Clin. Pharmacol. Ther. 2021 Aug 30
Selevsek,
N.,
Caiment, F., Nudischer, R., Gmuender, H., Agarkova, I.,
Atkinson, F.L., Bachmann, I., Baier, V., Barel, G., Bauer, C.,
et al. (2020)
Network integration and modelling of dynamic drug responses
at multi-omics levels.
Commun. Biol. 3, 1–15.
Abstract
Uncovering cellular responses from heterogeneous genomic data is
crucial for molecular medicine in particular for drug safety. This
can be realized by integrating the molecular activities in
networks of interacting proteins. As proof-of-concept we challenge
network modeling with time-resolved proteome, transcriptome and
methylome measurements in iPSC-derived human 3D cardiac
microtissues to elucidate adverse mechanisms of anthracycline
cardiotoxicity measured with four different drugs (doxorubicin,
epirubicin, idarubicin and daunorubicin). Dynamic molecular
analysis at in vivo drug exposure levels reveal a network of 175
disease-associated proteins and identify common modules of
anthracycline cardiotoxicity in vitro, related to mitochondrial
and sarcomere function as well as remodeling of extracellular
matrix. These in vitro-identified modules are transferable and are
evaluated with biopsies of cardiomyopathy patients. This to our
knowledge most comprehensive study on anthracycline cardiotoxicity
demonstrates a reproducible workflow for molecular medicine and
serves as a template for detecting adverse drug responses from
complex omics data.
Verheijen, M., Lienhard, M., Schrooders,
Y., Clayton, O., Nudischer, R., Boerno, S., Timmermann, B.,
Selevsek, N., Schlapbach, R., Gmuender, H., et al. (2019)
DMSO induces drastic changes in
human cellular processes and epigenetic landscape in vitro.
Sci. Rep. 9, 4641
Abstract
Though clinical trials for medical applications of dimethyl
sulfoxide (DMSO) reported toxicity in the 1960s, later, the FDA
classified DMSO in the safest solvent category. DMSO became widely
used in many biomedical fields and biological effects were
overlooked. Meanwhile, biomedical science has evolved towards
sensitive high-throughput techniques and new research areas,
including epigenomics and microRNAs. Considering its wide use,
especially for cryopreservation and in vitro assays, we evaluated
biological effect of DMSO using these technological innovations.
We exposed 3D cardiac and hepatic microtissues to medium with or
without 0.1% DMSO and analyzed the transcriptome, proteome and DNA
methylation profiles. In both tissue types, transcriptome analysis
detected >2000 differentially expressed genes affecting similar
biological processes, thereby indicating consistent cross-organ
actions of DMSO. Furthermore, microRNA analysis revealed
large-scale deregulations of cardiac microRNAs and smaller, though
still massive, effects in hepatic microtissues. Genome-wide
methylation patterns also revealed tissue-specificity. While
hepatic microtissues demonstrated nonsignificant changes, findings
from cardiac microtissues suggested disruption of DNA methylation
mechanisms leading to genome-wide changes. The extreme changes in
microRNAs and alterations in the epigenetic landscape indicate
that DMSO is not inert. Its use should be reconsidered, especially
for cryopreservation of embryos and oocytes, since it may impact
embryonic development.
Fernández, D., Sram, R.J., Dostal, M.,
Pastorkova, A., Gmuender, H., and Choi, H. (2018) Modeling
Unobserved
Heterogeneity in Susceptibility to Ambient Benzo[a]pyrene
Concentration among Children with Allergic Asthma Using an
Unsupervised Learning Algorithm
Int. J. Environ. Res. Public. Health 15, 1
Abstract
Current studies of gene × air pollution interaction typically seek
to identify unknown heritability of common complex illnesses
arising from variability in the host's susceptibility to
environmental pollutants of interest. Accordingly, a single
component generalized linear models are often used to model the
risk posed by an environmental exposure variable of interest in
relation to a priori determined DNA variants. However, reducing
the phenotypic heterogeneity may further optimize such approach,
primarily represented by the modeled DNA variants. Here, we reduce
phenotypic heterogeneity of asthma severity, and also identify
single nucleotide polymorphisms (SNP) associated with phenotype
subgroups. Specifically, we first apply an unsupervised learning
algorithm method and a non-parametric regression to find a
biclustering structure of children according to their allergy and
asthma severity. We then identify a set of SNPs most closely
correlated with each sub-group. We subsequently fit a logistic
regression model for each group against the healthy controls using
benzo[a]pyrene (B[a]P) as a representative airborne carcinogen.
Application of such approach in a case-control data set shows that
SNP clustering may help to partly explain heterogeneity in
children's asthma susceptibility in relation to ambient B[a]P
concentration with greater efficiency.
Jeong, A.,
Fiorito, G., Keski-Rahkonen, P., Imboden, M., Kiss, A., Robinot,
N., Gmuender, H., Vlaanderen, J., Vermeulen, R., Kyrtopoulos,
S., et al. (2018)
Perturbation of metabolic
pathways mediates the association of air pollutants with
asthma and cardiovascular diseases
Environ. Int. 119, 334–345
Abstract
Background: Epidemiologic evidence indicates common risk
factors, including air pollution exposure, for respiratory and
cardiovascular diseases, suggesting the involvement of common
altered molecular pathways.
Objectives: The goal was to find intermediate metabolites or
metabolic pathways that could be associated with both air
pollutants and health outcomes (“meeting-in-the-middle”), thus
shedding light on mechanisms and reinforcing causality.
Methods: We applied a statistical approach named
‘meet-in-the-middle’ to untargeted metabolomics in two
independent case-control studies nested in cohorts on
adult-onset asthma (AOA) and cardio-cerebrovascular diseases
(CCVD). We compared the results to identify both common and
disease-specific altered metabolic pathways.
Results: A novel finding was a strong association of AOA with
ultrafine particles (UFP; odds ratio 1.80 [1.26, 2.55] per
increase by 5000 particles/cm3). Further, we have identified
several metabolic pathways that potentially mediate the effect
of air pollution on health outcomes. Among those, perturbation
of Linoleate metabolism pathway was associated with air
pollution exposure, AOA and CCVD.
Conclusions: Our results suggest common pathway perturbations
may occur as a consequence of chronic exposure to air pollution
leading to increased risk for both AOA and CCVD.
Kuepfer,
L., Clayton, O., Thiel, C., Cordes, H., Nudischer, R., Blank,
L.M., Baier, V., Heymans, S., Caiment, F., Roth, A., et al.
(2018)
A
model-based assay design to reproduce in vivo patterns of
acute drug-induced toxicity
Arch. Toxicol. 92,
553–555
Abstract
Current studies of gene × air pollution interaction typically
seek to identify unknown heritability of common complex
illnesses arising from variability in the host's susceptibility
to environmental pollutants of interest. Accordingly, a single
component generalized linear models are often used to model the
risk posed by an environmental exposure variable of interest in
relation to a priori determined DNA variants. However, reducing
the phenotypic heterogeneity may further optimize such approach,
primarily represented by the modeled DNA variants. Here, we
reduce phenotypic heterogeneity of asthma severity, and also
identify single nucleotide polymorphisms (SNP) associated with
phenotype subgroups. Specifically, we first apply an
unsupervised learning algorithm method and a non-parametric
regression to find a biclustering structure of children
according to their allergy and asthma severity. We then identify
a set of SNPs most closely correlated with each sub-group. We
subsequently fit a logistic regression model for each group
against the healthy controls using benzo[a]pyrene (B[a]P) as a
representative airborne carcinogen. Application of such approach
in a case-control data set shows that SNP clustering may help to
partly explain heterogeneity in children's asthma susceptibility
in relation to ambient B[a]P concentration with greater
efficiency.
Verheijen,
M., Schrooders, Y., Gmuender, H., Nudischer, R., Clayton, O.,
Hynes, J., Niederer, S., Cordes, H., Kuepfer, L., Kleinjans,
J., et al. (2018)
Bringing
in vitro analysis closer to in vivo: Studying doxorubicin
toxicity and associated mechanisms in 3D human microtissues
with PBPK-based dose modelling
Toxicol. Lett. 294,
184–192
Abstract
Doxorubicin (DOX) is a chemotherapeutic agent of which the
medical use is limited due to cardiotoxicity. While acute
cardiotoxicity is reversible, chronic cardiotoxicity is
persistent or progressive, dose-dependent and irreversible.
While DOX mechanisms of action are not fully understood yet, 3
toxicity processes are known to occur in vivo: cardiomyocyte
dysfunction, mitochondrial dysfunction and cell death. We
present an in vitro experimental design aimed at detecting
DOX-induced cardiotoxicity by obtaining a global view of the
induced molecular mechanisms through RNA-sequencing. To better
reflect the in vivo situation, human 3D cardiac microtissues
were exposed to physiologically-based pharmacokinetic (PBPK)
relevant doses of DOX for 2 weeks. We analysed a therapeutic
and a toxic dosing profile. Transcriptomics analysis revealed
significant gene expression changes in pathways related to
"striated muscle contraction" and "respiratory electron
transport", thus suggesting mitochondrial dysfunction as an
underlying mechanism for cardiotoxicity. Furthermore,
expression changes in mitochondrial processes differed
significantly between the doses. Therapeutic dose reflects
processes resembling the phenotype of delayed chronic
cardiotoxicity, while toxic doses resembled acute
cardiotoxicity. Overall, these results demonstrate the
capability of our innovative in vitro approach to detect the
three known mechanisms of DOX leading to toxicity, thus
suggesting its potential relevance for reflecting the patient
situation. Our study also demonstrated the importance of
applying physiologically relevant doses during toxicological
research, since mechanisms of acute and chronic toxicity
differ.
Boei,
J.J.W.A., Vermeulen, S., Klein, B., Hiemstra, P.S., Verhoosel,
R.M., Jennen, D.G.J., Lahoz, A., Gmuender, H., and Vrieling, H.
(2017)
Xenobiotic metabolism in
differentiated human bronchial epithelial cells
Arch. Toxicol. 91,
2093–2105
Abstract
Differentiated human bronchial epithelial cells in air liquid
interface cultures (ALI-PBEC) represent a promising alternative
for inhalation studies with rodents as these 3D airway
epithelial tissue cultures recapitulate the human airway in
multiple aspects, including morphology, cell type composition,
gene expression and xenobiotic metabolism. We performed a
detailed longitudinal gene expression analysis during the
differentiation of submerged primary human bronchial epithelial
cells into ALI-PBEC to assess the reproducibility and
inter-individual variability of changes in transcriptional
activity during this process. We generated ALI-PBEC cultures
from four donors and focussed our analysis on the expression
levels of 362 genes involved in biotransformation, which are of
primary importance for toxicological studies. Expression of
various of these genes (e.g., GSTA1, ADH1C, ALDH1A1, CYP2B6,
CYP2F1, CYP4B1, CYP4X1 and CYP4Z1) was elevated following the
mucociliary differentiation of airway epithelial cells into a
pseudo-stratified epithelial layer. Although a substantial
number of genes were differentially expressed between donors,
the differences in fold changes were generally small. Metabolic
activity measurements applying a variety of different cytochrome
p450 substrates indicated that epithelial cultures at the early
stages of differentiation are incapable of biotransformation. In
contrast, mature ALI-PBEC cultures were proficient in the
metabolic conversion of a variety of substrates albeit with
considerable variation between donors. In summary, our data
indicate a distinct increase in biotransformation capacity
during differentiation of PBECs at the air-liquid interface and
that the generation of biotransformation competent ALI-PBEC
cultures is a reproducible process with little variability
between cultures derived from four different donors.
Choi,
H., Tabashidze, N., Rossner, P., Dostal, M., Pastorkova,
A., Kong, S.W., Gmuender, H., and Sram, R.J. (2017)
Altered
vulnerability to asthma at various levels of ambient
Benzo[a]Pyrene by CTLA4, STAT4 and CYP2E1 polymorphisms
Environ Pollut. Dec;
231 (Pt 1): 1134-1144
Abstract
BACKGROUND: Within fossil- and solid-fuel dependent
geographic locations, mechanisms of air pollution-induced
asthma remains unknown. In particular, sources of greater
genetic susceptibility to airborne carcinogen, namely,
benzo[a]pyrene (B[a]P) has never been investigated beyond
that of a few well known genes.
OBJECTIVES: To deepen our understanding on how the
genotypic variations within the candidate genes contribute
to the variability in the children's susceptibility to
ambient B[a]P on doctor-diagnosed asthma.
METHODS: Clinically confirmed asthmatic versus healthy
control children (aged, 7-15) were enrolled from
historically polluted and rural background regions in
Czech Republic. Contemporaneous ambient B[a]P
concentration was obtained from the routine monitoring
network. The sputum DNA was genotyped for 95 genes. B[a]P
interaction with SNPs was studied by two-stage,
semi-agnostic screening of 621 SNPs.
RESULTS: The median B[a]P within the highly polluted urban
center was 8-times higher than that in the background
region (7.8 vs. 1.1 ng/m(3)) during the period of
investigation. Within the baseline model, which considered
B[a]P exposure-only, the second tertile range was
associated with a significantly reduced odds (aOR = 0.28)
of asthma (95% CI, 0.16 to 0.50) compared to those at the
lowest range. However, the highest range of B[a]P was
associated with 3.18-times greater odds of the outcome
(95% CI, 1.77 to 5.71). Within the gene-environment
interaction models, joint occurrence of a high B[a]P
exposure range and having a high-risk genotype at CTLA4
gene (rs11571316) was associated with 9-times greater odds
(95% CI, 4.56-18.36) of the asthma diagnosis. Similarly,
rs11571319 at CTLA4 and a high B[a]P exposure range was
associated with a 8-times greater odds (95% CI,
3.95-14.27) of asthma diagnosis. Furthermore, having TG +
GG genotypes on rs1031509 near STAT4 was associated with
5-times (95% CI, 3.03-8.55) greater odds of asthma
diagnosis at the highest B[a]P range, compared to the odds
at the reference range. Also CYP2E1 AT + TT genotypes
(rs2070673) was associated with 5-times (95% CI, 3.1-8.8)
greater odds of asthma diagnosis at the highest B[a]P
exposure.
CONCLUSIONS: The children, who jointly experience a high
B[a]P exposure (6.3-8.5 ng/m3) as well as susceptible
genotypes in CTLA4 (rs11571316 and rs11571319), STAT4
(rs1031509), and CYP2E1 (rs2070673), respectively, are
associated with a significantly greater odds of having
doctor-diagnosed asthma, compared to those with neither
risk factors.
Vineis, P., Chadeau-Hyam, M., Gmuender,
H., Gulliver, J., Herceg, Z., Kleinjans, J., Kogevinas, M.,
Kyrtopoulos, S., Nieuwenhuijsen, M., Phillips, D., et al. (2017)
The exposome in practice: Design
of the EXPOsOMICS project
Int. J. Hyg. Environ. Health
220,
142–151
Abstract
EXPOsOMICS is a European Union funded project that aims to develop
a novel approach to the assessment of exposure to high priority
environmental pollutants, by characterizing the external and the
internal components of the exposome. It focuses on air and water
contaminants during critical periods of life. To this end, the
project centres on 1) exposure assessment at the personal and
population levels within existing European short and long-term
population studies, exploiting available tools and methods which
have been developed for personal exposure monitoring (PEM); and 2)
multiple “omic” technologies for the analysis of biological
samples (internal markers of external exposures). The search for
the relationships between external exposures and global profiles
of molecular features in the same individuals constitutes a novel
advancement towards the development of “next generation exposure
assessment” for environmental chemicals and their mixtures. The
linkage with disease risks opens the way to what are defined here
as ‘exposome-wide association studies’ (EWAS).
Inter-laboratory study of
human in vitro toxicogenomics-based tests as alternative
methods for evaluating chemical carcinogenicity: a
bioinformatics perspective
Arch. Toxicol. 90, 9, 2215-2229
Abstract
The assessment of the carcinogenic potential of chemicals with
alternative, human-based in vitro systems has become a major
goal of toxicogenomics. The central read-out of these assays is
the transcriptome, and while many studies exist that explored
the gene expression responses of such systems, reports on
robustness and reproducibility, when testing them independently
in different laboratories, are still uncommon. Furthermore,
there is limited knowledge about variability induced by the data
analysis protocols. We have conducted an inter-laboratory study
for testing chemical carcinogenicity evaluating two human in
vitro assays: hepatoma-derived cells and hTERT-immortalized
renal proximal tubule epithelial cells, representing liver and
kidney as major target organs. Cellular systems were initially
challenged with thirty compounds, genome-wide gene expression
was measured with microarrays, and hazard classifiers were built
from this training set. Subsequently, each system was
independently established in three different laboratories, and
gene expression measurements were conducted using anonymized
compounds. Data analysis was performed independently by two
separate groups applying different protocols for the assessment
of inter-laboratory reproducibility and for the prediction of
carcinogenic hazard. As a result, both workflows came to very
similar conclusions with respect to (1) identification of
experimental outliers, (2) overall assessment of robustness and
inter-laboratory reproducibility and (3) re-classification of
the unknown compounds to the respective toxicity classes. In
summary, the developed bioinformatics workflows deliver accurate
measures for inter-laboratory comparison studies, and the study
can be used as guidance for validation of future carcinogenicity
assays in order to implement testing of human in vitro
alternatives to animal testing.
Manawapat-Klopfer, A., Thomsen, L.T.,
Martus, P., Munk, C., Russ, R., Gmuender, H., Frederiksen, K.,
Haedicke-Jarboui, J., Stubenrauch, F., Kjaer, S.K., et al. (2016)
TMEM45A, SERPINB5 and p16INK4A
transcript levels are predictive for development of high-grade
cervical lesions
Am. J. Cancer Res. 6, 1524–1536
Abstract
Women persistently infected with human papillomavirus (HPV) type
16 are at high risk for development of cervical intraepithelial
neoplasia grade 3 or cervical cancer (CIN3+). We aimed to identify
biomarkers for progression to CIN3+ in women with persistent HPV16
infection. In this prospective study, 11,088 women aged 20-29
years were enrolled during 1991-1993, and re-invited for a second
visit two years later. Cervical cytology samples obtained at both
visits were tested for HPV DNA by Hybrid Capture 2 (HC2), and
HC2-positive samples were genotyped by INNO-LiPA. The cohort was
followed for up to 19 years via a national pathology register. To
identify markers for progression to CIN3+, we performed microarray
analysis on RNA extracted from cervical swabs of 30 women with
persistent HPV16-infection and 11 HPV-negative women. Six genes
were selected and validated by quantitative PCR. Three genes were
subsequently validated within a different and large group of women
from the same cohort. Secondly, Kaplan-Meier and Cox-regression
analyses were used to investigate whether expression levels of
those three genes predict progression to CIN3+. We found that high
transcript levels of TMEM45A, SERPINB5 and p16INK4a at baseline
were associated with increased risk of CIN3+ during follow-up. The
hazard ratios of CIN3+ per 10-fold increase in baseline expression
level were 1.6 (95% CI: 1.1-2.3) for TMEM45A, 1.6 (95% CI:
1.1-2.5) for p16INK4a, and 1.8 (95% CI: 1.2-2.7) for SERPINB5. In
conclusion, high mRNA expression levels of TMEM45A, SERPINB5 and
p16INK4a were associated with increased risk of CIN3+ in
persistently HPV16-infected women.
Hendrickx, D.M., Aerts,
H.J.W.L., Caiment, F., Clark, D., Ebbels, T.M.D., Evelo, C.T.,
Gmuender, H., Hebels, D.G.A.J., Herwig, R., Hescheler, J., et
al. (2015)
diXa: a data infrastructure for
chemical safety assessment
Bioinforma. Oxf. Engl. 31, 1505–1507
Abstract
MOTIVATION: The field of toxicogenomics (the application of
'-omics' technologies to risk assessment of compound toxicities)
has expanded in the last decade, partly driven by new legislation,
aimed at reducing animal testing in chemical risk assessment but
mainly as a result of a paradigm change in toxicology towards the
use and integration of genome wide data. Many research groups
worldwide have generated large amounts of such toxicogenomics
data. However, there is no centralized repository for archiving
and making these data and associated tools for their analysis
easily available.
RESULTS: The Data Infrastructure for Chemical Safety Assessment
(diXa) is a robust and sustainable infrastructure storing
toxicogenomics data. A central data warehouse is connected to a
portal with links to chemical information and molecular and
phenotype data. diXa is publicly available through a user-friendly
web interface. New data can be readily deposited into diXa using
guidelines and templates available online. Analysis descriptions
and tools for interrogating the data are available via the diXa
portal.
Rossner, P., Tulupova, E., Rossnerova,
A., Libalova, H., Honkova, K., Gmuender, H., Pastorkova, A.,
Svecova, V., Topinka, J., and Sram, R.J. (2015)
Reduced gene expression levels
after chronic exposure to high concentrations of air pollutants
Mutat. Res. 780, 60–70
Abstract
We analyzed the ability of particulate matter (PM) and chemicals
adsorbed onto it to induce diverse gene expression profiles in
subjects living in two regions of the Czech Republic differing in
levels and sources of the air pollution. A total of 312 samples
from polluted Ostrava region and 154 control samples from Prague
were collected in winter 2009, summer 2009 and winter 2010. The
highest concentrations of air pollutants were detected in winter
2010 when the subjects were exposed to: PM of aerodynamic diameter
<2.5 μm (PM2.5) (70 vs. 44.9 μg/m3); benzo[a]pyrene
(9.02 vs. 2.56 ng/m3) and benzene (10.2 vs. 5.5 μg/m3)
in Ostrava and Prague, respectively. Global gene expression
analysis of total RNA extracted from leukocytes was performed
using Illumina Expression BeadChips microarrays. The expression of
selected genes was verified by quantitative real-time PCR
(qRT-PCR). Gene expression profiles differed by locations and
seasons. Despite lower concentrations of air pollutants a higher
number of differentially expressed genes and affected KEGG (Kyoto
Encyclopedia of Genes and Genomes) pathways was found in subjects
from Prague. In both locations immune response pathways were
affected, in Prague also neurodegenerative diseases-related
pathways. Over-representation of the latter pathways was
associated with the exposure to PM2.5. The qRT-PCR analysis showed
a significant decrease in expression of APEX, ATM,
FAS, GSTM1, IL1B and RAD21
in subjects from Ostrava, in a comparison of winter 2010 and
summer 2009. In Prague, an increase in gene expression was
observed for GADD45A and PTGS2. In conclusion,
high concentrations of pollutants in Ostrava were not associated
with higher number of differentially expressed genes, affected
KEGG pathways and expression levels of selected genes. This
observation suggests that chronic exposure to air pollution may
result in reduced gene expression response with possible negative
health consequences.