Noninvasive assessment of cardiovascular health

Includes bibliographical references.Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.Cardiovascular health is currently assessed by a collection of hemodynamic parameters many of which can only be measured by invasive methods often requiring hospitalization. A non-invasive approach of evaluating some of these parameters, such as systemic vascular resistance (SVR), maximum left ventricular elasticity (ELV), end diastolic volume (VED), cardiac output and others, has been established. The method has three components: (1) a distributed model of the human cardiovascular system (Ozawa) to generate a solution library that spans the anticipated range of parameter values, (2) a method for establishing the multi-dimensional relationship between features computed from the arterial blood pressure and/or flow traces (e.g., mean arterial pressure, pulse amplitude, mean flow velocity) and the critical hemodynamic parameters, and (3) a parameter estimation method that provides the best fit between measured and computed data. Sensitivity analyses are used to determine the critical parameters that must be allowed to vary, and those that can be assumed to be constant in the model. Given the brachial pressure and velocity profiles (which can be measured non-invasively), this method can estimate SVR with an error of less than 3%, and ELv and VED with less than 10% errors. Measurements on healthy volunteers and patients were conducted in Brigham and Women's Hospital, Boston, MA. Carotid, brachial and radial pressures were measured by tonometry and velocities at corresponding locations were measured by ultrasound. Reasonable agreement is found between the measured pressure and velocity curves and the reconstructed ones. Invasive measurements of hemodynamic parameters are available for two of the patients, which are compared to predictions to evaluate the performance of parameter estimation routines.by Xinshu Xiao.S.M

Principal component based system identification and its application to the study of cardiovascular regulation

Includes bibliographical references (p. 197-212).Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2004.(cont.) Our methods analyze the coupling between instantaneous lung volume and heart rate and, subsequently, derive representative indices of parasympathetic and sympathetic control based on physiological and experimental findings. The validity of each method is evaluated via experimental data collected following interventions with known effect on the parasympathetic or sympathetic control. With the above techniques, this thesis explores an important topic in the field of space medicine: effects of simulated microgravity on cardiac autonomic control and orthostatic intolerance (OI). Experimental data from a prolonged bed rest study (simulation of microgravity condition) are analyzed and the conclusions are: 1) prolonged bed rest may impair autonomic control of heart rate; 2) orthostatic intolerance after bed rest is associated with impaired sympathetic responsiveness; 3) there may be a pre-bed rest predisposition to the development of OI after bed rest. These findings may have significance for studying Earth-bound orthostatic hypotension as well as for designing effective countermeasures to post-flight OI. In addition, they also indicate the efficacy of our proposed methods for autonomic function quantification.System identification is an effective approach for the quantitative study of physiologic systems. It deals with the problem of building mathematical models based on observed data and enables a dynamical characterization of the underlying physiologic mechanisms specific to the individual being studied. In this thesis, we develop and validate a new linear time-invariant system identification approach which is based on a weighted-principal component regression (WPCR) method. An important feature of this approach is its asymptotic frequency-selective property in solving time-domain parametric system identification problems. Owing to this property, data-specific candidate models can be built by considering the dominant frequency components inherent in the input (and output) signals, which is advantageous when the signals are colored, as are most physiologic signals. The efficacy of this method in modeling open-loop and closed-loop systems is demonstrated with respect to simulated and experimental data. In conjunction with the WPCR-based system identification approach, we propose new methods to noninvasively quantify cardiac autonomic control. Such quantification is important in understanding basic pathophysiological mechanisms or in patient monitoring, treatment design and follow-up.by Xinshu Xiao.Ph.D

Global analyses of endonucleolytic cleavage in mammals reveal expanded repertoires of cleavage-inducing small RNAs and their targets.

In mammals, small RNAs are important players in post-transcriptional gene regulation. While their roles in mRNA destabilization and translational repression are well appreciated, their involvement in endonucleolytic cleavage of target RNAs is poorly understood. Very few microRNAs are known to guide RNA cleavage. Endogenous small interfering RNAs are expected to induce target cleavage, but their target genes remain largely unknown. We report a systematic study of small RNA-mediated endonucleolytic cleavage in mouse through integrative analysis of small RNA and degradome sequencing data without imposing any bias toward known small RNAs. Hundreds of small cleavage-inducing RNAs and their cognate target genes were identified, significantly expanding the repertoire of known small RNA-guided cleavage events. Strikingly, both small RNAs and their target sites demonstrated significant overlap with retrotransposons, providing evidence for the long-standing speculation that retrotransposable elements in mRNAs are leveraged as signals for gene targeting. Furthermore, our analysis showed that the RNA cleavage pathway is also present in human cells but affecting a different repertoire of retrotransposons. These results show that small RNA-guided cleavage is more widespread than previously appreciated. Their impact on retrotransposons in non-coding regions shed light on important aspects of mammalian gene regulation

Splice site strength–dependent activity and genetic buffering by poly-G runs

Pre-mRNA splicing is regulated through the combinatorial activity of RNA motifs, including splice sites and splicing regulatory elements. Here we show that the activity of the G-run (polyguanine sequence) class of splicing enhancer elements is approx4-fold higher when adjacent to intermediate strength 5' splice sites (ss) than when adjacent to weak 5' ss, and approx1.3-fold higher relative to strong 5' ss. We observed this dependence on 5' ss strength in both splicing reporters and in global microarray and mRNA-Seq analyses of splicing changes following RNA interference against heterogeneous nuclear ribonucleoprotein (hnRNP) H, which cross-linked to G-runs adjacent to many regulated exons. An exon's responsiveness to changes in hnRNP H levels therefore depends in a complex way on G-run abundance and 5' ss strength. This pattern of activity enables G-runs and hnRNP H to buffer the effects of 5' ss mutations, augmenting both the frequency of 5' ss polymorphism and the evolution of new splicing patterns. Certain other splicing factors may function similarly.American Heart AssociationHuman Frontier Science Program (Strasbourg, France)National Institutes of Health (U.S.)National Science Foundation (U.S.) (equipment grant DBI-0821391

FoxP2 isoforms delineate spatiotemporal transcriptional networks for vocal learning in the zebra finch.

Human speech is one of the few examples of vocal learning among mammals yet ~half of avian species exhibit this ability. Its neurogenetic basis is largely unknown beyond a shared requirement for FoxP2 in both humans and zebra finches. We manipulated FoxP2 isoforms in Area X, a song-specific region of the avian striatopallidum analogous to human anterior striatum, during a critical period for song development. We delineate, for the first time, unique contributions of each isoform to vocal learning. Weighted gene coexpression network analysis of RNA-seq data revealed gene modules correlated to singing, learning, or vocal variability. Coexpression related to singing was found in juvenile and adult Area X whereas coexpression correlated to learning was unique to juveniles. The confluence of learning and singing coexpression in juvenile Area X may underscore molecular processes that drive vocal learning in young zebra finches and, by analogy, humans

Inference of Splicing Regulatory Activities by Sequence Neighborhood Analysis

Sequence-specific recognition of nucleic-acid motifs is critical to many cellular processes. We have developed a new and general method called Neighborhood Inference (NI) that predicts sequences with activity in regulating a biochemical process based on the local density of known sites in sequence space. Applied to the problem of RNA splicing regulation, NI was used to predict hundreds of new exonic splicing enhancer (ESE) and silencer (ESS) hexanucleotides from known human ESEs and ESSs. These predictions were supported by cross-validation analysis, by analysis of published splicing regulatory activity data, by sequence-conservation analysis, and by measurement of the splicing regulatory activity of 24 novel predicted ESEs, ESSs, and neutral sequences using an in vivo splicing reporter assay. These results demonstrate the ability of NI to accurately predict splicing regulatory activity and show that the scope of exonic splicing regulatory elements is substantially larger than previously anticipated. Analysis of orthologous exons in four mammals showed that the NI score of ESEs, a measure of function, is much more highly conserved above background than ESE primary sequence. This observation indicates a high degree of selection for ESE activity in mammalian exons, with surprisingly frequent interchangeability between ESE sequences

Interoceptive Regulation of Skeletal Tissue Homeostasis and Repair

Recent studies have determined that the nervous system can sense and respond to signals from skeletal tissue, a process known as skeletal interoception, which is crucial for maintaining bone homeostasis. The hypothalamus, located in the central nervous system (CNS), plays a key role in processing interoceptive signals and regulating bone homeostasis through the autonomic nervous system, neuropeptide release, and neuroendocrine mechanisms. These mechanisms control the differentiation of mesenchymal stem cells into osteoblasts (OBs), the activation of osteoclasts (OCs), and the functional activities of bone cells. Sensory nerves extensively innervate skeletal tissues, facilitating the transmission of interoceptive signals to the CNS. This review provides a comprehensive overview of current research on the generation and coordination of skeletal interoceptive signals by the CNS to maintain bone homeostasis and their potential role in pathological conditions. The findings expand our understanding of intersystem communication in bone biology and may have implications for developing novel therapeutic strategies for bone diseases

Splicing-specific transcriptome-wide association uncovers genetic mechanisms for schizophrenia

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area

Loss of MECP2 Leads to Activation of P53 and Neuronal Senescence.

To determine the role for mutations of MECP2 in Rett syndrome, we generated isogenic lines of human induced pluripotent stem cells, neural progenitor cells, and neurons from patient fibroblasts with and without MECP2 expression in an attempt to recapitulate disease phenotypes in vitro. Molecular profiling uncovered neuronal-specific gene expression changes, including induction of a senescence-associated secretory phenotype (SASP) program. Patient-derived neurons made without MECP2 showed signs of stress, including induction of P53, and senescence. The induction of P53 appeared to affect dendritic branching in Rett neurons, as P53 inhibition restored dendritic complexity. The induction of P53 targets was also detectable in analyses of human Rett patient brain, suggesting that this disease-in-a-dish model can provide relevant insights into the human disorder