Citations

Abstract Aims To compare the prevalence of autism spectrum disorder (ASD) in children with and without epilepsy using clinical diagnoses and chart review with research‐defined criteria and to examine sex ratios, age at ASD onset, and intellectual disability between groups. Method The Olmsted County birth cohort included 30 490 individuals, of whom 257 (0.84%) had epilepsy diagnosed before 19 years of age. The cohort was previously screened for ASD using three case definitions: research‐inclusive (ASD‐R I ), research‐narrow (ASD‐R N ), and clinically diagnosed ASD (ASD‐C). For those with ASD‐R I , we assessed sex, intellectual disability (IQ < 70), and age at ASD onset. Means and proportions are reported when available. Results ASD prevalence was significantly higher in participants with epilepsy across all definitions: ASD‐R I 21.4% versus 3.2%; ASD‐R N 14.0% versus 1.6%; and ASD‐C 7.9% versus 0.7%. Children with both epilepsy and ASD‐R I were more often female (38.2% vs 25.8%), had higher rates of intellectual disability (56.5% vs 15.4%), and met the ASD‐R I criteria at a younger age (mean 7 years 5 months vs 8 years 8 months). Interpretation Co‐occurring ASD and epilepsy are frequently associated with intellectual disability, earlier age at ASD diagnosis, and reduced male predominance.

Abstract Rare Mendelian disorders affect 300-400 million people globally. Although genetic testing has become widely adopted, gene-specific evidence for tailored variant interpretation remains scattered across resources. We present Gene Portals, a framework for gene-centered multimodal knowledge bases that co-localize expert-harmonized clinical data, functional assays, population variation, structural annotations and gene-specific ACMG/AMP specifications within a single resource. A modular interface integrates this unified evidence with VCEP-refined ACMG specifications to enable automated gene-specific variant classification, infer molecular mechanisms, and support cross-gene analyses. We demonstrate the framework’s utility across five Gene portals spanning eleven neurodevelopmental disorder-associated genes, integrating data from 4,423 individuals with 2,838 unique variants, 36,149 ClinVar submissions, and 1,044 expert-curated molecular readouts. By organizing evidence that is otherwise dispersed across multiple sources into a unified, queryable framework, the SCN, GRIN, CACNA1A, SATB2 and SLC6A1 Gene Portals became widely used community resources and provide an extensible template for standardized rare-disease variant interpretation and mechanism-aware discovery.

ABSTRACT: Objective: Determine the risk of autoimmune disease in research-identified cases of autism spectrum disorder (ASD) compared with referents using a longitudinal, population-based birth cohort. Methods: ASD incident cases were identified from a population-based birth cohort of 31,220 individuals. Inclusive ASD definition based on DSM-IV-TR autistic disorder, Asperger syndrome, and pervasive developmental disorder, not otherwise specified, was used to determine ASD cases. For each ASD case, 2 age- and sex-matched referents without ASD were identified. Diagnosis codes assigned between birth and December 2017 were electronically obtained. Individuals were classified as having an autoimmune disorder if they had at least 2 diagnosis codes more than 30 days apart. Cox proportional hazards models were fit to estimate the hazard ratio (HR) between ASD status and autoimmune disorder. Results: Of 1014 ASD cases, 747 (73.7%) were male. Fifty ASD cases and 59 of the 1:2 matched referents were diagnosed with first autoimmune disorder at the median age of 14 and 17.1 years, respectively. ASD cases had increased risk of autoimmune disease compared with matched referents (HR 1.74; 95% confidence interval [CI], 1.21–2.52). The increased risk was statistically significant among male patients (HR 2.01; 95% CI, 1.26–3.21) but not among the smaller number of female subjects (HR 1.38; 95% CI, 0.76–2.50). Conclusion: This study provides evidence from a longitudinal, population-based birth cohort for co-occurrence of ASD and autoimmune disorders. Thus, children with ASD should be monitored for symptoms of autoimmune disease and appropriate workup initiated.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

OBJECTIVES We aimed to describe the intellectual ability and ratio of boys to girls with average or higher IQ within autism spectrum disorder (ASD) cases identified in a population-based birth cohort. We hypothesized that research-identified individuals with ASD would be more likely to have average or higher IQ, compared to clinically diagnosed ASD. We also hypothesized the male to female ratio would decrease as the definition of ASD broadened. METHODS ASD incident cases were identified from 31 220 subjects in a population-based birth cohort. Research-defined autism spectrum disorder, inclusive criteria (ASD-RI) was based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision, autistic disorder (AD), Asperger Disorder, and pervasive developmental disorder not otherwise specified criteria. Research-defined autism spectrum disorder, narrow criteria (ASD-RN) was a narrower definition based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision AD criteria. Clinical diagnoses of ASD were abstracted from medical and school records. Intellectual ability was based on the last IQ score or on documented diagnoses of intellectual disability if no scores available. Average or higher IQ was defined as IQ ≥86. RESULTS A total of 59.1% of those with ASD-RI (n = 890), 51.2% of those with ASD-RN (n = 453), and 42.8% of those with clinically diagnosed autism spectrum disorder (n = 187) had average or higher IQ. Within the ASD-RI and ASD-RN groups, boys were more likely than girls to have an average or higher IQ (62.0% vs 51.3% [P = .004] and 54.1% vs. 42.5% [P = .03], respectively). CONCLUSION Our data suggest that nearly half of individuals with ASD have average or higher IQ. Boys with ASD are more likely to have average or higher IQ than girls. Patients with ASD and higher IQ remain at risk for not being identified.

American Academy of Pediatrics (AAP) guidelines for children with Down syndrome (DS) include assessment for celiac disease (CD), although data to support this recommendation have been inconsistent. We determined the incidence of CD among children with DS in a population-based birth cohort of children born from 1976 to 2000 in Olmsted County, Minnesota. Individuals with karyotype-confirmed DS and CD (using diagnosis codes, positive serology, and duodenal biopsies) were identified. The incidence of CD in DS was compared with the published incidence of CD for Olmsted County residents (17.4 [95% confidence interval = 15.2-19.6] per 100 000 person-years). Among 45 individuals with DS from the birth cohort, 3 (6.7%) were identified with positive celiac serology and confirmatory biopsies at ages 9, 12, and 23 years, for an incidence of 325 per 100 000 person-years. Thus, individuals with DS have more than 18 times the incidence rate of CD compared with the general population, supporting the AAP guidelines.

AbstractImmune checkpoint inhibitor therapies targeting PD‐1/PD‐L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD‐L1 expression on immune cells occupying ≥1% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab‐paclitaxel. However, concerns regarding variability between immunohistochemical PD‐L1 assay performance and inter‐reader reproducibility have been raised. High tumor‐infiltrating lymphocytes (TILs) have also been associated with response to PD‐1/PD‐L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin–stained slides and have shown reliable inter‐reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD‐L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD‐L1 and TIL analyses as a more comprehensive immuno‐oncological biomarker for patient selection for PD‐1/PD‐L1 inhibition‐based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk‐management framework that may help mitigate the risks of suboptimal patient selection for immuno‐therapeutic approaches in clinical trials and daily practice based on combined TILs/PD‐L1 assessment in BC. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.