From Cellular Characteristics to Disease Diagnosis: Uncovering Phenotypes with Supercells

Cell heterogeneity and the inherent complexity due to the interplay of multiple molecular processes within the cell pose difficult challenges for current single-cell biology. We introduce an approach that identifies a disease phenotype from multiparameter single-cell measurements, which is based on the concept of ‘‘supercell statistics’’, a single-cell-based averaging procedure followed by a machine learning classification scheme. We are able to assess the optimal tradeoff between the number of single cells averaged and the number of measurements needed to capture phenotypic differences between healthy and diseased patients, as well as between different diseases that are difficult to diagnose otherwise. We apply our approach to two kinds of single-cell datasets, addressing the diagnosis of a premature aging disorder using images of cell nuclei, as well as the phenotypes of two non-infectious uveitides (the ocular manifestations of Behc¸et’s disease and sarcoidosis) based on multicolor flow cytometry. In the former case, one nuclear shape measurement taken over a group of 30 cells is sufficient to classify samples as healthy or diseased, in agreement with usual laboratory practice. In the latter, our method is able to identify a minimal set of 5 markers that accurately predict Behc¸et’s disease and sarcoidosis. This is the first time that a quantitative phenotypic distinction between these two diseases has been achieved. To obtain this clear phenotypic signature, about one hundred CD8+ T cells need to be measured. Although the molecular markers identified have been reported to be important players in autoimmune disorders, this is the first report pointing out that CD8+ T cells can be used to distinguish two systemic inflammatory diseases. Beyond these specific cases, the approach proposed here is applicable to datasets generated by other kinds of state-of-the-art and forthcoming single-cell technologies, such as multidimensional mass cytometry, single-cell gene expression, and single-cell full genome sequencing techniques.Fil: Candia, Julian Marcelo. University of Maryland; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física de Líquidos y Sistemas Biológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física de Líquidos y Sistemas Biológicos; ArgentinaFil: Maunu, Ryan. University of Maryland; Estados UnidosFil: Driscoll, Meghan. University of Maryland; Estados UnidosFil: Biancotto, Angélique. National Institutes of Health; Estados UnidosFil: Dagur, Pradeep. National Institutes of Health; Estados UnidosFil: McCoy Jr., J Philip. National Institutes of Health; Estados UnidosFil: Nida Sen, H.. National Institutes of Health; Estados UnidosFil: Wei, Lai. National Institutes of Health; Estados UnidosFil: Maritan, Amos. Università di Padova; ItaliaFil: Cao, Kan. University of Maryland; Estados UnidosFil: Nussenblatt, Robert B. National Institutes of Health; Estados UnidosFil: Banavar, Jayanth R.. University of Maryland; Estados UnidosFil: Losert, Wolfgang. University of Maryland; Estados Unido

Role of Dendritic Cell Subsets in Immunity and Their Contribution to Non-infectious Uveitis

Dendritic cells (DCs) are a heterogeneous population. Murine DCs consist of conventional DCs (cDCs) and plasmacytoid DCs (pDCs). In human, the analogous populations are myeloid DCs (mDCs) and pDCs. Though distinct in phenotypes and functions, studies have shown that these DC subsets may interact or ‘crosstalk’ during immune responses. For example, cDCs may facilitate pDC maturation, while pDCs may enhance antigen presentation of cDCs in certain pathogenic conditions or even take on a cDC phenotype themselves. The role of DCs in non-infectious uveitis has been studied primarily in the experimental autoimmune uveitis mouse model and to a more limited extent in patients. Recent evidence shows that the number, phenotype and function of DC subsets are altered in this disease. We provide an overview of selected recent developments of pDCs and cDCs/mDCs, with special attention to their interaction and the dual roles of DC subsets in non-infectious uveitis

Heterogeneity of primary outcome measures used in clinical trials of treatments for intermediate, posterior, and panuveitis

BACKGROUND: Uveitis describes a heterogeneous group of conditions characterized by intraocular inflammation. Since most of the sight-threatening forms of uveitis are individually rare, there has been an increasing tendency for clinical trials to group distinct uveitis syndromes together despite clear variations in phenotype which may reflect real aetiological and pathogenetic differences. Furthermore this grouping of distinct syndromes, and the range of manifestations within each uveitis syndrome, leads to a wide range of possible outcome measures. In this study we wished to review the degree of consensus or otherwise in the choice of primary outcome measures for registered clinical trials related to uveitis. METHODS: Systematic review of data provided in clinical trial registries describing clinical trials dealing with medical treatment of intermediate, posterior, or panuveitis through 01 October 2013. We reviewed 15 on-line clinical trial registries approved by the International Committee of Medical Journal Editors. We identified all that met the following inclusion criteria: prospective, interventional design; target populations with intermediate, posterior or panuveitis; and one or more pre-specified outcome measures that were related to uveitis. Primary outcome measures were classified in terms of type (efficacy or safety or both; single, composite, or multiple); dimension (disease activity, disease damage, measured or patient-reported visual function); and domain (the specific study variable being measured). RESULTS: Of 195 registered uveitis studies, we identified 104 clinical trials that met inclusion criteria. There were 14 different domains used as primary outcome measures. Among clinical trials that utilized primary outcome measures of treatment efficacy (n = 94), 70 (74 %) used a measure of disease activity (vitreous haze in 40/70 [57 %]; macular oedema in 19/70 [27 %]) and 49 (70 %) used a measure of visual function (visual acuity in all cases). Multiple primary outcome measures were used in 23 (22 %) of 104 clinical trials. With regard to quality, in 12 (12 %) of 104 clinical trials, outcome measures were poorly defined. No clinical trial utilized a patient-reported study variable as primary outcome measure. CONCLUSIONS: This systematic review highlights the heterogeneity of outcome measures used in recent clinical trials for intermediate, posterior, and panuveitis. Current designs prioritize clinician-observed measures of disease activity and measurement of visual function as outcome measures. This apparent lack of consensus regarding outcome measures for the study of uveitis is a concern, as it prevents comparison of studies and meta-analyses, and weakens the evidence available to stake-holders, from patients to clinicians to regulators, regarding the efficacy and value of a given treatment

Translational Medicine - doing it backwards

In recent years the concept of "translational medicine" has been advanced in an attempt to catalyze the medical applications of basic biomedical research. However, there has been little discussion about the readiness of scientists themselves to respond to what we believe is a required new approach to scientific discovery if this new concept is to bear fruit. The present paradigm of hypothesis-driven research poorly suits the needs of biomedical research unless efforts are spent in identifying clinically relevant hypotheses. The dominant funding system favors hypotheses born from model systems and not humans, bypassing the Baconian principle of relevant observations and experimentation before hypotheses. Here, we argue that that this attitude has born two unfortunate results: lack of sufficient rigor in selecting hypotheses relevant to human disease and limitations of most clinical studies to certain outcome parameters rather than expanding knowledge of human pathophysiology; an illogical approach to translational medicine. If we wish to remain true to our responsibility and duty of performing research relevant to human disease, we must begin to think about fundamental new approaches

The status of clinical trials: Cause for concern

<p>Abstract</p> <p>Background</p> <p>Americans see clinical research as important, with over 15 million American residents participating in NIH-sponsored studies in 2008 and growing yearly.</p> <p>Methods</p> <p>Documents reporting NIH supported Clinical Research projects were reviewed.</p> <p>Results</p> <p>When compared with other studies, the number of interventional Phase III and Phase IV trials have decreased from 20% to 4.4% from 1994-2008.</p> <p>Conclusions</p> <p>This finding most likely has occurred for several reasons. One reason is that the physician lacks an infrastructure for designing and carrying out trials. This lack is because of an absence of a coordinated effort to train clinical trialists. It is clear that the Nation needs a more purposeful approach to developing and maintaining the infrastructure for designing and conducting clinical trials. Building it de novo trial by trial is profoundly inefficient, to say nothing about time consuming and error prone.</p

Autoimmune and autoinflammatory mechanisms in uveitis

The eye, as currently viewed, is neither immunologically ignorant nor sequestered from the systemic environment. The eye utilises distinct immunoregulatory mechanisms to preserve tissue and cellular function in the face of immune-mediated insult; clinically, inflammation following such an insult is termed uveitis. The intra-ocular inflammation in uveitis may be clinically obvious as a result of infection (e.g. toxoplasma, herpes), but in the main infection, if any, remains covert. We now recognise that healthy tissues including the retina have regulatory mechanisms imparted by control of myeloid cells through receptors (e.g. CD200R) and soluble inhibitory factors (e.g. alpha-MSH), regulation of the blood retinal barrier, and active immune surveillance. Once homoeostasis has been disrupted and inflammation ensues, the mechanisms to regulate inflammation, including T cell apoptosis, generation of Treg cells, and myeloid cell suppression in situ, are less successful. Why inflammation becomes persistent remains unknown, but extrapolating from animal models, possibilities include differential trafficking of T cells from the retina, residency of CD8(+) T cells, and alterations of myeloid cell phenotype and function. Translating lessons learned from animal models to humans has been helped by system biology approaches and informatics, which suggest that diseased animals and people share similar changes in T cell phenotypes and monocyte function to date. Together the data infer a possible cryptic infectious drive in uveitis that unlocks and drives persistent autoimmune responses, or promotes further innate immune responses. Thus there may be many mechanisms in common with those observed in autoinflammatory disorders

Overall and cancer related mortality among patients with ocular inflammation treated with immunosuppressive drugs: retrospective cohort study

Context Whether immunosuppressive treatment adversely affects survival is unclear

The Risk of Intraocular Pressure Elevation in Pediatric Noninfectious Uveitis

To characterize the risk and risk factors for intraocular pressure (IOP) elevation in pediatric non-infectious uveitis