Biol Psychiatry. 2025 Sep 30:S0006-3223(25)01485-4. doi: 10.1016/j.biopsych.2025.09.010. Online ahead of print. ABSTRACT BACKGROUND: Genetic testing may provide important diagnostic information for individuals with schizophrenia, but the frequency with which clinically significant variants are identified across different testing approaches has not been systematically evaluated. METHODS: We conducted a systematic review and meta-analysis searching MEDLINE, EMBASE, and APA PsycINFO (January 2007-June 2023) for studies reporting results of clinical genetic testing in schizophrenia. Two independent reviewers performed abstract/title screening, full-text review, and data extraction following PRISMA guidelines. A random-effects model was used to estimate the pooled and platform-specific proportions of individuals with pathogenic or likely pathogenic variants, with heterogeneity assessed using the I² statistic. RESULTS: Analysis of 31 studies (20,476 participants) showed that 6% (95% CI: 4% to 7%) of individuals with schizophrenia had a clinically significant genetic variant identified. Detection rates were 6% (95% CI: 4% to 8%) for chromosomal microarray, 5% (95% CI: -0.02% to 12%) for exome sequencing, and 7% (95% CI: 2% to 12%) for genome sequencing. Substantial heterogeneity was observed across studies (I² = 95.9%). Geographic representation was limited, with no studies from Latin America, South Asia, or Africa. CONCLUSIONS: Genetic testing identifies clinically informative variants in approximately 6% of individuals with schizophrenia. However, substantial heterogeneity across studies and limited geographic representation underscore the need for more standardized testing approaches and broader population sampling in future genetic research on schizophrenia. PMID:41038604 | DOI:10.1016/j.biopsych.2025.09.010

Nat Commun. 2025 Aug 7;16(1):7267. doi: 10.1038/s41467-025-61712-2. ABSTRACT Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform in-depth analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development. The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale case-based diagnostic analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser ( https://dbmi-bgm.github.io/udn-browser/ ). These results show that case-level diagnostic efforts should be supplemented by a joint genomic analysis across cohorts. PMID:40770127 | DOI:10.1038/s41467-025-61712-2

Cancer Discov. 2025 Aug 7:OF1-OF24. doi: 10.1158/2159-8290.CD-24-1738. Online ahead of print. ABSTRACT Extrachromosomal DNA (ecDNA) amplification enhances intercellular oncogene dosage variability and accelerates tumor evolution by violating foundational principles of genetic inheritance through its asymmetric mitotic segregation. Spotlighting high-risk neuroblastoma, we demonstrate how ecDNA amplification undermines the clinical efficacy of current therapies in cancers with extrachromosomal MYCN amplification. Integrating theoretical models of oncogene copy number-dependent fitness with single-cell ecDNA quantification and phenotype analyses, we reveal that ecDNA copy-number heterogeneity drives phenotypic diversity and determines treatment sensitivity through mechanisms unattainable by chromosomal oncogene amplification. We demonstrate that ecDNA copy number directly influences cell fate decisions in cancer cell lines, patient-derived xenografts, and primary neuroblastomas, illustrating how extrachromosomal oncogene dosage-driven phenotypic diversity offers a strong evolutionary advantage under therapeutic pressure. Furthermore, we identify senescent cells with reduced ecDNA copy numbers as a source of treatment resistance in neuroblastomas and outline a strategy for their targeted elimination to improve the treatment of MYCN-amplified cancers. SIGNIFICANCE: ecDNA-driven tumor genome evolution provides a major challenge to curative cancer therapies. We demonstrate that ecDNA copy-number dynamics drives treatment resistance by promoting oncogene dosage-dependent phenotypic heterogeneity in MYCN-amplified cancers. Exploiting phenotype-specific vulnerabilities of ecDNA cells, therefore, presents a powerful strategy to overcome treatment resistance. See related article by Korsah, p. XX. PMID:40773595 | DOI:10.1158/2159-8290.CD-24-1738

Genet Med. 2025 Mar 7:101403. doi: 10.1016/j.gim.2025.101403. Online ahead of print. ABSTRACT PURPOSE: To explore long-term trajectories of children who received rapid genome sequencing (RGS) in intensive care settings. METHODS: We examined the electronic health records (EHR) of 67 critically ill pediatric patients who received RGS six to eight years ago with a collective initial diagnostic yield of 46%. RESULTS: The median length of follow up was 6.2 years (IQR 4.0-7.2 years). RGS-diagnosed patients had a longer average follow-up time compared to undiagnosed patients (5.9 years vs 4.8 years, p = 0.026) and more subspecialty appointments per follow-up year (9.4 vs 6.9, p = 0.036). Mortality during the follow-up period was 9%. Patients averaged 2.1 hospital readmissions per follow-up year and 28.1 hospitalized days per follow-up year. Forty-four patients (66%) had a documented new phenotype in the EHR during their follow-up period. Seven patients received clinician-driven re-analysis during the follow-up period, yielding one new diagnosis. Systematic reanalysis of RGS performed as part of this study identified four new candidate diagnoses. CONCLUSION: Pediatric patients who receive RGS during intensive care unit hospitalizations continue to be high healthcare utilizers in subsequent years, regardless of whether RGS identified a diagnosis. Additionally, two-thirds of this cohort had a documented phenotypic change over the follow-up period, indicating dynamic clinical evolution in the years following RGS. PMID:40062436 | DOI:10.1016/j.gim.2025.101403

NPJ Genom Med. 2025 Jun 12;10(1):47. doi: 10.1038/s41525-025-00506-3. ABSTRACT Identifying critically ill newborns who will benefit from whole genome sequencing (WGS) is difficult and time-consuming due to complex eligibility criteria and evolving clinical features. The Mendelian Phenotype Search Engine (MPSE) automates the prioritization of neonatal intensive care unit (NICU) patients for WGS. Using clinical data from 2885 NICU patients, we evaluated the utility of different machine learning (ML) classifiers, clinical natural language processing (CNLP) tools, and types of Electronic Health Record (EHR) data to identify sick newborns with genetic diseases. Our results show that MPSE can identify children most likely to benefit from WGS within the first 48 h after NICU admission, a critical window for maximally impactful care. Moreover, MPSE provided stable, robust means to identify these children using many combinations of classifiers, CNLP tools, and input data types-meaning MPSE can be used by diverse health systems despite differences in EHR contents and IT support. PMID:40506467 | DOI:10.1038/s41525-025-00506-3

Am J Hum Genet. 2025 Apr 3:S0002-9297(25)00110-7. doi: 10.1016/j.ajhg.2025.03.011. Online ahead of print. ABSTRACT The use of genomic sequencing (GS) for prenatal diagnosis of fetuses with sonographic abnormalities has grown tremendously over the past decade. Fetal GS also offers an opportunity to identify incidental genomic variants that are unrelated to the fetal phenotype but may be relevant to fetal and newborn health. There are currently no guidelines for reporting incidental findings from fetal GS. In the United States, GS for adults and children is recommended to include a list of “secondary findings” genes (ACMG SF v.3.2) that are associated with disorders for which surveillance or treatment can reduce morbidity and mortality. The genes on ACMG SF v.3.2 predominantly cause adult-onset disorders. Importantly, many genetic disorders with fetal and infantile onset are treatable as well. A proposed solution is to create a “treatable fetal findings list,” which can be offered to pregnant individuals undergoing fetal GS or, eventually, as a standalone cell-free fetal DNA screening test. In this integrative review, we propose criteria for a treatable fetal findings list, then identify genetic disorders with clinically available or emerging fetal interventions and those for which clinical detection and intervention in the first week of life might lead to improved outcomes. Finally, we synthesize the potential benefits, limitations, and risks of a treatable fetal findings list. PMID:40209713 | DOI:10.1016/j.ajhg.2025.03.011

Nature. 2025 Mar 26. doi: 10.1038/s41586-025-08676-x. Online ahead of print. ABSTRACT Meningomyelocele (also known as spina bifida) is considered to be a genetically complex disease resulting from a failure of the neural tube to close. Individuals with meningomyelocele display neuromotor disability and frequent hydrocephalus, requiring ventricular shunting. A few genes have been proposed to contribute to disease susceptibility, but beyond that it remains unexplained¹. We postulated that de novo mutations under purifying selection contribute to the risk of developing meningomyelocele². Here we recruited a cohort of 851 meningomyelocele trios who required shunting at birth and 732 control trios, and found that de novo likely gene disruption or damaging missense mutations occurred in approximately 22.3% of subjects, with 28% of such variants estimated to contribute to disease risk. The 187 genes with damaging de novo mutations collectively define networks including actin cytoskeleton and microtubule-based processes, Netrin-1 signalling and chromatin-modifying enzymes. Gene validation demonstrated partial or complete loss of function, impaired signalling and defective closure of the neural tube in Xenopus embryos. Our results indicate that de novo mutations make key contributions to meningomyelocele risk, and highlight critical pathways required for neural tube closure in human embryogenesis. PMID:40140573 | DOI:10.1038/s41586-025-08676-x

Neuron. 2025 Apr 16;113(8):1126-1128. doi: 10.1016/j.neuron.2025.03.026. ABSTRACT In this issue of Neuron, Yang et al.¹ reveal that primary cilia in mouse prefrontal cortex excitatory neurons regulate stress responses via cAMP/PKA signaling. Stress induces ciliary elongation, enhancing corticosterone-mediated neuronal inhibition. Cilia loss reduces stress sensitivity, highlighting their role in stress adaptation, with potential therapeutic relevance. PMID:40245842 | DOI:10.1016/j.neuron.2025.03.026

NPJ Digit Med. 2025 Jan 30;8(1):72. doi: 10.1038/s41746-025-01458-9. ABSTRACT The Mendelian Phenotype Search Engine (MPSE), a clinical decision support tool using Natural Language Processing and Machine Learning, helped neonatologists expedite decisions to whole genome sequencing (WGS) to diagnose patients in the neonatal intensive care unit. After the MPSE was introduced, utilization of WGS increased, time to ordering WGS decreased, and WGS diagnostic yield increased. PMID:39885315 | DOI:10.1038/s41746-025-01458-9

Development. 2025 Jan 1;152(1):dev204306. doi: 10.1242/dev.204306. Epub 2025 Jan 2. ABSTRACT Human GABAergic inhibitory neurons (INs) in the telencephalon play crucial roles in modulating neural circuits, generating cortical oscillations, and maintaining the balance between excitation and inhibition. The major IN subtypes are based on their gene expression profiles, morphological diversity and circuit-specific functions. Although previous foundational work has established that INs originate in the ganglionic eminence regions in mice, recent studies have questioned origins in humans and non-human primates. We review the origins of INs in mice and compare with recent findings from primary human prenatal brain tissue culture experiments and lineage analysis from somatic variants in neurotypical human cadavers and human brain organoids. Together, these studies suggest potential primate- or human-specific processes that may have been overlooked in mouse models and could have implications for brain disorders. PMID:39745314 | DOI:10.1242/dev.204306