Pubmed du 18/04/22
1. Choi H, Byeon K, Park BY, Lee JE, Valk SL, Bernhardt B, Martino AD, Milham M, Hong SJ, Park H. Diagnosis-informed connectivity subtyping discovers subgroups of autism with reproducible symptom profiles. NeuroImage. 2022; 256: 119212.
Clinical heterogeneity has been one of the main barriers to develop effective biomarkers and therapeutic strategies in autism spectrum disorder (ASD). Recognizing this challenge, much effort has been made in recent neuroimaging studies to find biologically more homogeneous subgroups (called ‘neurosubtypes’) in autism. However, most approaches have rarely evaluated how much the employed features in subtyping represent the core anomalies of ASD, obscuring its utility in actual clinical diagnosis. To address this, we combined two data-driven methods, ‘connectome-based gradient’ and ‘functional random forest’, collectively allowing to discover reproducible neurosubtypes based on resting-state functional connectivity profiles that are specific to ASD. Indeed, the former technique provides the features (as input for subtyping) that effectively summarize whole-brain connectome variations in both normal and ASD conditions, while the latter leverages a supervised random forest algorithm to inform diagnostic labels to clustering, which makes neurosubtyping driven by the features of ASD core anomalies. Applying this framework to the open-sharing Autism Brain Imaging Data Exchange repository data (discovery, n = 103/108 for ASD/typically developing [TD]; replication, n = 44/42 for ASD/TD), we found three dominant subtypes of functional gradients in ASD and three subtypes in TD. The subtypes in ASD revealed distinct connectome profiles in multiple brain areas, which are associated with different Neurosynth-derived cognitive functions previously implicated in autism studies. Moreover, these subtypes showed different symptom severity, which degree co-varies with the extent of functional gradient changes observed across the groups. The subtypes in the discovery and replication datasets showed similar symptom profiles in social interaction and communication domains, confirming a largely reproducible brain-behavior relationship. Finally, the connectome gradients in ASD subtypes present both common and distinct patterns compared to those in TD, reflecting their potential overlap and divergence in terms of developmental mechanisms involved in the manifestation of large-scale functional networks. Our study demonstrated a potential of the diagnosis-informed subtyping approach in developing a clinically useful brain-based classification system for future ASD research.
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2. Liu Q, Yin W, Meijsen JJ, Reichenberg A, Gådin JR, Schork AJ, Adami HO, Kolevzon A, Sandin S, Fang F. Cancer risk in individuals with autism spectrum disorder. Annals of oncology : official journal of the European Society for Medical Oncology. 2022.
BACKGROUND: Whether individuals with autism spectrum disorders (ASDs) have a higher-than-expected risk of cancer remains unknown. PATIENTS AND METHODS: We carried out a population-based cohort study including 2.3 million individuals live-born to mothers from Nordic countries during 1987-2013 in Sweden with follow-up through 2016 (up to age 30 years). Individuals with ASD were ascertained through the Swedish National Patient Register. We estimated the relative risk of cancer in relation to ASD by odds ratios (ORs) and associated 95% confidence intervals (CIs) derived from logistic regression, after detailed adjustment for potential confounders. We also carried out a sibling comparison to address familial confounding and a genetic correlation analysis using the genome-wide association study summary statistics to address confounding due to potential polygenetic pleiotropy between ASD and cancer. RESULTS: We observed an overall increased risk of any cancer among individuals with ASD (OR 1.3, 95% CI 1.2-1.5), compared with individuals without ASD. The association for any cancer was primarily noted for narrowly defined autistic disorder (OR 1.7, 95% CI 1.3-2.1) and ASD with comorbid birth defects (OR 2.1, 95% CI 1.5-2.9) or both birth defects and intellectual disability (ID; OR 4.8, 95% CI 3.4-6.6). An association was also suggested for ASD with comorbid ID (OR 1.4; 95% CI 0.9-2.1), but was not statistically significant. ASD alone (i.e. without comorbid ID or birth defects) was not associated with an increased risk of any cancer (OR 1.0, 95% CI 0.8-1.2). Sibling comparison and genetic correlation analysis showed little evidence for familial confounding or confounding due to polygenetic pleiotropy between ASD and cancer. CONCLUSIONS: ASD per se is not associated with an increased risk for cancer in early life. The increased cancer risk among individuals with ASD is likely mainly attributable to co-occurring ID and/or birth defects in ASD.
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3. Rubenstein E, Ehrenthal DB, Nobles J, Mallinson DC, Bishop L, Jenkins MC, Kuo HH, Durkin MS. Brief report: Fertility rates in women with intellectual and developmental disabilities in Wisconsin Medicaid. Disability and health journal. 2022: 101321.
BACKGROUND: Women with intellectual and developmental disabilities (IDD) face stigma and inequity surrounding opportunity and care during pregnancy. Little work has quantified fertility rates among women with IDD which prevents proper allocation of care. OBJECTIVE: Our objective was to cross-sectionally describe fertility patterns among women with and without intellectual and developmental disabilities (IDD) in 10-years of Medicaid-linked birth records. STUDY DESIGN: Our sample was Medicaid-enrolled women with live births in Wisconsin from 2007 to 2016. We identified IDD through prepregnancy Medicaid claims. We calculated general fertility-, age-specific-, and the total fertility-rates and 95% confidence intervals (95% CI) for women with and without IDD and generated estimates by year and IDD-type. RESULTS: General fertility rate in women with IDD was 62.1 births per 1000 women with IDD (95% CI 59.2, 64.9 per 1000 women) and 77.1 per 1000 for women without IDD (95% CI: 76.8, 77.4 per 1000 women). General fertility rate ratio was 0.81 (95% CI: 0.7, 0.9). Total fertility was 1.80 births per woman with IDD and 2.05 births per woman without IDD (rate ratio: 0.89 95% CI: 0.5, 1.5). Peak fertility occurred later for autistic women (30-34 years), compared with women with other IDD (20-24 years). CONCLUSION: In Wisconsin Medicaid, general fertility rate of women with IDD was lower than women without IDD: the difference was attenuated when accounting for differing age distributions. Results highlight the disparities women with IDD face and the importance of allocating pregnancy care within Medicaid.
