Structural brain measures among children with and without ADHD in the Adolescent Brain and Cognitive Development Study cohort: a cross-sectional US population-based study.

BACKGROUND: Structural neuroimaging research has identified a variety of abnormalities in cortical and subcortical structures in children with ADHD. However, studies to date have not employed large, non-referred samples, complete with data on potential confounding variables. Here, we tested for differences in structural MRI measures among children with and without ADHD using data from the Adolescent Brain and Cognitive Development (ABCD) Study, the largest paediatric brain imaging study in the USA. METHODS: In this cross-sectional study, we used baseline demographic, clinical, and neuroimaging data from the ABCD Study, which recruited children aged 9-10 years between Sept 1, 2016, and Aug 31, 2018, representative of the sociodemographic features of the US population. ADHD was diagnosed by parent report of symptoms. Neuroimaging data underwent centralised quality control and processing by the ABCD team. Linear mixed effects models were used to estimate Cohen's d values associated with ADHD for 79 brain measures of cortical thickness, cortical area, and subcortical volume. We used a novel simulation strategy to assess the ability to detect significant effects despite potential diagnostic misclassification. FINDINGS: Our sample included 10 736 participants (5592 boys, 5139 girls; 5692 White, 2165 Hispanic, 1543 Black, 221 Asian, and 1100 of other race or ethnicity), of whom, 949 met the criteria for ADHD and 9787 did not. In the full model, which included potential confounding variables selected a priori, we found only 11 significant differences across the 79 brain measures after false discovery rate correction, all indicating reductions in brain measures among participants with ADHD. Cohen's d values were small, ranging from -0·11 to -0·06, and were not meaningfully changed by using a more restrictive comparison group or alternative diagnostic methods. Simulations indicated adequate statistical power to detect differences even if there was substantial diagnostic misclassification. INTERPRETATION: In a sample representative of the general population, children aged 9-10 years with ADHD differed only modestly on structural brain measures from their unaffected peers. Future studies might need to incorporate other MRI modalities, novel statistical approaches, or alternative diagnostic classifications, particularly for research aimed at developing ADHD diagnostic biomarkers. FUNDING: Edwin S Webster Foundation and Duke University, NC, USA.

Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth.

Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or a single ML algorithm. Here, we use multimodal MRI with a stacked ensemble ML approach that iteratively applies several ML algorithms (AutoML). Eligible participants in the Healthy Brain Network (N = 489) were split into training and test sets. Morphometry estimates, white matter connectomes, or both were entered into AutoML to develop BrainPAD models. The best model was then applied to a held-out evaluation dataset, and associations with psychometrics were estimated. Models using morphometry and connectomes together had a mean absolute error of 1.18 years, outperforming models using a single MRI modality. Lower BrainPAD values were associated with more symptoms on the CBCL (pcorr  = .012) and lower functioning on the Children's Global Assessment Scale (pcorr  = .012). Higher BrainPAD values were associated with better performance on the Flanker task (pcorr  = .008). Brain age prediction was more accurate using ComBat-harmonized brain data (MAE = 0.26). Associations with psychometric measures remained consistent after ComBat harmonization, though only the association with CGAS reached statistical significance in the reduced sample. Our findings suggest that BrainPAD scores derived from unharmonized multimodal MRI data using an ensemble ML approach may offer a clinically relevant indicator of psychiatric and cognitive functioning in youth.

Reduced expression of FILIP1L, a novel WNT pathway inhibitor, is associated with poor survival, progression and chemoresistance in ovarian cancer.

Filamin A interacting protein 1-like (FILIP1L) is an inhibitor of the canonical WNT pathway. WNT/ß-catenin signaling and its downstream pathway, epithelial-to-mesenchymal transition (EMT), play a key role in ovarian cancer metastasis and chemoresistance. To study the clinical implications of FILIP1L in regulating the WNT/ß-catenin pathway, the expression of FILIP1L, ß-catenin, SNAIL and SLUG was analyzed by immunohistochemistry on tissue microarrays of 369 ovarian samples ranging from normal to metastatic. In addition, the results were validated in mouse model and in vitro cell culture. In the present study, we demonstrated that FILIP1L expression was inversely correlated with poor prognosis, stage and chemoresistance in ovarian cancer. Notably, low FILIP1L expression was independent negative prognostic factor with respect to overall and disease-free survival. FILIP1L inhibited peritoneal metastases in orthotopic mouse model. FILIP1L knockdown induced chemoresistance in ovarian cancer cells and this phenotype was rescued by simultaneous knockdown of FILIP1L and SLUG, an EMT activator. We also demonstrated that FILIP1L regulates ß-catenin degradation. FILIP1L co-localizes with phospho-ß-catenin and increases phospho-ß-catenin at the centrosomes, destined for proteosomal degradation. Finally, we showed that FILIP1L regulates EMT. Overall, these findings suggest that FILIP1L promotes ß-catenin degradation and suppresses EMT, thereby inhibiting metastases and chemoresistance. Our study provides the first clinical relevance of FILIP1L in human cancer, and suggests that FILIP1L may be a novel prognostic marker for chemotherapy in ovarian cancer patients. Further, the modulation of FILIP1L expression may have the potential to be a target for cancer therapy.

Filamin A interacting protein 1-like inhibits WNT signaling and MMP expression to suppress cancer cell invasion and metastasis.

Identifying key mediators of cancer invasion and metastasis is crucial to the development of new and more effective therapies. We previously identified FILamin A Interacting Protein 1-Like (FILIP1L) as an important inhibitor of cell migration and invasion. FILIP1L expression was inversely correlated with the invasive potential of ovarian tumors. In our study, we established an orthotopic ovarian cancer model, wherein FILIP1L expression can be regulated in vivo. Using this model, we observed that expression of FILIP1L in ovarian cancer cells inhibited spontaneous lung metastasis. Experimental lung metastases (established via tail vein injection of cancer cells) as well as the extravasation step of metastasis were not inhibited by FILIP1L, suggesting that FILIP1L inhibits the earlier steps of metastasis such as invasion and intravasation. FILIP1L inhibited matrix metalloproteinase (MMP)-dependent invasion in vivo. MMP3, -7 and -9 were transcriptionally downregulated, and MMP9 protein expression and activity were inhibited in FILIP1L-expressing tumors. Importantly, overexpression of MMP9 compensated for the anti-invasive activity of FILIP1L. Furthermore, our studies suggest that FILIP1L regulates invasion and metastasis by inhibiting components of the WNT signaling pathway. FILIP1L expression reduced the induction of WNT target genes such as MMP3, -7 and -9, and ß-catenin-directed transcriptional activity, suggesting inhibition of the canonical WNT pathway. Nuclear ß-catenin, an indicator of an active canonical WNT pathway, was reduced in FILIP1L-expressing tumors. Overall, these findings suggest that FILIP1L reduces ß-catenin levels, which may lead to the transcriptional downregulation of WNT target genes such as MMPs, resulting in inhibition of metastasis. Modulation of FILIP1L expression has the potential to be a target for cancer therapy.

Adenosine A(2A) receptors promote collagen production by a Fli1- and CTGF-mediated mechanism.

INTRODUCTION: Adenosine, acting through the A(2A) receptor, promotes tissue matrix production in the skin and the liver and induces the development of dermal fibrosis and cirrhosis in murine models. Since expression of A(2A) receptors is increased in scleroderma fibroblasts, we examined the mechanisms by which the A(2A) receptor produces its fibrogenic effects. METHODS: The effects of A(2A) receptor ligation on the expression of the transcription factor, Fli1, a constitutive repressor for the synthesis of matrix proteins, such as collagen, is studied in dermal fibroblasts. Fli1 is also known to repress the transcription of CTGF/CCN2, and the effects of A(2A) receptor stimulation on CTGF and TGF-ß1 expression are also examined. RESULTS: A(2A) receptor occupancy suppresses the expression of Fli1 by dermal fibroblasts. A(2A) receptor activation induces the secretion of CTGF by dermal fibroblasts, and neutralization of CTGF abrogates the A(2A) receptor-mediated enhancement of collagen type I production. A(2A)R activation, however, resulted in a decrease in TGF-ß1 protein release. CONCLUSIONS: Our results suggest that Fli1 and CTGF are important mediators of the fibrogenic actions of adenosine and the use of small molecules such as adenosine A(2A) receptor antagonists may be useful in the therapy of dermal fibrosis in diseases such as scleroderma.