Genomic Sequencing in Diagnostics

Just published in Nature Communications (Nature Portfolio); we show how long-read sequencing (LRS) improves rare disease diagnosis, detecting variants missed by short-read sequencing. Key findings: - Optimized a wet bench protocol and a bioinformatics pipeline for haplotype-specific SNV, indel, CNV, and SV detection, annotation, filtration and clinical prioritization. - Developed “EpiMarker”, a tool that extracts DNA methylation profiles from long-read data, adding an epigenetic layer to genetic diagnostics. - Validated both genomic and epigenomic modules using 76 patient samples with known pathogenic variants across different diseases and mutation types. - Applied these tools to 51 undiagnosed rare disease patients—and uncovered 5 additional diagnoses (10% diagnostic yield increase!) beyond what short-read sequencing could detect. New findings were mainly due to CNVs, SVs, and methylation (phasing helped in a case with SNV + CNV). - Used methylation tagging to unambiguously diagnose spinal muscular atrophy (SMA), confirmed through paralog-specific variants (PSVs) deconvolution of SMN1/SMN2. 📄 Read more: [https://lnkd.in/dWEHRY9K] Work spearheaded by Shruti Sinha, PhD, with great support from Fatma Rabea and SathishKumar Ramaswamy Ph.D. Along with contributions from the team at Dubai Health and Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU): Ikram Chekroun Maha El Naofal, CG (ASCP), MB (ASCP) Ruchi Jain, Ph.D Roudha Alfalasi Nour Halabi Sawsan Alyafei Massy Sh Hassani, PhD Shruti Shenbagam Alan Taylor Mohammed Uddin Dafil Mohamed Almarri Stefan Du Plessis Alawi Alsheikh-Ali Grateful for all the support by Oxford Nanopore Technologies and their teams. #Genomics #RareDisease #LongReadSequencing #Epigenetics #Diagnostics

"Acute leukemia requires precise molecular classification and urgent treatment. However, standard-of-care diagnostic tests are time-intensive and do not capture the full spectrum of acute leukemia heterogeneity. Here, we developed a framework to classify acute leukemia using genome-wide DNA methylation profiling. We first assembled a comprehensive reference cohort (n = 2,540 samples) and defined 38 methylation classes." "Acute leukemia is an aggressive form of blood cancer affecting both pediatric and adult patients that is hierarchically classified according to the major lineages of hematopoiesis, including acute myeloid leukemia (AML), B-cell lymphoblastic leukemia/lymphoma (B-ALL), T-cell lymphoblastic leukemia/lymphoma (T-ALL) and rare cases of acute leukemia of ambiguous lineage (ALAL)1–4 . Acute leukemia lineages can be further categorized according to molecular subtypes defined by cytogenetic alterations, gene mutations and transcriptional and epigenomic features, which can inform prognosis and guide treatment selection5–8." "In this study, we established a comprehensive reference of DNA methylation classes in acute leukemia and developed a machine learning classifier for methylation-based diagnostics in the clinic. Our approach offers several key features to complement conventional methods. First, when coupling [methylation- and AI-guided rapid leukemia subtype inference] MARLIN to nanopore sequencing, results can be generated rapidly and in real-time, setting a realistic timeframe of hours or even minutes for generating preliminary molecular classifications. Providing this information to pathologists and treating clinicians could greatly accelerate treatment planning and potentially limit the development of oncologic emergencies caused by treatment delays. Second, methylation-based classification may resolve blind spots of conventional molecular diagnostic and cytogenetic testing, including classes associated with cryptic rearrangements (for example, DUX4-r) or molecular drivers of lineage-ambiguous cases (for example, MPAL with BCL11B activation)67. Third, methylation-based profiling may reveal novel predictive signatures of drug response. For example, methylation-based classification can identify HOX-activated subgroups directly regardless of genetic driver, although whether this predicts sensitivity to menin inhibition requires further study. Finally, nanopore sequencing and MARLIN are comparably easy to implement, making our approach suitable even in lower-resourced clinical settings where molecular diagnostic services and hematopathology expertise are difficult to access." https://lnkd.in/etQfEk8x

Sample to answer within a single shift in the ICU & PICU. Clinicians in the UK (Great Ormond Street and Guy’s & St Thomas’) are using Oxford Nanopore Technologies to ID pathogens and AMR in the same day. Two landmark studies (The Lancet Microbe and medRxiv) have just shown what many in clinical microbiology have hoped for: 👉 Rapid, pan-microbial metagenomic sequencing that identifies pathogens and resistance genes directly from patient samples, in real time. For clinicians and microbiologists, this represents a fundamental shift. No more waiting days for cultures while critically ill patients receive broad empiric therapy. Instead, metagenomics delivers actionable results within hours, guiding treatment, reducing diagnostic uncertainty, and improving outcomes for the sickest patients. This is no longer a futuristic goal; it's happening. > https://lnkd.in/g7sGKedr > https://lnkd.in/gsjyvtHV Now the challenge is integration: how do we make rapid sequencing accessible, affordable, and routine in critical care? #ClinicalMicrobiology #InfectiousDiseases #CriticalCare #Metagenomics #Sepsis #NextGenDiagnostics #PrecisionMedicine #PatientOutcomes

In my new edition of #ResearchSpotlight, I’m excited to highlight a study published in the European Journal of Human Genetics that caught my attention.  As powerful as #exome sequencing is, many patients still lack a conclusive diagnosis at the end of testing. In some cases, a monoallelic pathogenic variant associated with a recessive disorder is identified, but the patient remains undiagnosed because no relevant variant is detected in the other allele.  A group of researchers in the Netherlands recently tested the theory that, in these cases, whole-genome sequencing (#WGS) may help identify the elusive second variant by including analysis of non-coding regions—in which the first pathogenic variant was identified, focusing on splice-disrupting variants.    From 34,764 rare non-coding variants, 38 were identified as likely pathogenic with splice effects using a combination of tools, including Alamut™ Visual Plus.   The 15 most likely pathogenic variants were prioritized—one based on prior evidence, and 14 due to the advanced support provided by Alamut™ Visual Plus and SpliceAI. Among these 15 likely pathogenic non-coding variants, a functional effect was confirmed for three in subsequent experiments, providing a new, likely diagnosis for the patient.  These findings underscore not only the added value of genome sequencing but also the important role that bioinformatic software like Alamut™ Visual Plus plays in the variant annotation. As we push the boundaries of data-driven medicine, findings like these fuel our commitment to delivering actionable insights where they matter most. Read the full study: https://lnkd.in/ezDR2SSr  Gaby van de Ven, Maartje Pennings, Juliette de Vries, Michael Kwint, Jeroen van Reeuwijk, Jordi Corominas Galbany, Ronald van Beek, Eveline Kamping, Raoul Timmermans, Erik-Jan Kamsteeg, Lonneke Haer-Wigman, Susanne Roosing, Christian Gilissen, Hannie Kremer, Han G. Brunner, Helger Yntema, Lisenka Vissers

France (French Genomic Medicine Initiative) has integrated genome sequencing into clinical practice at a nationwide level. 🧬 62 pre-indications for rare diseases and 8 for cancers, but malformations and neurodevelopmental disorders 👶 are by far the most represented subgroups. 📊 12.737 results were returned to patients (as of December 31, 2023) with rare diseases, achieving a 30,6% diagnostic yield. The largest diagnostic yields were observed in: 🛠️ Rare skin disorders: 46,3% 👂 Sensory disorders: 40,5% 🧠 Central Nervous System disorders: 38,1% 👶 Neurodevelopmental disorders: 30,8% 🔍 A causal diagnosis was significantly more frequently reached when WGS (Whole Genome Sequencing) was used as a first-line diagnostic test (44%) compared to one or multiple genetic tests: 🛠️ 29,2% in patients with normal array-CGH 🧬 23,7% with negative targeted gene panels 🔬 23,2% with negative WES (Whole Exome Sequencing). Reasons: Noncoding pathogenic variants, structural variants, insufficient coverage, or other limitations not captured by WES. 📊 Diagnostic yield was higher in trio analysis (29.1%) compared to solo analysis (20,7%). 🤝 “WGS prescription in clinical practices critically enhanced our national diagnostic capacities for returning clinically significant results to the families.” https://lnkd.in/dmtqeTYk #GenomicMedicine #ClinicalGenomics #RareDiseases #WholeGenomeSequencing #WGS #NextGenerationSequencing #Diagnostics

"The Cancer Programme of the 100,000 Genomes Project was an initiative to provide whole-genome sequencing (WGS) for patients with cancer, evaluating opportunities for precision cancer care within the UK National Healthcare System (NHS). Genomics England, alongside NHS England, analyzed WGS data from 13,880 solid tumors spanning 33 cancer types, integrating genomic data with real-world treatment and outcome data, within a secure Research Environment. Incidence of somatic mutations in genes recommended for standard-of-care testing varied across cancer types. For instance, in glioblastoma multiforme, small variants were present in 94% of cases and copy number aberrations in at least one gene in 58% of cases, while sarcoma demonstrated the highest occurrence of actionable structural variants (13%). Homologous recombination deficiency was identified in 40% of high-grade serous ovarian cancer cases with 30% linked to pathogenic germline variants, highlighting the value of combined somatic and germline analysis. The linkage of WGS and longitudinal life course clinical data allowed the assessment of treatment outcomes for patients stratified according to pangenomic markers. Our findings demonstrate the utility of linking genomic and real-world clinical data to enable survival analysis to identify cancer genes that affect prognosis and advance our understanding of how cancer genomics impacts patient outcomes." New publication and great new data resource from the UK's 100,000 Genomes Project analyzing whole genome sequencing (WGS) data from 13,880 solid tumors spanning 33 cancer types. Congrats to Alona Sosinsky and larger team https://lnkd.in/gWdkwEeW

𝐂𝐚𝐬𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐰𝐞𝐞𝐤: 𝐂𝐡𝐢𝐥𝐝 𝐨𝐟 𝐜𝐨𝐧𝐬𝐚𝐧𝐠𝐮𝐢𝐧𝐞𝐨𝐮𝐬 𝐦𝐚𝐫𝐫𝐢𝐚𝐠𝐞 𝐰𝐢𝐭𝐡 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐩𝐡𝐞𝐧𝐨𝐭𝐲𝐩𝐢𝐜 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐬 𝐑𝐞𝐟𝐟𝐞𝐫𝐚𝐥 𝐫𝐞𝐚𝐬𝐨𝐧𝐬: 2 years old boy born of consanguineous marriage presented with Cerebral palsy (CP) and inability to hold his neck, microcephaly, developmental delay and suspected to be affected with metabolic disorder or neurometabolic disorder. He has a family history of mental and physical delays. He was referred for Whole Exome Sequencing to evaluate the presence of any pathogenic/likely pathogenic variants. 𝐑𝐞𝐬𝐮𝐥𝐭𝐬: 𝐓𝐰𝐨 𝐡𝐨𝐦𝐨𝐳𝐲𝐠𝐨𝐮𝐬 𝐥𝐢𝐤𝐞𝐥𝐲 𝐩𝐚𝐭𝐡𝐨𝐠𝐞𝐧𝐢𝐜 𝐯𝐚𝐫𝐢𝐚𝐧𝐭𝐬 𝐢𝐧 𝐭𝐰𝐨 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐠𝐞𝐧𝐞𝐬 𝐰𝐞𝐫𝐞 𝐢𝐝𝐞𝐧𝐭𝐢𝐟𝐢𝐞𝐝. 🔹A homozygous frameshift variant (c.362_366del, p. Glu121Valfs*3) in exon 2 of the 𝐃𝐎𝐍𝐒𝐎𝐍 𝐠𝐞𝐧𝐞 was detected. Homozygous mutation in the 𝐃𝐎𝐍𝐒𝐎𝐍 𝐠𝐞𝐧𝐞 are related to Microcephaly, short stature, and limb abnormalities (MISSLA) syndrome, that usually results in intrauterine growth retardation, microcephaly, variable short stature, and limb abnormalities mainly affecting the upper limb and radial ray. 🔹A homozygous splice site variant (c.1782+2T>C) in intron 20 of the ATP8A2 gene was detected. Homozygous mutation in the ATP8A2 gene are related to Cerebellar ataxia, impaired intellectual development, and dysequilibrium syndrome (CAMRQ), a genetically heterogeneous disorder characterized by congenital cerebellar ataxia and impaired intellectual development. 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐚𝐭𝐢𝐨𝐧𝐬: In such familial cases, couple might consider Preimplantation Genetic Testing (PGT-M), an early genetic diagnosis test for embryos produced during IVF, prior to their transfer to the uterus. PGT-M can prevent the transmission of inherited disorder to future children and achieve a healthy pregnancy. Therefore, it’s so important to provide comprehensive diagnostic strategy, for this kind of complex cases, to be able to identify all possible “disease causing” variants. At Lifespan Group, we have completely transformed our approach for rare diseases diagnostics, especially for children with complex phenotypic conditions, by moving away from diseases specific gene panels towards more comperhensive WES or WGS solutions. This enables us to simultaneously analyze multiple genes and copy number variants, providing a more accurate, cost-effective and time-efficient solution. #WGS #WES #genomics #multiomics #precisionmedicine #diseseprevention

Blood cancers such as leukemia make up nearly 10% of all new cancer cases in the US, with more than 180,000 new diagnoses in 2024 alone. Traditional sample testing is complex, costly, and may miss mutations that can significantly impact treatment decisions. Illumina participated in research showing that a single whole genome sequencing workflow, powered by the #DRAGEN heme pipeline had 100% sensitivity with a short 5 day turnaround time. Early next year, automatic risk stratification for AML will be added to Illumina Connected Insights, providing a streamlined informatic experience from DRAGEN variant calling to interpretation in Connected Insights. See this Illumina News Center article to learn more about how Illumina’s whole genome library preparation, sequencing, and informatics is powering advancements in heme clinical research.   https://lnkd.in/gHBT4ytC  

𝐓𝐡𝐞 𝐆𝐞𝐧𝐨𝐦𝐢𝐜 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧: 𝐇𝐨𝐰 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐈𝐬 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐂𝐚𝐧𝐜𝐞𝐫 𝐂𝐚𝐫𝐞 Cancer genome sequencing, also known as cancer genomics, is a cutting-edge technique that involves mapping and analyzing the entire genetic information of cancer cells. This process provides invaluable insights into the genetic alterations that drive the development, progression, and behavior of various types of cancers. Here's a detailed explanation of cancer genome sequencing: 𝟏. 𝐆𝐞𝐧𝐨𝐦𝐞 𝐚𝐧𝐝 𝐆𝐞𝐧𝐨𝐦𝐢𝐜 𝐀𝐥𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬: The genome of an organism is its complete set of DNA, containing all the genetic information needed for its development and functioning. In cancer, the DNA of normal cells undergoes changes or mutations, leading to alterations in genes that control cell growth, division, and other cellular functions. These genetic changes can contribute to the initiation and progression of cancer. 𝟐. 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬: Cancer genome sequencing involves the use of advanced technologies to read and decipher the sequence of DNA bases (adenine, thymine, cytosine, and guanine) that make up an individual's genome. There are various methods for sequencing, including next-generation sequencing (NGS) and single-molecule sequencing. These techniques enable the identification of genetic mutations, structural variations, and other genomic alterations. 𝟑. 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐀𝐥𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐃𝐞𝐭𝐞𝐜𝐭𝐞𝐝: 𝐂𝐚𝐧𝐜𝐞𝐫 𝐠𝐞𝐧𝐨𝐦𝐞 𝐬𝐞𝐪𝐮𝐞𝐧𝐜𝐢𝐧𝐠 𝐜𝐚𝐧 𝐢𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐬𝐞𝐯𝐞𝐫𝐚𝐥 𝐭𝐲𝐩𝐞𝐬 𝐨𝐟 𝐠𝐞𝐧𝐨𝐦𝐢𝐜 𝐚𝐥𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬: ✅ Point Mutations: Changes in a single DNA base pair, which can lead to altered protein function or gene expression. Copy Number Variations (CNVs): Duplications or deletions of segments of DNA, affecting the number of copies of specific genes. ✅ Structural Variations: Large-scale rearrangements, inversions, translocations, and fusions of DNA segments. ✅ Mutational Signatures: Patterns of mutations that provide insights into the underlying causes of DNA damage in cancer cells. 𝟒. 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: ✅ Precision Medicine: By understanding the specific genetic alterations driving a patient's cancer, clinicians can tailor treatments to target these alterations more effectively. ✅ Drug Development: Insights from cancer genome sequencing aid in identifying potential drug targets and developing targeted therapies. ✅ Prognostic Information: Genomic profiling can help predict the aggressiveness of the cancer and guide treatment decisions.