Singleton short-read genome sequencing (GS) is increasingly used as a first-line genetic test for childhood neurological disorders (such as intellectual disability, neurodevelopmental delay, motor delay, and hypotonia) with diagnostic yields from 26 to 35

High-throughput sequencing has transformed clinical diagnostics of rare diseases (RD), cancer and infectious diseases by enabling the identification of disease-causing genetic alterations and facilitating individualised treatment and care. In response to these advances, Genomic Medicine Sweden (GMS) was established in 2017 as a national collaborative effort to accelerate implementation of genomics-based precision medicine within Sweden's regionally organized, publicly funded healthcare system. GMS brings together the seven university healthcare regions and their associated medical faculties, in collaboration with healthcare regions across Sweden, Science for Life Laboratory, patient organizations, industry and governmental agencies. Activities are coordinated through national disease-specific expert groups, supported by cross-cutting functions in bioinformatics, health economics, ethics, education and patient engagement. At the operational level, seven Genomic Medicine Centres, embedded at university hospitals, develop and deliver harmonised genomic diagnostics nationwide. The National Genomics Platform provides secure infrastructure for large-scale data storage, analysis, and national and international data sharing. Following initial project-based funding, GMS now receives long-term governmental support. This review describes the national implementation of genomic-based precision diagnostics, discusses challenges and lessons learnt, and highlights key milestones across disease areas, including whole-genome sequencing in RD and paediatric cancer, comprehensive genomic profiling of haematological malignancies and solid tumours, pathogen genomics in microbiology, pharmacogenomic testing and emerging applications of polygenic risk scores in complex diseases. Collectively, these efforts have contributed to more than 500,000 genomic tests being performed within Swedish healthcare between 2017 and 2025. Finally, we outline future diagnostic needs and priority areas to ensure sustainable, scalable and equitable access to precision medicine.

Our understanding of the genetic mechanisms underlying rare diseases has rapidly advanced over the past decade, largely because of technological innovations. Yet clinical practice still has a strong monogenic focus, leaving many individuals undiagnosed. This Comment outlines how technological advances such as long-read sequencing should be adopted to increase multivariant testing in the clinic.

Marfan syndrome is an autosomal dominant connective tissue disorder caused by pathogenic variants in the fibrillin-1-encoding gene. The cancer risk in Marfan syndrome is not fully understood, but recent reports have suggested an increased risk in adults. This study assessed cancer risk in Marfan syndrome using population-based data from the Swedish National registers. We performed a register-based nationwide matched cohort study of 1544 individuals with Marfan syndrome, born 1930-2017. Each individual was matched to 50 comparisons by birth year, sex and birth county. Cancer risk was estimated using Cox proportional hazard models, expressed as hazard ratios (HRs) with 95% confidence intervals (CIs). All cancer cases diagnosed before age 20 years were classified as childhood cancer, and those diagnosed at age 20 years or older were classified as adult cancer. The overall risk of adult cancer was not increased in individuals with Marfan syndrome (HR 1.00, 95% CI 0.78-1.27). However, there was an increased risk of endocrine tumours in adults with Marfan syndrome (HR 2.86, 95% CI 1.40-5.85). Furthermore, an over two-fold increased risk of cancer was observed among children with Marfan syndrome (HR 2.44, 95% CI 1.25-4.80). In this study, we found an increased cancer risk in children with Marfan syndrome. In contrast to previous reports, we did not detect an increased overall cancer risk in adults with Marfan syndrome, but an elevated site-specific risk of endocrine tumours. Further, larger studies are warranted to evaluate the lifetime cancer risk in Marfan syndrome at different ages.

A variety of genomic rearrangement mechanisms contribute to copy number variations at the 17p11.2 locus driven in part by its complex genomic architecture which is characterized by low copy repeats (LCRs) and other repetitive elements. These copy number variants are primarily mediated by nonallelic homologous recombination (NAHR) leading to recurrent tandem duplications and reciprocal deletions of the genomic interval mapping between the repeats. Two notable neurodevelopmental genomic disorders: Potocki-Lupski Syndrome (PTLS; MIM: 610883) and Smith-Magenis Syndrome (SMS; MIM: 182290) are driven by LCRs that undergo NAHR between the directly oriented repeats causing a duplication (PTLS) or deletion (SMS) encompassing the dosage-sensitive gene RAI1. We observed that other uncommon gains of varying sizes and extent at the 17p11.2 locus, which do not include the RAI1 gene, could be found in patients ascertained with a neurodevelopmental delay (NDD) phenotype. We ascertained 15 individuals from 11 families with copy number gains at the 17p11.2 locus not encompassing the driver gene-RAI1; such individuals manifested a broad spectrum of neurodevelopmental phenotypes. To validate our genomic findings, investigate DNA rearrangement mechanism(s), and refine our understanding at the breakpoint junctions, we performed a combination of high-resolution array CGH (n = 15), short-read whole-genome sequencing (sr-GS, n = 4), long-read GS (lr-GS; ONT; n = 4 and PacBio HiFi; n = 4), and breakpoint junctional analysis on this subset. Phenotypes in each individual were systematically studied. The phenotypes noted in these 15 individuals from 11 families primarily included developmental delay, intellectual disability, and behavioral problems. The genomic variations found in these 11 families included simple copy number gains (n = 7), higher order amplifications (n = 2), and complex genomic rearrangements (n = 2) at the 17p11.2 locus, surrounding the RAI1 gene and not encompassing it. Individuals from 4/11 families carried inherited variants. Identification of such rearrangement gains at the 17p11.2 locus that do not include the driver gene RAI1 and yet research subjects still exhibit neurodevelopmental phenotypes creates an opportunity to (i) dissect the gene(s) and genetic mechanisms that might contribute to phenotypic variability at the PTLS locus and (ii) uncover previously unrecognized genes or disease pathways and mechanisms.

Neurodegenerative diseases (NDDs) are clinically and genetically heterogeneous, requiring neuropathology or molecular testing for a definitive diagnosis. Clinical whole genome sequencing (WGS) enables comprehensive variant calling across flexible gene lists that can be tailored to the clinical presentation. By allowing simultaneous detection of single-nucleotide variants, copy-number variants, structural variants, and repeat expansions, WGS has the potential to improve diagnostic yield, facilitate genetic counseling and support clinical trial inclusion. This study assesses the diagnostic performance of WGS in individuals with NDD. WGS in 500 individuals representing a wide spectrum of NDDs identified a disease-causing variant in 61 cases, resulting in a diagnostic yield of 12%. These variants were found in 16 different genes, with C9orf72 being the most prevalent. Repeat expansions represented the largest variant class, accounting for 35 of 61 LP/P cases (57%); most of which were C9orf72 expansions (31/35). In the largest phenotype groups, frontotemporal dementia (FTD) had the highest diagnostic yield (19%) followed by amyotrophic lateral sclerosis (ALS, 13%), whereas an underlying monogenic cause was expectedly low in Alzheimer disease (AD, 4%). A positive family history was present in the majority (74%) of FTD, ALS, combined ALS-FTD and AD cases with an LP/P finding. Clinical WGS provides a clear diagnostic advantage in NDDs marked by substantial clinical and genetic overlap. WGS enables comprehensive variant detection and mapping of genotype-phenotype relationships across the disease continuum. In FTD and ALS, these results support universal access to genetic testing independent of age at onset or family history.

Small supernumerary marker chromosomes (sSMCs) remain a diagnostic challenge despite sequencing advances. As the field shifts toward cytogenomics, there is a need to establish methodologies to resolve these complex genetic variants at base pair resolution, as well as to identify their chromosomal origin and formation mechanism. Here, we apply long-read genome sequencing (lrGS) in combination with the telomere-to-telomere (T2T-CHM13) assembly to characterize the structure and genomic content of 10 clinically detected sSMCs. We use sequencing data to reconstruct the derivative chromosomes, identify breakpoint junctions (BPJs), and infer formation mechanisms. We resolve the BPJs of nine of the 10 sSMCs at base pair resolution. The analysis reveals six simple intrachromosomal rearrangements (one continuous and five discontinuous) with one to three BPJs, one complex three-way translocation with two BPJs, and two highly complex intrachromosomal rearrangements with five and nine BPJs, respectively. Breakpoint analysis reveals distinct mechanistic signatures: Simple sSMCs show features consistent with microhomology-mediated end joining (MMEJ) or microhomology-mediated break-induced replication (MMBIR), whereas complex sSMCs demonstrate evidence of translocation, chromoanasynthesis, and breakage-fusion-bridge (BFB) cycles. Haplotype analysis supports trisomy rescue in four cases, including all three complex sSMCs. In summary, our study demonstrates that lrGS combined with T2T-CHM13 enables detailed structural and mechanistic characterization of sSMCs, providing experimental support for disruption of trisomy rescue as a key formation mechanism. This work illustrates the feasibility of resolving highly challenging chromosomal abnormalities using long-read sequencing technologies.

Neurodevelopmental disorders (NDDs) affect 2-4% of the population, are predominantly genetic and remain unsolved in ~50% of individuals. We show that rare biallelic variants in RNU2-2 are enriched and over-transmitted in individuals with unresolved NDDs. We define a recessive RNU2-2 syndrome, delineate its unique genetic architecture and show that it manifests clinically as a severe developmental and epileptic encephalopathy. We find that candidate biallelic variants are significantly correlated with reduced U2-2 abundance, implicating compromised transcript stability as a probable pathomechanism. We identify a decreased ratio of U2-2 to its paralog U2-1 as a potential diagnostic biomarker for this condition. We show that the recessive RNU2-2 syndrome is genetically, clinically and mechanistically distinct from the dominant RNU2-2 disorder. Within our cohort, the recessive RNU2-2 syndrome emerges as by far the most frequent recessive NDD, greatly disproportionate to the small genomic footprint of this non-protein-coding gene.

Motivation Long-read sequencing (LRS) is increasingly used for human medical research and clinical diagnostics due to its capacity to generate complete genome information. However, there is a lack of robust and easy-to-use pipelines for comprehensive LRS data analysis.Results Here we present Nallo, a Nextflow pipeline for analysis of PacBio and Oxford Nanopore data, with additional support for rare disease research projects. The pipeline detects a wide range of genetic variants, performs genome assembly, and reports CpG methylation. It also enables annotation and ranking of variants based on their predicted functional consequences.Availability and implementation Nallo is available from GitHub: https://github.com/genomic-medicine-sweden/nallo

OBJECTIVE:A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS:We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS:We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p = .005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE:We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

BACKGROUND:Biallelic pentanucleotide expansions in RFC1 cause cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS), and a growing spectrum of presentations. We aimed to clinically characterize a cohort of patients from Sweden with biallelic expansions in RFC1. METHODS:We retrospectively enrolled patients with homozygous expansions in RFC1 from a tertiary center in Sweden, evaluating clinical and genetic data. Assessments included nerve conduction studies (NCS, n = 27), electromyography (n = 7), quantitative sensory testing (n = 18), brain MRI (n = 27), and vestibular/eye motor tests (n = 18-21). RESULTS:Of the 30 patients enrolled, 28 were ethnic Swedish; 17/30 from smaller regions, including eight (27%) from Norrbotten. Twenty-two patients met the CANVAS criteria. Mean age of onset was 52 ± 12 years (range 20-70), and disease duration was 14 ± 12 years. Symptoms matched the CANVAS acronym with multisystemic features in 83%, including dysautonomia (77%), dyskinesia (36%), and bradykinesia (17%). Phenotypes overlapped with MSA-C (n = 2) and mitochondrial ataxias (n = 1). Notably, one symptomatic patient lacked neuropathy on NCS. Annual disease progression was slow (0.3 by spinocerebellar degeneration functional score, 1.2 by SARA). At vestibular testing, 47% showed a preserved caloric response and pathologic angular VOR with a nonsignificant trend among younger patients and milder ataxia; otolith function was largely preserved. DISCUSSION:Our findings expand the RFC1 spectrum, suggesting a founder effect in Sweden and extensive subclinical involvement. RFC1-spectrum disorder should also be considered in patients with cerebellar and vestibular dysfunction but lacking neuropathy. A discordant VOR pattern may represent an incipient sign of RFC1-spectrum disorder; interestingly, otolith pathways seem to be generally spared.

Abstract Background As clinical genetics evolves towards the broader field of clinical genomics, the diagnostic approach to rare diseases is undergoing a paradigm shift. This transformation has significantly impacted rare disease diagnostics, increasingly done through gene panels, whole exome and whole genome sequencing. To advance beyond genomics into precision medicine and encompass the breadth of relevant clinical scenarios, a true systems shift is required that challenges conventional barriers and enables the formation of cross-disciplinary, integrated environments. Methods The Genomic Medicine Center Karolinska Rare Diseases (GMCK-RD) has, for the past 10 years, brought together healthcare and academia to enable large-scale genome sequencing in a clinical diagnostics context. Within GMCK-RD, experts from various medical disciplines collaborate closely with clinical geneticists, bioinformaticians, and researchers to integrate genome sequencing into healthcare. Results In total, 15 644 individuals with suspected rare diseases were analyzed using clinical genome sequencing, including pediatric (48%), adult (48%) and fetal (4%) samples. The overall diagnostic yield was 22.6%, providing a diagnosis for 3 538 individuals with variants in 1 570 genes. Moreover, a rare disease analysis tool suite developed and validated in house includes a bioinformatic pipeline allowing for comprehensive data analysis covering a wide range of genetic variants including SNVs, INDELs, repeat expansions, uniparental disomies, balanced and unbalanced structural variants as well as insertions of mobile elements. Results are visualized and interpreted in custom-developed decision support systems functioning as an interpretation portal as well as a knowledge-base to capture the interpretation efforts made in a structured format allowing future secondary use. Conclusions Altogether, GMCK-RD has shifted healthcare in our region towards precision diagnostics. We emphasize the need to transition from traditional clinical genetic diagnostics to a broader clinical genomics approach. Beyond this shift, we advocate integrating genomics with specialized clinical and laboratory medicine, a concept pioneered for inborn errors of metabolism (IEM) with stepwise spread to additional disease groups. In this model, a multidisciplinary unit combines screening, targeted diagnostics, individualized treatment, and long-term patient follow-up. Here we provide a road map and guide for inspiration for centers aiming to implement genome sequencing in rare disease diagnostics.

Identification of genomic rearrangements by microarrays or short-read sequencing frequently lacks information about the exact architecture and breakpoints of variants due to technical limitations. Independent verification of complex structural variants (SVs) is often performed using custom targeted assays, making confirmation of clinically relevant findings time consuming and laborious. In this study we evaluate Oxford Nanopore long-read adaptive sampling for flexible and rapid confirmation and characterization of complex genomic rearrangements and structural variants. Adaptive sampling is an in silico target enrichment, where continued sequencing or ejection of a fragment is based on whether it matches a defined reference sequence. Using adaptive sampling, we targeted 10 regions with different structural variant types, including deletions, translocations, and complex rearrangements. Each sample was analyzed on a MinION or PromethION flow-cell, and sequencing resulted in between 14.1–18.3 Gb of data per sample, with mean autosomal on-target coverage of 28.4x and off-target read depth coverage of 5.3x. We were able to verify all 10 rearrangements, with breakpoint spanning reads for nine of the ten regions, and fully resolved the architecture of nine regions. We also show that background reads can be used to detect structural variants in non-targeted regions of the genome. Our results show that adaptive sampling represents a flexible and rapid strategy for confirmation and characterization of clinically relevant genomic rearrangements in clinical samples. By providing sequence information, read depth, and methylation data, nanopore adaptive sampling has advantages over other assays for variant confirmation used in diagnostic laboratories today.

Background/Objectives: Hypoparathyroidism (HPT) is a disorder caused by the insufficient production of parathyroid hormone (PTH). Its main features include decreased serum calcium, increased serum phosphorus, and abnormal bone modeling. In children, HPT is most commonly due to genetic disorders. Among rare genetic syndromes that can include HPT in their clinical spectrum is Kenny–Caffey syndrome (KCS) type 2. Conventional therapy for HPT primarily consists of oral calcium and active vitamin D metabolites. The major limitation of conventional therapy is hypercalciuria with an increased risk of nephrocalcinosis. However, a subset of patients fails to achieve the desired therapeutic response to conventional treatment; the reasons for this remain incompletely understood in some cases. The failure to achieve therapeutic targets and persistent hypercalciuria are the main indications for considering therapy with recombinant human parathyroid hormone (rhPTH). Methods: In addition to the review of the literature on rhPTH use in pediatric hypoparathyroidism, the first application of rhPTH in the treatment of genetically caused HPT in a child with Kenny–Caffey syndrome type 2 (KCS2) was described. Results: In this paper, we present a two-month-old infant who received rhPTH for 14 months. A heterozygous de novo p.Ser541Pro variant in the FAM111A gene was identified through whole-genome sequencing, indicating a diagnosis of KCS2. A biological mechanism linking FAM111A protein function with a more profound disruption of parathyroid development or function was proposed, suggesting that rhPTH therapy may be particularly beneficial in KCS2 cases. Conclusions: This is the first reported use of rhPTH in a child in Serbia and the first reported use in KCS type 2. By reviewing the literature, we analyzed the conditions in which rhPTH has been used, dosing approaches and durations, requirements for concomitant conventional therapy during rhPTH treatment, and the effects of rhPTH on calciuria. We provide an overview of rhPTH use in children. Additionally, based on the pathogenic genetic variant responsible for KCS2 in our patient, we propose possible etiologic explanations. This work aims to encourage a consideration of rhPTH use in children following its official approval.

This study aimed to identify genetic variants contributing to the development of early-diagnosed isolated intestinal malrotation. We conducted Genome sequencing on ten young children diagnosed with midgut volvulus due to intestinal malrotation who presented no other malformations or comorbidities. Our analysis focused on a panel of 442 genes previously associated with intestinal development, malrotation, ciliopathies and/or situs abnormalities. In one male patent we discovered two heterozygous variants in TTC7A, c.433G > A p.(Ala145Thr) and c.1057G > A p.(Glu353Lys). Carrier testing revealed that he inherited both variants from his mother with a mild intestinal rotation abnormality. Additionally, we identified inherited variants in two other male participants, c.1802 A > T p.(Asp601Val) in ROCK2 and, c.884 G > A p.(Arg295His) in LIMK2. These genes are part of a shared signaling pathway previously shown to cause intestinal malrotation in Xenopus when inhibited. Our findings suggest the potential involvement of TTC7A, ROCK2 and LIMK2-genes in the pathogenesis of intestinal malrotation; through the ROCK-signaling pathway.

Bladder exstrophy and epispadias complex (BEEC) is one of the most severe congenital malformations of the urogenital tract, significantly impacting continence, sexual function, and renal function. To date, the only recurrent genetic aberration identified is the 22q.11.2 microduplication, but several candidate regions and genes including components of the WNT signaling pathway have been proposed. This study aimed to identify additional genes contributing to the pathogenesis of BEEC and to verify previously suggested candidate genes. We performed trio-based whole genome sequencing on 19 individuals with BEEC and their unaffected parents; of those, five carried earlier reported microdeletions. The genome data was also filtered in silico for variants in 204 candidate genes selected from databases, publications, and in-house findings. Variants were prioritized based on allele frequency and predicted functional impact. In 8 of the 19 trios, our findings highlight members of the ADGR-gene family as novel candidate genes for BEEC, alongside other implicated genes such as TRANK1, CSNK1E, IFT122, SDK1, SDK2, and KIF19 and propose two more CNVs as risk factors for BEEC; on chromosome regions 1p36 and 16p11.2. This study identifies novel candidate genes for BEEC within the ADGR gene family. The results also further implicate a complex molecular background of BEEC.

Introduction:A trio analysis refers to the strategy of exome or genome sequencing of DNA from a patient, as well as parents, in order to identify the genetic cause of a disorder or syndrome. Methods:During the last 10 years, we have successfully applied exome or genome sequencing and performed trio analysis for 1,000 patients. Results:Overall, 39% of the patients were diagnosed, with the detection of causative variant(s). The variants were located in 308 different genes. Autosomal dominant de novo variants were detected in 46% of the solved cases. Detection rates were highest in patients with a syndromic neurodevelopmental disorder (46%) and in patients with known consanguinity (59%). Even for patients previously analyzed as singletons, using a pre-defined gene panel, a consecutive trio analysis resulted in the detection of a causative variant in 30%. Discussion:A major advantage of trio analysis is the immediate identification of de novo variants as well as confirmation of compound heterozygosity. Additionally, inherited variants from a healthy parent can be dismissed as non-disease causing. The trio strategy enables analysis of a high number of genes-or even the whole genome-simultaneously. The strengths of a trio analysis, in combination with analysis of genome sequence data, allows for the detection of a wide range of genetic aberrations. This enables a high diagnostic yield, even in previously analyzed patients. Our current protocol for trio analysis is based on genome sequencing data, which allows for simultaneous detection of single nucleotide variants, insertion/deletions, structural variants, expanded short tandem repeats, as well as a copy number analysis corresponding to an array-CGH, and analysis regarding SMN1 gene copies.

Copy number variation (CNV) of the amyloid-β precursor protein gene (APP) is a known cause of autosomal dominant Alzheimer disease (ADAD), but de novo genetic variants causing ADAD are rare. We report a mother and daughter with neuropathologically confirmed definite Alzheimer disease (AD) and extensive cerebral amyloid angiopathy (CAA). Copy number analysis identified an increased number of APP copies and genome sequencing (GS) revealed the underlying complex genomic rearrangement (CGR) including a triplication of APP with two unique breakpoint junctions (BPJs). The mosaic state in the mother had likely occurred de novo. Digital droplet PCR (ddPCR) on 42 different tissues, including 17 different brain regions, showed the derivative chromosome at varying mosaic levels (20–96%) in the mother who had symptom onset at age 58 years. In contrast, the derivative chromosome was present in all analyzed cells in the daughter whose symptom onset was at 34 years. This study reveals the architecture of a de novo CGR causing APP triplication and ADAD with a striking difference in age at onset between the fully heterozygous daughter compared to the mosaic mother. The GS analysis identified the complexity of the CGR illustrating its usefulness in identifying structural variants (SVs) in neurodegenerative disorders.

In rare disease research, sharing of individual health data is essential for advancing diagnostics and therapies, requiring robust and ethically sound informed consent processes. Within the Genomic Medicine Sweden Rare Diseases (GMS-RD) multicenter study, an electronic informed consent (eConsent) platform was developed to support data sharing, facilitate participation and enable research engagement. Tailored to the complex consent needs of rare disease contexts, the platform was piloted at three Genomic Medicine Centers in Sweden. A total of 2244 individuals were invited in the clinical routine cohort, with an overall eConsent rate of 18.6%. Uptake was highest among adult singletons (27.8%) and lowest in trios (14.3%). In contrast, the Undiagnosed Diseases Network (UDN) Sweden cohort achieved a 94% consent rate, attributed to targeted communication and active patient organization involvement. Key challenges included technical accessibility limitations, digital literacy deficits, comprehension and language barriers, and the burden of multi-step processes, especially for families. Findings underscore the need to improve usability, strengthen communication, and implement flexible consent management over time. eConsent can broaden participation in genomic research and promote responsible data sharing. However, in rare diseases contexts, it must be designed with inclusivity, clarity, and adaptability to meet the diverse participant needs.

This paper reports the findings of an international survey of health data ecosystems (HDEs) in 12 countries plus the H3 Africa project using live, structured interviews with senior project team members under the auspices of Canada's All for One Precision Health Initiative. We note the high level of interest in HDEs around the world, as well as in Canada, despite the financial, jurisdictional, and other barriers that continue to hold back widespread data sharing. We present results detailing operational profiles for each of the 13 participants, including whether their healthcare systems are centralized (national) or decentralized (regional), project start date, funding, information technology (IT) infrastructure, and the extent to which participants have implemented a data-sharing mandate. We find no evidence to confirm common assumptions about features conferring an advantage on HDE development, such as early launch date or top-down government mandate. We also find no evidence of a reference model to explain what makes any HDE effective, valuable, or successful and conclude, on the basis of our interviews, that the diversity that makes each of these projects unique may undermine collective actions like data sharing. While participants provided useful cautions about pitfalls they encountered, more research on these issues is required, and we anticipate that advanced assessment tools like the maturity level model (MLM) developed by the European Union (EU) may help countries understand what stage of the HDE development process they have reached and what strategies will be most effective for them in later stages.