IVF With PGT-A: Illuminating Patient Experience Around Embryo Sex Selection

Objective: To assess patient preference for knowledge of embryo sex and utilization of sex information in embryo selection, opportunities for patient education and support, and patient perspectives on nonmedical sex selection and its regulation.; Materials and Methods: An electronic survey was distributed by email to all English or Spanish speaking patients who underwent IVF with PGT-A through the Utah Center for Reproductive Medicine from January 2022 to December 2024. Quantitative data was analyzed using descriptive statistics through Microsoft Excel. Qualitive data was code for inductive content analysis through Dedoose software.; Results: Of 224 participants, 217 individuals (97%) indicated sex was included on their report of which 119 individuals (55%) were aware of the option to mask sex and 98 (45%) did not recall the option to mask sex. 83% of individuals indicated they would elect to know sex if given the option again. However, sex was most often described as a secondary factor in their selection decisions. Categories for desire to know embryo sex included: value of information, family planning, control for an aspect of the IVF process, and autonomy. Categories for desire to mask sex included: sex does not matter, health is most important, desire for a natural process, and ethics of sex selection.; Conclusions: Majority of participants desired access to sex information. Participants desired and sought out information and support throughout the IVF process. Participants also had misconceptions around the testing and genetic concepts. In this cohort, there was lack of consensus on whether individuals should be able to discard embryos of an undesired sex and if creation of clinic policy around non-medical sex selection is appropriate.; Impact Statement: These findings highlight the challenges around regulation and protection of non-medical sex selection, and the utility of genetic counseling in the ART space.

The value of cytogenetics in undiagnosed diseases AUTHOR LISTINGS AND AFFILIATIONS Malia M. Olson1, Erin E. Baldwin2, Erica F. Andersen3,4, Steven E. Boyden5, David H. Viskochil2, Hannah Anderson6, Pinar Bayrak-Toydemir3,4, Rong Mao3,4, Ashley Andrews2, Undiagnosed Diseases Network7, Lorenzo D. Botto2 1University of Utah Graduate Program in Genetic Counseling, Salt Lake City, Utah 2Department of Pediatrics, Division of Medical Genetics, University of Utah, Salt Lake City, Utah 3Department of Pathology, University of Utah, Salt Lake City, Utah 4ARUP Laboratories, Salt Lake City, Utah 5Utah Center for Genetic Discovery, Department of Human Genetics, University of Utah, Salt Lake City 6University of Utah Human Genetics Department 7National Institutes of Health Undiagnosed Diseases Network, Common Fund, Office of the Director and the National Human Genome Research Institute, National Institutes of Health, Bethesda, Md. Author Malia M. Olson Erin E. Baldwin Erica F. Andersen Affiliations ORCID https://orcid.org/0000-00021 0016-0333 3 https://orcid.org/0009-00007425-2399 3,4 https://orcid.org/0000-00027205-0600 Email [e-mail] [e-mail] [e-mail] 1 Steven E. Boyden David H. Viskochil Hannah Anderson Pinar BayrakToydemir Rong Mao Ashley Andrews Lorenzo D. Botto 5 2 3,4 https://orcid.org/0000-00015364-3366 https://orcid.org/0009-00065597-0268 [e-mail] https://orcid.org/0000-00025322-7116 [e-mail] [e-mail] 3,4 2 2 CORRESPONDING AUTHOR INFORMATION Malia M. Olson, ORDCID: 0000-0002-0016-0333, [e-mail], 970-497-0506 2 ABSTRACT Introduction: This study aimed to evaluate the incidence of cytogenetic findings in the Undiagnosed Diseases Network (UDN) cohort. We assessed the ongoing value of cytogenetic techniques, highlighting the challenges of detecting structural variants (SVs) with nextgeneration sequencing (NGS), especially balanced, large, mosaic, or complex rearrangements where no unique sequence is generated by breakpoints. Methods: We investigated the frequency of large cytogenetic diagnoses made by the UDN in a retrospective review of 807 diagnosed cases. We assessed the certainty of these diagnoses, their ability to explain participants’ manifestations, and their impact on medical management. We compiled a case series on illustrative cases. Results: Within the diagnosed cohort of UDN participants, 21 of 807 (2.6%) were diagnosed with cytogenetic findings that explained all or some of the participant’s major manifestations. Of these diagnoses, 90% (19/21) were made with high likelihood or certainty, and 76% (16/21) impacted the participants’ and/or families’ medical management. Many of these variants would be challenging to detect using currently available clinical NGS-based technologies. Conclusions: This study highlights the complementary role of cytogenetic analysis alongside genome sequencing, emphasizing the importance of multimodal testing approaches for undiagnosed patients. This approach supports accurate genetic counseling, recurrence risk assessment, and personalized management plans. INTRODUCTION DNA copy number variation is a common cause of human genetic conditions. Structural variants (SVs) are typically defined as DNA variants larger than 50 bp and include copy number 3 variants (CNVs) (deletions, duplications, and insertions) and copy number neutral variants (inversions and translocations). Copy-number variants range from chromosomal aneuploidy to microduplication and microdeletion syndromes to smaller structural variants (SVs) that can affect down to the gene or exon level. Given their clinical relevance, detecting SVs is essential for genetic diagnosis and medical management. Medical professionals and clinical laboratories increasingly utilize next-generation sequencing (NGS) technologies to detect germline structural variants. Genome-wide testing, including ES and GS, have excellent utility in clinical settings as they can detect a variety of genetic variants 1–5. Several studies have shown the utility of using exome sequencing (ES) and genome sequencing (GS) for the identification of clinically relevant variants in a wide range of cohorts, including those with rare diseases 6–9. NGS methodologies, particularly GS, offer superior resolution and the ability to detect smaller copy number variants (CNVs) and a broad range of genetic alterations, but certain complex rearrangements and largescale variations remain challenging to interpret solely based on sequencing data. Clinical GSbased copy number detection often relies on read depth comparisons across the genome, but many variant callers used in clinical GS are optimized for detecting small CNVs rather than largescale aneuploidies. Short-read sequencing presents additional challenges, as reads may not span breakpoints, preventing proper assembly of the altered sequence. Furthermore, GS struggles with coverage in repetitive genomic regions particularly prone to SVs and CNVs. As a result, balanced rearrangements, such as inversions or translocations, can remain challenging to detect by sequencing-based approaches. Additionally, when mosaicism is present at low levels, 4 the shift in read depth may be too subtle to distinguish from normal variation, batch effects, or sequencing noise, further complicating the detection of certain genomic alterations. While NGS can detect various genetic changes, cytogenetic testing modalities, including chromosome analysis and genomic microarray, can prove useful in detecting changes that are currently challenging to detect by NGS. In this study, we aim to assess the ongoing value of cytogenetic techniques, including karyotype, chromosomal microarray (CMA), and FISH, in the diagnosis of a cohort of undiagnosed patients. To achieve this, we analyzed data from the Undiagnosed Diseases Network, a research study backed by the National Institutes of Health to bring together clinical and research experts from across the U.S. to solve the most challenging medical mysteries using advanced technologies. Specifically, we examine cytogenetic findings among diagnosed participants within the Undiagnosed Diseases Network (UDN), defining cytogenetic findings as those larger than five megabases (Mb). Our objective is to highlight the potential challenges of detecting large CNVs and SVs with NGS technologies, especially balanced, large, mosaic, or complex rearrangements where no unique sequence is generated due to breakpoints. This exploratory study aims to quantify and describe the proportion of the UDN population diagnosed with clinically relevant large CNVs or SVs within the limit of detection of a standard karyotype or CMA to assess whether cytogenetic methodologies add diagnostic value and to determine how these diagnoses impact clinical management. We present a case series of UDN participants to explore how diagnoses established through cytogenetic testing provided diagnostic clarity. 5 MATERIALS AND METHODS Data Collection Participant data was retrospectively collected, focusing on cytogenetic changes identified through diagnostic testing. We collected diagnostic data on all UDN participants with an indicated diagnosis from March 15, 2018 to February 1, 2024 identifying 807 individuals with diagnoses within the UDN cohort. Individuals with large (greater than 5 Mb) cytogenetic diagnosis were identified through the categories of diagnosis name or use of a cytogenetic methodology to achieve the diagnosis. We analyzed the proportion of cytogenetic diagnoses made with certainty and those that explained most or all of the participant’s major manifestations. We also quantified the number of diagnoses that would have some or a major role in the management of the participant’s and/or the family’s health. Analysis Data were analyzed to assess the frequency and types of cytogenetic changes within the diagnosed cohort. Each identified cytogenetic finding was examined for its potential to fully or partially explain the major clinical manifestations of the participants. The certainty of each diagnosis was categorized based on whether the diagnosis was certain, highly likely, or tentative. The impact of the diagnosis on clinical management was recorded, specifically noting any changes in medical interventions or management plans attributable to the findings. The detection methodologies (e.g., karyotyping, CMA, GS) employed to identify each SV or large CNV were also documented. Descriptive statistics were used to calculate the frequency of each cytogenetic change type, the proportion of diagnoses that corresponded to major phenotypic 6 features, and the diagnostic certainty associated with each finding. Results were reported as percentages. RESULTS Within the diagnosed cohort of UDN participants, 21 of 807 (2.6%) were diagnosed with cytogenetic findings that explained all or some of the participant’s major manifestations (Table 1). Of these diagnoses, 90% (19/21) were made with high likelihood or certainty, and 76% (16/21) impacted the participants’ and/or families’ medical management. Many of these diagnoses would be challenging to detect using currently available clinical NGS-based technologies conducted on peripheral blood, including mosaic findings, genetic changes only detectable in certain sample types, or complex structural variants and rearrangements. CASE SERIES Gorlin Syndrome Caused by a Balanced Chromosome 9 Inversion A 17-year-old female was referred to the UDN despite having a clinical diagnosis of Gorlin syndrome due to her presentation not matching the typical manifestations of Gorlin syndrome and non-diagnostic extensive genetic testing. Clinical ES and GS reported no variants of interest. She had symptoms outside of the usual manifestations of Gorlin syndrome, including hypoplastic superior semicircular canal and Kallmann syndrome. She was diagnosed with a large balanced inversion of chromosome 9 following blood research GS, karyotype analysis, and FISH studies. The balanced inversion was missed by copy number variant callers used in the clinical genome analysis. It was identified, however, by research structural variant callers, which detected novel breakpoints. This diagnostic challenge 7 underscores the value of in-depth evaluation of balanced structural chromosome variants, particularly when it can be guided by clinical presentation. The inversion disrupted the PTCH1 gene, which explained her clinical diagnosis of Gorlin syndrome. The key takeaway, in this case, is that Mendelian-presenting conditions can have a cytogenetic etiology, extending beyond the common clinical assumption that karyotyping or CMA should only be considered for classic aneuploidy, microduplication, and microdeletion syndromes. A case report on this participant has been accepted for publication10. Mosaic Trisomy 4 A 2-year-old female was referred to the UDN for global developmental delays, speech delay, mild prominence of ventricles and subarachnoid spaces, metopic craniosynostosis, microcephaly, esotropia, monocular elevation, and deficiency of the right eye. Her facial features included thick eyebrows, long eyelashes, micrognathia, fused teeth, low-set ears, a smooth and long philtrum, a triangular face, and a broad forehead. Her skeletal findings included an underdeveloped right radius, thumb, and finger, bilateral small finger clinodactyly, short feet, scoliosis of the thoracic and lumbar spine, a tethered cord, and short stature. She was found to have a moderate ventricular septal defect. Before evaluation at the UDN, the proband had undergone extensive genomic evaluation including CMA, exome array, ES, which were all non-diagnostic. The UDN obtained the raw ES data for reanalysis and found no other significant changes that could be associated with the participant’s clinical findings. Trio GS was conducted on blood, and no variants of interest were found. . A skin sample was collected for RNA sequencing, and a karyotype was added on to this specimen. This testing revealed mosaic trisomy of chromosome 4 in 40% (8 8 out of 20) of cells. This diagnosis explained all major features of the participant’s phenotype and plays a major role in the management of the participant’s care. Knowing mosaic trisomy 4 was present in the skin sample, the UDN research team reanalyzed the GS (performed on blood), and were unable to identify any indication of trisomy 4 in the GS data. In this case, karyotyping on skin fibroblasts detected mosaicism that went undetected by microarray, ES, and GS on blood. Sample type can play a role in certain testing technology’s ability to detect genetic variants. Some sample types, such as blood, may select against certain genetic changes including aneuploidy. It is essential to consider that mosaicism detection can be variable between testing methodologies and sample types. It is also worth noting that GS may detect whole chromosome mosaicism in some cases where karyotyping would not. Since GS analyzes DNA extracted from uncultured cells, it avoids the potential selection against abnormal, aneuploid cells during the culturing of lymphocytes for karyotyping. This phenomenon has been reported in several cases involving autosomal aneuploidies 11–13. Similar to this case, a study investigating the frequency of undetected, clinically relevant chromosome abnormalities in postnatal referrals when replacing karyotyping with GS found several cases of rare chromosomal mosaicism in <10% of cells, including trisomy 8, trisomy 9, and monosomy 20 14. The key takeaway from this case is that by integrating karyotype with NGS-based methods, particularly in cases where testing on different tissue types may be informative, we can better address diagnostic challenges of each testing technology. This is because cytogenetic techniques are more amenable to using different sample types than GS. 9 BALANCED TRANSLOCATION WITH BRSK2 GENE DISRUPTION A 6-year-old female was referred to the UDN for severe global developmental delay, delayed growth, truncal hypotonia, a small corpus callosum and delayed myelination noted on MRI, Dany Walker variant, strabismus, torticollis, and café-au-lait macules. She had undergone extensive previous genetic workup including CMA, SMA1 FISH, a brain malformations panel, and trio ES with no diagnostic results. Following clinical GS reanalysis using research GS pipelines and karyotyping, she was diagnosed with a de novo balanced 11p15.5 - 17q22 translocation that disrupts BRSK2, resulting in a complete loss of function. This diagnosis explained some of her major manifestations. It is not currently known if her brain findings (small corpus callosum, delayed myelination and Dandy-Walker brain variant) are related to the BRSK2 gene disruption or if they are caused by something else. This diagnosis had some role in the management of the participant’s and/or her family’s health. The key takeaway from this case is that certain SVs, especially balanced rearrangements, are challenging to detect by clinically available ES and GS even when these rearrangements disrupt genes at breakpoints. DISCUSSION This study highlights the importance of integrating various genetic testing methodologies, such as cytogenetic techniques and NGS, in diagnosing patients with rare and undiagnosed conditions. As demonstrated in this case series and analysis of the diagnosed cohort from the UDN, cytogenetic findings provided definitive diagnoses in a cohort of participants. To be accepted into the UDN, providers make a case that patients have received a reasonable workup without achieving a diagnosis. When we consider that these UDN 10 participants were diagnosed or could have been diagnosed via karyotype or CMA, tests that are readily available clinically, it is important to explore how changes to the testing landscape may mean that certain patients are undergoing more extensive and costly workup than needed due to changes in testing strategies. These findings underscore the value of conventional cytogenetic techniques, particularly in instances where SVs and large CNVs may be challenging to detect using NGS alone. Our study demonstrates the diagnostic value of cytogenetic testing in a cohort of patients with undiagnosed conditions. Many difficult to detect genetic changes can be detected by cytogenetic techniques, with the specific challenges of GS being most directly addressed by supplementing with karyotyping. Karyotyping continues to offer clinical utility in specific scenarios, particularly when balanced structural variants are suspected. While NGS methodologies, particularly GS, offer superior resolution and the ability to detect smaller CNVs and a broader range of genetic alterations, certain complex rearrangements and large-scale variations remain challenging to interpret solely based on sequencing data. Our findings demonstrate that large cytogenetic alterations often play a crucial role in establishing diagnoses, especially for conditions that may not present with clear molecular signatures detectable by NGS alone. The challenges of detecting large-scale SVs using NGS methodologies have been documented in previous studies, with limitations in accurately determining breakpoints for balanced structural variants and difficulty in detecting larger or complex rearrangements15,16. Our study adds to this body of knowledge by showing that cytogenetic testing remains indispensable in certain diagnostic contexts. For patients within our cohort, the ability to visualize chromosomal abnormalities using karyotyping provided clarity that might not have 11 been achievable through GS or ES alone. Our case series demonstrates the ongoing need for multimodal testing approaches in clinical diagnostics, especially for patients facing long diagnostic odysseys. The implications extended beyond the affected individuals in cases where karyotyping revealed chromosomal abnormalities. The diagnoses often led to cascade testing for family members, highlighting the role of cytogenetic findings in informing both individual and familial medical management. This can significantly impact family planning, reproductive decisionmaking, and risk assessments. Genetic counseling is crucial in these contexts, helping families understand the broader implications of cytogenetic findings and receiving a risk assessment. Compared to cytogenetic techniques, diagnostic yields of GS will be much higher overall across a broad spectrum of referrals. However, as our study demonstrates, a complementary testing approach, including karyotyping, should be considered when other testing methodologies have not detected an etiology for a potential genetic condition. We may need to consider a flip in the testing strategy algorithm. Previously, cytogenetic methods would be pursued prior to GS, often due to availability and cost concerns. During this testing landscape shift where GS is becoming more clinically available, cytogenetic methods can be considered following negative ES or GS. Thus, as Hostenbach et al. (2019) posit, “We envisage [GS] as a promising ‘one test fits most,’ not as a ‘one test fits all.” This study reinforces the idea that cytogenetic techniques and GS should not be viewed as competing technologies but rather as complementary tools that together provide a more comprehensive view of a patient’s genome, both from a structural standpoint, and the ability to test different sample types (fibroblasts, 12 etc.). Future studies could explore the frequency of cytogenetic findings or the length of the diagnostic odyssey of those with rare SVs in the clinical genetics population. As the testing landscape continues to evolve and new genomic technologies progress, medical providers and laboratories offering clinical genetic testing face challenges. Providers face ordering the right test for the right patient at the right time, which proves challenging considering the breadth of genetic testing options available and when patients may present with complex medical histories, extensive previous genetic workup, and lengthy diagnostic odysseys. Genetic testing laboratories encounter several challenges when incorporating new genetic testing technologies into their test offerings. One major obstacle is the logistical complexity of handling diverse sample types, as different testing modalities often require specific collection methods. For example, karyotyping typically requires sodium heparin test tubes to preserve cells for culture, whereas molecular testing commonly uses EDTA tubes or buccal swabs. Many GS platforms are not validated on alternative sample types, like fibroblasts culture, FFPE, or fresh tissue, sample types which proved to be useful for diagnosis in our case series. Additionally, the collection of skin biopsy samples is more invasive than other sample collection methodologies but may be considered in cases where mosaicism is suspected. Different sample requirements make running multiple tests off one sample collection difficult. Additionally, many laboratories have distinct teams for cytogenetic and molecular testing, each with specialized expertise in their respective areas. While this division allows for a high level of proficiency in both domains, it can pose challenges when integrating new technologies that require knowledge from both fields. Collaborative efforts between these teams are essential to successfully incorporating emerging testing methodologies. Increased 13 cross-training and knowledge-sharing can enhance the workflow, enabling team members to better understand and support assays that combine cytogenetic and molecular techniques. This collaboration ensures a more seamless adoption of new technologies, comprehensive result interpretation, and optimization of testing capabilities across the laboratory. While improving the detection capabilities of CNVs by NGS methodologies and long-read sequencing may address the concerns highlighted by the present study, implementing these technologies into laboratory offerings and clinical practice inevitably takes time. Several limitations to our study should be acknowledged. First, we did not address test utilization or cost considerations, which are important factors in clinical decision-making and patient access to genetic testing. Incorporating these factors in future studies could provide a more comprehensive understanding of how different testing methodologies impact healthcare systems and patients. Additionally, while karyotyping typically has a resolution of 5 Mb, this cutoff is somewhat arbitrary, as some deletions or duplications may be smaller than 5 Mb and still detectable, while other larger abnormalities, especially terminal deletions, may remain cryptic. This limitation affects the interpretation of our findings, as our inclusion criteria of findings larger than 5 Mb does not guarantee that these genetic changes could reliably be detected through karyotyping. Furthermore, we could not deduce the incidence of cytogenetic abnormalities in the UDN cohort as karyotyping and CMA are not conducted systematically across all participants. In conclusion, our findings highlight the continued relevance of karyotyping in diagnosing rare diseases, especially in detecting large structural variants that are difficult to identify through NGS alone. A multimodal testing approach incorporating NGS and cytogenetic 14 techniques can shorten the diagnostic odyssey for many undiagnosed patients, providing clarity and guiding clinical management. Moreover, the genetic counseling and medical management implications of cytogenetic findings remain critical, not only for individual patients but also for their families. As genetic testing technologies evolve, clinicians must continue to use a combination of testing technologies to ensure that all clinically relevant genomic alterations are detected. ABBREVIATIONS ES: exome sequencing; GS: genome sequencing; NGS: next-generation sequencing; CNVs: copynumber variants; SVs: structural variants; Mb: megabase(s); UDN: Undiagnosed Diseases Network; CMA: chromosomal microarray DATA AVAILABILITY The UDN Data Management Coordinating Center (DMCC) facilitates the dissemination of deidentified data to NIH-designated controlled-access repositories and other pertinent resources on behalf of network sites.Genomic and phenotypic data are made accessible to the scientific community through dbGaP, with new data submissions occurring annually. To explore data available in the latest release, visit the UDN study page in dbGaP. Individuals interested in accessing UDN data through dbGaP should submit a data access request (DAR). Detailed instructions for this process can be found on the NIH Scientific Data Sharing website. ETHICS DECLARATION The University of Utah and NIH Institutional Review Boards (NIH IRB #:15HG0130) reviewed this study. All the participants, their respective parents, or their legal guardians provided consent for 15 research purposes. The consent provided by the participants, their parents, or their legal guardians included authorization to publish the data. Individual-level data was de-identified. ACKNOWLEDGEMENTS We’d like to thank the patients and their families for their continued willingness to share their story in hopes of helping other families, patients, and medical providers. FUNDING STATEMENT The research reported in this publication was supported in part by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UM1TR004409. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. REFERENCES 1. Carvill GL; M Heather C. Next-Generation Sequencing in Intellectual Disability. J Pediatr Genet. 2015;04(03):128-135. doi:10.1055/s-0035-1564439 2. 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Hochstenbach R, Van Binsbergen E, Schuring-Blom H, Buijs A, Ploos Van Amstel HK. A survey of undetected, clinically relevant chromosome abnormalities when replacing postnatal karyotyping by Whole Genome Sequencing. European Journal of Medical Genetics. 2019;62(9):103543. doi:10.1016/j.ejmg.2018.09.010 15. Redin C, Brand H, Collins RL, et al. The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies. Nature Genetics. 2017;49(1):36-45. doi:10.1038/ng.3720 16. Austin-Tse CA, Jobanputra V, Perry DL, et al. Best practices for the interpretation and reporting of clinical whole genome sequencing. npj Genom Med. 2022;7(1):27. doi:10.1038/s41525-022-00295-z 17 18 Table 1. Cytogenetic diagnoses made by the Undiagnosed Diseases Network and the methods by which these diagnoses were achieved. Diagnosis Chief Method Used to Obtain Diagnosis Diploid/triploid mosaicism CMAa 16p11.2(30,554,158-31,536,880)x1 CMA 46, XX sex reversal 4 GSb 17p13.3 deletion CMA 6p22.1q14.1 CMA 1q21.1 duplication CMA Diploid/triploid mosaicism CMA 17p13.3 deletion Karyotype 1p13.3 deletion CMA 20p13.3 duplication CMA Chromosome 7 paracentric inversion Karyotype Mosaic trisomy 20 Karyotype Mosaic chromosome 5p duplication syndrome GS X chromosome anomaly Karyotype Mosaic trisomy 4 Karyotype Chromosome Xq28 duplication syndrome Panelc Mosaic 16p13.3p11.2 duplication-related condition Karyotype Gorlin Syndrome - inversion Karyotype Wieacker-Wolff syndrome - deletion CMA Autosomal recessive hearing loss and male infertility - deletion CMA Osteosclerosis - duplication CMA Chromosomal microarray (CMA) Genome sequencing (GS) c Identified by an NGS-based panel sent by clinical providers. Not reported by prior CMA nor UDN GS. a b 19