Klee, Eric W.

ABSTRACT The cohesin complex, composed of SMC1, SMC3, RAD21, and STAG1/STAG2, is essential for chromosome cohesion, DNA repair, and transcriptional regulation. Pathogenic variants in cohesin components cause cohesinopathies. The classical characteristics of cohesinopathies include developmental delay (DD), intellectual disability (ID), feeding difficulties, hypotonia, short stature, hearing loss, and dysmorphic features. Here, we present a 5‐year‐old boy with classical cohesinopathy features, including DD/ID and feeding difficulties, along with non‐classical features such as hypoglycemia, recurrent fever, and immunodeficiency. Trio exome sequencing identified a novel de novo missense variant of uncertain significance (NM_005862.3:c.643G>A(p.Val215Ile)) in the STAG1 gene. The variant localizes to the RAD21 interaction interface, and molecular dynamics (MD) simulations revealed conformational changes comparable to other STAG1 variants reported as likely pathogenic in patients, supporting a deleterious effect which may disrupt the STAG1‐RAD21 interaction interface. This case expands the phenotypic and molecular spectrum of STAG1‐related cohesinopathy and advances our understanding of the disease mechanism.

ABSTRACT Ischemic events after contemporary percutaneous coronary intervention (PCI) are uncommon but carry high morbidity/mortality. Identifying patients at highest risk is critical to guide dual antiplatelet therapy (DAPT) intensity while minimizing bleeding. Current machine learning (ML) model‐developed risk scores do not incorporate pharmacogenetic data. To develop and externally validate ML models that integrate clinical, demographic, and CYP2C19 genetic information to predict 1‐year ischemic outcomes post‐PCI to refine clinical decision making. We analyzed 8317 patients from TAILOR‐PCI trial ( n = 4572) and the Precision PCI registry ( n = 3745). The outcome was a composite of cardiovascular death, myocardial infarction, stroke, and stent thrombosis at 1 year. Boruta feature selection identified 11 predictors. Multiple ML algorithms were trained in TAILOR‐PCI and validated in Precision PCI using cross‐validation and synthetic minority oversampling (SMOTE). Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The best external performance was achieved with a support vector machine (SVM, polynomial kernel) (AUC 0.667; sensitivity 0.871; specificity 0.282), while XGBoost provided a more balanced profile (AUC 0.619; sensitivity 0.442; specificity 0.688). Variable importance for the SVM polynomial model demonstrated that all 11 included Boruta feature selected predictors had relatively high importance (> 75). ML models trained on large clinical trial and real‐world registry datasets can help identify the small subset of patients at high ischemic risk after PCI. This distinction is of relevance because ischemic events are rare, and most patients may safely de‐escalate DAPT to reduce bleeding risk while maintaining ischemic protection through a multimodal approach to risk stratification. Trial Registration: TAILOR‐PCI URL: https://clinicaltrials.gov/ct2/show/NCT01742117

Abstract Rationale Idiopathic Pulmonary Fibrosis (IPF) is characterized by chronic progressive pulmonary fibrosis and high mortality. Genetic markers, summarized into a polygenic risk score (PRS), associate with IPF in well-phenotyped research cohorts. Objectives To evaluate the performance of the PRS using real-world data from routinely captured electronic healthcare records. Methods We conducted an observational study evaluating the association of a PRS for IPF with electronic healthcare record diagnosis of IPF as well as lung transplant-free survival in four independent cohorts; the Mass General Brigham Biobank (MGBB), Mayo Clinic Biobank (MCBB), Mayo Clinic Tapestry Cohort (Tapestry), and U.K. Biobank (UKBB). We used multivariable logistic regression and multivariable Cox proportional hazards models adjusting for age, gender, and principal components of ancestry. The cohorts then underwent fixed and random effects meta-analysis. Measurements and Main Results Of 37,709; 44,195; 43,202; and 447,422 participants from MGBB, MCBB, Tapestry and UKBB respectively, 1,015 (2.7%) 2,879 (6.5%), 1,310 (3.0%), and 2,742 (0.6%) participants had an IPF diagnosis. Meta-analysis demonstrated a high-risk PRS associated with IPF diagnosis, OR 2.88 (95%CI 2.41-3.44) compared to all other individuals. A high-risk PRS also associated with the composite endpoint of mortality or lung transplant among those with an IPF diagnosis, HR 1.23(95%CI 1.11-1.35) compared to all other individuals. Conclusions A PRS can identify those at risk for an IPF diagnosis and mortality in biobank-scale data, which may have implications for clinical decisions. Further work is necessary to evaluate the utility of adding genetics in clinical settings.

ABSTRACT Pathogenic variants in AMMECR1 have been associated with a rare multisystem disorder characterized by midface hypoplasia, hearing impairment, elliptocytosis, and nephrocalcinosis (MFHIEN). To date, most reported cases involve copy number variants or presumed loss‐of‐function alterations, with only a single prior report describing a missense variant supported by functional studies. Here, we report a patient with a heterozygous de novo AMMECR1 missense variant, NM_015365.3:c.649G>A p.(Val217Met) presenting with clinical features consistent with MFHIEN, including midface hypoplasia, partial hearing impairment, nephrocalcinosis, and elliptocytosis identified on peripheral blood smear. Comparative review of the literature highlights that while previously reported missense variants in AMMECR1 demonstrated altered intranuclear protein distribution and reduced expression in functional assays, clinical evidence supporting pathogenicity of non‐truncating variants remains limited. The phenotypic overlap between our patient and prior report strengthens the association between missense variations and the MFHIEN phenotype. Our findings support the pathogenic relevance of missense variation in AMMECR1 and emphasize the importance of integrating detailed phenotyping, including hematologic evaluation, with genomic data in the diagnosis of rare multisystem disorders. Additional cases and functional studies are needed to clarify genotype–phenotype correlations and underlying disease mechanisms.

Abstract Pathogenic variants in cardiomyopathy genes confer substantial disease risk, yet clinical penetrance varies widely. The population-level prevalence, age-specific penetrance, and the extent to which polygenic susceptibility modifies disease risk across diverse ancestries remain poorly defined. This population-based cohort study leveraged genome sequencing and linked electronic health record data from the All of Us Research Program (n=414,830). This study found that P/LP variants in cardiomyopathy-associated genes were present in 0.91% of participants (95% CI, 0.88%–0.94%), with similar prevalence across ancestry groups. Compared with non-carriers, variant carriers had significantly higher odds of all-cause heart failure (ACHF, OR, 2.58; 95% CI, 2.31–2.89), non-ischemic heart failure (NIHF, OR, 2.74; 95% CI, 2.42–3.10), and non-ischemic cardiomyopathy (NICM, OR, 4.99; 95% CI, 4.44–5.63). Among carriers, by age 50 years, 24.5% (95% CI, 14.5%–33.4%) developed ACHF, 17.2% (95% CI, 8.8%–24.8%) developed NIHF, and 30.1% (95% CI, 19.5%–40.2%) developed NICM. Higher polygenic risk for heart failure was independently associated with increased risk of ACHF (OR, 1.81; 95% CI, 1.74–1.89), NIHF (OR, 1.66; 95% CI, 1.58–1.75), and NICM (OR, 1.69; 95% CI, 1.59–1.80). Among carriers with elevated polygenic risk, odds of disease were substantially higher than among non-carriers at average polygenic risk (ACHF: OR, 4.71; 95% CI, 4.17–5.32; NIHF: OR, 4.56; 95% CI, 3.99–5.22; NICM: OR, 8.51; 95% CI, 7.44–9.73). Results showed that P/LP variants in cardiomyopathy genes were relatively common in this large, ancestrally diverse cohort, and conferred increased risk of cardiomyopathy and HF, with incomplete but clinically meaningful penetrance. Polygenic risk for HF independently and additively increased disease risk across ancestries. Integrating both may improve risk stratification and enable more precise, equitable care.

ABSTRACT Polyglucosan body myopathy type 2 (PGBM2; OMIM #616199) is an autosomal recessive myopathy caused by biallelic variants in GYG1 , which encodes glycogenin‐1. It is characterized by progressive muscle weakness and PAS‐positive, diastase‐resistant polyglucosan inclusions on muscle biopsy. We report a 64‐year‐old woman who developed progressive proximal weakness beginning in her early 50s, with polyglucosan bodies identified on muscle histopathology. Genome sequencing (GS) detected a single heterozygous pathogenic splice‐site variant, NM_004130.4( GYG1 ):c.143+3G>C. Given strong histopathologic evidence of PGBM2, GS data were reanalyzed, revealing an additional rare deep intronic variant, NM_004130.4( GYG1 ):c.7+992T>G, predicted to activate a cryptic exon. RNA sequencing (RNA‐seq) confirmed aberrant splicing from both variants, demonstrating exon 2 skipping associated with c.143+3G>C and cryptic exon inclusion caused by c.7+992T>G. Variant phasing posed a diagnostic challenge due to unavailable parental DNA, and long‐range PCR results were inconclusive. Long‐read GS definitively demonstrated that the two variants were in trans , establishing compound heterozygosity and confirming the molecular diagnosis. These findings enabled reclassification of the deep intronic variant as likely pathogenic. This case highlights the diagnostic limitations of conventional phasing approaches in adult‐onset recessive disorders and demonstrates the clinical utility of integrating genome reanalysis, RNA‐seq, and long‐read GS for resolving complex phasing challenges.

Abstract Scientific foundation models learn high-dimensional representations from diverse data modalities, yet what they encode and how to extract that knowledge remain open questions. Here we show that probing the internal representations of Evo 2, a 7-billion-parameter genomic foundation model, enables accurate and interpretable genetic variant effect prediction. We introduce a covariance-based probe that captures second-order structure from Evo 2 sequence embeddings to predict variant pathogenicity across variant types and functional consequences, matching or exceeding specialized predictors within their domains. To ground these predictions in known biological mechanisms, we train a complementary panel of probes on existing annotations to detect which genomic properties are disrupted by a variant. This categorized evidence is then integrated with each variant’s genomic context through a language model to generate variant-specific mechanistic hypotheses. Our pathogenicity predictions correlate with experimental measures of variant function, clinical penetrance, and biobank disease associations while the mechanistic hypotheses are consistent with expert reviews, known mechanism classes, and downstream molecular readouts. We release pathogenicity scores, disruption profiles, and contextualized interpretations for 4.2 million variants from the ClinVar database as an open resource through the Evo Variant Effect Explorer (EVEE). More broadly, this structured probing approach offers a general framework for interrogating foundation models across scientific disciplines and grounding their outputs in existing domain concepts.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal dominant genetic disorder that increases risk for premature coronary artery disease and has accessible and effective interventions. The Dutch lipid clinic network is currently the most used diagnostic criterion; however, genetic sequencing provides a definitive diagnosis of FH. The goals of this study were to determine whether germline genetic screening using exome sequencing could be used to efficiently identify individuals who were genotype positive for FH. METHODS: Participants were recruited from 3 geographically and racially diverse sites in the United States (Rochester, MN; Phoenix, AZ; and Jacksonville, FL). Participants underwent Exome+ sequencing (dba Helix, San Mateo, CA) and return of results for specific genetic findings in APOB , LDLR , or PCSK9 . A chart review was performed to collect demographics, personal, and family cardiovascular history. RESULTS: At the time of the study, 84 413 participants were enrolled in the Tapestry study. Annotation and interpretation of all variants in genes for FH resulted in the identification of 419 likely pathogenic and pathogenic variants (prevalence, 0.50%), which included 116 APOB , 298 LDLR , and 5 PCSK9 . Sixty-six percent were female, the mean body mass index was 27.3, with 12.3% reporting a history of diabetes. Hypertriglyceridemia (≥150 mg/dL) was present in 39.5% and reduced HDL (<50 mg/dL) was present in 56.7% of patients. 27.5% of patients were not on cholesterol-lowering medications, and only 10% of FH carriers were at goal low-density lipoprotein cholesterol levels. A history of coronary artery disease was reported in 22.4% of the cohort. Nearly 90% of these participants were newly diagnosed carriers of FH. Only 30.8% of confirmed genetic diagnoses of FH satisfied clinical (Dutch lipid clinic network) criteria for a diagnosis. CONCLUSIONS: Our results emphasize the need for wider utilization of germline genetic sequencing for enhanced screening and detection of individuals who have familial hypercholesterolemia. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05212428.

ABSTRACT Femoroacetabular impingement (FAI) of the hip results from altered morphology of the proximal femur and/or acetabulum, creating abnormal contact between these structures during normal hip range of motion. The etiology of this structural phenotype is unknown. This study aimed to identify common single‐nucleotide variants (SNVs) among two families with seemingly heritable FAI. Additionally, this study examined biologic networks among proteins encoded by identified SNVs and surveyed the literature regarding the role of these proteins in musculoskeletal development. Methodologically, blood samples were collected from affected and unaffected members of two separate families with a pattern of heritable FAI. Exome sequencing identified SNVs, and a protein–protein interaction network assessment, in addition to a literature review, was performed to better understand the role of variant‐associated genes in musculoskeletal development. Results showed 33 and 43 variant‐associated genes affected in Family 1 and Family 2, respectively. Although no overlap in variant‐associated genes was found between families, network analysis showed that variant‐associated genes are functionally interconnected and are known to interact with each other. Furthermore, the variant‐associated genes are broadly associated with musculoskeletal development. Ultimately, genetic analysis of two families of multiple generations of FAI revealed variations in genes regulating musculoskeletal development, with several being critical local regulators of bone morphogenesis.