Biology subjects

Chung, M. K.

Publications and source records attributed to Chung, M. K..

18 recordsLinked to original sources

bioRxiv2026

A Fractal-Dimension Framework for Quantifying Self-Similarity in Chromatin Folding

The three-dimensional folding of DNA is essential for genome function, but its organization remains difficult to summarize quantitatively across genomic scales. Here, we study DNA folding from Hi-C contact data using a network-based notion of fractal dimension. In this representation, genomic loci are treated as nodes, and observed Hi-C contacts define weighted edges, so that frequently interacting loci are closer in the resulting network. We then estimate fractal dimension using two complementary graph-based methods: the correlation dimension and the sandbox dimension. Validation on synthetic networks shows that the proposed estimators detect clear scaling behavior in hierarchical fractal-like networks, while distinguishing them from networks with local clustering but no stable multiscale self-similarity. Applied to intrachromosomal Hi-C data from the IMR90 human cell line, the method reveals approximate linear scaling regimes on log-log plots, suggesting fractal-like organization in chromatin contact networks. At the chromosome level, estimated fractal dimension tends to increase with chromosome size: larger chromosomes often have dimensions closer to 3, consistent with more compact and space-filling organization, whereas shorter chromosomes tend to have lower dimensions, closer to 1, consistent with simpler and more open folding patterns. A sliding-window analysis at 5 kb resolution further shows that fractal organization varies substantially along chromosomes rather than remaining uniform across genomic position. These results suggest that graph-based fractal dimension provides an interpretable summary of DNA folding complexity at both global and local scales. More broadly, the proposed framework offers a quantitative way to study multiscale genome organization from Hi-C data using tools from network geometry.

bioinformatics↗

bioRxiv2026

Thermodynamic rigidity of harmonic brain states relates to general mental ability in juvenile myoclonic epilepsy

Cognitive difficulties are increasingly recognized in juvenile myoclonic epilepsy (JME), but scalable biomarkers linking resting-state brain dynamics to general mental ability remain limited. Here, we combined topological data analysis, graph signal processing, machine learning, inverse Langevin modeling, and biophysical simulations to test whether EEG-derived network dynamics capture individual differences in general mental ability in JME. We studied 54 patients with JME and 45 healthy controls using resting-state high-density EEG and the raw estimated full-scale score derived from the Wechsler Abbreviated Scale of Intelligence (WASI), used here as an index of general mental ability. Subject-specific low-alpha activity was reconstructed with generalized eigendecomposition, and graph-derived features were extracted from the projection of topological and alpha-power signals onto the functional connectome, providing a graph-harmonic description of large-scale brain-state dynamics. In controls, dynamic EEG-derived features significantly predicted general mental ability, whereas the same framework failed in JME. Because prediction in controls was driven mainly by dynamic measures of smoothness (Dirichlet energy), we next examined the temporal organization of alpha-power smoothness using an inverse Langevin framework. Within the patient group, greater thermodynamic rigidity--that is, stronger confinement of fluctuations around preferred network states--was associated with lower general mental ability. Relative to controls, patients also showed lower thermodynamic noise, indicating a reduced tendency to explore alternative network regimes. Biophysical simulations suggested that reduced dendritic arborization can generate rigidity directly, whereas pharmacological stabilization of hyperexcitable circuits can shift the system toward a more rigid, lower-noise regime. Together, these findings suggest that cognition in JME is linked not only to altered resting-state network dynamics but also to stronger confinement of network-state fluctuations, with both intrinsic circuit abnormalities and treatment-related stabilization representing plausible routes to this rigid phenotype.

neuroscience↗

bioRxiv2026

Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order "loop" (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive-compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

neuroscience↗

bioRxiv2024

Integrated forward and reverse degradomics uncovers the proteolytic landscape of aortic aneurysms and the roles of MMP9 and mast cell chymase

BackgroundDysregulated proteolysis is implicated in thoracic (TAA) and abdominal aortic aneurysm (AAA) pathogenesis, but the proteolytic landscapes (degradomes) of aneurysmal and normal aorta, and contributions of individual proteases remain undefined. Here, a proteome-wide approach was used to uncover TAA and AAA degradomes, compare them quantitatively and define the specific role in aortic remodeling of two proteases consistently identified in the aneurysms, mast cell chymase (CMA1) and matrix metalloprotease 9 (MMP9). MethodsThe mass spectrometry-based N-terminomics strategy Terminal Amine Isotopic Labeling of Substrates (TAILS) was applied to Marfan syndrome TAAs (n=5), AAAs (n=16) and corresponding non-diseased aorta (TAs, n=4, and AAs, n=8) as a forward degradomics application, i.e., to define substrate and protease degradomes, and 8-plex iTRAQ-TAILS was used for quantitative comparison. Cleavage sites of CMA1 and MMP9 were sought by reverse degradomics, i.e., digestion of aortic proteins with these proteases, followed by 6-plex iTRAQ-TAILS. CMA1 and MMP9 proteolysis of biglycan was investigated using Amino-Terminal Oriented Mass spectrometry of Substrates (ATOMS). ResultsWe experimentally annotated 16,923 proteolytically derived peptides (substrate degradome) and 90 proteases (protease degradome) in the aorta. Quantitative substrate degradome comparisons identified specific differentially modulated pathways and networks in TAA and AAA. Reverse degradomics elucidated > 300 CMA1 and MMP9 substrate cleavage sites, of which, many, including orthogonally validated biglycan cleavage, occurred in the disease degradomes. ConclusionsUnbiased, proteome-wide forward degradomics of the aortic wall from TAA, AAA and non-diseased tissue generated the first systems biology view of vascular wall breakdown and public resource for the hitherto occult proteolytic landscape, demonstrating widespread extracellular matrix remodeling. The findings provide insights on aortic aneurysm pathways and potential disease biomarkers. Mapping of specific contributions of CMA1 and MMP9 on the aortic forward substrate degradome using reverse degradomics provides a strategy for defining the activities of all proteases involved in aortic disease.

biochemistry↗

bioRxiv2023

Whole genome association testing in 333,100 individuals across three biobanks identifies rare non-coding single variant and genomic aggregate associations with height

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N=200,003), TOPMed (N=87,652) and All of Us (N=45,445). We performed rare (<0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal, intergenic and deep-intronic annotation. We observed 29 independent variants associated with height at P < 6 x 10-10 after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed a novel approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

genetics↗

bioRxiv2023

Dysregulated Platelet Function and Thrombosis in Patients with Post-Acute Sequelae of COVID-19

BackgroundPost-acute sequelae of COVID-19 (PASC), also referred as Long-COVID, sometimes follows COVID-19, a disease caused by SARS-CoV-2. While SARS-CoV-2 is well-known to promote a prothrombotic state, less is known about the thrombosis risk in PASC. AimOur objective was to evaluate the platelet function and thrombotic potential in patients following recovery from SARS-CoV-2 with clear symptoms of PASC. MethodsPASC patients and matched healthy controls were enrolled in the study on average 15 months after documented SARS-CoV-2 infection. Platelet activation was evaluated by Light Transmission Aggregometry (LTA) and flow cytometry in response to platelet surface receptor agonists. Thrombosis in platelet-deplete plasma was evaluated by Factor Xa activity. A microfluidics system assessed thrombosis in whole blood under shear stress conditions. ResultsA mild increase in platelet aggregation in PASC patients through the thromboxane receptor was observed and platelet activation through the glycoprotein VI (GPVI) receptor was decreased in PASC patients compared to age- and sex-matched healthy controls. Thrombosis under shear conditions as well as Factor Xa activity were reduced in PASC patients. Plasma from PASC patients was an extremely potent activator of washed, healthy platelets - a phenomenon not observed when stimulating healthy platelets after incubation with plasma from healthy individuals. ConclusionsPASC patients show dysregulated responses in platelets and coagulation in plasma, likely caused by a circulating molecule that promotes thrombosis. A hitherto undescribed protective response appears to exists in PASC patients to counterbalance ongoing thrombosis that is common to SARS-CoV-2 infection.

pharmacology and toxicology↗

bioRxiv2022

Topological Data Analysis of Human Brain Networks Through Order Statistics

Understanding the topological characteristics of the brain network across a population is central to understanding brain functions. The abstraction of human connectome as a graph has been pivotal in gaining insights on the topological features of the brain network. The development of group-level statistical inference procedures in brain graphs while accounting for the heterogeneity and randomness still remains a difficult task. In this study, we develop a robust statistical framework based on persistent homology using the order statistics for analyzing brain networks. The use of order statistics greatly simplifies the computation of the persistent barcodes. We validate the proposed methods using comprehensive simulation studies and subsequently apply to the resting-state functional magnetic resonance images. We conclude a statistically significant topological difference between the male and female brain networks. Author summaryWe fit a random graph model to the brain network and compute the expected persistent barcodes using order statistics. This novel approach significantly simplifies the computation of expected persistent barcodes, which otherwise requires complex theoretical constructs. Subsequently, the proposed statistical framework is used to discriminate if two groups of brain networks are topologically different. The method is applied in determining the sexual dimorphism in the shape of resting-state functional magnetic resonance images.

neuroscience↗

bioRxiv2021

Network-based prediction and functional validation of metformin for potential treatment of atrial Fibrillation using human inducible pluripotent stem cell-derived atrial-like cardiomyocytes

Atrial fibrillation (AF) is a significant cause of morbidity and mortality, and effective therapeutic interventions are lacking. Here, we harness an integrative, network medicine approach to repurpose FDA-approved drugs for AF. We hypothesize that the use of an unbiased method for prioritizing AF drugs using patient transcriptomics data can help to identify alternative therapeutic strategies and mechanism-of-action for these drugs. To achieve this, we first characterized the molecular networks specific to AF by incorporating transcriptomic data of left atrial tissue. We quantified the network proximity of genes differentially expressed in AF to drug targets to identify putative drugs for repurposing. We identified nine high-confidence drug candidates that were validated using enrichment analysis of drug-gene signatures in human cell lines. We identified metformin for the potential treatment of AF and validated its use in human inducible pluripotent stem cell-derived atrial-like cardiomyocytes. We identified AF-specific dysregulated networks enriched in cardiac metabolism, ion transport, and immune pathways that were improved following metformin treatment. In summary, this study utilized network-based approaches for rapid identification of drugs that may be repurposed for AF treatment and validated metformin as a candidate drug using a robust human atrial cell model.

systems biology↗

bioRxiv2020

Topological Learning for Brain Networks

This paper proposes a novel topological learning framework that can integrate networks of different sizes and topology through persistent homology. This is possible through the introduction of a new topological loss function that enables such challenging task. The use of the proposed loss function bypasses the intrinsic computational bottleneck associated with matching networks. We validate the method in extensive statistical simulations with ground truth to assess the effectiveness of the topological loss in discriminating networks with different topology. The method is further applied to a twin brain imaging study in determining if the brain network is genetically heritable. The challenge is in overlaying the topologically different functional brain networks obtained from the resting-state functional magnetic resonance imaging (fMRI) onto the template structural brain network obtained through the diffusion tensor imaging (DTI).

bioinformatics↗

bioRxiv2020

Pollutants in Hong Kong Soils: Organochlorine Pesticides and Polychlorinated Biphenyls

Organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) were investigated in 138 soil samples collected in Hong Kong. Results showed that within the selected OCPs, only DDT and its metabolites (DDD and DDE) were frequently detected. Of 138 soil samples, 18% were non-detected for any DDT residues, while 25% were contaminated sporadically with DDT only (non-detected to 1090 {micro}g kg-1) and 57% contained various combinations of DDT, DDD and DDE (2.03 to 1118 {micro}g kg-1). In contrast, total PCBs ({sum}66 congeners) contamination was distributed more evenly (0.22 to 154 {micro}g kg-1) than DDTs, but serious contamination was found in industrial areas and soils collected near highways. Concentrations of 7 indicator PCBs ranged between non-detected to 34.5 {micro}g kg-1. The ratios of DDT/metabolites were typically greater than 1, thus suggesting recent application of DDT. Medium-range deposition from industrial areas within as well as away from the city is also suspected to be the origins of DDTs and PCBs found in Hong Kong soils. The concentrations of DDTs and PCBs in all soil samples did not exceed the recommended values in soil quality guidelines except 3 samples for DDT from locations far away from densely populated districts such as Tuen Mun and Tin Shui Wai. Therefore, DDTs and PCBs were not of significant concern in terms of their impacts on public health and environment.

pharmacology and toxicology↗

bioRxiv2020

Pollutants in Hong Kong Soil: As, Cd, Cr, Cu, Hg, Pb and Zn

Six heavy metals (Hg, Cu, Cd, Cr, Pb, Zn) and 1 metalloid (As) in surface soils of Hong Kong were investigated in 10 land use categories (urban park, greening area, country park, rural area, restored landfill, agricultural farmland, orchard farm, crematorium, industrial and near highway area). Edaphic Hg concentration in Hong Kong was firstly reported here. Clustering of land uses was observed based on total pollutants concentrations (sum of 7 metals). The most polluted cluster consisted of industrial and highway areas (median: 617 to 833 mg kg-1) and the runner-up cluster included urban park, greening area and restored landfill (median: 400 to 500 mg kg-1). However, this general finding was not observed for Hg, where higher concentration was found in agricultural farmland (median 109 g kg-1). The use of low quality fertilizers, together with the contribution from exhausts and wearable parts from automobiles were believed to be the major sources of Cr, Cu and Zn in Hong Kong, while the application of Hg-containing agrochemicals maybe the main mechanism of Hg contamination in agricultural soil. Based on the daily intake assumption of 0.2 g d-1 of soil particles by USEPA, direct ingestion of Hg-containing soils is not a major exposure pathway for population in Hong Kong. When comparing the edaphic heavy metal concentrations with Dutch soil quality guidelines demonstrated that Hg, Cd and Pb were not in level of health concerns, while Cu, Cr and Zn in less than 6% of total samples were found to exceed the Dutch intervention values sporadically. In contrast, suburban soils from northern and northeastern Hong Kong were mostly contaminated with As (10% of total samples) at concentration that could be potentially causing adverse health impacts to the nearby population. Pollutant in Hong Kong soils seriesO_LIChung, M. K., Hu, R., Cheung, K. C. & Wong, M. H. Pollutants in Hong Kong soils: Polycyclic aromatic hydrocarbons. Chemosphere 67, 464-473 (2007). http://doi.org/10.1016/j.chemosphere.2006.09.062 C_LIO_LIChung, M. K., Cheung, K. C. & Wong, M. H. Pollutants in Hong Kong Soil: As, Cd, Cr, Cu, Hg, Pb and Zn https://doi.org/10.1101/2020.02.16.951558 C_LIO_LIChung, M. K., Hu, R., Cheung, K. C. & Wong, M. H. Pollutants in Hong Kong Soils: Organochlorine Pesticides and Polychlorinated Biphenyls https://doi.org/10.1101/2020.02.16.951541 C_LI

pharmacology and toxicology↗

bioRxiv2019

Causal SNP regulating FAM13B expression identified for the Chr. 5q31 atrial fibrillation susceptibility loc

RationaleOur prior RNA sequencing study found that FAM13B gene expression in human left atrial appendages was strongly associated with an atrial fibrillation (AF) susceptibility-associated variant on chr. 5q31.\n\nObjectiveTo identify the common genetic variant responsible for regulating FAM13B expression and the effect of FAM13B expression on cardiomyocyte gene expression in order to gain insight into the functional mechanism of the chr. 5q31 AF susceptibility locus.\n\nMethods and ResultsBy taking advantage of a smaller linkage disequilibrium block in African descent subjects and available chromatin conformation data, we identified the common single nucleotide polymorphism (SNP) rs17171731 as a candidate genetic variant controlling FAM13B gene expression in the left atrium. Functional analysis demonstrated that the AF risk allele of rs17171731 had less enhancer activity than the protective allele. Gel mobility shift studies determined that the risk allele bound to an additional protein that may function as a transcriptional repressor. Knockdown of FAM13B expression in stem cell-derived human cardiomyocytes (iCM) altered the expression of >1000 genes and modified the sodium current, consistent with increased susceptibility to atrial fibrillation. Transfection of GFP tagged FAM13B into iCMs demonstrated expression on the plasma membrane and at the Z-disk.\n\nConclusionsThe chr. 5q31 AF risk variant was identified as rs17171731, with the risk allele having less enhancer activity, leading to decreased expression of FAM13B, which resides on the plasma membrane and the Z-disk, and appears to play a role in the regulation of cardiomyocyte gene expression and the late sodium current.

genomics↗

bioRxiv2019

Atrial fibrillation associated common risk variants in SYNE2 lead to lower expression of nesprin-2α1 and increased nuclear stiffness

RationaleAtrial fibrillation (AF) genome-wide association studies (GWAS) identified significant associations for rs1152591 and linked variants in the SYNE2 gene encoding the nesprin-2 protein that connects the nuclear membrane with the cytoskeleton\n\nObjectiveDetermine the effects of the AF-associated rs1152591 and rs1152595, two linked intronic single nucleotide polymorphisms (SNPs), on SYNE2 expression and investigate the mechanisms for their association with AF.\n\nMethods and ResultsRNA sequencing of human left atrial appendage (LAA) tissues indicated that rs1152591 and rs1152595 were significantly associated with the expressions of SYNE21, a short mRNA isoform, without an effect on the expression of the full-length SYNE2 mRNA. SYNE21 mRNA uses an alternative transcription start site and encodes an N-terminal deleted 62 kDa nesprin-21 isoform, which can act as a dominant-negative on nuclear-cytoskeleton connectivity. Western blot and qPCR assays confirmed that AF risk alleles of both SNPs were associated with lower expression of nesprin-21 in human LAA tissues. Reporter gene transfections demonstrated that the risk vs. reference alleles of rs1152591 and rs1152595 had decreased enhancer activity. SYNE2 siRNA knockdown (KD) or nesprin-21 overexpression studies in human stem cell-derived induced cardiomyocytes (iCMs) resulted in ~12.5 % increases in the nuclear area compared to controls (p<0.001). Atomic force microscopy demonstrated that SYNE2 KD or nesprin-21 overexpression led to 57.5% or 33.2% decreases, respectively, in nuclear stiffness compared to controls (p< 0.0001).\n\nConclusionsAF-associated SNPs rs1152591 and rs1152595 downregulate the expression of SYNE21, increasing nuclear-cytoskeletal connectivity and nuclear stiffness. The resulting increase in mechanical stress may play a role in the development of AF.

genomics↗

bioRxiv2019

Recovery of trait heritability from whole genome sequence data

Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be largely recovered from whole-genome sequence (WGS) data on 25,465 unrelated individuals of European ancestry. We assigned 33.7 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned genetic variance accordingly. The estimated heritability was 0.68 (SE 0.10) for height and 0.30 (SE 0.10) for BMI, with a range of ~0.60 - 0.71 for height and ~0.25 - 0.35 for BMI, depending on quality control and analysis strategies. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection thereon. Cumulatively variants with 0.0001 < MAF < 0.1 explained 0.47 (SE 0.07) and 0.30 (SE 0.10) of heritability for height and BMI, respectively. Our results imply that rare variants, in particular those in regions of low LD, is a major source of the still missing heritability of complex traits and disease.

genetics↗

bioRxiv2018

Genome-wide association meta-analysis of PR interval identifies 47 novel loci associated with atrial and atrioventricular electrical activity

Electrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.

genetics↗

bioRxiv2017

Toward Capturing the Exposome: Exposure Biomarker Variability and Co-Exposure Patterns in the Shared Environment

BACKGROUNDAlong with time, variation in the exposome is dependent on the location and sex of study participants. One specific factor that may influence exposure co-variations is a shared household environment.\n\nOBJECTIVESTo examine the influence of shared household and partners sex in relation to the variation in 128 endocrine disrupting chemical (EDC) exposures among couples.\n\nMETHODSIn a cohort comprising 501 couples trying for pregnancy, we measured 128 (13 chemical classes) persistent and non-persistent EDCs and estimated 1) sex-specific differences; 2) variance explained by shared household; and 3) Spearmans rank correlation coefficients (rs) for females, males, and couples exposures.\n\nRESULTSSex was correlated with 8 EDCs including polyfluoroalkyl substances (PFASs) (p < 0.05). Shared household explained 43% and 41% of the total variance for PFASs and blood metals, respectively, but less than 20% for the remaining 11 EDC classes. Co-exposure patterns of the exposome were similar between females and males, with within-class rs higher for persistent and lower for non-persistent chemicals. Median rss of polybrominated compounds and urine metalloids were 0.45 and 0.09, respectively, for females (0.41 and 0.08 for males), whereas lower rss for these 2 classes were found for couples (0.21 and 0.04).\n\nCONCLUSIONSOverall, sex did not significantly affect EDC levels in couples. Individual, rather than shared environment, could be a major factor influencing the co-variation of 128 markers of the exposome. Correlations between exposures are lower in couples than in individual partners and have important analytical and sampling implications for epidemiological study.

epidemiology↗

bioRxiv2017

Exact Topological Inference For Paired Brain Networks Via Persistent Homology

We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. The framework is general enough for dealing with any type of paired images such as twins, multimodal and longitudinal images. The exact nonparametric statistical inference procedure is derived on testing monotonic graph theory features that do not rely on time consuming permutation tests. The proposed method computes the exact probability in quadratic time while the permutation tests require exponential time. As illustrations, we apply the method to simulated networks and a twin fMRI study. In case of the latter, we determine the statistical significance of the heritability index of the large-scale reward network where every voxel is a network node.

neuroscience↗

bioRxiv2017

Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

In diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

neuroscience↗