Genetics in Medicine Open

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.

Next-generation sequencing has unraveled the genetic cause for many individuals with a rare disease, but a significant number of individuals remain undiagnosed using standard of care tests. It is anticipated that structural variants (SVs) have not been fully assessed in this context. Here, we performed optical genome mapping (OGM) for 57 trios and prioritized SVs using a two-step approach. First, we systematically identified all de novo SVs, and subsequently we studied all rare inherited SVs. Potential pathogenic SVs were confirmed using orthogonal methods. On average, we identified 6,289 SVs >500bp per proband, primarily insertions (69.8%) and deletions (27.1%). In total, we identified 13 de novo SVs, confirming a de novo mutation rate for large SVs of 0.23 or 1 in 4-5 cases. These de novo SVs impacted multiple (candidate) disease-associated genes, including NSF and FGF9. Additionally, on average per sample, we identified 11 rare inherited SVs overlapping with an established OMIM disease gene or its regulatory region, including a homozygous deletion affecting SCN9A causing congenital indifference to pain, a maternally inherited deletion in WWOX causing developmental and epileptic encephalopathy, and an interchromosomal insertion in the CMTX3 locus at Xq27.1 causing X-linked Charcot-Marie-Tooth disease. In total, we identified pathogenic SVs in three individuals and candidate disease-causing SVs in five other individuals. Overall, OGM enabled the accurate detection of challenging de novo and rare inherited SVs. Our results suggest a potential yield of disease-associated SVs in 5-14% of index cases, demonstrating that OGM can unravel previously hidden SVs in extensively tested individuals.

Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive bone marrow failure, congenital malformations, and cancer predisposition. Early identification of individuals with FA is critical for timely clinical management, yet phenotype-driven approaches to FA identification are hindered by inconsistencies in existing phenotypic profiles. We compared the Human Phenotype Ontology (HPO) annotations for FA in OMIM (215 terms across 22 complementation group entries) and Orphanet (106 terms in a single entry, ORPHA:84), quantifying overlap and anatomical system coverage. To address identified gaps, we developed a comprehensive custom HPO profile by extracting phenotypic terms from the entire Fanconi Cancer Foundation (FCF) Clinical Care Guidelines using OntoGPT, an LLM-based ontology extraction tool, followed by manual curation to ensure accuracy and clinical relevance. OMIM and Orphanet shared only 36 HPO terms (12.6% of their combined 285 unique terms), demonstrating substantial discordance. Our custom profile comprises 264 unique HPO terms, of which 161 (61.0%) are novel and not present in either existing source. The novel terms expand coverage particularly in musculoskeletal (39 terms, 23.8%), genitourinary (26 terms, 15.9%), limb (26 terms, 15.9%), head or neck (20 terms 12.2%), and digestive system (17 terms, 10.4%) phenotypes. Community-curated phenotypic profiles derived from clinical practice guidelines can substantially augment existing disease annotations. Our FA profile, the most comprehensive HPO-based phenotypic characterization of FA to date, is publicly available and provides a foundation for improved clinical decision support and EHR-based computable phenotyping that can accelerate diagnosis for individuals with FA. Furthermore, the LLM-assisted approach offers generalizable methods to improve the diagnostic odyssey for all rare diseases.

ObjectiveTo evaluate the analytical and clinical performance of fetal fraction (FF) enriched genome-wide noninvasive prenatal testing (GW-NIPT) for detection of clinically relevant copy number variants (CNVs) down to 1 Mb. MethodsWe retrospectively analyzed 10,501 singleton pregnancies tested with FF enrichment-based GW-NIPT between August 2023 and July 2025. CNV analysis was performed using BinDel and WisecondorX. ResultsFF enrichment increased median FF to 24% (2.4-fold increase). Clinically relevant CNVs, including microdeletions and microduplications, were reliably detected down to 1 Mb. Performance was robust across all maternal body mass index (BMI) categories. The retest rate was 0.95%, resulting in a final no-call rate of 0.03% with no BMI-attributable failures. The workflow demonstrated high sensitivity, specificity, and positive predictive value for common aneuploidies, rare autosomal trisomies, sex chromosome aneuploidies, subchromosomal CNVs, and pathogenic mitochondrial DNA variants. ConclusionsFF enrichment enhances the analytical resolution of first-trimester GW-NIPT, enabling reliable detection of subchromosomal CNVs down to 1 Mb across diverse patient populations. This approach broadens the scope of prenatal screening while maintaining low test failure rates. All positive findings require confirmatory diagnostic testing and appropriate genetic counseling.

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.

Severe combined immunodeficiency (SCID) is a heterogeneous, recessive disorder, associated with the onset of severe, recurrent infections in the first few months of life. SCID is fatal if left untreated, but outcomes can be significantly improved by prompt diagnosis and treatment, particularly prior to onset of infection. Consequently, SCID is already included in many newborn screening programmes around the world, as well as multiple international genomic newborn screening (gNBS) research programmes. However, there is a vital need to estimate penetrance of SCID variants in population cohorts, to mitigate the potential consequences of reporting low penetrance variants in a genotype-first gNBS setting. This study aimed to assess the penetrance and prevalence of these variants in the UK Biobank population cohort. Whole genome sequencing data from 490,640 individuals was used to interrogate 16 SCID genes for potentially causal variation. We identified 4206 carriers of single heterozygous pathogenic variants ([~]1% of cohort), but only 6 individuals double heterozygous, homozygous or hemizygous for relevant pathogenic variants. 3 individuals would be expected to require further testing had they been identified by gNBS, suggesting that fewer than 1 in 100,000 newborns might require follow-up testing due to SCID variants. Following detailed variant curation, we were able to identify only 2 unabected individuals likely to be harbouring biallelic pathogenic variants, potentially indicative of reduced penetrance. Nonetheless, SCID remains an excellent candidate for inclusion in gNBS studies, due its severity, clinical actionability and expected low false positive rate, although care should be taken when reporting hypomorphic variants.

Copy number variants (CNV) contribute significantly to the pathogenic variation associated with developmental disorders. CNV detection is often not included in standard exome sequencing (ES) analysis. Complementary methods such as chromosomal microarray are typically offered in diagnostic laboratories to diagnose pathogenic CNV. In this study, we aimed to develop an optimal approach for incorporating CNV detection within our ES analysis process for the Deciphering Developmental Disorders in Africa (DDD-Africa) cohort. We analyzed ES data from 505 probands with a developmental disorder, applying a CNV detection approach that assessed data generated using the tools CANOES and XHMM. When available, parental ES data was used to assess inheritance patterns. We confirmed a diagnosis in 42/505 (8,3%) patients with 44 pathogenic CNV identified in the probands. There were 31 deletions and 13 duplications. Among the 27 probands with parental data, all identified CNV were de novo. The addition of CNV analysis to our ES analysis pipeline resulted in an 8.3% increase in diagnostic yield in the DDD-Africa cohort without additional laboratory cost. This approach offers a feasible approach which is likely to reduce analytical cost and is suitable for low- and middle-income countries where funding and resources for genomic medicine initiatives are limited.

BackgroundMitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA-based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis. RNA sequencing (RNA-seq) provides a complementary layer of evidence by revealing functional consequences of genetic variation, thereby improving diagnostic yield. MethodsWe performed RNA-seq on skin fibroblasts from 140 pediatric patients with suspected mitochondrial disease who remained genetically undiagnosed after whole exome sequencing (WES). Aberrant RNA expression and splicing were identified using the detection of RNA outliers pipeline (DROP). Based on WES findings, patients were stratified into a candidate group (n=28), in which RNA-seq evaluated the pathogenicity of WES-identified variants of uncertain significance and an unsolved group (n=112), in which RNA-seq was used to pinpoint candidate genes. In six cases where RNA-seq identified the aberrant RNA-event but WES did not detect the causative variants, whole genome sequencing (WGS) was performed. ResultsIntegrative RNA-seq, WES, and WGS analysis resulted in a genetic diagnosis in 25% of patients overall (20/28 [71%] in the candidate group; 15/112 [13%] in the unsolved group). Aberrant splicing explained most candidate-group diagnoses, including variants misclassified by in silico predictors such as SpliceAI. Fourteen percent of protein-truncating variants predicted to undergo nonsense-mediated decay (NMD) escaped degradation, highlighting the functional limits of current predictions. The variants identified in the unsolved cohort included synonymous, missense, deep intronic, near-splice-site variants, and large deletions. The most frequent amongst them was a recurrent synonymous East Asian founder mutation in ECHS1, accounting for seven cases. Interestingly, across 231 pathogenic variants associated with aberrant RNA phenotypes compiled from this study and prior reports, half were non-coding and half were coding variants. ConclusionRNA-seq substantially enhances molecular diagnosis in mitochondrial disease by exposing cryptic splicing, regulatory, and NMD-escape events invisible to DNA sequencing alone. These data advocate transcriptome analysis as an essential component of comprehensive genomic diagnostics in neuro-metabolic disease. Significance StatementMitochondrial diseases remain among the most challenging inherited metabolic disorders to diagnose, with nearly half of patients unresolved despite advanced DNA sequencing. By integrating transcriptome profiling into the diagnostic workflow, this study demonstrates that RNA sequencing can reveal pathogenic mechanisms invisible to exome or genome analysis, including cryptic splicing, regulatory variants, and transcripts that escape nonsense-mediated decay. The findings establish RNA-seq as a decisive bridge between genotype and phenotype, uncovering functional consequences of genetic variation and redefining molecular diagnostics for mitochondrial and other neuro-metabolic diseases.

BackgroundExome sequencing (ES) has become a key diagnostic tool for rare diseases (RDs). However, most evidence on ES performance comes from high-income countries and patients from European ancestry. In countries such as Chile, limited access to next generation sequencing amplifies health disparities and highlights the need to identify which patients are most likely to benefit from ES. MethodsThis study presents the second phase of the Chilean DECIPHERD project, in which we performed ES in a new group of patients with RDs presenting with multiple congenital anomalies (MCA), neurodevelopmental disorders (NDD), and/or suspected inborn errors of immunity. To identify clinical and demographic factors associated with an increased probability of obtaining an informative ES result, we conducted a logistic regression analysis, combining the results of the first and second phases of the project. We also objectively evaluated global ancestry measured using ADMIXTURE, as a potential factor. ResultsSixty-seven patients participated in this second phase of DECIPHERD with a median age of 6 years (range: 0-27); 55.2% were female, with an average ({+/-} s.d.) proportion of Native American ancestry of 0.615 {+/-} 0.18. Clinically, 52.2% presented with both MCA and NDD, and the rest had other phenotype combinations. An informative result, including pathogenic or likely pathogenic variants in genes consistent with the patients phenotype, was identified in 34.3% of the cohort; 61% of these variants had not been previously reported in databases such as ClinVar. By combining the two phases of the study, we reached a total of 167 patients, in whom the presence of NDD and/or MCA significantly increased the probability of achieving an informative ES outcome. In contrast, previous use of gene panel testing was associated with a decreased likelihood of receiving an informative result. Ancestry was not associated with diagnostic yield. ConclusionsThis study demonstrates the utility of ES in achieving a diagnosis in a clinically diverse cohort of Chilean patients with RDs, and characterized features associated with a higher diagnostic yield. These findings may contribute to evidence-based patient prioritization strategies in settings with limited access to NGS resources.

BackgroundEffective interventions are needed to support co-creation of diabetes care plans that fit patients lives. We evaluated the QBSafe agenda-setting kit (14 conversation cards) for its impact on care fit and glycemic control when added to usual primary care. MethodsThis single-center, clinician-level cluster-randomized, open-label trial was conducted at a federally qualified health center in New Haven, Connecticut (ClinicalTrials.gov NCT05553912). Clinicians and their patients with type 2 diabetes and HbA1c >8% were randomized 1:1 to usual care with or without QBSafe cards. In the intervention arm, patients selected up to 3 cards highlighting concerns about life with diabetes prior to their visit. Primary outcomes were change at 6 months in care fit (Illness Intrusiveness Ratings Scale, IIRS) and HbA1c, analyzed by intention to treat. Secondary outcomes were treatment burden (Treatment Burden Questionnaire, TBQ) and diabetes distress (Diabetes Distress Scale, DDS), and satisfaction with visits. ResultsBetween February 2023 and July 2024, 143 participants (mean age 56 years; 61% female; 73% Hispanic; mean HbA1c 10%) were enrolled: 74 received usual care with QBSafe, 69 usual care alone. At 6 months, there were no significant between-arm differences in changes in IIRS (-3.9 [95% CI -10.4, 2.6]), HbA1c (-0.2% [95% CI -0.9, 0.5]), TBQ (1.0 [95% CI -16.6, 18.6]), or DDS (-0.1 [95% CI -0.4, 0.2]). Clinicians reported greater satisfaction when using QBSafe. Patient satisfaction was high and did not differ across arms. ConclusionsQBSafe cards improved clinician satisfaction but did not improve care fit or glycemic control. Future tools should focus on helping clinicians respond effectively to patient-identified challenges.

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.

RNA sequencing (RNA-Seq) is increasingly used alongside exome and genome sequencing to identify causal variants underlying rare Mendelian disorders. We present short-read RNA-Seq data from 5,412 individuals with a diverse range of rare disorders recruited to Genomics Englands 100,000 Genomes Project. We show that the proportion of genes from gene panels applied to different disorders which are well captured (transcripts per million (TPM) [&ge;] 5) from blood RNA varies widely, highlighting differences in applicability across disorder types. Using OUTRIDER and FRASER2 to identify gene expression and splicing outliers respectively, we identify at least one outlier event in a disorder relevant gene in 20% of the cohort. To prioritise likely diagnostic candidates, we apply multiple strategies including focussing on outlier events in known haploinsufficient genes (n=78), integrating outliers with structural variant calls (n=19), and using strategies integrating phenotypic presentation (Exomiser, n=39). We present a series of candidate diagnoses involving diverse variant types and disease mechanisms, demonstrating the broad utility of RNA-Seq in identifying and prioritising diagnostic candidates in individuals with a variety of different rare conditions and no known genetic diagnosis. Our findings demonstrate that blood-based RNA-Seq can deliver clinically relevant findings across a broad range of rare disorders.

Systematic analysis of copy number variants (CNVs) in large datasets is challenging and there are limited studies of homozygous copy number losses in rare disease exome datasets. Here we leveraged the genomic uniqueness and relative under-representation of the Indian population in the current public genomic databases and identified 42,386 possible homozygous losses (median count 20 per individual, range 0 - 55; median size 2.95 kb, range 99 bp - 4.76 Mb) in a heterogeneous cohort of 2,021 individuals with suspected Mendelian disorders, who had undergone exome sequencing using 12 different capture kits in a resource-limited setting. Employing a genomic position loss-count based approach, we filtered 1,224 rare homozygous loss calls in 718 individuals (median count 1 per individual, range 0 - 22; median size 3.49 kb, range 121 bp - 4.76 Mb) for further analysis, thus significantly reducing the analysis burden. Clinical correlation and validation of these rare calls enabled 10 new diagnoses in 240 unsolved individuals with at least one filtered rare homozygous loss call. This, led to nearly two-fold increase in diagnosis owing to homozygous deletions in our cohort. Further analysis of the data and identification of additional affected individuals through collaboration led to identification of biallelic FILIP1 and FAM177A1 variants as causes of a syndromic arthrogryposis and a neuromuscular disorder respectively. Both these conditions have been recently proven as ultra-rare recessive disorders, thus validating our approach. We also show that biallelic loss-of-function TFCP2L1 variants cause chronic kidney disease and VPS36 variants cause a severe recessive neurodevelopmental disorder characterised by microcephaly, motor delay, agenesis of the corpus callosum, cerebellar atrophy, seizures, hypotonia, spasticity and early death. Overall, these results demonstrate a scalable approach to screen homozygous losses for improving diagnostic yield and discovering disease-genes in large exome cohorts.

Wolfram syndrome is a rare autosomal recessive disorder caused by pathogenic variants in the WFS1 gene, characterized by early-onset diabetes mellitus, optic atrophy, sensorineural hearing loss, arginine vasopressin deficiency, and progressive neurodegeneration. The condition selectively affects pancreatic {beta} cells and neurons via chronic endoplasmic reticulum (ER) stress, and no proven disease-modifying therapy currently exists. Diabetes mellitus is typically the first manifestation, presenting at a mean age of 6 years as an insulin-dependent phenotype with preserved C-peptide and negative diabetes-related autoantibodies. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are well-established agents in the management of type 2 diabetes, augmenting glucose-dependent insulin secretion, suppressing glucagon, slowing gastric emptying, and promoting satiety. Preclinical evidence further suggests that GLP-1 RAs preserve {beta}-cell mass, attenuate ER stress, and confer neuroprotective effects, properties of particular therapeutic relevance to Wolfram syndrome. We conducted a retrospective cohort study of 84 participants with genetically confirmed Wolfram syndrome and insulin-dependent diabetes mellitus enrolled in the Washington University Wolfram Syndrome International Registry and Clinical Study. Clinical data were extracted from medical records; for participants concurrently enrolled in the Tracking Neurodegeneration in Early Wolfram Syndrome study, longitudinal data were obtained from that source as well. Thirty-five percent of eligible participants had received a GLP-1 RA at some point during follow-up. We characterize the prevalence of GLP-1 RA use, documented rationale for initiation, observed effects on glycemic control and visual outcomes, adverse effects, and reasons for discontinuation. No statistically significant changes in hemoglobin A1c (HbA1c) or body mass index (BMI) were observed. Visual acuity declined significantly at two years, consistent with expected disease progression. Gastrointestinal adverse effects were common and contributed to frequent discontinuation. These observational data provide important clinical context and a foundation for future prospective trials evaluating GLP-1 RAs as a potential disease-modifying strategy in Wolfram syndrome.

Exome sequencing (ES) is a cornerstone of clinical genetic diagnosis, yet its application in pharmacogenomics remains limited. While some pharmacogenetic variants are detectable by ES, clinically relevant loci such as CYP2D6, UGT1A1, and HLA remain challenging. We present a robust, comprehensive method to derive a complete pharmacogenomic profile directly from standard ES data. Our method addresses primary limitations of ES for pharmacogenomics, including low coverage and structural complexity at critical loci. We analyzed 66 samples from diverse sources, targeting 217 variants across a panel of 23 pharmacogenes. The method was validated by comparing its results with reference samples from the Genetic Testing Reference Material Coordination Program, as well as with the Veridose Core+CNV assay(R) (Agena) and the Personal Medicine Profile assay(R) (GeneTelligence). HLA typing performance was assessed and confirmed through comparison with both the Immucor LIFECODES HLA-SSO kit and a clinical transplantation-grade HLA assay. This validation demonstrates that ES can provide a comprehensive pharmacogenomic profile in a single, streamlined workflow, facilitating seamless integration of pharmacogenomics into precision medicine.

1The T2T-CHM13v2.0 reference genome added previously uncharacterized genomic sequences and improved the accuracy of repetitive stretches compared to former human genome assemblies. By comprehensive allelic variation analysis and read mapping statistics from sequencing reads aligned to hg38 and T2T-CHM13 assemblies in samples encompassing different sequencing designs and ethnicity groups, we observed that T2T-CHM13v2.0 assembly significantly reduces the reference mapping bias (RMB) and increases read mapping precision at clinically relevant sites, including BRCA1 pathogenic variants. Further, we report the presence of sequence dissimilarities among reference genomes in the proximity of ClinVar annotated variants, suggesting the need for data re-analysis and potential redesign of probes targeting clinically relevant regions. Overall, these findings support the implementation of T2T-CHM13 reference for the improvement of sequencing data analyses in the clinical genomic setting.

BackgroundGenetic risk scores (GRS) for type 1 diabetes (T1D) have been developed primarily in European populations, limiting their generalisability across ancestries. Indians differ from Europeans in clinical characteristics of T1D and overall genetic architecture, yet systematic evaluation of T1D GRS performance in multi-regional Indian cohorts is lacking. MethodsThe study included 597 T1D patients and 3347 non-diabetic controls from different regions in India. Genotyping, imputation, quality control analysis, and construction of the 67-SNPs T1D GRS were performed using standardised pipelines. Discriminative performance was assessed using Receiver Operative Curve-Area under Curve (ROC-AUC) analysis, and optimal thresholds were derived using Youdens index. HLA-DQ diplotype frequencies were compared, and association analysis was conducted using multivariable logistic regression. FindingsT1D GRS showed consistent discriminative performance across Indian cohorts [ROC-AUC=0.84 (range=0{middle dot}78-0{middle dot}87)], supporting its comprehensive use for T1D classification in India. Notably, its performance was lower in islet cell autoantibody (IA) negative compared with IA positive T1D patients (ROC-AUC, 0{middle dot}75 vs 0{middle dot}85) and in adult-onset than in childhood-onset patients (0{middle dot}74 vs 0{middle dot}84). We observed a lower frequency of protective HLA-DQ diplotypes and a strong association of HLA-DQ81 containing diplotypes in childhood-onset T1D. Application of an India-specific T1D GRS score improved the sensitivity than the European cut-off. InterpretationT1D GRS is a valuable unified diagnostic tool in Indians, but its performance varies by islet cell autoantibody status and age at onset, likely reflecting population-specific HLA architecture. European-derived T1D GRS thresholds under-classify the genetic risk, highlighting the importance of ancestry-aware optimisation in Indians. FundingCDRC grant CDRC202111026 and CSIR Intramural Grant P50. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown that a 67-SNPs T1D genetic risk score (GRS) can distinguish T1D patients from non-diabetic controls and other forms of diabetes, but its performance varies across ancestries. Islet cell autoantibodies (IA) have important diagnostic value for classifying type 1 diabetes (T1D). However, their prevalence in India varies widely, with up to one-quarter of patients testing negative, limiting their clinical utility. Evidence supporting the use of the T1D GRS in India, combined with IA antibodies status is limited to a single cohort representing one linguistic group. The applicability of T1D GRS across multi-centric clinical settings has not been systematically evaluated. Added value of this studyThis study validates the 67-SNPs T1D GRS across multiple Indian cohorts representing major linguistic groups, supporting its use as a unified diagnostic tool. Differences in T1DGRS performance between childhood-and adult-onset T1D are linked to enrichment of protective HLA-DQ diplotypes in adult-onset disease, providing genetic insight into disease heterogeneity. The study also demonstrates that European-derived GRS thresholds systematically under-classify genetic risk in Indians and the population-specific threshold is essential. Implications of all the available evidenceThe European-derived T1D GRS can be applied across Indian clinical settings with consistent discriminative performance. However, its utility is influenced by islet cell autoantibody status and the age at onset of disease. Ancestry-aware threshold optimisation substantially improves diagnostic accuracy and is essential for equitable implementation of T1D GRS in Indians. Larger studies are needed to identify population-specific risk variants and further refine genetic tools for clinical diagnosis.