137 research outputs found
Mathematical models of cellular decisions: investigating immune response and apoptosis
The main objective of this thesis is to develop and analyze mathematical models of cellular
decisions. This work focuses on understanding the mechanisms involved in specific
cellular processes such as immune response in the vascular system, and those involved in
apoptosis, or programmed cellular death.
A series of simple ordinary differential equation (ODE) models are constructed describing
the macrophage response to hemoglobin:haptoglobin (Hb:Hp) complexes that
may be present in vascular inflammation. The models proposed a positive feedback loop
between the CD163 macrophage receptor and anti-inflammatory cytokine interleukin-10
(IL-10) and bifurcation analysis predicted the existence of a cellular phenotypic switch
which was experimentally verified. Moreover, these models are extended to include the
intracellular mediator heme oxygenase-1 (HO-1). Analysis of the proposed models find a
positive feedback mechanism between IL-10 and HO-1. This model also predicts cellular
response of heme and IL-10 stimuli.
For the apoptotic (cell suicide) system, a modularized model is constructed encompassing
the extrinsic and intrinsic signaling pathways. Model reduction is performed
by abstracting the dynamics of complexes (oligomers) at a steady-state. This simplified
model is analyzed, revealing different kinetic properties between type I and type
II cells, and reduced models verify results. The second model of apoptosis proposes
a novel mechanism of apoptosis activation through receptor-ligand clustering, yielding
robust bistability and hysteresis. Using techniques from algebraic geometry, a model selection
criterion is provided between the proposed and existing model as experimental
data becomes available to verify the mechanism.
The models developed throughout this thesis reveal important and relevant mechanisms
specific to cellular response; specifically, interactions necessary for an organism
to maintain homeostasis are identified. This work enables a deeper understanding of the
biological interactions and dynamics of vascular inflammation and apoptosis. The results
of these models provide predictions which may motivate further experimental work and
theoretical study
Joining and decomposing reaction networks
In systems and synthetic biology, much research has focused on the behavior
and design of single pathways, while, more recently, experimental efforts have
focused on how cross-talk (coupling two or more pathways) or inhibiting
molecular function (isolating one part of the pathway) affects systems-level
behavior. However, the theory for tackling these larger systems in general has
lagged behind. Here, we analyze how joining networks (e.g., cross-talk) or
decomposing networks (e.g., inhibition or knock-outs) affects three properties
that reaction networks may possess---identifiability (recoverability of
parameter values from data), steady-state invariants (relationships among
species concentrations at steady state, used in model selection), and
multistationarity (capacity for multiple steady states, which correspond to
multiple cell decisions). Specifically, we prove results that clarify, for a
network obtained by joining two smaller networks, how properties of the smaller
networks can be inferred from or can imply similar properties of the original
network. Our proofs use techniques from computational algebraic geometry,
including elimination theory and differential algebra.Comment: 44 pages; extensive revision in response to referee comment
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
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Genome-wide association study of germline variants and breast cancer-specific mortality.
BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.ConclusionsWe uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients
Early Release Science of the exoplanet WASP-39b with JWST NIRISS
Transmission spectroscopy provides insight into the atmospheric properties
and consequently the formation history, physics, and chemistry of transiting
exoplanets. However, obtaining precise inferences of atmospheric properties
from transmission spectra requires simultaneously measuring the strength and
shape of multiple spectral absorption features from a wide range of chemical
species. This has been challenging given the precision and wavelength coverage
of previous observatories. Here, we present the transmission spectrum of the
Saturn-mass exoplanet WASP-39b obtained using the SOSS mode of the NIRISS
instrument on the JWST. This spectrum spans m in wavelength and
reveals multiple water absorption bands, the potassium resonance doublet, as
well as signatures of clouds. The precision and broad wavelength coverage of
NIRISS-SOSS allows us to break model degeneracies between cloud properties and
the atmospheric composition of WASP-39b, favoring a heavy element enhancement
("metallicity") of the solar value, a sub-solar
carbon-to-oxygen (C/O) ratio, and a solar-to-super-solar potassium-to-oxygen
(K/O) ratio. The observations are best explained by wavelength-dependent,
non-gray clouds with inhomogeneous coverage of the planet's terminator.Comment: 48 pages, 12 figures, 2 tables. Under review at Natur
A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
cited By 0Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.Peer reviewe
Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk
In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.Peer reviewe
CMB-S4: Forecasting Constraints on Primordial Gravitational Waves
CMB-S4---the next-generation ground-based cosmic microwave background (CMB)
experiment---is set to significantly advance the sensitivity of CMB
measurements and enhance our understanding of the origin and evolution of the
Universe, from the highest energies at the dawn of time through the growth of
structure to the present day. Among the science cases pursued with CMB-S4, the
quest for detecting primordial gravitational waves is a central driver of the
experimental design. This work details the development of a forecasting
framework that includes a power-spectrum-based semi-analytic projection tool,
targeted explicitly towards optimizing constraints on the tensor-to-scalar
ratio, , in the presence of Galactic foregrounds and gravitational lensing
of the CMB. This framework is unique in its direct use of information from the
achieved performance of current Stage 2--3 CMB experiments to robustly forecast
the science reach of upcoming CMB-polarization endeavors. The methodology
allows for rapid iteration over experimental configurations and offers a
flexible way to optimize the design of future experiments given a desired
scientific goal. To form a closed-loop process, we couple this semi-analytic
tool with map-based validation studies, which allow for the injection of
additional complexity and verification of our forecasts with several
independent analysis methods. We document multiple rounds of forecasts for
CMB-S4 using this process and the resulting establishment of the current
reference design of the primordial gravitational-wave component of the Stage-4
experiment, optimized to achieve our science goals of detecting primordial
gravitational waves for at greater than , or, in the
absence of a detection, of reaching an upper limit of at CL.Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note:
text overlap with arXiv:1907.0447
An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers
Introduction: Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. Methods: We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. Results: We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. Conclusions: This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.Peer reviewe
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