Eyad Almasri

Non-Invasive Prenatal Chromosomal Aneuploidy Testing - Clinical Experience: 100,000 Clinical Samples

Objective As the first laboratory to offer massively parallel sequencing-based noninvasive prenatal testing (NIPT) for fetal aneuploidies, Sequenom Laboratories has been able to collect the largest clinical population experience data to date, including >100,000 clinical samples from all 50 U.S. states and 13 other countries. The objective of this study is to give a robust clinical picture of the current laboratory performance of the MaterniT21 PLUS LDT. Study Design The study includes plasma samples collected from patients with high-risk pregnancies in our CLIA–licensed, CAP-accredited laboratory between August 2012 to June 2013. Samples were assessed for trisomies 13, 18, 21 and for the presence of chromosome Y-specific DNA. Sample data and ad hoc outcome information provided by the clinician was compiled and reviewed to determine the characteristics of this patient population, as well as estimate the assay performance in a clinical setting. Results NIPT patients most commonly undergo testing at an average of 15 weeks, 3 days gestation; and average 35.1 years of age. The average turnaround time is 4.54 business days and an overall 1.3% not reportable rate. The positivity rate for Trisomy 21 was 1.51%, followed by 0.45% and 0.21% rate for Trisomies 18 and 13, respectively. NIPT positivity rates are similar to previous large clinical studies of aneuploidy in women of maternal age ≥35 undergoing amniocentesis. In this population 3519 patients had multifetal gestations (3.5%) with 2.61% yielding a positive NIPT result. Conclusion NIPT has been commercially offered for just over 2 years and the clinical use by patients and clinicians has increased significantly. The risks associated with invasive testing have been substantially reduced by providing another assessment of aneuploidy status in high-risk patients. The accuracy and NIPT assay positivity rate are as predicted by clinical validations and the test demonstrates improvement in the current standard of care.

Clinical outcome of subchromosomal events detected by whole‐genome noninvasive prenatal testing

A novel algorithm to identify fetal microdeletion events in maternal plasma has been developed and used in clinical laboratory‐based noninvasive prenatal testing. We used this approach to identify the subchromosomal events 5pdel, 22q11del, 15qdel, 1p36del, 4pdel, 11qdel, and 8qdel in routine testing. We describe the clinical outcomes of those samples identified with these subchromosomal events.

Factors affecting levels of circulating cell‐free fetal DNA in maternal plasma and their implications for noninvasive prenatal testing

Sufficient fetal DNA in a maternal plasma sample is required for accurate aneuploidy detection via noninvasive prenatal testing, thus highlighting a need to understand the factors affecting fetal fraction.

Uterine leiomyoma confounding a noninvasive prenatal test result

Sequenom Laboratories, San Diego, CA, USA Department of Obstetrics and Gynecology, Saitama Medical University Hospital, Saitama, Japan Perinatal Medical Center, Saitama Medical Center, Jichi Medical University, Saitama, Japan GeneTech Inc., Tokyo, Japan Sequenom Laboratories, Grand Rapids, MI, USA Department of Obstetrics, Gynecology and Reproductive Medicine, Michigan State University, East Lansing, MI, USA *Correspondence to: Nilesh G. Dharajiya. E-mail: ndharajiya@sequenom.com These authors contributed equally to this article.

Rank-based edge reconstruction for scale-free genetic regulatory networks

BackgroundThe reconstruction of genetic regulatory networks from microarray gene expression data has been a challenging task in bioinformatics. Various approaches to this problem have been proposed, however, they do not take into account the topological characteristics of the targeted networks while reconstructing them.ResultsIn this study, an algorithm that explores the scale-free topology of networks was proposed based on the modification of a rank-based algorithm for network reconstruction. The new algorithm was evaluated with the use of both simulated and microarray gene expression data. The results demonstrated that the proposed algorithm outperforms the original rank-based algorithm. In addition, in comparison with the Bayesian Network approach, the results show that the proposed algorithm gives much better recovery of the underlying network when sample size is much smaller relative to the number of genes.ConclusionThe proposed algorithm is expected to be useful in the reconstruction of biological networks whose degree distributions follow the scale-free topology.

A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microarray experiments

BackgroundThe incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a cell. Most of the current research has been focused on the integration of multiple sets of microarray data as well as curated databases for a genome scale reconstruction. However, individual researchers are more interested in the extraction of most useful information from the data of their hypothesis-driven microarray experiments. How to compile the prior biological knowledge from literature to facilitate new hypothesis generation from a microarray experiment is the focus of this work. We propose a novel method based on the statistical analysis of reported gene interactions in PubMed literature.ResultsUsing Gene Ontology (GO) Molecular Function annotation for reported gene regulatory interactions in PubMed literature, a statistical analysis method was proposed for the derivation of a likelihood of interaction (LOI) score for a pair of genes. The LOI-score and the Pearson correlation coefficient of gene profiles were utilized to check if a pair of query genes would be in the above specified interaction. The method was validated in the analysis of two gene sets formed from the yeast Saccharomyces cerevisiae cell cycle microarray data. It was found that high percentage of identified interactions shares GO Biological Process annotations (39.5% for a 102 interaction enriched gene set and 23.0% for a larger 999 cyclically expressed gene set).ConclusionThis method can uncover novel biologically relevant gene interactions. With stringent confidence levels, small interaction networks can be identified for further establishment of a hypothesis testable by biological experiment. This procedure is computationally inexpensive and can be used as a preprocessing procedure for screening potential biologically relevant gene pairs subject to the analysis with sophisticated statistical methods.

Incorporating literature knowledge in Bayesian network for inferring gene networks with gene expression data

The reconstruction of gene networks from microarray geneexpression has been a challenging problem in bioinformatics. Variousmethods have been proposed for this problem. The incorporation of variousgenomic and proteomic data has been shown to enhance the learningability in the Bayesian Network (BN) approach. However, the knowledgeembedded in the large body of published literature has not been utilizedin a systematic way. In this work, prior knowledge on gene interactionwas derived based on the statistical analysis of published interactionsbetween pairs of genes or gene products. This information was used (1)to construct a structure prior and (2) to reduce the search space in theBN algorithm. The performance of the two approaches was evaluatedand compared with the BN method without prior knowledge on twotime course microarray gene expression data related to the yeast cell cycle.The results indicate that the proposed algorithms can identify edgesin learned networks with higher biological relevance. Furthermore, themethod using literature knowledge for the reduction of the search spaceoutperformed the method using a structure prior in the BN framework.

CASE REPORT: Sumatriptan-Associated Ischemic Colitis

Sumatriptan, a selective 5-hydroxytryptamine receptor agonist, is widely prescribed for the treatment of migraine headaches. It is believed to selectively activate intracranial 5-HT receptors, thereby causing vasoconstriction. However, there is increasing evidence that 5-HT receptors extend beyond the cranial arteries. For example, sumatriptan use has been linked to coronary vasospasm, myocardial ischemia, and myocardial infarctions (1, 2). We report a case of a 52-year-old woman, with no previous history of vascular disease, who developed ischemic colitis after increased use of sumatriptan for migraine headaches. In the literature, there have been two published accounts associating sumatriptan use with ischemic colitis in 10 patients (3, 4). However, many of these cases have been poorly characterized and confounded by concomitant drug use or other vascular risk factors. This report strengthens and better illuminates the association of sumatriptan with ischemic colitis.

Genome-wide cfDNA screening: clinical laboratory experience with the first 10,000 cases

PurposeInvasive diagnostic prenatal testing can provide the most comprehensive information about the genetic status of a fetus. Noninvasive prenatal screening methods, especially when using cell-free DNA (cfDNA), are often limited to reporting only on trisomies 21, 18, and 13 and sex chromosome aneuploidies. This can leave a significant number of chromosomal and subchromosomal copy-number variations undetected. In 2015, we launched a new genome-wide cfDNA screening test that has the potential to narrow this detection gap.MethodsHere, we review the results from the first 10,000 cases submitted to the Sequenom clinical laboratory for genome-wide cfDNA screening.ResultsThe high-risk indication for this cohort differed compared with standard cfDNA screening. More samples were submitted with ultrasound indications (25% compared with 13% for standard cfDNA screening) and fewer for advanced maternal age (51% for genome-wide screening versus 68% for standard cfDNA screening). A total of 554 positive calls were made, of which 164 were detectable only via genome-wide analysis.ConclusionThis reports indicates a difference in utilization compared with standard cfDNA screening, where positivity rates are higher and a large subset of positive calls could not have been made using standard cfDNA screening.

Incidental Detection of Maternal Neoplasia in Noninvasive Prenatal Testing

BACKGROUND Noninvasive prenatal testing (NIPT) uses cell-free DNA (cfDNA) as an analyte to detect copy-number alterations in the fetal genome. Because maternal and fetal cfDNA contributions are comingled, changes in the maternal genome can manifest as abnormal NIPT results. Circulating tumor DNA (ctDNA) present in cases of maternal neoplasia has the potential to distort the NIPT readout to a degree that prevents interpretation, resulting in a nonreportable test result for fetal aneuploidy. METHODS NIPT cases that showed a distortion from normal euploid genomic representation were communicated to the caregiving physician as nonreportable for fetal aneuploidy. Follow-up information was subsequently collected for these cases. More than 450000 pregnant patients who submitted samples for clinical laboratory testing >3 years are summarized. Additionally, in-depth analysis was performed for >79000 research-consented samples. RESULTS In total, 55 nonreportable NIPT cases with altered genomic profiles were cataloged. Of these, 43 had additional information available to enable follow-up. A maternal neoplasm was confirmed in 40 of these cases: 18 malignant, 20 benign uterine fibroids, and 2 with radiological confirmation but without pathological classification. CONCLUSIONS In a population of pregnant women who submitted a blood sample for cfDNA testing, an abnormal genomic profile not consistent with fetal abnormalities was detected in about 10 out of 100000 cases. A subset of these observations (18 of 43; 41.9%) was attributed to maternal malignant neoplasms. These observational results suggest the need for a controlled trial to evaluate the potential of using cfDNA as an early biomarker of cancer.