(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT)
`(19) World Intellectual Property
`Organization
`International Bureau
`
`(10) International Publication Number
`
`(43) International Publication Date
`WO 2012/1 59023 A2
`22 November 201 2 (22.11 .2012) WIPOI PCT
`
`
`é\ll»
`
`(51)
`
`(21)
`
`International Patent Classification: Not classified
`
`International Application N umber:
`
`PCT/US2012/0385 55
`
`(74) Agents: WHITHAM, Michael E. et al.; Whitham Curtis
`Christoflerson & Cook, PC,
`1 1491
`Sunset Hills Road,
`Suite 340, Reston, VA 20190 (US).
`
`(22)
`
`International Filing Date:
`
`18 May 2012 (18.05.2012)
`
`(81)
`
`(25)
`
`(26)
`
`(30)
`
`(71)
`
`(72)
`(75)
`
`Filing Language:
`
`Publication Language:
`
`English
`
`English
`
`Priority Data:
`61/488,019
`61/621,767
`
`l9 lVIay 2011 (19.05.2011)
`9 April 2012 (09.04.2012)
`
`US
`US
`
`Applicants 0hr all designated States except US): VIR-
`GINIA COMMONWEALTH UNIVERSITY [US/US];
`800 East Leigh Street, Suite 113, Richmond, VA 23219
`(US). THE U.S DEPARTMENT OF VETRANS AF-
`FAIRS [US/US]; 810 Vermont Avenue, Northwest, Wash—
`ington, DC 20420 (US). GEORGE NIASON UNIVER-
`SITY [US/US]; 4400 University Drive, MS 5G5 Research
`Building 1, Room 405, Fairfax, VA 22030 (US).
`
`Inventors; and
`Inventors/Applicants (fiar US only): BAJAJ, Jasmohan
`[IN/US]; 3121 W Franklin Street, Richmond, VA 23221
`(US). SANYAL, Arun [US/US]; 6998 Oil Millstone
`Drive, Mechanicsville, VA 23111 (US). GILLEVET,
`Patrick M. [CA/US]; 11627 Ayreshire Road, Oakton, VA
`22124 (US).
`
`Designated States (unless otherwise indicated, for every
`kind of national protection available): AE, AG, AL, AM,
`A0, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ,
`CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO,
`DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN,
`IIR, IIU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR,
`KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME,
`MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ,
`OM, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD,
`SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR,
`TT, TZ, UA, UG, US, UZ, vc, VN, ZA, ZM, ZW.
`
`(34)
`
`Designated States (unless otherwise indicated, for every
`kind of regional protection available): ARIPO (BW, GH,
`GM, KE, LR, LS, MW, MZ, NA, RW', SD, SL, SZ, TZ,
`UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ,
`TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK,
`EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV,
`MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM,
`TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW,
`ML, MR, NE, SN, TD, TG).
`Published:
`
`without international search report and to be republished
`upon receipt ofthat report (Rule 48.2(g))
`
`(54) Title: GUT MICROFLORA AS BIOMARKERS FOR THE PROGNOSIS OF CIRRHOSIS AND BRAIN DYSFUNCTION
`
`. m 7
`Vetllonellaceae Dialister
`w
`an. 7/
`Prevoielranc'ghae7other'
`P ravntell anean Prevotella
`BacterIodaceaeBactemides“Tam"e"52%8llttEreala
`TAR
`FIN
`W?
`(CG/ET:
`l
`
`For n(romdnadaceae7
`at
`:teroides
`
`LULRES
`
`Figure 4A
`
`animosptiaceae7ull1er
`
`
`
`7ulher/fl;:raoeae_flare
`
`
`
`\
`si®wJ. _ ,mm”M‘ Entembac EIiaceae
`7,
`fVeilone e
`Enterobacteriaceac7/ \
`E h
`-
`I\
`Ilaeae Phascolarctobacteiium
`(Lachnospiraceae7Rosebuna lncefiae Sedis
`/1
`XIV_BIautia
`sc erichia/Shi alla
`
`“ft?Er‘\
`
`Rummocoocaceae7Faecalibameriumw _ \
`..
`r
`' ErySIpeInIriciIaceae7other
`\
`Propioni-actenazeae mmombacterium
`\
`\
`W
`‘ -
`hm
`Rum IIIOCUCCdCEae_0Li|EF @V
`Rikeneliaoeaefiflstipes
`eptostrep ococcaccaefither
`P
`/W
`ST
`ErySIpeo Ic aceae
`IIriCEhanteI
`€73,522
`
`A.
`SirePtOCOmfioeafirepmmmus
`Ammoria
`
`RIimInococcaceae Osciliibaciet
`
`Staphylo
`ccac_
`Staphylococcus
`
`(57) Abstract: A systems biology approach is used to characterize and relate the intestinal (gut) microbiome of a host organism (e.g.
`a human) to physiological proccsscs Within the host. Information regarding thc types and rclativc amounts of gut microflora is cor-
`related with physiological processes indicative of, e. g, a patient's risk of developing a disease or condition, likelihood of responding
`to a particular treatment, for adjusting treatment protocols, etc. The information is also used to identify novel suitable therapeutic tar—
`gets and/or to develop and monitor the outcome of therapeutic treatments. An exemplary disease/condition is the development of
`hepatic encephalopathy (HE), particularly in patients With liver cirrhosis.
`
`
`
`W02012/159023A2I||||||||||||||||||||||||||||||||||||||||||||||||||I|||||||||||||||||||||||||||||||||||||||||||
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`GUT MICROFLORA AS BIOMARKERS FOR THE PROGNOSIS OF
`
`CERRHOSIS AND BRAIN DYSFUNCTION
`
`DESCRIPTION
`
`BACKGROUND OF THE ENVENTEON
`
`Field ofrhe Invention
`
`10
`
`The invention generally relates to methods for predicting, for patients, a level of risk
`
`fOr developing a disease or condition associated with particular patterns of gut microflora
`
`(microbiome) colonization. in particular, the inventiori provides methods of correlating the
`
`presence or absence and/or relative abundances of gut microflora with a patient’s risk of
`
`developing an associated disease or condition, and deveIOping suitable treatments based on
`
`15
`
`the correlation.
`
`Background 01’th Invention
`
`20
`
`25
`
`30
`
`The human body, consisting of about 100 trillion cells, carries about ten times as
`
`many microorganisms in the intestines. It is estimated that these gut flora have around 100
`
`times as many genes in aggregate as there are in the human genome. Research suggests that
`
`the relationship between gut flora and humans is not merely commensal (a non—harmful
`
`coexistence), but rather a symbiotic relationship. These microorganisms perform a host of
`
`useful functions, such as fermenting unused energy substrates, training the immune system,
`
`forming a protective mucosal biofilm, preventing growth of harmful, pathogenic bacteria,
`
`regulating the development of the gut, producing vitamins for the host (cg. biotin and
`
`vitamin K), producing hormones to direct the host to store fats, producing signaling
`
`molecules that promote homeostasis, metabolizing drugs and xenobiotics, etc. However, in
`
`certain conditions, some species are thought to be capable of causing or promoting disease.
`
`For example, cirrhosis is often complicated by hepatic encephalopathy (HE), a
`
`condition characterized by cognitive impairment and poor survival, and there is evidence
`
`that pathogenic abnormalities in HE are related to the gut flora and their by—products, such
`
`as ammonia and endotoxin in the setting of intestinal barrier dysfunction and systemic
`Ml...
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`inflammation. However, no clear correspondence between cognitive impairment and gut
`
`microfiora has been established.
`
`The current treatments for HE rely on manipulation of the gut flora. However, this
`
`treatment is not successful in all cases. Success is hampered by a poor understanding of the
`
`identity and mechanism of action of gut flora.
`
`Moreover, prior techniques for the characterization of gut flora has been severely
`
`limited by the use of culture—based techniques that do not support the growth of the majority
`
`of the intestinal bacteria.
`
`The prior art has thus far failed to provide methods of readily and accurately
`
`assessing the complement of microfiora present in an individual, and/or of correlating the
`
`presence of particular microbes with particular diseases and conditions, and/or the risk of
`
`developing the same. This is particularly true with respect to patients with HE.
`
`SUMMARY OF THE INVENTION
`
`The invention provides methods for assessing the gut microflora of individuals, for
`
`identifying appropriate therapeutic targets and developing appropriate treatment protocols
`
`based on the assessment, and for monitoring the progress or outcome of treatment strategies.
`
`The methods involve the use of a systems biology approach using correlation network
`
`analysis (or similar approaches including without limitation non—parametric multivariate
`
`analysis, a Support Vector Machine, correlation difference network analysis, Dirichlet
`
`models, Bayesian models, and Linear models) to characterize the intestinal microflora of an
`
`individual, and to relate the patterns or distributions of microflora (“signatures”) to
`
`physiological processes, metabolic processes (metabolome), and clinical measures of health.
`
`The complex interactions of the microbiome and the human host are defined herein as the
`
`metabiome. For example, the signatures are correlated with various hallmarks or symptoms
`
`of disease and the activation and/or deactivation of physiological proc esses related to disease,
`
`based on known, previously established prototype signatures. Information gained by the
`
`methods of the invention may be advantageously used, for example, to diagnose conditions,
`
`to confirm diagnoses, to predict a patient’s risk of developing a disease or condition (e. g.
`
`prior to the onset of symptoms), to identify suitable therapeutic targets, and to monitor or
`
`track the outcome of therapeutic intervention. In particular, methods related to individuals
`
`who suffer from liver diseases, as well as those who have HE or who are at risk for
`
`-2...
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`developing HE are provided.
`
`The present invention provides methods of assessing the presence or the risk of
`
`development of encephalopathy in a patient with liver disease. The methods comprise the
`
`steps of l) analyzing gut microflora of said patient in order to determine a gut microbiome
`
`signature for said patient; 2) comparing said gut microbiome signature of said patient to one
`
`or more gut microbiome reference signatures, wherein said one or more gut microbiome
`
`reference signatures include at least one of a positive gut microbiome reference signature
`
`based on results from control subjects with encephalopathy and a negative gut microbiome
`
`reference signature based on results from control subjects without encephalopathy; and if
`
`said gut microbiome signature for said patient statistically significantly matches said
`
`positive gut microbiome reference signature, (e.g. includes the same types and/or the same
`
`relative abundances, ratios, etc. of microflora in statistically significant amounts), then
`
`concluding that said patient has or is at risk of developing encephalopathy; andx'or if said gut
`
`microbiome signature for said patient statistically significantly matches said negative gut
`
`microbiome reference signature, then concluding that said patient does not have or is not at
`
`risk of developing encephalopathy. In some embodiments, a statistically significant match
`
`has a P value of 0.05 or less. In some embodiments, the gut microflora is analyzed in a
`
`biological sample preferably selected from a stool sample, a sample of the lumen content, a
`
`mucosal biopsy sample, an oral sample, a blood sample and a urine sample. In other
`
`embodiments, the gut microbiome signature may include one or more of: bacterial taxa
`
`identified in said biological sample; bacterial metabolic products in said biological sample;
`
`and proteins in said biological sample. In yet other embodiments, the gut microbiome
`
`signature is based on an analysis of amplification products of DNA and/or RNA of said gut
`
`microflora, e.g. is based on an analysis of amplification products of genes coding for one or
`
`more of: Small Subunit rRNA, Intervening Transcribed Spacer, and Large Subunit rRNA. In
`
`some embodiments, the gut microbiome signature includes results obtained by assaying the
`
`mRNA composition of said biological samples. In some embodiments, the liver disease is
`
`cirrhosis and the encephalopathy is hepatic encephalopathy (HE). In some embodiments of
`
`the invention, the gut microbiome signature of said patient includes an indication of the
`
`presence and/or relevant abundance of at least one of Alcaligeneceae, Blautia, Bm‘kholderia,
`
`Enterobacteriaceae, Fecalibactcrium. Fitsobacteriaccae, Incertae Sedis' XIV,
`
`Lachnospimceae, Porphyromonadaceae, Roseburia, Ruminococcaceae and Veillonellaceae.
`
`In other embodiments, when the gut niicroflora signature of said patient
`_3_
`
`indicates the
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`presence of Alcaligencceae and Porphyromonadaceae in said gut microflora,
`
`then said
`
`concluding step results in a conclusion that said patient has or is at risk of developing
`
`encephalopathy. In other embodiments, the method further comprises the step of assessing,
`
`based on said gut microbiome signature,
`
`the presence or the risk of development of
`
`inflammation, endotoxemia, and/or endothelial dysfunction in said patient.
`
`In yet other
`
`embodiments,
`
`the one or more symptoms of a disease or condition is differentiated from
`
`normal conditions using at least one methodology selected from the group consisting of
`
`nonparametric multivariate analysis, a Support Vector Machine, correlation network
`
`analysis, correlation difference network analysis, Dirichlet models, Bayesian models, and
`
`10
`
`Linear models.
`
`IS
`
`20
`
`25
`
`30
`
`The invention also provides a treatment method for a patient with a liver disease The
`
`method comprises the steps of l) analyzing gut microflora of said patient in order to
`
`determine a gut microbiome signature for said patient; 2) comparing said gut microbiome
`
`signature of said patient to one or more gut microbiome reference signatures; and, based on
`
`said step of comparing, 3) concluding whether or not said patient has or is at risk for
`
`developing at least one of
`
`one or more conditions of interest; and if said patient has or is at
`
`risk for developing at least one of said one or more conditions of interest, then selecting
`
`from one or more treatment protocols appropriate for said one or more conditions of interest.
`
`In some embodiments, the one or more conditions of interest include encephalopathy,
`
`inflammation, endotoxemia, endothelial dysfunction and coma. In other embodiments, the
`
`treatment protocols include one or more of: antiwviral therapy for hepatitis B, C and/or D;
`
`weight loss therapy; surgery for non—alcoholic liver disease and obesity~assoeiated liver
`
`disease, alcohol abstinence for alcoholic liver disease, therapy for Wilson’s disease, alpha-l
`
`anti~trypsin repletion, and therapies specific for hepatic encephalopathy and liver transplant.
`
`The invention provides a method of monitoring the efficacy of a treatment protocol
`
`in a patient with liver disease or a condition associated with liver disease, comprising the
`
`steps of l) analyzing gut micreflora of said patient in order to determine a gut microbiome
`
`signature for said patient; and 2) comparing said gut microbiome signature of said patient to
`
`one or more gut microbiome reference signatures, wherein said one or more gut microbiome
`
`reference signatures include at least one of a positive gut microbiome reference signature
`
`based on results from control subjects with encephalopathy and a negative gut microbiome
`
`reference signature based on results from centrol subjects without encephalopathy; wherein
`
`if said gut microbiome signature for said patient Statistically significantly matches said
`_4_
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`positive gut microbiome reference signature, then concluding that said treatment protocol is
`
`not efficacious. Alternatively, the process could conclude that said treatment protocol is
`
`efficacious if said gut microbiome signature for said patient statistically significantly
`
`matches said negative gut microbiome reference signature. However, a treatment protocol
`
`may be deemed efficacious even if the treated patient’s signature does not match that of a
`
`healthy (or asymptomatic) control, so long as the signature indicates a change away from the
`
`signature of a control group with encephalopathy, eg. lowered amounts of non—beneficial
`
`bacteria (e.g. at least about 10% lower, or 20, 30, 40, 50, 60, 70, 80, 90 or even 100%
`
`decrease in the presence of at least one unwanted bacterium, and/or a corresponding increase
`
`in at least one beneficial or desirable bacterium). ln some embodiments, the method further
`
`comprises the step of repeating said steps of said method at multiple spaced—apart time
`
`intervals, e.g. said method is carried out prior to commencement of said treatment protocol,
`
`during said treatment protocol and/or after cessation of said treatment protocol.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`Figure 1. Principal Coordinate Analysis of the Fecal Microbiome of Controls and Cirrhotic
`
`Patients. This graph shows the variation in fecal microbiome plotted on a principal
`
`coordinate analysis plot. Points that are closer to each other are similar with respect to their
`
`stool microbiota. The healthy controls represented by the black dots are clustered together
`
`while the cirrhotic patients represented by the gray dots are distant from the controls. This
`
`indicates a difference in the stool microbiome of healthy controls compared to eiirhotie
`
`patients.
`
`Figure 2A—B. Correlation Network Analysis of Cirrhotic Patients with and without Hepatic
`
`Encephalopathy. Only correlations with a coefficient 220.90 are displayed. Grey nodes
`
`indicate microbiome families; white nodes indicate cognitive tests and black nodes are
`
`serum inflammatory markers. A dashed line connecting nodes indicate positive correlation
`
`and a solid line indicates negative correlation >090. The p values for the correlations are
`
`displayed on or near the lines connecting the nodes. MELD: model for end—stage liver
`
`disease score, DST: digit symbol test, LDTe: line drawing test errors.
`
`A, Patients with HE (n=l7) have a high number of significant correlations. There are
`
`significant positive correlations between lL—23 and several bacterial families. Prevorellaceae
`
`and Fusobaczeriaceae are positively correlated with inflammation. Since a low score on
`-5-
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`DST and high one on LDTe
`
`indicate poor performance, Alcaligerraceae
`
`and
`
`Porphyromonadaceae were correlated with poor cognition. The p—values for all
`
`these
`
`correlations are less than the 4‘h decimal place indicating a very high significance.
`
`B, Patients without HE have very few significant correlations (n38). There was a significant
`
`negative correlation between MELD score and Ruminococcaceae and a positive correlation
`
`between Veilloneliaccae and Porphyromonadaceac.
`
`Figure SAuF. Correlation Network and Sub-networks of the mucosal inicrobiome of HE
`
`patients. A, correlation Network of the mucosal microbiorne of HE patients As can be seen,
`
`autoehthonous genera belonging to the Rrrmr'nococcaceae, Lacimospiraceae and Incertae
`
`10
`
`Sedis families are associated with good cognition,
`
`lower MELD,
`
`lower ammonia, and
`
`decreased inflammation. Sub—networks from this complex network are displayed in the
`
`figures 8—1:; B, sub-network of the HE mucosa microbiome showing the negative correlation
`
`of the autochthonous bacteria to MELD score and inflammation; C, sub—network of the HE
`
`mucosa microbiorne showing the negative correlation of the inflammatory cytokines,
`
`particularly IL~17 with autochthonous bacteria and positive correlation with Lures
`
`(indicating worse cognition with increased inflammation), endothelial activation (leAM—l),
`
`MELD
`
`score
`
`and
`
`non—autochthonous
`
`bacterial
`
`genera
`
`(Burkholdcriaceae,
`
`Erysrpelorhricaceae; D, a high lure number indicates poor cognition. This sub—network of
`
`the HE mucosa microbiome shows that lures are negatively correlated with autochthonous
`
`bacterial genera (Rosebzzrt’a and Dar—ea) while they are correlated positively with
`
`Burkholderiaceae and Incertae scdr’s X? and as expected with ammonia and inflammatory
`
`cytokines; E, a high number on NCT—B indicates poor performance. This sub—network of the
`
`HE mucosal microbiome shows a negative correlation i.e. good NCT—B performance with
`
`the abundances of Ruminococcaceae_Fecalibactermm. This autochthonous genus has been
`
`associated with lower MELD score, lower inflammation (EL-1’7 and IL—10) and is positively
`
`correlated with other beneficial autochthonous bacteria; F, M2gasphaera was significantly
`
`more abundant
`
`in HE;
`
`in this
`
`sub—network Megasphaem abundance is significantly
`
`correlated with sVCAMwl
`
`(marker of endothelial activation) and with poor cognitive
`
`performance (a high score on SDT and LDTt indicates poor while a high score on DST
`
`indicates good cognitive performance). Connecting dashed lines indicate a significant
`
`negative while solid lines mean a significantly positive correlation. Nodes in gray are
`
`bacterial genera, double cross hatch are inflammatory eytokines, white are cognitive tests,
`
`black are clinical variables, heavy cross hatch are markers of endothelial activation and fine
`_6_
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`cross hatch are neuro-glial markers. A high score on DST (digit symbol) and Targets
`
`indicates good cognition while a high score on the rest of the cognitive tests indicates poor
`
`performance. SDT: serial dotting, LDTt: Line tracing test
`
`time and NCT—A/B: number
`
`connection test ALB.
`
`5
`
`Figure 4A-D. Correlation network and sub-networks of the mucosal microbiome of patients
`
`without HE. Indicators and abbreviations are the same as in Figure 3. A, Correlation
`
`network of the mucosal microbiome of patients without HE. Autochthonous genera
`
`belonging to the Ruminococcaceae, Lac/mospiraceae and Incertae Sedis families are
`
`associated with good cognition,
`
`lower MELD, ammonia, and inflammation; B,
`
`this
`
`10
`
`subwnetwork of patients without HE shows that bacteria genera belonging to autochthonous
`
`families (Ruminococcaccac and Lachnospiraceae) are positively correiated with each other
`
`while
`
`negatively
`
`correlated with potentially
`
`pathogenic Enterobacteriaceae
`
`and
`
`Propionibacierimn; C, this sttbmnetwork of the nowHE mucosal microbiome again shows the
`
`positive correlation of the autochthonous bacteria with each other and a negative correlation
`
`1.5
`
`with time required to complete NCTnA, which indicates good cognitive performance; D, a
`
`high score on targets and low score on lures indicates good cognitive performance. We again
`
`found a correlation between poor performance on lures and targets with genera belonging to
`
`Porphyromonadaccae and Alcaligenaceae.
`
`Figure 5A-B is a schematic diagram and flow chart of a system and method for performing
`
`20
`
`the various embodiments of the invention.
`
`DETAILED DESCRIPTION
`
`The pathogenesis of HE spans several metabolic processes, and a systems biology
`
`25
`
`approach was used as described herein to identify novel functional correlations between HE
`
`and gut microflora. As such, HE provides an exemplary system for the application of the
`
`methods and systems of the invention. For example, the studies disclosed herein successfully
`
`demonstrated a link between the composition of the gut microbiome and cognition,
`
`inflammation, and endothelial dysfunction in cirrhotic patients with and without HE. The a
`
`30
`
`priori hypothesis was that the gut microbiome composition (“signature”) would be correlated
`
`with cognition and inflammation in cirrhotic patients with HE and that this association or
`
`signature would be different from those who have never developed HE. This hypothesis was
`
`confirmed, and has led to the development of methods of assessing the propensity (risk,
`_'7_
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`likelihood, etc.) of a patient to develop a disease knovvn to be associated with a particular
`
`pattern of gut microflora, methods of identifying suitable therapeutic targets (and hence
`
`targeted treatment protocols), methods of developing treatment protocols, and methods of
`
`monitoring the progress of treatment. In addition, the gut microflora signature may be used as
`
`the basis for developing targeted motecules to counter the inflammation, bacterial
`
`end—products and microflora and/or to produce prebiotics/probioticsfmodified bacteria {e.g.
`
`genetically modified bacteria) to replenish, in individuals in need thereof, abnonnaliy low
`
`quantities of autochthonous bacteria. associated with the gut of healthy or asymptomatic
`
`individuals, and to reduce the harmful bacteria associated with untoward or undesirable
`
`conditions such as inflammation and brain dysfunction.
`
`The foliowing definitions are used throughout:
`
`Gut. The gut of an individual generally comprises, for example, the stomach (or stomachs, in
`
`ruminants), the colon, the small intestine, the large intestine, cecum, and the rectum.
`
`However, in some embodiments, other organs andi’or cavities may be included in this
`
`category. In addition, regions of the gut may be subdivided, e. g. the right vs the left side of
`
`the colon may have different microflora populations due to the time required for digesting
`
`materiai to move through the colon, and changes in its composition with time. Synonyms
`
`include the gastrointestinal tract, or possibly the digestive system, although the latter is
`
`generally also understood to comprise the mouth, esophagus, etc.
`
`Microfiora refers to the coliective bacteria and other microorganisms in an ecosystem of a
`
`host (e.g. an animal such as a human) or in a single part of the host’s body, e.g. the gut. An
`
`equivalent term is “microbiota”.
`
`Microbiome: the totality of microbes (bacteria, fungae, protists), their genetic elements
`
`(genomes) in a defined environment, e. g. within the gut of a host.
`
`Metabolome: all the metaboiic compounds in a defined environment, e. g. within the gut of a
`
`host.
`
`Immunome: all the immune interactions within the host and between the host and
`
`microbiome in a defined environment, e.g. within the gut of a host.
`
`Metabiome: all the interactions between the microbiome, the human host and environment in
`
`a defined environment, e.g. the microbiome, metabolome, and immunome.
`
`Transcriptome: the mRNA composition of a sample.
`
`Prebiotics are non-digestibie food ingredients that stimulate the growth and/or activity of
`”.8.“
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`bacteria in the digestive system. Typically, prebiotics are carbohydrates (such as
`
`oligosaecharides), but the term may include non-carbohydrates. The most prevalent forms of
`
`prebiotics are nutritionaily classed as soluble fiber. Exemplary prebiotics include but are not
`
`limited to various short—chain, long—chain, and “full—spectrum” polysaccharides such as
`
`oligofructose, inulin, polysaccharides with molecular link—lengths from 2—64 links per
`
`molecule [c.g. Oligofructose—Bnriched Inulin (0131)], galactooligosaccharides, and others.
`
`The term prebiotics may refer to commercial preparations of purified forms of these
`
`substances, and/or to natural sources, e. g. soybeans, inulin sources (such as Jerusalem
`
`artichoke, jicama, and chicory root), raw oats, unrefined Wheat, unrefined barley, yacon,
`
`oligosaccharides from milk, etc.
`
`Probiotics are live microorganisms thought to be beneficial to the host organism, examples of
`
`which include lactic acid bacteria (LAB), bifidobacteria, certain yeasts and bacilli, etc.
`
`Treatment with probiotics as described herein may be implemented by their consumption as
`
`part of fermented foods with specially added active live cultures (e.g. yogurt, soy yogurt,
`
`kefir, various cheeses, etc. ) or as dietary suppiements (eg. tablets, powders, liquids, etc.
`
`which contain probiotie organisms), or in any other form.
`
`Unless defined otherwise, all technical and scientific terms used herein have the same
`
`meaning as commonly understood by one of ordinary skill in the art to which this invention
`
`belongs. Although any methods and materials similar or equivalent to those described herein
`
`can also be used in the practice or testing of the present invention, representative illustrative
`
`methods and materials are now described.
`
`In one embodiment, the present invention provides methods for diagnosing patients at
`
`risk for developing a disease or condition correlated with the presence or absence of (and/or
`
`the relative distribution of) particular taxa of microbes in the gut, or in a particular component
`
`of or location within the gut. Such patients may have a higher than average or higher than
`
`nonnal chance of developing overt symptoms of the disease or condition, compared to
`
`individuals who have different gut microbes, or different amounts of microbes, or different
`
`relative amounts of microbes. Early identification of such a propensity allows early
`
`intervention, 6. g. by altering the identity and/or the relative abundance of gut mierofiora
`
`associated with, and possibly causing, the disease/condition, so that development of the
`
`disease/condition may be avoided, or delayed, or the associated symptoms may be lessened.
`
`In some embodiments, the patient may already exhibit overtly one or more symptoms
`
`of a disease of interest. But, by using the methods of the invention, it is possible to ascertain
`-94..
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`Whether or not a likely cause of the disease sympt0m(s) is gut microfiora identity
`
`(composition of the microbiomc) and/or distribution, and hence whether or not gut microflora
`
`are a likely target for successful treatment. In other embodiments, a subject may be
`
`asymptomatic with respect to a disease or condition of interest, but for some reason, may be
`
`deemed susceptible to developing the disease or condition, and the methods of the invention
`
`provide a way to predict whether or not this is likely to occur. in some embodiments, the
`
`identification of particular microflora (e.g. of particular phyla, genera or species of microbe)
`
`may allow targeted therapies directed against the microbe or microbes which are undesirable,
`
`and/0r therapies which increase the amount of desirable gut microflora, e.g. those which
`
`compete with the undesirable microbes, and/or which supply activities or produce substances
`
`which are beneficial, especially with respect to the disease or condition of interest.
`
`The methods of die invention may involve steps of identifying a patient, the health or
`
`medical condition of whom might benefit from the knowiedge provided by the method. The
`
`patient may be completely asymptomatic at the time of the analysis (but for some reason, a
`
`medical professional determines that the patient may benefit from the practice of the
`
`invention, e.g. the patient may be known to have a liver condition or disease), or the patient
`
`may be in the eariy, or even Eater, stages of the disease, and can benefit from the knowledge
`
`of the status of the gut microflora. In order to practice the methods of the invention, generally
`
`a sample of gut microfiora is obtained from the patient by any method known to those of skili
`
`in the art, and the sample is tested for the presence or absence of, and/or for the relative
`
`abundance of, at least one taxon of microbes. Generally, the taxa which are targeted for
`
`assessment are one or more la‘xa, the presence of which is known to be correlated with a
`
`particular disease or condition, or with particular symptoms associated or correlated with a
`
`disease/condition. In some embodiments, identification of a singie or a few (e.g. about 10 or
`
`fewer, or about 100 or fewer) key microbes may be sufficient to iink the presence of the
`
`microbes to the likely deveiopment of a disease. However, in other embodiments, a broad
`
`taxonomy determination is made, e. g. dozens, hundreds, or thousands [or more) taxa may be
`
`targeted for assessment of their presence and/or absence and/or relative abundance.
`
`Suitable biological samples for interrogation using the methods of the invention
`
`inciude but are not limited to: samples of gut contents and/or mucosal biopsies obtained
`
`directiy by an invasive technique e.g. by surgery, by rectal or intestinal sampling via
`
`colonoscopy-type procedures, or by other means. Preferably, samples are obtained by iess
`
`invasive methods, e.g. stool samples, inciuding stool cards, gas pacs, home collection, etc.
`-30-
`
`10
`
`15
`
`20
`
`25
`
`30
`
`

`

`WO 2012/159023
`
`PCT/US2012/038555
`
`In one embodiment, oral samples, such as oral rinses, oral swabs etc. are collected e.g. to
`
`correlate the oral microbiome with the gut microbiome, or for other purposes.
`
`After a sample is obtained, the types andfor the quantity (e. g. occurrence) in the
`
`sample of at least one microbe of interest is determined. In addition, a total amount of
`
`microbes may be determined, and then for each constituent microbe, a fractional percentage
`
`(e.g. relative amount, ratio, distribution, frequency, percentage, etc.) of the total is calculated.
`
`The result is typically correlated with at least one suitable control result, e.g. control results of
`
`the same parameter(s) obtained from healthy individuals (negative control), and/or
`
`individuals known to have a disease or condition of interest (positive control), or from
`
`subjects who have had the disease and condition of int