The cost for diagnosis by implementing CMA as primary test thus is anticipated to be even lowered. Despite its limitations, the current study provides important evidence that the proposed algorithm is cost saving whilst maximizing the number of diagnoses achieved for invasive prenatal diagnosis in the public healthcare system in Hong Kong. Technology advancement involving next generation sequencing and software improvements such as automation are likely to further increase diagnostic rate, reduce costs, and shorten TAT.
It is therefore recommended to switch to the proposed algorithm, with the implementation of aCGH as a routine test for invasive prenatal diagnosis following QF-PCR, to facilitate the uptake of such advances into the Hong Kong public healthcare system through evidence of clinical- and cost-effectiveness. Future areas for research should include establishing the willingness-to-pay thresholds in the local setting to guide decision makers for efficient allocation of healthcare resources.
Chromosome analysis of human amniotic-fluid cells. Identification of human chromosomes by DNA-binding fluorescent agents. Clinical utility of chromosomal microarray analysis in invasive prenatal diagnosis.
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Arch Gynecol Obstet. Risks and recommendations in prenatally detected De novo balanced chromosomal rearrangements from assessment of long-term outcomes. Am J Hum Genet. Download references. The authors would like to acknowledge and thank participants involved in the study, medical colleagues, nurses and clerical staff involved in subject recruitment in Queen Elizabeth Hospital and Tsan Yuk Hospital, and laboratory staff involved in prenatal diagnosis.
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. You can also search for this author in PubMed Google Scholar. All authors contributed to the conception and design of the work. All of the authors reviewed and approved the final manuscript. Informed written consent was obtained from all women who agreed to participate in the study. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Primary analysis: detailed workflow of the proposed algorithm. Figure S1b Primary analysis: detailed workflow of the current algorithm. Secondary analysis: detailed workflow of the proposed algorithm. Figure S2b Secondary analysis: detailed workflow of the current algorithm.
Primary indication of invasive testing for prenatal cases. Reprints and Permissions. Chung, C. Cost-effectiveness analysis of chromosomal microarray as a primary test for prenatal diagnosis in Hong Kong. BMC Pregnancy Childbirth 20, Download citation.
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Seven of these 31 patients had variants that could have been measured by the specific probes on the array, but the GSA failed to do so, because these probes did not pass the stringent QC after rare-variant calling performed with zCall.
For 2 of these 31 patients, the GSA was only able to identify 1 of 2 variants as these patients were compound heterozygous. Interestingly, in 35 patients whom conventional diagnostics did not find a causative genetic variant Table S2 , our customized GSA could detect pathogenic variants and lead to a diagnosis in 6 patients.
These genes were not analyzed as the potential genetic cause during conventional diagnostics, possibly due to overlapping clinical phenotypes of the patients. In 7 patients some heterozygous variants were previously detected patient no.
For the other 5 patients, GSA could not replicate the results found from the conventional methods as the probes were not added on the array. A newly updated version of the GSA is expected to allow all these SNVs to be assessed in more detail and reveal how well they can be detected.
For 5 variants in 3 samples, Sanger sequencing could not be performed because of lack of available DNA. For the remaining 41 variants, Sanger sequencing could confirm 38 out of 41 variants In 12 PID patients, CNV analysis based on the array genotyping data could reveal large chromosomal aberrations and microdeletions at the gene level.
Three of the previously known exon deletions that were discovered during conventional diagnostics could be reproduced, including 2 patients with a homozygous DNA cross-link repair protein 1C DCLRE1C deletion Figure 1A and 1 patient with a hemizygous x-linked inhibitor of apoptosis protein XIAP deletion patient no.
Figure 1. Interestingly, 2 PID patients without a previous genetic diagnosis were recognized as having monosomy 7, which is suspected for a hematologic malignancy rather than PID patient no. However, 34 variants could not be investigated due to limited coverage of probes at the time of GSA design; and, 3 of the 4 previously detected CNVs could also be replicated. These 37 patients included 29 patients in whom conventional methods had previously detected genetic variants 26 patients by SNV and 3 by CNV analysis , but also 8 newly suspected patients 6 by SNV and 2 patients suspected from leukemia as detected by CNV analysis.
In 28 patients that had established variants with conventional techniques the variants could not be replicated by GSA due to the sparse coverage of the custom probes at the time that the array was designed and therefore these patients could not obtain a conclusive genetic diagnosis. The detected variants leading to the diagnosis and numbers of patients in whom a diagnosis was made, comparing between conventional methods and GSA is shown in Figure 2 and Table S3.
Figure 2. Flow chart describing the numbers of variants identified by GSA array compared to conventional methods in 95 clinically diagnosed PID patients in the first run. As indicated above, 39 PID samples could be investigated for inter-assay validation in the second run.
Our results demonstrated that for 37 out of 39 patients, the genetically causal variants from the first run could be replicated in the second run Large CNVs such as large chromosomal aberrations were replicated; however, small heterozygous exon deletions did not replicate well probably due to short primer length of the custom probes. Finally, we compared all post-QC data for the custom variants from the first run with the data generated from the second run for these 39 patients 8, and 8, variants respectively.
There was overlap between 8, variants and we found only 13 0. The costs for NGS in one patient including analysis in a clinical diagnostic setting is about 1, Euros.
However, the costs depend strongly on the national economic system and the local health care infrastructure. The net price for WES without analysis and overhead varies from to Euros. With our effort, we performed the PID array test for the affordable price of about 40 Euros per sample.
This makes the diagnostic array an affordable promising candidate for initial screening analysis in the standard-of-care, in particular in developing countries, where genetic testing is not yet available. A high-throughput, rapid and inexpensive tool is required for identifying underlying genetic defects in a clinical care setting, especially in low-income countries.
SNP array technology is a powerful genomic analysis tool which has been widely used at the population level, but not for detecting rare pathogenic SNV variants. In this study, we present a comprehensive diagnostic SNP array that is able to screen at a genome-wide level, including rare PID gene variants. This method possesses potential advantages as compared to conventional targeted gene panel NGS diagnostics.
Moreover, we observed a high validation accuracy compared to NGS data 0. This is different from a recent previous study, which found a very low association between array and NGS data However, there are important differences between the two studies.
SNP calling is based on different algorithms in these two platforms and thus might influence variant calling, particularly for rare variants. Secondly, we used the zCall algorithm to enhance rare variant calling, results in better genotype calling for this class of variants. Karyotyping identified abnormalities in 2. In contrast, whole-genome CMA tests turned up potential culprits in 7. These results come as no surprise to most researchers in autism genetics, who for the past two years have rallied around copy number variations — DNA deletions and duplications — that turn up with microarray analysis.
The same sentiment is expressed in the new consensus report from the International Standard Cytogenomic Array Consortium , a group of researchers from clinical genetics laboratories. After reviewing 33 studies, the group found that CMA finds a genetic cause of autism in up to 20 percent of all individuals tested, significantly higher than the 5 percent yield of karyotyping.
Not all insurance companies cover CMA tests. Thanks in part to CMA, Canadians have seen a surge in genetic testing services. Microarray tests may actually save money in the long run.
In the U. CMA testing may be a gateway to getting more help for families of children with previously undiagnosed conditions. A CMA diagnosis can also provide psychosocial benefit for the family, including access to a new support community of individuals with a similar diagnosis. See the case examples below, and the Apply Results section, for examples and resources related to the clinical utility of CMA results.
In , the American College of Medical Genetics recommended CMA as first-tier testing in the population of individuals with developmental delay, intellectual impairment, autism spectrum and multiple congenital anomalies. CMA can also detect most gross chromosome abnormalities detected by standard karyotype. Karyotype is still appropriate for patients who strongly fit the features of a specific chromosomal abnormality diagnosis, such as Down syndrome.
Targeted molecular genetic testing is appropriate for conditions such as Fragile X syndrome that are not detected by CMA. However, CMA may be useful when those tests have failed to yield a diagnosis, when a patient has a diagnosis but an unusual course, or when the differential includes multiple conditions with overlapping features.
When in doubt, consult with a clinical or laboratory genetics specialist see How do I get help? In general, genetic testing costs more than routine lab tests. While CMA is currently more expensive than traditional chromosome analysis, the diagnostic yield is significantly higher in patients with certain indications. Costs are decreasing as technology improves. There is a risk of uncertain, uninformative or unexpected findings.
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