What helps define outcomes in persistent uninterpretable non-invasive prenatal testing: Maternal factors, fetal fraction or quality scores?

OBJECTIVES: To assess maternal characteristics and comorbidities in patients with persistent uninterpretable non-invasive prenatal testing (NIPT) and to evaluate the association with adverse pregnancy outcome in a general risk population. METHODS: A retrospective cohort study (July 2017-December 2020) was conducted of patients with persistent uninterpretable NIPT samples. Maternal characteristics and pregnancy outcomes were compared with the general Belgian obstetric population. RESULTS: Of the 148 patients with persistent uninterpretable NIPT, 37 cases were due to a low fetal fraction (LFF) and 111 due to a low quality score (LQS). Both groups (LFF, LQS) showed more obesity (60.6%, 42.4%), multiple pregnancies (18.9%, 4.5%) and more obstetrical complications. In the LQS group, a high rate of maternal auto-immune disorders (30.6%) was seen and hypertensive complications (17.6%), preterm birth (17.6%) and neonatal intensive care unit (NICU) admission (22%) were significantly increased. In the LFF group hypertensive complications (21.6%), gestational diabetes (20.6%), preterm birth (27%), SGA (25.6%), major congenital malformations (11.4%), c-section rate (51.4%) and NICU admission (34.9%) were significantly increased. Chromosomal abnormalities were not increased in both groups. CONCLUSIONS: Patients with persistent uninterpretable NIPT have significantly more maternal obesity, comorbidities and adverse pregnancy outcome than the general population and should receive high-risk pregnancy care. Distinguishing between LFF and LQS optimizes counseling because maternal characteristics and pregnancy outcome differ between these groups.

Pan-Cancer Detection and Typing by Mining Patterns in Large Genome-Wide Cell-Free DNA Sequencing Datasets.

BACKGROUND: Cell-free DNA (cfDNA) analysis holds great promise for non-invasive cancer screening, diagnosis, and monitoring. We hypothesized that mining the patterns of cfDNA shallow whole-genome sequencing datasets from patients with cancer could improve cancer detection. METHODS: By applying unsupervised clustering and supervised machine learning on large cfDNA shallow whole-genome sequencing datasets from healthy individuals (n = 367) and patients with different hematological (n = 238) and solid malignancies (n = 320), we identified cfDNA signatures that enabled cancer detection and typing. RESULTS: Unsupervised clustering revealed cancer type-specific sub-grouping. Classification using a supervised machine learning model yielded accuracies of 96% and 65% in discriminating hematological and solid malignancies from healthy controls, respectively. The accuracy of disease type prediction was 85% and 70% for the hematological and solid cancers, respectively. The potential utility of managing a specific cancer was demonstrated by classifying benign from invasive and borderline adnexal masses with an area under the curve of 0.87 and 0.74, respectively. CONCLUSIONS: This approach provides a generic analytical strategy for non-invasive pan-cancer detection and cancer type prediction.

Deep Sequencing of HIV-1 RNA and DNA in Newly Diagnosed Patients with Baseline Drug Resistance Showed No Indications for Hidden Resistance and Is Biased by Strong Interference of Hypermutation.

Deep sequencing of plasma RNA or proviral DNA may be an interesting alternative to population sequencing for the detection of baseline transmitted HIV-1 drug resistance. Using a Roche 454 GS Junior HIV-1 prototype kit, we performed deep sequencing of the HIV-1 protease and reverse transcriptase genes on paired plasma and buffy coat samples from newly diagnosed HIV-1-positive individuals. Selection was based on the outcome of population sequencing and included 12 patients with either a revertant amino acid at codon 215 of the reverse transcriptase or a singleton resistance mutation, 4 patients with multiple resistance mutations, and 4 patients with wild-type virus. Deep sequencing of RNA and DNA detected 6 and 43 mutations, respectively, that were not identified by population sequencing. A subsequently performed hypermutation analysis, however, revealed hypermutation in 61.19% of 3,188 DNA reads with a resistance mutation. The removal of hypermutated reads dropped the number of additional mutations in DNA from 43 to 17. No hypermutation evidence was found in the RNA reads. Five of the 6 additional RNA mutations and all additional DNA mutations, after full exclusion of hypermutation bias, were observed in the 3 individuals with multiple resistance mutations detected by population sequencing. Despite focused selection of patients with T215 revertants or singleton mutations, deep sequencing failed to identify the resistant T215Y/F or M184V or any other resistance mutation, indicating that in most of these cases there is no hidden resistance and that the virus detected at diagnosis by population sequencing is the original infecting variant.

Markers associated with persisting low-level viraemia under antiretroviral therapy in HIV-1 infection.

OBJECTIVES: To identify host and viral characteristics associated with long-term persisting low-level viraemia (PLLV) under antiretroviral therapy (ART). PATIENTS AND METHODS: Seventy-one ART-treated patients with long-term PLLV (20-250 copies/mL) and 102 control patients with systematically undetectable viral load (VL) were selected retrospectively from ART-treated patients followed at the Ghent HIV reference centre. Host and viral characteristics were compared using univariate and multivariate analyses. RESULTS: Higher plasma VL at therapy initiation (OR 3.52; 95% CI 1.86-6.65; P < 0.001), therapy re-initiation after an interruption (OR 3.94; 95% CI 1.70-9.16; P = 0.001), male gender (OR 4.28; 95% CI 1.40-13.00; P = 0.011), a protease inhibitor-based regimen (OR 2.90; 95% CI 1.20-6.97; P = 0.017) and predicted CCR5 co-receptor tropism (OR 2.53; 95% CI 1.05-6.11; P = 0.039) were independently associated with PLLV. CONCLUSIONS: VL at ART initiation, therapy history, gender, ART regimen and co-receptor tropism were independently associated with PLLV. Gender, therapy history, co-receptor tropism and VL at ART initiation could be valuable predictive markers to identify patients at risk for PLLV.

Population screening for 15q11-q13 duplications: corroboration of the difference in impact between maternally and paternally inherited alleles.

Maternally inherited 15q11-q13 duplications are generally found to cause more severe neurodevelopmental anomalies compared to paternally inherited duplications. However, this assessment is mainly inferred from the study of patient populations, causing an ascertainment bias towards patients at the more severe end of the phenotypic spectrum. Here, we analyze the low coverage genome-wide cell-free DNA sequencing data obtained from pregnant women during non-invasive prenatal screening (NIPS). We detect 23 15q11-q13 duplications in 333,187 pregnant women (0.0069%), with an approximately equal distribution between maternal and paternal duplications. Maternally inherited duplications are always associated with a clinical phenotype (ranging from learning difficulties to intellectual impairment, epilepsy and psychiatric disorders), while paternal duplications are normal or associated with milder phenotypes (mild learning difficulties and dyslexia). This data corroborates the difference in impact between paternally and maternally inherited 15q11-q13 duplications, contributing to the improvement of genetic counselling. We recommend reporting 15q11-q13 duplications identified during genome-wide NIPS with appropriate genetic counselling for these pregnant women in the interest of both mothers and future children.

Cell-free DNA methylome analysis for early preeclampsia prediction.

Preeclampsia (PE) is a leading cause for peripartal morbidity, especially if developing early in gestation. To enable prophylaxis in the prevention of PE, pregnancies at risk of PE must be identified early-in the first trimester. To identify at-risk pregnancies we profiled methylomes of plasma-derived, cell-free DNA from 498 pregnant women, of whom about one-third developed early-onset PE. We detected DNA methylation differences between control and PE pregnancies that enabled risk stratification at PE diagnosis but also presymptomatically, at around 12 weeks of gestation (range 9-14 weeks). The first-trimester risk prediction model was validated in an external cohort collected from two centers (area under the curve (AUC) = 0.75) and integrated with routinely available maternal risk factors (AUC = 0.85). The combined risk score correctly predicted 72% of patients with early-onset PE at 80% specificity. These preliminary results suggest that cell-free DNA methylation profiling is a promising tool for presymptomatic PE risk assessment, and has the potential to improve treatment and follow-up in the obstetric clinic.

Machine learning-based detection of immune-mediated diseases from genome-wide cell-free DNA sequencing datasets.

The early detection of tissue and organ damage associated with autoimmune diseases (AID) has been identified as key to improve long-term survival, but non-invasive biomarkers are lacking. Elevated cell-free DNA (cfDNA) levels have been observed in AID and inflammatory bowel disease (IBD), prompting interest to use cfDNA as a potential non-invasive diagnostic and prognostic biomarker. Despite these known disease-related changes in concentration, it remains impossible to identify AID and IBD patients through cfDNA analysis alone. By using unsupervised clustering on large sets of shallow whole-genome sequencing (sWGS) cfDNA data, we uncover AID- and IBD-specific genome-wide patterns in plasma cfDNA in both the obstetric and general AID and IBD populations. We demonstrate that pregnant women with AID and IBD have higher odds of receiving inconclusive non-invasive prenatal screening (NIPS) results. Supervised learning of the genome-wide patterns allows AID prediction with 50% sensitivity at 95% specificity. Importantly, the method has the potential to identify pregnant women with AID during routine NIPS. Since AID pregnancies have an increased risk of severe complications, early recognition or detection of new-onset AID can redirect pregnancy management and limit potential adverse events. This method opens up new avenues for screening, diagnosis and monitoring of AID and IBD.

Rare autosomal trisomies detected by non-invasive prenatal testing: an overview of current knowledge.

Non-invasive prenatal testing has been introduced for the detection of Trisomy 13, 18, and 21. Using genome-wide screening also other "rare" autosomal trisomies (RATs) can be detected with a frequency about half the frequency of the common trisomies in the large population-based studies. Large prospective studies and clear clinical guidelines are lacking to provide adequate counseling and management to those who are confronted with a RAT as a healthcare professional or patient. In this review we reviewed the current knowledge of the most common RATs. We compiled clinical relevant parameters such as incidence, meiotic or mitotic origin, the risk of fetal (mosaic) aneuploidy, clinical manifestations of fetal mosaicism for a RAT, the effect of confined placental mosaicism on placental function and the risk of uniparental disomy (UPD). Finally, we identified gaps in the knowledge on RATs and highlight areas of future research. This overview may serve as a first guide for prenatal management for each of these RATs.

Comprehensive genome-wide analysis of routine non-invasive test data allows cancer prediction: A single-center retrospective analysis of over 85,000 pregnancies.

BACKGROUND: Implausible false positive results in non-invasive prenatal testing (NIPT) have been occasionally associated with the detection of occult maternal malignancies. Hence, there is a need for approaches allowing accurate prediction of whether the NIPT result is pointing to an underlying malignancy, as well as for organized programs ensuring efficient downstream clinical management of these cases. METHODS: Using a data set of 88,294 NIPT performed at University Hospital Leuven (Belgium) between November 2013 and March 2020, we retrospectively evaluated the positive predictive value (PPV) of our NIPT approach for cancer detection. In this approach, whole-genome cell-free DNA (cfDNA) data from NIPT were scrutinized for the presence of (sub)chromosomal copy number alterations (CNAs) predictive for a malignancy, using an unbiased NIPT analysis pipeline coined GIPSeq. For suspected cases, the presence of a maternal cancer was evaluated via subsequent multidisciplinary clinical follow-up examinations. The cancer-specificity of the identified CNAs in cfDNA was assessed through genetic analyses of a tumor biopsy. FINDINGS: Fifteen women without a cancer history were identified with a GIPSeq result suggestive of a malignant process. Their cfDNA profiles showed either genome-wide aberrations or a single trisomy 8. Upon clinical examinations, a solid or hematological cancer was identified in 4 and 7 cases, respectively. Three women were identified as having a clonal mosaicism. For one case no underlying condition was found. These numbers add to a PPV of 73%. Based on this experience, we presented a multidisciplinary care path for efficient clinical management of these cases. INTERPRETATION: The presented approach for analysing NIPT results has a high PPV, yet unknown sensitivity, for detecting asymptomatic malignancies upon routine NIPT. Given the complexity of diagnosing a pregnant woman with cancer, clinical follow-up should occur in a well-designed multidisciplinary setting, such as via the care model that we presented here. FUNDING: This work was supported by Research Foundation Flanders and KU Leuven funding.