Patent Application
20230193390
The application herein incorporates by reference in its entirety the sequence listing material in the ASCII text file named “21.07.02 P104951WO01 Sequence Listing”, created Nov. 9, 2022, and having the size of 504 kilobytes, filed with this application.
The invention relates to disease processes.
Fibrosis, also known as fibrotic scarring, is a pathological wound healing in which connective tissue replaces normal parenchymal tissue to the extent that it goes unchecked, leading to considerable tissue remodelling and the formation of permanent scar tissue. Sclerosis is a type of fibrosis in which there is the stiffening of a tissue or anatomical feature, usually caused by a replacement of the normal organ-specific tissue with connective tissue. The structure may be said to have undergone sclerotic changes or display sclerotic lesions, which refers to the process of sclerosis. Fibrosis is a complex condition where the regulatory and causative aspects cannot be easily elucidated.
The outcome of scleroderma depends on the extent of disease. Those with localised disease generally have a normal life expectancy. In those with systemic disease typical life expectancy is about 11 years from onset. Death is often due to lung, gastrointestinal, or heart complications.
The inventors have identified chromosome conformation signatures relevant to the presence of fibrosis or the stage of fibrosis. Accordingly the invention provides a process for detecting a chromosome state which represents a subgroup in a population comprising determining whether a chromosome interaction relating to that chromosome state is present or absent within a defined region of the genome; and
(i) corresponds to any one of the chromosome interactions represented by any probe shown in Table 1, 3 or 4; and/or
(ii) is present in a 4,000 base region which comprises or which flanks (i);
and/or
(a) corresponds to any one of the chromosome interactions represented by any probe shown in Table 2, 5 or 6; and/or
(b) is present in a 4,000 base region which comprises or which flanks (a).
Table 1 shows 100 markers relating to early or late fibrosis, with 50 markers corresponding to each.
Table 2 shows 100 markers relating to presence of fibrosis, with 50 associated with disease and 50 associated with absence of disease.
Table 3 shows 100 markers associated with early fibrosis.
Table 4 shows 100 markers associated with late fibrosis.
Table 5 shows 100 markers associated with presence of fibrosis.
Table 6 shows 100 markers associated with the absence of fibrosis.
Table 7 shows SHAPLEY results for markers associated with early fibrosis.
Table 8 shows SHAPLEY results for markers associated with late fibrosis.
Table 9 shows SHAPLEY results for markers associated with presence of fibrosis.
Table 10 shows SHAPLEY results for markers associated with absence of fibrosis.
The chromosome interactions which are typed may be referred to as ‘markers’, ‘CCS’, ‘chromosome conformation signature’, ‘epigenetic interaction’ or ‘EpiSwitch markers’ herein. Such interactions are recognised in the art as regions of the chromosome coming together in a stable manner and this represents a distinct mode of regulation. A chromosome interaction can also be referred to as a ‘juxtaposition’ of chromosomes, chromosome ‘folding’ or ‘chromatin interaction’. Such interactions can be detected, for example, using the 3C (chromosome conformation capture) method.
The word ‘type’ will be interpreted as per the context, but will usually refer to detection of whether a specific chromosome interaction is present or absent.
Different subgroups are mentioned herein, but essentially the invention allows identification of groups relating to fibrosis, and in particular to early or late fibrosis, or to presence or absence of fibrosis. The invention therefore provides a method of diagnosis (or detecting) the stage of fibrosis or the presence or fibrosis.
The chromosome interactions which are typed in the method of the invention are defined in Tables 1 to 6. They are defined by means of the probe sequences which detect the ligated product made by an EpiSwitch method (see
The word ‘method’ is used herein to refer to the ‘process’ of the invention, unless the context requires otherwise.
The invention relates to determining different aspects of fibrosis, particularly in respect to the presence or stage of fibrosis. This determining is by typing any of the relevant markers disclosed herein, for example in Table 1 or 2, or preferred combinations of markers, or markers in defined specific regions disclosed herein. The typing may be of any of the markers shown in Table 3, 4, 5 or 6 or selections (combinations) of markers from these tables.
Specific number of markers may be chosen from any group of markers which is specifically disclosed herein. Preferred numbers of markers are at least 3, 5, 8, 10, 15 and at least 20. Preferred groups of markers are those shown in each table, or each part of a table (for example Table 1.a1), or all the markers associated with a distinct characteristic of fibrosis.
The invention includes a process of typing a patient to identify whether they have fibrosis and/or the stage of fibrosis. The invention includes diagnosis of an individual for any condition or stage of disease as defined herein (i.e. prognosis), which can be thought of as determining the subgroup they belong to. The fibrosis may be a skin fibrotic condition, which may preferably be scleroderma.
The invention also concerns a panel of epigenetic markers which relates to fibrosis. The panel may have been optimised in some way, for example by GLMNET analysis.
The invention therefore allows personalised therapy to be given to the patient which accurately reflects the patient's needs.
Any therapy, for example drug, which is mentioned herein may be administered to an individual based on the result of the process.
Marker sets are disclosed in the Tables and Figures. In one embodiment at least 10 markers from any disclosed marker set are used in the invention. In another embodiment at least 20% of the markers from any disclosed marker set are used in the invention.
The process of the invention comprises a typing system for detecting chromosome interactions relevant to fibrosis. This typing may be performed using the EpiSwitch™ system mentioned herein which is based on cross-linking regions of chromosome which have come together in the chromosome interaction, subjecting the chromosomal DNA to cleavage and then ligating the nucleic acids present in the cross-linked entity to derive a ligated nucleic acid with sequence from both the regions which formed the chromosomal interaction. Detection of this ligated nucleic acid allows determination of the presence or absence of a particular chromosome interaction. The ligated nucleic acid therefore acts as a marker for the presence of the chromosome interaction. Preferably the ligated nucleic acid is detected by PCR or a probe based method, including a qPCR method.
Any suitable typing method can be used for detecting the presence or absence of chromosome interactions, for example a method in which the proximity of the chromosomes in the interaction is detected and/or in which a marker that reflects chromosome interaction status is detected.
The chromosomal interactions may be identified using the process described herein in which populations of first and second nucleic acids are used. These nucleic acids can also be generated using EpiSwitch™ technology.
As used herein, the term ‘epigenetic’ and ‘chromosome’ interactions typically refer to interactions between distal regions of a chromosome, said interactions being dynamic and altering, forming or breaking depending upon the state of the region of the chromosome. That state will typically reflect the presence or stage of fibrosis.
In particular processes of the invention chromosome interactions are typically detected by first generating a ligated nucleic acid that comprises sequence from both regions of the chromosomes that are part of the interactions. In such processes the regions can be cross-linked by any suitable means. In a preferred aspect, the interactions are cross-linked using formaldehyde, but may also be cross-linked by any aldehyde, or D-Biotinoyl-e-aminocaproic acid-N-hydroxysuccinimide ester or Digoxigenin-3-O-methylcarbonyl-e-aminocaproic acid-N-hydroxysuccinimide ester. Para-formaldehyde can cross link DNA chains which are 4 Angstroms apart. Preferably the chromosome interactions are on the same chromosome. Typically the chromosome interactions are 2 to 10 Angstroms apart.
The chromosome interaction may reflect the status of the region of the chromosome, for example, if it is being transcribed or repressed in response to change of the physiological conditions. Chromosome interactions which are specific to subgroups as defined herein have been found to be stable, thus providing a reliable means of measuring the differences between the two subgroups.
In addition, chromosome interactions specific to a fibrosis characteristic will normally occur early in a biological process, for example compared to other epigenetic markers such as methylation or changes to binding of histone proteins. Thus the process of the invention is able to detect early stages of a biological process. This allows early intervention (for example treatment) which may as a consequence be more effective. Chromosome interactions also reflect the current state of the individual and therefore can be used to assess changes to disease status. Furthermore there is little variation in the relevant chromosome interactions between individuals within the same subgroup. Detecting chromosome interactions is highly informative with up to 50 different possible interactions per gene, and so processes of the invention can for example interrogate 500,000 different interactions.
Herein the term ‘marker’ or ‘biomarker’ refers to a specific chromosome interaction which can be detected (typed) in the invention. Specific markers are disclosed herein, any of which may be used in the invention. Further sets of markers may be used, for example in the combinations or numbers disclosed herein. The specific markers disclosed in the tables herein are preferred as well as markers presents in genes and regions mentioned in the tables herein are preferred. These may be typed by any suitable process, for example the PCR or probe based methods disclosed herein, including a qPCR method. The markers are defined herein by location or by probe and/or primer sequences.
Epigenetic chromosomal interactions may overlap and include the regions of chromosomes shown to encode relevant or undescribed genes, but equally may be in intergenic regions. It should further be noted that the inventors have discovered that epigenetic interactions in all regions are equally important in determining the status of the chromosomal locus. These interactions are not necessarily in the coding region of a particular gene located at the locus and may be in intergenic regions.
The chromosome interactions which are detected in the invention could be caused by changes to the underlying DNA sequence, by environmental factors, DNA methylation, non-coding antisense RNA transcripts, non-mutagenic carcinogens, histone modifications, chromatin remodelling and specific local DNA interactions. The changes which lead to the chromosome interactions may be caused by changes to the underlying nucleic acid sequence, which themselves do not directly affect a gene product or the mode of gene expression. Such changes may be for example, SNPs within and/or outside of the genes, gene fusions and/or deletions of intergenic DNA, microRNA, and non-coding RNA. For example, it is known that roughly 20% of SNPs are in non-coding regions, and therefore the process as described is also informative in non-coding situation. In one aspect the regions of the chromosome which come together to form the interaction are less than 5 kb, 3 kb, 1 kb, 500 base pairs or 200 base pairs apart on the same chromosome.
The chromosome interaction which is detected is preferably within any of the genes in the regions defined by Table 1 or 2. The chromosome interaction which is detected is preferably within any of the genes in the regions defined by Table 3, 4, 5 or 6. However it may also be upstream or downstream of the gene, for example up to 50,000, up to 30,000, up to 20,000, up to 10,000 or up to 5000 bases upstream or downstream from the gene or from the coding sequence.
Typing according to the process of the invention may be carried out at multiple time points, for example to monitor the progression of the disease. This may be at one or more defined time points, for example at at least 1, 2, 5, 8 or 10 different time points. The durations between at least 1, 2, 5 or 8 of the time points may be at least 5, 10, 20, 50, 80 or 100 days. Typically there are 3 time points at least 50 days apart.
As used herein, a “subgroup” preferably refers to a population subgroup (a subgroup in a population), more preferably a subgroup in the population of a particular animal such as a particular eukaryote, or mammal. Most preferably, a “subgroup” refers to a subgroup in the human population. Therefore the most preferred type of individuals for all aspects of the inventions are humans.
The invention includes detecting and treating particular subgroups in a population. The inventors have discovered that chromosome interactions differ between subsets (for example at least two subsets) in the relevant population. Identifying these differences will allow physicians to categorize their patients as a part of one subset of the population. The invention therefore provides physicians with a process of personalizing medicine for the patient based on their epigenetic chromosome interactions.
Such testing may be used to select how to subsequently treat the patient, for example the type of drug and/or its dose and/or its frequency of administration.
Certain aspects of the invention utilise ligated nucleic acids, in particular ligated DNA. These comprise sequences from both of the regions that come together in a chromosome interaction and therefore provide information about the interaction. The EpiSwitch™ process described herein uses generation of such ligated nucleic acids to detect chromosome interactions.
Thus a process of the invention may comprise a step of generating ligated nucleic acids (e.g. DNA) by the following steps (including a process comprising these steps):
(i) cross-linking of epigenetic chromosomal interactions present at the chromosomal locus, preferably in vitro;
(ii) optionally isolating the cross-linked DNA from said chromosomal locus;
(iii) subjecting said cross-linked DNA to cutting, for example by restriction digestion with an enzyme that cuts it at least once (in particular an enzyme that cuts at least once within said chromosomal locus);
(iv) ligating said cross-linked cleaved DNA ends (in particular to form DNA loops); and
(v) optionally identifying the presence of said ligated DNA and/or said DNA loops, in particular using techniques such as PCR (polymerase chain reaction), to identify the presence of a specific chromosomal interaction.
These steps may be carried out to detect the chromosome interactions for any aspect mentioned herein. The steps may also be carried out to generate the first and/or second set of nucleic acids mentioned herein.
PCR (polymerase chain reaction) may be used to detect or identify the ligated nucleic acid, for example the size of the PCR product produced may be indicative of the specific chromosome interaction which is present, and may therefore be used to identify the status of the locus. In preferred aspects the primers shown in Table 1 or 2 are used. In other preferred aspects the primers shown in Table 3, 4, 5 or 6 are used.
The skilled person will be aware of numerous restriction enzymes which can be used to cut the DNA within the chromosomal locus of interest. It will be apparent that the particular enzyme used will depend upon the locus studied and the sequence of the DNA located therein. A non-limiting example of a restriction enzyme which can be used to cut the DNA as described in the present invention is Taql.
The EpiSwitch™ Technology also relates to the use of microarray EpiSwitch™ marker data in the detection of epigenetic chromosome conformation signatures specific for phenotypes. Aspects such as EpiSwitch™ which utilise ligated nucleic acids in the manner described herein have several advantages. They have a low level of stochastic noise, for example because the nucleic acid sequences from the first set of nucleic acids of the present invention either hybridise or fail to hybridise with the second set of nucleic acids. This provides a binary result permitting a relatively simple way to measure a complex mechanism at the epigenetic level. EpiSwitch™ technology also has fast processing time and low cost. In one aspect the processing time is 3 hours to 6 hours.
The process of the invention will normally be carried out on a sample. The sample may be obtained at a defined time point, for example at any time point defined herein. The sample will normally contain DNA from the individual. It will normally contain cells. In one aspect a sample is obtained by minimally invasive means, and may for example be a blood sample. DNA may be extracted and cut up with a standard restriction enzyme. This can pre-determine which chromosome conformations are retained and will be detected with the EpiSwitch™ platforms. Due to the synchronisation of chromosome interactions between tissues and blood, including horizontal transfer, a blood sample can be used to detect the chromosome interactions in tissues, such as tissues relevant to disease.
The invention relates to certain nucleic acids, such as the ligated nucleic acids which are described herein as being used or generated in the process of the invention. These may be the same as, or have any of the properties of, the first and second nucleic acids mentioned herein with reference to a screening method described below. The nucleic acids of the invention typically comprise two portions each comprising sequence from one of the two regions of the chromosome which come together in the chromosome interaction. Typically each portion is at least 8, 10, 15, 20, 30 or 40 nucleotides in length, for example 10 to 40 nucleotides in length. Preferred nucleic acids comprise sequence from any of the genes mentioned in any of the tables. Typically preferred nucleic acids comprise the specific probe sequences mentioned in Table 1, 2, 3, 4, 5 or 6; or fragments and/or homologues of such sequences.
Preferably the nucleic acids are DNA. It is understood that where a specific sequence is provided the invention may use the complementary sequence as required in the particular aspect. Preferably the nucleic acids are DNA. It is understood that where a specific sequence is provided the invention may use the complementary sequence as required in the particular aspect.
The primers shown in Table 1 and 2 may also be used in the invention as mentioned herein. In one aspect primers are used which comprise any of: the sequences shown in Table 1 or 2; or fragments and/or homologues of any sequence shown in Table 1 or 2. The primers shown in Table 3, 4, 5 or 6 may also be used in the invention as mentioned herein. In one aspect primers are used which comprise any of: the sequences shown in Table 3, 4, 5 or 6; or fragments and/or homologues of any sequence shown in Table 3, 4, 5 or 6.
The second set of nucleic acid sequences has the function of being a set of index sequences, and is essentially a set of nucleic acid sequences which are suitable for identifying subgroup specific sequence. They can represents the ‘background’ chromosomal interactions and might be selected in some way or be unselected. They are in general a subset of all possible chromosomal interactions.
The second set of nucleic acids may be derived by any suitable process. They can be derived computationally or they may be based on chromosome interaction in individuals. They typically represent a larger population group than the first set of nucleic acids. In one particular aspect, the second set of nucleic acids represents all possible epigenetic chromosomal interactions in a specific set of genes. In another particular aspect, the second set of nucleic acids represents a large proportion of all possible epigenetic chromosomal interactions present in a population described herein. In one particular aspect, the second set of nucleic acids represents at least 50% or at least 80% of epigenetic chromosomal interactions in at least 20, 50, 100 or 500 genes, for example in 20 to 100 or 50 to 500 genes.
The second set of nucleic acids typically represents at least 100 possible epigenetic chromosome interactions which modify, regulate or in any way mediate a phenotype in population. The second set of nucleic acids may represent chromosome interactions that affect a disease state (typically relevant to diagnosis or prognosis) in a species. The second set of nucleic acids typically comprises sequences representing epigenetic interactions both relevant and not relevant to a prognosis subgroup.
In one particular aspect the second set of nucleic acids derive at least partially from naturally occurring sequences in a population, and are typically obtained by in silico processes. Said nucleic acids may further comprise single or multiple mutations in comparison to a corresponding portion of nucleic acids present in the naturally occurring nucleic acids. Mutations include deletions, substitutions and/or additions of one or more nucleotide base pairs. In one particular aspect, the second set of nucleic acids may comprise sequence representing a homologue and/or orthologue with at least 70% sequence identity to the corresponding portion of nucleic acids present in the naturally occurring species. In another particular aspect, at least 80% sequence identity or at least 90% sequence identity to the corresponding portion of nucleic acids present in the naturally occurring species is provided.
In one particular aspect, there are at least 100 different nucleic acid sequences in the second set of nucleic acids, preferably at least 1000, 2000 or 5000 different nucleic acids sequences, with up to 100,000, 1,000,000 or 10,000,000 different nucleic acid sequences. A typical number would be 100 to 1,000,000, such as 1,000 to 100,000 different nucleic acids sequences. All or at least 90% or at least 50% or these would correspond to different chromosomal interactions.
In one particular aspect, the second set of nucleic acids represent chromosome interactions in at least 20 different loci or genes, preferably at least 40 different loci or genes, and more preferably at least 100, at least 500, at least 1000 or at least 5000 different loci or genes, such as 100 to 10,000 different loci or genes. The lengths of the second set of nucleic acids are suitable for them to specifically hybridise according to Watson Crick base pairing to the first set of nucleic acids to allow identification of chromosome interactions specific to subgroups. Typically the second set of nucleic acids will comprise two portions corresponding in sequence to the two chromosome regions which come together in the chromosome interaction. The second set of nucleic acids typically comprise nucleic acid sequences which are at least 10, preferably 20, and preferably still 30 bases (nucleotides) in length. In another aspect, the nucleic acid sequences may be at the most 500, preferably at most 100, and preferably still at most 50 base pairs in length. In a preferred aspect, the second set of nucleic acids comprises nucleic acid sequences of between 17 and 25 base pairs. In one aspect at least 100, 80% or 50% of the second set of nucleic acid sequences have lengths as described above. Preferably the different nucleic acids do not have any overlapping sequences, for example at least 100%, 90%, 80% or 50% of the nucleic acids do not have the same sequence over at least 5 contiguous nucleotides.
Given that the second set of nucleic acids acts as an ‘index’ then the same set of second nucleic acids may be used with different sets of first nucleic acids which represent subgroups for different characteristics, i.e. the second set of nucleic acids may represent a ‘universal’ collection of nucleic acids which can be used to identify chromosome interactions relevant to different characteristics.
The first set of nucleic acids are typically from subgroups relevant to fibrosis. The first nucleic acids may have any of the characteristics and properties of the second set of nucleic acids mentioned herein. The first set of nucleic acids is normally derived from samples from the individuals which have undergone treatment and processing as described herein, particularly the EpiSwitch™ cross-linking and cleaving steps. Typically the first set of nucleic acids represents all or at least 80% or 50% of the chromosome interactions present in the samples taken from the individuals.
Typically, the first set of nucleic acids represents a smaller population of chromosome interactions across the loci or genes represented by the second set of nucleic acids in comparison to the chromosome interactions represented by second set of nucleic acids, i.e. the second set of nucleic acids is representing a background or index set of interactions in a defined set of loci or genes.
Any of the types of nucleic acid populations mentioned herein may be present in the form of a library comprising at least 200, at least 500, at least 1000, at least 5000 or at least 10000 different nucleic acids of that type, such as ‘first’ or ‘second’ nucleic acids. Such a library may be in the form of being bound to an array. The library may comprise some or all of the probes or primer pairs shown in Table 1 or 2. The library may comprise some or all of the probes or primer pairs shown in Table 3, 4, 5 or 6. The library may comprise all of the probe sequence from any of the tables disclosed herein.
The invention typically requires a means for allowing wholly or partially complementary nucleic acid sequences from the first set of nucleic acids and the second set of nucleic acids to hybridise. In one aspect all of the first set of nucleic acids is contacted with all of the second set of nucleic acids in a single assay, i.e. in a single hybridisation step. However any suitable assay can be used.
The nucleic acids mentioned herein may be labelled, preferably using an independent label such as a fluorophore (fluorescent molecule) or radioactive label which assists detection of successful hybridisation. Certain labels can be detected under UV light. The pattern of hybridisation, for example on an array described herein, represents differences in epigenetic chromosome interactions between the two subgroups, and thus provides a process of comparing epigenetic chromosome interactions and determination of which epigenetic chromosome interactions are specific to a subgroup in the population of the present invention.
The term ‘pattern of hybridisation’ broadly covers the presence and absence of hybridisation between the first and second set of nucleic acids, i.e. which specific nucleic acids from the first set hybridise to which specific nucleic acids from the second set, and so it not limited to any particular assay or technique, or the need to have a surface or array on which a ‘pattern’ can be detected.
The Chromosome Interactions which are Typed
The chromosome interactions which are typed are:
(i) those which specifically defined in any of Tables 1, 2, 3, 4, 5 or 6, for example either by probe sequence or by position numbers on the chromosome, and/or
(ii) those which are present in the genes or regions defined in any of Tables 1, 2, 3, 4 5 or 6, and/or
(iii) those present in a 4,000 base region which comprises or which flanks any specific chromosome interaction defined in any of Tables 1, 2, 3, 4, 5 or 6.
The chromosome interactions which are typed can be those mentioned in the subset shown in
Any preferred number of chromosome interactions can be typed as mentioned herein from (i), (ii) or (iii), but typically at least 5, 8, 10, 12, 15, 20, 30 or 40 interactions will be typed.
Selecting a Subgroup with Particular Characteristics
This section provides examples of the number of interactions that can be typed from any one table.
The invention includes a process in which a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 1. In one embodiment at least 10 chromosome interactions represented by the probes in Table 1 are typed.
The invention also includes a process in which specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 2. In one embodiment at least 10 chromosome interactions represented by the probes in Table 2 are typed.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 1 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 1 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 1.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 2 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 2 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 2.
The invention includes a process in which a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 3. In one embodiment at least 10 chromosome interactions represented by the probes in Table 3 are typed.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 3 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 3 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 3.
The invention includes a process in which a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 4. In one embodiment at least 10 chromosome interactions represented by the probes in Table 4 are typed.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 4 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 5 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 4.
The invention includes a process in which a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 5. In one embodiment at least 10 chromosome interactions represented by the probes in Table 5 are typed.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 5 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 5 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 5.
The invention includes a process in which a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 6. In one embodiment at least 10 chromosome interactions represented by the probes in Table 6 are typed.
The invention provides a process in which all of the chromosome interactions represented by the probes in Table 6 are typed. In certain embodiments at least 30, 40, 50, 60 or 80 of the chromosome interactions represented by the probes in Table 6 are typed. In particular embodiments at least 10, 20, 30, 50 or 80 chromosome interactions are typed which are present in a 4,000 base region which comprises or which flanks the chromosome interactions represented by the probes in Table 6.
The invention provides a process which comprises detecting the presence or absence of chromosome interactions, typically 5 to 20 or 5 to 500 such interactions, preferably 20 to 300 or 50 to 100 interactions, in order to determine the presence or absence of a characteristic relating to a subgroup. Preferably the chromosome interactions are those in any of the genes mentioned herein or in which chromosome interactions of the invention are present within.
In one aspect all of the interactions of Table 1 are typed. In one aspect all of the interactions of Table 2 are typed. In one aspect all of the interactions of Table 3 are typed. In one aspect all of the interactions of Table 4 are typed. In one aspect all of the interactions of Table 5 are typed. In one aspect all of the interactions of Table 6 are typed. In one aspect all of the interactions of Tables 3 and 4 are typed. In one aspect all of the interactions of Tables 5 and 6 are typed. In one aspect all of the interactions of Tables 3, 4, 5 and 6 are typed.
The detection of certain interactions shows presence of the relevant characteristic, whilst the presence of other interactions shows absence of the relevant characteristic as described in the tables.
Selecting Markers from Different Tables
The chromosome interactions which are typed can be selected from a single table or from more than one of Tables 1, 2, 3, 4, 5 or 6. Typically at least 5, 8, 10, 12, 15, 20, 25, 30, 40, 50, 60, 70, 80 interactions are typed. This number of interactions can be selected from 1, 2, 3, 4, 5 of or all of the Tables 1, 2, 3, 4, 5 or 6. In one aspect at least 5, 8, 10, 12, 15, 20 interactions to be typed are selected from all of Tables 3, 4, 5 and 6. In one aspect at least 3, 5, 8 or 10 interactions are selected from each of Tables 3 and 4. In one aspect at least 3, 5, 8 or 10 interactions are selected from each of Tables 5 and 6. In one aspect at least 10 interactions to be typed are selected from each of Tables 3 and 4. In one aspect at least 10 interactions to be typed are selected from each of Tables 5 and 6.
A SHAPLEY analysis provides one way of measuring the performance of an individual marker. Tables 7 to 10 show the results of such modelling. In one aspect the markers to be typed can be selected based on these results, example based on any of the parameters which are shown. In a preferred aspect the chromosome interactions which are typed represent the top 10, 20, 30, 40, 50 or 60 markers selected based on such a parameter.
In a preferred aspect the ‘SHAPLEY_diff’ column is used to provide an indication of the power of a marker, and so for example the marker ORF1_chr6_31267448_31269252_31531115_31534994_RF_1 in Table 7 could be seen as the most powerful marker, given that it has the highest value for ‘SHAPLEY_diff’. Tables 7 to 10 list the markers in order of magnitude of ‘SHAPLEY_diff’, going from the most important to the less important as one goes down each table.
In one aspect at least 3 markers may be typed from the 5, 8, 10 or 20 markers shown at the top of Table 7. In one aspect at least 5 markers are typed from the 10 markers shown at the top of Table 7. In one aspect at least 5 markers may be typed from 20, 30, 40 or 50 markers shown at the top of Table 7. In one aspect at least 10 markers may be typed from the 30, 40 or 50 markers shown at the top of Table 7. In one aspect at least the 5, 8 or 10 markers shown at the top of Table 7 may be typed.
In one aspect at least 3 markers may be typed from the 5, 8, 10 or 20 markers shown at the top of Table 8. In one aspect at least 5 markers are typed from the 10 markers shown at the top of Table 8. In one aspect at least 5 markers may be typed from 20, 30, 40 or 50 markers shown at the top of Table 8. In one aspect at least 10 markers may be typed from the 30, 40 or 50 markers shown at the top of Table 8. In one aspect at least the 5, 8 or 10 markers shown at the top of Table 8 may be typed.
In one aspect at least 3 markers may be typed from the 5, 8, 10 or 20 markers shown at the top of Table 9. In one aspect at least 5 markers are typed from the 10 markers shown at the top of Table 9. In one aspect at least 5 markers may be typed from 20, 30, 40 or 50 markers shown at the top of Table 9. In one aspect at least 10 markers may be typed from the 30, 40 or 50 markers shown at the top of Table 9. In one aspect at least the 5, 8 or 10 markers shown at the top of Table 9 may be typed.
In one aspect at least 3 markers may be typed from the 5, 8, 10 or 20 markers shown at the top of Table 10. In one aspect at least 5 markers are typed from the 10 markers shown at the top of Table 10. In one aspect at least 5 markers may be typed from 20, 30, 40 or 50 markers shown at the top of Table 10. In one aspect at least 10 markers may be typed from the 30, 40 or 50 markers shown at the top of Table 10. In one aspect at least the 5, 8 or 10 markers shown at the top of Table 10 may be typed.
The Individual that is Tested
The individual that is tested in the process of the invention may have been selected in some way. The individual may be susceptible to any condition mentioned herein and/or may be in need of any therapy mentioned in. The individual may be receiving any therapy mentioned herein. In particular, the individual may have, or be suspected of having, fibrosis. The individual may have, or be suspected of having, a skin fibrotic condition, which may preferably be scleroderma.
The individual may have, or be suspected of having, a scleroderma condition that results in changes to the skin, blood vessels, muscles, and internal organs. The individual may have any one of the following symptoms: areas of thickened skin, stiffness, feeling tired, and poor blood flow to the fingers or toes with cold exposure. The individual may have, or be suspected of having, CREST syndrome, which may manifest as calcium deposits, Raynaud's syndrome, esophageal problems, thickening of the skin of the fingers and toes, and areas of small dilated blood vessels.
In one aspect the locus (including the gene and/or place where the chromosome interaction is detected) may comprise a CTCF binding site. This is any sequence capable of binding transcription repressor CTCF. That sequence may consist of or comprise the sequence CCCTC which may be present in 1, 2 or 3 copies at the locus. The CTCF binding site sequence may comprise the sequence CCGCGNGGNGGCAG (in IUPAC notation). The CTCF binding site may be within at least 100, 500, 1000 or 4000 bases of the chromosome interaction or within any of the chromosome regions shown Table 1 or 2. The CTCF binding site may be within at least 100, 500, 1000 or 4000 bases of the chromosome interaction or within any of the chromosome regions shown Table 3, 4, 5 or 6.
When detection is performed using a probe, typically sequence from both regions of the probe (i.e. from both sites of the chromosome interaction) could be detected. In preferred aspects probes are used in the process which comprise or consist of the same or complementary sequence to a probe shown in any table. In some aspects probes are used which comprise sequence which is homologous to any of the probe sequences shown in the tables.
Tables 1 to 6 show specific markers represented by probes and relevant data. The probe sequences show sequence which can be used to detect a ligated product generated from both sites of gene regions that have come together in chromosome interactions, i.e. the probe will comprise sequence which is complementary to sequence in the ligated product. The first two sets of Start-End positions show probe positions, and the second two sets of Start-End positions show the relevant 4 kb region.
Table 1 shows 100 markers relating to early or late fibrosis (scleroderma), with 50 markers corresponding to each. Table 2 shows 100 markers relating to presence of fibrosis (scleroderma), with 50 associated with disease and 50 associated with absence of disease.
Table 3 shows 100 markers associated with early fibrosis (scleroderma).
Table 4 shows 100 markers associated with late fibrosis (scleroderma).
Table 5 shows 100 markers associated with presence of fibrosis (scleroderma).
Table 6 shows 100 markers associated with the absence of fibrosis (scleroderma).
The following information is provided in the probe data table:
RP—Rsum the Rank Product statistics evaluated per each chromosome interaction
FC—Interaction frequency (positive or negative)
Pfp—estimated percentage of false positive predictions (pfp), both considering positive and negative chromosome interactions
Pval—estimated pvalues per each CCSs being positive and negative
Adj.P.value (FDR)—False discovery rate adjusted p.value
Loop Detected—which state the loop is found in
Simple permutation-based estimation is used to determine how likely a given RP value or better is observed in a random experiment. This has the following steps:
1. Generate p permutations of k rank lists of length n.
2. Calculate the rank products of the n CCS in the p permutations.
3. Count (c) how many times the rank products of the CCS in the permutations are smaller or equal to the observed rank product. Set c to this value.
4. Calculate the average expected value for the rank product by: Erp (g)=c/p.
5. Calculate the percentage of false positives as: pfp (g)=Erp (g)/rank (g) where rank (g) is the rank of CCS g in a list of all n CCSs sorted by increasing RP.
The rank product statistic ranks chromosome interactions according to intensities within each microarray and calculates the product of these ranks across multiple microarrays. This technique can identify chromosome interactions that are consistently detected among the most differential chromosome interactions in a number of replicated microarrays. Where the p-value is 0 this indicates that there is very little variation in the Rank Product of the CCS across the samples, this is a good example of the signal to noise and effect size of CCS. Where p value is 0 and pfp is 0 this means that permutated Rank Product doesn't differ from the actual observed Rank Product. These methods are described Breitling R and Herzyk P (2005) Rank-based methods as a non-parametric alternative of the t-test for the analysis of biological microarray data. J Bioinf Comp Biol 3, 1171-1189.
The FC indicates prevalence of marker in each comparison, 2 means twice over average test, 1.5 means 1.5 over the average test, etc., and so FC indicates the weight of a marker to phenotype/group. The FC value can be used to give an indication of how many markers are needed for a highly effective test.
The probes are designed to be 30 bp away from the Taq1 site. In case of PCR, PCR primers are typically designed to detect ligated product but their locations from the Taq1 site vary. Probe locations:
Start 1—30 bases upstream of Taql site on fragment 1
End 1—Taql restriction site on fragment 1
Start 2—Taql restriction site on fragment 2
End 2—30 bases downstream of Taql site on fragment 2
4 kb Sequence Location:
Start 1—4000 bases upstream of Taql site on fragment 1
End 1—Taql restriction site on fragment 1
Start 2—Taql restriction site on fragment 2
End 2—4000 bases downstream of Taql site on fragment 2
SHAPLEY analysis can show the importance of each marker. It related to the marginal contribution of the marker to the Random Forest Model. The Shapley value is a solution concept in cooperative game theory applied to Machine learning to explain the contribution of markers to models Table 7 shows SHAPLEY results for markers associated with early fibrosis.
Table 8 shows SHAPLEY results for markers associated with late fibrosis.
Table 9 shows SHAPLEY results for markers associated with presence of fibrosis.
Table 10 shows SHAPLEY results for markers associated with absence of fibrosis.
In these tables the following information is provided:
HC_SHAPLEY—Health Control Class SHAPLEY value
SSc_SHAPLEY—SSc Class SHAPLEY value
E_SHAPLEY—Early Class SHAPLEY value
L_SHAPLEY—Late Class SHAPLEY value
SHAPLEY_diff—Difference between the two classes SHAPLEY Values
RPs_class1_class2—Rank Product Difference
RPrank_class1_class2—Rank Product Rank
pfp_class1_class2—percentage of false predictions
pval_class1_class2—Rank Product Pvalue
LogFC—Log Abundance Difference
FC—Linear Abundance Difference
The invention described herein relates to chromosome conformation profile and 3D architecture as a regulatory modality in its own right, closely linked to the phenotype. The discovery of biomarkers was based on annotations through pattern recognition and screening on representative cohorts of clinical samples representing the differences in phenotypes. We annotated and screened significant parts of the genome, across coding and non-coding parts and over large sways of non-coding 5′ and 3′ of known genes for identification of statistically disseminating consistent conditional disseminating chromosome conformations, which for example anchor in the non-coding sites within (intronic) or outside of open reading frames.
In selection of the best markers we are driven by statistical data and p values for the marker leads. Selected and validated chromosome conformations within the signature are disseminating stratifying entities in their own right, irrespective of the expression profiles of the genes used in the reference. Further work may be done on relevant regulatory modalities, such as SNPs at the anchoring sites, changes in gene transcription profiles, changes at the level of H3K27ac.
We are taking the question of clinical phenotype differences and their stratification from the basis of fundamental biology and epigenetics controls over phenotype—including for example from the framework of network of regulation. As such, to assist stratification, one can capture changes in the network and it is preferably done through signatures of several biomarkers, for example through following a machine learning algorithm for marker reduction which includes evaluating the optimal number of markers to stratify the testing cohort with minimal noise. This may end with 3-20 markers. Selection of markers for panels may be done by cross-validation statistical performance (and not for example by the functional relevance of the neighbouring genes, used for the reference name).
A panel of markers (with names of adjacent genes) is a product of clustered selection from the screening across significant parts of the genome, in non-biased way analysing statistical disseminating powers over 14,000-60,000 annotated EpiSwitch sites across significant parts of the genome. It should not be perceived as a tailored capture of a chromosome conformation on the gene of know functional value for the question of stratification. The total number of sites for chromosome interaction are 1.2 million, and so the potential number of combinations is 1.2 million to the power 1.2 million. The approach that we have followed nevertheless allows the identifying of the relevant chromosome interactions.
The specific markers that are provided by this application have passed selection, being statistically (significantly) associated with the condition. This is what the data in the relevant table demonstrates. Each marker can be seen as representing an event of biological epigenetic as part of network deregulation that is manifested in the relevant condition. In practical terms it means that these markers are prevalent across groups of patients when compared to controls. On average, as an example, an individual marker may typically be present in 80% of patients tested and in 10% of controls tested.
Simple addition of all markers would not represent the network interrelationships between some of the deregulations. This is where the standard multivariate biomarker analysis GLMNET (R package) is brought in. GLMNET package helps to identify interdependence between some of the markers, that reflect their joint role in achieving deregulations leading to disease phenotype. Modelling and then testing markers with highest GLMNET scores offers not only identify the minimal number of markers that accurately identifies the patient cohort, but also the minimal number that offers the least false positive results in the control group of patients, due to background statistical noise of low prevalence in the control group. Typically a group (combination) of selected markers (such as 3 to 10) offers the best balance between both sensitivity and specificity of detection, emerging in the context of multivariate analysis from individual properties of all the selected statistical significant markers for the condition.
The tables herein show the reference names for the array probes (60-mer) for array analysis that overlaps the juncture between the long range interaction sites, the chromosome number and the start and end of two chromosomal fragments that come into juxtaposition.
Methods of preparing samples and detecting chromosome conformations are described herein. Optimised (non-conventional) versions of these processes can be used, for example as described in this section.
Typically the sample will contain at least 2×105 cells. The sample may contain up to 5×105 cells. In one aspect, the sample will contain 2×105 to 5.5×105 cells
Crosslinking of epigenetic chromosomal interactions present at the chromosomal locus is described herein. This may be performed before cell lysis takes place. Cell lysis may be performed for 3 to 7 minutes, such as 4 to 6 or about 5 minutes. In some aspects, cell lysis is performed for at least 5 minutes and for less than 10 minutes.
Digesting DNA with a restriction enzyme is described herein. Typically, DNA restriction is performed at about 55° C. to about 70° C., such as for about 65° C., for a period of about 10 to 30 minutes, such as about 20 minutes.
Preferably a frequent cutter restriction enzyme is used which results in fragments of ligated DNA with an average fragment size up to 4000 base pair. Optionally the restriction enzyme results in fragments of ligated DNA have an average fragment size of about 200 to 300 base pairs, such as about 256 base pairs.
In one aspect, the typical fragment size is from 200 base pairs to 4,000 base pairs, such as 400 to 2,000 or 500 to 1,000 base pairs.
In one aspect of the EpiSwitch process a DNA precipitation step is not performed between the DNA restriction digest step and the DNA ligation step.
DNA ligation is described herein. Typically the DNA ligation is performed for 5 to 30 minutes, such as about 10 minutes.
The protein in the sample may be digested enzymatically, for example using a proteinase, optionally Proteinase K. The protein may be enzymatically digested for a period of about 30 minutes to 1 hour, for example for about 45 minutes. In one aspect after digestion of the protein, for example Proteinase K digestion, there is no cross-link reversal or phenol DNA extraction step.
In one aspect PCR detection is capable of detecting a single copy of the ligated nucleic acid, preferably with a binary read-out for presence/absence of the ligated nucleic acid.
The process of the invention can be described in different ways. It can be described as a process of making a ligated nucleic acid comprising (i) in vitro cross-linking of chromosome regions which have come together in a chromosome interaction; (ii) subjecting said cross-linked DNA to cutting or restriction digestion cleavage; and (iii) ligating said cross-linked cleaved DNA ends to form a ligated nucleic acid, wherein detection of the ligated nucleic acid may be used to determine the chromosome state at a locus, and wherein preferably:
The process of the invention can be described as a process for detecting chromosome states which represent different subgroups in a population comprising determining whether a chromosome interaction is present or absent within a defined epigenetically active region of the genome, wherein preferably:
Knowledge of chromosome interactions can be used to identify new treatments for conditions. The invention provides processes and uses of chromosome interactions defined herein to identify or design new therapeutic agents, for example relating to therapy of fibrosis or related sub-conditions.
Homologues of polynucleotide/nucleic acid (e.g. DNA) sequences are referred to herein. Such homologues typically have at least 70% homology, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98% or at least 99% homology, for example over a region of at least 10, 15, 20, 30, 100 or more contiguous nucleotides, or across the portion of the nucleic acid which is from the region of the chromosome involved in the chromosome interaction. The homology may be calculated on the basis of nucleotide identity (sometimes referred to as “hard homology”).
Therefore, in a particular aspect, homologues of polynucleotide/nucleic acid (e.g. DNA) sequences are referred to herein by reference to percentage sequence identity. Typically such homologues have at least 70% sequence identity, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98% or at least 99% sequence identity, for example over a region of at least 10, 15, 20, 30, 100 or more contiguous nucleotides, or across the portion of the nucleic acid which is from the region of the chromosome involved in the chromosome interaction.
For example the UWGCG Package provides the BESTFIT program which can be used to calculate homology and/or % sequence identity (for example used on its default settings) (Devereux et al (1984) Nucleic Acids Research 12, p387-395). The PILEUP and BLAST algorithms can be used to calculate homology and/or % sequence identity and/or line up sequences (such as identifying equivalent or corresponding sequences (typically on their default settings)), for example as described in Altschul S. F. (1993) J Mol Evol 36:290-300; Altschul, S, F et al (1990) J Mol Biol 215:403-10.
Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information. This algorithm involves first identifying high scoring sequence pair (HSPs) by identifying short words of length W in the query sequence that either match or satisfy some positive-valued threshold score T when aligned with a word of the same length in a database sequence. T is referred to as the neighbourhood word score threshold (Altschul et al, supra). These initial neighbourhood word hits act as seeds for initiating searches to find HSPs containing them. The word hits are extended in both directions along each sequence for as far as the cumulative alignment score can be increased. Extensions for the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached. The BLAST algorithm parameters W5 T and X determine the sensitivity and speed of the alignment. The BLAST program uses as defaults a word length (W) of 11, the BLOSUM62 scoring matrix (see Henikoff and Henikoff (1992) Proc. Natl. Acad. Sci. USA 89: 10915-10919) alignments (B) of 50, expectation (E) of 10, M=5, N=4, and a comparison of both strands.
The BLAST algorithm performs a statistical analysis of the similarity between two sequences; see e.g., Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90: 5873-5787. One measure of similarity provided by the BLAST algorithm is the smallest sum probability (P(N)), which provides an indication of the probability by which a match between two polynucleotide sequences would occur by chance. For example, a sequence is considered similar to another sequence if the smallest sum probability in comparison of the first sequence to the second sequence is less than about 1, preferably less than about 0.1, more preferably less than about 0.01, and most preferably less than about 0.001.
The homologous sequence typically differs by 1, 2, 3, 4 or more bases, such as less than 10, 15 or 20 bases (which may be substitutions, deletions or insertions of nucleotides). These changes may be measured across any of the regions mentioned above in relation to calculating homology and/or % percentage sequence identity.
Homology of a ‘pair of primers’ can be calculated, for example, by considering the two sequences as a single sequence (as if the two sequences are joined together) for the purpose of then comparing against the another primer pair which again is considered as a single sequence.
The second set of nucleic acids may be bound to an array, and in one aspect there are at least 15,000, 45,000, 100,000 or 250,000 different second nucleic acids bound to the array, which preferably represent at least 300, 900, 2000 or 5000 loci. In one aspect one, or more, or all of the different populations of second nucleic acids are bound to more than one distinct region of the array, in effect repeated on the array allowing for error detection. The array may be based on an Agilent SurePrint G3 Custom CGH microarray platform. Detection of binding of first nucleic acids to the array may be performed by a dual colour system.
This section is relevant both to:
The invention provides therapeutic agents for use in preventing or treating a disease condition in certain individuals, for example those identified by a process of the invention. This may comprise administering to an individual in need a therapeutically effective amount of the agent. The invention provides use of the agent in the manufacture of a medicament to prevent or treat a condition in certain individuals. The disease or condition may be fibrosis, any type of fibrosis sub-condition or a stage of fibrosis.
The formulation of the agent will depend upon the nature of the agent. The agent will be provided in the form of a pharmaceutical composition containing the agent and a pharmaceutically acceptable carrier or diluent. Suitable carriers and diluents include isotonic saline solutions, for example phosphate-buffered saline. Typical oral dosage compositions include tablets, capsules, liquid solutions and liquid suspensions. The agent may be formulated for parenteral, intravenous, intramuscular, subcutaneous, transdermal or oral administration.
The dose of an agent may be determined according to various parameters, especially according to the substance used; the age, weight and condition of the individual to be treated; the route of administration; and the required regimen. A physician will be able to determine the required route of administration and dosage for any particular agent. A suitable dose may however be from 0.1 to 100 mg/kg body weight such as 1 to 40 mg/kg body weight, for example, to be taken from 1 to 3 times daily.
The therapeutic agent may be any such agent disclosed herein, or may target any ‘target’ disclosed herein, including any protein or gene disclosed herein in any table. It is understood that any agent that is disclosed in a combination should be seen as also disclosed for administration individually.
Therapeutic agents which can be used in the invention include:
The therapeutic agent may be selected from the following:
Astocilizumab is a preferred therapeutic agent.
Any of the substances, such as nucleic acids or therapeutic agents, mentioned herein may be in purified or isolated form. They may be in a form which is different from that found in nature, for example they may be present in combination with other substance with which they do not occur in nature. The nucleic acids (including portions of sequences defined herein) may have sequences which are different to those found in nature, for example having at least 1, 2, 3, 4 or more nucleotide changes in the sequence as described in the section on homology. The nucleic acids may have heterologous sequence at the 5′ or 3′ end. The nucleic acids may be chemically different from those found in nature, for example they may be modified in some way, but preferably are still capable of Watson-Crick base pairing. Where appropriate the nucleic acids will be provided in double stranded or single stranded form. The invention provides all of the specific nucleic acid sequences mentioned herein in single or double stranded form, and thus includes the complementary strand to any sequence which is disclosed.
The invention provides a kit for carrying out any process of the invention, including detection of a chromosomal interaction relating to prognosis. Such a kit can include a specific binding agent capable of detecting the relevant chromosomal interaction, such as agents capable of detecting a ligated nucleic acid generated by processes of the invention. Preferred agents present in the kit include probes capable of hybridising to the ligated nucleic acid or primer pairs, for example as described herein, capable of amplifying the ligated nucleic acid in a PCR reaction. A kit of the invention may comprise means to detect a panel of markers, such as any number of combination of markers disclosed herein.
The invention provides use of a reagent for preparing kit for carrying out the process of the invention. Such a reagent may be any suitable substance mentioned herein, such as the agents which are capable of detection of products of detection processes, including reagents which are any of the probes or primers mentioned herein. The invention provides use of the reagent in the process of the invention. The invention provides use of the reagent in the preparing of a means for carrying out the invention. The invention also provides a process for detecting a characteristic of fibrosis, including any type of fibrosis mentioned here and including detecting the stage of fibrosis or the presence of fibrosis.
The invention provides a method of obtaining diagnostic information relating to fibrosis, such as the stage and/or presence of fibrosis. The invention provides a method of detecting a chromosome state defined by any number or combination of chromosome interactions disclosed herein. The invention provides a method of detecting a specific pattern of chromosome interactions, for example as defined by any number or combination of chromosome interactions disclosed herein.
The invention provides a device that is capable of detecting the relevant chromosome interactions. The device preferably comprises any specific binding agents, probe or primer pair capable of detecting the chromosome interaction, such as any such agent, probe or primer pair described herein.
The invention provides use of detection of chromosome interactions as defined herein (for example by number or specific combination) to detect a characteristic of fibrosis, for example as defined herein. The invention provides use of a reagent (for example a probe, primer, label, device or array) in any method of the invention.
The markers which are disclosed herein have been found to be ‘disseminating markers’ capable of determining the relevant subgroup and Tables 1 to 6 show which subgroup each marker is present in.
In practical terms it means that these markers are prevalent across the relevant subgroup when compared to controls (as is shown by the FC value, for example). On average, as an example, an individual marker may typically be present in 80% of the relevant subgroup and in 10% of controls (for the subgroup). When testing an individual the result will be a combination of ‘present’ and ‘absent’ chromosome interactions for each of the markers shown in Tables 1 to 6 allowing determination of the subgroup for the individual. Typically presence/absence of at least 8 markers out of 10 compared to the ‘ideal’ result shown in the table can be used to assign the individual to a subgroup.
The invention relates to markers which are effective detecting a characteristic relating to fibrosis as described herein. Clearly different numbers of markers can be used as the basis of a test. In one aspect the invention provides a process for detecting a chromosome state which represents a subgroup in a population comprising determining whether a chromosome interaction relating to that chromosome state is present or absent within a defined region of the genome; wherein:
(i) one or more chromosome interactions are typed which are associated with early stage fibrosis from Tables 1 and 3 and if at least 70% or 80% of these are present the individual is classed as have early stage fibrosis, and/or
(ii) one or more chromosome interactions are typed which are associated with early stage fibrosis from Tables 1 and 3 and if at least 70% or 80% of these are absent the individual is classed as not having early stage fibrosis, and/or
(iii) one or more chromosome interactions are typed which are associated with late stage fibrosis from Tables 1 and 4 and if at least 70% or 80% of these are present the individual is classed as have late stage fibrosis, and/or
(iv) one or more chromosome interactions are typed which are associated with late stage fibrosis from Tables 1 and 4 and if at least 70% or 80% of these are absent the individual is classed as not having late stage fibrosis, and/or
(v) one or more chromosome interactions are typed which are associated with presence of fibrosis from Tables 2 and 5 and if at least 70% or 80% of these are present the individual is classed as having fibrosis, and/or
(vi) one or more chromosome interactions are typed which are associated with presence of fibrosis from Tables 2 and 5 and if at least 70% or 80% of these are absent the individual is classed as not having fibrosis, and/or
(vii) one or more chromosome interactions are typed which are associated with absence of fibrosis from Tables 2 and 6 and if at least 70% or 80% of these are present the individual is classed as having absence of fibrosis, and/or
(viii) one or more chromosome interactions are typed which are associated with absence of fibrosis from Tables 2 and 6 and if at least 70% or 80% of these are absent the individual is classed as having fibrosis.
In this aspect any number and combination of markers may be typed, for example as disclosed herein.
In one aspect quantitative detection of the ligated sequence which is relevant to a chromosome interaction is carried out using a probe which is detectable upon activation during a PCR reaction, wherein said ligated sequence comprises sequences from two chromosome regions that come together in an epigenetic chromosome interaction, wherein said process comprises contacting the ligated sequence with the probe during a PCR reaction, and detecting the extent of activation of the probe, and wherein said probe binds the ligation site. The process typically allows particular interactions to be detected in a MIQE compliant manner using a dual labelled fluorescent hydrolysis probe.
The probe is generally labelled with a detectable label which has an inactive and active state, so that it is only detected when activated. The extent of activation will be related to the extent of template (ligation product) present in the PCR reaction. Detection may be carried out during all or some of the PCR, for example for at least 50% or 80% of the cycles of the PCR.
The probe can comprise a fluorophore covalently attached to one end of the oligonucleotide, and a quencher attached to the other end of the nucleotide, so that the fluorescence of the fluorophore is quenched by the quencher. In one aspect the fluorophore is attached to the 5′end of the oligonucleotide, and the quencher is covalently attached to the 3′ end of the oligonucleotide. Fluorophores that can be used in the process of the invention include FAM, TET, JOE, Yakima Yellow, HEX, Cyanine3, ATTO 550, TAMRA, ROX, Texas Red, Cyanine 3.5, LC610, LC640, ATTO 647N, Cyanine 5, Cyanine 5.5 and ATTO 680. Quenchers that can be used with the appropriate fluorophore include TAM, BHQ1, DAB, Eclip, BHQ2 and BBQ650, optionally wherein said fluorophore is selected from HEX, Texas Red and FAM. Preferred combinations of fluorophore and quencher include FAM with BHQ1 and Texas Red with BHQ2.
Use of the Probe in a qPCR Assay
Hydrolysis probes of the invention are typically temperature gradient optimised with concentration matched negative controls. Preferably single-step PCR reactions are optimized. More preferably a standard curve is calculated. An advantage of using a specific probe that binds across the junction of the ligated sequence is that specificity for the ligated sequence can be achieved without using a nested PCR approach. The processes described herein allow accurate and precise quantification of low copy number targets. The target ligated sequence can be purified, for example gel-purified, prior to temperature gradient optimization. The target ligated sequence can be sequenced. Preferably PCR reactions are performed using about 10 ng, or 5 to 15 ng, or 10 to 20 ng, or 10 to 50 ng, or 10 to 200 ng template DNA. Forward and reverse primers are designed such that one primer binds to the sequence of one of the chromosome regions represented in the ligated DNA sequence, and the other primer binds to other chromosome region represented in the ligated DNA sequence, for example, by being complementary to the sequence.
The invention includes selecting primers and a probe for use in a PCR process as defined herein comprising selecting primers based on their ability to bind and amplify the ligated sequence and selecting the probe sequence based properties of the target sequence to which it will bind, in particular the curvature of the target sequence.
Probes are typically designed/chosen to bind to ligated sequences which are juxtaposed restriction fragments spanning the restriction site. In one aspect of the invention, the predicted curvature of possible ligated sequences relevant to a particular chromosome interaction is calculated, for example using a specific algorithm referenced herein. The curvature can be expressed as degrees per helical turn, e.g. 10.5° per helical turn. Ligated sequences are selected for targeting where the ligated sequence has a curvature propensity peak score of at least 5° per helical turn, typically at least 10°, 15° or 20° per helical turn, for example 5° to 20° per helical turn. Preferably the curvature propensity score per helical turn is calculated for at least 20, 50, 100, 200 or 400 bases, such as for 20 to 400 bases upstream and/or downstream of the ligation site. Thus in one aspect the target sequence in the ligated product has any of these levels of curvature. Target sequences can also be chosen based on lowest thermodynamic structure free energy.
In one aspect only intrachromosomal interactions are typed/detected, and no extrachromosomal interactions (between different chromosomes) are typed/detected.
In particular aspects certain chromosome interactions are not typed, for example any specific interaction mentioned herein (for example as defined by any probe or primer pair mentioned herein). In some aspects chromosome interactions are not typed in any of the genes relevant to chromosome interactions mentioned herein.
The data provided herein shows that the markers are ‘disseminating’ ones able to differentiate cases and non-cases for the relevant disease situation. Therefore when carrying out the invention the skilled person will be able to determine by detection of the interactions which subgroup the individual is in. In one embodiment a threshold value of detection of at least 70% of the tested markers in the form they are associated with the relevant subgroup situation may be used to determine whether the individual is in the relevant subgroup.
In one aspect any single marker disclosed in any table might be typed together any other number or combination of markers disclosed herein (for example from the same table or one or more other tables).
In one aspect 1, 2, 3, 4, or more groups of markers may be typed which are each a number or combination of markers disclosed herein.
In one aspect 200 or less markers are typed, for example 100 or less markers, 50 or less, 25 or less, or 20 or less markers are typed. In one aspect 200 or less of the specific markers shown in the tables are typed, for example 100 or less, 50 or less, 25 or less, or 20 or less such markers are typed.
The invention provides a process of determining which chromosomal interactions are relevant to a chromosome state corresponding to an prognosis subgroup of the population, comprising contacting a first set of nucleic acids from subgroups with different states of the chromosome with a second set of index nucleic acids, and allowing complementary sequences to hybridise, wherein the nucleic acids in the first and second sets of nucleic acids represent a ligated product comprising sequences from both the chromosome regions that have come together in chromosomal interactions, and wherein the pattern of hybridisation between the first and second set of nucleic acids allows a determination of which chromosomal interactions are specific to an prognosis subgroup. The subgroup may be any of the specific subgroups defined herein, for example with reference to particular conditions or therapies.
The contents of all publications mentioned herein are incorporated by reference into the present specification and may be used to further define the features relevant to the invention. The contents of all priority applications are incorporated by reference into the present specification and may be used to define the features relevant to the invention.
The method of the invention may include analysis of the chromosome interactions identified in the individual, for example using a classifier, which may increase performance, such as sensitivity or specificity. The classifier is typically one that has been ‘trained’ on samples from the population and such training may assist the classifier to detect any subgroup mentioned herein.
Certain embodiments will be described with reference to numbered paragraphs:
Paragraph 1. A process for detecting a chromosome state which represents a subgroup in a population comprising determining whether a chromosome interaction relating to that chromosome state is present or absent within a defined region of the genome; and
(i) is present in any one of the regions or genes listed in Table 1; and/or
(ii) corresponds to any one of the chromosome interactions represented by any probe shown in Table 1; and/or
(iii) is present in a 4,000 base region which comprises or which flanks (i) or (ii);
or
(a) is present in any one of the regions or genes listed in Table 2; and/or
(b) corresponds to any one of the chromosome interactions represented by any probe shown in Table 2, and/or
(c) is present in a 4,000 base region which comprises or which flanks (a) or (b).
Paragraph 2. A process according to Paragraph 1 wherein the subgroup relates to the stage of sclerosis or the presence of sclerosis.
Paragraph 3. A process according to Paragraph 1 or 2 wherein a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 1.
Paragraph 4. A process according to any one of the preceding Paragraphs wherein a specific combination of chromosome interactions are typed comprising at least 3, 5, 8, 10 or 20 of the chromosome interactions represented by the probes in Table 2.
Paragraph 5. A process according to any one of the preceding Paragraphs which is carried out to detect the whether the fibrosis is early stage or late stage fibrosis.
Paragraph 6. A process according to any one of the preceding Paragraphs which is carried out to determine the stage of fibrosis in an individual and wherein at least 10 chromosome interactions represented by the probes of Table 1 are typed.
Paragraph 7. A process according to any one of Paragraphs 1 to 4 which is carried out to determine the stage of presence of fibrosis in an individual and wherein at least 10 chromosome interactions represented by the probes of Table 2 are typed.
Paragraph 8. A process according to any one of the preceding Paragraphs in which the chromosome interactions are typed:
(i) by a probe that has at least 70% identity to any of the specific probe sequences mentioned in Table 1 or 2, and/or
(ii) by a primer pair which has at least 70% identity to any primer pair in Table 1 or 2.
Paragraph 9. A process according to any one of the preceding Paragraphs, wherein:
Paragraph 10. A process according to any one of the preceding Paragraphs wherein:
Paragraph 11. A process according to any one of the preceding Paragraphs, wherein the first set of nucleic acids is obtainable in a process comprising the steps of:
(i) cross-linking of chromosome regions which have come together in a chromosome interaction;
(ii) subjecting said cross-linked regions to cleavage, optionally by restriction digestion cleavage with an enzyme; and
(iii) ligating said cross-linked cleaved DNA ends to form the first set of nucleic acids (in particular comprising ligated DNA).
Paragraph 12. A process according to any one of the preceding Paragraphs wherein said defined region of the genome:
(i) comprises a single nucleotide polymorphism (SNP); and/or
(ii) expresses a microRNA (miRNA); and/or
(iii) expresses a non-coding RNA (ncRNA); and/or
(iv) expresses a nucleic acid sequence encoding at least 10 contiguous amino acid residues; and/or
(v) expresses a regulating element; and/or
(vii) comprises a CTCF binding site.
Paragraph 13. A process according to any one of the preceding Paragraphs wherein:
Paragraph 14. A process according to any one of Paragraphs 1 to 12 which is carried out to identify or design a therapeutic agent for fibrosis;
and wherein optionally:
Paragraph 15. A process according to Paragraph 14 which comprises selecting a target based on detection of the chromosome interactions, and preferably screening for a modulator of the target to identify a therapeutic agent for fibrosis, wherein said target is optionally a protein.
Paragraph 16. A process according to any one of the preceding claims, wherein the typing or detecting comprises specific detection of the ligated product by quantitative PCR (qPCR) which uses primers capable of amplifying the ligated product and a probe which binds the ligation site during the PCR reaction, wherein said probe comprises sequence which is complementary to sequence from each of the chromosome regions that have come together in the chromosome interaction, wherein preferably said probe comprises:
an oligonucleotide which specifically binds to said ligated product, and/or
a fluorophore covalently attached to the 5′ end of the oligonucleotide, and/or
a quencher covalently attached to the 3′ end of the oligonucleotide, and
optionally
said fluorophore is selected from HEX, Texas Red and FAM; and/or
said probe comprises a nucleic acid sequence of length 10 to 40 nucleotide bases, preferably a length of 20 to 30 nucleotide bases.
Paragraph 17. A therapeutic agent for use in a method of treating fibrosis in an individual that has been identified as being in need of the therapeutic agent by a process according to any one of Paragraphs 1 to 12 and 16.
The EpiSwitch™ platform technology detects epigenetic regulatory signatures of regulatory changes between normal and abnormal conditions at loci. The EpiSwitch™ platform identifies and monitors the fundamental epigenetic level of gene regulation associated with regulatory high order structures of human chromosomes also known as chromosome conformation signatures. Chromosome signatures are a distinct primary step in a cascade of gene deregulation. They are high order biomarkers with a unique set of advantages against biomarker platforms that utilize late epigenetic and gene expression biomarkers, such as DNA methylation and RNA profiling.
The custom EpiSwitch™ array-screening platforms come in 4 densities of, 15K, 45K, 100K, and 250K unique chromosome conformations, each chimeric fragment is repeated on the arrays 4 times, making the effective densities 60K, 180K, 400K and 1 Million respectively.
The 15K EpiSwitch™ array can screen the whole genome including around 300 loci interrogated with the EpiSwitch™ Biomarker discovery technology. The EpiSwitch™ array is built on the Agilent SurePrint G3 Custom CGH microarray platform; this technology offers 4 densities, 60K, 180K, 400K and 1 Million probes. The density per array is reduced to 15K, 45K, 100K and 250K as each EpiSwitch™ probe is presented as a quadruplicate, thus allowing for statistical evaluation of the reproducibility. The average number of potential EpiSwitch™ markers interrogated per genetic loci is 50, as such the numbers of loci that can be investigated are 300, 900, 2000, and 5000.
The EpiSwitch™ array is a dual colour system with one set of samples, after EpiSwitch™ library generation, labelled in Cy5 and the other of sample (controls) to be compared/analyzed labelled in Cy3. The arrays are scanned using the Agilent SureScan Scanner and the resultant features extracted using the Agilent Feature Extraction software. The data is then processed using the EpiSwitch™ array processing scripts in R. The arrays are processed using standard dual colour packages in Bioconductor in R: Limma*. The normalisation of the arrays is done using the normalisedWithinArrays function in Limma* and this is done to the on chip Agilent positive controls and EpiSwitch™ positive controls. The data is filtered based on the Agilent Flag calls, the Agilent control probes are removed and the technical replicate probes are averaged, in order for them to be analysed using Limma*. The probes are modelled based on their difference between the 2 scenarios being compared and then corrected by using False Discovery Rate. Probes with Coefficient of Variation (CV)<=30% that are <=−1.1 or =>1.1 and pass the p<=0.1 FDR p-value are used for further screening. To reduce the probe set further Multiple Factor Analysis is performed using the FactorMineR package in R.
*Note: LIMMA is Linear Models and Empirical Bayes Processes for Assessing Differential Expression in Microarray Experiments. Limma is an R package for the analysis of gene expression data arising from microarray or RNA-Seq.
The pool of probes is initially selected based on adjusted p-value, FC and CV<30% (arbitrary cut off point) parameters for final picking. Further analyses and the final list are drawn based only on the first two parameters (adj. p-value; FC).
EpiSwitch™ screening arrays are processed using the EpiSwitch™ Analytical Package in R in order to select high value EpiSwitch™ markers for translation on to the EpiSwitch™ PCR platform.
Probes are selected based on their corrected p-value (False Discovery Rate, FDR), which is the product of a modified linear regression model. Probes below p-value <=0.1 are selected and then further reduced by their Epigenetic ratio (ER), probes ER have to be <=−1.1 or =>1.1 in order to be selected for further analysis. The last filter is a coefficient of variation (CV), probes have to be below <=0.3.
The top 40 markers from the statistical lists are selected based on their ER for selection as markers for PCR translation. The top 20 markers with the highest negative ER load and the top 20 markers with the highest positive ER load form the list.
The resultant markers from step 1, the statistically significant probes form the bases of enrichment analysis using hypergeometric enrichment (HE). This analysis enables marker reduction from the significant probe list, and along with the markers from step 2 forms the list of probes translated on to the EpiSwitch™ PCR platform.
The statistical probes are processed by HE to determine which genetic locations have an enrichment of statistically significant probes, indicating which genetic locations are hubs of epigenetic difference.
The most significant enriched loci based on a corrected p-value are selected for probe list generation. Genetic locations below p-value of 0.3 or 0.2 are selected. The statistical probes mapping to these genetic locations, with the markers from step 2, form the high value markers for EpiSwitch™ PCR translation.
EpiSwitch™ biomarker signatures demonstrate high robustness, sensitivity and specificity in the stratification of complex disease phenotypes. This technology takes advantage of the latest breakthroughs in the science of epigenetics, monitoring and evaluation of chromosome conformation signatures as a highly informative class of epigenetic biomarkers. Current research methods deployed in academic environment require from 3 to 7 days for biochemical processing of cellular material in order to detect CCSs. Those procedures have limited sensitivity, and reproducibility; and furthermore, do not have the benefit of the targeted insight provided by the EpiSwitch™ Analytical Package at the design stage.
CCS sites across the genome are directly evaluated by the EpiSwitch™ Array on clinical samples from testing cohorts for identification of all relevant stratifying lead biomarkers. The EpiSwitch™ Array platform is used for marker identification due to its high-throughput capacity, and its ability to screen large numbers of loci rapidly. The array used was the Agilent custom-CGH array, which allows markers identified through the in silico software to be interrogated.
Potential markers identified by EpiSwitch™ Array are then validated either by EpiSwitch™ PCR or DNA sequencers (i.e. Roche 454, Nanopore MinION, etc.). The top PCR markers which are statistically significant and display the best reproducibility are selected for further reduction into the final EpiSwitch™ Signature Set, and validated on an independent cohort of samples. EpiSwitch™ PCR can be performed by a trained technician following a standardised operating procedure protocol established. All protocols and manufacture of reagents are performed under ISO 13485 and 9001 accreditation to ensure the quality of the work and the ability to transfer the protocols. EpiSwitch™ PCR and EpiSwitch™ Array biomarker platforms are compatible with analysis of both whole blood and cell lines. The tests are sensitive enough to detect abnormalities in very low copy numbers using small volumes of blood.
The tables give names to particular sets of probes and primers to be used in aspects of the invention. Alternative primer names for the following PCR marker sets are shown below:
For OBD168-669.671: OBD168-013.015
For OBD168-1729.1731: OBD168-265.267
For OBD168-1841.1843: OBD168-353.355
For OBD168-1361.1363: OBD168-97.99
For OBD168-1529.1531: OBD168-645.647
For OBD168-681.683: OBD168-661.663
For OBD168-921.923: OBD168-717.719
For OBD168-893.895: OBD168-705.707
For OBD168-1273.1275: OBD168-749.751
For OBD168-1629.1631: OBD168-737.739
For OBD168-885.887: OBD168-733.735
For OBD168-1741.1743: OBD168-781.783
The invention is illustrated by the following Examples:
In this work systemic sclerosis is being used as a model disease to investigate the chromatin conformation signature relevant to fibrosis.
Systemic sclerosis (scleroderma, SSc) is a heterogeneous fibrosis disease in which clinical outcomes vary widely. Predicting outcomes on an individual basis remains challenging despite progress made through autoantibody analysis and gene expression profiling. Effective targeted therapies are evolving and accurately predicting outcomes is important to enable patient stratification for therapy.
Scleroderma (systemic sclerosis, SSc) is a severe connective tissue disease in which an autoimmune process at onset is associated with downstream fibrosis of the skin and internal organs, as well as vascular damage. In general, SSc is difficult to treat and patients continue to suffer a disabling, progressive and potentially lethal disease. Comprehensive genetic studies have indicated association of scleroderma susceptibility with genes involved in innate and adaptive immunity. Activated macrophages are seen to infiltrate into the perivascular tissue at an early stage of the disease, expressing markers of the profibrotic M2 phenotype, such as CD206 and secreting growth factors such as TGFβ which drive fibrosis. Macrophages derived from SSc patients display an activation signature characterised by high CD206 and elevated arginase1, highest in patients with severe disease. Soluble CD206 is elevated in plasma and tissue fluid of patients as a biomarker of the M2 activation state. In co-culture, SSc macrophages secrete factors which stimulate fibroblasts to increase collagen I production.
In the present work, through profiling of blood derived macrophages a mixed activation state of macrophages has been identified in this disease. This includes identifying a macrophage activation signature which indicates a combined pro-inflammatory as well as M2-like pro-fibrotic state. Macrophages form patients release inflammatory proteins characteristic of this disease including IL-6, but are also pro-fibrotic, stimulating fibroblasts in co-culture. Using a signature across 3 markers (IFN¥, CD206 and Arg1) an activation signature present in 50% of patients has been identified, which is not seen in healthy control samples. These characteristics persist in tissue culturing implying that the signature results from an epigenetic change which fundamentally alters the macrophage state. Likely initiating factors including Th2 cytokines encountered in the disease microenvironment, tissue stiffness in the disease microenvironment, or stimulation by antibody/antigen complexes carried into the cells systemically.
Chromatin Conformation Signature (CCS) profiling of peripheral blood for systemic epigenetic deregulations was used in this work. The EpiSwitch platform offering high throughput and resolution chromosome conformation (3C) capture detects significant regulatory changes in 3D genome architecture and maps long range interaction between distant genomic locations. This, in turn, reveals the spatial disposition and physical properties of the chromosome, such as chromatin loops and inter-chromosomal connections, which have a role in network organization and genetic epistasis controlling gene expression.
This methodology was applied to patients with SSc to identify CCS associated with different phenotypes and can be used to stratify and identify patients into pathogenic subtypes.
We aimed to determine significant chromatin conformation signatures associated with presence of scleroderma and also detection of early and late phenotypes of scleroderma.
The EpiSwitch—based chromosome conformation capture (3C) method was applied to blood samples from early phenotype, and late phenotype SSc patients. Intact nuclei were isolated from peripheral blood mononuclear cells and subjected to formaldehyde fixation resulting in crosslinking between physically touching segments of the genome via contacts between their DNA bound proteins. For quantification of cross-linking frequencies, the cross-linked DNA was digested and then subjected to ligation. Cross-linking was then reversed and individual ligation products detected and quantified by EpiSwitch custom oligo array annotated across the whole genome to the anchoring sites of 3D genome architecture.
The UK sample cohort consisted of 4 Healthy Controls and 6 Scleroderma patient samples. The 6 Scleroderma patients were split between Early and Late stage disease. EpiSwitch libraries were generated from the received sample cohort (n=8) using the Robotic Delta9.1 with Qiagen column purification protocols. A pooled control was created from the 4 extracted Healthy control samples. These libraries were processed for using on the custom designed Agilent CGH array.
7 significant CCSs were found over the HLA-C, HLA-B and TNF regions on Chromosome 6 in the early phenotype. The top 10 pathways for genetic locations associated to the CCSs are shown in the table below for the early phenotype.
2 significant CCSs were found centred around the IFNG region of chromosome 12 in the late phenotype. The top 10 pathways for genetic locations associated to significant CCSs are shown in the table below for the late phenotype.
Table 1 and Table 2 show the markers that were identified by this work. They represent part of the 3D genomic regulatory control. There were distinct CCSs in the early phenotype compared to the late showing the CCSs change as the disease progresses and varies between phenotypes. The CCSs can be linked to each clinically defined subgroup to be used as a biomarker tool to predict outcome and progression in patients. The present work therefore provides both diagnostic and prognostic markers.
Subsequent work done in the same way identified the markers shown in Tables 3 to 6. The data provided in Tables 1 to 6 show the efficacy of these markers in identifying the subgroups they are associated with.
It must be appreciated that identifying the markers shown in the tables required the testing of many potential markers. A total of 170229 markers were studied in an array. In the first analysis, they were shortlisted to 100 diagnostic (HC VS SSc) and prognostic (late SSc VS early SSc) markers, (170029 dropped out). In the second analysis, a shortlist of top 200 prognostic (unique markers present in early and late SSc) and 200 diagnostic (unique markers present in SSc and HC) markers prepared (169829 dropped out).
For the second set of markers of Tables 3 to 6 additional modelling values has been provided based on a SHAPLEY analysis. The markers were used to build a Random Forest model and the markers contribution to the models was calculated using SHAPLEY. The results are shown in Tables 7 to 10, where the SHAPLEY difference column in each tab is the variable to rank importance, the larger the difference the more important it is in the model.
The top 100 markers for either early v late disease or SSc v pHC (healthy control), generate an average model accuracy of 94%, this is compared to a mean average of 45% when you randomly select 100 markers and do this 100 times. This difference in classifying accuracy clearly demonstrates the power of the statistically selected markers.
In conclusion, the present work has led to the identification of markers which each have a powerful association with a distinct characteristic of fibrosis, and therefore individual markers or small numbers of these markers can be the basis of an effective test for the stage or presence of fibrosis.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2008269.9 | Jun 2020 | GB | national |
This application is a 371 National Stage filing and claims the benefit under 35 U.S.C. § 120 of International Application No. PCT/GB2021/051356, filed 2 Jun. 2021, which claims priority to Great Britain Application No. GB2008269.9, filed 2 Jun. 2020, each of which is incorporated herein by reference in its entirety.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/GB2021/051356 | 6/2/2021 | WO |
