title: From cellular characteristics to disease diagnosis: uncovering phenotypes with supercells.
abstract: 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 Behçet'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 Behçet'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.
authors.affiliation: Department of Physics, University of Maryland, College Park, Maryland, United States of America ; School of Medicine, University of Maryland, Baltimore, Maryland, United States of America ; IFLYSIB and CONICET, University of La Plata, La Plata, Argentina.candia@umd.edu          .
authors.forename: Julián
authors.initials: J
authors.lastname: Candia
authors.affiliation: Department of Physics, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Ryan
authors.initials: R
authors.lastname: Maunu
authors.affiliation: Department of Physics, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Meghan
authors.initials: M
authors.lastname: Driscoll
authors.affiliation: Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, Maryland, United States of America, Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Angélique
authors.initials: A
authors.lastname: Biancotto
authors.affiliation: Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Pradeep
authors.initials: P
authors.lastname: Dagur
authors.affiliation: Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, Maryland, United States of America,; Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: J Philip
authors.initials: JP
authors.lastname: McCoy
authors.affiliation: Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: H Nida
authors.initials: HN
authors.lastname: Sen
authors.affiliation: Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Lai
authors.initials: L
authors.lastname: Wei
authors.affiliation: Dipartimento di Fisica “G. Galilei,” Università di Padova, Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, Padua, Italy.
authors.forename: Amos
authors.initials: A
authors.lastname: Maritan
authors.affiliation: Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Kan
authors.initials: K
authors.lastname: Cao
authors.affiliation: Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Robert B
authors.initials: RB
authors.lastname: Nussenblatt
authors.affiliation: Department of Physics, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Jayanth R
authors.initials: JR
authors.lastname: Banavar
authors.affiliation: Department of Physics, University of Maryland, College Park, Maryland, United States of America.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Losert
mesh_terms: D001185:Artificial Intelligence; D003933:Diagnosis; D006801:Humans
references.citation: Am J Clin Pathol. 2012 Jan;137(1):75-85
references.pmid: 22180480
references.citation: Sci Transl Med. 2011 Jun 29;3(89):89ra58
references.pmid: 21715679
references.citation: Cytometry A. 2012 Dec;81(12):1022-30
references.pmid: 23044634
references.citation: Proc Natl Acad Sci U S A. 2005 Sep 6;102(36):12879-84
references.pmid: 16129833
references.citation: Cytometry B Clin Cytom. 2010;78 Suppl 1:S69-82
references.pmid: 20839340
references.citation: J Theor Biol. 2008 Feb 7;250(3):547-59
references.pmid: 18045620
references.citation: Proc Natl Acad Sci U S A. 2000 Jul 18;97(15):8409-14
references.pmid: 10890920
references.citation: J Immunol. 2009 Jun 1;182(11):7317-24
references.pmid: 19454729
references.citation: J Autoimmun. 2011 Dec;37(4):319-27
references.pmid: 21959269
references.citation: PLoS One. 2012;7(5):e37038
references.pmid: 22662133
references.citation: Nat Methods. 2009 May;6(5):377-82
references.pmid: 19349980
references.citation: Nat Cell Biol. 2012 Nov;14(11):1139-47
references.pmid: 23103910
references.citation: Bioinformatics. 2012 Apr 1;28(7):1009-16
references.pmid: 22383736
references.citation: BMC Bioinformatics. 2009 Apr 09;10:106
references.pmid: 19358741
references.citation: Aging (Albany NY). 2012 Feb;4(2):119-32
references.pmid: 22354768
references.citation: Bioinformatics. 2012 Aug 1;28(15):2052-8
references.pmid: 22595209
references.citation: Cell. 2010 May 14;141(4):559-63
references.pmid: 20478246
references.citation: Proc Natl Acad Sci U S A. 2007 Mar 20;104(12):4949-54
references.pmid: 17360355
references.citation: Arch Dermatol Res. 2012 Oct;304(8):639-45
references.pmid: 22310732
references.citation: Brain. 2011 Dec;134(Pt 12):3560-77
references.pmid: 22058139
references.citation: Science. 2005 Apr 22;308(5721):523-9
references.pmid: 15845847
references.citation: Phys Rev Lett. 2011 Jun 10;106(23):238106
references.pmid: 21770549
references.citation: Science. 2011 May 6;332(6030):677-8
references.pmid: 21551055
references.citation: Nat Methods. 2013 Mar;10(3):228-38
references.pmid: 23396282
references.citation: Dev Cell. 2012 May 15;22(5):1079-91
references.pmid: 22542839
references.citation: Nature. 2008 May 22;453(7194):544-7
references.pmid: 18497826
references.citation: Proc Natl Acad Sci U S A. 2012 Dec 11;109(50):20667-72
references.pmid: 23188796
references.citation: Science. 2011 May 6;332(6030):687-96
references.pmid: 21551058
references.citation: J Clin Immunol. 2013 May;33(4):767-74
references.pmid: 23435610
references.citation: Proc Natl Acad Sci U S A. 2010 Jan 12;107(2):610-5
references.pmid: 20080726
references.citation: Nat Rev Genet. 2006 Dec;7(12):940-52
references.pmid: 17139325