Multiset partial least squares with rank order of groups for integrating multi-omics data (preprint)

As more multi-omics data such as metabolome, proteome and transcriptome data are acquired, statistical analyses to integrate multi-omics data has been required. Multivariate analysis for integration of multi-omics data has been proposed such as multiset partial least squares (PLS). However, when we want to extract scores about the rank order of groups such as severity of disease as well as difference of groups, we could not always extract scores with rank order of groups by using multiset PLS. Therefore, we proposed multiset PLS with rank order of groups (multiset PLS-ROG) to integrate multiple omics dataset. We visualized multiple omics data by using multiset PLS-ROG in two studies of multi-omics and multi-organ derived metabolome data. After we visualize data and focus on a specific score with phenotype of interest, it is important to select compounds to identify biomarker candidates or make biological inferences. In ordinary principal component analysis (PCA) or PLS, we could select statistical significantly compounds correlated with PC or PLS score by using PC or PLS loadings. However, multiset PLS loading has not been used because its statistical property has not been clarified. Then, we clarified statistical property of multiset PLS and multiset PLS-ROG loading, and we could identify statistically significant compounds by using statistical hypothesis testing. We implemented multiset PLS-ROG to R loadings package, freely available in CRAN.

A dPCR-NIPT assay for detections of trisomies 21, 18 and 13 in a single-tube reaction-could it replace serum biochemical tests as a primary maternal plasma screening tool?

BACKGROUND: The next generation sequencing (NGS) based non-invasive prenatal test (NIPT) has outplayed the traditional serum biochemical tests (SBT) in screen of fetal aneuploidies with a high sensitivity and specificity. However, it has not been widely used as a primary screen tool due to its high cost and the cheaper SBT is still the choice for primary screen even with well-known shortages in sensitivity and specificity. Here, we report a multiplex droplet digital PCR NIPT (dPCR-NIPT) assay that can detect trisomies 21, 18 and 13 (T21, T18 and T13) in a single tube reaction with a better sensitivity and specificity than the SBT and a much cheaper price than the NGS-NIPT. METHODS: In this study, the dPCR-NIPT assay's non-clinical characteristics were evaluated to verify the cell free fetal DNA (cffDNA) fraction enrichment efficiencies, the target cell free DNA (cfDNA) concentration enrichment, the analytical sensitivity, and the sample quality control on the minimum concentration of cfDNA required for the assay. We validated the clinical performance for this assay by blindly testing 283 clinical maternal plasma samples, including 36 trisomic positive samples, from high risk pregnancies to access its sensitivity and specificity. The cost effectiveness of using the dPCR-NIPT assay as the primary screen tool was also analyzed and compared to that of the existing contingent strategy (CS) using the SBT as the primary screen tool and the strategy of NGS-NIPT as the first-tier screen tool in a simulating situation. RESULTS: For the non-clinical characteristics, the sample processing reagents could enrich the cffDNA fraction by around 2 folds, and the analytical sensitivity showed that the assay was able to detect trisomies at a cffDNA fraction as low as 5% and the extracted cfDNA concentration as low as 0.2 ng/µL. By testing the 283 clinical samples, the dPCR-NIPT assay demonstrated a detection sensitivity of 100% and a specificity of 95.12%. Compared to the existing CS and the NGS-NIPT as the first-tier screen strategy, dPCR-NIPT assay used as a primary screen tool followed by the NGS-NIPT rescreen is the most economical approach to screen pregnant women for fetal aneuploidies without sacrificing the positive detection rate. CONCLUSION: This is the first report on a dPCR-NIPT assay, consisting of all the necessary reagents from sample processing to multiplex dPCR amplification, can detect T21, T18 and T13 in a single tube reaction. The study results reveal that this assay has a sensitivity and specificity superior to the SBT and a cost much lower than the NGS-NIPT. Thus, from both the test performance and the economic benefit points of views, using the dPCR-NIPT assay to replace the SBT as a primary screen tool followed by the NGS-NIPT rescreen would be a better approach than the existing CS for detection of fetal aneuploidies in maternal plasma.

The use of oocyte cryopreservation for fertility preservation in patients with sex chromosome disorders: a case series describing outcomes.

PURPOSE: Characterize outcomes among adolescents and young adults (AYAs) with sex chromosome disorders (SCDs) after oocyte cryopreservation (OC) consultation. METHODS: Retrospective case series of all AYA (< 25 years) patients with SCDs seen for OC consultation from 2011 to 2019 at a large, urban, academic fertility center. All AYA patients with an SCD seen for OC consult in the study time period were reviewed and included. Data collected included patient age, SCD type, number of patients who attempted OC, number of cycles attempted, and cycle outcomes. RESULTS: Twenty-two patients were included: 9 with Turner syndrome, 12 with mosaic Turner syndrome, and 1 with 47,XXX. Mean age at consult was 14.7 ± 3.5 years. Fourteen patients elected for OC: 5 with Turner syndrome, 8 with mosaic Turner syndrome, and 1 47,XXX who pursued 31 OC cycles total. Of those 14 patients, 10 underwent retrieval, 9 froze oocytes, and 8 froze mature (MII) oocytes. Seven patients underwent > 1 cycle and 7 had ≥ 1 cancelation. 3/3 patients who pursued cycles after 1st cancelation never got to retrieval. Age, SCD type, and baseline FSH did not predict ability to freeze MIIs. One patient returned after OC and attempted 4 ovulation induction cycles and 2 IVF cycles; all were canceled for low response. CONCLUSIONS: AYA patients with SCDs have a high risk of poor response and cycle cancelation but the majority froze MIIs. Thus, setting expectations is important. A larger sample size is needed to evaluate possible clinical predictors of success.