Characteristics of undiagnosed diseases network applicants: implications for referring providers

Breaking barriers: fostering equitable access to pediatric genomics through innovative care models and technologies

The integration of genomic medicine into pediatric clinical practice is a critical need that remains largely unmet, especially in socioeconomically challenged and rural areas where healthcare disparities are most pronounced. This review seeks to summarize the barriers responsible for delayed diagnosis and treatment, and examines diverse care models, technological innovations, and strategies for dissemination and implementation aimed at addressing the evolving genomic needs of pediatric populations. Through a comprehensive review of the literature, we explore proposed methodologies to bridge this gap in pediatric healthcare, with a specific emphasis on understanding and speeding implementation approaches and technologies to mitigate disparities in underserved populations, including rural and marginalized communities. There are both external and internal factors to consider in demographic and social determinants when evaluating patient access. To address these barriers, potential solutions include telegenetic services, alternative care delivery models, pediatric subspecialist expansion, and non-genetic provider education. By improving access to pediatric genomic services, therapeutic interventions will also be more available to all pediatric patients. IMPACT STATEMENT: Genomic testing has clinical utility in pediatric populations but access for people from diverse demographic and social-economic groups is problematic. Understanding barriers responsible for delayed genetic diagnosis and treatment in pediatric populations will improve reach, adoption, implementation, and maintenance of genomic medicine in pediatric healthcare context. Innovative care models, adaptation of appropriate technologies, and strategies aimed at addressing pediatric genomic needs are needed.

The Brain Gene Registry: a data snapshot

Monogenic disorders account for a large proportion of population-attributable risk for neurodevelopmental disabilities. However, the data necessary to infer a causal relationship between a given genetic variant and a particular neurodevelopmental disorder is often lacking. Recognizing this scientific roadblock, 13 Intellectual and Developmental Disabilities Research Centers (IDDRCs) formed a consortium to create the Brain Gene Registry (BGR), a repository pairing clinical genetic data with phenotypic data from participants with variants in putative brain genes. Phenotypic profiles are assembled from the electronic health record (EHR) and a battery of remotely administered standardized assessments collectively referred to as the Rapid Neurobehavioral Assessment Protocol (RNAP), which include cognitive, neurologic, and neuropsychiatric assessments, as well as assessments for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Co-enrollment of BGR participants in the Clinical Genome Resource's (ClinGen's) GenomeConnect enables display of variant information in ClinVar. The BGR currently contains data on 479 participants who are 55% male, 6% Asian, 6% Black or African American, 76% white, and 12% Hispanic/Latine. Over 200 genes are represented in the BGR, with 12 or more participants harboring variants in each of these genes: CACNA1A, DNMT3A, SLC6A1, SETD5, and MYT1L. More than 30% of variants are de novo and 43% are classified as variants of uncertain significance (VUSs). Mean standard scores on cognitive or developmental screens are below average for the BGR cohort. EHR data reveal developmental delay as the earliest and most common diagnosis in this sample, followed by speech and language disorders, ASD, and ADHD. BGR data has already been used to accelerate gene-disease validity curation of 36 genes evaluated by ClinGen's BGR Intellectual Disability (ID)-Autism (ASD) Gene Curation Expert Panel. In summary, the BGR is a resource for use by stakeholders interested in advancing translational research for brain genes and continues to recruit participants with clinically reported variants to establish a rich and well-characterized national resource to promote research on neurodevelopmental disorders.

International Undiagnosed Diseases Programs (UDPs): components and outcomes

Over the last 15 years, Undiagnosed Diseases Programs have emerged to address the significant number of individuals with suspected but undiagnosed rare genetic diseases, integrating research and clinical care to optimize diagnostic outcomes. This narrative review summarizes the published literature surrounding Undiagnosed Diseases Programs worldwide, including thirteen studies that evaluate outcomes and two commentary papers. Commonalities in the diagnostic and research process of Undiagnosed Diseases Programs are explored through an appraisal of available literature. This exploration allowed for an assessment of the strengths and limitations of each of the six common steps, namely enrollment, comprehensive clinical phenotyping, research diagnostics, data sharing and matchmaking, results, and follow-up. Current literature highlights the potential utility of Undiagnosed Diseases Programs in research diagnostics. Since participants have often had extensive previous genetic studies, research pipelines allow for diagnostic approaches beyond exome or whole genome sequencing, through reanalysis using research-grade bioinformatics tools and multi-omics technologies. The overall diagnostic yield is presented by study, since different selection criteria at enrollment and reporting processes make comparisons challenging and not particularly informative. Nonetheless, diagnostic yield in an undiagnosed cohort reflects the potential of an Undiagnosed Diseases Program. Further comparisons and exploration of the outcomes of Undiagnosed Diseases Programs worldwide will allow for the development and improvement of the diagnostic and research process and in turn improve the value and utility of an Undiagnosed Diseases Program.

Genomics Research with Undiagnosed Children: Ethical Challenges at the Boundaries of Research and Clinical Care

OBJECTIVE

To explore the perspectives of parents of undiagnosed children enrolled in genomic diagnosis research regarding their motivations for enrolling their children, their understanding of the potential burdens and benefits, and the extent to which their experiences ultimately aligned with or diverged from their original expectations.

STUDY DESIGN

In-depth interviews were conducted with parents, audio-recorded and transcribed. A structured codebook was applied to each transcript, after which iterative memoing was used to identify themes.

RESULTS

Fifty-four parents participated, including 17 (31.5%) whose child received a diagnosis through research. Themes describing parents' expectations and experiences of genomic diagnosis research included (1) the extent to which parents' motivations for participation focused on their hope that it would directly benefit their child, (2) the ways in which parents' frustrations regarding the research process confused the dual clinical and research goals of their participation, and (3) the limited clinical benefits parents ultimately experienced for their children.

CONCLUSIONS

Our results suggest that parents of undiagnosed children seeking enrollment in genomic diagnosis research are at risk of a form of therapeutic misconception-in this case, diagnostic misconception. These findings indicate the need to examine the processes and procedures associated with this research to communicate appropriately and balance the potential burdens and benefits of study participation.

Advancing Understanding of Inequities in Rare Disease Genomics

PURPOSE

Advances in genomic research have facilitated rare disease diagnosis for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other health care contexts. Quantifying and describing inequities in genetic diagnostic yield is inherently challenging due to barriers to both clinical and research genetic testing. We therefore present an implementation protocol developed to expand access to our rare disease genomic research study and to further understand existing inequities.

METHODS AND FINDINGS

The Rare Genomes Project (RGP) at the Broad Institute of MIT and Harvard offers research genome sequencing to individuals with rare disease who remain genetically undiagnosed through direct interaction with the individual or family. This presents an opportunity for diagnosis beyond the clinical context, thus eliminating many barriers to access. An initial goal of RGP was to equalize access to genomic sequencing by decoupling testing access from proximity to a major medical center and physician referral. However, study participants over the initial 3 years of this project were predominantly white and well resourced. To further understand and address the lack of diversity within RGP, we developed a novel protocol embedded within the larger RGP study, in an approach informed by an implementation science framework. The aims of this protocol were: (1) to diversify recruitment and enrollment within RGP; (2) understand the process and context of implementing genomic medicine for rare disease diagnosis; and (3) investigate the value of a diagnosis for underserved populations.

IMPLICATIONS

Improved understanding of existing inequities and potential strategies to address them are needed to advance equity in rare disease genetic diagnosis and research. In addition to the moral imperative of equity in genomic medicine, this approach is critical in order to fully understand the genomic underpinnings of rare disease.

Demographic Characteristics Associated With Perceptions of Personal Utility in Genetic and Genomic Testing: A Systematic Review

Importance

The expansion of genetic and genomic testing in health care has led to recognition that these tests provide personal as well as clinical utility to patients and families. However, available systematic reviews on this topic have not reported the demographic backgrounds of participants in studies of personal utility, leaving generalizability unclear.

Objective

To determine the demographic characteristics of participants in studies examining the personal utility of genetic and genomic testing in health care.

Evidence Review

For this systematic review, we utilized and updated the results of a highly cited 2017 systematic review on the personal utility of genetics and genomics, which identified relevant articles published between January 1, 2003, and August 4, 2016. We also used the original methods to update this bibliography with literature published subsequently up to January 1, 2022. Studies were screened for eligibility by 2 independent reviewers. Eligible studies reported empirical data on the perspectives of patients, family members, and/or the general public in the US on the personal utility of any type of health-related genetic or genomic test. We utilized a standardized codebook to extract study and participant characteristics. We summarized demographic characteristics descriptively across all studies and by subgroup based on study and participant characteristics.

Findings

We included 52 studies with 13 251 eligible participants. Sex or gender was the most frequently reported demographic characteristic (48 studies [92.3%]), followed by race and ethnicity (40 studies [76.9%]), education (38 studies [73.1%]), and income (26 studies [50.0%]). Across studies, participants disproportionately were women or female (mean [SD], 70.8% [20.5%]), were White (mean [SD], 76.1% [22.0%]), had a college degree or higher (mean [SD], 64.5% [19.9%]), and reported income above the US median (mean [SD], 67.4% [19.2%]). Examination of subgroups of results by study and participant characteristics evidenced only small shifts in demographic characteristics.

Conclusions and Relevance

This systematic review examined the demographic characteristics of individual participants in studies of the personal utility of health-related genetic and genomic testing in the US. The results suggest that participants in these studies were disproportionately White, college-educated women with above-average income. Understanding the perspectives of more diverse individuals regarding the personal utility of genetic and genomic testing may inform barriers to research recruitment and uptake of clinical testing in currently underrepresented populations.

Advancing Understanding of Inequities in Rare Disease Genomics

Purpose

Advances in genomic research have led to the diagnosis of rare, early-onset diseases for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other healthcare contexts. Even quantifying and describing inequities in genetic diagnostic yield is challenging due to variation in referrals to clinical genetics practices and other barriers to clinical genetic testing.

Methods

The Rare Genomes Project (RGP) at the Broad Institute of MIT and Harvard offers research genome sequencing to individuals with rare disease who remain genetically undiagnosed through direct interaction with the individual or family. This presents an opportunity for diagnosis beyond the clinical context, thus eliminating many barriers to access.

Findings

An initial goal of RGP was to equalize access to genomic sequencing by decoupling testing access from proximity to a major medical center and physician referral. However, our study participants are overwhelmingly non-disadvantaged, as evidenced by their access to specialist care and genetic testing prior to RGP enrollment, and are also predominantly white.

Implications

We therefore describe our novel initiative to diversify RGP enrollment in order to advance equity in rare disease genetic diagnosis and research. In addition to the moral imperative of medical equity, this is also critical in order to fully understand the genomic underpinnings of rare disease. We utilize a mixed methods approach to understand the priorities and values of underrepresented communities, existing disparities, and the obstacles to addressing them: all of which is necessary to promote equity in future genomic medicine initiatives.

Toward representative genomic research: the children's rare disease cohorts experience

Background

Due to racial, cultural, and linguistic marginalization, some populations experience disproportionate barriers to genetic testing in both clinical and research settings. It is difficult to track such disparities due to non-inclusive self-reported race and ethnicity categories within the electronic health record (EHR). Inclusion and access for all populations is critical to achieve health equity and to capture the full spectrum of rare genetic disease.

Objective

We aimed to create revised race and ethnicity categories. Additionally, we identified racial and ethnic under-representation amongst three cohorts: (1) the general Boston Children's Hospital patient population (general BCH), (2) the BCH patient population that underwent clinical genomic testing (clinical sequencing), and (3) Children's Rare Disease Cohort (CRDC) research initiative participants.

Design and Methods

Race and ethnicity data were collected from the EHRs of the general BCH, clinical sequencing, and CRDC cohorts. We constructed a single comprehensive set of race and ethnicity categories. EHR-based race and ethnicity variables were mapped within each cohort to the revised categories. Then, the numbers of patients within each revised race and ethnicity category were compared across cohorts.

Results

There was a significantly lower percentage of Black or African American/African, non-Hispanic/non-Latine individuals in the CRDC cohort compared with the general BCH cohort, but there was no statistically significant difference between the CRDC and the clinical sequencing cohorts. There was a significantly lower percentage of multi-racial, Hispanic/Latine individuals in the CRDC cohort than the clinical sequencing cohort. White, non-Hispanic/non-Latine individuals were over-represented in the CRDC compared to the two other groups.

Conclusion

We highlight underrepresentation of certain racial and ethnic populations in sequencing cohorts compared to the general hospital population. We propose a range of measures to address these disparities, to strive for equitable future precision medicine-based clinical care and for the benefit of the whole rare disease community.

Rare diseases, common barriers: disparities in pediatric clinical genetics outcomes

BACKGROUND

Identifying a precise genetic diagnosis can improve outcomes for individuals with rare disease, though the resources required to do so may impede access and exacerbate healthcare disparities leading to inequitable care. Our objective was therefore to determine the effect of multiple sociodemographic factors on the yield of the diagnostic evaluation for genetics outpatients.

METHODS

This is a retrospective cohort study from 2017 to 2019 of outpatient genetics referrals at a pediatric academic tertiary care center. Exposures included: primary language, insurance type, and neighborhood resources (via the Childhood Opportunity Index, COI). The primary outcome was identification of a genetic diagnosis within 2 years of the initial clinic visit.

RESULTS

COI quintile was not significantly associated with the odds of diagnosis but was significantly associated with clinic attendance, with lower neighborhood resources leading to incomplete referrals. Limited English proficiency was associated with a higher odds of diagnosis, though at an older age. Public insurance was associated with increased access to genetic testing.

CONCLUSIONS

Lower neighborhood resources are negatively associated with clinic attendance. Our findings further suggest delays in care and a referral bias for more severe phenotypes among families with limited English proficiency. Improved access to clinical genetics is needed to improve diagnostic equity.

IMPACT

The resources required to identify a genetic diagnosis may impede access and exacerbate healthcare disparities leading to inequitable care. In an analysis of pediatric outpatient genetics referrals, we observed a significant association between neighborhood resources and clinic attendance but not diagnostic yield for those attending, and a higher diagnostic yield for families with limited English proficiency, suggesting referral bias for more severe phenotypes. Thus, the primary barrier to finding a genetic diagnosis was initiation of care, not the ensuing diagnostic odyssey. Further research efforts should be directed at increasing access to clinical genetics evaluations for children with rare disease.

Beyond race: Recruitment of diverse participants in clinical genomics research for rare disease

Purpose: Despite recent attention to increasing diversity in clinical genomics research, researchers still struggle to recruit participants from varied sociodemographic backgrounds. We examined the experiences of parents from diverse backgrounds with enrolling their children in clinical genomics research on rare diseases. We explored the barriers and facilitators parents encountered and possible impacts of sociodemographic factors on their access to research.

Methods: We utilized semi-structured interviews with parents of children participating in the Undiagnosed Diseases Network. Interview data were analyzed using comparative content analysis.

Results: We interviewed 13 Hispanic, 11 non-Hispanic White, four Asian, and two biracial parents. Participants discussed different pathways to clinical genomics research for rare disease as well as how sociodemographic factors shaped families’ access. Themes focused on variation in: 1) reliance on providers to access research; 2) cultural norms around health communication; 3) the role of social capital in streamlining access; and 4) the importance of language-concordant research engagement.

Conclusion: Our findings suggest that variables beyond race/ethnicity may influence access in clinical genomics research. Future efforts to diversify research participation should consider utilizing varied recruitment strategies to reach participants with diverse sociodemographic characteristics.

Geographic Upon Noninfectious Diseases Accounting for Fever of Unknown Origin (FUO): A Systematic Review and Meta-analysis

Background

Diagnostic outcomes for fever of unknown origin (FUO) remain with notable numbers of undiagnosed cases. A recent systemic review and meta-analysis of studies reported geographic variation in FUO-related infectious diseases. Whether geography influences types of FUO noninfectious diagnoses deserves examination.

Methods

Medline (PubMed), Embase, Scopus, and Web of Science databases were searched systematically using medical subject headings published from January 1, 1997, to March 31, 2021. Prospective clinical studies investigating participants meeting adult FUO defining criteria were selected if they assessed final diagnoses. Meta-analyses were based on the random-effects model according to World Health Organization (WHO) geographical regions.

Results

Nineteen studies with significant heterogeneity were analyzed, totaling 2,667 participants. Noninfectious inflammatory disorders had a pooled estimate at 20.0% (95%CI: 17.0-23.0%). Undiagnosed illness had a pooled estimate of 20.0% (95%CI: 14.0-26.0%). The pooled estimate for cancer was 15.0% (95%CI: 12.0-18.0%). Miscellaneous conditions had a pooled estimate of 6.0% (95%CI: 4.0-8.0%). Noninfectious inflammatory disorders and miscellaneous conditions were most prevalent in the Western Pacific region with a 27.0% pooled estimate (95%CI: 20.0-34.0%) and 9.0% (95%CI: 7.0-11.0%), respectively. The highest pooled estimated for cancer was in the Eastern Mediterranean region at 25.0% (95%CI: 18.0-32.0%). Adult-onset Still’s disease (114 [58.5%]), systemic lupus (52 [26.7%]), and giant-cell arteritis (40 [68.9%]) predominated among the noninfectious inflammatory group. Lymphoma (164 [70.1%]) was the most common diagnosis in the cancer group.

Conclusions

In this systematic review and meta-analysis, noninfectious disease diagnostic outcomes varied among WHO-defined geographies. Evaluation of FUO should consider local variations in disease prevalence.

Diagnostic journeys: characterization of patients and diagnostic outcomes from an academic second opinion clinic

OBJECTIVES

Diagnostic programs and second opinion clinics have grown and evolved in the recent years to help patients with rare, puzzling, and complex conditions who often suffer prolonged diagnostic journeys, but there is a paucity of literature on the clinical characteristics of these patients and the efficacy of these diagnostic programs. This study aims to characterize the diagnostic journey, case features, and diagnostic outcomes of patients referred to a team-based second opinion clinic at Stanford.

METHODS

Retrospective chart review was performed for 237 patients evaluated for diagnostic second opinion in the Stanford Consultative Medicine Clinic over a 5 year period. Descriptive case features and diagnostic outcomes were assessed, and correlation between the two was analyzed.

RESULTS

Sixty-three percent of our patients were women. 49% of patients had a potential precipitating event within about a month prior to the start of their illness, such as medication change, infection, or medical procedure. A single clear diagnosis was determined in 33% of cases, whereas the remaining cases were assessed to have multifactorial contributors/diagnoses (20%) or remained unclear despite extensive evaluation (47%). Shorter duration of illness, fewer prior specialties seen, and single chief symptom were associated with higher likelihood of achieving a single clear diagnosis.

CONCLUSIONS

A single-site academic consultative service can offer additional diagnostic insights for about half of all patients evaluated for puzzling conditions. Better understanding of the clinical patterns and patient experiences gained from this study helps inform strategies to shorten their diagnostic odysseys.

Congenital anomalies and genetic disorders in neonates and infants: a single-center observational cohort study

Neonates with genetic disorders or congenital anomalies (CA) contribute considerably to morbidity and mortality in neonatal intensive care units (NICUs). The objective of this study is to study the prevalence of genetic disorders in an academic level IV NICU. We retrospective collected and analyzed both clinical and genetic data of all 1444 infants admitted to the NICU of the Radboudumc (October 2013 to October 2015). Data were collected until infants reached at least 2 years of age. A total of 13% (194/1444) of the patients were genetically tested, and 32% (461/1444) had a CA. A total of 37% (72/194) had a laboratory-confirmed genetic diagnosis. In 53%, the diagnosis was made post-neonatally (median age = 209 days) using assays including exome sequencing. Exactly 63% (291/461) of the patients with CA, however, never received genetic testing, despite being clinically similar those who did.Conclusions: Genetic disorders were suspected in 13% of the cohort, but only confirmed in 5%. Most received their genetic diagnosis in the post-neonatal period. Extrapolation of the diagnostic yield suggests that up to 6% of our cohort may have remained genetically undiagnosed. Our data show the need to improve genetic care in the NICU for more inclusive, earlier, and faster genetic diagnosis to enable tailored management. What is Known: • Genetic disorders are suspected in many neonates but only genetically confirmed in a minority. • The presence of a genetic disorder can be easily missed and will often lead to a diagnostic odyssey requiring extensive evaluations, both clinically and genetically. What is New: • Different aspects of the clinical features and uptake of genetic test in a NICU cohort. • The need to improve genetic care in the NICU for more inclusive, earlier, and faster genetic diagnosis to enable tailored management.

Patients as Partners in Rare Disease Diagnosis and Research

There is great value in understanding the patient perspective in rare disease diagnosis and research, and in partnering actively with patients and their families throughout the process. Meaningful and respectful interaction between patients and researchers leads to learning on both sides, and ultimately, to better research outcomes. Researchers can help patients understand how research is conducted and what the latest advances and perceived gaps in research are, and patients, who have direct experience living with their health conditions, can impart to researchers what is most important to them. We describe our engagement with patients in the Undiagnosed Diseases Network (UDN) program, as well as the lessons we have learned to date. In the UDN, patients have been instrumental in bringing meaning to the work of clinicians and researchers, building patient communities, making the network aware of unmet patient needs, advocating for additional research funding, and disseminating UDN research findings. Although patient engagement in the UDN has already had a significant positive impact on our work, we continue to strive to involve patients earlier in the process, in the research design itself, and in addressing power dynamics that may arise between clinicians, researchers, and patients.

Estimating the class prior for positive and unlabelled data via logistic regression

In the paper, we revisit the problem of class prior probability estimation with positive and unlabelled data gathered in a single-sample scenario. The task is important as it is known that in positive unlabelled setting, a classifier can be successfully learned if the class prior is available. We show that without additional assumptions, class prior probability is not identifiable and thus the existing non-parametric estimators are necessarily biased in general if extra assumptions are not imposed. The magnitude of their bias is also investigated. The problem becomes identifiable when the probabilistic structure satisfies mild semi-parametric assumptions. Consequently, we propose a method based on a logistic fit and a concave minorization of its (non-concave) log-likelihood. The experiments conducted on artificial and benchmark datasets as well as on a large clinical database MIMIC indicate that the estimation errors for the proposed method are usually lower than for its competitors and that it is robust against departures from logistic settings.

Machine Learning of Patient Characteristics to Predict Admission Outcomes in the Undiagnosed Diseases Network

IMPORTANCE

The Undiagnosed Diseases Network (UDN) is a national network that evaluates individual patients whose signs and symptoms have been refractory to diagnosis. Providing reliable estimates of admission outcomes may assist clinical evaluators to distinguish, prioritize, and accelerate admission to the UDN for patients with undiagnosed diseases.

OBJECTIVE

To develop computational models that effectively predict admission outcomes for applicants seeking UDN evaluation and to rank the applications based on the likelihood of patient admission to the UDN.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study included all applications submitted to the UDN from July 2014 to June 2019, with 1209 applications accepted and 1212 applications not accepted. The main inclusion criterion was an undiagnosed condition despite thorough evaluation by a health care professional; the main exclusion criteria were a diagnosis that explained the objective findings or a review of the records that suggested a diagnosis. A classifier was trained using information extracted from application forms, referral letters from health care professionals, and semantic similarity between referral letters and textual description of known mendelian disorders. The admission labels were provided by the case review committee of the UDN. In addition to retrospective analysis, the classifier was prospectively tested on another 288 applications that were not evaluated at the time of classifier development.

MAIN OUTCOMES AND MEASURES

The primary outcomes were whether a patient was accepted or not accepted to the UDN and application order ranked based on likelihood of admission. The performance of the classifier was assessed by comparing its predictions against the UDN admission outcomes and by measuring improvement in the mean processing time for accepted applications.

RESULTS

The best classifier obtained sensitivity of 0.843, specificity of 0.738, and area under the receiver operating characteristic curve of 0.844 for predicting admission outcomes among 1212 accepted and 1210 not accepted applications. In addition, the classifier can decrease the current mean (SD) UDN processing time for accepted applications from 3.29 (3.17) months to 1.05 (3.82) months (68% improvement) by ordering applications based on their likelihood of acceptance.

CONCLUSIONS AND RELEVANCE

A classification system was developed that may assist clinical evaluators to distinguish, prioritize, and accelerate admission to the UDN for patients with undiagnosed diseases. Accelerating the admission process may improve the diagnostic journeys for these patients and serve as a model for partial automation of triaging or referral for other resource-constrained applications. Such classification models make explicit some of the considerations that currently inform the use of whole-genome sequencing for undiagnosed disease and thereby invite a broader discussion in the clinical genetics community.

The influence of social determinants of health on the genetic diagnostic odyssey: who remains undiagnosed, why, and to what effect?

Although Mendelian genetic disorders are individually rare, they are collectively more common and contribute disproportionately to pediatric morbidity and mortality. Remarkable advances in the past decade have led to identification of the precise genetic variants responsible for many of these conditions. Confirming the molecular diagnosis through genetic testing allows for individualized treatment plans in addition to ending the diagnostic odyssey, which not only halts further unnecessary testing but may also result in immense psychological benefit, leading to improved quality of life. However, ensuring equitable application of these advances in genomic technology has been challenging. Though prior studies have revealed disparities in testing for genetic predisposition to cancer in adults, little is known about the prevalence and nature of disparities in diagnostic testing in the pediatric rare disease population. While it seems logical that those with impaired access to healthcare would be less likely to receive the genetic testing needed to end their odyssey, few studies have addressed this question directly and the potential impact on health outcomes. This review synthesizes the available evidence regarding disparities in pediatric genetic diagnosis, defining the need for further, prospective studies with the ultimate goal of delivering precision medicine to all who stand to benefit. IMPACT: Social determinants of health are known to contribute to inequality in outcomes, though the impact on pediatric rare disease patients is not fully understood. Diagnostic genetic testing is a powerful tool, though it may not be available to all in need. This article represents the first effort, to our knowledge, to evaluate the existing literature regarding disparities in genetic testing for pediatric rare disease diagnosis and identify gaps in care.

Theoretical and clinical disease and the biostatistical theory

Although concepts of disease have received much scrutiny, the benefits of distinguishing between theoretical and clinical disease-and what is meant by those terms-may not be as readily apparent. One way of characterizing the distinction between theoretical and clinical conceptions of disease is by relying on Boorse's biostatistical theory (BST) for a conception of theoretical disease. Clinical disease could then be defined as theoretical disease that is diagnosed. Explicating this distinction provides a useful extension of the BST. The benefits of this approach are clearly and non-normatively demarcating disease from non-disease, while allowing for values and purpose to determine what criteria are used in clinical practice to represent a disease's underlying dysfunction. Through discussion of a variety of medical conditions, including polycystic ovary syndrome and type 2 diabetes mellitus, I explore how the relationship between BST-based theoretical and clinical disease could make sense of various features of clinical practice and medical theory. It could do this by lending focus to a nuanced understanding of the pathophysiological defects present in disease and the means by which they are assessed. This could contribute to making sense of revised nosologies and diagnostic criteria.

The undiagnosed diseases program: Approach to diagnosis

Undiagnosed and rare conditions are collectively common and affect millions of people worldwide. The NIH Undiagnosed Diseases Program (UDP) strives to achieve both a comprehensive diagnosis and a better understanding of the mechanisms of disease for many of these individuals. Through the careful review of records, a well-orchestrated inpatient evaluation, genomic sequencing and testing, and with the use of emerging strategies such as matchmaking programs, the UDP succeeds nearly 30 percent of the time for these highly selective cases. Although the UDP process is built on a unique set of resources, case examples demonstrate steps genetic professionals can take, in both clinical and research settings, to arrive at a diagnosis for their most challenging cases.

Understanding access to genomics in an ethnically diverse south Florida population: A comparison of demographics in odyssey and rapid whole genome sequencing programs

Advances in genomic medicine have evolved to include rapid whole genome sequencing (rWGS) in pediatric intensive care settings. Traditionally, genetic testing was conducted in outpatient clinics, with stepwise genetic testing occurring over several years. This delayed the time to diagnosis, making it more difficult to include underrepresented groups, such as those who identify as Black and Latinx. National genetic sequencing programs have also struggled to engage these participants in their studies, leading to a significant disparity in access to new genetic technologies. The purpose of our study was to compare the demographic characteristics of families enrolled in both an Odyssey Program (N = 46), defined as outpatients in the Genetics Clinic who have had prior genetic testing, and a newly implemented rWGS (N = 52) sequencing program. Despite living in a large, ethnically diverse city, our results indicated that parents in the Odyssey program differed significantly from parents in the rWGS program in level of education, family income, and insurance status. For example, 71.5% of parents in the diagnostic Odyssey program had a college or advanced degree, whereas 42% of parents in the rWGS program had this level of education. Family income and insurance also differed, with 48.6% of families in the Odyssey program earning $100,000 or more versus 28.2% in rWGS; 56% of parents in the Odyssey program had private insurance with 26% on Medicaid whereas only 23% of parents in rWGS had private insurance, with the vast majority of children on Medicaid (69%). Thus, our Odyssey program illustrates some of the common pitfalls in implementing genomic testing in an ethnically diverse community, including lack of referrals, travel to outpatient visits, and a cultural mismatch with providers. The successful enrollment of underrepresented groups in the rWGS program demonstrates that given the opportunity to participate in genetic testing, families are interested and aware of the potential benefits of this testing for their child. As genomic sequencing transitions from outpatient to inpatient settings, an opportunity arises to close the health disparity gap. Recommendations for implementing rWGS in pediatric, intensive care settings that address the common barriers faced by underrepresented families are discussed.

Epigenetic Inheritance Underlying Pulmonary Arterial Hypertension

In pulmonary arterial hypertension (PAH), the Warburg effect (glycolytic shift) and mitochondrial fission are determinants of phenotype alterations characteristic of the disease, such as proliferation, apoptosis resistance, migration, endothelial-mesenchymal transition, and extracellular matrix stiffness. Current therapies, focusing largely on vasodilation and antithrombotic protection, do not restore these aberrant phenotypes suggesting that additional pathways need be targeted. The multifactorial nature of PAH suggests epigenetic changes as potential determinants of vascular remodeling. Transgenerational epigenetic changes induced by hypoxia can result in permanent changes early in fetal development increasing PAH risk in adulthood. Unlike genetic mutations, epigenetic changes are pharmacologically reversible, making them an attractive target as therapeutic strategies for PAH. This review offers a landscape of the most current clinical, epigenetic-sensitive changes contributing to PAH vascular remodeling both in early and later life, with a focus on a network medicine strategy. Furthermore, we discuss the importance of the application (from morphogenesis to disease onset) of molecular network-based algorithms to dissect PAH molecular pathobiology. Additionally, we suggest an integrated network-based program for clinical disease gene discovery that may reveal novel biomarkers and novel disease targets, thus offering a truly innovative path toward redefining and treating PAH, as well as facilitating the trajectory of a comprehensive precision medicine approach to PAH.