Syndromes Without a Name Bring Labs an Uphill Battle

Although the definition of a rare disease varies regionally, these conditions collectively affect as much as 6 percent of the global population—or about one in every 17 people.¹ The vast majority (about 80 percent) of rare diseases are genetic disorders.²

But despite significant advances in molecular diagnostic technologies, patients often wait years for a diagnosis to explain their symptoms and experiences, and as many as half never receive one.³ In an era when genetic and genomic testing are theoretically accessible and affordable, why do these syndromes without a name still present such a challenge—and how can labs change that?

Connecting patients with testing

For some patients, the answer is as simple as access. People in low- and middle-income countries may have limited or no access⁴ to molecular diagnostics for a variety of reasons: labs may lack the infrastructure or equipment required to offer such testing, personnel may lack the training necessary to perform or interpret the tests, patients may be geographically isolated from service provision, or the cost of such testing may exceed patients’ or health systems’ ability to pursue it.

Even in developed countries, individual patients may be limited by insurance coverage and criteria, out-of-pocket funding, or a lack of access to facilities that provide the necessary testing.

In every region, poor health literacy further exacerbates these issues.⁵ Patients who don’t have or provide the necessary information to prompt genetic testing may never be offered it; those who are unaware of this testing—or the different types of testing available—may struggle to advocate effectively for more in-depth diagnostics. Even after receiving a test order, patients who don’t understand the reasoning behind the tests may fear the potential results. Likewise, patients who don’t trust that their results will be handled privately and sensitively may not complete the testing.⁶

Determining a diagnosis

Patients who do have access to medical care frequently experience delays or misdiagnoses due to nonspecific or overlapping symptoms.⁷ Many rare diseases and syndromes without a name feature common symptoms such as fatigue, pain, or developmental delays that can be attributed to a wide range of disorders; even more specific presentations such as cardiac conditions,⁸ hereditary cancer syndromes,⁹ or vision loss¹⁰ may yield misdiagnoses by professionals who order inappropriate or insufficient testing or incorrectly interpret patients’ test results.

Patients who do receive testing often qualify for specific investigations on the basis of their clinical presentation—but single-gene and small-panel testing may miss diagnoses based on genes or variants not included in those panels. For example, many hereditary connective tissue panels exclude the TNXB gene (causative for classical-like Ehlers-Danlos syndrome) due to a pseudogene that interferes with accurate sequencing,¹¹ meaning that these panels are not capable of providing diagnostic information for patients with pathogenic TNXB mutations.

In some cases, patients who don’t receive conclusive results from gene or panel testing may proceed to whole exome sequencing (WES) or whole genome sequencing (WGS), large-scale tests that have been shown to yield diagnoses in approximately one-quarter to one-third of people who undergo them.¹² In the remaining patients, variants of unknown significance, genes that present sequencing challenges, complex multifactorial conditions, or disorders resulting from epigenetic or non-genetic causes complicate the search for answers.

Although the cost of sequencing has fallen significantly over the last two decades,¹³ payers remain hesitant to provide coverage—despite clear evidence of both cost savings and care improvement as a result. A study of WES in patients who had been denied coverage demonstrated that over one-third of these patients received a diagnosis based on the sequencing and the majority of those underwent a change in clinical care.¹⁴ Another study in acutely ill infants demonstrated significant cost savings as a result of whole genome sequencing—by spending $1.7 million for both testing and treatment, the intensive care units participating in the study saved $2.2 to $2.9 million in overall healthcare costs.¹⁵

When the search continues

Genomic sequencing is often seen as a final step by providers supporting undiagnosed patients. But when even this approach fails, what routes remain open in the search for solutions?

Research suggests a number of potential approaches, including:

• Additional sequencing of both unaffected and affected family members
• Periodic reanalysis of results to incorporate new patient and research information
• In-depth genomic studies, such as structural variant analysis, long-read sequencing, and pan-genome reference alignment
• Functional examination of variants of unknown significance
• Epigenetic studies, such as DNA methylation profiling
• Transcriptomic analysis to detect aberrant splicing, expression, or structural variants
• Proteomic, lipidomic, and metabolomic studies
• Computer- or AI-assisted case matching to compare patients with similar phenotypes

Unfortunately, these tools often present financial or logistical challenges for both labs and patients. Some technologies needed to pursue detailed investigations are available only at large research institutions or centralized laboratories and, as with exome and genome sequencing, health insurance providers often decline to cover them.

Nonetheless, the technologies’ ability to facilitate diagnoses is proven. Automated result reanalysis, for example, has been shown to increase diagnostic yield by 4 to 26 percent beyond WES or WGS.¹⁶ One clinical laboratory’s experience with a single case-matching database resulted in clinical characterization for 45 percent of candidate genes—providing additional diagnostic information for 477 individuals whose mutations were previously unknown, of uncertain significance, or incorrectly classified.¹⁷

Complicating factors

Even when tests are accessible and well-understood, a diagnosis may not be forthcoming. Often, this comes as a result of interpretation challenges arising from a lack of diversity in genomic research and databases, which are often biased toward individuals of European ancestry.¹⁸ Variants more common in non-European populations are less likely to be classified or yield a definitive diagnosis.¹⁹

However, new efforts are currently underway to increase the diversity of datasets and reference genomes with the goal of ensuring better precision health care for all people.

Despite great strides in molecular diagnostics—and their affordability—many patients are never able to pinpoint their syndromes without a name, let alone pursue effective treatment. Although clinical labs may be limited in their ability to alleviate financial or logistical barriers to high-tech molecular testing, there is a vital role to play in collaborating with patients’ primary care providers to determine appropriate test ordering, interpretation, and next steps. With this support, patients in search of a diagnosis may find that the answers they need are finally within reach.

References:

1. Nguengang Wakap S et al. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet. 2020;28(2):165–173. doi:10.1038/s41431-019-0508-0.
2. The Lancet Global Health. The landscape for rare diseases in 2024. Lancet Glob Health. 2024;12(3):e341. doi:10.1016/S2214-109X(24)00056-1.
3. Graessner H et al. Solving the unsolved rare diseases in Europe. Eur J Hum Genet. 2021;29(9):1319–1320. doi:10.1038/s41431-021-00924-8.
4. Adeyi OA. Pathology services in developing countries—the West African experience. Arch Pathol Lab Med. 2011;135(2):183–186. doi:10.5858/2008-0432-CCR.1.
5. Williams JR et al. Precision medicine: familiarity, perceived health drivers, and genetic testing considerations across health literacy levels in a diverse sample. J Genet Couns. 2018;28:59–69. doi:10.1007/s10897-018-0291-z.
6. Saulsberry K, Terry SF. The need to build trust: a perspective on disparities in genetic testing. Genet Test Mol Biomarkers. 2013;17(9):647–648. doi:10.1089/gtmb.2013.1548.
7. “Profile of Rare Diseases.” In Rare Diseases and Orphan Products: Accelerating Research and Development, eds. Field MJ, Boat TF, 41–72. Washington, DC: The National Academies Press, 2010.
8. Manrai AK et al. Genetic misdiagnoses and the potential for health disparities. N Engl J Med. 2016;375(7):655–665. doi:10.1056/NEJMsa1507092.
9. Shaw T et al. Missed diagnosis or misdiagnosis: common pitfalls in genetic testing. Singapore Med J. 2023;64(1):67–73. doi:10.4103/singaporemedj.SMJ-2021-467.
10. Ibanez MB 4th et al. Stargardt misdiagnosis: how ocular genetics helps. Am J Med Genet A. 2021;185(3):814–819. doi:10.1002/ajmg.a.62045.
11. Van Dijk FS et al. TNXB-Related Classical-Like Ehlers-Danlos Syndrome. GeneReviews. September 15, 2022. https://www.ncbi.nlm.nih.gov/books/NBK584019/#tnxb-eds.Molecular_Genetics.
12. Smedley D et al. 100,000 Genomes pilot on rare-disease diagnosis in health care — preliminary report. N Engl J Med. 2021;385(20):1868–1880. doi:10.1056/NEJMoa2035790.
13. Whole genome sequencing price and trends 2024. 3billion. December 18, 2023. https://3billion.io/blog/whole-genome-sequencing-price-and-trends-2024.
14. Reuter CM et al. Yield of whole exome sequencing in undiagnosed patients facing insurance coverage barriers to genetic testing. J Genet Couns. 2019;28(6):1107–1118. doi:10.1002/jgc4.1161.
15. Dimmock D et al. Project Baby Bear: rapid precision care incorporating rWGS in 5 California children’s hospitals demonstrates improved clinical outcomes and reduced costs of care. Am J Hum Genet. 2021;108(7):1231–1238. doi:10.1016/j.ajhg.2021.05.008.
16. Marwaha S et al. A guide for the diagnosis of rare and undiagnosed disease: beyond the exome. Genome Med. 2022;14(1):23. doi:10.1186/s13073-022-01026-w.
17. Towne MC et al. Diagnostic testing laboratories are valuable partners for disease gene discovery: 5-year experience with GeneMatcher. Hum Mutat. 2022;43(6):772–781. doi:10.1002/humu.24342.
18. Petrovski S, Goldstein DB. Unequal representation of genetic variation across ancestry groups creates healthcare inequality in the application of precision medicine. Genome Biol. 2016;17(1):157. doi:10.1186/s13059-016-1016-y.
19. Florentine MM et al. Racial and ethnic disparities in diagnostic efficacy of comprehensive genetic testing for sensorineural hearing loss. Hum Genet. 2022;141(3–4):495–504. doi:10.1007/s00439-021-02338-4.