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Cardiovascular diseases (CVDs) remain the leading cause of death worldwide. Many studies have provided evidence that both genetic and environmental factors induce atherosclerosis, leading thus to cardiovascular complications. Atherosclerosis is an inflammatory disease, and aging is strongly associated with the development of atherosclerosis. Recent experimental evidence suggests that clonal hematopoiesis (CH) is an emerging cardiovascular risk factor that contributes to the development of atherosclerosis and cardiac dysfunction and exacerbates cardiovascular diseases. CH is caused by somatic mutations in recurrent genes in hematopoietic stem cells, leading to the clonal expansion of mutated blood cell clones. Many of the mutated genes are known in the context of myeloid neoplasms. However, only some individuals carrying CH mutations develop hematologic abnormalities. CH is clearly age dependent and is not rare: at least 10%–20% of people >70 years old carry CH. The newly discovered association between myeloid leukemia-driver mutations and the progression of CVDs has raised medical interest. In this review, we summarize the current view on the contribution of CH in different cardiovascular diseases, CVD risk assessment, patient stratification, and the development of novel therapeutic strategies.
Despite advances in the medical and interventional clinical management of patients, cardiovascular diseases (CVDs) remain the leading cause of death worldwide. It is well appreciated that atherosclerosis represents the underlying cause of most CVDs [1]. Atherosclerosis is a chronic inflammatory disease that leads to the formation of atheromatous lesions in the vessel associated with increased recruitment, adhesion, and proliferation of different leukocyte subsets to the endothelium [1]. Several cardiovascular risk factors (CRFs) have been found to enhance the risk of CVD (Figure 1), including hypercholesterolemia (HC), diabetes mellitus (DM), hypertension, metabolic syndrome, obesity, and smoking [2]. Inflammation plays a crucial role in the development of CVDs and several studies have reported that CRFs enhance production of myeloid cells and multipotent hematopoietic progenitors in the bone marrow and in this way may promote atherosclerosis and disease development [3].
Attention-Deficit/Hyperactivity Disorder (ADHD) is frequently comorbid with other psychiatric disorders and also with somatic conditions, such as obesity. In addition to the clinical overlap, significant genetic correlations have been found between ADHD and obesity as well as body mass index (BMI). The biological mechanisms driving this association are largely unknown, but some candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the link between ADHD and obesity measures. Using the largest GWAS summary statistics currently available for ADHD (N=53,293), BMI (N=681,275), and obesity (N=98,697), we first tested the association of dopaminergic and circadian rhythm gene sets with each phenotype. This hypothesis-driven approach showed that the dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), while the circadian rhythm gene set was associated with BMI only (P=1.28×10−3). We then took a data-driven approach by conducting genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. This approach further supported the implication of dopaminergic signaling in the link between ADHD and obesity measures, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was significantly enriched in both the ADHD-BMI and ADHD-obesity gene-based meta-analysis results. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering the shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of preventive interventions and/or efficient treatment of these conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720–10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81×10−3) and BMI (P=1.63×10−5), the circadian rhythm was associated with BMI (P=1.28×10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7×10−3; replication data P=3.9×10−2) – a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
The ubiquitin-related SUMO system represents a versatile post-translational modification pathway controlling a variety of cellular signalling networks. In mammalian cells, lysine residues of target proteins can be covalently modified with three SUMO isoforms (SUMO1, SUMO2 and SUMO3) resulting in conjugation of either single SUMO moieties or formation of poly-SUMO chains. Importantly, SUMO modification is a reversible process, where the deconjugation of SUMO from its substrates is mediated by SUMO proteases. In humans, the best-characterized subfamily is the SENP family of SUMO-specific isopeptidases comprised of SENP1-3 and SENP5-7. For undisturbed cellular signalling events, a proper balance of SUMO conjugation and deconjugation is crucial. SENPs fulfil the important function of counteracting SUMOylation. A key question is how the relatively low number of SENPs specifically controls the SUMOylation status of hundreds of cellular proteins.
The aim of this thesis was to uncover the regulation and substrate specificity of distinct SUMO isopeptidases in order to better understand their role in cellular signalling pathways.
In the first part of this work, we investigated the influence of hypoxia on SUMO signalling, in particular on the activity of SENPs. Importantly, we found that the catalytic activity of distinct SENPs (especially SENP1 and SENP3) is strongly but reversibly diminished under low oxygen. As a consequence, the SUMO modification of a specific subset of proteins is changed under hypoxia. We specifically identified proteins being hyperSUMOylated after 24 hours of hypoxia by SUMO1 immunoprecipitation followed by mass spectrometry. We further validated the transcriptional co-repressor BHLHE40 as hypoxic SUMO target and confirmed SENP1 as responsible isopeptidase for deconjugation of SUMOylated BHLHE40. We provide evidence that SUMO conjugation to BHLHE40 enhances its repressive functions on the expression of the metabolic master regulator PGC-1α. Therefore we propose a model where inactivation of SENP1 under hypoxia results in SUMOylated BHLHE40, possibly contributing to metabolic reprogramming under hypoxia.
To get insight into substrate selectivity of SENP family members, in particular SENP3 and SENP6, we choose a proteomic profiling strategy. For the identification of specific SUMO substrates controlled by SENP3, we applied a large-scale IP-MS approach in SENP3 KO and WT cells. The most strongly induced SUMO targets in the absence of SENP3 were key regulators of ribosome maturation. We identified factors involved in the remodelling of both 90S and 60S pre-ribosomes. SENP3 has already been described as being critically involved in maturation of the pre-60S subunit and 28S rRNA processing. Previously described SENP3-regulated master targets in this process are the ribosome maturation factors PELP1 and Las1L. Importantly, both were also identified as the most significantly regulated SENP3 targets in our unbiased proteomic approach. Importantly, however, enhanced SUMOylation was also detected on 90S-associated regulators, such as BMS1. Altogether, these data strengthen the functional link between SENP3 and ribosome biogenesis and point to a role of SENP3 beyond 60S maturation.
In addition to SENP3, we explored the substrate specificity of SENP6, which mainly acts on polymeric SUMO2/3 chains. Applying a proteomic profiling strategy, we were able to identify SENP6-controlled SUMO networks functioning in DNA damage response as well as chromatin organization. We demonstrated that SENP6 reverses polySUMOylation of several subunits of the cohesin complex, thereby regulating the SUMOylation status and chromatin association of this complex. Furthermore, we found a tight interaction of SENP6 with the hPSO4/PRP19 complex, involved in DNA damage response by activation of the ATR-CHK1 signalling cascade. In cells depleted of SENP6, we observe deficient recruitment of the co-activator ATRIP to chromatin which results in diminished CHK1 activation. We therefore illustrate a general role of SENP6 in the control of chromatin-associated protein networks involved in genome integrity and chromatin organization.
Doxorubicin-loaded human serum albumin nanoparticles overcome transporter-mediated drug resistance
(2019)
Resistance to systemic drug therapies is a major reason for the failure of anti-cancer therapies. Here, we tested doxorubicin-loaded human serum albumin (HSA) nanoparticles in the neuroblastoma cell line UKF-NB-3 and its ABCB1-expressing sublines adapted to vincristine (UKF-NB-3rVCR1) and doxorubicin (UKF-NB-3rDOX20). Doxorubicin-loaded nanoparticles displayed increased anti-cancer activity in UKF-NB-3rVCR1 and UKF-NB-3rDOX20 cells relative to doxorubicin solution, but not in UKF-NB-3 cells. UKF-NB-3rVCR1 cells were resensitised by nanoparticle-encapsulated doxorubicin to the level of UKF-NB-3 cells. UKF-NB-3rDOX20 cells displayed a more pronounced resistance phenotype than UKF-NB-3rVCR1 cells and were not re-sensitised by doxorubicin-loaded nanoparticles to the level of parental cells. ABCB1 inhibition using zosuquidar resulted in similar effects like nanoparticle incorporation, indicating that doxorubicin-loaded nanoparticles circumvent ABCB1-mediated drug efflux. The limited re-sensitisation of UKF-NB-3rDOX20 cells to doxorubicin by circumvention of ABCB1-mediated efflux is probably due to the presence of multiple doxorubicin resistance mechanisms. So far, ABCB1 inhibitors have failed in clinical trials, probably because systemic ABCB1 inhibition results in a modified body distribution of its many substrates including drugs, xenobiotics, and other molecules. HSA nanoparticles may provide an alternative, more specific way to overcome transporter-mediated resistance.
Resistance to systemic drug therapy is a major reason for the failure of anticancer therapies. Here, we tested doxorubicin-loaded human serum albumin (HSA) nanoparticles in the neuroblastoma cell line UKF-NB-3 and its ABCB1-expressing sublines adapted to vincristine (UKF-NB-3rVCR1) and doxorubicin (UKF-NB-3rDOX20). Doxorubicin-loaded nanoparticles displayed increased anticancer activity in UKF-NB-3rVCR1 and UKF-NB-3rDOX20 cells relative to doxorubicin solution, but not in UKF-NB-3 cells. UKF-NB-3rVCR1 cells were re-sensitised by nanoparticle-encapsulated doxorubicin to the level of UKF-NB-3 cells. UKF-NB-3rDOX20 cells displayed a more pronounced resistance phenotype than UKF-NB-3rVCR1 cells and were not re-sensitised by doxorubicin-loaded nanoparticles to the level of parental cells. ABCB1 inhibition using zosuquidar resulted in similar effects like nanoparticle incorporation, indicating that doxorubicin-loaded nanoparticles successfully circumvent ABCB1-mediated drug efflux. The limited re-sensitisation of UKF-NB-3rDOX20 cells to doxorubicin by circumvention of ABCB1-mediated efflux is probably due to the presence of multiple doxorubicin resistance mechanisms. So far, ABCB1 inhibitors have failed in clinical trials probably because systemic ABCB1 inhibition results in a modified body distribution of its many substrates including drugs, xenobiotics, and other molecules. HSA nanoparticles may provide an alternative, more specific way to overcome transporter-mediated resistance.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
Cross-frequency coupling of sleep oscillations is thought to mediate memory consolidation. While the hippocampus is deemed central to this process, detailed knowledge of which oscillatory rhythms interact in the sleeping human hippocampus is lacking. Combining intracranial hippocampal and non-invasive electroencephalography from twelve neurosurgical patients, we characterized spectral power and coupling during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Hippocampal coupling was extensive, with the majority of channels expressing spectral interactions. NREM consistently showed delta–ripple coupling, but ripples were also modulated by slow oscillations (SOs) and sleep spindles. SO–delta and SO–theta coupling, as well as interactions between delta/theta and spindle/beta frequencies also occurred. During REM, limited interactions between delta/theta and beta frequencies emerged. Moreover, oscillatory organization differed substantially between i) hippocampus and scalp, ii) sites along the anterior-posterior hippocampal axis, and iii) individuals. Overall, these results extend and refine our understanding of hippocampal sleep oscillations.
Background: Iron deficiency anemia is common in pregnancy with a prevalence of approximately 16% in Austria; however, international guideline recommendations on screening and subsequent treatment with iron preparations are inconsistent. The aim of this study was to find out how often pregnant women take iron-containing supplements, and who recommended them. As hemoglobin data were available for a sub-group of women, hemoglobin status during pregnancy and associated consumption of iron-containing medications were also recorded.
Methods: This cross-sectional study was conducted at the Mother-Child-Booklet service center of the Styrian Health Insurance Fund in Graz, Austria. A questionnaire containing seven questions was developed. Absolute and relative numbers were determined, and corresponding 95% confidence intervals calculated using bootstrapping techniques.
Results: A total of 325 women completed the questionnaire, 11% had been diagnosed with anemia before becoming pregnant, 67% reported taking iron-containing compounds. The women reported taking 45 different products but 61% took 1 of 3 different supplements. Overall, 185 (57%) women had not been diagnosed with anemia before becoming pregnant but reported taking an iron-containing supplement and 89% of the women took supplements on the recommendation of their physician. Of the 202 women whose hemoglobin status was assessed, 92% were found not to be anemic.
Conclusion: Overall, 67% of pregnant women took iron-containing compounds, irrespective of whether they were deficient in iron. Physicians were generally responsible for advising them to take them. No standardized procedure is available on which to base the decision whether to take iron during pregnancy, even in guidelines. As most guidelines only recommend taking iron supplements in cases of anemia, the high percentage of women taking them in Austria is incomprehensible.e
Highlights
• The goal was to assess the intra- and inter-scanner reproducibility of qMRI data.
• Mean scan-rescan variations were not exceeding 2.14%.
• Mean inter-scanner model deviations were not exceeding 5.21%.
• Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low.
Abstract
Background: Quantitative MRI (qMRI) techniques allow assessing cerebral tissue properties. However, previous studies on the accuracy of quantitative T1 and T2 mapping reported a scanner model bias of up to 10% for T1 and up to 23% for T2. Such differences would render multi-centre qMRI studies difficult and raise fundamental questions about the general precision of qMRI. A problem in previous studies was that different methods were used for qMRI parameter mapping or for measuring the transmitted radio frequency field B1 which is critical for qMRI techniques requiring corrections for B1 non-uniformities.
Aims: The goal was to assess the intra- and inter-scanner reproducibility of qMRI data at 3 T, using two different scanner models from the same vendor with exactly the same multiparametric acquisition protocol.
Methods: Proton density (PD), T1, T2* and T2 mapping was performed on healthy subjects and on a phantom, performing each measurement twice for each of two scanner models. Although the scanners had different hardware and software versions, identical imaging sequences were used for PD, T1 and T2* mapping, adapting the codes of an existing protocol on the older system line by line to match the software version of the newer scanner. For T2-mapping, the respective manufacturer’s sequence was used which depended on the software version. However, system-dependent corrections were carried out in this case. Reproducibility was assessed by average values in regions of interest.
Results: Mean scan-rescan variations were not exceeding 2.14%, with average values of 1.23% and 1.56% for the new and old system, respectively. Inter-scanner model deviations were not exceeding 5.21% with average values of about 2.2–3.8% for PD, 2.5–3.0% for T2*, 1.6–3.1% for T1 and 3.3–5.2% for T2.
Conclusions: Provided that identical acquisition sequences are used, discrepancies between qMRI data acquired with different scanner models are low. The level of systematic differences reported in this work may help to interpret multi-centre data.