predicted how processes in the stem cell niche affect the speed of disease progression. Combining the mathematical model with data of individual patients, we quantified the selective pressure LSCs exert on HSCs and demonstrated the model's prognostic significance. A novel model-based risk-stratification approach allowed extraction of prognostic information from counts of healthy and malignant cells at the time of diagnosis. This model's feasibility was demonstrable based on a cohort of patients with ALDH-rare AML and shows that the model-based risk stratification is an independent predictor of disease-free and overall survival. This proof-of-concept study shows how model-based interpretation of patient data can improve prognostic scoring and contribute to personalized medicine. SIGNIFICANCE: Combining a novel mathematical model of the human hematopoietic stem cell niche with individual patient data enables quantification of properties of leukemic stem cells and improves risk stratification in acute myeloid leukemia.

Mathematical modeling of plant cell fate transitions controlled by hormonal signals.

Coordination of fate transition and cell division is crucial to maintain the plant architecture and to achieve efficient production of plant organs. In this paper, we analysed the stem cell dynamics at the shoot apical meristem (SAM) that is one of the plant stem cells locations. We designed a mathematical model to elucidate the impact of hormonal signaling on the fate transition rates between different zones corresponding to slowly dividing stem cells and fast dividing transit amplifying cells. The model is based on a simplified two-dimensional disc geometry of the SAM and accounts for a continuous displacement towards the periphery of cells produced in the central zone. Coupling growth and hormonal signaling results in a nonlinear system of reaction-diffusion equations on a growing domain with the growth rate depending on the model components. The model is tested by simulating perturbations in the level of key transcription factors that maintain SAM homeostasis. The model provides new insights on how the transcription factor HECATE is integrated in the regulatory network that governs stem cell differentiation.

New targeted approaches for epigenetic age predictions.

BACKGROUND: Age-associated DNA methylation changes provide a promising biomarker for the aging process. While genome-wide DNA methylation profiles enable robust age-predictors by integration of many age-associated CG dinucleotides (CpGs), there are various alternative approaches for targeted measurements at specific CpGs that better support standardized and cost-effective high-throughput analysis. RESULTS: In this study, we utilized 4647 Illumina BeadChip profiles of blood to select CpG sites that facilitate reliable age-predictions based on pyrosequencing. We demonstrate that the precision of DNA methylation measurements can be further increased with droplet digital PCR (ddPCR). In comparison, bisulfite barcoded amplicon sequencing (BBA-seq) gave slightly lower correlation between chronological age and DNA methylation at individual CpGs, while the age-predictions were overall relatively accurate. Furthermore, BBA-seq data revealed that the correlation of methylation levels with age at neighboring CpG sites follows a bell-shaped curve, often associated with a CTCF binding site. We demonstrate that within individual BBA-seq reads the DNA methylation at neighboring CpGs is not coherently modified, but reveals a stochastic pattern. Based on this, we have developed a new approach for epigenetic age predictions based on the binary sequel of methylated and non-methylated sites in individual reads, which reflects heterogeneity in epigenetic aging within a sample. CONCLUSION: Targeted DNA methylation analysis at few age-associated CpGs by pyrosequencing, BBA-seq, and particularly ddPCR enables high precision of epigenetic age-predictions. Furthermore, we demonstrate that the stochastic evolution of age-associated DNA methylation patterns in BBA-seq data enables epigenetic clocks for individual DNA strands.

Oscillations in a white blood cell production model with multiple differentiation stages.

In this work we prove occurrence of a super-critical Hopf bifurcation in a model of white blood cell formation structured by three maturation stages. We provide an explicit analytical expression for the bifurcation point depending on model parameters. The Hopf bifurcation is a unique feature of the multi-compartment structure as it does not exist in the corresponding two-compartment model. It appears for a parameter set different from the parameters identified for healthy hematopoiesis and requires changes in at least two cell properties. Model analysis allows identifying a range of biologically plausible parameter sets that can explain persistent oscillations of white blood cell counts observed in some hematopoietic diseases. Relating the identified parameter sets to recent experimental and clinical findings provides insights into the pathological mechanisms leading to oscillating blood cell counts.

A structured population model of clonal selection in acute leukemias with multiple maturation stages.

Recent progress in genetic techniques has shed light on the complex co-evolution of malignant cell clones in leukemias. However, several aspects of clonal selection still remain unclear. In this paper, we present a multi-compartmental continuously structured population model of selection dynamics in acute leukemias, which consists of a system of coupled integro-differential equations. Our model can be analysed in a more efficient way than classical models formulated in terms of ordinary differential equations. Exploiting the analytical tractability of this model, we investigate how clonal selection is shaped by the self-renewal fraction and the proliferation rate of leukemic cells at different maturation stages. We integrate analytical results with numerical solutions of a calibrated version of the model based on real patient data. In summary, our mathematical results formalise the biological notion that clonal selection is driven by the self-renewal fraction of leukemic stem cells and the clones that possess the highest value of this parameter are ultimately selected. Moreover, we demonstrate that the self-renewal fraction and the proliferation rate of non-stem cells do not have a substantial impact on clonal selection. Taken together, our results indicate that interclonal variability in the self-renewal fraction of leukemic stem cells provides the necessary substrate for clonal selection to act upon.