Next generation sequencing (NGS) is a rapidly developing area in genetics. Utilizing this technology in the management of disorders with complex genetic background and not recurrent mutation hot spots can be extremely useful. In this study, we applied NGS, namely semiconductor sequencing to determine the most significant osteogenesis imperfecta-related genetic variants in the clinical practice. We selected genes coding collagen type I alpha-1 and-2 (COL1A1, COL1A2) which are responsible for more than 90% of all cases. CRTAP and LEPRE1/P3H1 genes involved in the background of the recessive forms with relatively high frequency (type VII and VIII) represent less than 10% of the disease. In our six patients (1–41 years), we identified 23 different variants. We found a total of 14 single nucleotide variants (SNV) in COL1A1 and COL1A2, 5 in CRTAP and 4 in LEPRE1. Two novel and two already well-established pathogenic SNVs have been identified. Among the newly recognized mutations, one results in an amino acid change and one of them is a stop codon. We have shown that a new full-scale cost-effective NGS method can be developed and utilized to supplement diagnostic process of osteogenesis imperfecta with molecular genetic data in clinical practice.

Neuropathy is a serious and frequent complication of type 2 diabetes (T2DM). This study was carried out to search for genetic factors associated with the development of diabetic neuropathy by whole exome sequencing. For this study, 24 patients with long-term type 2 diabetes with neuropathy and 24 without underwent detailed neurological assessment and whole exome sequencing. Cardiovascular autonomic function was evaluated by cardiovascular reflex tests. Heart rate variability was measured by the triangle index. Sensory nerve function was estimated by Neurometer and Medoc devices. Neuropathic symptoms were characterized by the neuropathy total symptom score (NTSS). Whole exome sequencing (WES) was performed on a Thermo Ion GeneStudio S5 system determining the coding sequences of approximately 32,000 genes comprising 50 million base pairs. Variants were detected by Ion Reporter software and annotated using ANNOVAR, integrating database information from dbSNP, ClinVar, gnomAD, and OMIM. Integrative genomics viewer (IGV) was used for visualization of the mapped reads. We have identified genetic variants that were significantly associated with increased (22–49-fold) risk of neuropathy (rs2032930 and rs2032931 of recQ-mediated genome instability protein 2 (RMI2) gene), rs604349 of myosin binding protein H like (MYBPHL) gene and with reduced (0.07–0.08-fold) risk (rs917778 of multivesicular body subunit 12B (MVB12B) and rs2234753 of retinoic acid X receptor alpha (RXRA) genes). The rs2032930 showed a significant correlation with current perception thresholds measured at 5 Hz and 250 Hz for n. medianus (p = 0.042 and p = 0.003, respectively) and at 5 Hz for n. peroneus (p = 0.037), as well as the deep breath test (p = 0.022) and the NTSS (p = 0.023). The rs2032931 was associated with current perception thresholds (p = 0.003 and p = 0.037, respectively), deep breath test (p = 0.022), and NTSS (p = 0.023). The rs604349 correlated with values measured at 2000 (p = 0.049), 250 (p = 0.018), and 5 Hz (p = 0.005) for n. medianus, as well as warm perception threshold measured by Medoc device (p = 0.042). The rs2234753 showed correlations with a current perception threshold measured at 2000 Hz for n. medianus (p = 0.020), deep breath test (p = 0.040), and NTSS (p = 0.003). There was a significant relationship between rs91778 and cold perception threshold (p = 0.013). In our study, genetic variants have been identified that may have an impact on the risk of neuropathy developing in type 2 diabetic patients. These results could open up new opportunities for early preventive measures and might provide targets for new drug developments in the future.

The pathogenesis of diabetic neuropathy involves complex interactions between metabolic and genetic factors. This study aimed to identify novel genetic variants associated with neuropathy risk in type 2 diabetes through reanalysis of whole-exome sequencing data. We identified seven new SNPs with significant associations, including intronic variants in TTN, PLCB1, CCNI, and CDC34 and a 5′-upstream variant in BTG2. These variants are implicated in muscle elasticity, neurotransmission, endothelial regeneration, and apoptosis resistance, suggesting multifaceted genetic contributions to neuropathy development. These findings enhance our understanding of diabetic neuropathy and may support future advances in risk stratification and therapy development.

Aims DiGeorge syndrome (DGS) due to 22q11.2 microdeletion is characterized by a high degree of phenotypic variability. This study aimed to elucidate the molecular and cellular mechanisms underlying this variability and exacerbation of cardiovascular manifestations by developing a human induced pluripotent stem cell (hiPSC)-based model using a three-generation family. Methods and results We established hiPSC lines and their cardiovascular derivatives from a family carrying the identical 22q11.2 deletion but displaying a wide spectrum of cardiovascular involvement, allowing for a direct comparison of genetics and phenotypes at the cellular level. Genetic analyses revealed no de novo mutation in the DG region genes in patients, and no correlation between the cumulative number of genetic variants and the severity of DGS. However, we observed the presence of gene variants that may modulate predisposition to the disease with possible role in cardiovascular development. Cardiomyocytes from DGS-hiPSC with prominent cardiac symptoms exhibited altered expression of connexin-43, suggesting disruptions in early cardiac morphogenesis compared to asymptomatic relatives. Endothelial cells differentiated from symptomatic DGS-hiPSC showed impaired migration and disrupted tubular morphology with dysregulation of angiogenesis and vascular integrity pathways at the transcriptomic level. To bridge in vitro and transcriptomics findings with in vivo relevance, we performed deep clinical phenotyping for each participant and applied gene-to-phenotype correlation algorithms using large-scale clinical registry data. Conclusion Our results demonstrate that hiPSC-derived cardiovascular cells from DGS patients recapitulate disease-specific morphological and functional abnormalities, enabling identification of genotype-phenotype relationships that underlie clinical heterogeneity. Translational Perspective By modelling DGS with patient-derived hiPSC from a uniquely multigenerational family, our study reveals how shared genetic microdeletions can result in divergent pathophysiological outcomes at the cellular level. This work establishes that individualised hiPSC models faithfully reflect cardiac and vascular anomalies observed in patients and delineate the cellular and transcriptional mechanisms underlying these differences. These results facilitate early identification of pathogenic mechanisms, potentially enabling more refined risk assessment and personalised monitoring strategies for DGS patients - both for cardiovascular manifestations and potentially for extra-cardiac features.