Detection of sex chromosome aneuploidies using quantitative fluorescent PCR in the Hungarian population

Prenatal diagnosis of non-mosaic sex chromosome abnormalities: a 10-year experience from a tertiary referral center

OBJECTIVES

The aim of this study was to explore the frequency and profile of non-mosaic sex chromosome abnormalities detected in prenatal diagnosis over the past 10 years.

METHODS

We retrospectively reviewed pregnancies diagnosed with non-mosaic sex chromosome abnormalities between January 2012 and December 2021, using karyotyping and/or single nucleotide polymorphism (SNP) array. Maternal age, indications for testing, and outcomes were recorded.

RESULTS

Traditional karyotyping identified 269 (0.90 %) cases of non-mosaic sex chromosome abnormalities among 29,832 fetuses, including 249 cases of numerical abnormalities, 15 unbalanced structural abnormalities, and 5 balanced structural abnormalities. The overall detection rate of common sex chromosome aneuploidies (SCAs) was 0.81 %, with 47,XXY, 47,XXX, 47,XYY, and 45,X accounting for 0.32 , 0.19, 0.17, and 0.13 % respectively. All showed a fluctuating upward trend over the study period, except for 45,X. During the first five years (2012-2016), the major indication for testing was advanced maternal age (AMA), followed by abnormal ultrasound, abnormal noninvasive prenatal testing (NIPT), and abnormal maternal serum screening (MSS). In the second five years (2017-2021), the most frequent indication was abnormal NIPT, followed by AMA, abnormal ultrasound, and abnormal MSS. Among the 7,780 cases that underwent SNP array in parallel, an additional 29 clinically significant aberrations were detected. The most frequent aberration was a microdeletion in the Xp22.31 region, which was associated with X-linked ichthyosis.

CONCLUSIONS

Fetal sex chromosome abnormalities are important findings in prenatal diagnosis. The application of NIPT and SNP array technology has greatly improved the detection of SCAs and submicroscopic aberrations associated with sex chromosomes.

QF-PCR: a valuable first-line prenatal and postnatal test for common aneuploidies in South Africa

Quantitative fluorescence-polymerase chain reaction (QF-PCR) is useful for the detection of aneuploidies involving chromosomes 13, 18, 21, X and Y. Due to the rapid turn-around time and reduced cost compared to traditional karyotyping, QF-PCR has been used as an alternative test for both pre- and postnatal aneuploidy detection in Johannesburg, South Africa since 2001. An internal review of 13,396 aneuploidy tests processed using QF-PCR between January 2015 and December 2019 was performed, and the results showed that the majority (~ 88%) of cases were postnatal tests, with prenatal samples accounting for only ~ 12% of cases. The most common aneuploidies detected were Trisomy 21 (20.6%), Trisomy 18 (3.7%) and Trisomy 13 (2.4%), while sex chromosome aneuploidies were only detected in < 1% of cases. The average percentage of positive cases over the 5-year period was 32.1% for postnatal samples and 11.3% for prenatal samples. QF-PCR testing of the common aneuploidies is being used appropriately, and the high percentage of positive cases demonstrates the value of QF-PCR as prenatal and postnatal tests, particularly in limited resource settings. The higher proportion of positive postnatal cases suggests that referrals are clinically appropriate. However, there is under- and uneven utilization of genetic services in many provinces in South Africa, and the state of prenatal genetic services is poor, as reflected by the low number of prenatal referrals. These results demonstrate the need for programs which will improve the genetic knowledge of referring doctors and the general public, thereby improving the broader utilisation of QF-PCR aneuploidy diagnostic testing, so that patients receive appropriate diagnoses and subsequent management.

seXY: a tool for sex inference from genotype arrays

Motivation

Checking concordance between reported sex and genotype-inferred sex is a crucial quality control measure in genome-wide association studies (GWAS). However, limited insights exist regarding the true accuracy of software that infer sex from genotype array data.

Results

We present seXY, a logistic regression model trained on both X chromosome heterozygosity and Y chromosome missingness, that consistently demonstrated >99.5% sex inference accuracy in cross-validation for 889 males and 5,361 females enrolled in prostate cancer and ovarian cancer GWAS. Compared to PLINK, one of the most popular tools for sex inference in GWAS that assesses only X chromosome heterozygosity, seXY achieved marginally better male classification and 3% more accurate female classification.

Availability and Implementation

https://github.com/Christopher-Amos-Lab/seXY.

Contact

Christopher.I.Amos@dartmouth.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.