An algorithm to identify patients aged 0-3 with rare genetic disorders.

BACKGROUND: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders. RESULTS: Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy. CONCLUSIONS: The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

Digenic Inheritance in Rare Disorders and Mitochondrial Disease-Crossing the Frontier to a More Comprehensive Understanding of Etiology.

Our understanding of rare disease genetics has been shaped by a monogenic disease model. While the traditional monogenic disease model has been successful in identifying numerous disease-associated genes and significantly enlarged our knowledge in the field of human genetics, it has limitations in explaining phenomena like phenotypic variability and reduced penetrance. Widening the perspective beyond Mendelian inheritance has the potential to enable a better understanding of disease complexity in rare disorders. Digenic inheritance is the simplest instance of a non-Mendelian disorder, characterized by the functional interplay of variants in two disease-contributing genes. Known digenic disease causes show a range of pathomechanisms underlying digenic interplay, including direct and indirect gene product interactions as well as epigenetic modifications. This review aims to systematically explore the background of digenic inheritance in rare disorders, the approaches and challenges when investigating digenic inheritance, and the current evidence for digenic inheritance in mitochondrial disorders.

Rare genetic disorders that impair parathyroid hormone synthesis, secretion, or bioactivity provide insights into the diagnostic utility of different parathyroid hormone assays.

PURPOSE OF REVIEW: Parathyroid hormone (PTH) is the major peptide hormone regulator of blood calcium homeostasis. Abnormal PTH levels can be observed in patients with various congenital and acquired disorders, including chronic kidney disease (CKD). This review will focus on rare human diseases caused by PTH mutations that have provided insights into the regulation of PTH synthesis and secretion as well as the diagnostic utility of different PTH assays. RECENT FINDINGS: Over the past years, numerous diseases affecting calcium and phosphate homeostasis have been defined at the molecular level that are responsible for reduced or increased serum PTH levels. The underlying genetic mutations impair parathyroid gland development, involve the PTH gene itself, or alter function of the calcium-sensing receptor (CaSR) or its downstream signaling partners that contribute to regulation of PTH synthesis or secretion. Mutations in the pre sequence of the mature PTH peptide can, for instance, impair hormone synthesis or intracellular processing, while amino acid substitutions affecting the secreted PTH(1-84) impair PTH receptor (PTH1R) activation, or cause defective cleavage of the pro-sequence and thus secretion of a pro- PTH with much reduced biological activity. Mutations affecting the secreted hormone can alter detection by different PTH assays, thus requiring detailed knowledge of the utilized diagnostic test. SUMMARY: Rare diseases affecting PTH synthesis and secretion have offered helpful insights into parathyroid biology and the diagnostic utility of commonly used PTH assays, which may have implications for the interpretation of PTH measurements in more common disorders such as CKD.

Monkeypox Outbreak 2022, from a Rare Disease to Global Health Emergence: Implications for Travellers.

Monkeypox (mpox), a zoonotic disease caused by the monkeypox virus (MPXV), poses a significant public health threat with the potential for global dissemination beyond its endemic regions in Central and West Africa. This study explores the multifaceted aspects of monkeypox, covering its epidemiology, genomics, travel-related spread, mass gathering implications, and economic consequences. Epidemiologically, mpox exhibits distinct patterns, with variations in age and gender susceptibility. Severe cases can arise in immunocompromised individuals, underscoring the importance of understanding the factors contributing to its transmission. Genomic analysis of MPXV highlights its evolutionary relationship with the variola virus and vaccinia virus. Different MPXV clades exhibit varying levels of virulence and transmission potential, with Clade I associated with higher mortality rates. Moreover, the role of recombination in MPXV evolution remains a subject of interest, with implications for understanding its genetic diversity. Travel and mass gatherings play a pivotal role in the spread of monkeypox. The ease of international travel and increasing globalization have led to outbreaks beyond African borders. The economic ramifications of mpox outbreaks extend beyond public health. Direct treatment costs, productivity losses, and resource-intensive control efforts can strain healthcare systems and economies. While vaccination and mitigation strategies have proven effective, the cost-effectiveness of routine vaccination in non-endemic countries remains a subject of debate. This study emphasizes the role of travel, mass gatherings, and genomics in its spread and underscores the economic impacts on affected regions. Enhancing surveillance, vaccination strategies, and public health measures are essential in controlling this emerging infectious disease.

Drug development blossoms for rare, fatal bone disease.

Five drugs are now approved or in trials for genetic condition that triggers misplaced bone growth.

Diagnostic yield of exome and genome sequencing after non-diagnostic multi-gene panels in patients with single-system diseases.

BACKGROUND: Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. RESULTS: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). CONCLUSION: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates.

Dementia in Rare Genetic Neurodevelopmental Disorders: A Systematic Literature Review.

BACKGROUND AND OBJECTIVES: Knowledge of young-onset Alzheimer disease in adults with Down syndrome has greatly improved clinical care. However, little is known about dementia in rare genetic neurodevelopmental disorders (RGNDs). In this review, a comprehensive overview is provided of reports on dementia and cognitive/adaptive trajectories in adults with RGNDs. METHODS: A systematic literature review was conducted in Embase, Medline ALL, and PsycINFO on December 6, 2022. The protocol was registered in PROSPERO (CRD42021223041). Search terms for dementia, cognitive and adaptive functioning, and RGNDs were combined using generic terms and the Orphanet database. Study characteristics and descriptive data on genetic diagnosis, clinical and neuropathologic features, comorbidities, and diagnostic methods were extracted using a modified version of the Cochrane Data Extraction Template. RESULTS: The literature search yielded 40 publications (17 cohorts, 23 case studies) describing dementia and/or cognitive or adaptive trajectories in adults with 14 different RGNDs. Dementia was reported in 49 individuals (5 cohorts, 20 cases) with a mean age at onset of 44.4 years. Diagnostics were not disclosed for half of the reported individuals (n = 25/49, 51.0%). A total of 44 different psychodiagnostic instruments were used. MRI was the most reported additional investigation (n = 12/49, 24.5%). Comorbid disorders most frequently associated with cognitive/adaptive decline were epilepsy, psychotic disorders, and movement disorders. DISCUSSION: Currently available literature shows limited information on aging in RGNDs, with relatively many reports of young-onset dementia. Longitudinal data may provide insights into converging neurodevelopmental degenerative pathways. We provide recommendations to optimize dementia screening, diagnosis, and research.

Unveiling the genetic tapestry: Rare disease genomics of spinal muscular atrophy and phenylketonuria proteins.

Rare diseases, defined by their low prevalence, present significant challenges, including delayed detection, expensive treatments, and limited research. This study delves into the genetic basis of two noteworthy rare diseases in Saudi Arabia: Phenylketonuria (PKU) and Spinal Muscular Atrophy (SMA). PKU, resulting from mutations in the phenylalanine hydroxylase (PAH) gene, exhibits geographical variability and impacts intellectual abilities. SMA, characterized by motor neuron loss, is linked to mutations in the survival of motor neuron 1 (SMN1) gene. Recognizing the importance of unveiling signature genomics in rare diseases, we conducted a quantitative study on PAH and SMN1 proteins of multiple organisms by employing various quantitative techniques to assess genetic variations. The derived signature-genomics contributes to a deeper understanding of these critical genes, paving the way for enhanced diagnostics for disorders associated with PAH and SMN1.

Improving the care of children with GENetic Rare disease: Observational Cohort study (GenROC)-a study protocol.

INTRODUCTION: Around 2000 children are born in the UK per year with a neurodevelopmental genetic syndrome with significantly increased morbidity and mortality. Often little is known about expected growth and phenotypes in these children. Parents have responded by setting up social media groups to generate data themselves. Given the significant clinical evidence gaps, this research will attempt to identify growth patterns, developmental profiles and phenotypes, providing data on long-term medical and educational outcomes. This will guide clinicians when to investigate, monitor or treat symptoms and when to search for additional or alternative diagnoses. METHODS AND ANALYSIS: This is an observational, multicentre cohort study recruiting between March 2023 and February 2026. Children aged 6 months up to 16 years with a pathogenic or likely pathogenic variant in a specified gene will be eligible. Children will be identified through the National Health Service and via self-recruitment. Parents or carers will complete a questionnaire at baseline and again 1 year after recruitment. The named clinician (in most cases a clinical geneticist) will complete a clinical proforma which will provide data from their most recent clinical assessment. Qualitative interviews will be undertaken with a subset of parents partway through the study. Growth and developmental milestone curves will be generated through the DECIPHER website (https://deciphergenomics.org) where 5 or more children have the same genetic syndrome (at least 10 groups expected). ETHICS AND DISSEMINATION: The results will be presented at national and international conferences concerning the care of children with genetic syndromes. Results will also be submitted for peer review and publication.

Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.

Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.

The value of knowing: preferences for genetic testing to diagnose rare muscle diseases.

BACKGROUND: Genetic testing can offer early diagnosis and subsequent treatment of rare neuromuscular diseases. Options for these tests could be improved by understanding the preferences of patients for the features of different genetic tests, especially features that increase information available to patients. METHODS: We developed an online discrete-choice experiment using key attributes of currently available tests for Pompe disease with six test attributes: number of rare muscle diseases tested for with corresponding probability of diagnosis, treatment availability, time from testing to results, inclusion of secondary findings, necessity of a muscle biopsy, and average time until final diagnosis if the first test is negative. Respondents were presented a choice between two tests with different costs, with respondents randomly assigned to one of two costs. Data were analyzed using random-parameters logit. RESULTS: A total of 600 online respondents, aged 18 to 50 years, were recruited from the U.S. general population and included in the final analysis. Tests that targeted more diseases, required less time from testing to results, included information about unrelated health risks, and were linked to shorter time to the final diagnosis were preferred and associated with diseases with available treatment. Men placed relatively more importance than women on tests for diseases with available treatments. Most of the respondents would be more willing to get a genetic test that might return unrelated health information, with women exhibiting a statistically significant preference. While respondents were sensitive to cost, 30% of the sample assigned to the highest cost was willing to pay $500 for a test that could offer a diagnosis almost 2 years earlier. CONCLUSION: The results highlight the value people place on the information genetic tests can provide about their health, including faster diagnosis of rare, unexplained muscle weakness, but also the value of tests for multiple diseases, diseases without treatments, and incidental findings. An earlier time to diagnosis can provide faster access to treatment and an end to the diagnostic journey, which patients highly prefer.

The impact of rare cancer and early-line treatments on the benefit of comprehensive genome profiling-based precision oncology.

BACKGROUND: Comprehensive genome profiling (CGP) serves as a guide for suitable genomically matched therapies for patients with cancer. However, little is known about the impact of the timing and types of cancer on the therapeutic benefit of CGP. MATERIALS AND METHODS: A single hospital-based pan-cancer prospective study (TOP-GEAR; UMIN000011141) was conducted to examine the benefit of CGP with respect to the timing and types of cancer. Patients with advanced solid tumors (>30 types) who either progressed with or without standard treatments were genotyped using a single CGP test. The subjects were followed up for a median duration of 590 days to examine therapeutic response, using progression-free survival (PFS), PFS ratio, and factors associated with therapeutic response. RESULTS: Among the 507 patients, 62 (12.2%) received matched therapies with an overall response rate (ORR) of 32.3%. The PFS ratios (≥1.3) were observed in 46.3% (19/41) of the evaluated patients. The proportion of subjects receiving such therapies in the rare cancer cohort was lower than that in the non-rare cancer cohort (9.6% and 17.4%, respectively; P = 0.010). However, ORR of the rare cancer patients was higher than that in the non-rare cancer cohort (43.8% and 20.0%, respectively; P = 0.046). Moreover, ORR of matched therapies in the first or second line after receiving the CGP test was higher than that in the third or later lines (62.5% and 21.7%, respectively; P = 0.003). Rare cancer and early-line treatment were significantly and independently associated with ORR of matched therapies in multivariable analysis (P = 0.017 and 0.004, respectively). CONCLUSION: Patients with rare cancer preferentially benefited from tumor mutation profiling by increasing the chances of therapeutic response to matched therapies. Early-line treatments after profiling increase the therapeutic benefit, irrespective of tumor types.

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Patient preferences in genetic newborn screening for rare diseases: study protocol.

INTRODUCTION: Rare diseases (RDs) collectively impact over 30 million people in Europe. Most individual conditions have a low prevalence which has resulted in a lack of research and expertise in this field, especially regarding genetic newborn screening (gNBS). There is increasing recognition of the importance of incorporating patients' needs and general public perspectives into the shared decision-making process regarding gNBS. This study is part of the Innovative Medicine Initiative project Screen4Care which aims at shortening the diagnostic journey for RDs by accelerating diagnosis for patients living with RDs through gNBS and the use of digital technologies, such as artificial intelligence and machine learning. Our objective will be to assess expecting parent's perspectives, attitudes and preferences regarding gNBS for RDs in Italy and Germany. METHODS AND ANALYSIS: A mixed method approach will assess perspectives, attitudes and preferences of (1) expecting parents seeking genetic consultation and (2) 'healthy' expecting parents from the general population in two countries (Germany and Italy). Focus groups and interviews using the nominal group technique and ranking exercises will be performed (qualitative phase). The results will inform the treatment of attributes to be assessed via a survey and a discrete choice experiment (DCE). The total recruitment sample will be 2084 participants (approximatively 1000 participants in each country for the online survey). A combination of thematic qualitative and logit-based quantitative approaches will be used to analyse the results of the study. ETHICS AND DISSEMINATION: This study has been approved by the Erlangen University Ethics Committee (22-246_1-B), the Freiburg University Ethics Committee (23-1005 S1-AV) and clinical centres in Italy (University of FerraraCE: 357/2023/Oss/AOUFe and Hospedale Bambino Gesu: No.2997 of 2 November 2023, Prot. No. _902) and approved for data storage and handling at the Uppsala University (2022-05806-01). The dissemination of the results will be ensured via scientific journal publication (open access).

Improving access to gene therapy for rare diseases.

Effective gene therapy approaches have been developed for many rare diseases, including inborn errors of immunity and metabolism, haemoglobinopathies and inherited blindness. Despite successful pre-clinical and clinical results, these gene therapies are not widely available, primarily for non-medical reasons. Lack of commercial interest in therapies for ultra-rare diseases, costs of development and complex manufacturing processes required for advanced therapy medicinal products (ATMPs) are some of the main problems that are restricting access. The complexities and costs of navigating the regulatory environments in different jurisdictions for treatments that affect small numbers of patients is a problem unique to ATMPS for rare and ultra-rare diseases. In this Perspective, we outline some of the challenges and potential solutions that, we hope, will improve access to gene therapy for rare diseases.

Between hope and reality: treatment of genetic diseases through nucleic acid-based drugs.

Rare diseases (RD) affect a small number of people compared to the general population and are mostly genetic in origin. The first clinical signs often appear at birth or in childhood, and patients endure high levels of pain and progressive loss of autonomy frequently associated with short life expectancy. Until recently, the low prevalence of RD and the gatekeeping delay in their diagnosis have long hampered research. The era of nucleic acid (NA)-based therapies has revolutionized the landscape of RD treatment and new hopes arise with the perspectives of disease-modifying drugs development as some NA-based therapies are now entering the clinical stage. Herein, we review NA-based drugs that were approved and are currently under investigation for the treatment of RD. We also discuss the recent structural improvements of NA-based therapeutics and delivery system, which overcome the main limitations in their market expansion and the current approaches that are developed to address the endosomal escape issue. We finally open the discussion on the ethical and societal issues that raise this new technology in terms of regulatory approval and sustainability of production.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Prediction of Individual Disease Progression Including Parameter Uncertainty in Rare Neurodegenerative Diseases: The Example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS).

The aim of this study was to develop a model to predict individual subject disease trajectories including parameter uncertainty and accounting for missing data in rare neurological diseases, showcased by the ultra-rare disease Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS). We modelled the change in SARA (Scale for Assessment and Rating of Ataxia) score versus Time Since Onset of symptoms using non-linear mixed effect models for a population of 173 patients with ARSACS included in the prospective real-world multicenter Autosomal Recessive Cerebellar Ataxia (ARCA) registry. We used the Multivariate Imputation Chained Equation (MICE) algorithm to impute missing covariates, and a covariate selection procedure with a pooled p-value to account for the multiply imputed data sets. We then investigated the impact of covariates and population parameter uncertainty on the prediction of the individual trajectories up to 5 years after their last visit. A four-parameter logistic function was selected. Men were estimated to have a 25% lower SARA score at disease onset and a moderately higher maximum SARA score, and time to progression (T50) was estimated to be 35% lower in patients with age of onset over 15 years. The population disease progression rate started slowly at 0.1 points per year peaking to a maximum of 0.8 points per year (at 36.8 years since onset of symptoms). The prediction intervals for SARA scores 5 years after the last visit were large (median 7.4 points, Q1-Q3: 6.4-8.5); their size was mostly driven by individual parameter uncertainty and individual disease progression rate at that time.

mRNA therapies: Pioneering a new era in rare genetic disease treatment.

Rare genetic diseases, often referred to as orphan diseases due to their low prevalence and limited treatment options, have long posed significant challenges to our medical system. In recent years, Messenger RNA (mRNA) therapy has emerged as a highly promising treatment approach for various diseases caused by genetic mutations. Chemically modified mRNA is introduced into cells using carriers like lipid-based nanoparticles (LNPs), producing functional proteins that compensate for genetic deficiencies. Given the advantages of precise dosing, biocompatibility, transient expression, and minimal risk of genomic integration, mRNA therapies can safely and effectively correct genetic defects in rare diseases and improve symptoms. Currently, dozens of mRNA drugs targeting rare diseases are undergoing clinical trials. This comprehensive review summarizes the progress of mRNA therapy in treating rare genetic diseases. It introduces the development, molecular design, and delivery systems of mRNA therapy, highlighting their research progress in rare genetic diseases based on protein replacement and gene editing. The review also summarizes research progress in various rare disease models and clinical trials. Additionally, it discusses the challenges and future prospects of mRNA therapy. Researchers are encouraged to join this field and collaborate to advance the clinical translation of mRNA therapy, bringing hope to patients with rare genetic diseases.

Genomic Answers for Kids: Toward more equitable access to genomic testing for rare diseases in rural populations.

Next-generation sequencing has revolutionized the speed of rare disease (RD) diagnoses. While clinical exome and genome sequencing represent an effective tool for many RD diagnoses, there is room to further improve the diagnostic odyssey of many RD patients. One recognizable intervention lies in increasing equitable access to genomic testing. Rural communities represent a significant portion of underserved and underrepresented individuals facing additional barriers to diagnosis and treatment. Primary care providers (PCPs) at local clinics, though sometimes suspicious of a potential benefit of genetic testing for their patients, have significant constraints in pursuing it themselves and rely on referrals to specialists. Yet, these referrals are typically followed by long waitlists and significant delays in clinical assessment, insurance clearance, testing, and initiation of diagnosis-informed care management. Not only is this process time intensive, but it also often requires multiple visits to urban medical centers for which distance may be a significant barrier to rural families. Therefore, providing early, "direct-to-provider" (DTP) local access to unrestrictive genomic testing is likely to help speed up diagnostic times and access to care for RD patients in rural communities. In a pilot study with a PCP clinic in rural Kansas, we observed a minimum 5.5 months shortening of time to diagnosis through the DTP exome sequencing program as compared to rural patients receiving genetic testing through the "traditional" PCP-referral-to-specialist scheme. We share our experience to encourage future partnerships beyond our center. Our efforts represent just one step in fostering greater diversity and equity in genomic studies.