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PubMed2026

Deep tissue sequencing improves genetic diagnostic yield in focal cortical dysplasia.

Focal cortical dysplasias (FCDs) are malformations of cortical development associated with drug-resistant focal epilepsy. We analyzed surgical tissue from 25 consecutive cases recruited from adult and pediatric epilepsy surgery programs. We performed high-depth sequencing of lesional tissue, validated somatic variants using droplet digital PCR or amplicon sequencing, and investigated genotype-phenotype correlations. A pathogenic or likely pathogenic variant was detected in 64% (n = 16/25) of cases. Of these, five cases with FCDIIa or FCDIIb had germline variants in NPRL3 (n = 3) or DEPDC5 (n = 2). Somatic variants were identified in 44% (n = 11/25) of cases. The genetic yield for FCDIIb was 77% of cases having a pathogenic mTOR pathway variant detected (n = 10/13), and for FCDIIa 66% (n = 6/9). High depth sequencing approaches allowed detection of somatic variants with very low (down to 0.4%) variant allele fractions (VAFs). No pathogenic variants were detected in 3 cases with FCDI. 62% (n = 15/24) of the cases with ≥12 months follow up experienced a favourable seizure outcome (Engel 1-2) following surgery. Of note, n = 9 patients required repeat surgery to resect residual dysplasia. Determining a genetic diagnosis reveals aetiology and paves the way to precision therapies that may benefit those with FCD who do not respond to current treatments.

Humans↗

PubMed2026

Analyzing Meiosis in Maize.

Meiosis is central to sexual reproduction and the main source of genetic diversity in plants. Understanding how meiotic processes are regulated has direct relevance to agriculture. As meiotic recombination is the vehicle of plant breeding, gaining the ability to influence recombination patterns can accelerate crop improvement. Maize is a powerful model for studying plant meiosis, thanks to its large chromosomes, well-developed genetics, and the availability of diverse cytogenetic and molecular tools. Insights gained from maize studies can extend to other species. In this review, we describe a variety of approaches for examining meiosis and meiotic recombination in maize. Cytological techniques, including protein immunolocalization and fluorescence in situ hybridization (FISH), enable visualization of chromosome structure and behavior, as well as crossover (CO) formation. Chromatin immunoprecipitation (ChIP) is used in meiosis research to determine locations of recombination proteins, identify recombination sites, and elucidate chromatin features, such as histone modifications. Quantification of COs at specific genomic sites through pollen typing by droplet digital PCR allows precise high-resolution measurement of recombination rates. Combining cytology, protein localization, and molecular assays provides a multiscale picture of meiosis, linking molecular mechanisms to chromosome behavior and, ultimately, to genetic variation.

Journal Article↗

PubMed2025

Timing Genomic Antigen Loss in Multiple Myeloma Treated with T Cell-Redirecting Immunotherapies.

UNLABELLED: Genomic antigen loss is a recurring mechanism of resistance to chimeric antigen receptor T-cell (CAR-T) and T-cell engagers (TCE) in relapsed/refractory multiple myeloma (RRMM). Yet, it remains unclear whether these events are acquired under treatment or merely selected from preexisting, undetectable clones. By leveraging chemotherapy mutational signatures as temporal barcodes within whole-genome sequencing data, we could time genomic antigen escape in 4 of 11 patients with RRMM. In all cases, the biallelic loss was driven by genomic events acquired after exposure to BCMA- and GPCR5D-targeted CAR-T/TCE and not present at baseline. Longitudinal digital PCR analysis corroborated that resistance mutations were undetectable at therapy initiation but emerged preceding relapse. Among 752 newly diagnosed patients, only 2.7% and 9% had monoallelic inactivation of TNFRSF17 and GPCR5D, respectively, with no biallelic loss. Our findings suggest limited utility of mutational screening prior to CAR-T/TCE while underscoring the importance of dynamic surveillance during therapy. SIGNIFICANCE: Multiple myeloma has been demonstrated to recurrently develop resistance to T-cell redirection via genomic antigen escape. By leveraging chemotherapy mutational signatures, we demonstrate that somatic antigen-escape mechanisms are uniformly acquired following treatment initiation and not selected from among preexisting clones, emphasizing the importance of dynamic longitudinal surveillance for their emergence. See related commentary by Kauer et al., p. 532.

Humans↗

PubMed2026

Circulating Tumor DNA in Breast Cancer: A Liquid Biopsy Revolution for Non-Invasive Genomic Profiling and Clinical Decision-Making.

Breast cancer remains the most frequently diagnosed cancer and a leading cause of cancer-related mortality among women worldwide, underscoring the need for accurate, minimally invasive biomarkers to support precision oncology. Conventional tissue biopsy remains the standard for molecular characterization but is limited by its invasiveness, inability to capture spatial and temporal tumor heterogeneity, and challenges in serial monitoring. Circulating tumor DNA (ctDNA), a tumor-derived fraction of cell-free DNA, has emerged as a promising liquid biopsy biomarker capable of providing real-time genomic information throughout disease progression. This narrative review examines recent advances in ctDNA biology, analytical technologies, clinical applications, current limitations, and future directions in breast cancer management. A structured literature search of PubMed/MEDLINE, Scopus, Embase, Web of Science, and Google Scholar identified relevant English-language publications from 2015 to 2026. Current evidence indicates that highly sensitive platforms, including digital PCR, BEAMing, and next-generation sequencing, can detect clinically actionable alterations in genes such as PIK3CA, ESR1, TP53, ERBB2, AKT1, and BRCA1/2. ctDNA has demonstrated particular utility in identifying minimal residual disease, monitoring therapeutic response, detecting emerging resistance mechanisms, and guiding targeted treatment selection in advanced breast cancer. However, applications in early cancer detection, population screening, and artificial intelligence-assisted clinical decision-making remain investigational. Widespread clinical implementation is constrained by low ctDNA abundance in early-stage disease, analytical variability, limited assay standardization, and cost considerations. Continued technological innovation, prospective multicenter validation, standardized testing protocols, and evidence-based clinical guidelines are essential to fully integrate ctDNA into routine precision breast cancer care.

breast cancer↗

PubMed2025

From Diagnosis, Therapy Decision-Making to Genetic Risk Assessment: The Impact of ctDNA Testing on Comprehensive Cancer Management-A Case Report.

Circulating tumor DNA (ctDNA) testing is a minimally invasive alternative to tissue biopsy and is ideal for inaccessible tumors or limited samples. It captures tumor heterogeneity over time and different anatomic locations, unlike the static snapshot provided by a biopsy. In this report, we describe a 68-year-old female with an initial diagnosis of metastatic pancreatic adenocarcinoma (a pancreas head mass with multiple bilateral lung nodules). Mutation profiling of the pancreatic mass biopsy using a comprehensive cancer next-generation sequencing (NGS) panel was unsuccessful due to insufficient tissue. Consequently, ctDNA testing using a pan-cancer NGS panel was performed, and an EGFR p.L858R variant at 2.15% was identified. Interestingly, this activating variant is highly specific to non-small cell lung cancer (NSCLC), which raised the possibility of a synchronous tumor unrelated to the pancreatic mass. Immunohistochemistry showed the EGFR variant in station 7 lymph nodes but not in pancreatic biopsy tissue, supporting the inference that the variant originated from the lung mass. Droplet digital PCR on the limited pancreatic biopsy identified a KRAS p.Q61 variant, which was absent by ctDNA testing, suggesting a pancreatic primary with low ctDNA levels. In addition to diagnosing a primary lung cancer, ctDNA testing guided treatment decisions. With a primary EGFR p.L858R-mutant NSCLC, osimertinib was administered, resulting in a partial response within 10 months. In addition, given the synchronous primary pancreatic adenocarcinoma, germline testing was performed, revealing a CDKN2A p.I49T variant consistent with melanoma-pancreatic cancer syndrome, prompting comprehensive cancer surveillance and familial testing. This case illustrates how ctDNA testing enabled a comprehensive evaluation by clarifying the diagnosis, identifying actionable biomarkers, and facilitating genetic risk assessment, ultimately having a significant impact on the patient's clinical management.

Humans↗

PubMed2025

Analytical and clinical performance validation of HPV-SEQ, a novel NGS-based liquid biopsy platform for detection and quantification of human papilloma virus circulating tumor DNA.

BACKGROUND: Human papillomavirus (HPV) is the primary causative driver of oropharyngeal squamous cell carcinoma (OPSCC). Accurate detection of HPV-DNA is critical for risk stratification and management of OPSCC. However, assays designed to detect HPV in primary tumors do not allow monitoring of HPV-DNA over time, whereas commercially available droplet digital PCR-based methods for assessment of circulating cell free (cf)HPV-DNA in plasma remain suboptimal, hindering adaptation into clinical practice. We have developed HPV-SEQ, a novel next-generation-sequencing (NGS) based method for detection and quantification of HPV16/18 DNA in plasma of patients with OPSCC. METHODS: The assay uses primers targeting the L1 gene of HPV16 and HPV18 viral genomes and strain specific calibrators at a defined concentration to determine the ratio of native HPV to a known standard, enabling accurate reporting of patient-derived HPV16/18 viral load in a sample. This study was conducted using two different patient populations in addition to healthy donors and contrived material. All experiments were performed to fulfill several applicable analytical, performance and validation guidelines. RESULTS: A thorough analytical characterization and clinical validation of this platform demonstrates that HPV-SEQ detects cfHPV-DNA with exceptional limit of quantification and high precision, providing a foundation for integrating this platform into clinical settings. CONCLUSIONS: This ultra-sensitive HPV profiling method with optimal analytical performance may represent a significant advancement in risk stratification, treatment management, and post-treatment surveillance for patients with OPSCC.

Humans↗

PubMed2026

Metabolomics and genomics reveal high diversity and concentrations of cyanopeptides during a Microcystis bloom.

Cyanobacterial blooms are an immense global problem that release complex mixtures of poorly characterized biologically active cyanopeptides into freshwater. In this study, metabolomics and genomics were used to assess the diversity and concentrations of cyanopeptides during a dense Microcystis bloom during the late summer of 2023 in Lake Champlain, a large transboundary lake situated between Canada and the United States. Despite the relatively low genetic diversity of the bloom determined by 16S rRNA metabarcoding, 151 cyanopeptides were detected by non-targeted metabolomics. This represents the most recorded cyanopeptides from a single lake plankton bloom event to date. Fifty-two cyanopeptides were previously reported and 99 represent putative new structures. Standards from the microcystin, cyanopeptolin, microginin, and anabaenopeptin groups were used to either quantify or approximate respective cyanopeptide concentrations over the sampling period. Cyanopeptolins were the most diverse (n = 68) cyanopeptides and the second most abundant, reaching 12,892 μg/L. Microginins were the second most diverse (n = 24) and reached the highest concentrations (18,262 μg/L). Anabaenopeptins were the third most diverse (n = 17) cyanopeptides, reaching 4,818 μg/L. Only 8 microcystins were detected, reaching 4,935 μg/L, where MC-LR was the dominant congener. Target cyanopeptide biosynthesis genes for microcystins (mcyE), cyanopeptolins (mcnC), anabaenopeptins (apnD), microviridins (mdnC), and aeruginosins (aerA) were also quantified using digital droplet PCR (ddPCR). The gene copy numbers for mcyE, mcnC, and apnD were highly correlated with their corresponding cyanopeptide concentrations. Overall, the studied Microcystis bloom produced a very diverse cyanopeptide mixture with high cyanopeptide concentrations including non-microcystin groups.

Microcystis↗

PubMed2025

Utility of Plasma Cell-free Chromatin Immunoprecipitation to Detect Cardiac Allograft Rejection.

BACKGROUND: Antibody-mediated rejection (AMR) remains the major risk factor for allograft loss across all solid organ transplantation. Unfortunately, its diagnosis relies on biopsy, an invasive gold standard that often sample unaffected allograft tissue leading to missed diagnosis. Plasma donor-derived cell-free DNA (dd-cfDNA) is noninvasive biomarker that has high sensitivity but low specificity for AMR diagnosis. This proof-of-concept study assessed the utility of cell-free chromatin immunoprecipitation (cfChIP) as a surrogate for gene expression to detect cardiac AMR and the associated pathobiology. METHODS: The discovery GRAfT multicenter cohort of heart transplant patients (NCT02423070) identified AMR, acute cellular rejection (ACR), and stable controls based on biopsy and ddcfDNA results. Plasma cfChIP-sequencing was performed to identify peaks, associated genes and pathobiological pathways. Plasma from an external cohort (GTD, NCT01985412) was also analyzed to verify pathways identified. Digital droplet PCR (ddPCR) assays targeting differential regions were constructed to test the diagnostic performance of cfDNA to detect AMR/ACR from stable controls (rejection-specific assays) or AMR from ACR (AMR-specific assays). RESULTS: The cohort included 21 AMR, 28 ACR, and 45 stable controls from GRAfT and GTD, and 23 healthy controls. cfChIP detected expected active genes, including housekeeping genes and gene targets of transplant immunosuppressive drugs but not inactive genes. Unsupervised clustering of the discovery GRAfT cohort assigned 95% of samples correctly as AMR, ACR or stable control. Differential analysis identified pathobiological pathways of AMR such as neutrophil degranulation and complement activation. The pathways were consistent in GTD samples. Rejection-specific assays detected AMR/ACR from controls with AUC of 0.78 - 0.95. AMR-specific assays detected AMR from ACR with AUC of 0.71 - 0.85, sensitivities of 0.73 - 0.94 and specificities of 0.73 - 0.80. CONCLUSION: This study provides valuable preliminary data supporting the use of cfChIP to detect AMR and the associated pathobiological pathways.

Allograft rejection↗

PubMed2026

High-Sensitivity ctDNA Analysis Uncovers Relevant Signals Missed by NGS in Pancreatic Cancer.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) carries high mortality despite multimodal therapy, and improved biomarkers are needed to guide perioperative care. This study evaluated the prognostic significance of Kirsten rat sarcoma virus (KRAS)-mutant circulating tumor DNA (ctDNA) detected by next-generation sequencing (NGS) and digital droplet PCR (ddPCR) in localized PDAC. EXPERIMENTAL DESIGN: In this prospective cohort study (2020-2024), patients with localized PDAC undergoing neoadjuvant chemotherapy (NAC) were enrolled across multiple sites within Northwestern Medicine. Blood samples for ctDNA were assessed at diagnosis, after NAC, and after resection using tumor-agnostic NGS and ddPCR targeting KRAS G12D/V/R mutations. Overall survival (OS) was assessed using Kaplan-Meier analysis. RESULTS: The cohort included 106 patients. At diagnosis, KRAS ctDNA was detected in 17.2% (17/99) by NGS and 64.9% (63/97) by ddPCR. Detection by both platforms was associated with shorter OS, with the higher-sensitivity ddPCR assay providing greater prognostic discrimination by identifying additional patients with poor outcomes not captured by NGS (NGS median OS 11.2 vs. 30.5 months, P < 0.001; ddPCR median OS 24.7 vs. 70.9 months, P = 0.004). Stratified by detection method, median OS was shortest in patients with ctDNA detected by both NGS and ddPCR (10.9 months), longest in those not detected by either platform (40.7 months), and intermediate in patients detected only by ddPCR (26.9 months; P < 0.001). CONCLUSIONS: In localized PDAC, KRAS-mutant ctDNA detected by NGS or ddPCR was associated with worse survival. ddPCR identified additional patients missed by NGS. Integrating ddPCR with NGS ctDNA measures may improve perioperative risk stratification, although validation is needed before clinical implementation.

Humans↗

PubMed2026

Potato Black Scurf and Stem Canker: Pathogen Biology, Global Distribution, and Traditional and Modern Diagnostics.

Rhizoctonia solani is a soil- and seed-borne fungal pathogen of potatoes. It is a persistent threat to potato production worldwide. The symptoms appear as black scurf on tubers and stem canker, causing severe yield and quality losses of potatoes. The pathogen reproduces asexually via hyphae and sclerotia. Its genetic diversity is organized into anastomosis groups (AGs), with AG3-PT being the predominant group on potato. The global trade of seed potatoes is very important for agricultural development; however, it has facilitated the dissemination of the pathogen across regions. Moreover, disease development is affected by environmental and agronomic factors, causing variable symptom severity and differential economic impacts. Given the pathogen's genetic complexity, accurate diagnosis is very important, necessitating a transition from traditional culture-based and biochemical methods toward molecular, genomic, and emerging digital technologies. Methods such as PCR, isothermal amplification, sequencing, sensor-based biosensing, and artificial intelligence-driven imaging have improved the detection, quantification, and noninvasive monitoring of the pathogen. Combining these diagnostic methods into a tiered framework will be helpful for precision disease surveillance, informed disease management decision-making, and the development of sustainable potato production systems.

black scurf↗

PubMed2025

Advances in diagnosis of diseases causing diarrhea in newborn calves.

Diarrhea in newborn calves is a serious global health problem. It poses challenges for animal industry, veterinarians and researchers due to the rapid onset of dehydration. Mixed infections make treatment complicated, and many young calves suffer high rates of illness and death from this condition. Numerous enteropathogens are associated with diarrhea in newborn calves, encompassing viruses, bacteria, parasites, and protozoa. Their occurrence differs by region, yet the most prevalent infections include E. coli, Salmonella species, Clostridium perfringens, Clostridium difficile, Rotavirus, Coronavirus, Cryptosporidium, Toxocara, Giardia and Eimeria. This review outlines the diagnostic techniques for diseases that lead to diarrhea in newborn calves. Diagnosis is based on clinical manifestations; however, the laboratory identification of etiological items is the only valid way for detecting the illness's aetiology and initiating treatment protocols. Classic methods such as bacterial culturing, fecal flotation, direct microscopy, and virus isolation help us understand pathogens better. Immunological assays like ELISA and immunochromatography are fast, accurate, affordable, and useful for on-farm detection. They help identify specific antigens or antibodies efficiently. Molecular methods including PCR (standard, multiplex, real time and digital), LAMP assays, DNA microarrays and whole-genome sequencing allow highly accurate and sensitive detection. They can identify pathogens effectively, even at very low levels. Nanotechnology-based assays introduce a novel level of sensitivity and specificity, often yielding quick results with minimal sample volumes. In conclusion, accurate and rapid diagnosis using advanced techniques is critical for managing and preventing diseases that lead to diarrhea in newborn calves.

Animals↗

PubMed2025

Methylation-based droplet digital polymerase chain reaction shows high concordance with chronic lymphocytic leukemia IGHV somatic mutation status.

OBJECTIVE: Somatic hypermutation at immunoglobulin heavy chain variable (IGHV) genes, an established prognostic and predictive biomarker for chronic lymphocytic leukemia (CLL), is assessed by gene sequencing. We developed a single methylation-specific droplet digital polymerase chain reaction (methyl-ddPCR) to predict IGHV status in patients with CLL. METHODS: The CLL methylation array and IGHV data from the International Cancer Genome Consortium (ICGC) were used for biomarker discovery. Top-ranked candidate regions were manually screened for PCR primer and probe binding sites. A single methyl-ddPCR was evaluated on an internal cohort of CLLs with mutated (M), unmutated (U), and inconclusive IGHV results originally determined by next-generation sequencing (NGS). RESULTS: Analysis of ICGC data identified array probe cg23844018 as a candidate for the PCR. The corresponding CpG site showed high methylation levels in U-CLL and lower levels in M-CLL. On the internal cohort, a single optimal cutoff correctly classified 104 of 115 U- and M-CLLs (90.4%; area under the curve = 0.96). The PCR data correlated with some prognostic fluorescence in situ hybridization and CLL subset groupings. Limited analysis suggests that the PCR may be able to stratify some patients with CLL who have inconclusive results on IGHV NGS testing. CONCLUSIONS: The methyl-ddPCR showed high concordance with CLL IGHV status in an internal cohort.

Humans↗

PubMed2025

Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection.

Artificial intelligence models using digital histopathology slides stained with hematoxylin and eosin offer promising, tissue-preserving diagnostic tools for patients with cancer. Despite their advantages, their clinical utility in real-world settings remains unproven. Assessing EGFR mutations in lung adenocarcinoma demands rapid, accurate and cost-effective tests that preserve tissue for genomic sequencing. PCR-based assays provide rapid results but with reduced accuracy compared with next-generation sequencing and require additional tissue. Computational biomarkers leveraging modern foundation models can address these limitations. Here we assembled a large international clinical dataset of digital lung adenocarcinoma slides (N = 8,461) to develop a computational EGFR biomarker. Our model fine-tunes an open-source foundation model, improving task-specific performance with out-of-center generalization and clinical-grade accuracy on primary and metastatic specimens (mean area under the curve: internal 0.847, external 0.870). To evaluate real-world clinical translation, we conducted a prospective silent trial of the biomarker on primary samples, achieving an area under the curve of 0.890. The artificial-intelligence-assisted workflow reduced the number of rapid molecular tests needed by up to 43% while maintaining the current clinical standard performance. Our retrospective and prospective analyses demonstrate the real-world clinical utility of a computational pathology biomarker.

Humans↗

PubMed2025

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast Cancer.

Deep learning models applied to digital histology can predict gene expression signatures (GES) and offer a low-cost, rapidly available alternative to molecular testing at the time of diagnosis. We optimized transformer-based models to infer GES results and applied this approach to pre-treatment H&E-stained biopsies from 1,940 breast cancer patients treated with neoadjuvant chemotherapy in clinical trial and real-world cohorts. The most predictive histology-derived GES for pathologic complete response (pCR) in the I-SPY2 trial was validated in four external cohorts: CALGB 40601, CALGB 40603, a trial of durvalumab plus CT, and standard-of-care CT-treated patients from the University of Chicago. Among HER2-negative patients, a transformer-based model trained using a signature composed of estrogen-regulated genes, proliferation, apoptosis, and interferon response genes predicted pCR with an AUC of 0.794, outperforming models based on clinical features alone (AUC 0.704, p = 0.001), pathologist TIL assessment, and a model trained directly to predict response from I-SPY2 cases. Tertiles of this signature stratify patients into clinically relevant groups with increasing likelihood of complete response, with pCR rates ≥50% in the top tertile regardless of treatment or hormone receptor status. Additional transformer-based signature models predicted response to specific therapies (but not chemotherapy alone), including a HER2 signaling signature in IO-treated patients, and a claudin-low signature in bevacizumab treated patients. In HER2- cohorts with available gene expression data and histology, models trained on expression data performed similarly to digital histology predictions, but the combination of gene expression and histology outperformed histology alone. These findings suggest that histology-based GES provides additive information to RNA sequencing data and can inform precision treatment selection across breast cancer subtypes.

Journal Article↗

PubMed2026

OligoSeq: Rapid nanopore-sequencing of single-stranded oligonucleotides.

Nanopore-based DNA sequencing technology has achieved remarkable success in sequencing increasingly long DNA strands (e.g., over a million nucleotides long) for genomics research and biotechnology applications. However, the same level of progress has not been achieved for DNA oligonucleotides (usually ≤ 300 nucleotides long). Oligonucleotides play a crucial role in genome engineering efforts through oligo library generation and in DNA data storage, where they are used to encode computer information, such as binary (digital) data in DNA libraries. To enable these applications, accurate sequencing of oligonucleotides in a way that allows to assess for sequence variability, quality and length is essential. But sequencing solutions for oligonucleotides - particularly DNA primers for PCR, oligo DNA libraries used for mutagenesis or cDNA libraries used in gene expression analysis - remain inadequate. To address this gap, OligoSeq is presented as an innovative approach that integrates two complementary techniques: AmpliSeq (based on PCR) and RevSeq (based on reverse complementation with sequence-specific or random primers) to facilitate sequencing of single-stranded oligonucleotides using reference sequence anchor matches of more than ≥ 90% identity spanning from about 70% to 10% with AmpliSeq or RevSeq with random nonamers, respectively, and resolving the final reference sequence based on the most likely candidate from basecall frequencies, regardless of length and double-stranding method. OligoSeq can be integrated with nanopore sequencing technology pipelines and can be used as a reference for other sequencing platforms requiring double-stranded adapters, offering a practical and scalable alternative for standard quality control in single-stranded oligonucleotide synthesis. The use of nanopore technology, compatible with the double-stranding methods showcased, is shown to be the most cost-effective method for resolving original DNA sequences of different length and quality, and to assess its sequence variability, compared to other methods such as Illumina, PacBio or HPLC/MS.

Sequence Analysis, DNA↗

PubMed2024

Single Nucleotide Polymorphisms in RUNX2 and BMP2 contributes to different vertical facial profile.

The vertical facial profile is a crucial factor for facial harmony with significant implications for both aesthetic satisfaction and orthodontic treatment planning. However, the role of single nucleotide polymorphisms (SNPs) in the development of vertical facial proportions is still poorly understood. This study aimed to investigate the potential impact of some SNPs in genes associated with craniofacial bone development on the establishment of different vertical facial profiles. Vertical facial profiles were assessed by two senior orthodontists through pre-treatment digital lateral cephalograms. The vertical facial profile type was determined by recommended measurement according to the American Board of Orthodontics. Healthy orthodontic patients were divided into the following groups: "Normodivergent" (control group), "Hyperdivergent" and "Hypodivergent". Patients with a history of orthodontic or facial surgical intervention were excluded. Genomic DNA extracted from saliva samples was used for the genotyping of 7 SNPs in RUNX2, BMP2, BMP4 and SMAD6 genes using real-time polymerase chain reactions (PCR). The genotype distribution between groups was evaluated by uni- and multivariate analysis adjusted by age (alpha = 5%). A total of 272 patients were included, 158 (58.1%) were "Normodivergent", 68 (25.0%) were "Hyperdivergent", and 46 (16.9%) were "Hypodivergent". The SNPs rs1200425 (RUNX2) and rs1005464 (BMP2) were associated with a hyperdivergent vertical profile in uni- and multivariate analysis (p-value < 0.05). Synergistic effect was observed when evaluating both SNPs rs1200425- rs1005464 simultaneously (Prevalence Ratio = 4.0; 95% Confidence Interval = 1.2-13.4; p-value = 0.022). In conclusion, this study supports a link between genetic factors and the establishment of vertical facial profiles. SNPs in RUNX2 and BMP2 genes were identified as potential contributors to hyperdivergent facial profiles.

Polymorphism, Single Nucleotide↗