Congenital microcephaly and lissencephaly spectrum disorders are characterized by disrupted neuronal proliferation and migration, often driven by underlying genetic variants. Here, we identified and characterized of a novel gene (Tetratricopeptide Repeat Domain 14, TTC14) and its homozygous missense variant (c.89 A > G; p.His30Arg (p.H30R)) in a female proband presenting with microcephaly, epileptic spasms, global developmental delay, and neuroimaging features of simplified gyral pattern, focal pachygyria, and corpus callosum thinning. Trio-based whole exome sequencing revealed this variant to be rare and autosomal recessively inherited from both asymptomatic parents. Structural modeling demonstrated that H30 lies at the start of an α-helical region and is evolutionarily conserved. The p.His30Arg substitution caused significant steric clashes and disrupted local folding. Interaction network analysis and molecular dynamics simulations confirmed structural destabilization, increased conformational flexibility, and loss of stability in the mutant protein. While mRNA and protein levels remained unaltered, the TTC14-p.His30Arg protein mislocalized from the nucleus to the cytosol and formed aggregates. Functionally, proband fibroblasts exhibited increased cell death and altered cell cycle progression. TTC14 interacts with RNA splicing and mRNA processing proteins, and gene ontology analysis implicated it in RNA binding and spliceosomal complex assembly in key brain regions including the cerebral cortex, hippocampus, and white matter. These findings collectively suggest that TTC14 plays a crucial role in RNA metabolism during neurodevelopment, and that the p.His30Arg variant impairs its function, possibly leading to a neurodevelopmental disorder within the lissencephaly spectrum. This study identifies TTC14 as a likely pathogenic candidate gene in cortical malformation syndromes.

Facioscapulohumeral muscular dystrophy (FSHD) is a common hereditary neuromuscular disorder. The Russian FSHD Patient Registry was established in 2019 following the development of a PCR-based method for genetic confirmation of the diagnosis. The registry included 491 participants, of whom 51% were male. The mean age was 38.2 years (range 0-97 years), indicating a younger cohort compared to international data. Genetic confirmation of FSHD type 1 or type 2 was achieved for 76% of participants (n = 373). The remaining participants had not yet undergone genetic testing and were included based on clinical and anamnestic data. D4Z4 repeat units (RUs) ranged from 1 to 10, with equally predominant 3, 5, and 6 RUs, making our cohort more similar to Asian cohorts published earlier. Clinical assessment forms and patient-reported questionnaires were analyzed for 279 and 134 patients with genetically confirmed diagnoses, respectively. A moderate inverse correlation was found between RU number and clinical severity scales. Shoulder girdle weakness was the most common onset manifestation (45.2%), followed by facial weakness (34.4%). A delta-adjusted cluster analysis (n = 187) identified three distinct disease progression trajectories based on the temporal pattern of muscle involvement. The smallest cluster comprised patients with very slow progression, in whom facial muscle involvement occurred at late stages. The Russian FSHD registry provides a comprehensive characterization of a large national cohort, revealing a D4Z4 repeat unit distribution similar to Asian countries and a younger demographic profile than reported in international data. Cluster analysis identified three distinct disease progression trajectories, offering a valuable framework for improved patient stratification.

The Mulam people, an ethnic minority group native to southern China, primarily inhabit the Guangxi region. Systematic whole-genome studies on the Mulam population remain limited. In this study, we analyzed genome-wide genotyping data comprising over 700,000 single-nucleotide polymorphisms (SNPs) derived from 107 saliva samples of Mulam individuals in Guangxi, to investigate their genetic origins and relationships with other southern East Asian populations. Based on ancestry inference and population genetic analysis, we identified three major ancestral components in the Mulam genome: ancient Yellow River farmers, indigenous southern East Asian populations, and Austronesian-related groups. These results support historical records indicating that the proto-Mulam were formed through the integration of ancient Yellow River migrants with indigenous southern East Asian communities. Furthermore, shared southern East Asian ancestry reveals a genetic link between the Mulam and Taiwanese indigenous peoples, likely resulting from prehistoric southward population movements. This study emphasizes the complex genetic makeup of the Mulam people and offers new perspectives on population history and dynamics in East Asia.

Melatonin exerts pleiotropic physiological functions and diverse disease associations, but its genetic architecture remains largely uncharacterized. Using low-coverage whole-genome sequencing (lcWGS) in 3,605 Han Chinese adults, we identified four independent loci (P < 1 × 10[-7]) associated with circulating melatonin (pg/mL)-located within or near LINC01807, PTPRD, EDIL3/NBPF22P, and LMO1/STK33. Conditional analyses indicated that the STAARpipeline single-variant and sliding-window signals were largely driven by these genome-wide association study (GWAS) lead variants, whereas a gene-centric noncoding aggregation signal in the ZSWIM9 promoter region remained independent. These genes showed tissue-specific expression in neural, vascular, and adrenal tissues (GTEx). The heritability of serum melatonin was estimated at 21.72% (SE = 11.2%, P = 0.029) using GCTA-GREML, with the four independent significant loci collectively explaining 3.40%. Genetic risk score and one-sample Mendelian randomization analyses suggested a protective effect of higher serum melatonin levels on hypertension risk (OR = 0.45, P = 0.015), as well as on systolic (β = - 4.14, P = 0.014) and diastolic blood pressure (β = - 3.10, P = 0.007). Summary-data-based Mendelian Randomization and colocalization analyses suggested that LMO1 and PTPRD may influence hypertension through tissue-specific expression and DNA methylation. These findings reveal novel genetic contributors to melatonin regulation and establish their putative causal relationship with hypertension.

Alpha thalassemia is a common inherited blood disorder worldwide, with varying prevalence among different populations. This study investigates the prevalence and spectrum of alpha thalassemia deletions in the Oraon tribe, one of the largest indigenous populations in central-eastern India. Two hundred and twenty-seven Oraon individuals were genotyped using multiplex PCR for seven common alpha-globin gene deletions and triplications. Hematological profiling was performed on automated cell counter. A high frequency of alpha globin gene deletions was observed in the Oraon population, with the -α[3.7] deletion being predominant. The homozygous -α[3.7]/-α[3.7] genotype was found in 32.6% of Oraons, significantly higher than in other tribes. Compound heterozygosity (-α[3.7]/-α[4.2]) was also common (15.4%). Hematological analysis revealed significant differences between genotypes, with -α[4.2]/-α[4.2] individuals displaying lower hemoglobin levels. One individual with HbH disease (--[SA]/-α[3]·[7]) was identified with characteristic hematological features. The high prevalence of alpha thalassemia deletions in Oraons may reflect historical malaria selective pressure. These findings have important implications for public health strategies and clinical management of hemoglobinopathies in this community. The study underscores the genetic complexity of alpha thalassemia in indigenous populations and highlights the need for comprehensive screening approaches. Further research including non-deletional mutations is needed to provide a complete spectrum of α-thalassemia in this population.

Weiss-Kruszka syndrome (WSKA; OMIM 618619) is a rare autosomal dominant neurodevelopmental disorder caused by haploinsufficiency of ZNF462, a zinc-finger transcription factor involved in chromatin regulation and early embryonic development. WSKA is characterized by developmental delay, hypotonia, craniofacial dysmorphic features (around 8) and variable congenital anomalies. Genome-wide DNAm profiling was performed on peripheral blood DNA from 9 WSKA cases with (likely) pathogenic ZNF462 variants and matched controls to look for differential methylation. Analysis using the EpiSign™ pipeline identified a robust DNAm pattern, or episignature, specific to WSKA syndrome. Supervised machine-learning classification demonstrated high sensitivity and specificity, with reproducibility confirmed by leave-one-out cross-validation, as well as correctly classifying a validation case with a pathogenic ZNF462 variant. Comparative analysis revealed partial overlap of genome-wide DNA methylation changes between the WSKA episignature and other neurodevelopmental disorders involving chromatin regulators. Functional annotation of differentially methylated probes and regions demonstrated enrichment for pathways related to neurodevelopment, neuron function and cell adhesion. These findings define and validate a distinct DNAm episignature for WSKA, providing a valuable diagnostic biomarker to support variant classification and offering insight into the epigenomic consequences of ZNF462 haploinsufficiency.

Pathogenic variation of SLC26A4 gene causes both Pendred syndrome (PDS) and non-syndromic enlarged vestibular aqueduct (NSEVA/DFNB4), two autosomal recessive disorders. The former accounts for approximately 6% of human genetic hearing loss, making it the second most common form of syndromic deafness after Usher syndrome, while the latter is the most common radiological malformation associated with childhood sensorineural hearing loss (SNHL). Here, we used short- and long-read single-cell RNA sequencing (scRNA-seq) of pendrin-expressing cells in the murine cochlea to identify a novel short isoform of Slc26a4. We demonstrate that the short Slc26a4 isoform is expressed in both the inner ear and kidney and investigate its interactions and functions. We also characterize the genotype-phenotype association for SLC26A4-related hearing loss in the context of these two isoforms. These results provide a new reference for molecular profiling of pendrin and offer novel insights into cell-type-specific splicing events and SLC26A4-related hearing loss.

Exome sequencing (ES) has become a primary tool for diagnosing neurodevelopmental disorders (NDDs), yet the interpretation of genetic variants in large, heterogeneous cohorts presents significant challenges that automated pipelines often fail to resolve. This study showcases the complexities and novel findings derived from a decade-long analysis of 419 Italian NDD patient-parent trios. While ES established a molecular diagnosis in 36.5% of cases (53.8% in syndromic presentations), our investigation moves beyond diagnostic yield to highlight the critical value of manual curation integrated with deep phenotyping. We demonstrate how this rigorous approach uncovers complex disease mechanisms, revealing that variants initially misclassified as missense or stop-gain are, in fact, pathogenic splicing defects confirmed by functional analysis. Furthermore, we resolve the paradox of pathogenic truncating PPM1D variants in control databases by demonstrating their somatic mosaic nature, a crucial insight for population data interpretation. Our work also refines gene-disease correlations by challenging the established role of MID2 in NDDs, providing further evidence for DSCAM as a high-confidence risk gene, and expanding the known phenotypic spectrum of disorders, such as a novel GNAI2-related syndrome lacking expected immune dysfunction. This study underscores that navigating the complexities of large NDD cohorts requires a detailed, expert-driven approach to not only enhance diagnostic yield but also to advance our fundamental understanding of rare disease genetics.

Rare undiagnosed diseases impose a substantial burden on patients, families, and health systems. Collectively they affect an estimated 300-350 million people worldwide. Of these, approximately 250 million live in low- and middle-income countries (LMICs). Many rare diseases have a genetic basis and can be diagnosed using molecular testing. However, patients in LMICs often lack access to advanced diagnostics and specialist care, leading to prolonged diagnostic odysseys and significant distress. To address this gap, the Global Genomic Medicine Collaborative (G2MC) implemented a Rare Disease Pilot Project to enable clinical genomic testing at six LMIC sites (Chile, Malaysia, Mexico, Nepal, South Africa, Sri Lanka). Using trio exome sequencing for 18 selected families, supplemented by chromosomal microarray as indicated, definitive molecular diagnoses were established in 5 families (pathogenic/likely pathogenic variants explaining the phenotype). An additional 8 families had suspected molecular diagnoses with strong phenotype correlation that require functional validation, while 5 families remained undiagnosed at the end of the pilot. The integration of genomic data into clinical decision-making enabled definitive diagnoses, precise management, and genetic counseling for these patients. The pilot also strengthened local capacity building by conducting cross-site case conferences and enabling local reanalysis of sequence data at sites with bioinformatics capabilities. This study demonstrates the feasibility, effectiveness, and adaptability of implementing exome sequencing in resource-limited settings and highlights its potential to transform rare disease diagnosis and care in LMICs.

Synonymous mutations, once regarded as silent, are increasingly recognized as pathogenic through disruption of mRNA splicing. Here, we report a prenatal case with classic features of Smith-Lemli-Opitz syndrome (SLOS), including increased nuchal translucency, enlarged kidneys, and fetal growth restriction. Whole-exome sequencing identified compound heterozygous DHCR7 variants: a previously reported missense variant, NM_001360.3:c.1220A > G (p.Asn407Ser), and a novel synonymous variant, NM_001360.3:c.963G > A (p.Gln321 =). Functional validation using minigene assays and patient-derived cDNA demonstrated that c.963G > A causes aberrant splicing, resulting in a premature termination codon and production of a truncated protein lacking the sterol-sensing domain, which contains multiple recurrent pathogenic missense sites. These findings establish the deleterious effect of this synonymous change, analogous to the well-characterized splice-site variant NM_001360.3:c.964 - 1G > C (historically referred to as IVS8 - 1G > C). In sum, this study provides the first definitive evidence that a synonymous DHCR7 variant can act as a likely pathogenic allele through splicing disruption. Moreover, it offers critical molecular insight and a refined framework for interpreting synonymous variants-particularly variants of uncertain significance-with important implications for clinical diagnosis, genetic counseling, and prenatal care.

Sindhis are an Indo-Aryan ethnolinguistic community primarily associated with the Sindh region of present-day Pakistan. The Sindhi community is celebrated for its vibrant culture, unique dialect, and notable accomplishments in commerce and the arts, reflecting a rich historical legacy. Following the partition of India in 1947, many Sindhis migrated from the Sindh region to India and around the world, establishing diaspora communities. Previous genetic studies on Sindhis have focused on those residing in Pakistan, with a notable lack of genome-wide research specifically addressing Indian Sindhis. In this study, we investigated the demographic history of Sindhi populations across India and Pakistan by analysing hundreds of thousands of biallelic markers from 113 Indian Sindhi individuals, alongside existing data from Pakistani Sindhis. Our allele frequency analysis revealed strong genetic connections between Sindhi populations in Pakistan and India. Haplotype-based assessments further confirmed recent shared ancestry between these groups and highlighted genetic similarities with neighbouring populations. Identity-by-descent (IBD) analyses reinforced the close genetic relationships between Indian and Pakistani Sindhis, as well as their ties to nearby Pakistani groups. Interestingly, analysis of Runs of Homozygosity (RoH) revealed distinct patterns of marriage practices, suggesting that Pakistani Sindhis exhibit higher homozygosity, likely due to the prevalence of consanguineous marriages. Additionally, local ancestry analysis identified a dominant ancestral component associated with modern populations of the Indus Valley region. The results illuminate the complex genetic structure of the Sapta-Sindhu region and trace the origins of Sindhi Diaspora communities back to the ancient region of Sindh.

A central challenge in polygenic risk prediction is measuring and controlling for confounding due to population stratification. Standard approaches include adjusting for leading principal components (PCs) of genetic variation and using linear mixed models in genome-wide association studies (GWAS). Evidence of adequate control is typically inferred from reductions in the linkage disequilibrium score regression (LDSC) intercept and the preservation of polygenic risk score (PRS) performance in within-sibling settings. Here, we investigate how the number of PCs included during GWAS/PRS construction relates to the loss of predictive performance when moving from population-based analyses to that of discordant sibling pairs (within-sibling attenuation). This design detects confounding arising from environmental and genetic background effects correlated with population structure. Analyses were performed in the self-identified White subset of the UK Biobank (UKB) for coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer, with educational attainment included as a comparison trait as it is known to exhibit substantial within-sibling attenuation. We find that increasing the number of PCs does not consistently reduce within-sibling attenuation across traits. Furthermore, reductions in attenuation do not closely correspond to decreases in the LDSC intercept, and mixed model-based methods offer little additional improvement in prediction or attenuation. Overall, our results suggest that confounding targeted by PC-adjustment and linear mixed models is either minimal in the UKB, or remains inadequately captured by current methods, reflecting limitations as to how much standard population structure correction improves the causal validity of PRS in the UKB.

Chromosomal triplications are rare structural variations often associated with complex phenotypes. We report the molecular characterization of a novel intrachromosomal triplication at 18q12.1q21.2 identified in a fetus with ultrasound abnormalities. Conventional karyotyping and array-CGH revealed a partial tetrasomy and a 26 Mb region of loss of homozygosity (LOH), extending from the triplication to the telomere. Long-read sequencing (LRS) identified breakpoint junctions revealing a direct-inverted-direct triplication structure. Breakpoint analysis suggested that this rearrangement arose through a U-type exchange between sister chromatids, likely mediated by microhomology-based mechanisms. This process likely generated a transient dicentric chromosome that subsequently broke during mitosis. The resulting duplicated chromosome may have been stabilized by telomere capture, consistent with the triplicated 18q12.1q21.2 region followed by the 18q21.2q23 LOH. Nine genes within the triplicated region, including SMAD2 and SMAD4, showed high predicted sensitivity to increased dosage, possibly contributing to the clinical phenotype. This study highlights the utility of LRS in defining complex chromosomal rearrangements and emphasizes the importance of molecular breakpoint analysis for understanding pathogenic mechanisms and improving genetic prenatal diagnosis.

A missense variant of adenylate cyclase 7 (AC7), p.Asp439Glu, has been significantly associated with ulcerative colitis (UC) in genome-wide association studies. Previous work suggested that this variant is reduced in expression and exhibits impaired cyclic adenosine-3',5'-monophosphate (cAMP) synthesis, thus skewing T-cell cytokine profiles. Here, we investigated the variant's function measuring dynamic cAMP responses in live HEK293 cells. We show that p.Asp439Glu generates significantly reduced basal cAMP levels despite normal expression. Stimulation with sphingosine-1-phosphate (S1P) and phorbol 12-myristate 13-acetate (PMA) induced a reduced cAMP increase in cells expressing mutant AC7, indicating reduced responsiveness to G-protein-coupled receptor (GPCR) and protein kinase C (PKC) activation. Western blot analysis showed altered downstream phosphorylation of cAMP response element-binding protein (CREB) and cAMP-dependent transcription factor (ATF1) in cells expressing the variant. Higher levels of phosphorylated CREB and ATF1 were observed in cells expressing p.Asp439Glu AC7 under basal conditions while stimulation with S1P had no effect on protein phosphorylation. Our findings provide direct biochemical evidence for strongly impaired AC7 function caused by the variant p.Asp439Glu. These results may pave the way for more causally defined and genotype-specific treatment strategies in UC.

While falling costs have expanded access to genomic sequencing, clinical utility is frequently hindered by the challenge of interpreting complex genetic data. Variant analysis for rare disease patients especially requires significant time and expertise, creating a bottleneck that delays diagnostics. Although advances in genetic variant classification have improved diagnostic precision, they have also increased the identification of variants of uncertain significance (VUSs), widening the interpretation gap between data generation and clinical actionability. The high prevalence of VUSs can lead to false reassurance or psychological distress by misinterpretting inconclusive results. We propose that artificial intelligence (AI) is a critical clinical decision-support tool for bridging this gap, offering a scalable framework to optimize variant interpretation and shorten the diagnostic odyssey. While reclassification ultimately requires biological evidence that AI cannot replace, these tools serve as essential aggregators and prioritizers, especially as guidelines transition toward the upcoming quantitative ACMG v4 framework. We advocate integrating AI throughout the genetic diagnostic workflow-from initial phenotyping to variant prioritization-to facilitate data-driven, personalized treatment. We outline current AI-assisted approaches and discuss anticipated challenges in this pursuit, such as privacy, training data bias and quality, model explainability, and the necessity of a total product life cycle for validation. To address these challenges, we provide recommendations for "human-in-the-loop" design and intuitive workflow integration to ensure AI tools meet the highest standards of precision, reproducibility, and transparency to maximize adoption. By standardizing AI across the variant analysis pipeline, we can fast-track the path to genetic diagnoses, effectively bridging the interpretation gap and enabling rapid delivery of personalized medical interventions.