Sex-based differences in functional brain activity during working memory in survivors of pediatric acute lymphoblastic leukemia

BACKGROUND: Long-term survivors of pediatric acute lymphoblastic leukemia are at elevated risk for neurocognitive deficits and corresponding brain dysfunction. This study examined sex-based differences in functional neuroimaging outcomes in acute lymphoblastic leukemia survivors treated with chemotherapy alone. METHODS: Functional magnetic resonance imaging (fMRI) and neurocognitive testing were obtained in 123 survivors (46% male; median [min-max] age = 14.2 years [8.3-26.5 years]; time since diagnosis = 7.7 years [5.1-12.5 years]) treated on the St. Jude Total XV treatment protocol. Participants performed the n-back working memory task in a 3 T scanner. Functional neuroimaging data were processed (realigned, slice time corrected, normalized, smoothed) and analyzed using statistical parametric mapping with contrasts for 1-back and 2-back conditions, which reflect varying degrees of working memory and task load. Group-level fMRI contrasts were stratified by sex and adjusted for age and methotrexate exposure. Statistical tests were 2-sided (P \u3c .05 statistical significance threshold). RESULTS: Relative to males, female survivors exhibited less activation (ie, reduced blood oxygen dependent-level signals) in the right parietal operculum, supramarginal gyrus and inferior occipital gyrus, and bilateral superior frontal medial gyrus during increased working memory load (family-wise error-corrected P = .004 to .008, adjusting for age and methotrexate dose). Female survivors were slower to correctly respond to the 2-back condition than males (P \u3c .05), though there were no differences in overall accuracy. Performance accuracy was negatively correlated with fMRI activity in female survivors (Pearson\u27s r = -0.39 to -0.29, P = .001 to .02), but not in males. CONCLUSIONS: These results suggest the working memory network is more impaired in female survivors than male survivors, which may contribute to ongoing functional deficits

Investigating the Role of Hypothalamic Tumor Involvement in Sleep and Cognitive Outcomes Among Children Treated for Craniopharyngioma

Objective: Despite excellent survival prognosis, children treated for craniopharyngioma experience significant morbidity. We examined the role of hypothalamic involvement (HI) in excessive daytime sleepiness (EDS) and attention regulation in children enrolled on a Phase II trial of limited surgery and proton therapy. Methods: Participants completed a sleep evaluation (N = 62) and a continuous performance test (CPT) during functional magnetic resonance imaging (fMRI; n = 29) prior to proton therapy. Results: EDS was identified in 76% of the patients and was significantly related to increased HI extent (p = .04). There was no relationship between CPT performance during fMRI and HI or EDS. Visual examination of group composite fMRI images revealed greater spatial extent of activation in frontal cortical regions in patients with EDS, consistent with a compensatory activation hypothesis. Conclusion: Routine screening for sleep problems during therapy is indicated for children with craniopharyngioma, to optimize the timing of interventions and reduce long-term morbidity

Building the Future Therapies for Down Syndrome: The Third International Conference of the T21 Research Society

Research focused on Down syndrome has increased in the last several years to advance understanding of the consequences of trisomy 21 (T21) on molecular and cellular processes and, ultimately, on individuals with Down syndrome. The Trisomy 21 Research Society (T21RS) is the premier scientific organization for researchers and clinicians studying Down syndrome. The Third International Conference of T21RS, held June 6–9, 2019, in Barcelona, Spain, brought together 429 scientists, families, and industry representatives to share the latest discoveries on underlying cellular and molecular mechanisms of T21, define cognitive and behavioral challenges and better understand comorbidities associated with Down syndrome, including Alzheimer’s disease and leukemia. Presentation of cutting-edge results in neuroscience, neurology, model systems, psychology, cancer, biomarkers and molecular and phar­ma­cological therapeutic approaches demonstrate the compelling interest and continuing advancement in all aspects of understanding and ameliorating conditions associated with T21

Building the Future Therapies for Down Syndrome:The Third International Conference of the T21 Research Society

Research focused on Down syndrome has increased in the last several years to advance understanding of the consequences of trisomy 21 (T21) on molecular and cellular processes and, ultimately, on individuals with Down syndrome. The Trisomy 21 Research Society (T21RS) is the premier scientific organization for researchers and clinicians studying Down syndrome. The Third International Conference of T21RS, held June 6-9, 2019, in Barcelona, Spain, brought together 429 scientists, families, and industry representatives to share the latest discoveries on underlying cellular and molecular mechanisms of T21, define cognitive and behavioral challenges and better understand comorbidities associated with Down syndrome, including Alzheimer's disease and leukemia. Presentation of cutting-edge results in neuroscience, neurology, model systems, psychology, cancer, biomarkers and molecular and phar-ma-cological therapeutic approaches demonstrate the compelling interest and continuing advancement in all aspects of understanding and ameliorating conditions associated with T21

Opportunities, barriers, and recommendations in down syndrome research

Recent advances in medical care have increased life expectancy and improved the quality of life for people with Down syndrome (DS). These advances are the result of both pre-clinical and clinical research but much about DS is still poorly understood. In 2020, the NIH announced their plan to update their DS research plan and requested input from the scientific and advocacy community. The National Down Syndrome Society (NDSS) and the LuMind IDSC Foundation worked together with scientific and medical experts to develop recommendations for the NIH research plan. NDSS and LuMind IDSC assembled over 50 experts across multiple disciplines and organized them in eleven working groups focused on specific issues for people with DS. This review article summarizes the research gaps and recommendations that have the potential to improve the health and quality of life for people with DS within the next decade. This review highlights many of the scientific gaps that exist in DS research. Based on these gaps, a multidisciplinary group of DS experts has made recommendations to advance DS research. This paper may also aid policymakers and the DS community to build a comprehensive national DS research strategy

Early Imaging-Based Predictive Modeling of Cognitive Performance following Therapy for Childhood ALL

In the United States, Acute Lymphoblastic Leukemia (ALL), the most common child and adolescent malignancy, accounts for roughly 25% of childhood cancers diagnosed annually with a 5-year survival rate as high as 94%. This improved survival rate comes with an increased risk for delayed neurocognitive effects in attention, working memory, and processing speed. Predictive modeling and characterization of neurocognitive effects are critical to inform the family and also to identify patients for interventions targeting. Current state-of-the-art methods mainly use hypothesis-driven statistical testing methods to characterize and model such cognitive events. While these techniques have proven to be useful in understanding cognitive abilities, they are inadequate in explaining causal relationships, as well as individuality and variations. In this study, we developed multivariate data-driven models to measure the late neurocognitive effects of ALL patients using behavioral phenotypes, Diffusion Tensor Magnetic Resonance Imaging (DTI) based tractography data, morphometry statistics, tractography measures, behavioral, and demographic variables. Alongside conventional machine learning and graph mining, we adopted \u27Stability Selection\u27 to select the most relevant features and choose models that are consistent over a range of parameters. The proposed approach demonstrated substantially improved accuracy (13%-26%) over existing models and also yielded relevant features that were verified by domain experts