Prenatal Exome and Genome Sequencing for Fetal Structural Abnormalities

Abstract

As prenatal exome sequencing (ES) becomes integrated into clinical care, it is critical that providers caring for women with fetal anomalies recognize not only the benefits, but also the challenges and considerations related to this technology. This overview of prenatal sequencing includes information about indications for sequencing, methods, diagnostic yield, clinical utility, variant interpretation, ethical considerations and dilemmas, practical considerations (i.e. turnaround time and cost), pre- and post-test counseling points, and psychological impact of testing on families.

Introduction

Birth defects affect 3–4 % of all livebirths and account for 20% of infant deaths¹. Historically, prenatal diagnosis has focused on detection of chromosomal abnormalities, particularly trisomy 21, using metaphase karyotype. More recently, chromosomal microarray analysis (CMA) is increasingly used to provide higher resolution detection of cytogenetic abnormalities². However, CMA does not detect most single gene disorders. With advances in DNA technology, an increasing number of single gene disorders are amenable to genetic diagnosis. Next generation sequencing (NGS) can screen for a large number of conditions when a genetic diagnosis is suspected.

Advanced sequencing technologies such as exome and genome sequencing are being increasingly integrated into pediatric and adult clinical care³. Next generation sequencing tests may interrogate a single gene, a panel of selected genes, the exome (the protein-coding genes that make up 1–2% of the genome), or the entire genome. While sequencing of the entire genome (whole genome sequencing (WGS)) is feasible, exome sequencing (ES) is less costly and provides a more manageable amount of data to interpret. Multiple published series have reported on the diagnostic yield of fetal ES in the setting of fetal anomalies when CMA is normal (table 1)^4–12.

Table 1:

Studies reporting on diagnostic yield of whole exome sequencing

Reference	No. cases	Inclusion criteria	Method	Positive/definite diagnoses	Comments
Petrovski et al., 2019 8	234	Prospective; any anomaly	Trio ES	10% (overall) 19% (multisystem)	Higher yield with multisystem organ abnormalities
Lord et al., 2019 6	610	Prospective; any anomaly	Trio ES	8.5% (overall) 15.4% (multisystem)	Higher yield with multisystem organ abnormalities
Vora et al., 2020 11	102	Prospective and retrospective; 87.3% of cohort had multiple anomalies	Trio ES	20.6% overall	Higher yield given majority of cohort had multisystem anomalies
Sparks et al., 2020 9	127	Nonimmune hydrops	Trio ES (90% of cases)	29%	30% of diagnoses were RASopathies
Lei et al., 2020 4	163	Congenital anomalies of the kidney and urinary tract with or without other abnormalities	Trio ES	12.3%	Higher yield in multisystem abnormalities (27%)
Normand et al., 2018 7	146	Any structural abnormality; clinical diagnostic lab	Trio ES (39%)	32%	Higher yield with multisystem abnormalities (60%; 39/65) and craniofacial abnormalities (46%; 22/48)
Li et al, 2020 5	260	Congenital heart defects	Trio ES	10%	Higher yield in cardiac rhabdomyoma (60%), complex CHDs (16.7%), septal defects (14%)
Stanley et al., 2020 10	246	Stillbirths	Proband only	6.1%	Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34)
Yaron et al, 2022 64	86	Central nervous abnormalities	Trio ES	44%	Highest diagnostic yield was noted in cases categorized as multisystem (14/32, 44%) and complex brain anomalies (14/24, 58%).

While ES sequencing is a powerful diagnostic tool, its use presents challenges that include a lengthy turnaround time (usually 3 to 4 weeks but when clinically indicated, much faster turnaround of genome sequencing has been reported)¹³, detection of variants of uncertain significance (VUS), cost and concerns for health equity, psychological impact, counseling regarding incidental and secondary findings, and prenatal specific ethical dilemmas related to advanced sequencing technologies¹⁴. This review will focus on next generation sequencing strategies for molecular prenatal diagnosis.

Historical development of prenatal tests

Fluorescence In Situ Hybridization (FISH), Karyotype, and Chromosomal Microarray

Historically, karyotype was the only modality available for prenatal testing in the setting of fetal anomalies. However, karyotyping is limited by the need for culturing, leading to a turnaround time of at least one week or longer, as well as a relatively low resolution. Large deletions and duplications may be identified with karyotype when more than 5 million base pairs are affected but karyotype cannot detect smaller copy number variants (CNVs) or single gene disorders. Fluorescence in situ hybridization (FISH) technology was introduced in the 1980s and can overcome some of these limitations. FISH can be performed on uncultured cells and provide rapid identification of major autosomal aneuploidies. This method can also be used on metaphase cells to assess for selected deletions and duplications, such as the 22q11.2 (DiGeorge) deletion syndrome.

In 2012, a study by Wapner et al. reported that chromosomal microarray (CMA) had increased diagnostic yield compared to standard karyotype¹⁵. CMA can be performed on uncultured cells and therefore also has a much more rapid turnaround time. In addition, CMA can detect deletions and duplications far smaller than those detected by karyotype¹⁶. Results can also be obtained from nonviable cells with this technique and, thus are more likely to provide a result in cases of stillbirth. Given that microarray is able to detect aneuploidy as well as smaller deletions and duplications with rapid turnaround, it is now recommended for evaluation of structural abnormalities as the initial testing strategy, rather than conventional karyotype¹⁷.

Molecular Technologies

Targeted Gene Panels

Targeted gene panels are used to target sets of genes that are associated with a specific clinical phenotype, such as a skeletal dysplasia. Targeted gene panels provide comprehensive analysis of selected genes, including optimal sequencing depth and coverage of the included genes, as well as deletion/duplication testing for copy number variants below the resolution of CMA^18–20. Such panels are typically less expensive than exome sequencing and can be a cost-effective method of diagnosis for well-defined phenotypes. Panels are most useful when the phenotype is clear and when they include most of the relevant genes for possible genetic disorders involving that phenotype. However, targeting the best panel for fetal sequencing can be challenging. Fetal phenotyping involves primarily imaging, and may be limited by gestational age, fetal position, and maternal body habitus. Consideration of the neurobehavioral characteristics used for phenotyping children and adults is generally not possible and minor dysmorphic features are typically not identified. In addition, prenatal phenotypes for single gene disorders often differ significantly from what is described in postnatal cases^12,21.

One suggested benefit of targeted gene panels is lower cost when compared to exome and genome sequencing, although costs vary significantly between laboratories. Some panels may cost as little as a few hundred dollars, while others cost several thousand²². Furthermore, if a gene panel is negative, additional testing such as exome sequencing may be recommended, adding to overall costs. Rapid advances in our understanding of genetic disease also diminish the usefulness of gene panels, which generally only include previously reported genes. This is in contrast to exome or genome sequencing, in which new genes may be discovered. Figure 2 shows comparison of targeted panels to both exome and genome sequencing.

Figure 2.

Comparisons between genome, exome, and targeted sequencing. Modified from http://www.genomesop.com/somatic-mutations/⁶⁶

Exome sequencing

Exome sequencing entails analysis of the protein coding regions of the genome, which are referred to as the exons. There are approximately 20,000 protein-coding genes²³, although not all of these are associated with known human diseases. A smaller number of disease-associated genes (4000–5000) are evaluated in some laboratory settings; this is sometimes termed the ‘clinical exome’. (Figure 1).

Figure 1:

Diagnostic capability of prenatal genetic tests. (Reprinted from Hardisty EE, Vora NL. Advances in genetic prenatal diagnosis and screening. Curr Opin Pediatr 2014;26:634–8.)⁶⁵.

In prenatal diagnosis, trio-based sequencing (including both parents as well as the fetus) is often used because this approach can filter out uninformative variants, identify de novo variants (present in the fetus but absent from the parents), and determine inheritance of recessive variants. The diagnostic yield of ES depends on several factors, including the use of trios versus proband only sequencing; the presence of single versus multiple anomalies; and whether the cases were pre-selected by a genetics expert¹².

While ES can detect many single gene disorders, this method cannot identify all variants. In some cases, there may be incomplete coverage of relevant genes due to technical issues such as repetitive sequences and high GC content²⁴. ES usually does not detect variants in noncoding regions, triplet repeat disorders, indels (small insertions and deletions between 100 and 100,000 base pairs), or structural variants (rearrangements and translocations²⁵). ES cannot reliably detect copy number variants so does not replace the need for CMA; published prenatal studies utilizing ES have almost all included only patients in whom CMA was nondiagnostic.

Whole Genome Sequencing

Whole genome sequencing (WGS) analyzes both the intronic and exonic regions of the genome. The intronic non-coding regions, which are not included in ES, include regulatory regions important for protein function. “Deep intronic variants”, which are not in the exon or the exon-intron boundary, can cause alternative splice sites that impact gene function. WGS is also not a completely comprehensive genomic test but can detect some types of variants that are not detectable with exome sequencing²⁶. WGS can identify copy number variants, including those below the resolution of CMA, as well as other structural variants and expansions of short tandem repeats. WGS can also overcome other limitations of ES, such as insufficient coverage of certain coding exons (e.g. GC-rich exons), and can detect as many as 3% of protein-coding variants missed by ES^27,28.

In addition to more comprehensive testing, WGS does not require the capture step used for ES and therefore the turnaround time is faster (Figure 3). In neonatal intensive care unit settings, a rapid whole genome can be completed in 24–48 hours and results in as little as 17 hours have been reported^29,30. Recent studies of WGS in postnatal settings have identified more causative variants in coding and non-coding regions in autism³¹, congenital heart disease³², and diaphragmatic hernia³³. Therefore, WGS has substantial benefits over ES and is likely to become the primary technology for rapid sequencing in the future. However, bioinformatics tools for genome sequencing are less developed than those available for exome sequencing and the cost of genome sequencing remains high, in part due to the cost of data management and analysis. As the cost of WGS decreases, this approach is likely to become more commonly used in prenatal diagnosis and potentially to supplant currently available testing, including as a single test to replace both CMA and ES^29,34.

Figure 3.

Sequencing technique. Modified from Goh G, Choi M. Application of whole exome sequencing to identify disease-causing variants in inherited human diseases. Genomics Inform. 2012 Dec;10(4):214–9.⁶⁷

Clinical Indications

Most series reporting on prenatal exome sequencing have studied fetuses with one or more structural anomalies detected by ultrasound (Table 1)^4–12. It is known that some fetal anomalies are associated with Mendelian syndromes caused by single gene disorders and exome sequencing seeks to diagnose these cases. Given the limited phenotypic information obtained by prenatal imaging, most series include fetuses with one or more anomalies without an obvious cause, usually after a normal chromosomal microarray (CMA). The diagnostic yield varies markedly, from about 6.2% to 80%, and depends in part on the stringency of the indications^4–12 as well as discrepancies among labs regarding variant interpretation.

Professional Society Guidelines

A recent position paper of the International Society for Prenatal Diagnosis describes the following indications for prenatal exome sequencing: (1) a current pregnancy with a fetus with a single major anomaly or with multiple organ system anomalies suggestive of a possible genetic etiology, but nondiagnostic CMA; or with no CMA result following multidisciplinary review in which the fetal phenotype strongly suggests a single gene disorder; (2) a prior undiagnosed fetus (or child) with an anomaly or anomalies suggesting a genetic etiology, and a recurrence of unexplained similar anomalies in the current pregnancy³⁵. This position statement emphasizes that ES should not be routinely used for indications other than fetal anomalies. In most circumstances, interpretation of exome sequencing data requires comparison of phenotype findings with the variants that are identified, to determine whether any variants have been associated with similar features previously. If there is no phenotypic overlap, the variants are often assumed not to be causative. In part for this reason, there is currently no evidence to support routine prenatal exome sequencing in the absence of ultrasound findings, although several ongoing studies are seeking to address the cost and efficacy of predictive genomic testing in both children and adults.

The American College of Medical Genetics and Genomics (ACMGG) has also published guidance stating that ES can be considered with fetal structural anomalies when CMA or karyotype are normal. This statement further recommends that targeted panels be sent when a specific single gene disorder is suspected, and that exome sequencing be performed after consultation with a provider with genetics expertise (prenatal genetic counselor or clinical genetics physician)³⁶.

Sequencing technique

At the time of the human genome project, scientists used Sanger sequencing, which was expensive and time-consuming. Subsequent efforts to reduce costs have led to the development of the less expensive and more efficient technologies referred to as next-generation sequencing (NGS)³⁷.

In NGS, the DNA is cut into fragments of approximately 1000 to 10000 base pairs (bp) referred to as “reads”; the pool of fragments is called the sequencing library. Most commonly, each read is paired with the read from the opposite end of the fragment; these are termed “paired-end” reads. With whole genome sequencing (WGS), the entire genome is sequenced while with exome sequencing (ES), only the 1–2% of the genes that include the coding exons are sequenced (Figure 3). With exome sequencing, the DNA fragments that overlap with exons and their flanking introns are purified from the entire library. A similar methodology is used for sequencing with targeted multigene panels.

The sequencing library is immobilized on a solid surface, amplified in clusters, denatured and then sequenced by synthesis of a new complementary strand. In this process, each nucleotide (A, C, G, T) has a different fluorescent tag, so that its insertion at a specific location in the sequenced fragment can be recorded^38–40. This is repeated multiple times in “massively parallel sequencing” and the obtained sequence reads are aligned using bioinformatics tools to generate a consensus sequence that is compared to the human reference sequence^38,39.

The sequencing reads are ordered by their best match to a position on the reference sequence (Figure 3). Software tools identify differences from the reference genome, and a statistical hypothesis is computed to determine whether any mismatch is more likely to represent a true genetic difference, or some type of error. Many regions of the human genome share identical or highly similar sequences, therefore errors in alignment are inherent in the process of short read mapping. Alignment errors may also occur due to errors in the NGS data, or due to differences in the human reference sequence relative to the sequence data that is undergoing alignment. A sequencing test or run should ideally cover each nucleotide in the human genome at least 30 times to minimize the chance of errors. Given that there are 3 billion base pairs in the human genome, each run produces approximately 90 billion pieces of data and interpretation of this tremendous quantity of data is highly complex⁴¹.

Two metrics that are used to describe the quality of a genomic sequence are the depth, which refers to the number of overlapping reads for each base pair, and the sequence coverage, which refers to the fraction of the sequence that is covered at sufficient depth. The American College of Medical Genetics and Genomics (ACMG) recommends that for diagnostic exome sequencing, ≥90–95% of the sequence should be covered at least 10-fold and that the average depth should be ≥ 100-fold⁴².

Variant interpretation

The next step in exome and genome sequencing is to determine whether any observed genetic differences are likely to be causative of the indication for testing, or possibly other disease. Variation in the genome is ubiquitous, and a typical exome sequence identifies approximately 40,000 sequence variants, while a genome sequence identifies approximately 3 million variants that differ from the human genome reference³⁹. The challenge is to determine which of these differences are benign and which are disease-causing.

After sequencing is completed, “variant-calling” using bioinformatic algorithms is used to detect mismatches between a reference sequence and the mapped reads. Such mismatches can arise due to a true variant but can also occur due to errors in sequencing chemistry, genetic differences in individuals originally contributing to the human reference sequence, or errors in the alignment process^43,44. The reference sequence comes from individuals from different ethnic backgrounds, which introduces complications in the current methodologies for analyzing sequencing data^44,45. Statistical models are used to assign a likelihood that a detected mismatch represents a true genotype and computer algorithms filter out large numbers of variants that are not causal of disease, yielding a small subset that are more closely assessed for potential pathogenicity^44,46. Variant filtering balances sensitivity and specificity, and removing false variants at the cost of failing to identify significant genetic differences⁴⁷.

Variant annotation is the process of determining the potential effect of a variant on the function of a gene and the likelihood that the phenotype is due to the variant. NGS generates thousands of sequence variants, and these must be filtered and prioritized for clinical interpretation. The annotation process enriches for rare variants, which are more likely to be pathogenic, and eliminates common variants, which are more likely to be benign, and also predicts functional effect. Annotation tools assess the frequency of variants in population databases, evolutionary conservation of the variant across species, and the genomic structure where the variant is located. Large-scale genomic sequencing databases, such as the Genome Aggregation Database (gnomAD) are used to distinguish common and rare variants while databases of previously assessed variants, such as ClinVar, collect and distribute information about previously interpreted variants⁴⁸.

Considerations in variant annotation include the strength of an association of the variant with the disease and with the phenotype of the patient; the possibility of phenotypic heterogeneity must always be considered. In addition to the clinical databases discussed above, a number of other matching databases, such as Gene-Matcher (https://genematcher.org/), DECIPHER (https://decipher.sanger.ac.uk/), and Phenome-Central (https://www.phenomecentral.org/) can identify similar cases using de-identified data, such as gene names or disease features. These tools are publicly available and do not require computational expertise.

Variant classification

The data obtained through variant annotation are used to classify the potentially significant variants. Standard terminology recommended by the American College of Medical Genetics and Genomics (ACMG) classifies variants as pathogenic, likely pathogenic, likely benign, benign, and of uncertain significance based on different types of variant evidence (e.g., population data, computational data, functional data, segregation data)⁴⁶. In most molecular diagnostic laboratories, evaluation of pathogenicity is based on application of a categorical system of 28 criteria to estimate the probability of pathogenicity. If the probability that a variant is pathogenic is greater than 99%, it is considered pathogenic; whereas, if the probability is between 90% and 99%, the variant is classified as likely pathogenic. If the evidence indicates that the probability of pathogenicity is less than 90% but the findings do not clearly prove that the variant is benign and without health consequences, the variant is termed a variant of uncertain significance (VUS)³⁹.

The ACMG guidelines suggest that variants of uncertain significance should not be used in clinical decision making. There is significant variability between laboratories in interpretation of gene variants, in part due to a lack of publicly available prenatal databases or standardized prenatal curation efforts such as those developed for postnatal phenotypes in ClinVar⁴⁹ or the Human Gene Mutation Database⁵⁰.

Variants of uncertain significance (VUS)

Interpreting a VUS is complex, particularly if it will potentially be used for reproductive decision making. Significant genetics expertise is required as some VUS are likely to be pathogenic while others are almost certainly benign. Many preimplantation genetic testing (PGT) laboratories will not select embryos based on a VUS, and IVF with preimplantation genetic testing is associated with significant costs and risks. When results are uncertain, women need additional support and may feel abandoned by providers if they are unable to provide adequate information and support⁵¹. Patients who understand the potential for uncertain results find the ambiguity more acceptable when it occurs⁵². While the ethical principles of autonomy and non-maleficence support providing VUS information to the patient, clinical interpretation and context are critically important to assure that the family understands the uncertainty.

Secondary and incidental findings

In addition to potentially identifying a genetic cause of a fetal anomaly, exome sequencing may identify risk variants for genetic disorders unrelated to the phenotype being investigated; these results have been referred to as secondary, incidental, or medically actionable findings^53,54. The ACMG recommends that 73 medically actionable genes should be assessed and reported as secondary findings when exome sequencing is performed. The goal is to identify and manage risks for selected highly penetrant genetic disorders—most are cardiovascular or cancer predisposition genes -- through established interventions aimed at preventing or significantly reducing morbidity and mortality⁵⁴. Some laboratories will only test the parents for secondary findings that are detected in the fetus, while others will evaluate all three individuals for variants in these 73 genes.

The reported incidence rate of pathogenic (P) or likely pathogenic (LP) variants for such actionable genes is 1–3% in prenatal as well as postnatal series^54–58. In part due to the unique ethical challenges of prenatal diagnosis, the ACMG recommendations regarding the reporting of secondary findings do not address sequencing in a prenatal setting. Rather, the recommendations note that “…This evaluation and reporting should be performed for all clinical germline (constitutional) exome and genome sequencing… in all subjects, irrespective of age but excluding fetal samples⁵⁵.” ACMG does not specifically recommend against reporting secondary findings in prenatal series, rather, they are agnostic and leave the subject unresolved. Prenatal studies have found that most pregnant women request reporting of secondary findings when exome sequencing is performed⁵⁶.

Clinical interpretation

Clinicians ordering exome sequencing should appreciate that a genetic test reporting a pathogenic variant is not equivalent to diagnosing a patient with the associated disorder. Rather, the genetic test result must be correlated with the patient’s clinical characteristics and family history to arrive at a clinical-molecular diagnosis. A genetic finding is not a definitive diagnostic tool; rather, it can help provide evidence for or against conditions that might be causing the specific phenotype.

Interpretation of exome sequencing results requires consideration of the phenotype and consistency with prior reports regarding any identified variants. The prenatal phenotype is more limited when compared with that available in a neonate or infant as many important features cannot be detected prenatally, such as intellectual disability, seizures, and other neurologic findings. Additional clinical features are often recognized later in pregnancy and after birth and this should prompt consideration of reanalysis of ES interpretation as such additional findings are more likely in cases with a genetic cause⁵⁷. In a study of 20 fetuses with structural anomalies who underwent prenatal ES, none had diagnoses identified prenatally. However, after birth, additional findings resulted in reinterpretation such that a variant thought to be causative was identified in 4 cases, for a detection rate of 20%⁵⁸. Reanalysis may result in reinterpretation even without additional phenotypic features, due to new data regarding novel genes or variants. Patients who have undergone prenatal ES and are considering another pregnancy should be encouraged to be seen for a preconception visit prior to the next pregnancy at which time reinterpretation of ES results can be requested.

Diagnostic yield of prenatal exome sequencing

A number of series of prenatal exome sequencing cases have been reported (Table 1). The diagnostic yield in such series has ranged from a low of 6.2% to as high as 80%^4–12; the highest yields are associated with multiple anomalies, and recurrent anomalies highly suspected to be genetic. As table 1 shows, diagnostic yields are highest with nonimmune fetal hydrops, skeletal dysplasias, and central nervous system anomalies.

Pre- and posttest counseling

Before prenatal ES is performed, there are critical components of pretest counseling that should be reviewed. These include the chance that a result will be obtained, what type of results are possible including the possibility of a VUS, preferences regarding incidental and secondary findings, the potential for unanticipated findings (such as misattributed paternity), turnaround time, preferences for data-sharing, and ongoing evolution of knowledge in genetics and the potential for reanalysis. Post-test counseling and return of results should consider the documented pretest discussions of preferences regarding which results will be returned^11,12. Components of adequate pre- and post-test counseling are listed in Table 2.

Table 2:

Main Counseling Points

Pre-test counseling for fetal exome sequencing

Exome sequencing evaluates small changes, called variants, within individual genes. Exome sequencing cannot detect all types of genetic variants Exome sequencing can identify different types of results, including positive results with a very likely diagnosis, negative results with no diagnosis found, and uncertain results where a variant was found but the significance is not clear The chance of finding a variant that is clinically significant varies but on average is about 20–25% The turnaround time for results varies but on average is about 3–4 weeks There is the option to receive any positive results of 73 medically actionable diseases as recommended by ACMG; this is entirely voluntary DNA is usually requested from both parents as this can help with interpretation of any variants found in the fetus or infant There is the possibility of unexpected findings regarding paternity or other family relationships Some laboratories share data with public databases; the data is de-identified and this helps other clinicians and patients. Patients may be asked to consent to broader data-sharing. Our understanding of genetics is constantly evolving, and reanalysis of results in the future may change interpretation of any findings

Post-test counseling for fetal exome sequencing

Negative results do not necessarily mean that there is no genetic disorder in the fetus. Exome sequencing cannot detect all genetic variants. In most cases, uncertain results should not be used for future preimplantation or prenatal testing. Uncertain results should be discussed with a geneticist who can interpret the significance of any findings. Negative and uncertain cases may benefit from reanalysis if any new clinical findings are identified, or with a new pregnancy, or after a year or longer has passed.

Clinical utility

Detection of a genetic variant may or may not result in changes in patient care or improvements in outcomes^59,60. There are currently limited data reporting on how prenatal ES alters delivery planning or neonatal management, e.g. use of targeted medications, subspecialty referrals, and additional imaging or procedures)⁶¹. Collecting these data will be important to understand how a prenatal sequencing diagnosis affects outcomes for mothers and infants.

Financial Considerations

At this time, limited data are available regarding the cost-effectiveness and impact on health care utilization based on prenatal sequencing. A recent study comparing diagnostic yield of targeted gene panels and exome sequencing for nonimmune hydrops noted that the cost of prenatal exome sequencing ranged from $2458 to $7500²². An ongoing prospective whole genome sequencing study also aims to investigate clinical utility, cost, and cost effectiveness. While NGS tests are expensive, they may compare favorably to a “diagnostic odyssey” in which a series of tests are performed until a diagnosis is made.

Public Policy Considerations

Given that most large databases of genome/exome data include variants from largely European white populations, interpretation of variants in other populations results in more VUS⁶². Many populations choose not to have DNA tests or participate in research due to historical abuses. Thus, it is important to consider how to avoid inadvertently creating health care disparities when new technologies become implemented into clinical practice.

Summary of challenges, opportunities, and future directions

A limitation of exome sequencing is the dearth of qualified personnel to interpret the results. Enhanced education for providers and patients and novel techniques for obtaining informed consent would help assure optimal implementation of these tests. Consensus guidelines for reporting variants in a prenatal context are also necessary. Given the complexity of variant analysis, prenatal sequencing provision through centers of excellence has been proposed to standardize pre- and post-test counseling and variant interpretation⁶³. A summary of the challenges and opportunities of prenatal sequencing is shown in Table 3.

Table 3.

Challenges and opportunities associated with prenatal exome sequencing.

Summary of challenges	Opportunities
Cost Timing of results Variant interpretation Variants of uncertain significance Limited prenatal phenotypes Dearth of GC Potential to uncover familial relationships (nonpaternity, incest)	Improved prenatal diagnosis Inform care in immediate newborn period Enable precision therapies in future Enable immediate initiation of gene therapies after birth Reproductive decision making Accurate recurrence risk counseling Gene discovery

In the future, some families will likely request exome or genome sequencing as screening for a structurally normal fetus. Currently, this is not supported by scientific evidence and is not recommended by professional societies. Predictive genomic testing in children and adults is being studied with regards to diagnostic yield, clinical utility, and cost. However, ethical frameworks to thoughtfully account for the specific prenatal considerations related to exome sequencing are needed as the technology continues to evolve and costs decrease. Because exome sequencing in prenatal diagnosis will inevitably increase, it is imperative that we prepare for the challenges proactively.

Glossary of Common Genetic Terms

Base Pairs

Adenine, Cytosine, Guanine, and Thymine which represent the four chemical letters or base pairs making up human genomic information

CMA

Chromosomal microarray, detect deletions and duplications at a resolution of 50- to 100-kb level

CNV

Copy number variation, large insertions or deletions of DNA often defined as greater than 100,000 base pairs

Exome Sequencing

All 20,000 genes (approximately 1.5% of the human genome) are selected by a process of chemical hybridization, followed by next-generation sequencing. Regions of the genome which do not encode for genes are not assayed

Gene Panel Test

The DNA from one or more genes related to a pathogenic condition are selected by a process of chemical hybridization or targeted amplification which is then followed by next-generation sequencing

Genome Sequencing

All exonic and intronic regions of the genome are sequenced

HPO

Human phenotype ontology, provides a standardized vocabulary of phenotypic abnormalities encountered in human disease

Indel

An insertion or deletion of DNA. Example: Reference ACTGCGT, Insertion ACTGTCTGCGT, Deletion ACGT

Reference Sequence

A version of the human genome produced by the human genome project from multiple individuals used as a baseline for comparison to sequencing information from single individuals

SNP

Single nucleotide polymorphism (benign variant changes). Example: Reference ACTGCGT, Alterative allele ACTACGT

SNV

Single nucleotide variant

STRs

Short tandem repeats, microsatellite with repeat units that are 2 to 7 base pairs in length, with the number of repeats varying among individuals, making STRs effective for human identification purposes (paternity, identification of individuals)

SV

Structural variant such as deletions, tandem duplications, inversions

Glossary specific to sequencing terms

Coverage

The number of times a portion of the genome is sequenced in a sequencing reaction. Often expressed as “depth of coverage” and numerically as 1X, 2X, 3X, etc

Exome

The portion of the genome consisting of protein-coding sequences (as opposed to introns or noncoding DNA between genes)

Exome sequencing

A technique for sequencing just the protein-coding regions of genes in a genome (known as the exome)

Gene variant

A permanent change in the DNA sequence of a gene. Previously referred to as a gene mutation, but because changes in DNA do not always cause disease, gene variant is considered a more accurate term

Genetic heterogeneity

A phenotype caused by more than one gene

Next generation sequencing

DNA sequencing technology that permits rapid sequencing of large portions of the genome, greatly increasing the throughput over classic Sanger sequencing

Pathogenic and likely pathogenic variant

Classifications of gene variants meeting specific American College of Medical Genetics and Genomics (ACMG) criteria. A pathogenic variant is thought to directly contribute to the development of disease while a likely pathogenic variant has a high likelihood (greater than 90%) to be disease-causing

Phenotype

The total observable characteristics of an individual, resulting from interaction of the genotype with the environment

RASopathy

A group of developmental syndromes caused by variants in genes that alter the Ras subfamily and mitogen-activated protein kinases that control signal transduction. Examples of RASopathy disorders include Noonan syndrome and neurofibromatosis type 1

Targeted gene panel

Sequencing approach that analyzes a select set of genes or gene regions that have known or suspected associations with the disease or phenotype under study

Trio exome sequencing

An approach to exome sequencing in which the affected individual and their unaffected parents are all studied. Trio study design (father, mother, and child) can identify inherited/non-inherited or de novo variants and aid in classification of putative causal variants

Variant call format files

The Variant Call Format (VCF) specifies the format of a text file used in bioinformatics for storing gene sequence variations

Variant filtering

A secondary genomic sequencing analysis step that consists of identifying highly confident variants and removing the ones that are falsely called

Variant curation

A process of using information from publicly available resources and internal laboratory data to assess a variant-disease relationship. A classification for each variant is assigned based on ACMG evidence codes and strength

Variant of unknown significance (VUS)

Genetic variant that cannot be definitively determined to be associated with a specific phenotype