Genetics in Medicine Open

Background: RNA sequencing (RNA-seq) is increasingly recognized as a complementary tool to DNA-based sequencing for improving the diagnostic yield in Mendelian disorders. However, how the diagnostic performance of RNA-seq varies across molecularly and phenotypically distinct patient subgroups remains poorly defined. This study aimed to evaluate and compare the diagnostic utility of RNA-seq across three stratified groups of patients with non-diagnostic exome sequencing. Methods: We performed RNA-seq on whole blood samples from 90 patients with suspected Mendelian disease in whom clinical exome or whole-exome sequencing had failed to establish a molecular diagnosis. Patients were prospectively stratified into three groups of 30: (i) patients with a candidate variant of uncertain significance (VUS) with predicted splicing impact (Group 1), (ii) patients with a specific clinical pre-diagnosis but no identified pathogenic variant (Group 2), and (iii) patients without a specific pre-diagnosis or candidate variant (Group 3). Aberrant splicing, gene expression outliers, and allele-specific expression were analyzed using multiple bioinformatic tools and compared against a GTEx-derived control cohort. Results: RNA-seq contributed to a molecular diagnosis in 29 of 88 evaluable patients (32.9%). Diagnostic yield differed substantially across groups: 82.8% (24/29) in Group 1, 6.9% (2/29) in Group 2, and 10% (3/30) in Group 3. In Group 1, RNA-seq enabled reclassification of candidate VUS through direct demonstration of aberrant splicing events. In Group 2, RNA-seq identified a somatic mosaic ACTB variant missed by exome sequencing and reclassified a previously deprioritized APPL1 VUS. In Group 3, a deep intronic pseudoexon-activating variant in IGBP1 was identified in two siblings with severe microcephaly, providing evidence for a candidate X-linked microcephaly gene, and a pathogenic RNU4-2 variant was detected in a patient with ReNU syndrome, a non-protein-coding gene not captured by standard exome sequencing. Conclusions: RNA-seq has the highest diagnostic utility when applied to evaluate candidate splice variants identified by prior DNA testing but also provides independent diagnostic value in patients without candidate variants. The systematic comparison across stratified patient groups supports the integration of RNA-seq into clinical genomic workflows and highlights the need for standardized analytic frameworks.

The human opsin gene cluster at Xq28 contains highly similar OPN1LW and OPN1MW genes essential for red-green color vision. Current molecular methods cannot accurately analyze this complex locus, limiting diagnosis of color vision deficiencies (CVD) and detection of carrier status. We performed Nanopore long-read sequencing of 206 individuals, comparing alignment-based analysis with targeted de novo assembly. Alignment-based methods performed poorly, whereas targeted assembly achieved 99% concordance for OPN1LW and 92% for OPN1MW copy numbers and resolved gene order in all XY individuals and 87% of XX individuals. This approach detected CVD in 3.2% of XY individuals and identified 8% of XX individuals as carriers, consistent with population estimates. Moreover, it molecularly explained the phenotypic severity in a family with Bornholm eye disease and clarified carrier status in an XX individual suspected of carrying two CVD haplotypes. Our approach provides a comprehensive, reference-free method for accurate analysis of expressed opsin genes and reliable CVD carrier detection.

BackgroundTandem repeat expansions (TREs) cause over 60 known neurological, neuromuscular, and developmental disorders. Detecting these expansions genome-wide is challenging due to their size, sequence complexity (including interruptions), and population variation. While long-read sequencing is an emerging technology that can fully resolve many TREs, no methods have been described for genome-wide identification and prioritization of candidate pathogenic TREs with this technology. MethodsUsing a newly developed pipeline called TRoLR (Tandem Repeat outliers identified with Long Reads), we analyzed haplotype-resolved long-read genome assemblies from 471 ancestrally diverse individuals to define population distributions for over three million tandem repeat loci, capturing clinically relevant interruptions. Outlier expansions were identified relative to these distributions and prioritized by genomic location and comparison to known pathogenic loci. The framework was applied to 47 cases from the Undiagnosed Diseases Network. ResultsPopulation stratification of repeat metrics was observed at 7% of loci, with highest variability among individuals of African ancestry. Outlier analysis confirmed known pathogenic CNBP and ATXN8OS expansions, detected carrier-range alleles at RFC1, CSTB, and FXN, and revealed a novel CGG expansion in the 5 UTR of PCMTD2 exhibiting hypermethylation and intergenerational instability. Genome-wide screening also identified intronic pentanucleotide expansions at IQCB1 and MAP3K15 in controls composed of motifs that have been associated with pathogenicity at other disease loci. ConclusionsQuantifying the longest uninterrupted repeat segment in long-read assemblies enables detection of clinically relevant repeat expansions and loss of stabilizing interruptions. This approach enhances both diagnostic confirmation and discovery of candidate pathogenic expansions, with implications for clinical interpretation and research into complex repeat-mediated disorders.

BackgroundThe diagnostic yield for 46,XY disorders of sex development (DSD) remains limited. Whole-genome sequencing (WGS) improves detection of both coding and non-coding variants that may be missed by routine testing. Cytochrome b5, encoded by CYB5A, is an essential co-factor for CYP17A1-mediated 17,20-lyase activity. We report on WGS on a Vietnamese family with 46,XY DSD with two siblings presenting with female external genitalia. MethodsClinical assessment and hormone profiling were conducted. WGS was conducted on peripheral blood DNA, in two affected siblings followed by variant annotation and ACMG-based classification. A minigene RNA splicing assay in HEK293 cells was used to evaluate the functional impact of the CYB5A intronic variant. ResultsThe patients hormone profile showed low testosterone and estradiol. WGS identified compound-heterozygous CYB5A variants: a paternally inherited missense variant (p.Val34Glu, likely pathogenic) and a maternally inherited deep intronic deletion (c.129+862_129+863del) for which SpliceAI predicted aberrant splicing. Minigene assays confirmed that the intronic deletion creates cryptic splice sites, resulting in pseudoexon inclusion and a premature stop codon, consistent with nonsense-mediated decay. The intronic variant meets ACMG criteria for pathogenicity. ConclusionThis family expands the spectrum of CYB5A-related DSD and demonstrates that compound-heterozygous variants, including deep intronic defects, can lead to a disruption in 17,20-lyase activity. These findings highlight the importance of WGS and functional assays for identifying clinically relevant non-coding variants in DSD.

Background Orofacial clefts (OFCs) and other palate abnormalities (PAs) are among the most common birth defects worldwide and are characterized by the abnormal formation of the lip and/or palate. Genetic studies have traditionally classified OFC cases as either syndromic, involving OFCs alongside other congenital anomalies, or nonsyndromic, which represent the majority of cases and occur in isolation. Emerging genomic evidence indicates that genes traditionally associated with syndromic forms of OFC can also harbor variants contributing to isolated cases, challenging the notion of a strict dichotomy between these categories and supporting their integration for gene discovery. Methods In this study, we applied multiple analytic approaches to characterize the genetic architecture of OFC and PAs by integrating genomic data from 2,497 trios with an OFC (n=2080) and PA (n=417) affected proband. We compared these findings across OFC subtypes and syndromic status with those from 5,515 control trios to identify enriched biological pathways and mechanisms and to prioritize candidate genes using variant burden testing. Results We observed a significant enrichment of de novo protein-truncating and damaging missense variants in cases compared to controls (OR = 2.17, p = 1.21x10-32), with particularly strong signals in biologically relevant gene sets involving OFC-associated, constrained, Mendelian disorder, and mouse candidate genes. Variant burden testing identified 39 OFC risk genes at FDR [≤] 0.05, which we then integrated with 593 established OFC genes to interrogate the functional underpinnings of OFC via network analysis. This analysis revealed 309 high-order interactor genes not previously associated with OFC. Notably, this OFC network clustered into ten distinct biological pathways, with nucleosome-associated genes showing significant enrichment among cases in our cohort (OR = 14.8, p = 8.1x10-4). In a final integrative step, we combined evidence across all analyses to nominate 231 candidate genes, 32 of which contained at least two deleterious de novo variants in our cohort. Conclusions These findings underscore the value of integrating diverse OFC and PA subtypes, syndromic status, and variant classes to refine the genetic architecture of these disorders, highlighting both phenotypic expansion of known disease genes and the emergence of novel gene-phenotype associations.

Background: Biallelic variants in GFM2, encoding mitochondrial elongation factor G2 (mtEFG2), a GTPase involved in the termination stage of mitochondrial translation, cause autosomal recessive combined oxidative phosphorylation deficiency. Noncoding structural variants may be missed by exome sequencing but can disrupt splicing and provide opportunities for variant-specific therapeutic rescue. We investigated the molecular mechanism underlying suspected Leigh syndrome in an infant with mitochondrial disease and evaluated whether splice-switching oligonucleotide (SSO) treatment could correct the pathogenic splicing defect. Methods: The proband underwent exome sequencing followed by short-read and long-read whole genome sequencing. RNA sequencing, reverse-transcription PCR, quantitative PCR, and cycloheximide treatment were used to characterize the effect of the identified intronic duplication on GFM2 splicing and transcript stability. Patient-derived fibroblasts were treated with SSOs targeting the aberrant splice junction. Rescue was assessed by RNA studies, western blotting, and spectrophotometric measurement of cytochrome c oxidase (COX). Results: Whole genome sequencing identified a paternally-inherited GFM2 missense variant, NM_032380.5:c.2195C>T p.(Pro732Leu), in trans to a maternally-inherited 221-nucleotide intronic duplication, NM_032380.5:c.2029-741_2029-521dup. RNA studies revealed a 87-nucleotide pseudoexon, generated by activation of a cryptic acceptor splice site within the duplicated sequence. The resulting transcript harbored a premature termination codon (PTC) and underwent nonsense-mediated decay, as confirmed by cycloheximide rescue. Together with reduced mtEFG2 protein levels on western blot, the findings supported a loss-of-function mechanism. Enzymatic analysis of affected fibroblasts showed reduced activity of the mtDNA-dependent complex IV subunit COX, with preservation of the nuclear-encoded complex II enzyme succinate dehydrogenase and the control enzyme citrate synthase, consistent with impaired mitochondrial translation. A SSO targeting the aberrant intron-pseudoexon junction nearly abolished pseudoexon inclusion, restored correctly spliced GFM2 transcript from the duplication-containing allele, increased mtEFG2 protein levels, and significantly improved COX activity. Conclusions: This study identifies a pathogenic intronic GFM2 duplication that causes mitochondrial disease through pseudoexon activation and nonsense-mediated decay. The findings demonstrate the value of integrated genome and transcriptome analysis for exome-negative mitochondrial disease and provide in-vitro proof of concept that SSOs can restore transcript processing, protein expression, and mitochondrial respiratory-chain function in patient-derived cells.

Variant databases ClinVar and gnomAD are the backbone of clinical variant interpretation, but their population composition is skewed toward European ancestry. Whether this skew creates systematic classification disadvantages for non-European patients with monogenic diabetes has not been examined at the database level. ClinVar variant_summary (GRCh38, April 2026; 4,421,188 variants) was cross-referenced with gnomAD v4.0 genome data for 17 monogenic diabetes genes. Annotation coverage and variant classification rates were computed stratified by genetic ancestry group (AFR, AMR, EAS, SAS, MID, NFE, FIN, ASJ). Of 14,691 gnomAD variants across the 17 genes, only 29.7% had any ClinVar classification (range: 12.7%-61.3% by gene). Among classified variants, non-Finnish European (NFE) variants had the highest variant of uncertain significance (VUS) rate (32.1%) and the lowest benign/likely benign fraction (41.6%), consistent with a large submission volume without functional follow-up. African-ancestry (AFR) variants showed the second-highest VUS rate (29.2%), not statistically distinguishable from NFE after Bonferroni correction, while all other non-European groups had significantly lower rates (all p < 0.001). GCK showed a pattern inversion - non-European VUS rate (18.5%) exceeding European (15.0%) - consistent with progressive reclassification in European populations absent in non-European cohorts. Annotation coverage and VUS divergence were uncorrelated (r = -0.15, p = 0.57). The primary equity problem is a 70% annotation gap combined with a non-European curation deficit, not a simple VUS excess. Ancestry-stratified evaluation of ClinGen Variant Curation Expert Panel (VCEP) criteria performance is warranted across disease domains.

Introduction: BEACONS-NBS (Building Evidence and Collaboration for GenOmics in Nationwide Newborn Screening) is the first research study to integrate whole genome sequencing into newborn screening (NBS) across multiple U.S. states and territorial public health laboratory programs (PHLPs). We developed a list of conditions for screening. Methods: We designed inclusion criteria and assembled an initial condition list from published resources. The list was revised by clinical experts, molecular geneticists, genetic counselors, PHLPs, rare disease advocacy organizations, the BEACONS-NBS Community Advisory Board, and project leadership from the National Institutes of Health. For each condition, we provided a rationale for early detection, diagnostic signs or biomarkers, and treatments or surveillance strategies. Results: The BEACONS-NBS condition list includes 777 conditions associated with 743 genes, one copy number variant, and two aneuploidies and is larger than those used in other genomic NBS research studies in the U.S. and United Kingdom. Most conditions are inborn errors of immunity (37.2%), inherited metabolic disorders (18.7%), or endocrine conditions (18.1%). Nearly all conditions (93.3%) can be confirmed using a non-genetic test. Discussion: BEACONS-NBS has established a condition list for implementation across multiple state and territorial PHLPs, enabling the prospective evaluation of feasibility of population-wide genomic NBS.

Wolfram syndrome is a rare genetic disorder characterized by antibody-negative early-onset atypical diabetes mellitus, optic nerve atrophy, sensorineural hearing loss, diabetes insipidus (arginine vasopressin deficiency), and progressive neurodegeneration, with significant variability in disease severity. We assessed the accuracy of a genotype-based severity scoring system to predict the onset of cardinal symptoms in Wolfram syndrome. This system is based on the type of WFS1 variants (in-frame or out-of-frame) and their location relative to transmembrane domains. Severity scores were assigned to 324 patients with documented onset ages for diabetes mellitus, optic atrophy, hearing loss, and diabetes insipidus. Our analysis revealed a clear correlation between severity scores and earlier onset of diabetes mellitus and optic atrophy. Patients with in-frame variants outside transmembrane domains exhibited milder symptoms, especially WFS1 c.1672C>T (p.Arg558Cys) variant, whereas those with out-of-frame variants showed the earliest onset. Severity scores 3 and 4 did not follow the expected progression, suggesting that transmembrane domain involvement in both alleles may result in greater severity. These findings suggest that this scoring system provides valuable insights into the progression of Wolfram syndrome and may guide clinical care. Further refinement may improve its utility for predicting the onset of non-diabetic symptoms.

Biallelic disease-causing variants in IGHMBP2 cause spinal muscular atrophy with respiratory distress type I (SMARD1) and Charcot-Marie-Tooth type 2S (CMT2S). We present 12 unrelated patients with clinically suspected IGHMBP2-related-disease, each carrying a variant deep in intron 8 of IGHMBP2 (c.1235+1076G>A (n=6), c.1235+450G>A (n=5), and c.1235+894C>A (n=1)), along with a known deleterious variant in trans. To assess aberrant pathogenic splicing induced by these deep intronic variants in a relevant model, patient-derived induced pluripotent stem cells were differentiated into motor neurons (iMNs). Long-read RNA sequencing revealed introduction of different pseudoexons by each variant: c.1235+450G>A (626bp), c.1235+1076G>A (112bp and 77bp) and c.1235+894C>A (182bp). Although each variant utilizes a unique splice acceptor site, they all activate the same cryptic donor site, enabling a therapeutic approach to redirect aberrant splicing for all the variants using a single shared antisense oligonucleotide (ASO). Treatment of iMNs with this single ASO restored full-length IGHMBP2 protein in c.1235+894G>A and c.1235+1076G>A by decreasing the use of the novel acceptor site. In contrast, ASO treatment did not correct the splicing in c.1235+450G>A, suggesting that additional splice correction will be needed for this specific variant. A CRISPR interference screen of IGHMBP2 loss-of-function in iMNs identified ribonucleoprotein complex biogenesis (RNP), and rRNA and tRNA processing as top pathways implicated in motor neuron vulnerability. Proteomics and transcriptomics analysis of successfully treated patient iMNs revealed correction of RNP biogenesis and rRNA processing defects. This study highlights the importance of characterizing deep intronic variants in disease-relevant cells to assist the diagnostic process and inform therapeutics development. One Sentence SummaryIntron 8 of IGHMBP2 is a hotspot for splice activating pathogenic variants causing SMARD1 and CMT2S, which can be targeted with a single antisense oligonucleotide to correct the aberrant splicing, increase protein and restore cellular function in patient derived motor neurons.

Mutations in MAP3K7 are responsible for two distinct syndromes Cardiospondylocarpofacial (CSCF) and Frontometaphyseal dysplasia 2 (FMD2). Both are characterized by skeletal malformations, facial dysmorphisms, hearing loss, and mild intellectual disability. While cardiac defects are predominant in CSCF, keloid scar is a distinct feature in FMD2. Problem with gonadal development and disorders of sexual development (DSD) have not been previously chracterized. Here we report three syndromic cases of 46,XY DSD with CSCF or FMD2, each carrying a novel heterozygous missense variants in MAP3K7 (NM_145331.3:c.250G>A; p.V84M, NM_145331.3:c.195A>G; p.I65M, and NM_145331.3: c.574A>G; p.S192G). The DSD phenotypes include cryptorchidism, micropenis, small testis, and hypospadias. In silico tools predict all three variants are deleterious. All three MAP3K7 variants occur in the kinase domain at highly conservative positions among mammals. MAP3K7 is highly expressed in human fetal Sertoli cells. MAP3K7 knock-out in HEK293T cells led to downregulation of GATA4 and FOG2 expression by RNA-Seq. Like MAP3K1, MAP3K7 phosphorylated p38 while all three MAP3K7 variants did not alter phosphorylated p38 compared to wildtype in HEK293TMAP3K7-/- cells. Two MAP3K7 missense mutants (p.V84M and p.I65M) ectopically activate ovarian beta catenin/ Wnt signalling in TOPFLASH assays. Our data suggest that MAP3K7 contributes to male sex differentiation by increasing expression of pro-testis genes GATA4 and FOG2 in HEK293TMAP3K7-/- cells and antagonizing pro-ovarian beta-catenin signalling, and that one or more of these activities were likely affected in 3 cases of 46,XY DSD with CSCF/FMD2 during sex development.

Yield of reported results from genetic testing provides a proximal measure of clinical usefulness. While ACMG/AMP guidelines provide representations of uncertainty for individual genetic variant classification, additional factors are considered when determining whether results explain a patient's presentation. To standardize cross-consortium analysis, a working group of the Clinical Sequencing Evidence-Generating Research (CSER2) consortium iteratively identified factors used when contextualizing variant-level results to case-level interpretation (i.e., interpretation of an individual's genetic data with respect to the indication for testing). Sites independently categorized results; complex cases were discussed collaboratively, leading to revision of classification categories. Our metric incorporates factors beyond classification of reported variants. Analogous to variant-level results, "Definitive Positive" and "Probable Positive" represent certainty that results may be clinically explanatory. The category "Inconclusive" applies when results may or may not fully explain the patient presentation, with subdivision into multiple (non-exclusive) subcategories. Cases falling outside all of the other categories are considered "Negative". The overall diagnostic yield by this metric and use of categories for inconclusive results varied by CSER project, in part paralleling study design differences. This case-level categorization provides a meaningful assessment of diagnostic yield, and for inconclusive cases identifies potentially resolvable factors for case resolution.

PurposeDiagnostic yield from exome and genome sequencing varies widely across studies. It remains unclear how much of this variation reflects patient-level factors (e.g., sex, clinical features, race/ethnicity, genetic ancestry) versus site-level practices such as sequencing modality or variant interpretation workflows. We aimed to quantify the contributions of these factors to diagnostic outcomes across five U.S. clinical sequencing sites. MethodsWe performed a cross-sectional analysis of 3,008 prenatal, neonatal, and pediatric cases from the NHGRI Clinical Sequencing Evidence-Generating Research (CSER) consortium (2017-2023). Clinical indications spanned neurodevelopmental, neurological, immunological, metabolic, craniofacial, skeletal, cardiac, prenatal, and oncologic presentations. Genetic ancestry was inferred from sequencing data, and variants were interpreted using ACMG/AMP guidelines to classify DNA-based diagnoses. Generalized linear mixed models were used to estimate associations between diagnostic yield and fixed effects (sex, prenatal status, isolated cancer, number of clinical indications, sequencing modality, race/ethnicity, and genetic ancestry), while modeling study site as a random effect to quantify between-site variation. ResultsThe overall diagnostic yield was 19.0%. Multiple clinical indications (OR=1.47, 95% CI 1.20-1.80, p<0.001) were associated with higher diagnostic yield, and male sex (OR=0.80, 95% CI 0.66-0.96, p=0.017) and prenatal status (OR=0.63, 95% CI 0.44-0.90, p=0.012) were associated with lower yield. Sequencing modality, race/ethnicity, genetic ancestry, and isolated cancer were not statistically significantly associated with diagnostic outcomes.. A model without fixed effects attributed [~]10% of variance in diagnostic yield to between-site differences. After adjusting for covariates, site-level variance decreased to 5.7%, indicating consistent variation across sites not explained by measured patient factors. ConclusionAcross five sites, patient-level clinical features influenced diagnostic yield, but substantial site-level variation remained even after adjustment. Differences in variant interpretation, or case-classification practices may contribute to this residual variability. Further efforts to increase consistency in exome- and genome-sequencing diagnostic workflows may help reduce inter-site differences.

Objectives: Diabetes affects over 500 million people globally and glycemia is inadequately managed. Metformin is the most frequently prescribed initial treatment for type 2 diabetes globally, yet glycemic response trajectories to metformin in routine real-world care and predictors of treatment response have not been well described. We aimed to identify glycemic response trajectories in adults prescribed metformin monotherapy as initial type 2 diabetes treatment and predictors of poor glycemic response to metformin. Design: Observational cohort study using latent class mixed models to identify hemoglobin A1c (HbA1c) trajectory classes, followed by random forests machine learning to predict trajectory class membership. Setting: US Veterans Affairs Healthcare System Participants: Adults treated with metformin alone for >30 days after diabetes diagnosis with a minimum of two HbA1c measurements from 90 days prior to two years after the first metformin prescription (N=140,413). Exposures: Demographic, laboratory, vital sign, and comorbidity data were included as predictors of metformin response trajectory Main Outcomes and Measures: We included all HbA1c measurements (487,604 total) for two years after metformin initiation to define metformin glycemic response trajectories. Results: We identified three HbA1c trajectories: stably low (89.7% of sample, mean HbA1c decrease from 7.2% to 6.6%), brisk response (7.1% of sample, mean HbA1c decrease from 11.4% to 7.0%), and non-response (3.1% of sample, mean HbA1c increase from 8.9% to 10.8%). Of those in the stably low and brisk response classes at 2 years, 91% maintained HbA1c at approximately 7% on metformin alone for 5 years after drug initiation. Prediction models could accurately predict brisk response (91% accuracy) but not metformin non-response (59% accuracy). Conclusions: Most individuals treated initially with metformin monotherapy have a beneficial and durable glycemic response. Predicting individuals who will not respond to metformin may be challenging but is evident within six months with recommended glycemic surveillance. The findings support current guidelines for HbA1c surveillance when initiating diabetes treatment.

Purpose Patients carrying Germline Pathogenic Variants (GPVs) in multiple cancer susceptibility genes (CSGs) can be described within the context of Multi-locus Inherited Neoplasia Allele Syndrome (MINAS). The role of each GPV is typically interpreted based on clinical phenotypes. Here, we used tumor sequencing, particularly mutational signatures, to investigate the contribution of GPVs in MUTYH and PALB2 to colorectal polyposis and breast cancer in a single patient at a molecular level. Methods We analyzed tumor sequencing data, including mutational signatures and genomic scars, of a breast tumor and a colorectal polyp from a patient with biallelic GPVs in MUTYH and a heterozygous GPV in PALB2. Results The colorectal polyp showed a dominant contribution of MUTYH-associated Base Excision Repair deficiency (BERd) mutational signatures, with no evidence of Homologous Recombination Repair Deficiency (HRD). In contrast, the breast tumor showed both MUTYH-driven BERd and HRD-associated signatures, including SBS3, ID6 and an elevated HRD score, despite the absence of a detectable second hit in PALB2. These findings suggest a differential contribution from the CSGs, with MUTYH contributing to both lesions and PALB2 contributing specifically to the breast tumor. The observed pattern does not align with the additive or synergistic models described in MINAS. Conclusions Our study provides evidence that mutational signatures can elucidate the contribution of multiple CSGs to tumorigenesis within a single patient. These findings extend current interpretations of MINAS beyond additive or synergistic phenotypes, which may help to better understand tumor etiology, with potential clinical implications, including eligibility for targeted therapies.

Purpose. Periodic reanalysis of genome sequencing data can yield additional diagnoses as knowledge evolves, yet manual reanalysis is labour-intensive. We compared automated and manual reanalysis approaches in rare disease genomics. Methods. We reanalyzed 377 rare disease cases: 158 with pathogenic or likely pathogenic (P/LP) findings, 49 with variants of uncertain significance (VUS) findings, and 170 had no findings. Manual reanalysis used standard diagnostic workflow for all cases without prior P/LP diagnoses (219 cases). An automated pipeline using Talos was benchmarked on the 158 P/LP cases before application to the 219-case reanalysis cohort. The mean reanalysis interval was 660 days. Results. Manual reanalysis identified three additional P/LP cases and two newly classified as VUS, increasing P/LP cases from 158 (41.9%) to 161 (42.7%). Talos recovered all three P/LP findings but only identified one of the two new VUS findings. Benchmarking showed 80.0% singleton concordance and 75.2% (82.8% proband-only) trio concordance, with approximately three variants per case. Conclusion. Reanalysis at 1.8 years yields modest but clinically meaning- ful gain. Automated reanalysis closely approximates manual performance while reducing hands-on effort, supporting scalable reanalysis in routine genomic care. Keywords: rare disease genomics, genome sequencing, automated reanalysis, variant prioritization, Talos, diagnostic yield

BackgroundA vision of lifelong genomic medicine, in which stored genomic data can inform a lifetime of care has long animated the field of genomic medicine. Component pieces of this vision are being researched or are already in clinical practice, including dozens of projects around the world sequencing healthy newborns, along with reanalysis of stored genomic data. Whether lifelong genomic medicine is desirable, and, if so, whether it is feasible, has not been explored in the literature. Methods and FindingsWe conducted and thematically analyzed interviews with over 50 US-based healthcare professionals, including clinical geneticists, genetic counselors, primary care clinicians, laboratory personnel, and those who have implemented genomic screening in health systems. We found broad endorsement of the value of lifelong genomic medicine across groups. Perceived clinical value stemmed from the existence of genomic information relevant at multiple stages of life, the ability to query the genome if an individuals medical circumstances change, and the ability to inform patients about relevant evolving scientific advances. Participants also articulated an efficiency argument for reanalyzing stored genomic data rather than retesting. The clinical value was contested by a few participants, who argued for more targeted testing for the clinical situation and disputed the efficiency argument. Many participants viewed the model as inevitable, with operational precedent already established for many component activities. The feasibility of lifelong genomic medicine was limited not by scientific barriers but by governance gaps spanning delivery models, consent, data stewardship, recontact, and the pediatric-to-adult transition. These gaps have equity implications that are cumulative and mutually reinforcing. ConclusionsThe concept of lifelong genomic medicine was widely viewed as acceptable and desired. However, until the governance infrastructure is established, including accountability, funding, data stewardship, and recontact mechanisms, population-scale genomic sequencing risks proceeding faster than the frameworks needed to make it responsible.

ObjectivesIt is not known which clinical features optimally differentiate type 1 and 2 diabetes at diagnosis. We aimed to determine which clinical features differentiate adult-onset type 1 and 2 diabetes at diagnosis and develop classification models combining these features with and without islet-autoantibodies. DesignA prospective cohort study with prediction model development and validation. SettingUK primary and secondary care. Participants1800 adults ([&ge;]18 years) diagnosed with diabetes in the previous 12 months, excluding known secondary or monogenic diabetes. Main outcome measuresType 1 and 2 diabetes defined by a combination of insulin treatment and endogenous insulin production (measured using C-peptide) assessed [&ge;]three years after diabetes diagnosis. ResultsEleven clinical features and routinely measured biomarkers discriminated type 1 from type 2 diabetes independently of diagnosis age and BMI. Lower age-at-diagnosis, BMI and waist-hip ratio, unintentional weight-loss, and higher presentation HbA1c or glucose were the most discriminative features, with other features only weakly discriminative. Models integrating clinical features with and without islet-autoantibodies, developed in those age 18-50 years at diabetes diagnosis, had high performance in internal validation (clinical features only: AUCROC (95% CI) 0.94 (0.93, 0.96), clinical features and islet-autoantibodies: AUCROC 0.97 (0.96, 0.98)), and maintained high discrimination in older adults (age >50 at diagnosis; clinical features only: AUCROC 0.93 (0.90, 0.96), clinical features and islet-autoantibodies: AUCROC 0.97 (0.94, 0.99)). Simplifying the models to a point-based score (the StartRight Score) resulted in similar performance. These models had higher performance than current clinical guidance. In UK primary care data models were strongly predictive of outcomes associated with type 1 diabetes, including in those initially treated as type 2 diabetes. ConclusionsLower age-at-diagnosis, BMI, and wait-hip ratio, unintentional weight-loss and high presentation glycaemia are the most discriminative features for diagnosis of type 1 diabetes in adults. Models combining routine clinical features, with or without islet-autoantibodies, have high accuracy and could assist clinical classification and prioritisation of classification biomarker testing. Study registrationhttps://clinicaltrials.gov/study/NCT03737799 Summary boxesO_ST_ABSSection 1: What is already known on this topicC_ST_ABSO_LIMost type 1 diabetes occurs in adults, but differentiating it from type 2 diabetes, which is much more common, is challenging, and misclassification is common. C_LIO_LIAge-at-diagnosis and BMI are currently the only clinical features robustly shown to distinguish between type 1 and type 2 diabetes at diagnosis; many other features included in textbooks and guidelines have little supporting evidence. C_LIO_LIGuideline bodies, including the UK National Institute for Health and Care Excellence (NICE), have identified a need for evidence on what features discriminate type 1 and 2 diabetes in adults, and how these features can be combined to improve diagnosis. C_LI Section 2: What this study addsO_LIThis is the first study to prospectively assess the utility of clinical features for diabetes subtype at diagnosis. C_LIO_LIThe five most discriminative routine clinical features for distinguishing type 1 from type 2 diabetes at diagnosis are age-at-diagnosis, BMI, waist-hip ratio, pre-diagnosis unintentional weight-loss, and presentation glycaemia (HbA1c or glucose). C_LIO_LIMany features included in current guidelines were only very weakly discriminative of subtype, and no single clinical feature was able to adequately differentiate between type 1 and type 2 diabetes alone. C_LIO_LIA clinical prediction model combining ten routinely available clinical features, with or without islet-autoantibodies, as both a prototype calculator and a points-based score (the StartRight Score), had high accuracy in differentiating type 1 from type 2 diabetes and outperforms current clinical guidance and islet-autoantibody assessment alone. C_LI

Interpreting HNF1B variants is challenging in clinical practice. We aimed to integrate functional, clinical, and family data to improve variant classification, describe clinical features of carriers and report registry-level prevalence of HNF1B alterations. Clinical, genetic, and family data were analyzed from the Norwegian MODY Registry (NMR) and the Norwegian Childhood Diabetes Registry (NCDR). Clinical features of sequence variant and 17q12 deletion (17q12del) carriers were summarized, and variants were classified using ACMG-AMP-ClinGen criteria. Registry-level prevalence was reported with 95% confidence intervals. HNF1B sequence variants were functionally assessed, showing that the lower transactivation (TA) was associated with higher clinical severity. Eleven variants demonstrated impaired functional activity, with TA inversely correlated with clinical burden ({varrho} = -0.701, p = 0.002). We identified 28 individuals with 17q12del (21 in NMR, seven in NCDR) and 15 individuals carrying 14 unique (LP/P) sequence variants, all detected in the NMR. Overall, 36/486 probands (7.4%) with genetically confirmed monogenic diabetes in the NMR carried an LP/P HNF1B sequence variant or 17q12del. In the NCDR, [~] 0.2% carried 17q12del (7/3,583; 3/7 GADA/IA-2A-positive). Functional data enabled reclassification of three variants. Since many pediatric 17q12del carriers in the NMR were referred for testing due to structural renal anomalies without diabetes, HNF1B screening should be considered in children with renal/extra-renal features, irrespective of diabetes or autoantibody status. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/26348894v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@41feforg.highwire.dtl.DTLVardef@ccc48borg.highwire.dtl.DTLVardef@17ba2e9org.highwire.dtl.DTLVardef@4919b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Despite the multidimensional value of implementing genomic medicine, in terms of diagnostic yield, cost-effectiveness, and optimisation of care trajectories, its deployment in many African countries, including Algeria, remains constrained by major structural and interpretive challenges, compounded by the persistent underrepresentation of African populations in genomic databases with direct consequences for variant interpretation and clinical decision-making. We implemented a fully in-house whole-exome sequencing (WES) workflow structured through a clinically driven sequential framework in 14 unrelated patients with unexplained neurodevelopmental disorders, in a context of high consanguinity and enriched recessive inheritance. A definitive molecular diagnosis was established in 8 cases, with pathogenic or likely pathogenic variants identified in MECP2, PTPN11, FOXG1, ARV1, GNAO1, ATM, ROBO3, and CHD3. Five cases yielded variants of uncertain significance and one clinically relevant incidental finding was identified. Beyond its diagnostic contribution, this study reveals persistent interpretive limitations: a disproportionate VUS burden, complex incidental finding management, and reduced accessibility to classification criteria, reflecting database underrepresentation, the predominance of private variants, and the limits of current frameworks in consanguineous settings. These findings underscore the necessity of population-specific reference datasets, iterative phenotyping, adapted ethical frameworks, and strategies addressing territorial disparities in access. This work demonstrates that WES implementation requires a structured multidisciplinary ecosystem integrating clinical, bioinformatic, and ethical dimensions, and provides a transferable model for the sustainable integration of genomic medicine in under-resourced settings, while highlighting the global scientific value of incorporating underrepresented populations into genomic research.