bims-tyki2d 2026-06-14 papers

Issue of 2026–06–14
five papers selected by
Zoya Panahloo, UCB

J Appl Lab Med. 2026 Jun 09. pii: jfag079. [Epub ahead of print]

AI'm Here to Help: Enhancing Laboratory Genetic Counseling with Artificial Intelligence.

Zöe Powis, Khalida Liaquat, Matthew L Tschirgi.

BACKGROUND: Artificial intelligence (AI) is transforming the fields of genetics and genetic counseling, enhancing both clinical and laboratory practices. The rise of AI technologies has drawn attention to their potential impact on genetic counseling, particularly in patient diagnosis and the counseling processes.
CONTENT: In the laboratory, AI plays a critical role in improving communication between laboratory genetic counselors and healthcare providers by automating routine tasks and optimizing workflows. These advancements allow genetic counselors to dedicate more time to addressing complex inquiries, improving genetic test selection, and helping providers interpret genetic test results. As AI continues to integrate into laboratory genetic counseling practice, it presents both opportunities and challenges. At the time of submission, there is a large knowledge gap regarding AI and its application to laboratory genetic counseling, given the lack of published information on this topic.
SUMMARY: This article summarizes existing literature, the history and current applications of AI in laboratory genetic counseling, examines its benefits and limitations, and explores future directions for its implementation in the field.

DOI: https://doi.org/10.1093/jalm/jfag079

Genome Med. 2026 Jun 11. pii: 83. [Epub ahead of print]18(1):

Genetically supported drug target prioritization for rare diseases.

Robert Chen, Áine Duffy, Matthew Mort, David N Cooper, Ghislain Rocheleau, Daniel M Jordan, Ron Do.

RareGPS is a machine-learning framework prioritizing drug targets for rare and uncommon diseases, integrating 11 genetic, clinical, and experimental evidence sources. It uses the full distribution of genetic associations across allele-frequency bins in an allelic-series model. Across 161 phenotypes, RareGPS outperforms existing resources for predicting drug indications and clinical trial progression; top 1% targets show 58-fold higher likelihood of advancing from nonindicated to phase IV and 8-fold from phase I to IV versus the middle 50%. We validated RareGPS using prescriptome analyses in two million patients and an independent literature evaluation tool (AMELIE). We publish predictions for 3,021,965 gene-phenotype pairs.

Keywords: Drug Discovery; Electronic Health Records; Genetic Association Studies; Machine Learning; Off-Label Use; Rare Diseases

DOI: https://doi.org/10.1186/s13073-026-01671-5

Arch Med Res. 2026 Jun 11. pii: S0188-4409(26)00088-3. [Epub ahead of print]57(8): 103466

Rare disease nomenclature and coding: challenges, systems, and policies in the global context.

Ashray Vohora, Sylvie Maiella, Caterina Lucano, Kurt Kirch, Carina Thomas, Stefanie Weber, Ana Rath.

Rare diseases (RD) collectively affect millions of people worldwide yet remain poorly represented in generic coding terminologies. This lack of representation impedes patient visibility in health systems, in turn engendering downstream consequences such as negatively impacting patient outcomes, clinical research, and RD policy. This review evaluates the intricacies of the common coding systems currently employed to capture RD, and surveys the coding practices and policies in select countries as they pertain to RD. We analyse published literature, mappings between terminologies, and results from recent European projects to assess the applicability of generic and specific coding standards in clinical and registry settings. Globally, RD coding practices are demonstrated to be inconsistent and highly variable, although often rely on generic terminologies (ICD variations and other broad terminologies). Major drivers include heterogeneous national policies and the reliance on legacy standards. Furthermore, our findings reveal that generic classifications, due to their intended use for statistical purposes, provide limited and uneven coverage for RD and lack mechanisms to flag RD patients who have not yet received a diagnosis. In contrast, the Orphanet nomenclature (ORPHAcodes) offers coverage of all RD in the Orphanet knowledge base, a dedicated code for undiagnosed cases, and mappings to major terminologies, thereby improving patient visibility and data interoperability. We propose that the routine use of ORPHAcodes alongside generic classifications, supported by legal frameworks, governance, and implementation support, will enhance RD outcomes and facilitate RD research and policymaking. Coordinated stakeholder collaboration will be essential to realise these benefits to the RD community.

Keywords: Codification policy; Health data; Health information systems; Medical terminology; Rare Disease

DOI: https://doi.org/10.1016/j.arcmed.2026.103466

Genet Med. 2026 Jun 09. pii: S1098-3600(26)00943-3. [Epub ahead of print] 102625

Genomics to Enhance Newborn Screening ?

Alban Ziegler, Wendy K Chung.

Newborn screening is a major public health achievement, enabling early detection and treatment of serious medical conditions before onset of irreversible damage to health. The scope of newborn screening has continuously expanded with the addition and innovations in screening platforms including tandem mass spectrometry. Genomic newborn screening provides another platform using genomic DNA sequencing as a first-tier test to improve and expand screening for actionable genetic conditions. Genome coverage affords flexibility to incorporate new diseases rapidly as new effective therapies are available. Several pilot studies around the world have demonstrated the feasibility and high parental uptake of genomic newborn screening and highlight challenges that need to be addressed including accurate and efficient variant interpretation across all ancestral groups, effective methods to physiologically assess DNA screening results, accurate penetrance estimates with population based screening to inform what genes and variants within genes to include on screening and how to manage individuals with positive screening results, meeting rapid turnaround time requirements, increasing scale, decreasing cost, and providing the evidence and health economic data about value to inform policy. Successful implementation will likely evolve over time and would be facilitated by dedicated national infrastructure to support DNA sequencing, variant interpretation and follow up to allow for feedback to improve and optimize the screening system. International sharing of genomic newborn screening experience could maximize efficiency of improvement, especially in these early stages and will need to balance data sharing and data privacy. By dramatically expanding the scope of conditions screened and identified shortly after birth, genomic newborn screening has the potential to improve public health for future generations of children, especially if and when platforms for gene based therapies are safe, effective, and affordable for large numbers of conditions.

Keywords: GUARDIAN; Gene based therapies; Genomic newborn screening; Newborn screening; Scope

DOI: https://doi.org/10.1016/j.gim.2026.102625

J Neurol. 2026 Jun 09. pii: 384. [Epub ahead of print]273(7):

Muscle biopsy in genomic era: real-world diagnostic and clinical implications over 10 years.

Dario Zoppi, Rosario Russo, Virginia Boemia, Martina De Maria, Anita Marciano E Ortolano, Francesca Vallefuoco, Elvira D'Amico, Gianni Di Costanzo, Anna Russo, Teresa Somma, Maria Nolano, Rosa Iodice, Luigi Maria Cavallo, Fiore Manganelli, Lucia Ruggiero.

BACKGROUND: The diagnostic role of muscle biopsy has evolved with the increasing availability of next-generation sequencing (NGS). However, real-world data on its clinical impact in contemporary neuromuscular practice remain limited.
OBJECTIVE: To evaluate the diagnostic yield of muscle biopsy in a 10 year consecutive cohort, assessing concordance across clinical suspicion, histopathological findings, and final clinical diagnosis, and exploring demographic predictors of biopsy outcome.
METHODS: A retrospective cohort study of all consecutive muscle biopsies performed at a single tertiary neuromuscular center (2015-2025). Concordance analysis was performed at two levels: clinical suspicion vs. biopsy conclusion, and biopsy conclusion vs. final diagnosis at the last follow-up. Sex- and age-related differences across biopsy categories were evaluated using chi-square and Kruskal-Wallis tests.
RESULTS: Among 401 consecutive biopsies (56.9% male; median age 49 years), overall concordance between clinical suspicion and biopsy conclusion was 42.3%. Concordance with final clinical diagnosis was substantially higher, reaching 94.0% for idiopathic inflammatory myopathies (IIMs) among evaluable cases. Non-specific myopathic findings and normal biopsies accounted for 36.0% of cases; however, patients with non-specific myopathic findings were significantly more likely to receive a conclusive diagnosis at follow-up than those with normal biopsies (43.8% vs. 23.4%; OR 2.54, 95% CI 1.23-5.26, p = 0.011). Sex distribution differed significantly across biopsy categories (p < 0.001), with IIMs showing marked female predominance (69.1%).
CONCLUSIONS: Muscle biopsy retains high diagnostic value in contemporary neuromuscular practice when applied to clinically selected patients. Beyond establishing specific diagnoses, biopsy findings carry prognostic significance and provide demographic signatures that reinforce their clinical validity.

Keywords: Diagnostic yield; HyperCKemia; Muscle biopsy; Next-generation sequencing

DOI: https://doi.org/10.1007/s00415-026-13917-8