WO2019092438A1 - Procédé de détection d'une anomalie chromosomique fœtale - Google Patents

Procédé de détection d'une anomalie chromosomique fœtale Download PDF

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WO2019092438A1
WO2019092438A1 PCT/GB2018/053255 GB2018053255W WO2019092438A1 WO 2019092438 A1 WO2019092438 A1 WO 2019092438A1 GB 2018053255 W GB2018053255 W GB 2018053255W WO 2019092438 A1 WO2019092438 A1 WO 2019092438A1
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chromosome
fetal
fragment
size
calculating
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Matthew Forman
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Premaitha Limited
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material

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  • the invention relates to a novel method of detecting a fetal chromosomal abnormality, in particular, the invention relates to the detection of trisomy 21 (Down's syndrome) which comprises the step of calculating the probability (w) of each fragment size (s) being fetal in origin.
  • the invention also relates to kits for performing said method.
  • the invention also relates to a method of predicting the gender of a fetus within a pregnant female subject.
  • Down's Syndrome is a relatively common genetic disorder, affecting about 1 in 800 live births. This syndrome is caused by the presence of an extra whole chromosome 21 (trisomy 21 , T21), or less commonly, an extra substantial portion of that chromosome. Trisomies involving other autosomes (i.e. T13 or T18) also occur in live births, but more rarely than T21.
  • NIPD non-invasive prenatal diagnosis
  • the cell-free plasma DNA (referred to hereinafter as 'plasma DNA') consists primarily of short DNA molecules (80-200bp) of which typically 5%-20% are of fetal origin, the remainder being maternal (Birch et al., 2005, Clin Chem 51 , 312-320; Fan et al., 2010, Clin Chem 56, 1279-1286).
  • the cellular origins of plasma DNA molecules, and the mechanisms by which they enter the blood and are subsequently cleared from the circulation, are poorly understood. However, it is widely believed that the fetal component is largely the result of apoptotic cell death within the placenta (Bianchi, 2004, Placenta 25, S93- S101).
  • the fraction of the plasma DNA molecules that are of fetal origin varies from case to case with substantial individual variation. Superimposed on the individual variation is a general trend towards an increasing fetal component as gestational age increases (Birch et al., 2005, supra; Galbiati et al., 2005, Hum Genet 117, 243-248).
  • the fetal component is readily detectable early in gestation, typically as early as week 8.
  • the extra chromosome that characterises T21 would be expected to cause a 50% excess of DNA molecules derived from that chromosome, by comparison with a normal pregnancy.
  • the imbalance that results is expected to be only 5%, or a relative increase in the number of chromosome 21-derived fragments to a value of 1.05 relative to 1.00 for a normal pregnancy.
  • the imbalance in the number of chromosome 21-derived molecules in the population of molecules in maternal plasma will be correspondingly smaller or larger.
  • nucleotide sequence data ('DNA sequencing') for DNA molecules from maternal plasma.
  • bioinformatic techniques must be applied to assign, most simply by comparison with a reference human genome or genomes, individual molecules to chromosomes from which they originate.
  • a slight imbalance in the population of molecules is detectable as an excess in the number of chromosome 21-derived molecules over that expected from a normal pregnancy.
  • chromosome 21 comprises only a small fraction of the human genome (less than 2%)
  • a large number of DNA molecules from maternal plasma must be randomly sampled, sequenced, and assigned bioinformatically to particular chromosomes.
  • the total number of plasma DNA molecules required to be both (1) characterised by nucleotide sequence information derived from them, and then (2) reliably assigned to chromosomal locations, is smaller than that required to sample all or most of the fetal genome, but it is at least several hundred thousand molecules.
  • the minimal number required is a function of the fraction of the plasma DNA that makes up the fetal component of the population of maternal cell-free plasma DNA molecules.
  • the number is between one million or several million molecules.
  • the challenge of applying this method is considerable because of the high quantitative accuracy required in counting DNA molecules from particular chromosomal locations.
  • the DNA from maternal plasma is a mixture of genomes within which the fetal component is a small part. This quantitative technical problem is different in nature from identifying mutations at a particular locus within a DNA sample.
  • nucleotide sequence data can be obtained for sufficiently large numbers of plasma DNA, and given that bioinformatic methods can be reliably applied to assign a sufficiently large number to their chromosomal origin, statistical methods may be applied to determine the presence or absence of a chromosomal imbalance in the population of plasma DNA molecules with statistical confidence.
  • An obvious method to utilise sequencing data would be to exclude all fragments outside of a specified range, therefore increasing the fetal fraction in silico. However, this approach would render most of the sequencing data useless and would require a significant increase in the amount of sample processed and sequenced. Thus, digital enrichment could be considered as expensive, inefficient and impractical for use in a routine laboratory environment.
  • An alternative solution would be to enrich the proportion of the DNA originating from the fetus prior to sequencing. Such enrichment is already typically utilised via size selection methods that remove fragments of approximately 200bp or larger. Such methods have limited sensitivity and ability to enrich fetal fraction. To date, no method has been described that would allow a highly accurate and precise enrichment of fetal DNA from a biological sample.
  • a method of detecting a fetal chromosomal abnormality which comprises the steps of: (a) isolating nucleic acid fragments from within a biological sample obtained from a pregnant female subject;
  • step (d) calculating a total target weighted count (Nc ta rget) by summing the values obtained in step (b);
  • step (e) calculating a total reference weighted count (Nc) by summing the values obtained in step (c);
  • a method of predicting the gender of a fetus within a pregnant female subject comprising the steps of:
  • step (d) calculating a total target weighted count (Nc ta rget) by summing the values obtained in step (b);
  • step (e) calculating a total reference weighted count (Nc) by summing the values obtained in step (c);
  • Figure 1 Graphical Representation Depicting the Probability of a fragment of a given size being fetal.
  • Figure 2 Autosome ratio comparison, size-weighted vs. unweighted
  • Figure 5 Distributions of T21 -affected and unaffected sample groups for unweighted and weighted analysis methods.
  • FIG. 6 Distributions of T18-affected and unaffected sample groups for unweighted and weighted analysis methods.
  • Figure 7 Distributions of T13-affected and unaffected sample groups for unweighted and weighted analysis methods.
  • Figure 8 Effective fetal fraction at analysis for both the unweighted and size- weighted analysis methods.
  • Figure 9 Comparison of effective fetal fraction for trisomy-affected samples at analysis, between unweighted and size-weighted analysis methods.
  • a method of detecting a fetal chromosomal abnormality which comprises the steps of:
  • step (d) calculating a total target weighted count (Nc ta rget) by summing the values obtained in step (b);
  • step (e) calculating a total reference weighted count (Nc) by summing the values obtained in step (c);
  • the inventors have developed an alternative approach which makes better use of all fragments analysed. This utilises the known differences in fragment size profiles between fetal and maternal DNA molecules to weight (i.e. prioritise) fragments preferentially in the analysis if these have a higher probability of reflecting the karyotype of the fetus than that of the mother, and conversely to de-emphasise contributions from fragments which have a higher probability of originating from maternal tissue other than the placenta.
  • each fragment instead contributes a value of w[s] , where w is a weighting function and s is the size of the fragment in nucleotides, which is determined as part of the sequencing process.
  • the weighting function w used here is the probability that a fragment is fetal in origin, as plotted in Figure 1 and extrapolated in the specific probability (w) values shown in Table 1.
  • the total weighted count, N c , assigned to a chromosome c then results from summing all of the w[s] values for all fragments found to align against that chromosome.
  • the step of calculating the probability (w) of each fragment size (s) being fetal in origin in steps (b) and (c) comprises identifying the size (s) of each aligned fragment and allocating a w value for said fragment based on the values presented in Table 1.
  • the N Ctarget value is subjected to a GC correction step (as in prior methodology) and a normalised measure of the presence of fragments from this
  • chromosome in the sample is calculated; this is done for a target chromosome c ta rget by forming a proportion of the fragments counted against all autosomes (the proportion is relative to the sum of the N c values calculated for all autosomal chromsomes; these N c values have all also been subject to a GC correction step).
  • Calculation of the ratio i.e. 'autosome ratio' in step (f) is referred to as calculating the fi Ctarget value:
  • This autosome ratio is then used as input to a statistical model, which estimates the probability of trisomy to produce the final test result calculated in step (g).
  • references herein to "fetal chromosomal abnormality" refer to any genetic variation within a fetal chromosome and includes any variation in the native, non- mutant or wild type genetic code of said fetus.
  • genetic variations include: aneuploidies, duplications, translocations, mutations (e.g. point mutations), substitutions, deletions, single nucleotide polymorphisms (SNPs), chromosome abnormalities, Copy Number Variation (CNV), epigenetic changes and DNA inversions.
  • SNP single-nucleotide polymorphism
  • the genetic variation is a functional mutation i.e. one which is causative of a clinically relevant fetal disease or disorder.
  • a functional mutation i.e. one which is causative of a clinically relevant fetal disease or disorder.
  • a disease or disorder include thalassemia and cystic fibrosis, in addition to fragment length disorders, such as fragile X syndrome.
  • Mutations may be functional in that they affect amino acid encoding, or by disruption of regulatory elements (e.g., which may regulate gene expression, or by disruption of sequences - which may be exonic or intronic - involved in regulation of splicing).
  • fetal chromosomal abnormalities include: Down's Syndrome (Trisomy 21), Edward's Syndrome (Trisomy 18), Patau syndrome (Trisomy 13), Trisomy 9, Warkany syndrome (Trisomy 8), Cat Eye Syndrome (4 copies of chromosome 22), Trisomy 22, and Trisomy 16.
  • the detection of an abnormality in a gene, chromosome, or part of a chromosome, copy number may comprise the detection of and/or diagnosis of a condition selected from the group comprising Wolf-Hirschhorn syndrome (4p-), Cri du chat syndrome (5p-), Williams-Beuren syndrome (7-), Jacobsen Syndrome (11-), Miller-Dieker syndrome (17- ), Smith-Magenis Syndrome (17-), 22ql 1.2 deletion syndrome (also known as Velocardiofacial Syndrome, DiGeorge Syndrome, conotruncal anomaly face syndrome, Congenital Thymic Aplasia, and Strong Syndrome), Angelman syndrome (15-), and Prader-Willi syndrome (15-).
  • a condition selected from the group comprising Wolf-Hirschhorn syndrome (4p-), Cri du chat syndrome (5p-), Williams-Beuren syndrome (7-), Jacobsen Syndrome (11-), Miller-Dieker syndrome (17- ), Smith-Magenis Syndrome (17-), 22ql 1.2 deletion syndrome also known as Velocardiofacial Syndrome, DiGeorge Syndrome, conotrun
  • the detection of an abnormality in the chromosome copy number may comprise the detection of and/or diagnosis of a condition selected from the group comprising Turner syndrome (Ullrich-Turner syndrome or monosomy X), Klinefelter's syndrome, 47.XXY or XXY syndrome, 48.XXYY syndrome, 49.XXXXY Syndrome, Triple X syndrome, XXXX syndrome (also called tetrasomy X, quadruple X, or 48, XXXX), XXXXX syndrome (also called pentasomy X or 49, XXXXX) and XYY syndrome.
  • Turner syndrome Ullrich-Turner syndrome or monosomy X
  • Klinefelter's syndrome 47.XXY or XXY syndrome
  • 48.XXYY syndrome 48.XXYY syndrome
  • 49.XXXXY Syndrome Triple X syndrome
  • XXXX syndrome also called tetrasomy X, quadruple X
  • the target chromosome is chromosome 13, chromosome 18, chromosome 21 , the X chromosome or the Y chromosome.
  • the fetal chromosomal abnormality is a fetal chromosomal aneuploidy.
  • the fetal chromosomal aneuploidy is trisomy 13, trisomy 18 or trisomy 21.
  • the fetal chromosomal aneuploidy is trisomy 21 (Down's syndrome).
  • the skilled worker in the field will readily understand that the methodology of the invention can be applied to diagnosing cases where the fetus carries a substantial part of chromosome 21 rather than an entire chromosome.
  • the fetal chromosomal abnormality is a chromosomal insertion or a deletion, for example of up to 1 Mb, up to 5Mb, up to 10 Mb or up to 20Mb or greater than 20Mb.
  • samples may be obtained from the pregnant female subject in accordance with routine procedures.
  • the biological sample is maternal blood, plasma, serum, urine or saliva.
  • the biological sample is maternal plasma.
  • the step of obtaining maternal plasma will typically involve a 5-20ml blood sample (typically a peripheral blood sample) being withdrawn from the pregnant female subject (typically by venipuncture). Obtaining such a sample is therefore characterised as noninvasive of the fetal space, and is minimally invasive for the mother. Blood plasma is prepared by conventional means after removal of cellular material by centrifugation (Maron et al., 2007, Methods Mol Med 132, 51-63).
  • DNA is extracted from the maternal plasma by conventional methodology which is unbiased with respect to the nucleotide sequences of the plasma DNA (Maron et al., 2007, supra).
  • the population of plasma DNA molecules will typically comprise a fraction that is of fetal origin, and a fraction of maternal origin.
  • the step of isolating in step (a) comprises the preparation of a library of nucleic acid fragments.
  • step (a) comprises the preparation of a library of nucleic acid fragments ranging in size from 75-250 bp. It will be appreciated that the steps of isolating, fragmenting and library preparation may be conducted in accordance with routine procedures well known to the skilled person.
  • library preparation comprises the sequential steps of DNA end repair, adaptor ligation, clean up and PCR. Full experimental details of how a suitable nucleic acid library may be prepared are described in the methods section herein, in particular steps 1 - 49.
  • Steps (b) and (c) of the method of the invention conduct an alignment or matching analysis. Such an analysis will initially require measurement of the presence of one or more target sequences within the fragments isolated in step (a) or alternatively sequencing of said fragments. Thus, in one embodiment, steps (b) and (c) initially comprise sequencing the fragments isolated in step (a) or subjecting said fragments to SNP based methodology prior to alignment.
  • steps (b) and (c) initially comprise sequencing the fragments isolated in step (a).
  • the sequence data is obtained by a sequencing platform which comprises use of a polymerase chain reaction.
  • the sequence data is obtained using a next generation sequencing platform.
  • sequencing platforms have been extensively discussed and reviewed in: Loman et al (2012) Nature Biotechnology 30(5), 434- 439; Quail et al (2012) BMC Genomics 13, 341 ; Liu et al (2012) Journal of Biomedicine and Biotechnology 2012, 1-1 1 ; and Meldrum et al (2011) Clin Biochem Rev. 32(4): 177-195; the sequencing platforms of which are herein incorporated by reference.
  • next generation sequencing platforms include: Roche 454 (i.e. Roche 454 GS FLX), Applied Biosystems' SOLiD system (i.e. SOLiDv4), lllumina's GAIIx, HiSeq 2000 and MiSeq sequencers, Life Technologies' Ion Torrent semiconductor-based sequencing instruments, Pacific Biosciences' PacBio RS and Sanger's 3730x1.
  • Roche 454 i.e. Roche 454 GS FLX
  • SOLiDv4 Applied Biosystems' SOLiD system
  • lllumina's GAIIx HiSeq 2000 and MiSeq sequencers
  • Life Technologies' Ion Torrent semiconductor-based sequencing instruments Pacific Biosciences' PacBio RS and Sanger's 3730x1.
  • Each of Roche's 454 platforms employ pyrosequencing, whereby chemiluminescent signal indicates base incorporation and the intensity of signal correlates to the number of bases incorporated through homopolymer reads.
  • the isolated fragments are sequenced by a sequencing platform which comprises use of semiconductor-based sequencing methodology.
  • semiconductor-based sequencing methodology are that the instrument, chips and reagents are very cheap to manufacture, the sequencing process is fast (although off-set by emPCR) and the system is scalable, although this may be somewhat restricted by the bead size used for emPCR.
  • the isolated fragments are sequenced by a sequencing platform which comprises use of sequencing-by-synthesis.
  • Illumina's sequencing-by-synthesis (SBS) technology is currently a successful and widely-adopted next-generation sequencing platform worldwide.
  • TruSeq technology supports massively-parallel sequencing using a proprietary reversible terminator-based method that enables detection of single bases as they are incorporated into growing DNA strands.
  • a fluorescently-labeled terminator is imaged as each dNTP is added and then cleaved to allow incorporation of the next base. Since all four reversible terminator-bound dNTPs are present during each sequencing cycle, natural competition minimizes incorporation bias.
  • the isolated fragments are sequenced by a sequencing platform which comprises use of nanopore-based sequencing methodology.
  • the nanopore-based methodology comprises use of organic-type nanopores which mimic the situation of the cell membrane and protein channels in living cells, such as in the technology used by Oxford Nanopore Technologies (e.g. Branton D, Bayley H, et al (2008). Nature Biotechnology 26 (10), 1146-1153).
  • the nanopore-based methodology comprises use of a nanopore constructed from a metal, polymer or plastic material.
  • the next generation sequencing platform is selected from Life Technologies' Ion Torrent platform or Illumina's MiSeq.
  • the next generation sequencing platforms of this embodiment are both small in size and feature fast turnover rates but provide limited data throughput.
  • the next generation sequencing platform is a personal genome machine (PGM) which is Life Technologies' Ion Torrent Personal Genome Machine (Ion Torrent PGM).
  • PGM personal genome machine
  • Ion Torrent PGM Life Technologies' Ion Torrent Personal Genome Machine
  • the Ion Torrent device uses a strategy similar to sequencing-by-synthesis (SBS) but detects signal by the release of hydrogen ions resulting from the activity of DNA polymerase during nucleotide incorporation. In essence, the Ion Torrent chip is a very sensitive pH meter.
  • ISFET ion-sensitive field-effect transistor
  • the use of ISFET devices is well known to the person skilled in the art and is well within the scope of technology which may be used to obtain the sequence data required by the methods of the invention (Prodromakis et a/ (2010) IEEE Electron Device Letters 31 (9), 1053-1055; Purushothaman et al (2006) Sensors and Actuators B 1 14, 964-968; Toumazou and Cass (2007) Phil. Trans. R. Soc. B, 362, 1321-1328; WO 2008/107014 (DNA Electronics Ltd); WO 2003/073088 (Toumazou); US 2010/0159461 (DNA Electronics Ltd); the sequencing methodology of each are herein incorporated by reference).
  • the isolated fragments are sequenced by a sequencing platform which comprises use of release of ions, such as hydrogen ions.
  • ions such as hydrogen ions.
  • This embodiment provides a number of key advantages.
  • the Ion Torrent PGM is described in Quail et al (2012; supra) as the most inexpensive personal genome machines on the market (i.e. approx. $80,000).
  • Loman et al (2012; supra) describes the Ion Torrent PGM as producing the fastest throughput (80-100 Mb/h) and the shortest run time ( ⁇ 3 h).
  • the sequence data is obtained by multiplex capable iterations based upon the Life Technologies' Ion Torrent platform, such as an Ion Proton with a PI or Pll Chip, and further derivative devices and components thereof.
  • Such a matching analysis typically involves a bioinformatic analysis which is performed using suitable software and allocates hits for each fragment of a given chromosome (i.e. a target or reference chromosome) based on whether said fragment aligns with or is deemed to have originated from said chromosome.
  • a bioinformatic analysis which is performed using suitable software and allocates hits for each fragment of a given chromosome (i.e. a target or reference chromosome) based on whether said fragment aligns with or is deemed to have originated from said chromosome.
  • the alignment is conducted using IONA® software (Premaitha Helath pic), Bowtie2 or BWA-SW (Li and Durbin (2010) Bioinformatics, Epub) alignment software or alignment software employing Maximal Exact Matching techniques, such as BWA-MEM
  • the alignment is conducted using Bowtie2 software.
  • the Bowtie2 software is Bowtie2 2.0.0-beta7.
  • the alignment is conducted using alignment software employing Maximal Exact Matching (MEM) techniques, such as BWA-MEM
  • the method additionally comprises the step of collapsing duplicate reads from the sequence data obtained prior to alignment steps (b) and (c).
  • step (b) comprises size-weighting of each fragment which uniquely aligns to a target region of a target chromosome by calculating the probability (w) of each fragment size (s) being fetal in origin and step (c) comprises size-weighting each fragment which uniquely aligns to one or more target regions within one or more reference chromosomes by calculating the probability (w) of each fragment size (s) being fetal in origin.
  • references herein to "target region” refer to a portion or all of said target and/or reference chromosomes.
  • the target chromosome is a region within a chromosome and the reference chromosome is a region within the same chromosome as the target chromosome.
  • the method additionally comprises enrichment of the sample for the genomic region suspected to contain the fetal chromosomal abnormality.
  • the embodiment will typically make use of a process of selection through a hybridisation based technique and will allow the pre-selection to either retain or remove pre-selected target sequences prior to sequencing.
  • the indel/mismatch cost weighting must be parameterised to low in this analysis. With these pre-conditions, non- stringent fragment-length matches are determined.
  • using this bioinformatic approach typically about 95% of sample reads are mapped to the genome. Reads are only counted as assigned to a chromosomal location if they match to a unique position in the genome, typically bringing the proportion of sample reads uniquely matched and subsequently counted for the chromosomal assignments to about 50%.
  • the alignment is conducted with respect to a whole chromosome, for example, the analysis would therefore comprise detecting an excess of a given
  • the alignment is conducted with respect to a part of said chromosome, for example, matches will be analysed solely with respect to a particular pre-determined region of a chromosome. It is believed that this embodiment of the invention provides a more sensitive matching technique by virtue of targeting a specific region of a chromosome.
  • fragment size profiles weight fragments preferentially for chromosome ratio computation if these have a higher probability of reflecting the karyotype of the fetus than that of the mother, and conversely to de- emphasise contributions from fragments which have a higher probability of originating from maternal tissue other than the placenta.
  • CountWeightFragSizeMax (s max ).
  • the range limits are also required to be specified as part of configuration data.
  • the weighting map values are to be stored in a real number type with precision equivalent to or greater than that of 'single precision' format (as defined by IEEE-754: 1985).
  • CountWeightFragSizeMissingAction This may take on the values Ignore or Integrate. The method proceeds as follows for any unique fragment alignment event, generating a count increment u.
  • CountWeightFragSizeMissingAction has the value Integrate
  • the sequencing read length for the fragment (I) is used as a lower bound on a size range, with the upper bound for the range being
  • the value ultimately determined for u is finally added to the accumulated aligned fragment count (N c ) for the chromosome against which it was found to align.
  • N c accumulated aligned fragment count
  • Accumulated, weighted aligned fragment counts determined in this way are subject to correction according to GC content, as in prior methodology, and the corrected values then used in computation of autosome and other chromosome ratios for input to trisomy likelihood models (ff in values), fetal fraction estimation (R x ) and sex determination (R x and optionally also R Y ).
  • a chromosome ratio that is to be used as part of the Run Control validity check should not be subject to weighting according to fragment size (but should still be subject to GC correction).
  • the hits are then typically normalised to a common number.
  • the ratio of each hits for a target region of a target chromosome compared with hits on one or more reference chromosomes is then calculated as R ClargeV as described previously herein.
  • R ClargeV the ratio of each hits for a target region of a target chromosome compared with hits on one or more reference chromosomes.
  • the method of the invention additionally comprises the step of normalizing or adjusting the number of matched hits based on the amount of fetal DNA within the sample.
  • the method of the invention additionally comprises the step of calculating statistical significance of the ratio of each hits for a target region of a target chromosome compared with hits on other chromosomes.
  • the statistical significance test comprises calculation of the z-score in accordance with conventional statistical analysis of the reduced counting data.
  • other statistical methods may be applied by skilled workers in the field.
  • the z-score indicates how many standard deviations an element is from the mean.
  • a z-score value of 2.0 or more for the count ratio indicates a probability of approx 98% that the count ratio value indicates a Trisomy 21 pregnancy.
  • step (f) comprises calculation of a likelihood ratio which is indicative of a fetal chromosomal abnormality for a target chromosome and is typically based upon a number of factors, such as the fetal fraction, etc. Full details of how a likelihood ratio may be calculated are described in WO 2014/033455.
  • Chromosome Y DNA which is inherited from the paternal parent of the fetus, is a diagnostic marker of a male fetus.
  • a further aspect of the present invention is the detection of the gender of the fetus as indicated by the presence of Chromosome Y sequences.
  • fetal SNPs single nucleotide polymorphisms
  • the number of such alleles inherited from the fetus' father, and detected as variants differing from the relatively more abundant maternal alleles is a function of the fraction of the plasma DNA that is fetal.
  • This provides an alternative, gender-independent, method for estimating the fraction of maternal plasma DNA that is fetal in origin.
  • a method of predicting the gender of a fetus within a pregnant female subject comprising the steps of:
  • step (d) calculating a total target weighted count (Nc ta rget) by summing the values obtained in step (b);
  • step (e) calculating a total reference weighted count (Nc) by summing the values obtained in step (c);
  • the reference chromosome is selected from an autosome (i.e. non-sex chromosome).
  • fragments aligning to a Y chromosome is indicative of a male gender prediction (i.e. XY). It will be appreciated that the absence of fragments aligning to a Y chromosome is indicative of a female gender prediction (i.e. XX).
  • kits for performing any of the methods defined herein which comprises instructions for use of the kit in accordance with any of the methods defined herein.
  • the kit additionally comprises one or more reagents and/or one or more consumables as defined herein.
  • a kit as defined herein in a method of detecting a fetal chromosomal abnormality within a pregnant female subject or a method of predicting the gender of a fetus within a pregnant female subject.
  • Bioanalyser® reagents e.g. HT DNA 1 K/ 12K/ High Sensitivity LabChip® and HT DNA Hi Sensitivity Reagent Kit (Cat. Nos. 760517 & CLS760672; Perkin Elmer) Agilent High Sensitivity DNA Analysis Kit (Cat. No. 5067-4626; Agilent Technologies)
  • the lONA® test utilises cell-free DNA (cfDNA) derived from the plasma fraction of whole blood as the input sample for analysis.
  • cfDNA cell-free DNA
  • a DNA extraction kit validated for use in extracting cfDNA from plasma must be used. Sample processing should be performed according to the instructions provided by the DNA extraction kit manufacturer, or to established procedures known to those skilled in the art.
  • the manual protocol for DNA library preparation in the lONA® test utilises the reagents provided in the lONA® Library Preparation Kit. Batching of samples is recommended when using the manual protocol for the lONA® Library Preparation Kit to avoid reduced sample throughput, in comparison with the automated protocol. 1. Remove the DNA from the freezer (if required) and thaw for 30 minutes at ambient temperature (15 to 25°C).
  • a master mix for the End Repair reagents can be prepared for this step if multiple DNA samples are being tested. An overage of at least one reaction is recommended. The number of samples that can be tested using the lONA® Library Preparation Kit may be reduced if using this method.
  • For each sample pipette the End Repair reaction up and down 10 times to mix and pulse spin for 5 seconds using an appropriate benchtop centrifuge. Store the lONA® Library Preparation Kit Plate 1 in a refrigerator until required for the Adaptor Ligation reaction. Transfer each sample tube (or 96-well reaction plate) to a thermal cycler to perform the End Repair reaction. Set the thermal cycler to the following cycling conditions and run the End Repair reaction:
  • a master mix for the End Repair reagents can be prepared for this step if multiple DNA samples are being tested. An overage of at least one reaction is recommended. The number of samples that can be tested using the IONA® Library Preparation Kit may be reduced if using this method. Pipette the barcoded adaptors in columns 6 to 9 of the IONA® Library Preparation Kit Plate 1 (Table 3) up and down 10 times to mix. Note: Perform this for the appropriate number of samples being prepared. Use one barcoded adaptor per sample. Add 8 ⁇ _ of the barcoded adaptor assigned to the appropriate sample to the Adaptor Ligation reaction for the sample. The Adaptor Ligation reaction volume is 100 ⁇ .
  • the barcoded adaptor number (Table 3; Columns 6-9) used for each sample must be recorded as each sample will be analysed in subsequent steps according to its individual barcode.
  • For each sample pipette the Adaptor Ligation reaction up and down 10 times to mix and pulse spin for 5 seconds using an appropriate benchtop centrifuge. Store the IONA® Library Preparation Kit Plate 1 in a refrigerator until required for the Library PCR reaction. Transfer each sample to the verified thermal cycler to perform the Adaptor Ligation reaction. Set the thermal cycler to the following cycling conditions and run the Adaptor Ligation reaction:
  • a master mix for the Library PCR reagents can be prepared for this step if multiple DNA samples are being tested. An overage of at least one reaction is recommended. The number of samples that can be tested using the IONA® Library Preparation Kit may be reduced if using this method. For each sample, pipette the Library PCR reaction up and down 10 times to mix and pulse spin for 5 seconds using an appropriate benchtop centrifuge. Note: Return the IONA® Library Preparation Kit Plate 1 to the freezer for storage.
  • PCR amplified libraries can be stored in the freezer (-15 to -25°C) and the workflow completed within 20 working days. Return the IONA® Library Preparation Kit Plate 2 to the refrigerator for storage until required.
  • PCR amplified libraries may be too concentrated to be run undiluted on certain DNA analyser platforms. It is recommended that a 1/5 dilution is prepared of each library to be quantified.
  • concentration of each library must be recorded in molarity for subsequent normalisation and multiplexing, prior to sequencing. Correct the concentrations for dilution factors as required. Note: Ensure that the concentration of any library being quantified is within the limits of detection of the DNA analyser platform being used. 6. Perform the normalisation and multiplexing of samples prior to size selection using the following steps. Up to 8 samples can be multiplexed for sequencing in a single run. Ensure sample libraries with the same barcoded adaptor number are NOT added in the same multiplexed pool. 7. Select up to 8 samples and their corresponding concentrations (molarity; nM) from quantification. Identify the sample with the lowest concentration - this value is the TARGET concentration all samples will be normalised to. 8. Use the following calculation for each sample to be pooled to determine the volumes required for the multiplexing of libraries:
  • Volumes underlined in the example indicate final volumes to be added.
  • a minimum volume of 100 ⁇ _ of the pooled samples is required for subsequent steps. If fewer than 5 samples are being multiplexed, the 20 ⁇ _ volume shown in the calculation above can be increased as necessary.
  • the next generation sequencing reaction can be performed using a semi-automated or fully automated protocol.
  • the IONA® test has been validated using the Ion ChefTM instrument and the Ion ProtonTM next generation sequencing platform (Thermo Fisher). The workflow for this automated DNA library protocol is described below.
  • Ion PI Chip Kit V3 of Ion PI V2 BC (Cat. No. A26771 or 4484270; Thermo Fisher)
  • Isopropanol, molecular biology grade if using Ion PI V2 BC chips e.g. Cat. No. 11388461 ; Fisher Scientific
  • Execution of the main bioinformatics pipeline proceeds as follows through the use of the IONA ® Software: For each sequencing run of eight samples, multiplexed sequence reads are retrieved from the sequencing platform in the form of an unmapped BAM file. The multiplexed assembly of reads is initially subject to a barcode classification step, in which barcoded 5' adapters are identified and matched against a predefined set, in order to split the multiplex into reads against individual samples for further processing. Following an early filtering step to remove a small number of very short reads, fragments are mapped to the 'hg19' human genome reference using a gap-tolerant read alignment module. Post-filtering of alignment results is then carried out to remove duplicate reads arising in PCR stages of the test workflow, determined as those whose 5' end map to the reference at the same position as any other read.
  • Fragments determined to have aligned uniquely in the genome reference are then binned by autosome, with the resulting counts subject to a calibration step to correct sequencing coverage bias correlated to GC content; this is achieved by first characterising the level of over- or under-representation of fragments according to their average GC content when binned across the genome reference, and then inverting and applying as a corrective weighting to fragment counts per chromosome.
  • Fragments may additionally be subject to a size weighting step, as defined herein as the subject of the present invention, which increases the effective fetal fraction at the point of analysis to give increased separation between the trisomy-affected and trisomy-unaffected groups.
  • the resulting fragment count data are used as input to a set of mixture models that incorporate distributions of expected values under both trisomy-affected and unaffected hypotheses for trisomy 13, 18 and 21 tests.
  • Each model generates a test likelihood ratio that is then used, together with maternal age-derived prior probabilities of trisomy, to quantify the probability of each trisomy taking into account both age and the corresponding DNA test result.
  • the IONA ® Software also performs internal validity checks. Workflow data quality checks take place, which make use of sequencing and alignment metrics to ensure sequence data are of sufficient quality for further analysis to take place. Additionally, following the generation of per-autosome fragment counts, the run validity check takes place. This step first isolates fragments derived from sequencing an In-Run Control designed to simulate a Trisomy 21-positive sample with approximately 10% fetal fraction, and then compares the proportion of counts from these fragments which aligned against chromosome 21 using a reference range previously set in the software configuration. If the proportion meets the reference criteria, the run validity check passes. Separate validity checks also take place for each sample.
  • sequencing data sets corresponding to these samples were extracted from data archives, and analysed using two bioinformatics analysis pipelines:
  • Figures 2, 3 and 4 are scatter plots relating the autosome ratios generated by both the unweighted and size-weighted analyses for each sample, for each of the three chromosomes 21 , 18 and 13 respectively. These correspond to the tests for trisomies 21 , 18 and 13 respectively.
  • Each plot also contains a dotted line through equal autosome ratios between the unweighted and weighted analysis methods. It can be seen in each case that while the autosome ratios for trisomy-unaffected samples remain clustered around the 'no effect' line indicating that the distributions of unaffected samples are unchanged, the autosome ratios calculated for trisomy-affected samples are increased for the size-weighted method compared with the baseline unweighted method. Additionally, the increase can be seen to be greater for larger autosome ratios than for smaller ones, indicating that the size-weighted method confers a scaling (amplification) effect on trisomy-affected autosome ratios.
  • Figures 5, 6 and 7 show empirical distribution functions (kernel density estimates) together with the contributing plotted autosome ratio values, for the trisomy-unaffected and affected groups separately. It can be seen clearly that under the fragment size-weighting method, the affected sample group distributions are shifted and scaled upwards relative to the case of the unweighted method, while unaffected sample groups remain at their original locations. 2.1.1 Effect on performance
  • a trisomy determination is made in the IONA ® Software using a statistical model which has been fitted to the expected unaffected and trisomy group distributions for the population.
  • Sensitivity and specificity performance measures for a system such as the IONA ® test are a function of the number of true unaffected and affected cases correctly classified, and the statistical model or cutoff used to determine a result.
  • increasing the separation between unaffected and affected data will have the effect of improving overall performance.
  • reducing separation would have a detrimental effect on overall performance.
  • consistent increased separation was observed between autosome ratio values for the unaffected and affected groups under the fragment size-weighted method when compared with the baseline unweighted method (i.e., between the new and current methods).
  • Fetal fraction at analysis in a given trisomy sample is proportional to the difference between the autosome ratio for that sample and the expected value (mean) autosome ratio seen for unaffected samples, thus:
  • F eff is the calculated effective fetal fraction seen by the analysis stage.
  • Figure 9 further demonstrates the fetal fraction scaling effect due to the inclusion of size-weighting of each fragment.
  • This plot relates fetal fraction values at analysis for individual trisomy-affected samples as calculated from their autosome ratios, for the original unweighted and new size-weighted analysis cases.
  • the average proportional increase in fetal fraction seen at the trisomy analysis stage due to the improved counting scheme, for all trisomy-affected samples included, is 13.2%.
  • the study examined the separation between distributions of autosome ratios generated by analysing trisomy-affected and trisomy-unaffected samples using the IONA ® test process, using both the existing (unweighted) count analysis method and a new count analysis method which incorporates weighting by fragment size.

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Abstract

L'invention concerne un nouveau procédé de détection d'une anomalie chromosomique fœtale, l'invention concernant en particulier la détection de la trisomie 21 (syndrome de Down) qui comprend l'étape de calcul de la probabilité (w) que chaque taille de fragment (s) est d'origine fœtale. L'invention concerne également des kits de mise en œuvre de ce procédé. L'invention concerne encore un procédé de prédiction du sexe d'un fœtus à l'intérieur d'un sujet féminin gravide.
PCT/GB2018/053255 2017-11-10 2018-11-12 Procédé de détection d'une anomalie chromosomique fœtale WO2019092438A1 (fr)

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Citations (1)

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Publication number Priority date Publication date Assignee Title
EP3202915A1 (fr) * 2016-02-03 2017-08-09 Verinata Health, Inc. Utilisation de la taille des fragments d'adn extracellulaire pour déterminer des variations du nombre de copies

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3202915A1 (fr) * 2016-02-03 2017-08-09 Verinata Health, Inc. Utilisation de la taille des fragments d'adn extracellulaire pour déterminer des variations du nombre de copies

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ARBABI ARYAN ET AL: "Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction", BIOINFORMATICS, OXFORD UNIVERSITY PRESS, SURREY, GB, vol. 32, no. 11, 1 June 2016 (2016-06-01), pages 1662 - 1669, XP009505717, ISSN: 1367-4803, DOI: 10.1093/BIOINFORMATICS/BTW178 *
DINEIKA CHANDRANANDA ET AL: "High-resolution characterization of sequence signatures due to non-random cleavage of cell-free DNA", BMC MEDICAL GENOMICS, vol. 8, no. 1, 17 June 2015 (2015-06-17), XP055450660, DOI: 10.1186/s12920-015-0107-z *
STEPHANIE C.Y. YU ET AL: "Combined Count- and Size-Based Analysis of Maternal Plasma DNA for Noninvasive Prenatal Detection of Fetal Subchromosomal Aberrations Facilitates Elucidation of the Fetal and/or Maternal Origin of the Aberrations", CLINICAL CHEMISTRY, vol. 63, no. 2, 14 December 2016 (2016-12-14), pages 495 - 502, XP055469251, ISSN: 0009-9147, DOI: 10.1373/clinchem.2016.254813 *
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