Parkinsonism Relat Disord. 2026 May 22;148:108367. doi: 10.1016/j.parkreldis.2026.108367. Online ahead of print. ABSTRACT BACKGROUND: While genetic testing in Movement Disorders (MD) has expanded enormously, access to genetic testing and genetic counseling remains asymmetric at the global scale. Guidance on efficient testing strategies for clinicians, governments and stakeholders is crucial. OBJECTIVES: Establish a list of genetic movement disorders considered essential as determined by a group of MD experts. METHODS: All genes associated with MD were searched using the OMIM and MDS Gene database. We collected all additional tests available at 4 different laboratories from the EuroGentest database. The results were compiled in 6 questionnaires. A genetic test was considered essential if molecular testing had a direct impact in the management of the patient, including treatment of the disease or its comorbidities, or genetic counseling of the patient and family members. Two Delphi rounds were conducted asking MD experts which specific tests they considered essential in an adult MD clinic. RESULTS: Fifty-nine disorders were considered essential to genetically identify by the MD experts. This included 25 genes associated with ataxia, 15 with parkinsonism, 14 with dystonia, eight with chorea, five with paroxysmal disorders, four with myoclonus, four with hereditary spastic paraparesis, and one with tremor. Sixteen disorders reached 100% consensus among experts: Huntington’s disease, PxMD-PPRT2, Wilson’s disease, DYT-SGCE, DYT-THAP1, DYT-TOR1A, DYT/PARK-GCH1, Fragile-X Tremor-ataxia syndrome, PARK-GBA, PARK-LRRK2, PARK-PINK1, PARK-PRKN, PARK-SNCA, Cerebrotendinous Xanthomatosis, Ataxia-Telangiectasia, and Niemann-Pick disease type C. CONCLUSION: This study provides a list of genetic MD that should be molecularly tested in adult centers with a compatible phenotype according to a group of MD experts. PMID:42202611 | DOI:10.1016/j.parkreldis.2026.108367

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