Revealing genomic heterogeneity and commonality: A penalized integrative analysis approach accounting for the adjacency structure of measurements.

Advancements in high-throughput genomic technologies have revolutionized the field of disease biomarker identification by providing large-scale genomic data. There is an increasing focus on understanding the relationships among diverse patient groups with distinct disease subtypes and characteristics. Complex diseases exhibit both heterogeneity and shared genomic factors, making it essential to investigate these patterns to accurately detect markers and comprehensively understand the diseases. Integrative analysis has emerged as a promising approach to address this challenge. However, existing studies have been limited by ignoring the adjacency structure of genomic measurements, such as single nucleotide polymorphisms (SNPs) and DNA methylations. In this study, we propose a structured integrative analysis method that incorporates a spline type penalty to accommodate this adjacency structure. We utilize a fused lasso type penalty to identify both heterogeneity and commonality across the groups. Extensive simulations demonstrate its superiority compared to several direct competing methods. The analysis of The Cancer Genome Atlas melanoma data with DNA methylation measurements and GENEVA diabetes data with SNP measurements exhibit that the proposed analysis lead to meaningful findings with better prediction performance and higher selection stability.

Financial toxicity, coping strategies, and quality of life among Chinese patients with hematologic malignancies: a cross-sectional study.

PURPOSE: Financial toxicity is used to describe the financial hardship experienced by cancer patients. Financial toxicity may cause negative consequences to patients, whereas little is known in Chinese context. This study aimed to explore the level of financial toxicity, coping strategies, and quality of life among Chinese patients with hematologic malignancies. PATIENTS AND METHODS: We conducted a prospective, observational study among 274 Chinese patients with hematologic malignancies from November 2021 to August 2022 in Sun Yat-sen University Cancer Center. Clinical data were extracted from electronic clinical records. Data on financial toxicity, coping strategies, and quality of life were collected using PRO measures. Chi-square or independent t test and multivariate logistic regression were performed to explore the associated factors of financial toxicity and quality of life, respectively. Effects of financial toxicity on coping strategies were examined using Chi-square. RESULTS: The mean age of the participants was 50.2 (± 14.6) years. Male participants accounted for 57.3%. About half of the participants reported high financial toxicity. An average median of ¥200,000 on total medical expenditures since the diagnosis was reported. The average median monthly out-of-pocket health expenditure relating to cancer treatment was ¥20,000 (range ¥632-¥172,500) after reimbursement. Reduce daily living expenses (64.9%), borrowing money (55.7%), and choosing cheaper regimens (19.6%) were the commonly used strategies to cope with financial burden. Financial toxicity was negatively associated with quality of life (ß = 0.071, P = 0.001). CONCLUSIONS: Financial toxicity was not uncommon in patients with hematological malignancies. Reducing daily living expenses, abandoning treatment sessions, and borrowing money were the strategies commonly adopted by participants to defray cancer costs. Additionally, participants with high level of financial toxicity tended to have worse quality of life. Therefore, actions from healthcare providers, policy-makers, and other stakeholders should be taken to help cancer patients mitigate their financial toxicity.

[Related factors and equity of health status among floating population in China based on geographic information system analysis].

OBJECTIVE: To understand the health status, influencing factors and spatial distribution of the Chinese floating population and to evaluate the health equity of the floating population. METHODS: All the data were collected from the 2017 Migrant Population Dynamic Monitoring Survey in China, binary Logistic regression was used to analyze the factors that might affect the health of the floating population, and the concentration index method was used to evaluate the health equity of the floating population. Spatial autocorrelation analyses the spatial aggregation of health status and health equity. RESULTS: The unhealthy rate of the floating population in China was 2.71%. Age and gender show a statistically significant impact on self-rated health; that is, as age increases, the self-rated health of the migrant population gradually deteriorates, and women are more likely to think that they are unhealthy. Fairness analysis shows that the concentration index of the floating population is 0.021 7, the urban household registration floating population is 0.021 6, and the rural household registration floating population is 0.021 9. It is shown that the fairness of the health status of the floating population is biased towards the high-income class, and the rural household registration floating population' s health unfairness is greater than that of the urban household registration migration population. Moreover, Moran' s i=0.211 for self-rated health and Moran' s i=0.291 for the unhealthy rate indicate that self-rated health has a spatial aggregation trend. Moran' s i=0.136 showed the characteristics of spatial clustering, and the two-week prevalence fairness of the floating population was mainly in the northern and southeastern coastal areas. CONCLUSION: In general, the health status of the floating population in China is relatively good. The main influencing factors of health included gender and age. The central tendency of health inequity is reflected in the southeast coastal and northern regions, which are characterized by poverty. Attention to spatial aggregation is not only helpful to analyze the reasons of floating population, but also to study the health differences between different regions and health-related factors, to improve the overall health level of the whole population.

Loss of Y chromosome in leukocytes can be regarded as a male-specific age predictor for age group estimation in forensic genetics.

Age prediction is an important field in forensic and aging research. Traditional methods used DNA methylation, telomere shortening, and mitochondrial DNA mutations to conduct age prediction models. Sex chromosomes, like the Y chromosome, have a significant role in aging as previously reported in hematopoietic disease and many non-reproductive cancers. Until now, there is no age predictor based on the percentage of loss of Y chromosome (LOY). LOY has been previously revealed to be correlated with Alzheimer's disease, short survival, and higher risk of cancer. The possible correlation of LOY between normal aging was not fully explored. In this study, we conducted age prediction by measuring LOY percentage by droplet digital PCR (ddPCR), based on 232 healthy male samples, including 171 blood samples, 49 saliva samples, 12 semen samples. The age group of samples ranges from 0 to 99 years, with two individuals in almost every single age. Pearson correlation method was performed to calculate the correlation index. The result indicated a correlation index of 0.21 (p = 0.0059) between age and LOY percentage in blood samples, with the regression formula being y = - 0.016823 + 0.001098x. The correlation between LOY percentage and age is obvious only when the individuals were divided into different age groups (R = 0.73, p = 0.016). In the studied saliva and semen samples, p-values of the correlation are 0.11 and 0.20, respectively, showing no significant association between age and LOY percentage in these two biological materials. For the first time, we investigated male-specific age predictor based on LOY. The study showed that LOY in leukocytes can be regarded as a male-specific age predictor for age group estimation in forensic genetics. This study might be indicative for forensic applications and aging research.

Bruton tyrosine kinase inhibitors preserve anti-CD19 chimeric antigen receptor T-cell functionality and reprogram tumor micro-environment in B-cell lymphoma.

BACKGROUND AIMS: Combination therapy is being actively explored to improve the efficacy and safety of anti-CD19 chimeric antigen receptor T-cell (CART19) therapy, among which Bruton tyrosine kinase inhibitors (BTKIs) are highly expected. BTKIs may modulate T-cell function and remodel the tumor micro-environment (TME), but the exact mechanisms involved and the steps required to transform different BTKIs into clinical applications need further investigation. METHODS: We examined the impacts of BTKIs on T-cell and CART19 phenotype and functionality in vitro and further explored the mechanisms. We evaluated the efficacy and safety of CART19 concurrent with BTKIs in vitro and in vivo. Moreover, we investigated the effects of BTKIs on TME in a syngeneic lymphoma model. RESULTS: Here we identified that the three BTKIs, ibrutinib, zanubrutinib and orelabrutinib, attenuated CART19 exhaustion mediated by tonic signaling, T-cell receptor (TCR) activation and antigen stimulation. Mechanistically, BTKIs markedly suppressed CD3-ζ phosphorylation of both chimeric antigen receptor and TCR and downregulated the expression of genes associated with T-cell activation signaling pathways. Moreover, BTKIs decreased interleukin 6 and tumor necrosis factor alpha release in vitro and in vivo. In a syngeneic lymphoma model, BTKIs reprogrammed macrophages to the M1 subtype and polarized T helper (Th) cells toward the Th1 subtype. CONCLUSIONS: Our data revealed that BTKIs preserved T-cell and CART19 functionality under persistent antigen exposure and further demonstrated that BTKI administration was a potential strategy for mitigating cytokine release syndrome after CART19 treatment. Our study lays the experimental foundation for the rational application of BTKIs combined with CART19 in clinical practice.

IL-10 plus the EASIX score predict bleeding events after anti-CD19 CAR T-cell therapy.

Chimeric antigen receptor (CAR) T-cell-associated coagulopathy can cause bleeding events. To explore risk factors for hemorrhage after CAR T-cell therapy, we retrospectively analyzed routine indicators in 56 patients with non-Hodgkin lymphoma and B-cell acute lymphoblastic leukemia who received anti-CD19 CAR T-cell therapy. Disturbance of coagulation occurred mainly within one month post infusion, especially on day 7 and 14. The cumulative incidence of bleeding events within one month was 32.8%, with the median onset of 7 (range, 0-28) days. All bleeding events were grade 1-3. Patients who experienced bleeding events within one month had longer prothrombin time, higher IL-6, higher IL-10, and lower platelets before lymphodepletion. There were also correlations among coagulation-, inflammatory-, and tumor burden-related markers. Multi-variate analysis showed IL-10 (> 7.98 pg/mL; adjusted odds ratio [OR], 13.84; 95% confidence interval [CI], 2.03-94.36; P = 0.007) and the endothelial activation and stress index (EASIX, defined as dehydrogenase [U/L] × creatinine [mg/dL] / platelets [×109 cells/L]; >7.65; adjusted OR, 7.06; 95% CI, 1.03-48.23; P = 0.046) were significant risk factors for bleeding events. IL-10 plus the EASIX defined three risk groups for bleeding events with cumulative incidence of 100% (hazard ratio [HR], 14.47; 95% CI, 2.78-75.29; P < 0.0001), 38.5% (HR, 3.68; 95% CI, 0.82-16.67; P = 0.089), and 11.8% (reference), respectively. Future studies are needed to verify the risk assessment models for bleeding events after CAR T-cell treatment in larger cohorts.

Therapeutic Effect of Polaprezinc on Reflux Esophagitis in the Rat Model.

BACKGROUND/AIMS: To explore the protective effects and therapeutic mechanism of Esomeprazole (PPI), polaprezinc granule (PZ), and PPI + PZ on reflux esophagitis (RE) in the rat model. METHODS: Wistar rats were randomly divided into 9 groups, which contain the control group, the acid cessation group (0.7% HCl, Q3D × 4), and the acid persistence group (0.7% HCl, Q3D × 11). PPI was administered by gavage at 8 mg·kg-1 body weight and PZ was administered by gavage at 120 mg·kg-1 body weight once a day for 15 days. The gastric cardia tissue of the feeding tube was observed under the light microscope, and the levels of interleukin-8 (IL-8) and prostaglandin E2 (PGE2) were measured by ELISA. The expression of EGFR, Akt, p-Akt, and p-mTOR was detected by Western blot. RESULTS: The ELISA results showed that the levels of IL-8 and PGE2 were significantly increased in the model group, but decreased in all groups after treatment. In the acid cessation group, PZ treatment had the most significant effect on reducing IL-8 levels and PPI + PZ treatment had the most significant effect on reducing PGE2 levels. In the acid persistence group, the PPI treatment had the most significant effect on reducing the levels of IL-8 and PGE2, and the PZ treatment could also significantly reduce their levels, close to the normal value. Western blot results showed that the expression of PI3K/Akt/mTOR pathway protein was increased in the model group, while its expression was decreased after treatment. CONCLUSIONS: Polaprezinc has a significant therapeutic effect on RE in rats, which can reduce the levels of IL-8 and PGE2 and downregulate the expression of PI3K/Akt/mTOR signal pathway protein. The efficacy of polaprezinc in the treatment of reflux esophagitis is comparable to that of PPI, and the combination of them is more effective in the reflux esophagitis treatment.

Structural insight into the individual variability architecture of the functional brain connectome.

Human cognition and behaviors depend upon the brain's functional connectomes, which vary remarkably across individuals. However, whether and how the functional connectome individual variability architecture is structurally constrained remains largely unknown. Using tractography- and morphometry-based network models, we observed the spatial convergence of structural and functional connectome individual variability, with higher variability in heteromodal association regions and lower variability in primary regions. We demonstrated that functional variability is significantly predicted by a unifying structural variability pattern and that this prediction follows a primary-to-heteromodal hierarchical axis, with higher accuracy in primary regions and lower accuracy in heteromodal regions. We further decomposed group-level connectome variability patterns into individual unique contributions and uncovered the structural-functional correspondence that is associated with individual cognitive traits. These results advance our understanding of the structural basis of individual functional variability and suggest the importance of integrating multimodal connectome signatures for individual differences in cognition and behaviors.

Inference of population structure and admixture proportion from Y chromosomal data of Chinese population.

In the past two decades, Y chromosome data has been generated for human population genetic studies. These Y chromosome datasets were produced with various testing methods and markers, thus difficult to combine them for a comprehensive analysis. In this study, we combine four human Y chromosomal datasets of Han, Tibetan, Hui, and Li ethnic groups. The dataset contains 27 microsatellites and 137 single nucleotide polymorphisms these populations share in common. We assembled a single dataset containing 2439 individuals from 25 nationwide populations in China. A systematic analysis of genetic distance and clustering was performed. To determine the gene flow of the studied population with worldwide populations, we modeled the ancestry informative markers. The reference panel was regarded as a mixture of South Asian (SAS), East Asian (EAS), European (EUR), African (AFR), and American (AMR) populations from 1000 Genomes data of Y chromosome using nonlinear data-fitting. We then calculated the admixture proportion of these four studied populations with 26 worldwide populations. The results showed that the Han and Hui have great genetic affinity, and Hui is the most admixed ethnic group, with 61.53% EAS, 34.65% SAS, 1.91% AFR, 1.56% AMR, and 0.04% EUR ancestry component (the AMR is highly admixed and thus should be ignored). All the other three ethnic groups contained more than 97% EAS ancestry component. The Li is the least admixed population in this study. The combined dataset in this study is the largest of this kind reported to date and proposes reference population data for use in future paternal genetic studies and forensic genealogical identification.

Developmental validation of the Microreader™ RM-Y ID System: a new rapidly mutating Y-STR 17-plex system for forensic application.

Y-chromosomal short tandem repeats (Y-STRs) are widely applied to evolutionary, genealogical, and kinship analyses of male linages in forensic studies, but these low to midrange mutated Y-STRs typically fail to separate related males from the same paternal lineage. Recently, rapidly mutating Y-STRs (RM Y-STRs) have been demonstrated to improve the differentiation of male relatives and individuals. The Microreader™ RM-Y ID System is a new RM Y-STR kit that is capable of simultaneously amplifying 17 RM Y-STRs. Herein, to verify the efficiency and accuracy of the Microreader™ RM-Y ID System, developmental validation was conducted, including PCR-based studies, sensitivity, stability, species specificity, mixture, stutter percentage, and precision studies. Full profiles could be obtained when the hematin concentration was 250 µM, humic acid concentration was 1500 ng/µl, and tannic acid concentration was 200 ng/µl. Full profiles of the mixture of males/males could be detected up to a ratio of 19:1, and full profiles of females/males could always be detected even at ratios up to 24,000:1. Moreover, the forensic characteristics of 250 DNA-confirmed father-son pairs were analysed. The results showed that these 17 RM Y-STRs had high power for forensic discrimination (HD = 1) in the Chinese Han population, and the mutation rates were in the range of 4 × 10-3 (95% CI 1.00 × 10-4 to 2.21 × 10-2, DYS464) to 8.8 × 10-2 (95% CI 5.60 × 10-2 to 1.30 × 10-1, DYF399S1), indicating that the kit was effective for RM Y-STR studies and absolute individualisation of interrelated male individuals.

Oridonin represses epithelial-mesenchymal transition and angiogenesis of thyroid cancer via downregulating JAK2/STAT3 signaling.

Oridonin, a bioactive diterpenoid isolated from Rabdosia rubescens, has been reported to exert anticancer activity in various cancers. However, the molecular mechanism of oridonin in thyroid cancer has not yet been elucidated. In the present study, oridonin was found to significantly inhibit migration and invasion of thyroid cancer TPC-1 and BCPAP cells, as evidenced by wound healing assay, transwell migration assay and Matrigel invasion assay. In addition, oridonin could partially impede epithelial-mesenchymal transition by upregulating E-Cadherin expression and downregulating N-Cadherin and vimentin expressions in a concentration-dependent manner. Accumulating evidence indicated that JAK2 (Janus kinase-2)/STAT3 (Signal Transducer and Activator of Transcription 3) signaling pathway was associated with epithelial-mesenchymal transition. As expected, the protein levels of phosphorylated-JAK2 and phosphorylated-STAT3 were dramatically reduced upon oridonin treatment in thyroid cancer TPC-1 and BCPAP cells. Subsequently, the findings revealed that JAK2 overexpression could weaken the anti-metastatic effect and partially attenuate MET (mesenchymal-to-epithelial transition) by oridonin, while AG490, a JAK2 antagonist, enhanced the above process in thyroid cancer cells. The subsequent results showed that oridonin inhibited angiogenesis and VEGFA expression in thyroid cancer cells by tube formation assay, western blot and ELISA assay. Meanwhile, AG490 could further attenuate oridonin-treated VEGFA protein level. In addition, the in vivo results further confirmed that oridonin inhibited tumorigenicity in thyroid cancer xenograft. In conclusion, the results demonstrated that oridonin repressed metastatic phenotype, angiogenesis and modulated EMT (epithelial-mesenchymal transition) of thyroid cancer cells via the inactivation of JAK2/STAT3 signaling pathway, suggesting that JAK2 may be a novel therapeutic target of oridonin against thyroid cancer.

CIVET-Macaque: An automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques.

The MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness from in-vivo human MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed for and applied to human data and are often challenged by non-human primates (NHP) data. Amongst recent attempts to improve performance on NHP data, deep learning models appear to outperform the traditional tools. However, given the minimal sample size of most NHP studies and notable variations in data quality, the deep learning models are very rarely applied to multi-site samples in NHP imaging. To overcome this challenge, we used a transfer-learning framework that leverages a large human imaging dataset to pretrain a convolutional neural network (i.e. U-Net Model), and then transferred this to NHP data using a small NHP training sample. The resulting transfer-learning model converged faster and achieved more accurate performance than a similar U-Net Model trained exclusively on NHP samples. We improved the generalizability of the model by upgrading the transfer-learned model using additional training datasets from multiple research sites in the Primate Data-Exchange (PRIME-DE) consortium. Our final model outperformed brain extraction routines from popular MRI packages (AFNI, FSL, and FreeSurfer) across a heterogeneous sample from multiple sites in the PRIME-DE with less computational cost (20 s~10 min). We also demonstrated the transfer-learning process enables the macaque model to be updated for use with scans from chimpanzees, marmosets, and other mammals (e.g. pig). Our model, code, and the skull-stripped mask repository of 136 macaque monkeys are publicly available for unrestricted use by the neuroimaging community at https://github.com/HumanBrainED/NHP-BrainExtraction.

A collaborative resource platform for non-human primate neuroimaging.

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field .

Yesprit and Yeaseq: Applications for designing primers and browsing sequences for research using the four Schizosaccharomyces species.

The polymerase chain reaction (PCR)-based gene targeting method, which can delete a specific gene or introduce tags, has been widely utilized to study gene function in fission yeast. One of the critical steps in this method is to design primers for amplifying DNA fragments of deletion or tagging modules and for checking the integration of those DNA fragments at designated loci. Although the primer design tool Pombe PCR Primer Program (PPPP) is available for Schizosaccharomyces pombe, there is no such publicly available application for the other three fission yeast species, S. cryophilus, S. japonicus, and S. octosporus. Likewise, no application enabling DNA/protein sequence retrieval for these three fission yeast species is available either. Therefore, access to such functionality would substantially assist in retrieval of gene sequences of interest and primer design in these fission yeast species. In this report, we describe two applications for fission yeast study: Yesprit and Yeaseq. Yesprit is a primer design tool for strain construction using the PCR-based method, and Yeaseq is a sequence viewer that can acquire the DNA/protein sequences of specific genes. Both tools can be run on the Windows, macOS, and Linux platforms. We believe that the Yesprit and Yeaseq will facilitate research using the four fission yeast species.

Paternal genetic structure of Kyrgyz ethnic group in China revealed by high-resolution Y-chromosome STRs and SNPs.

Kyrgyz ethnic group is one of the nomads in China, with the majority in Xinjiang and a small part of them living in Heilongjiang province. Historically, they have went through five migrations westward due to the wars. The name "Kyrgyz" means 40 tribes, originating from the primary groups of Kyrgyz. However, it is a largely understudied population, especially from the Y chromosome. In this study, we used a previously validated high-resolution Y-chromosome single nucleotide polymorphisms (Y-SNPs) and short tandem repeats (Y-STRs) system to study Kyrgyz ethnic group. A total of 314 male samples of Kyrgyz ethnic group were genotyped by 173 Y-SNPs and 27 Y-STRs. After data analysis, the results unveiled that Kyrgyz ethnic group was a population with high percentage of both haplogroup C2a1a3a1d∼-F10091 (91/134) and R1a1a1b2a2-Z2124 (109/134), which has never been reported. This implied that Kyrgyz ethnic group might have gone through bottleneck effects twice, with these two main lineages left. Mismatch analysis indicated that the biggest mismatch number in haplogroup C2a1a3a1d∼-F10091 was 10, while that of haplogroup R1a1a1b2a2-Z2124 was 20. This huge difference reflected the different substructure in two lineages, suggesting that haplogroup C2a1a3a1d∼-F10091 might have the least admixture compared to the other two lineages. After admixture modelling with other datasets, the conclusion could be drawn that Kyrgyz ethnic group had great genetic affinity with Punjabi from Lahore, Pakistan, which supported that Kyrgyz ethnic group in China was close to central Asian.

The development and initial evaluation of referral flowchart for suspected neuroblastoma for pediatricians in nononcology clinics in China.

BACKGROUND: The delayed diagnosis of neuroblastoma (NB) is common in China, which results in the prognosis of NB in China lagging behind that in developed countries. METHODS: A referral flowchart for suspected NB was implemented in nononcology clinics at Beijing Children's Hospital (BCH). Patients with symptoms of suspected NB were referred from nononcology clinics in BCH to oncology clinics and confirmed NB cases were regarded as referral group. The control group comprised patients initially diagnosed with NB who came directly to oncology clinics in BCH from other regions nationwide. The age at NB diagnosis was compared as primary outcome, and the 5-year overall survival (OS) and event-free survival (EFS) were compared via the Kaplan-Meier method and log-rank tests. RESULTS: In total, 3337 children with suspected NB were screened consecutively from 687 070 pediatric patients. Through examination of urine vanillylmandelic acid and homovanillic acid, or B-ultrasound, 102 of 3337 patients were referred to oncologists for comprehensive evaluations. Eventually, 29 referred patients were diagnosed as NB and the hospital-based diagnosis rate of NB was 4.2 per 100 000 visits. The median age at diagnosis in the referral group was 21.0 months, which was 9 months earlier than that of the control group (30.0 months, P = .026). The 5-year OS rate was 72.4% in the referral group, which was higher than that of the control group (66.7%) but without statistical significance (P = .664). CONCLUSION: Delayed NB detection could be avoided by training pediatricians in nononcology clinics to detect suspected NB and refer these patients to oncologists.

The spatial organization of the chronnectome associates with cortical hierarchy and transcriptional profiles in the human brain.

The chronnectome of the human brain represents dynamic connectivity patterns of brain networks among interacting regions, but its organization principle and related transcriptional signatures remain unclear. Using task-free fMRI data from the Human Connectome Project (681 participants) and microarray-based gene expression data from the Allen Institute for Brain Science (1791 brain tissue samples from six donors), we conduct a transcriptome-chronnectome association study to investigate the spatial configurations of dynamic brain networks and their linkages with transcriptional profiles. We first classify the dynamic brain networks into four categories of nodes according to their time-varying characteristics in global connectivity and modular switching: the primary sensorimotor regions with large global variations, the paralimbic/limbic regions with frequent modular switching, the frontoparietal cortex with both high global and modular dynamics, and the sensorimotor association cortex with limited dynamics. Such a spatial layout reflects the cortical functional hierarchy, microarchitecture, and primary connectivity gradient spanning from primary to transmodal areas, and the cognitive spectrum from perception to abstract processing. Importantly, the partial least squares regression analysis reveals that the transcriptional profiles could explain 28% of the variation in this spatial layout of network dynamics. The top-related genes in the transcriptional profiles are enriched for potassium ion channel complex and activity and mitochondrial part of the cellular component. These findings highlight the hierarchically spatial arrangement of dynamic brain networks and their coupling with the variation in transcriptional signatures, which provides indispensable implications for the organizational principle and cellular and molecular functions of spontaneous network dynamics.

Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain.

Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.

Differentially categorized structural brain hubs are involved in different microstructural, functional, and cognitive characteristics and contribute to individual identification.

Very little is known regarding whether structural hubs of human brain networks that enable efficient information communication may be classified into different categories. Using three multimodal neuroimaging data sets, we construct individual structural brain networks and further identify hub regions based on eight widely used graph-nodal metrics, followed by comprehensive characteristics and reproducibility analyses. We show the three categories of structural hubs in the brain network, namely, aggregated, distributed, and connector hubs. Spatially, these distinct categories of hubs are primarily located in the default-mode system and additionally in the visual and limbic systems for aggregated hubs, in the frontoparietal system for distributed hubs, and in the sensorimotor and ventral attention systems for connector hubs. These categorized hubs exhibit various distinct characteristics to support their differentiated roles, involving microstructural organization, wiring costs, topological vulnerability, functional modular integration, and cognitive flexibility; moreover, these characteristics are better in the hubs than nonhubs. Finally, all three categories of hubs display high across-session spatial similarities and act as structural fingerprints with high predictive rates (100%, 100%, and 84.2%) for individual identification. Collectively, we highlight three categories of brain hubs with differential microstructural, functional and, cognitive associations, which shed light on topological mechanisms of the human connectome.