Matthew Rabinowitz

Noninvasive prenatal aneuploidy testing of chromosomes 13, 18, 21, X, and Y, using targeted sequencing of polymorphic loci.

This study aims to develop a noninvasive prenatal test on the basis of the analysis of cell‐free DNA in maternal blood to detect fetal aneuploidy at chromosomes 13, 18, 21, X, and Y.

Preclinical validation of a microarray method for full molecular karyotyping of blastomeres in a 24-h protocol

BACKGROUND Preimplantation genetic screening (PGS) has been used in an attempt to determine embryonic aneuploidy. Techniques that use new molecular methods to determine the karyotype of an embryo are expanding the scope of PGS. METHODS We introduce a new method for PGS, termed ‘parental support’, which leverages microarray measurements from parental DNA to ‘clean’ single-cell microarray measurements on embryonic cells and explicitly computes confidence in each copy number call. The method distinguishes mitotic and meiotic copy errors and determines parental source of aneuploidy. RESULTS Validation with 459 single cells of known karyotype indicated that per-cell false-positive and false-negative rates are roughly equivalent to the ‘gold standard’ metaphase karyotype. The majority of the cells were run in parallel with a clinical commercial PGS service. Computed confidences were conservative and roughly concordant with accuracy. To examine ploidy in human embryos, the method was then applied to 26 disaggregated, cryopreserved, cleavage-stage embryos for a total of 134 single blastomeres. Only 23.1% of the embryos were euploid, though 46.2% of embryos were mosaic euploid. Mosaicism affected 57.7% of the embryos. Counts of mitotic and meiotic errors were roughly equivalent. Maternal meiotic trisomy predominated over paternal trisomy, and maternal meiotic trisomies were negatively predictive of mosaic euploid embryos. CONCLUSIONS We have performed a major preclinical validation of a new method for PGS and found that the technology performs approximately as well as a metaphase karyotype. We also directly measured the mechanism of aneuploidy in cleavage-stage human embryos and found high rates and distinct patterns of mitotic and meiotic aneuploidy.

A new positioning system using television synchronization signals

The technique discussed herein may be used to position a range of wireless devices that require location information when in inclement urban conditions, including PDAs, laptops, cellular phones, asset-tracking devices and radios for emergency response personnel. We make use of synchronization signals that are part of the standard for Television set forth by the Advanced Television Systems Committee. Consequently, the technique described herein requires no changes to the television broadcast stations. The signal can accommodate robust indoor positioning where the Global Positioning System (GPS) fails, since the television synchronization signals typically have a power advantage over GPS of more than 40 dB. In addition, the effects of multipath are substantially mitigated since the signals have a bandwidth of roughly 6 MHz, and substantially superior geometry for triangulating lateral position to that which GPS can typically provide in inclement environments. A wide range of VHF and UHF frequencies have been allocated to television stations; consequently, there is redundancy built into the system to protect against deep fades on particular channels. In addition, unlike GPS, the synch signals are not affected by transmitter Doppler, ionospheric propagation delays, or data that is modulated onto the signals. In overview, the technology exploits the considerable Digital TV infrastructure to achieve more reliable, accurate and rapid positioning than can be achieved with existing technologies.

Single-nucleotide polymorphism-based noninvasive prenatal screening in a high-risk and low-risk cohort.

OBJECTIVE: To estimate performance of a single-nucleotide polymorphism–based noninvasive prenatal screen for fetal aneuploidy in high-risk and low-risk populations on single venopuncture. METHODS: One thousand sixty-four maternal blood samples from 7 weeks of gestation and beyond were included; 1,051 were within specifications and 518 (49.3%) were low risk. Cell-free DNA was amplified, sequenced, and analyzed using the Next-generation Aneuploidy Test Using SNPs algorithm. Samples were called as trisomies 21, 18, 13, or monosomy X, or euploid, and male or female. RESULTS: Nine hundred sixty-six samples (91.9%) successfully generated a cell-free DNA result. Among these, sensitivity was 100% for trisomy 21 (58/58, confidence interval [CI] 93.8–100%), trisomy 13 (12/12, CI 73.5–100%), and fetal sex (358/358 female, CI 99.0–100%; 418/418 male, CI 99.1–100%), 96.0% for trisomy 18 (24/25, CI 79.7–99.9%), and 90% for monosomy X (9/10, CI 55.5–99.8%). Specificity for trisomies 21 and 13 was 100% (905/905, CI 99.6–100%; and 953/953, CI 99.6–100%, respectively) and for trisomy 18 and monosomy X was 99.9% (938/939, CI 99.4–100%; and 953/954, CI 99.4–100%, respectively). However, 16% (20/125) of aneuploid samples did not return a result; 50% (10/20) had a fetal fraction below the 1.5th percentile of euploid pregnancies. Aneuploidy rate was significantly higher in these samples (P<.001, odds ratio 9.2, CI 4.4–19.0). Sensitivity and specificity did not differ in low-risk and high-risk populations. CONCLUSIONS: This noninvasive prenatal screen performed with high sensitivity and specificity in high-risk and low-risk cohorts. Aneuploid samples were significantly more likely to not return a result; the number of aneuploidy samples was especially increased among samples with low fetal fraction. This underscores the importance of redraws or, in rare cases, invasive procedures based on low fetal fraction. LEVEL OF EVIDENCE: II

SNP-based non-invasive prenatal testing detects sex chromosome aneuploidies with high accuracy

This study aimed to develop a single‐nucleotide polymorphism‐based and informatics‐based non‐invasive prenatal test that detects sex chromosome aneuploidies early in pregnancy.

Detection of triploid, molar, and vanishing twin pregnancies by a single-nucleotide polymorphism–based noninvasive prenatal test

OBJECTIVE We sought to determine the ability of single-nucleotide polymorphism-based noninvasive prenatal testing (NIPT) to identify triploid, unrecognized twin, and vanishing twin pregnancies. STUDY DESIGN The study included 30,795 consecutive reported clinical cases received for NIPT for fetal whole-chromosome aneuploidies; known multiple gestations were excluded. Cell-free DNA was isolated from maternal blood samples, amplified via 19,488-plex polymerase chain reaction, and sequenced. Sequencing results were analyzed to determine fetal chromosome copy number and to identify the presence of additional fetal haplotypes. RESULTS Additional fetal haplotypes, indicative of fetal triploidy, vanishing twin, or undetected twin pregnancy, were identified in 130 (0.42%) cases. Clinical confirmation (karyotype for singleton pregnancies, ultrasound for multifetal pregnancies) was available for 58.5% (76/130) of cases. Of the 76 cases with confirmation, 42.1% were vanishing twin, 48.7% were viable twin, 5.3% were diandric triploids, and 3.9% were nontriploid pregnancies that lacked evidence of co-twin demise. One pregnancy had other indications suggesting triploidy but lacked karyotype confirmation. Of the 5 vanishing twin cases with a known date of demise, 100% of losses occurred in the first trimester; up to 8 weeks elapsed between loss and detection by NIPT. CONCLUSION This single-nucleotide polymorphism-based NIPT successfully identified vanished twin, previously unrecognized twin, and triploid pregnancies. As vanishing twins are more likely to be aneuploid, and undetected residual cell-free DNA could bias NIPT results, the ability of this method to identify additional fetal haplotypes is expected to result in fewer false-positive calls and prevent incorrect fetal sex calls.

Origins and rates of aneuploidy in human blastomeres.

OBJECTIVE To characterize chromosomal error types and parental origin of aneuploidy in cleavage-stage embryos using an informatics-based technique that enables the elucidation of aneuploidy-causing mechanisms. DESIGN Analysis of blastomeres biopsied from cleavage-stage embryos for preimplantation genetic screening during IVF. SETTING Laboratory. PATIENT(S) Couples undergoing IVF treatment. INTERVENTION(S) Two hundred seventy-four blastomeres were subjected to array-based genotyping and informatics-based techniques to characterize chromosomal error types and parental origin of aneuploidy across all 24 chromosomes. MAIN OUTCOME MEASURE(S) Chromosomal error types (monosomy vs. trisomy; mitotic vs. meiotic) and parental origin (maternal vs. paternal). RESULT(S) The rate of maternal meiotic trisomy rose significantly with age, whereas other types of trisomy showed no correlation with age. Trisomies were mostly maternal in origin, whereas paternal and maternal monosomies were roughly equal in frequency. No examples of paternal meiotic trisomy were observed. Segmental error rates were found to be independent of maternal age. CONCLUSION(S) All types of aneuploidy that rose with increasing maternal age can be attributed to disjunction errors during meiosis of the oocyte. Chromosome gains were predominantly maternal in origin and occurred during meiosis, whereas chromosome losses were not biased in terms of parental origin of the chromosome. The ability to determine the parental origin for each chromosome, as well as being able to detect whether multiple homologs from a single parent were present, allowed greater insights into the origin of aneuploidy.

Genomic imbalance in products of conception: single-nucleotide polymorphism chromosomal microarray analysis.

OBJECTIVE: To report the full cohort of identifiable anomalies, regardless of known clinical significance, in a large-scale cohort of postmiscarriage products-of-conception samples analyzed using a high-resolution single-nucleotide polymorphism (SNP)–based microarray platform. High-resolution chromosomal microarray analysis allows for the identification of visible and submicroscopic cytogenomic imbalances; the specific use of SNPs permits detection of maternal cell contamination, triploidy, and uniparental disomy. METHODS: Miscarriage specimens were sent to a single laboratory for cytogenomic analysis. Chromosomal microarray analysis was performed using a SNP-based genotyping microarray platform. Results were evaluated at the cytogenetic and microscopic (greater than 10 Mb) and submicroscopic (less than 10 Mb) levels. Maternal cell contamination was assessed using information derived from fetal and maternal SNPs. RESULTS: Results were obtained on 2,389 of 2,392 specimens (99.9%) that were less than 20 weeks of gestation. Maternal cell contamination was identified in 528 (22.0%) specimens. The remaining 1,861 specimens were considered to be of true fetal origin. Of these, 1,106 (59.4%) showed classical cytogenetic abnormalities: aneuploidy accounted for 945 (85.4%), triploidy for 114 (10.3%), and structural anomalies or tetraploidy for the remaining 47 (4.2%). Of the 755 (40.6%) cases considered normal at the cytogenetic level, SNP chromosomal microarray analysis revealed a clinically significant copy number change or whole-genome uniparental disomy in 12 (1.6%) and three (0.4%) cases, respectively. CONCLUSION: Chromosomal microarray analysis of products-of-conception specimens yields a high diagnostic return. Using SNPs extends the scope of detectable genomic abnormalities and facilitates reporting “true” fetal results. This supports the use of SNP chromosomal microarray analysis for cytogenomic evaluation of miscarriage specimens when clinically indicated. LEVEL OF EVIDENCE: III

Common variants spanning PLK4 are associated with mitotic-origin aneuploidy in human embryos

Chromosome number varies in humans Pregnancy loss is often associated with a loss of chromosome number, a condition known as aneuploidy. When examining aneuploid embryos during in vitro fertilization cycles, McCoy et al. found a large genomic region associated with defects in maternal chromosome number (see the Perspective by Vohr and Green). This region contains a gene, Polo-like Kinase 4 (PLK4), that is known to affect chromosome segregation and has variants that correlate with an increased rate of maternal aneuploidy. Surprisingly, such variants occur at relatively high levels in human populations and may be under positive selection. Science, this issue p. 235; see also p. 180 Prenatal genetic screening reveals the candidate gene Polo-like kinase 4, variants of which may affect embryo survival rates. [Also see Perspective by Vohr and Green] Aneuploidy, the inheritance of an atypical chromosome complement, is common in early human development and is the primary cause of pregnancy loss. By screening day-3 embryos during in vitro fertilization cycles, we identified an association between aneuploidy of putative mitotic origin and linked genetic variants on chromosome 4 of maternal genomes. This associated region contains a candidate gene, Polo-like kinase 4 (PLK4), that plays a well-characterized role in centriole duplication and has the ability to alter mitotic fidelity upon minor dysregulation. Mothers with the high-risk genotypes contributed fewer embryos for testing at day 5, suggesting that their embryos are less likely to survive to blastocyst formation. The associated region coincides with a signature of a selective sweep in ancient humans, suggesting that the causal variant was either the target of selection or hitchhiked to substantial frequency.

Accurate prediction of HIV-1 drug response from the reverse transcriptase and protease amino acid sequences using sparse models created by convex optimization

MOTIVATION Genotype-phenotype modeling problems are often overcomplete, or ill-posed, since the number of potential predictors-genes, proteins, mutations and their interactions-is large relative to the number of measured outcomes. Such datasets can still be used to train sparse parameter models that generalize accurately, by exerting a principle similar to Occams Razor: When many possible theories can explain the observations, the most simple is most likely to be correct. We apply this philosophy to modeling the drug response of Type-1 Human Immunodeficiency Virus (HIV-1). Owing to the decreasing expense of genetic sequencing relative to in vitro phenotype testing, a statistical model that reliably predicts viral drug response from genetic data is an important tool in the selection of antiretroviral therapy (ART). The optimization techniques described will have application to many genotype-phenotype modeling problems for the purpose of enhancing clinical decisions. RESULTS We describe two regression techniques for predicting viral phenotype in response to ART from genetic sequence data. Both techniques employ convex optimization for the continuous subset selection of a sparse set of model parameters. The first technique, the least absolute shrinkage and selection operator, uses the l(1) norm loss function to create a sparse linear model; the second, the support vector machine with radial basis kernel functions, uses the epsilon-insensitive loss function to create a sparse non-linear model. The techniques are applied to predict the response of the HIV-1 virus to 10 reverse transcriptase inhibitor and 7 protease inhibitor drugs. The genetic data are derived from the HIV coding sequences for the reverse transcriptase and protease enzymes. When tested by cross-validation with actual laboratory measurements, these models predict drug response phenotype more accurately than models previously discussed in the literature, and other canonical techniques described here. Key features of the methods that enable this performance are the tendency to generate simple models where many of the parameters are zero, and the convexity of the cost function, which assures that we can find model parameters to globally minimize the cost function for a particular training dataset. AVAILABILITY Results, tables and figures are available at ftp://ftp.genesecurity.net. SUPPLEMENTARY INFORMATION An Appendix to accompany this article is available at Bioinformatics online.