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PubMed2026

Forensic applicability of genetic profile generation from hair roots and shafts: Integration of retrotransposon polymorphisms and morphological predictors.

Genetic profiles were successfully obtained from hair samples both directly plucked from the scalp and indirectly from personal items such as combs and hairbrushes. Additionally, 100 genetic profiles were generated from buccal swabs from all donors, allowing the calculation of population allele and genotype frequencies. Complete genetic profiles were recovered from samples containing less than 0.012 ng of total nuclear DNA. Nuclear DNA yield per hair root was highly variable, whereas hair shafts yielded up to 2 ng of total nuDNA and in some cases less than 0.1 ng. Multiple correspondence analysis (MCA) revealed that hair growth phase and the presence of a root were not significantly associated with successful profile recovery; instead, greater hair thickness and direct sampling correlated with higher success rates. In certain cases, the Insertion/Null (INNUL) markers system, InnoTyper 21, outperformed the Power Plex Fusion 6 C STR kit. For forensic purposes, using the entire hair shaft provided better profiling outcomes than using the root alone. All Insertion/Null (INNUL) markers were in Hardy-Weinberg equilibrium, except for a few loci showing minor linkage disequilibrium. These results highlight the analytical potential of INNUL markers for obtaining nuclear DNA profiles from hair, even in challenging forensic contexts.

Humans↗
PubMed2026

Genetic Profile, Treatment Response, and Outcomes of BCR::ABL1-Positive Mixed-Phenotype Acute Leukemia: A Study From the BCR::ABL1 Pathology Group.

Mixed-phenotype acute leukemia (MPAL) with BCR::ABL1 fusion is rare, and its clinicopathological features, genetic landscape, therapeutic response, and patient outcomes remain incompletely defined, as does its relationship to blast-phase chronic myeloid leukemia. In this multicenter study of 44 patients, 86.4% had B/myeloid MPAL, 72.7% showed lymphoid predominance, 40.9% had complex karyotypes, and 68.3% harbored somatic mutations, most commonly RUNX1 mutations (46.3%). RUNX1 mutations frequently co-occurred with acute myeloid leukemia (AML)-associated alterations, whereas DNMT3A, TET2, and BCORL1 mutations were restricted to RUNX1-mutated cases. In contrast, acute lymphoblastic leukemia (ALL)-associated alterations (IKZF1 mutation/deletion and ETV6 mutations) were confined to RUNX1-wild-type patients. TP53 and signaling pathway mutations (NRAS, KRAS, PTPN11, and FLT3) were not detected. Forty-two patients received induction chemotherapy and/or immunotherapy combined with tyrosine kinase inhibitors: 74.2% of lymphoid-predominant patients and 63.6% of myeloid-predominant patients received ALL- and AML-type therapies, respectively. Ten patients relapsed, and 2 had primary refractory disease; some exhibited a dynamic shift in predominant lineage immunophenotype, chromosomal alterations, and somatic mutations at the relapse or refractory stage. The overall remission rate was 86.8%, with no significant differences across ALL-, AML-, or hybrid-type regimens. After a median follow-up of 24.2 months, the median overall survival was 52.5 months. Complex karyotype was associated with inferior overall survival compared with cases lacking additional chromosomal alterations (P = .02), whereas RUNX1 mutations were not. No significant differences in genetic profiles, treatment response, or outcomes were observed between patients with and without chronic myeloid leukemia-like features. This study provides a comprehensive genomic and clinical characterization of BCR::ABL1-positive MPAL, supporting improved risk stratification and future therapeutic strategies.

Adolescent↗
PubMed2026

ECHO: a nanopore sequencing-based workflow for (epi)genetic profiling of the human repeatome.

SUMMARY: The human genome is dominated by repetitive DNA, whose genetic and epigenetic variation plays a key role in gene regulation, genome stability, and disease. Recent advances in long-read sequencing now enable large-scale, haplotype-resolved, and DNA methylation-informative analysis of the human genome, including on previously inaccessible complex and repetitive regions. However, the comprehensive, simultaneous characterisation of the "human repeatome" remains challenging, largely due to the lack of comprehensive tools integrated in a single pipeline that can capture the full spectrum of variation across diverse types of DNA repeats. Here, we present ECHO, a user-friendly, Snakemake-based pipeline for the "(Epi)genomic Characterisation of Human Repetitive Elements using Oxford Nanopore Sequencing." ECHO provides a reproducible and scalable framework for end-to-end analysis of whole-genome nanopore sequencing data, enabling integrative but also tailored (epi)genetic analyses of the human repeatome. AVAILABILITY AND IMPLEMENTATION: ECHO is freely available at Github: https://github.com/leenput/ECHO-pipeline, with the archived version at Zenodo: https://zenodo.org/records/19068468.

Humans↗
PubMed2025

Development and validation of blood-based diagnostic biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) using EpiSwitch® 3-dimensional genomic regulatory immuno-genetic profiling.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating, multifactorial disorder characterised by profound fatigue, post-exertional malaise, cognitive impairments, and autonomic dysfunction. Despite its significant impact on quality of life, ME/CFS lacks definitive diagnostic biomarkers, complicating diagnosis and management. Recent evidence highlights potential blood tests for ME/CFS biomarkers in immunological, genetic, metabolic, and bioenergetic domains. Chromosome conformations (CCs) are potent epigenetic regulators of gene expression and cross-tissue exosome signalling. We have previously developed an epigenetic assay, EpiSwitch®, that employs an algorithm-based CCs analysis. Using EpiSwitch® technology, we have shown the presence of disease-specific CCs in peripheral blood mononuclear cells (PBMCs) of patients with amyotrophic lateral sclerosis (ALS), rheumatoid arthritis (RA), prostate and colorectal cancers, diffuse Large B-cell lymphoma and severe COVID-19. In a recent paper, we have identified a profile of systemic chromosome conformations in cancer patients reflective of the predisposition to respond to immune checkpoint inhibitors, PD-1/PD-L1 antagonists, with 85% accuracy. In this Retrospective case/control study (EPI-ME, Epigenetic Profiling Investigation in Myalgic Encephalomyelitis), we used whole blood samples retrospectively collected from n = 47 patients with severe ME/CFS and n = 61 age-matched healthy control patients to perform whole-genome 3D DNA screening for CCs correlating to ME/CFS diagnosis. We identified a 200-marker model for ME/CFS diagnosis (Episwitch®CFS test). First testing on the retrospective independent validation cohort demonstrated a strong systemic ME/CFS signal with a sensitivity of 92% and a specificity of 98%.Pathways analysis revealed several likely contributors to the pathology of ME/CFS, including interleukins, TNFα, neuroinflammatory pathways, toll-like receptor signalling and JAK/STAT. Comparison with pathways involved in the action of Rituximab and glatiramer acetate (Copaxone) (therapies with potential in ME/CFS treatment) identified IL2 as a shared pathway with clear patient clustering, indicating a possibility of a potential responder group for targeted treatment.

Humans↗
PubMed2025

Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles.

In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.

Journal Article↗
PubMed2025

Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease.

IMPORTANCE: Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD. OBJECTIVE: To identify genetic risk loci and cardiovascular risk factors with AS-specific associations. DESIGN, SETTING, AND PARTICIPANTS: This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023. EXPOSURES: Genetic variants. MAIN OUTCOMES AND MEASURES: Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts. RESULTS: A total of 18 792 participants with AS and 434 249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P = 1.60 × 10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P = 1.27 × 10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P = .04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development. CONCLUSIONS AND RELEVANCE: This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.

Humans↗
PubMed2026

Virtual Tumors Enable Prediction of Personalized Therapeutic Combinations for Non-Small Cell Lung Cancer.

UNLABELLED: The disease burden from non-small cell lung cancer (NSCLC) adenocarcinoma is substantial, with a million new cases diagnosed globally each year and a 5-year survival rate of less than 20%. The lack of therapeutic options personalized to individual patients leads to high variation in survival. The combination of patient stratification with personalized treatment has the potential to improve outcomes; however, the variation in mutations found in patients with NSCLC adenocarcinoma makes experimentally determining treatment combinations time-consuming and expensive. In this study, we developed an interpretable mechanistic model to decipher complex signaling interplay and guide personalized therapy in NSCLC adenocarcinoma. This "virtual tumor" model encompassed key tumor-intrinsic oncogenic signaling pathways for efficiently predicting rational drug-drug and drug-radiotherapy combination therapies in NSCLC. Diverse genetic profiles were simulated for testing more than 10,000 therapeutic strategies to identify optimal approaches to overcome resistance mechanisms specific to genetic profiles and p53 status. The virtual tumor model reproduced drug additivity screens, predicted radiosensitizing genes validated in a CRISPR screen, and identified 53BP1 as a potential drug target that improved the therapeutic window during radiotherapy. A 19-gene signature derived from the virtual tumor framework stratified patients most likely to benefit from radiotherapy, which was validated using The Cancer Genome Atlas (TCGA) data. These results show the utility of virtual tumors to predict effective therapeutic combinations and present a computational resource for large-scale screening of personalized therapies to guide clinical decision-making in patients with NSCLC. SIGNIFICANCE: A computational framework that simulates thousands of personalized treatment strategies offers a scalable, cost-effective way to tailor therapies and improve outcomes for patients with genetically diverse NSCLC.

Humans↗
PubMed2026

Evaluation of bone preparation approaches using length-based analysis and targeted sequencing for forensic human identification of historic skeletal remains.

Advances in DNA technology have significantly enhanced the forensic community's ability to develop genetic profiles from unidentified human skeletal remains. However, sampling requires mechanical grinding of hard tissues before DNA isolation. This processing can compromise genetic profiles, particularly in aged bones. We compared the industry-standard pulverization method with an alternative powder-free preparation involving prolonged demineralization and subsequent slicing of 19th-century cortical bone. Data from DNA quantification, STR genotyping, and targeted SNP sequencing were used to evaluate powdered samples versus demineralized slices from paired human bones. Average human DNA yields for pulverized samples and demineralized slices were 0.032&#x2009;ng and 0.692&#x2009;ng, respectively. Demineralized slices recovered more amplifiable DNA than traditional homogenization methods (p&#x2009;<&#x2009;0.05). No pulverized samples produced STR profiles, whereas demineralized slices from the same bone samples yielded partial profiles. Samples underwent DNA repair, library preparation, and hybridization capture using the FORensic Capture Enrichment (FORCE) panel. Applying low-coverage (1X) analysis of high-throughput sequencing (HTS) data, demineralized slices outperformed those prepared by traditional pulverization methods (p&#x2009;<&#x2009;0.05) and substantially increased the information recovered compared with conventional STR analysis methods. Based on HTS data from pulverized samples, DNA fragment length ranged from 27 to 95&#x2009;bp, and FORCE SNP recovery was 33.23%. In contrast, for demineralized slices, DNA fragment length ranged from 85 to 114&#x2009;bp, and FORCE SNP recovery was 83.24%. The required reagents and equipment are typically available in forensic labs, and the workflow outlined herein significantly increases the success of DNA recovery from challenging skeletal samples.

Humans↗
PubMed2025

Polygenic and developmental profiles of autism differ by age at diagnosis.

Although autism has been historically conceptualised as a condition that emerges in early childhood, many autistic people are diagnosed later in life. It is unknown whether earlier and later diagnosed autism have different developmental trajectories and genetic profiles. Using longitudinal data from four independent birth cohorts, we demonstrate that two different socioemotional and behavioural trajectories are associated with age at diagnosis. In independent cohorts of autistic individuals, common genetic variants account for approximately 11% of the variance in age at autism diagnosis, comparable to the contribution of individual sociodemographic and clinical factors, which typically explain less than 15% of this variance. We further demonstrate that the polygenic architecture of autism can be decomposed into two modestly genetically correlated (rg = 0.38, SE = 0.07) autism polygenic factors. One of these factors is associated with earlier autism diagnosis, and lower social and communication abilities in early childhood but is only modestly genetically correlated with ADHD and mental health conditions. Conversely, the second factor is associated with later autism diagnosis, increased socioemotional and behavioural difficulties in adolescence, and has moderate to high positive genetic correlations with Attention-Deficit/Hyperactivity Disorder and mental health conditions. These findings indicate that earlier and later diagnosed autism have different developmental trajectories and genetic profiles. Our findings have important implications for how we conceptualise autism and provide one model to explain some of the diversity within autism.

Journal Article↗
PubMed2025

Polygenic and developmental profiles of autism differ by age at diagnosis.

Although autism has historically been conceptualized as a condition that emerges in early childhood1,2, many autistic people are diagnosed later in life3-5. It is unknown whether earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Using longitudinal data from four independent birth cohorts, we demonstrate that two different socioemotional and behavioural trajectories are associated with age at diagnosis. In independent cohorts of autistic individuals, common genetic variants account for approximately 11% of the variance in age at autism diagnosis, similar to the contribution of individual sociodemographic and clinical factors, which typically explain less than 15% of this variance. We further demonstrate that the polygenic architecture of autism can be broken down into two modestly genetically correlated (rg&#x2009;=&#x2009;0.38, s.e.&#x2009;=&#x2009;0.07) autism polygenic factors. One of these factors is associated with earlier autism diagnosis and lower social and communication abilities in early childhood, but is only moderately genetically correlated with attention deficit-hyperactivity disorder (ADHD) and mental-health conditions. Conversely, the second factor is associated with later autism diagnosis and increased socioemotional and behavioural difficulties in adolescence, and has moderate to high positive genetic correlations with ADHD and mental-health conditions. These findings indicate that earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Our findings have important implications for how we conceptualize autism and provide a model to explain some of the diversity found in autism.

Humans↗
PubMed2025

Bayesian Modeling of Cancer Outcomes Using Genetic Variables Assisted by Pathological Imaging Data.

With the increasing maturity of genetic profiling, an essential and routine task in cancer research is to model disease outcomes/phenotypes using genetic variables. Many methods have been successfully developed. However, oftentimes, empirical performance is unsatisfactory because of a "lack of information." In cancer research and clinical practice, a source of information that is broadly available and highly cost-effective comes from pathological images, which are routinely collected for definitive diagnosis and staging. In this article, we consider a Bayesian approach for selecting relevant genetic variables and modeling their relationships with a cancer outcome/phenotype. We propose borrowing information from (manually curated, low-dimensional) pathological imaging features via reinforcing the same selection results for the cancer outcome and imaging features. We further develop a weighting strategy to accommodate the scenario where information borrowing may not be equally effective for all subjects. Computation is carefully examined. Simulations demonstrate competitive performance of the proposed approach. We analyze TCGA (The Cancer Genome Atlas) LUAD (lung adenocarcinoma) data, with overall survival and gene expressions being the outcome and genetic variables, respectively. Findings different from the alternatives and with sound properties are made.

Humans↗
PubMed2024

Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes.

Multiple myeloma is a treatable, but currently incurable, hematological malignancy of plasma cells characterized by diverse and complex tumor genetics for which precision medicine approaches to treatment are lacking. The Multiple Myeloma Research Foundation's Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile study ( NCT01454297 ) is a longitudinal, observational clinical study of newly diagnosed patients with multiple myeloma (n&#x2009;=&#x2009;1,143) where tumor samples are characterized using whole-genome sequencing, whole-exome sequencing and RNA sequencing at diagnosis and progression, and clinical data are collected every 3&#x2009;months. Analyses of the baseline cohort identified genes that are the target of recurrent gain-of-function and loss-of-function events. Consensus clustering identified 8 and 12 unique copy number and expression subtypes of myeloma, respectively, identifying high-risk genetic subtypes and elucidating many of the molecular underpinnings of these unique biological groups. Analysis of serial samples showed that 25.5% of patients transition to a high-risk expression subtype at progression. We observed robust expression of immunotherapy targets in this subtype, suggesting a potential therapeutic option.

Humans↗
PubMed2026

Precision periodontology in clinical practice: bridging omics and clinical decision-making.

BACKGROUND: Precision periodontology integrates molecular diagnostics, genomics, and advanced imaging into clinical decision-making. Despite major advances in microbiome characterisation, host genetics, and inflammatory biomarkers, their translation into routine care remains limited. OBJECTIVES: To critically appraise current evidence on microbiome-based profiling, genetic and epigenetic markers, host-response biomarkers, and three-dimensional imaging in periodontology, and to propose a conceptual decision-support framework linking diagnostic outputs to potential therapeutic actions and future implementation research. MATERIALS AND METHODS: A narrative review searching PubMed/MEDLINE, Scopus, Embase, and the Cochrane Library (2010-2025) using terms related to precision periodontology, subgingival microbiome, periodontitis genetics and epigenetics, salivary and GCF biomarkers, aMMP-8, CBCT, risk assessment, and artificial intelligence. Priority was given to meta-analyses, systematic reviews, longitudinal studies, and guideline documents. RESULTS: Microbiological testing has defined but narrow indications; single-SNP genotyping has not demonstrated clinical utility commensurate with cost; aMMP-8 point-of-care testing is among the most extensively investigated host-response tools and may have adjunctive value in selected monitoring and peri-implant scenarios; however, current evidence remains insufficient to support routine diagnostic implementation. CBCT may directly influence surgical decision-making through defect morphology characterisation. AI-based models show promise but lack prospective clinical validation. These conclusions are consistent with the 20th EFP Workshop Consensus Report. CONCLUSIONS: Precision periodontology currently operates in addition to, rather than in replacement of, conventional staging and grading. We propose a conceptual decision-threshold framework for the selective consideration of molecular and advanced imaging tools when their additive contribution may meaningfully inform management. This framework should be regarded as a research-oriented decision-support model rather than a validated clinical algorithm. CLINICAL RELEVANCE: Clinicians are provided with a structured, evidence-based framework that identifies specific clinical scenarios where molecular diagnostics, host-response biomarkers, and three-dimensional imaging may meaningfully modify periodontal treatment decisions, supporting the operationalisation of precision approaches in daily practice.

Humans↗
PubMed2025

Severe hypercholesterolemia in a pediatric cohort: Familial homozygous and autosomal recessive hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is a genetic disorder characterized by impaired clearance of low-density lipoprotein cholesterol (LDL-C), leading to severe hypercholesterolemia and increased risk of premature cardiovascular disease (CVD). Our study aims to describe and compare the clinical, biochemical, and genetic profiles of pediatric patients diagnosed with FH based on LDL-C levels exceeding 400 mg/dL (10.4 mmol/L) and confirmed by biallelic pathogenic variants in low-density lipoprotein receptor (LDLR) or low-density lipoprotein receptor adapter protein-1 (LDLRAP1) genes. METHODS: This retrospective cohort study included 39 pediatric patients diagnosed with FH at a tertiary care center. Clinical data were analyzed, including age at diagnosis, family history, lipid profile, presence of xanthomas, and cardiovascular complications. Molecular analysis was conducted using next-generation sequencing (NGS) and Sanger sequencing to confirm pathogenic variants. Statistical comparisons were performed between the LDLR and LDLRAP1 variant groups regarding lipid profiles, treatment response, and cardiovascular outcomes. RESULTS: Among 39 patients, 32 and 7 had pathogenic variants in LDLR and LDLRAP1 genes, respectively. Genetic analysis identified 27 unique pathogenic variants in LDLR (including 5 novel mutations) and 4 in LDLRAP1 causal for autosomal recessive hypercholesterolemia (ARH), highlighting the molecular diversity of FH. Compared to the LDLR variant group, LDLRAP1 variant patients had significantly lower untreated LDL-C levels (640.0 &#xb1; 155.6 mg/dL [16.6 &#xb1; 4.0 mmol/L] vs 506.9 &#xb1; 130.1 mg/dL [13.1 &#xb1; 3.4 mmol/L], P = .026] and showed a superior response to lipid-lowering therapy (LLT), with a greater percentage (70.6% &#xb1; 12.0%) reduction in LDL-C levels (P = .015). While xanthomas were present in 62.5% of LDLR variant patients, they were less frequent (42.9%) in the LDLRAP1 group (P = .107). Cardiovascular complications were observed exclusively in LDLR variant patients. Fourteen patients required lipoprotein apheresis (LA), and one underwent liver transplantation due to severe aortic stenosis. CONCLUSION: This study highlights the importance of genetic testing in differentiating classical semidominant homozygous FH from ARH, given their phenotypic overlap but distinct treatment responses. LDLRAP1 variant patients with ARH exhibit better LDL-C reductions with conventional LLT, suggesting a milder phenotype. Early diagnosis, aggressive LLT, and novel treatments are essential to mitigate cardiovascular risk. Future studies with larger cohorts and long-term follow-ups are needed to refine treatment strategies for pediatric FH.

Humans↗
PubMed2026

Cytokines and Inflammatory Gene Polymorphisms Associated With Nosocomial Pulmonary Infection After Spontaneous Intracerebral Hemorrhage.

Nosocomial pulmonary infection is a frequent complication after spontaneous intracerebral hemorrhage and may worsen neurological recovery, prolong hospitalization, and increase clinical burden. This retrospective clinical-laboratory study presents a reproducible workflow for evaluating inflammatory biomarker and host immune-genetic profiles associated with nosocomial pulmonary infection after primary spontaneous intracerebral hemorrhage. Patients are classified according to whether nosocomial pulmonary infection occurs after admission. Peripheral venous blood is collected in the early post-admission period under standardized pre-analytical conditions. Serum is separated, aliquoted, and stored for enzyme-linked immunosorbent assay measurement of IL-1&#x3b2;, IL-6, IL-10, IL-17, IFN-&#x3b3;, TNF-&#x3b1;, TLR2, TLR4, and TLR9. In parallel, genomic DNA is extracted from anticoagulated whole blood and used for polymerase chain reaction-restriction fragment length polymorphism genotyping of selected cytokine- and Toll-like receptor-related loci. The workflow also includes quality-control procedures for sample handling, duplicate ELISA measurements, DNA purity assessment, genotype calling, and repeat genotyping. Statistical analysis includes between-group comparison of clinical characteristics and biomarker levels, Hardy-Weinberg equilibrium testing, logistic regression analysis for genotype and allele associations, adjustment for relevant clinical covariates, and false-discovery-rate correction for multiple genetic comparisons. This combined clinical, inflammatory, and immune-genetic workflow may help characterize infection-risk profiles after spontaneous intracerebral hemorrhage, although prospective multicenter validation is still required before routine clinical application.

Humans↗
PubMed2025

Bone Adhered Sediments as a Source of Target and Environmental DNA and Proteins.

In recent years, sediments from cave environments have provided invaluable insights into ancient hominids, as well as past fauna and flora. Unfortunately, however, sediments are not always collected during excavation. In this study, we analyzed an overlooked but abundant resource in archaeological collections - sediments adhered to bone. We performed metagenomics and metaproteomics analysis on sediment from several human skeletal elements, originating from Neolithic to Medieval sites in England. We were able to reconstruct a partial human genome, the genetic profile of which matches that recovered from the original skeletal element. Additionally, aDNA sequences matching the genomes of endogenous gut microbiome bacteria were identified. We also found the presence of genetic sequences corresponding to animals and plants. In particular, we managed to retrieve the partial genome and proteome of a Black Rat (Rattus rattus), sharing close genetic affinities to other medieval Rattus rattus. Our results demonstrate that material that is usually ignored or discarded, can be used to reveal information about the individual and the environmental conditions at the time of their death.

Animals↗
PubMed2026

Genome-Wide Association Analyses Identify Distinct Genetic Architectures for Extreme Early-Onset and Late-Onset T2D.

AIMS: Type 2 diabetes (T2D) is a heterogeneous disorder with substantial variation in age at onset (AAO). This study aimed to characterize the distinct genetic architectures and biological mechanisms underlying extreme AAO-defined T2D subtypes. MATERIALS AND METHODS: Using 74&#x2009;795 European-ancestry participants from the UK Biobank, we performed genome-wide association studies (GWAS) of relatively early-onset T2D (eoT2D; AAO <&#x2009;55&#x2009;years) and late-onset T2D (loT2D; AAO &#x2265;&#x2009;70&#x2009;years). We investigated subtype-specific genetic loci, SNP-based heritability, genetic correlations, Mendelian randomization (MR)-based relationships, polygenic risk scores (PRS) and phenome-wide association studies (PheWAS). Single-cell transcriptomic data from human pancreatic tissues were further used to evaluate cell-type-specific expression patterns of candidate genes. RESULTS: SNP-based heritability was substantially higher for eoT2D than loT2D (11.2% vs. 6.4%), with eoT2D displaying distinct genetic loci related to &#x3b2;-cell function and insulin regulation, including SLC30A8 and IRS1. By contrast, loT2D showed a comparatively lipid-related genetic profile, featuring APOE-associated signals and expression patterns in immune-related cell populations. Linkage disequilibrium score regression (LDSC) and MR analyses further underscored this divergence: eoT2D exhibited broader genetic overlap with cardiometabolic traits, whereas loT2D showed stronger relationships with traditional metabolic risk factors. Finally, subtype-specific PRSs improved risk discrimination beyond conventional covariates, although their clinical utility warrants further evaluation. CONCLUSIONS: Extreme AAO-defined T2D subtypes exhibit partially distinct genetic architectures, highlighting AAO as an important dimension of T2D heterogeneity and providing a framework for future age-stratified genetic risk assessment.

Type 2 diabetes↗
PubMed2026

Clinical and endocrine correlates of genetic etiologies in severe hypospadias: Study from 34 patients.

OBJECTIVE: Hypospadias is a prevalent congenital anomaly (0.3%-1.0%); however, severe hypospadias (defined as proximal cases with the meatus at the penoscrotal junction, scrotum, or perineum) is a rare and clinically challenging entity with a multifactorial etiology. This study aimed to characterize the interrelationships among the clinical, endocrine, and genetic profiles in children with severe hypospadias. MATERIALS AND METHODS: We conducted a comprehensive analysis of 34 male patients with severe hypospadias. Preoperative hormone levels were measured using two methods: chemiluminescent immunoassay for luteinizing hormone and follicle-stimulating hormone, and liquid chromatography-tandem mass spectrometry for testosterone (T), dihydrotestosterone (DHT), dehydroepiandrosterone (DHEA), 17&#x3b1;-hydroxyprogesterone (17&#x3b1;-OHP), and other steroids. Genetic analysis was conducted via whole exome sequencing. RESULTS: The diagnostic yield of clinically relevant genetic variants (including pathogenic and likely pathogenic, and variants of uncertain significance) in our cohort was 41.2% (14/34) of patients. Patients carrying these variants exhibited a more complex phenotypic profile compared to non-carriers, including a significantly higher rate of patients with &#x2265;3 associated malformations and a greater prevalence of cryptorchidism. Furthermore, the group with clinically relevant variants showed selective elevations in adrenal-derived precursors, specifically 17&#x3b1;-OHP and DHEA. Correlation analysis revealed significant positive associations of both 17&#x3b1;-OHP levels and the T/DHT ratio with the number of associated malformations. CONCLUSION: This study reveals significant genetic heterogeneity in patients with severe hypospadias. Those carrying genetic variants was associated with more severe clinical phenotypes, while certain endocrine variations, including the elevation of adrenal-derived hormones, were also observed in this cohort.

Humans↗