Milena Banjevic

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.

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.

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.

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.

Evidence of Selection against Complex Mitotic-Origin Aneuploidy during Preimplantation Development.

Whole-chromosome imbalances affect over half of early human embryos and are the leading cause of pregnancy loss. While these errors frequently arise in oocyte meiosis, many such whole-chromosome abnormalities affecting cleavage-stage embryos are the result of chromosome missegregation occurring during the initial mitotic cell divisions. The first wave of zygotic genome activation at the 4–8 cell stage results in the arrest of a large proportion of embryos, the vast majority of which contain whole-chromosome abnormalities. Thus, the full spectrum of meiotic and mitotic errors can only be detected by sampling after the initial cell divisions, but prior to this selective filter. Here, we apply 24-chromosome preimplantation genetic screening (PGS) to 28,052 single-cell day-3 blastomere biopsies and 18,387 multi-cell day-5 trophectoderm biopsies from 6,366 in vitro fertilization (IVF) cycles. We precisely characterize the rates and patterns of whole-chromosome abnormalities at each developmental stage and distinguish errors of meiotic and mitotic origin without embryo disaggregation, based on informative chromosomal signatures. We show that mitotic errors frequently involve multiple chromosome losses that are not biased toward maternal or paternal homologs. This outcome is characteristic of spindle abnormalities and chaotic cell division detected in previous studies. In contrast to meiotic errors, our data also show that mitotic errors are not significantly associated with maternal age. PGS patients referred due to previous IVF failure had elevated rates of mitotic error, while patients referred due to recurrent pregnancy loss had elevated rates of meiotic error, controlling for maternal age. These results support the conclusion that mitotic error is the predominant mechanism contributing to pregnancy losses occurring prior to blastocyst formation. This high-resolution view of the full spectrum of whole-chromosome abnormalities affecting early embryos provides insight into the cytogenetic mechanisms underlying their formation and the consequences for human fertility.

Validation of an Enhanced Version of a Single-Nucleotide Polymorphism-Based Noninvasive Prenatal Test for Detection of Fetal Aneuploidies.

Objective: To validate an updated version (Version 2) of a single-nucleotide polymorphism (SNP)-based noninvasive prenatal test (NIPT) and to determine the likelihood of success when testing for fetal aneuploidies following a redraw. Methods: Version 2 was analytically validated using 587 plasma samples with known genotype (184 trisomy 21, 37 trisomy 18, 15 trisomy 13, 9 monosomy X, 4 triploidy and 338 euploid). Sensitivity, specificity and no-call rate were calculated, and a fetal-fraction adjustment was applied to enable projection of these values in a commercial distribution. Likelihood of success of a second blood draw was computed based on fetal fraction and maternal weight from the first draw. Results: Validation of this methodology yielded high sensitivities (≥99.4%) and specificities (100%) for all conditions tested with an observed no-call rate of 2.3%. The no-call threshold for sample calling was reduced to 2.8% fetal fraction. The redraw success rate was driven by higher initial fetal fractions and lower maternal weights, with the fetal fraction being the more significant variable. Conclusions: The enhanced version of this SNP-based NIPT method showed a reduced no-call rate and a reduced fetal-fraction threshold for sample calling in comparison to the earlier version, while maintaining high sensitivity and specificity.