Triple Interactions Between the Environment, Brain, and Behavior in Children: An ABCD Study

BACKGROUND

Environmental exposures play a crucial role in shaping children's behavioral development. However, the mechanisms by which these exposures interact with brain functional connectivity and influence behavior remain unexplored.

METHODS

We investigated the comprehensive environment-brain-behavior triple interactions through rigorous association, prediction, and mediation analyses, while adjusting for multiple confounders. Particularly, we examined the predictive power of brain functional network connectivity (FNC) and 41 environmental exposures for 23 behaviors related to cognitive ability and mental health in 7655 children selected from the Adolescent Brain Cognitive Development (ABCD) Study at both baseline and follow-up.

RESULTS

FNC demonstrated more predictability for cognitive abilities than for mental health, with cross-validation from the UK Biobank study (N = 20,852), highlighting the importance of thalamus and hippocampus in longitudinal prediction, while FNC+environment demonstrated more predictive power than FNC in both cross-sectional and longitudinal prediction of all behaviors, especially for mental health (r = 0.32-0.63). We found that family and neighborhood exposures were common critical environmental influencers on cognitive ability and mental health, which can be mediated by FNC significantly. Healthy perinatal development was a unique protective factor for higher cognitive ability, whereas sleep problems, family conflicts, and adverse school environments specifically increased risk of poor mental health.

CONCLUSIONS

This work revealed comprehensive environment-brain-behavior triple interactions based on the ABCD Study, identified cognitive control and default mode networks as the most predictive functional networks for a wide repertoire of behaviors, and underscored the long-lasting impact of critical environmental exposures on childhood development, in which sleep problems were the most prominent factors affecting mental health.

Automated individual cortical parcellation via consensus graph representation learning

Cortical parcellation plays a pivotal role in elucidating the brain organization. Despite the growing efforts to develop parcellation algorithms using functional magnetic resonance imaging, achieving a balance between intra-individual specificity and inter-individual consistency proves challenging, making the generation of high-quality, subject-consistent cortical parcellations particularly elusive. To solve this problem, our paper proposes a fully automated individual cortical parcellation method based on consensus graph representation learning. The method integrates spectral embedding with low-rank tensor learning into a unified optimization model, which uses group-common connectivity patterns captured by low-rank tensor learning to optimize subjects' functional networks. This not only ensures consistency in brain representations across different subjects but also enhances the quality of each subject's representation matrix by eliminating spurious connections. More importantly, it achieves an adaptive balance between intra-individual specificity and inter-individual consistency during this process. Experiments conducted on a test-retest dataset from the Human Connectome Project (HCP) demonstrate that our method outperforms existing methods in terms of reproducibility, functional homogeneity, and alignment with task activation. Extensive network-based comparisons on the HCP S900 dataset reveal that the functional network derived from our cortical parcellation method exhibits greater capabilities in gender identification and behavior prediction than other approaches.

Requisite role of dorsal raphé in contextual cocaine-memory reconsolidation

Memory reconsolidation is a process by which labile drug memories are restabilized in long-term memory stores, permitting their enduring control over drug-seeking behaviors. In the present study, we investigated the involvement of the dorsal raphé nuclei (DRN) in cocaine-memory reconsolidation. Sprague-Dawley rats (male, female) were trained to self-administer cocaine in a distinct environmental context to establish contextual drug memories. They then received extinction training in a different context. Next, the rats were re-exposed to the cocaine-predictive context for 15 min to reactivate their cocaine memories or remained in their home cages (no-reactivation control). Memory reactivation was sufficient to increase c-Fos expression, an index of neuronal activation, in the DRN, but not in the median raphé nuclei, during reconsolidation, compared to no reactivation. To determine whether DRN neuronal activity was necessary for cocaine-memory reconsolidation, rats received intra-DRN baclofen plus muscimol (BM; GABAB/A agonists) or vehicle microinfusions immediately after or 6 h after a memory reactivation session conducted with or without lever access. The effects of DRN functional inactivation on long-term memory strength, as indicated by the magnitude of context-induced cocaine seeking, were assessed 72 h later. Intra-DRN BM treatment immediately after memory reactivation with or without lever access attenuated subsequent context-induced cocaine-seeking behavior, independent of sex. Conversely, BM treatment in the adjacent periaqueductal gray (PAG) immediately after memory reactivation, or BM treatment in the DRN 6 h after memory reactivation, did not alter responding. Together, these findings indicate that the DRN plays a requisite role in maintaining cocaine-memory strength during reconsolidation.

Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering

BACKGROUND

Similarities among schizophrenia (SZ), schizoaffective disorder (SAD) and bipolar disorder (BP) including clinical phenotypes, brain alterations and risk genes, make it challenging to perform reliable separation among them. However, previous subtype identification that transcend traditional diagnostic boundaries were based on group-level neuroimaging features, ignoring individual-level inferences.

METHODS

455 psychoses (178 SZs, 134 SADs and 143 BPs), their first-degree relatives (N = 453) and healthy controls (HCs, N = 220) were collected from Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP I) consortium. Individualized covariance structural differential networks (ICSDNs) were constructed for each patient and multi-site clustering was used to identify psychosis subtypes. Group differences between subtypes in clinical phenotypes and voxel-wise fractional amplitude of low frequency fluctuation (fALFF) were calculated, as well as between the corresponding relatives.

RESULTS

Two psychosis subtypes were identified with increased whole brain structural covariance, with decreased connectivity between amygdala-hippocampus and temporal-occipital cortex in subtype I (S-I) compared to subtype II (S-II), which was replicated under different clustering methods, number of edges and across datasets (B-SNIP II) and different brain atlases. S-I had higher emotional-related symptoms than S-II and showed significant fALFF decrease in temporal and occipital cortex, while S-II was more similar to HC. This pattern was consistently validated on relatives of S-I and S-II in both fALFF and clinical symptoms.

CONCLUSIONS

These findings reconcile categorical and dimensional perspectives of psychosis neurobiological heterogeneity, indicating that relatives of S-I might have greater predisposition in developing psychosis, while relatives of S-II are more likely to be healthy. This study contributes to the development of neuroimaging informed diagnostic classifications within psychosis spectrum.

[Efficacy and safety of endovascular therapy after 24 h from ischemic stroke onset in patients with acute anterior circulation ischemic stroke]

Objective: To explore the effectiveness and safety of endovascular treatment (EVT) for patients with acute anterior circulation ischemic stroke with symptom onset exceeding 24 h. Methods: In this retrospective cohort study, data were extracted from patients who underwent endovascular treatment for acute anterior circulation ischemic stroke at the First Hospital of Jilin University from February 2019 to April 2022. A total of 569 patients were included, with a mean age of 63 (54-70) years. Among them, 398 (69.9%) were male. The patients were divided into two groups based on symptom onset time:>24 h group and≤24 h group. Propensity score matching (PSM) was used to match the patients in a 1︰1 ratio between the>24 h group and the≤24 h group. Logistic regression was used to evaluate the impact of symptom onset time on outcome events. Results: Before PSM, compared with≤24 h group, the>24 h group had a younger age [56 (48, 64) vs. 64 (55, 70), Z=-3. 60, P<0.001]; lower proportion of prior atrial fibrillation [1.8% (1/57) vs. 21.1% (108/512), χ2=12.39, P<0.001]; lower proportion of wake-up stroke [7.0% (4/57) vs. 27.7% (142/512), χ2=11.54, P<0.001]; lower baseline NIHSS score [11.0 (7.5, 14.0) vs. 13.0 (10.0, 16.0), Z=-3.22, P<0.001]; and a higher American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology(ASITN/SIR) grading (P<0.001). After PSM, there were no significant differences in baseline characteristics between the two groups. There was no significant difference in the proportion of patients with a modified Rankin Scale (mRS) score≤2 at 90 days after surgery between the two groups (before matching: 42.0% vs. 40.4%, OR=0.745, 95%CI 0.407-1.362, P=0.339; after matching: 51.8% vs. 39.3%, OR=0.511, 95%CI 0.212-1.236, P=0.136). No significant differences were observed in the incidence of any safety outcomes between the>24 h group and the≤24 h group. Conclusion: For patients with acute anterior circulation ischemic stroke with symptom onset exceeding 24 h, EVT is feasible after strict radiological screening and has similar safety and effectiveness as for patients with symptom onset under 24 h.

Development and Validation of Clinical-Metabolic-Radiomics Model Based on Nomogram-Revised Risk Index for Prognosis Prediction in Patients with Extranodal Natural Kill/T Cell Lymphoma

PURPOSE/OBJECTIVE(S)

To identify clinical-metabolic-radiomics model using clinical data and 18F-FDG PET/CT image for predicting progression-free survival (PFS) of nasal-type extranodal natural killer/T cell lymphoma (ENKTCL) on the basis of the nomogram-revised risk index (NRI) model previously established and validated by our research group.

MATERIALS/METHODS

A total of 133 ENKTCL patients were prospectively included and randomly divided into a training cohort (n = 73) and a validation cohort (n = 50). 107 features and 7 commonly used metabolic parameters (SUVmax, MTV, TLG, SD, TLR, TAR and TBR) were extracted from baseline PET images of the patients. Least absolute shrinkage and selection operator (LASSO) following Cox regression were used to select optimal features and parameters. NRI-metabolic-radiomics model was developed and validated in the two cohorts and compared with NRI model and NRI-metabolic model.

RESULTS

TLG and 5 radiomics features were selected after LASSO and Cox regression. NRI-metabolic (NRI-TLG) model and NRI-metabolic-radiomics (NRI-TLG-RAD) model was developed based on NRI, TLG and selected 5 radiomics features. For PFS, NRI-TLG-RAD showed better PFS discrimination than NRI-TLG model and NRI model in both training cohort (C-index = 0.791, 0.743 and 0.690, respectively) and validation cohort (C-index = 0.785, 0.707, and 0.610 respectively). Moreover, NRI-TLG-RAD model and NRI-TLG model divided more patients into low-risk group (No. of patients: 66, 42 vs. 20) and very high-risk group (No. of patients: 25, 25 vs. 9), compared to preexisting NRI model.

CONCLUSION

The addition of metabolic and radiomics information improved the prognostic performance of preexisting NRI model greatly. Better prognostic discrimination and more reasonable patient division of the new NRI-TLG and NRI-TLG-RAD model may provide the basis for more precise treatment modality in the future.

Optimizing the Combination of Cytotoxic Drugs Along with Radiotherapy as Effective Treatment for Extranodal NK/T-Cell Lymphoma

PURPOSE/OBJECTIVE(S)

The optimal combination of cytotoxic drugs along with radiotherapy (RT) is unknown. We undertook multidrug screening process to identify the most efficacious cytotoxic drugs, and appraise the efficacy of various drug combinations.

MATERIALS/METHODS

We reviewed 3105 patients who received 40 chemotherapy regimens with different combinations of nine drug classes and/or RT. Least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses were used to screen efficacious single drugs and identify optimal combinations for overall survival (OS). Inverse probability of treatment weighting (IPTW) and multivariable analyses were used to compare survival between treatment regimens.

RESULTS

Screening and validation revealed RT, asparaginase (ASP), and gemcitabine (GEM) to be the most efficacious single modality/drugs. RT remained an important component of first-line treatment, whereas ASP was a fundamental drug of non-anthracycline (ANT)-based regimens. Addition of RT to non-ANT-based or ASP/GEM-based regimens, or addition of an ASP-drug into ANT-based or GEM/PLA-based regimens, improved 5-year OS significantly. Use of ASP/GEM-based regimens led to significantly higher 5-year OS (79.9%) compared with ASP/ANT-based (69.2%, P = 0.001), ASP/MTX-based (63.5%, P = 0.011), or ASP/NOS-based (63.2%, P<0.001) regimens. The survival benefit of ASP/GEM-based regimens over other ASP-based regimens was substantial across risk-stratified and advanced-stage subgroups. The survival benefits of a combination of RT, ASP, and GEM were consistent after adjustment for confounding factors by IPTW.

CONCLUSION

These results suggest that combining ASP/GEM with RT for ENKTCL is an efficacious and feasible therapeutic option, and provides a rationale and strategy for developing combination therapies.

Early Cardiotoxicity in Patients Receiving Hypofractionated Radiotherapy after Breast Conserving Surgery: Analysis of a Prospective Study

PURPOSE/OBJECTIVE(S)

To evaluate the early cardiotoxicity of hypofractionated radiotherapy (HFRT) in patients with left-sided breast cancer after breast-conserving surgery, and to investigate the correlation between cardiotoxicity and cardiac dose.

MATERIALS/METHODS

A total of 103 women from 2017 to 2018 who received left-sided whole-breast with or without regional nodal irradiation either using deep inspiration breath-hold (DIBH) or free-breathing (FB) technique were prospectively enrolled. N-terminal pro-B-type natriuretic peptide (NT-proBNP), electrocardiogram, and radionuclide myocardial perfusion imaging were conducted before and after HFRT. Logistic regression analyses were performed to determine the association of cancer treatment, cardiac dose, and cardiovascular risk factors with cardiotoxic effects.

RESULTS

The mean dose (Dmean) of the heart, left anterior descending coronary artery (LAD), left ventricular (LV), and right ventricular (RV) in all patients was 403 cGy, 1685 cGy, 627 cGy, and 444 cGy, respectively. In comparison to FB, DIBH significantly reduced cardiac dose (heart Dmean 250 cGy vs. 570 cGy, LAD Dmean 1250 cGy vs. 2170 cGy, LV Dmean 420 cGy vs. 850 cGy, RV Dmean 260 cGy vs. 650 cGy; all p<0.001). With a median follow-up of 49 months (range, 2-65 months), no patients had clinical cardiac abnormalities or cardiac-related symptoms, but 42 (41%) patients had subclinical cardiac events. Among them, 41 were electrocardiogram changes, and one had LV ejection fraction decreased by 10% compared with the baseline level. Twenty-five (60%) recovered during follow-up, of which 17 (40%) experienced subclinical changes only once. The mean value of NT-proBNP did not change significantly before and after HFRT. In univariate analyses, DIBH technique significantly decreased the risk of subclinical cardiac events compared with FB (OR 0.31, 95% CI 0.14-0.71; p = 0.006); however, higher mean doses of heart and LV, anthracycline-based chemotherapy, obesity, and hypertension were associated with increased risk of subclinical cardiac events (all p<0.05).

CONCLUSION

Early subclinical cardiac damage after HFRT in left-sided breast cancer is dose-related, and mostly manageable and reversible without medical intervention.

Adaptive Ultra-Hypofractionated Whole-Pelvic Radiotherapy in High-Risk and Very High-Risk Prostate Cancer on 1.5-1.5 MR Linac: The Estimated Delivered Dose and Early Toxicity Results

PURPOSE/OBJECTIVE(S)

To study the feasibility and safety for patients with high-risk (HR) and very high-risk (VHR) prostate cancer treated with adaptive ultra-hypofractionated whole-pelvic radiotherapy (UHF-WPRT) on 1.5 magnetic resonance (MR)-Linac.

MATERIALS/METHODS

Sevenpatients with clinical stage T3a-4N0-1M0-1c consecutively treated with UHF-WPRT on a 1.5-T MR-Linac were recruited prospectively in a phase II trial (NCT05183074, ChiCTR2000033382). A 36.25 Gy dose in five fractions was delivered every other day with a boost of 40 Gy to the whole prostate, as well as 25 Gy to whole pelvic nodal area with a concomitant boost of 35 Gy to metastatic regional nodes. To estimate the delivered dose, we collected data by 3D-MR for the following stages: pre-MR, position verification-MR (PV-MR) in the Adapt-To-Shape (ATS) workflow, and 3D-MR during the beam-on phase (Bn-MR) and at the end of RT (post-MR). The target and organ-at-risk contours in the PV-MR, Bn-MR, and post-MR stages were projected from the pre-MR data by deformable image registration and manually adapted by the physician, followed by dose recalculation for the ATS plan. The cumulative acute genitourinary (GU) and gastrointestinal (GI) toxicities were evaluated as per NCI-CTCAE 5.0 criteria. The primary endpoints were acute ≥grade 3 genitourinary (GU) and gastrointestinal (GI) toxicities during the first 3 months.

RESULTS

Overall, 133 MR scans were collected (35 pre-MR, 35 PV-MR, 31 Bn-MR and 32 post-MR scans). With a median on-couch time of 61 minutes, the mean prostate and pelvic planning target volume (PTV)-V95% of all scans was 96.98 ± 3.06% and 96.44 ± 2.85%, respectively. The corresponding mean prostate clinical target volume (CTV)-V100% was 99.89 ± 0.32%, 98.71 ± 1.90%, 97.77 ± 2.89%, and 98.56 ± 1.72%, and the mean pelvic CTV-V100% was 97.57% ± 3.70%, 96.54 ± 3.80%, 95.43 ± 4.31%, and 94.39 ± 4.47% on pre-MR, PV-MR, Bn-MR and post-MR scans, respectively. For the 4 patients with positive nodes, the mean V100% of metastatic regional nodes was 99.89 ± 0.81%. The median V29 Gy change in the rectal wall was -1% (-18%-20%). The V29 Gy of the rectal wall increased by >15% was observed in one scan. A slight increase in the high dose of bladder wall was noted due to gradual bladder growth during the workflow. With median follow-up time of 7.3 (4.6-12.2) months, all patients were followed-up for more than 3 months. No patient was observed with acute CTCAE grade 2 or more severe GU or GI toxicities (0%).

CONCLUSION

UHF-RT to prostate and pelvic with ATS workflow is well tolerated by patients with HR and VHR prostate cancer, with only mild GU and GI toxicities. The 3D-MR-based dosimetry analysis demonstrated clinically acceptable estimated dose coverage of target volumes during the beam-on period.

Engaging Ambulatory Cancer Patients to Develop and Validate a Comprehensive New Patient-Reported Outcomes Measure

PURPOSE/OBJECTIVE(S)

The ambulatory cancer program in Alberta, Canada routinely collects Patient-Reported Outcomes (PROs) using a common symptom rating measure, the Edmonton Symptom Assessment System-Revised (ESAS-r). The purpose of this study was to redesign, test, and validate a modified ESAS-r (the ESAS-r Cancer) for use in the province's new clinical information system and online patient portal.

MATERIALS/METHODS

Patient advisors participated in regular meetings to redesign the measure, creating expanded definitions for the original symptoms and new symptoms, added based on trends identified in our historical PRO data. To test the modified measure, patient advisors first completed the measure online to test the feasibility of remote electronic completion. Next, the advisors participated in cognitive interviews to discuss and finalize the wording of each symptom definition for clarity. To test the validity and reliability of the finalized measure, 1600 randomly sampled patients were mailed paper copies of the ESAS-r Cancer, ESAS-r, and a validated PRO measure called the Memorial System Assessment Scale-Short Form (MSAS-SF), which is often used with cancer patients. Canonical Correlation Analysis and exploratory factor analyses were performed to assess concurrent and construct validity of the ESAS-r Cancer against ESAS-r, using MSAS-SF as the gold standard. Cronbach's α was calculated to assess reliability.

RESULTS

The nine original ESAS-r symptoms were retained and six new symptoms were added to create the ESAS-r Cancer. All but one of the 26 patient advisors (96.2%) who completed the online measure did so without assistance. After two rounds of cognitive interviews all symptom definitions were finalized and deemed clear by almost all advisors. 461 patients (29% response rate) completed all three questionnaires. Using MSAS-SF as the gold standard, ESAS-r Cancer showed stronger canonical correlation than ESAS-r, indicating higher concurrent validity and fitting degree. ESAS-r Cancer also accounted for more information included on MSAS-SF than did ESAS-r, explaining more variance (75.2% vs. 73.5%). As revealed by factor analysis, the three-dimensional factor structure of ESAS-r Cancer outperformed the two-dimensional factor structure of ESAS-r, by allowing for new constructs within measurement. The reliability of ESAS-r Cancer was verified (Cronbach's α = .903, > threshold of 0.8) and slightly higher than ESAS-r (Cronbach's α = .884).

CONCLUSION

ESAS-r Cancer is now in use with patients throughout Alberta's cancer program. The redesign, testing, and validation process involved patient engagement throughout. Patient testing and perspectives were critical as ESAS-r Cancer is intended for use with ambulatory cancer patients. ESAS-r Cancer can help ensure patients are included in care decisions and that their perspectives are involved in guiding care.

Association of Overall Survival Benefit Profile of Radiotherapy with Progression-Free Survival after Chemotherapy for Diffuse Large B-Cell Lymphoma

PURPOSE/OBJECTIVE(S)

Benefit of radiotherapy (RT) after chemotherapy (CT) of diffuse large B-cell lymphoma (DLBCL) remains controversial. It is unknown whether improved progression-free survival (PFS) by RT translate into an overall survival (OS) benefit. To address this question, our research comprehensively evaluated the risk-benefit assessment of RT in DLBCL through an in-depth examination of previously reported data from randomized controlled trials (RCTs) and retrospective comparative studies.

MATERIALS/METHODS

After screening and quality control, this study included 7 randomized controlled trials and 52 retrospective studies of combined-modality therapy (CMT) versus CT alone. The correlation between PFS and OS was evaluated using the Pearson linear correlation coefficient at trial- and study arm-level. A risk-benefit assessment to describe the OS benefit of RT was performed in meta-analyses of pooled HROS with PFS patterns.

RESULTS

In RCTs, strong correlations were found between HRPFS and HROS at trial-level (r = 0.876), and PFS and OS at treatment arm-level, regardless of treatments (r = 0.945-0.964 for all, CMT or CT). In retrospective studies, similar correlations between HRPFS and HROS (r = 0.639-0.650), and PFS and OS rates (r = 0.882-0.910) were observed, independent of treatments or rituximab. Adding RT into rituximab-based CT increased the average PFS rate from 63.6 ± 18.9% to 81.5 ± 10.6% (P<0.001), with differential OS benefits of RT between studies. Patients can be stratified into four PFS patterns (>80%, >60-80%, >40-60%, and ≤40%); absolute gain in OS from RT ranged from ≤5% at PFS >80% to ∼21% at PFS ≤40%, with pooled-HROS from 0.70 (95% CI, 0.51-0.97) to 0.48 (95% CI, 0.36-0.63) after rituximab-based CT. Linear analysis revealed an OS advantage of CMT over CT alone in a PFS-dependent manner.

CONCLUSION

We demonstrate a varied OS benefit profile of RT upon different PFS patterns, and provide valuable evidence for making treatment decisions and designing clinical trials. Future strategies to select the use of RT will need careful tailoring in clinical practice or within RCT to optimize outcome.

Lymphocyte Count Kinetics and the Effect of Different Radiotherapy Techniques on Radiation-Induced Lymphopenia in Patients with Breast Cancer Receiving Hypofractionated Postmastectomy Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiation-induced lymphopenia (RIL) is associated with poor prognosis in solid tumors. This study aimed to describe the lymphocyte kinetics in patients with breast cancer receiving hypofractionated postmastectomy radiotherapy (RT) and to investigate the association of different RT techniques with RIL.

MATERIALS/METHODS

We assessed 607 patients who received hypofractionated postmastectomy RT for breast cancer in our prospective clinical database from 8 hospitals. All patients received irradiation to the chest wall and supraclavicular fossa. RT techniques included integrated RT with the photon-based intensity modulated techniques to irradiate all target volumes (integrated RT) and a hybrid approach combining photon irradiation to supraclavicular nodes and electron irradiation to the chest wall (hybrid RT). Peripheral lymphocyte counts (PLC) were tested prior to RT (baseline), weekly during RT, at 1, 2 weeks, 3, 6 months after RT, and then every 6 months. Grade 3+ RIL was defined as PLC nadir during RT of <0.5 ×103/ml. Mean PLC was compared by the t test. Univariate, multivariate, and propensity score matching (PSM) analyses were used to evaluate the effect of different RT techniques on grade 3+ RIL.

RESULTS

During RT, 121 (19.9%) of patients had grade 3+ RIL. The PLC started to recover at 1 week and reached baseline levels 1 year after RT. A greater proportion of the patients treated with the integrated RT (90/269, 33.5%) developed grade 3+ PLC compared with those receiving hybrid RT (31/338, 9.2%, P < 0.001). After conducting PSM, multivariate analyses showed lower baseline PLC (HR = 0.15, P<0.001) and RT technique (the integrated RT vs. hybrid RT, HR = 4.76, P<0.001) were independent risk factors for grade 3+ RIL. The PLC in patients receiving the integrated RT after RT were higher than that in those receiving hybrid RT (p<0.05).

CONCLUSION

RT technique affect the risk of and recovery from RIL, which may impact survival. Choosing appropriate RT technique to minimize RIL might be considered to benefit their outcomes.

Association of Treatment Disparities and Primary Sites with the Survival of Non-Gastric Early-Stage MALT Lymphoma

PURPOSE/OBJECTIVE(S)

To investigate the association between utilization of radiotherapy and differences in survival among patients with non-gastric early-stage mucosa-associated lymphoid tissue (MALT) lymphoma at different primary sites.

MATERIALS/METHODS

A total of 5,995 patients with non-gastric early-stage MALT lymphoma in the Surveillance, Epidemiology, and End Results (SEER) database treated between 2000-2015 were extracted and analyzed. Mediation analyses were conducted to quantitatively determine the proportion of the relationship between OS and primary sites mediated by radiotherapy. Inverse probability of treatment weighting (IPTW) was conducted to control confounding factors affecting treatment choice.

RESULTS

After controlling for confounding factors, pulmonary MALT lymphoma was found to have the highest rate of omitted radiotherapy compared to other primary sites, including ocular adnexa, salivary gland, skin and other sites. Multivariate Cox analyses showed that lung MALT lymphoma patients had the lowest 10-year OS rate of 58.3%, while skin MALT lymphoma patients had the highest 10-year OS rate of 81.6%. After balancing confounding factors that potentially affected the choice of radiotherapy using IPTW, differences in utilization of radiotherapy explained a significant portion of the poor prognosis of lung MALT lymphoma (35.6%, P = 0.002) and the favorable prognosis of skin MALT lymphoma (6.1%, P <0.001).

CONCLUSION

Differences in survival among patients with non-gastric early-stage MALT lymphoma at different primary sites are associated with disparities in the utilization of radiotherapy.

Radiotherapy Effect on Long-Term Net Survival Benefit for Early-Stage Diffuse Large B-Cell Lymphoma in the Rituximab Era

PURPOSE/OBJECTIVE(S)

It is controversial whether to add consolidative radiotherapy (RT) after chemoimmunotherapy in the first-line treatment for diffuse large B-cell lymphoma (DLBCL). This study aimed to investigate the long-term net survival benefit of RT for early-stage DLBCL in the rituximab era.

MATERIALS/METHODS

The data of 10,841 adult patients with early-stage DLBCL from the Surveillance, Epidemiology, and End Results (SEER) database between 2002 and 2015 were extracted and analyzed. The patients had received combined modality treatment (CMT, chemotherapy plus RT) or chemotherapy alone. Linear regression analysis was performed for RT utilization by year of diagnosis. Competing risk analysis was used to evaluate the cumulative incidence of mortality according to the cause of death. Inverse probability of treatment weighting (IPTW) was used to balance the distribution of covariates between treatment arms. Relative survival (RS), standardized mortality ratio (SMR), and transformed Cox regression were performed to estimate the net survival benefit of RT by controlling for background mortality.

RESULTS

Linear regression revealed that the slope of the best-fit line for RT utilization over time was negative between 2002 and 2015 (m = -0.006, P = 0.003). A total of 4,648 deaths were recorded among 10,841 patients; 55.6% were lymphoma-related death (LRD), and 44.4% were attributed to other causes. Patients initially treated with CMT had a lower cumulative incidence of LRD than chemotherapy alone (HR 0.63, 95% CI: 0.57-0.69; P < 0.001). The 10-year overall survival (OS) rate of 66.1%, RS rate of 85.0%, and SMR of 1.71 achieved with CMT were significantly better than chemotherapy alone (OS, 53.0%; RS, 69.8%; SMR, 2.62; P < 0.001). By IPTW and multivariable analysis, the addition of RT remained associated with better OS (HR 0.67, 95% CI: 0.62-0.71; P < 0.001) and RS (HR 0.69, 95% CI: 0.65-0.74; P < 0.001).

CONCLUSION

RT was associated with better long-term net survival in patients with early-stage DLBCL in the rituximab era.

FAM3L: Feature-Aware Multi-Modal Metric Learning for Integrative Survival Analysis of Human Cancers

Survival analysis is to estimate the survival time for an individual or a group of patients, which is a valid solution for cancer treatments. Recent studies suggested that the integrative analysis of histopathological images and genomic data can better predict the survival of cancer patients than simply using single bio-marker, for different bio-markers may provide complementary information. However, for the given multi-modal data that may contain irrelevant or redundant features, it is still challenge to design a distance metric that can simultaneously discover significant features and measure the difference of survival time among different patients. To solve this issue, we propose a Feature-Aware Multi-modal Metric Learning method (FAM3L), which not only learns the metric for distance constraints on patients' survival time, but also identifies important images and genomic features for survival analysis. Specifically, for each modality of data, we firstly design one feature-aware metric that can be decoupled into a traditional distance metric and a diagonal weight for important feature identification. Then, in order to explore the complex correlation across multiple modality data, we apply Hilbert-Schmidt Independence Criterion (HSIC) to jointly learn multiple metrics. Finally, based on the learned distance metrics, we apply the Cox proportional hazards model for prognosis prediction. We evaluate the performance of our proposed FAM3L method on three cancer cohorts derived from The Cancer Genome Atlas (TCGA), the experimental results demonstrate that our method can not only achieve superior performance for cancer prognosis, but also identify meaningful image and genomic features correlating strongly with cancer survival.

Elevated C-reactive protein mediates the liver-brain axis: a preliminary study

BACKGROUND

Chronic liver diseases of all etiologies exist along a spectrum with varying degrees of hepatic fibrosis. Despite accumulating evidence implying associations between liver fibrosis and cognitive functioning, there is limited research exploring the underlying neurobiological factors and the possible mediating role of inflammation on the liver-brain axis.

METHODS

Using data from the UK Biobank, we examined the cross-sectional association of liver fibrosis (as measured by Fibrosis-4 score) with cognitive functioning and regional grey matter volumes (GMVs) while adjusting for numerous covariates and multiple comparisons. We further performed post-hoc preliminary analysis to investigate the mediating effect of C-reactive protein (CRP) on the association between liver fibrosis and both cognitive functioning and GMVs.

FINDINGS

We analysed behaviour from up to 447,626 participants (N ranged from 45,055 to 447,533 per specific cognitive metric) 37 years and older. 38,244 participants (age range 44-82 years) had GMV data collected at a median 9-year follow-up. Liver fibrosis showed significant associations with cognitive performance in reasoning, working memory, visual memory, prospective memory, executive function, and processing speed. Subgroup analysis indicated larger effects sizes for symbol digital substitution but smaller effect sizes for trail making in middle-aged people than their old counterparts. Neuroimaging analyses revealed significant associations between liver fibrosis and reduced regional GMVs, primarily in the hippocampus, thalamus, ventral striatum, parahippocampal gyrus, brain stem, and cerebellum. CRP levels were significantly higher in adults with advanced liver fibrosis than those without, indicating an elevated systemic inflammation. Moreover, the serum CRP significantly mediated the effect of liver fibrosis on most cognitive measures and regional GMVs in the hippocampus and brain stem.

INTERPRETATION

This study provides a well-powered characterization of associations between liver fibrosis, cognitive impairment, and grey matter atrophy. It also highlights the possibly mediating role of systemic inflammation on the liver-brain axis. Early surveillance and prevention of liver diseases may reduce cognitive decline and brain GMV loss.

FUNDING

National Science Foundation, and National Institutes of Health.

A functional connectome signature of blood pressure in >30 000 participants from the UK biobank

AIMS

Elevated blood pressure (BP) is a prevalent modifiable risk factor for cardiovascular diseases and contributes to cognitive decline in late life. Despite the fact that functional changes may precede irreversible structural damage and emerge in an ongoing manner, studies have been predominantly informed by brain structure and group-level inferences. Here, we aim to delineate neurobiological correlates of BP at an individual level using machine learning and functional connectivity.

METHODS AND RESULTS

Based on whole-brain functional connectivity from the UK Biobank, we built a machine learning model to identify neural representations for individuals' past (∼8.9 years before scanning, N = 35 882), current (N = 31 367), and future (∼2.4 years follow-up, N = 3 138) BP levels within a repeated cross-validation framework. We examined the impact of multiple potential covariates, as well as assessed these models' generalizability across various contexts.The predictive models achieved significant correlations between predicted and actual systolic/diastolic BP and pulse pressure while controlling for multiple confounders. Predictions for participants not on antihypertensive medication were more accurate than for currently medicated patients. Moreover, the models demonstrated robust generalizability across contexts in terms of ethnicities, imaging centres, medication status, participant visits, gender, age, and body mass index. The identified connectivity patterns primarily involved the cerebellum, prefrontal, anterior insula, anterior cingulate cortex, supramarginal gyrus, and precuneus, which are key regions of the central autonomic network, and involved in cognition processing and susceptible to neurodegeneration in Alzheimer's disease. Results also showed more involvement of default mode and frontoparietal networks in predicting future BP levels and in medicated participants.

CONCLUSION

This study, based on the largest neuroimaging sample currently available and using machine learning, identifies brain signatures underlying BP, providing evidence for meaningful BP-associated neural representations in connectivity profiles.

Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank

BACKGROUND

Physical frailty is a state of increased vulnerability to stressors and is associated with serious health issues. However, how frailty affects and is affected by numerous other factors, including mental health and brain structure, remains underexplored. We aimed to investigate the mutual effects of frailty and health using large, multidimensional data.

METHODS

For this population-based study, we used data from the UK Biobank to examine the pattern and direction of association between physical frailty and 325 health-related measures across multiple domains, using linear mixed-effect models and adjusting for numerous confounders. Participants were included if complete data were available for all five indicators of frailty, all covariates, and at least one health measure. We further examined the association between frailty and brain structure and the role of this association in mediating the relationship between frailty and health outcomes.

FINDINGS

483 033 participants aged 38-73 years were included in the study at baseline (between Dec 19, 2006, and Oct 1, 2010); at a median follow-up of 9 years (IQR 8-10), behavioural data were available for 46 501 participants and neuroimaging data for 40 210 participants. The severity of physical frailty was significantly associated with decreased cognitive performance (Cohen's d=0·025-0·162), increased early-life risks (d=0·026-0·111), unhealthy lifestyle (d=0·013-0·394), poor physical fitness (d=0·007-0·668), increased symptoms of poor mental health (d=0·032-0·607), severe environmental pollution (d=0·013-0·064), and adverse biochemical markers (d=0·025-0·198). Some associations were bidirectional, with the strongest effects on mental health measures. The severity of frailty correlated with increased total white matter hyperintensity and lower grey matter volume, particularly in subcortical regions (d=0·027-0·082), which significantly mediated the association between frailty and health-related outcomes, although the mediated effects were small.

INTERPRETATION

Physical frailty is associated with diverse unfavourable health-related outcomes, which can be mediated by differences in brain structure. Our findings offer a framework for guiding preventative strategies targeting both frailty and psychiatric disorders.

FUNDING

National Institute of Mental Health, National Science Foundation.

Antidepressant treatment-related brain activity changes in remitted major depressive disorder

Recent evidence has shown that some brain regions are core hubs and play a key role in the treatment of depression. Twenty-five unmedicated patients with major depressive disorder (MDD) were included, and telephone follow-up was performed at 8, 24, and 48 weeks after enrollment. After reaching clinical remission, they were scheduled for a second magnetic resonance imaging scan and clinical evaluation. Thirty-one healthy controls were also investigated. The intrinsic functional connectivity (degree centrality) of each participant was mapped using a computationally efficient approach. Then, functional connectivity of patients was calculated between the identified regions of interest by degree centrality analysis and every voxel. Later, linear regression analysis was used to identify potential variables predictive of an improvement in disease severity. The prominent hubs identified by degree centrality analysis included the cerebellum, inferior temporal gyrus, lingual gyrus, dorsal medial prefrontal cortex (DMPFC), and dorsal lateral prefrontal cortex. We also found that the increased degree centrality of DMPFC was associated with improvement in depressive symptoms. The brain activity associated with antidepressant effects, especially brain connectivity changes in the left DMPFC, can potentially be used to monitor treatment response and predict treatment outcomes.

[Eriocitrin suppresses proliferation and migration of hepatocellular carcinoma SMMC-7721 cells by promoting ROS production and activating the MAPK pathway]

OBJECTIVE

To investigate the role of the ROS/MAPK signaling axis in mediating the inhibitory effect of eriocitrin on proliferation and migration of hepatocellular carcinoma SMMC-7721 cells.

METHODS

SMMC-7721 cells were treated with different concentrations of eriocitrin for 24 h, and the changes in cell viability were detected with CCK-8 assay. The migration and invasion abilities of the treated cells were evaluated using Transwell and scratch healing assays, the cell proliferation was assessed with colony-forming assay, and changes in nuclear morphology were observed with DAPI staining. Western blotting was performed to examine the changes in the expressions of E-cadherin, N-cadherin, MMP-2, MMP-9, PARP, Pro-caspase 3, pJNK, p-P38, and p-ERK. The effect of eriocitrin on PARP cleavage in SMMC-7721 cells pretreated with ERK, JNK and P38 inhibitors (U0126, SB203580 and SP600125, respectively) was detected using Western blotting. The effect of treatment with Nacetyl-cysteine (NAC, 30 μmol/L) and eriocitrin (100, 200, and 300 μg/mL), alone or in combination, on reactive oxygen species (ROS) levels in the cells was examined using a DCFH-DA fluorescent probe.

RESULTS

Eriocitrin below 50 μg/mL did not produce significant effect on the viability of SMMC-7721 cells (P>0.05). Treatment with eriocitrin significantly inhibited scratch healing, migration, and colony formation of the cells (P < 0.01), reduced the protein expressions of N-cadherin, MMP-2, and MMP-9 (P < 0.01), and up-regulated E-cadherin protein expression (P < 0.05). Eriocitrin-treated SMMC-7721 cells showed obvious apoptotic morphologies with decreased Procaspase 3 expression and increased PARP cleavage (P < 0.01) and phosphorylation levels of JNK, P38, and ERK (P < 0.01); Eriocitrin-induced PAPR cleavage was obviously enhanced by U0126 and SB203580 but attenuated by SP600125. Treatment with 300 μg/mL eriocitrin for 30 min significantly increased ROS level in the cells, and this effect was obviously suppressed by NAC.

CONCLUSION

Eriocitrin can suppress the proliferation and migration and promote apoptosis of hepatocellular carcinoma SMMC-7721 cells by promoting ROS production and activating the MAPKs signaling pathway.

Psychotic Symptom, Mood, and Cognition-associated Multimodal MRI Reveal Shared Links to the Salience Network Within the Psychosis Spectrum Disorders

Schizophrenia (SZ), schizoaffective disorder (SAD), and psychotic bipolar disorder share substantial overlap in clinical phenotypes, associated brain abnormalities and risk genes, making reliable diagnosis among the three illness challenging, especially in the absence of distinguishing biomarkers. This investigation aims to identify multimodal brain networks related to psychotic symptom, mood, and cognition through reference-guided fusion to discriminate among SZ, SAD, and BP. Psychotic symptom, mood, and cognition were used as references to supervise functional and structural magnetic resonance imaging (MRI) fusion to identify multimodal brain networks for SZ, SAD, and BP individually. These features were then used to assess the ability in discriminating among SZ, SAD, and BP. We observed shared links to functional and structural covariation in prefrontal, medial temporal, anterior cingulate, and insular cortices among SZ, SAD, and BP, although they were linked with different clinical domains. The salience (SAN), default mode (DMN), and fronto-limbic (FLN) networks were the three identified multimodal MRI features within the psychosis spectrum disorders from psychotic symptom, mood, and cognition associations. In addition, using these networks, we can classify patients and controls and distinguish among SZ, SAD, and BP, including their first-degree relatives. The identified multimodal SAN may be informative regarding neural mechanisms of comorbidity for psychosis spectrum disorders, along with DMN and FLN may serve as potential biomarkers in discriminating among SZ, SAD, and BP, which may help investigators better understand the underlying mechanisms of psychotic comorbidity from three different disorders via a multimodal neuroimaging perspective.

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder

BACKGROUND

Although electroconvulsive therapy (ECT) is an effective treatment for depression, ECT cognitive impairment remains a major concern. The neurobiological underpinnings and mechanisms underlying ECT antidepressant and cognitive impairment effects remain unknown. This investigation aims to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks and assesses whether they are associated with the ECT-induced electric field (E-field) with an optimal pulse amplitude estimation.

METHODS

A single site clinical trial focused on amplitude (600, 700, and 800 mA) included longitudinal multimodal imaging and clinical and cognitive assessments completed before and immediately after the ECT series (n = 54) for late-life depression. Another two independent validation cohorts (n = 84, n = 260) were included. Symptom and cognition were used as references to supervise fMRI and sMRI fusion to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks. Correlations between ECT-induced E-field within these two networks and clinical and cognitive outcomes were calculated. An optimal pulse amplitude was estimated based on E-field within antidepressant-response and cognitive-impairment networks.

RESULTS

Decreased function in the superior orbitofrontal cortex and caudate accompanied with increased volume in medial temporal cortex showed covarying functional and structural alterations in both antidepressant-response and cognitive-impairment networks. Volume increases in the hippocampal complex and thalamus were antidepressant-response specific, and functional decreases in the amygdala and hippocampal complex were cognitive-impairment specific, which were validated in two independent datasets. The E-field within these two networks showed an inverse relationship with HDRS reduction and cognitive impairment. The optimal E-filed range as [92.7-113.9] V/m was estimated to maximize antidepressant outcomes without compromising cognitive safety.

CONCLUSIONS

The large degree of overlap between antidepressant-response and cognitive-impairment networks challenges parameter development focused on precise E-field dosing with new electrode placements. The determination of the optimal individualized ECT amplitude within the antidepressant and cognitive networks may improve the treatment benefit-risk ratio.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02999269.

Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

BACKGROUND

Grip strength is a widely used and well-validated measure of overall health that is increasingly understood to index risk for psychiatric illness and neurodegeneration in older adults. However, existing work has not examined how grip strength relates to a comprehensive set of mental health outcomes, which can detect early signs of cognitive decline. Furthermore, whether brain structure mediates associations between grip strength and cognition remains unknown.

METHODS

Based on cross-sectional and longitudinal data from over 40,000 participants in the UK Biobank, this study investigated the behavioral and neural correlates of handgrip strength using a linear mixed effect model and mediation analysis.

RESULTS

In cross-sectional analysis, we found that greater grip strength was associated with better cognitive functioning, higher life satisfaction, greater subjective well-being, and reduced depression and anxiety symptoms while controlling for numerous demographic, anthropometric, and socioeconomic confounders. Further, grip strength of females showed stronger associations with most behavioral outcomes than males. In longitudinal analysis, baseline grip strength was related to cognitive performance at ~9 years follow-up, while the reverse effect was much weaker. Further, baseline neuroticism, health, and financial satisfaction were longitudinally associated with subsequent grip strength. The results revealed widespread associations between stronger grip strength and increased grey matter volume, especially in subcortical regions and temporal cortices. Moreover, grey matter volume of these regions also correlated with better mental health and considerably mediated their relationship with grip strength.

CONCLUSIONS

Overall, using the largest population-scale neuroimaging dataset currently available, our findings provide the most well-powered characterization of interplay between grip strength, mental health, and brain structure, which may facilitate the discovery of possible interventions to mitigate cognitive decline during aging.

Neuropsychiatric symptoms associated multimodal brain networks in Alzheimer's disease

Concomitant neuropsychiatric symptoms (NPS) are associated with accelerated Alzheimer's disease (AD) progression. Identifying multimodal brain imaging patterns associated with NPS may help understand pathophysiology correlates AD. Based on the AD continuum, a supervised learning strategy was used to guide four-way multimodal neuroimaging fusion (Amyloid, Tau, gray matter volume, brain function) by using NPS total score as the reference. Loadings of the identified multimodal patterns were compared across the AD continuum. Then, regression analyses were performed to investigate its predictability of longitudinal cognition performance. Furthermore, the fusion analysis was repeated in the four NPS subsyndromes. Here, an NPS-associated pathological-structural-functional covaried pattern was observed in the frontal-subcortical limbic circuit, occipital, and sensor-motor region. Loading of this multimodal pattern showed a progressive increase with the development of AD. The pattern significantly correlates with multiple cognitive domains and could also predict longitudinal cognitive decline. Notably, repeated fusion analysis using subsyndromes as references identified similar patterns with some unique variations associated with different syndromes. Conclusively, NPS was associated with a multimodal imaging pattern involving complex neuropathologies, which could effectively predict longitudinal cognitive decline. These results highlight the possible neural substrate of NPS in AD, which may provide guidance for clinical management.

Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.

Aberrant brain functional and structural developments in MECP2 duplication rats

Transgenic animal models with homologous etiology provide a promising way to pursue the neurobiological substrates of the behavioral deficits in autism spectrum disorder (ASD). Gain-of-function mutations of MECP2 cause MECP2 duplication syndrome, a severe neurological disorder with core symptoms of ASD. However, abnormal brain developments underlying the autistic-like behavioral deficits of MECP2 duplication syndrome are rarely investigated. To this end, a human MECP2 duplication (MECP2-DP) rat model was created by the bacterial artificial chromosome transgenic method. Functional and structural magnetic resonance imaging (MRI) with high-field were performed on 16 male MECP2-DP rats and 15 male wildtype rats at postnatal 28 days, 42 days, and 56 days old. Multimodal fusion analyses guided by locomotor-relevant metrics and social novelty time separately were applied to identify abnormal brain networks associated with diverse behavioral deficits induced by MECP2 duplication. Aberrant functional developments of a core network primarily composed of the dorsal medial prefrontal cortex (dmPFC) and retrosplenial cortex (RSP) were detected to associate with diverse behavioral phenotypes in MECP2-DP rats. Altered developments of gray matter volume were detected in the hippocampus and thalamus. We conclude that gain-of-function mutations of MECP2 induce aberrant functional activities in the default-mode-like network and aberrant volumetric changes in the brain, resulting in autistic-like behavioral deficits. Our results gain critical insights into the biomarker of MECP2 duplication syndrome and the neurobiological underpinnings of the behavioral deficits in ASD.

A Neuroimaging Signature of Cognitive Aging from Whole-Brain Functional Connectivity

Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in the brain in terms of neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it is shown that both cognitive function (domains spanning executive function, emotion processing, motor function, and memory) and human age can be reliably predicted from unique patterns of functional connectivity, with models generalizable in two external datasets (n = 533 and n = 453). Results show that cognitive decline and normal aging both manifest decrease within-network connections (especially default mode and ventral attention networks) and increase between-network connections (somatomotor network). Whereas dorsal attention network is an exception, which is highly predictive on cognitive ability but is weakly correlated with aging. Further, the positively weighted connections in predicting fluid intelligence significantly mediate its association with age. Together, these findings offer insights into why normal aging is often associated with cognitive decline in terms of brain network organization, indicating a process of neural dedifferentiation and compensational theory.

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration.

Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging

Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating individual differences in various behavioral phenotypes and clinical outcomes is of growing interest. However, the field is experiencing challenges regarding the interpretability of the results. Approaches to defining the specific contribution of functional connections, regions, or networks in prediction models are urgently needed, which may help explore the underlying mechanisms. In this article, we systematically review the methods and applications for interpreting brain signatures derived from predictive neuroimaging based on a survey of 326 research articles. Strengths, limitations, and the suitable conditions for major interpretation strategies are also deliberated. In-depth discussion of common issues in existing literature and the corresponding recommendations to address these pitfalls are provided. We highly recommend exhaustive validation on the reliability and interpretability of the biomarkers across multiple datasets and contexts, which thereby could translate technical advances in neuroimaging into concrete improvements in precision medicine.

Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder

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Overlap has been noted disorders which fall on the psychotic spectrum.

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Univariate studies may miss joint brain features across diagnostic categories.

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mCCA with jICA is paired with features across the psychotic spectrum to produce joint components.

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One joint component displayed a significant relationship with cognitive scores.

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The replicate trends of cortical-subcortical irregularity in psychotic spectrum disorders.

Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB).

Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.

A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with 18F-FDG PET

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This is the first study identifying a resting-state fMRI pattern in SCA3.

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This pattern was closely associated with a metabolic (¹⁸F-FDG PET) counterpart.

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Pattern subject scores were highly correlated with ataxia severity.

Spinocerebellar ataxia type 3 (SCA3) is a rare genetic neurodegenerative disease. The neurobiological basis of SCA3 is still poorly understood, and up until now resting-state fMRI (rs-fMRI) has not been used to study this disease. In the current study we investigated (multi-echo) rs-fMRI data from patients with genetically confirmed SCA3 (n = 17) and matched healthy subjects (n = 16). Using independent component analysis (ICA) and subsequent regression with bootstrap resampling, we identified a pattern of differences between patients and healthy subjects, which we coined the fMRI SCA3 related pattern (fSCA3-RP) comprising cerebellum, anterior striatum and various cortical regions. Individual fSCA3-RP scores were highly correlated with a previously published ¹⁸F-FDG PET pattern found in the same sample (rho = 0.78, P = 0.0003). Also, a high correlation was found with the Scale for Assessment and Rating of Ataxia scores (r = 0.63, P = 0.007). No correlations were found with neuropsychological test scores, nor with levels of grey matter atrophy. Compared with the ¹⁸F-FDG PET pattern, the fSCA3-RP included a more extensive contribution of the mediofrontal cortex, putatively representing changes in default network activity. This rs-fMRI identification of additional regions is proposed to reflect a consequence of the nature of the BOLD technique, enabling measurement of dynamic network activity, compared to the more static ¹⁸F-FDG PET methodology. Altogether, our findings shed new light on the neural substrate of SCA3, and encourage further validation of the fSCA3-RP to assess its potential contribution as imaging biomarker for future research and clinical use.

Whole-Brain Functional Connectivity Dynamics Associated With Electroconvulsive Therapy Treatment Response

BACKGROUND

Depressive episodes (DEPs), characterized by abnormalities in cognitive functions and mood, are a leading cause of disability. Electroconvulsive therapy (ECT), which involves a brief electrical stimulation of the anesthetized brain, is one of the most effective treatments used in patients with DEP due to its rapid efficacy.

METHODS

In this work, we investigated how dynamic brain functional connectivity responds to ECT and whether the dynamic responses are associated with treatment outcomes and side effects in patients. We applied a fully automated independent component analysis-based pipeline to 110 patients with DEP (including diagnosis of unipolar depression or bipolar depression) and 60 healthy control subjects. The dynamic functional connectivity was analyzed by a combination of the sliding window approach and clustering analysis.

RESULTS

Five recurring connectivity states were identified, and patients with DEPs had fewer occurrences in one brain state (state 1) with strong positive and negative connectivity. Patients with DEP changed the occupancy of two states (states 3 and 4) after ECT, resulting in significantly different occurrences of one additional state (state 3) compared with healthy control subjects. We further found that patients with DEP had diminished global metastate dynamism, two of which recovered to normal after ECT. The changes in dynamic connectivity characteristics were associated with the changes in memory recall and Hamilton Depression Rating Scale of DEP after ECT.

CONCLUSIONS

These converging results extend current findings on subcortical-cortical dysfunction and dysrhythmia in DEP and demonstrate that ECT might cause remodeling of brain functional dynamics that enhance the neuroplasticity of the diseased brain.

Three-way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

Advances in imaging acquisition techniques allow multiple imaging modalities to be collected from the same subject. Each individual modality offers limited yet unique views of the functional, structural, or dynamic temporal features of the brain. Multimodal fusion provides effective ways to leverage these complementary perspectives from multiple modalities. However, the majority of current multimodal fusion approaches involving functional magnetic resonance imaging (fMRI) are limited to 3D feature summaries that do not incorporate its rich temporal information. Thus, we propose a novel three‐way parallel group independent component analysis (pGICA) fusion method that incorporates the first‐level 4D fMRI data (temporal information included) by parallelizing group ICA into parallel ICA via a unified optimization framework. A new variability matrix was defined to capture subject‐wise functional variability and then link it to the mixing matrices of the other two modalities. Simulation results show that the three‐way pGICA provides highly accurate cross‐modality linkage estimation under both weakly and strongly correlated conditions, as well as comparable source estimation under different noise levels. Results using real brain imaging data identified one linked functional–structural–diffusion component associated to differences between schizophrenia and controls. This was replicated in an independent cohort, and the identified components were also correlated with major cognitive domains. Functional network connectivity revealed visual–subcortical and default mode‐cerebellum pairs that discriminate between schizophrenia and controls. Overall, both simulation and real data results support the use of three‐way pGICA to identify multimodal spatiotemporal links and to pursue the study of brain disorders under a single unifying multimodal framework.

Efficacy and Toxicity of Alternative Radiation Treatment Schemes for Patients With Hematologic Malignancies: A Collaborative ILROG COVID Era Report

Purpose/Objective(s)

The COVID19 pandemic required radiation oncologists (ROs) to consider shorter treatment courses to minimize patient and staff exposure and conserve healthcare resources. Hematologic ROs adopted hypofractionated radiation therapy (hRT) regimens according to guidelines published by the International Lymphoma Radiation Oncology Group (ILROG). We report for the first time the preliminary efficacy and toxicity of these novel hypofractionated regimens in the treatment of hematologic malignancies.

Materials/Methods

We conducted a multicenter, multinational retrospective study under the direction of the ILROG. All patients receiving hRT according to ILROG guidelines from 1/1/2020 to 8/31/2020 were included. Patient and treatment details were abstracted from separate institutional databases. Toxicity was graded using CTCAE v5.0.

Results

Ninety-three patients from 4 institutions treated with 114 RT courses were included. Patient and treatment details are displayed in Table 1. Median follow up for the cohort was 179 days, and 77 patients (82%) were alive at last follow up. Maximal toxicity experienced by patients included Grade 1 (n = 16), Grade 2 (n = 1) and Grade 3 (n = 1) toxicities. Of 80 sites with response assessment within the RT field, 69% of patients achieved a complete response (n = 55), 20% partial response (n = 16), 9% stable disease (n = 7), and 2% progressive disease (n = 2). No COVID19 infections during or after RT have been documented in this patient cohort.

Conclusion

HRT according to ILROG guidelines resulted in low rates of acute toxicity and reasonable short-term treatment efficacy. Longer follow up and comparison with control groups is needed to draw more definitive conclusions and will be presented at the Annual Meeting.

BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders

Deep learning has shown great potential to adaptively learn hidden patterns from high dimensional neuroimaging data, so as to extract subtle group differences. Motivated by the convolutional neural networks and prototype learning, we developed a brain-network-based convolutional prototype learning model (BNCPL), which can learn representations that simultaneously maximize inter-class separation while minimize within-class distance. When applying BNCPL to distinguish 208 depressive disorders from 210 healthy controls using resting-state functional connectivity (FC), we achieved an accuracy of 71.0% in multi-site pooling classification (3 sites), with 2.4-7.2% accuracy increase compared to 3 traditional classifiers and 2 alternative deep neural networks. Saliency map was also used to examine the most discriminative FCs learned by the model; the prefrontal-subcortical circuits were identified, which were also correlated with disease severity and cognitive ability. In summary, by integrating convolutional prototype learning and saliency map, we improved both the model interpretability and classification performance, and found that the dysregulation of the functional prefrontal-subcortical circuit may play a pivotal role in discriminating depressive disorders from healthy controls.

[Mechanism of PI3K/AKT/mTOR signaling pathway for mediating anti-inflammatory and anti-oxidant effects of chrysin: a protein microarray-based study]

OBJECTIVE

To investigate the mechanism of PI3K/AKT/mTOR signaling pathway for mediating the anti-inflammatory and anti-oxidant effects of chrysin.

METHODS

RAW264.7 cells were treated with different concentrations of chrysin for 24 h, and the changes in cell viability were detected using CCK-8 method. The cells with or without chrysin pretreatment for 2 h were stimulated with lipopolysaccharide (LPS) for different lengths of time, and the related signal molecules were screened using protein chip technique. In cells pretreated with chrysin for 2 h followed by LPS stimulation for 18 h, the release of IL-6, MCP-1 and TNF-α by the cells was detected with ELISA, and NO production was examined using Griess method, and ROS level was determined using DCFH-DA. The effects of chrysin, LPS, and their combination on the mRNA expressions of iNOS and COX-2 were detected using RT-PCR; Western blotting was performed to examine the changes in cellular expressions of p-AKT, p-PRAS40, p-mTOR, mTOR, p-P70S6k, p-S6RP and S6RP following the treatments with LPS, N-Acetyl-L-cysteine, and chrysin, alone or in combinations.

RESULTS

Chrysin below 60 μg/mL did not significantly affect the viability of RAW264.7 cells (P>0.05). Chrysin treatment significantly reduced the release of IL-6, MCP-1, and TNF-α and the level of NO (P < 0.01), and inhibited the mRNA and protein expressions of iNOS and COX-2 (P < 0.01) in the cells. The results of protein chip screening suggested that LPS could activate the AKT/mTOR pathway, which was significantly inhibited by chrysin pretreatment, and the results were verified by Western blotting (P < 0.01). Chrysin treatment significantly reduced the generation of endogenous ROS, and treatment with N-Acetyl-L-cysteine to eliminate intracellular ROS obviously reduced the expressions of iNOS and COX-2 (P < 0.05) and blocked the AKT/mTOR pathway (P < 0.05).

CONCLUSION

Chrysin can inhibit the synthesis of the upstream signaling molecule ROS to inhibit the activation of AKT/mTOR signaling pathway, regulate the translation process of ribosomes, down-regulate the synthesis and release of pro-inflammatory cytokines and inflammatory mediators, and thus produce anti-inflammatory effects.

Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker

BACKGROUND

Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues.

METHODS

A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels.

RESULTS

Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%.

CONCLUSIONS

Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.