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Base by Base

Gustavo Barra
Base by Base
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  • 114: One-hour extraction-free loop-mediated isothermal amplification HPV DNA assay for point-of-care testing in Maputo, Mozambique
    ️ Episode 114: One-hour extraction-free loop-mediated isothermal amplification HPV DNA assay for point-of-care testing in Maputo, Mozambique In this episode of PaperCast Base by Base, we explore the development of a rapid and affordable HPV DNA test designed for cervical cancer screening in low-resource settings. The study introduces a one-hour, extraction-free loop-mediated isothermal amplification (LAMP) assay that directly processes cervicovaginal samples without complex infrastructure. Study Highlights:The researchers designed a multiplex LAMP assay targeting HPV16, HPV18, and HPV45—the three HPV types most responsible for cervical cancer—along with a cellular control. Using a simple benchtop fluorimeter, the test delivered results in under one hour with high analytical sensitivity and specificity. Clinical validation in Houston, Texas, showed perfect concordance with the reference standard, while evaluation in Maputo, Mozambique, achieved 93% concordance. The assay minimized handling steps by using chemical lysis and direct addition of lysate to the reaction, enabling point-of-care applicability. Conclusion:This proof-of-concept assay demonstrates the potential to expand cervical cancer screening in low-resource settings through a rapid, accurate, and affordable molecular test. Reference:Barra, M.J., Wilkinson, A.F., Ma, A.E., Goli, K., Atif, H., Osman, N.M.R.B., Lorenzoni, C., Tivir, G., Lathrop, E.H., Castle, P.E., Guo, M., Montealegre, J.R., Baker, E.S., Salcedo, M.P., Schmeler, K.M., & Richards-Kortum, R.R. (2025). One-hour extraction-free loop-mediated isothermal amplification HPV DNA assay for point-of-care testing in Maputo, Mozambique. *Nature Communications*, 16, 7295. https://doi.org/10.1038/s41467-025-62454-x License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/ Keywords: HPV, cervical cancer screening, LAMP assay, point-of-care diagnostics, low-resource settings On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.  
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  • 113: Joint, Multifaceted Genomic Analysis Enables Diagnosis of Ultra-Rare Monogenic Presentations
    ️ Episode 113: Joint, Multifaceted Genomic Analysis Enables Diagnosis of Ultra-Rare Monogenic Presentations In this episode of PaperCast Base by Base, we explore how the Undiagnosed Diseases Network (UDN) applied whole‑genome sequencing and new, well‑calibrated statistics to jointly analyze diverse, ultra‑rare monogenic cases across the consortium, yielding confirmed and putative diagnoses while enabling privacy‑preserving cross‑cohort discovery via shareable summary statistics. Study Highlights:The authors introduce RaMeDiES, a suite of analytical methods that detect gene‑level recurrence of deleterious de novo variants (RaMeDiES‑DN) and prioritize compound‑heterozygous configurations (RaMeDiES‑CH), with an individual‑level ranking (RaMeDiES‑IND) to surface single‑case recessive candidates. Using 4,236 individuals with harmonized whole‑genome data—including over a thousand complete trios—the framework integrates state‑of‑the‑art mutation‑rate models and variant effect scores, and extends to deep intronic splice‑altering variants supported by a massively parallel splicing reporter assay. The joint analysis recapitulates known diagnoses and uncovers new or strengthened gene–disease links, including de novo signals in KIF21A, BAP1, RHOA, KMT2B, histone H4 genes (H4C5), LRRC7 and ZNF865, and a compound‑heterozygous candidate in MED11 with RNA‑seq evidence of intron retention. Pathway‑level analysis within phenotype‑clustered patient groups highlights enriched biological modules such as the immunoproteasome (POMP/PSMB8) and a transmembrane signaling set containing CACNA1C, GABRA3 and HCN4, aligning with shared clinical features. The team releases an open browser of cohort findings and the open‑source RaMeDiES software to enable automated, de‑identified cross‑cohort analyses. Conclusion:This work shows that rigorous, summary‑statistic–based joint genomics can boost rare‑disease diagnosis and gene discovery while paving the way for scalable, privacy‑aware international meta‑analyses. Reference:Kobren, S. N., Moldovan, M. A., Reimers, R., Traviglia, D., Li, X., Barnum, D., Veit, A., Corona, R. I., Carvalho Neto, G. de V., Willett, J., Berselli, M., Ronchetti, W., Nelson, S. F., Martinez‑Agosto, J. A., Sherwood, R., Krier, J., Kohane, I. S., Undiagnosed Diseases Network, & Sunyaev, S. R. (2025). Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra‑rare monogenic presentations. Nature Communications, 16, 7267. https://doi.org/10.1038/s41467-025-61712-2 License:This episode is based on an open‑access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one‑time or monthly donation here: https://basebybase.castos.com/ Keywords: rare disease genomics, de novo recurrence, compound heterozygous, RaMeDiES, Undiagnosed Diseases Network On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.
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  • 112: Local Genetic Sex Differences in Quantitative Traits
    ️ Episode 112: Local Genetic Sex Differences in Quantitative Traits In this episode of PaperCast Base by Base, we explore how genetic differences between males and females are distributed across the genome, moving beyond global averages of heritability and correlation. The study introduces a fine-scale approach using LAVA to examine local genetic sex differences across 157 quantitative traits in the UK Biobank. Study Highlights:The researchers analyzed sex-stratified GWAS summary statistics and partitioned the genome into nearly 2,500 loci. They estimated local heritabilities, genetic correlations, and equality of genetic effects, finding that nearly every trait had at least one locus with sex-specific genetic architecture. Many differences appeared in blood biomarkers, with testosterone, urate, and lipoprotein traits showing strong local divergence. The study also demonstrated how interpretations vary depending on whether genetic effect sizes are assessed on raw or standardized scales, with standardized scales being more informative for heritability comparisons. Moreover, loci such as APOE and AKR1C genes revealed clear biological differences between the sexes, highlighting how local analyses can uncover dimorphic mechanisms missed in global assessments. Conclusion:This work shows that local analyses provide crucial insights into sex-specific genetic effects, revealing subtle but biologically meaningful differences that global metrics can obscure. Reference:Uffelmann, E., de Leeuw, C., Schipper, M., & Posthuma, D. (2025). Local genetic sex differences in quantitative traits. *Nature Communications, 16*(7232). https://doi.org/10.1038/s41467-025-62504-4 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/  Keywords: sex differences, local heritability, genetic correlation, GWAS, quantitative traits On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.  
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  • 111: A Multimodal Dataset for Precision Oncology in Head and Neck Cancer
    ️ Episode 111: A Multimodal Dataset for Precision Oncology in Head and Neck Cancer In this episode of PaperCast Base by Base, we explore the creation of HANCOCK, a comprehensive multimodal dataset designed to advance precision oncology in head and neck cancer. The study addresses the urgent need for large, publicly available datasets to improve biomarker discovery and outcome prediction in this challenging disease. Study Highlights:The HANCOCK dataset integrates real-world data from 763 patients, including demographics, pathology, blood tests, surgery reports, and histologic images. By combining these modalities, the researchers created multimodal patient vectors that capture complex interdependencies and enable robust machine learning analyses. They demonstrated that multimodal integration significantly improves prediction of survival and recurrence compared to single-modality approaches, achieving high accuracy with Random Forest classifiers. Furthermore, the study showed that incorporating imaging data using multiple instance learning and pathology foundation models enhances clinical endpoint prediction, reinforcing the value of multimodal strategies for oncology. Conclusion:This work establishes HANCOCK as a unique open-access resource that will catalyze future research in biomarker discovery, multimodal AI integration, and personalized treatment strategies for head and neck cancer. Reference:Dörrich M, Balk M, Heusinger T, Beyer S, Mirbagheri H, Fischer DJ, Kanso H, Matek C, Hartmann A, Iro H, Eckstein M, Gostian A-O, Kist AM. A multimodal dataset for precision oncology in head and neck cancer. *Nature Communications*. 2025;16:7163. https://doi.org/10.1038/s41467-025-62386-6 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/ Keywords: head and neck cancer, multimodal dataset, machine learning, biomarkers, precision oncology On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.  
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  • 110: Whole-exome sequencing identifies new schizophrenia risk genes
    ️ Episode 110: Whole-exome sequencing identifies new schizophrenia risk genes In this episode of PaperCast Base by Base, we explore a landmark whole-exome sequencing study that expands our understanding of the rare genetic variants contributing to schizophrenia risk. By combining newly sequenced samples with large-scale published datasets, researchers provide the most comprehensive analysis to date of rare coding variants in this psychiatric disorder. Study Highlights:The study analyzed exome sequencing data from 4,650 new schizophrenia cases and 5,719 controls, which were combined with previously published datasets totaling nearly 29,000 cases, over 103,000 controls, and 3,444 proband-parent trios. Using meta-analysis, researchers identified exome-wide significant associations for two genes, STAG1 and ZNF136, strengthening prior evidence of their role in schizophrenia. Six additional genes reached statistical support at a false discovery rate below 5%, including SLC6A1 and KLC1, which were associated with damaging missense variants. The implicated genes overlap with those involved in neurodevelopmental and psychiatric disorders such as autism, developmental delay, and epilepsy. These findings highlight the convergence of rare coding variants with common variant signals and structural variation, particularly in pathways related to chromatin organization and neuronal signaling. Conclusion:This study advances the genetic landscape of schizophrenia by implicating new risk genes, underscoring the importance of rare coding variants and offering insights into disease mechanisms with potential relevance for future precision psychiatry. Reference:Chick, S. L., Holmans, P., Cameron, D., Grozeva, D., Sims, R., Williams, J., Bray, N. J., Owen, M. J., O’Donovan, M. C., Walters, J. T. R., & Rees, E. (2025). Whole-exome sequencing analysis identifies risk genes for schizophrenia. *Nature Communications, 16*, 7102. https://doi.org/10.1038/s41467-025-62429-y License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/  Keywords: schizophrenia, rare coding variants, whole-exome sequencing, STAG1, SLC6A1 Chapters (00:00:00) - The genetics of schizophrenia(00:01:21) - Celebrating the genetic puzzle of schizophrenia(00:05:28) - The Bigger Study of Schizophrenia(00:08:29) - Schizophrenia genetics: The gold standard(00:10:59) - The convergence of genetic signals for STAG1 and KLC1(00:12:21) - Scratching the genetic map of schizophrenia(00:16:49) - Schizophrenia genetic diversity and how to spot it
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Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.
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