Search

Problem Inflammatory biomarkers are associated with preeclampsia ( PE) and poor fetal growth; however, genetic epidemiologic studies have been limited by reduced gene coverage and the exclusion of African American mothers. Method of study Cases and controls ( N = 1646) from a pregnancy cohort were genotyped for 503 tag SNPs in 40 genes related to inflammation. Gene-set analyses were stratified by race and were followed by a single SNP analysis within significant gene sets. Results Gene-level associations were found for IL6 and KLRD1 for term small for gestational age ( SGA) among African Americans. LTA/ TNF and TBX21 were associated with PE among European Americans. The strongest association was for PE among European Americans for an upstream regulator of TNF with RR = 1.8 (95% CI 1.1-2.7). Conclusion Although previous studies have suggested null associations, increased tagging and stratification by genetic ancestry suggests important associations between IL6 and term SGA for African Americans, and a TNF regulator and PE among European Americans ( N = 149). [ABSTRACT FROM AUTHOR]

Although epigenetic regulation plays a critical role in embryonic development, few studies have examined the relationship of epigenome-wide methylation with fetal growth. Using the Infinium HumanMethylation450 BeadChip (Illumina, Inc., San Diego, California) in a substudy of 1,046 infants from the Norwegian Mother and Child Cohort Study (MoBa) enrolled between 1999 and 2008, we examined epigenome-wide cord blood DNA methylation in relation to birth weight. In multivariable-adjusted robust linear regression models, we identified differential methylation at 19 cytosine-guanine dinucleotides (CpGs) associated with either decreased (AT-rich interactive domain 5B (MRF1-like) (ARID5B), 2 CpGs) or increased (x-ray repair complementing defective repair in Chinese hamster cells 3 (XRCC3), 4 CpGs) birth weight. ARID5B knockout mice have less adipose tissue and significantly lower weight in the postnatal period. XRCC3 plays a key role in the maintenance of chromosome stability and the repair of DNA damage. Although there are fewer data on the other implicated genes, many of these genes have been shown to have roles in developmental processes. This constitutes the largest and most robust study of birth weight using an epigenome-wide methylation platform and offers potential insights into epigenetic mechanisms of fetal growth. [ABSTRACT FROM AUTHOR]

An earlier version of this article included a number of typesetting mistakes. These were corrected on October 16, 2020. The publisher apologizes for the errors made during production. The symbol "Λn" was incorrectly published as "Γn" in equations 46 and 47. The correct equations are provided in this correction. [ABSTRACT FROM AUTHOR]

Background: Epigenetic modifications, such as DNA methylation,due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear.Objective: We investigated epigenome-wide methylationin cord blood of newborns in relation to maternal smoking during pregnancy.Methods: We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium Human Methylation450Bead Chip (450K).Results: We found differential DNA methylation at epigenome-wide statistical significance(p-value < 1.06 × 10-7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway,which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke.Conclusions: We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure. [ABSTRACT FROM AUTHOR]

The incidence of esophageal adenocarcinoma (EA) has been increasing rapidly, particularly among white males, over the past few decades in the USA. However, the etiology of EA and the striking male predominance is not fully explained by known risk factors. To identify susceptible genes for EA risk, we conducted a pathway-based candidate gene association study on 335 Caucasian EA cases and 319 Caucasian controls. A total of 1330 single-nucleotide polymorphisms (SNPs) selected from 354 genes were analyzed using an Illumina GoldenGate assay. The genotyped common SNPs include missense and exonic SNPs, SNPs within untranslated regions and 2 kb 5′ of the gene, and tagSNPs for genes with little functional information available. Logistic regression adjusted for potential confounders was used to assess the genetic effect of each SNP on EA risk. We also tested gene–gender interactions using the likelihood ratio tests. We found that the genetic variants in the apoptosis pathway were significantly associated with EA risk after correcting for multiple comparisons. SNPs of rs3127075 in Caspase-7 (CASP7) and rs4661636 in Caspase-9 (CASP9) genes that play a critical role in apoptosis were found to be associated with an increased risk of EA. A protective effect of SNP rs572483 in the progesterone receptor (PGR) gene was observed among women carrying the variant G allele [adjusted odds ratio (OR) = 0.19; 95% confidence interval (CI) = 0.08–0.46] but was not observed among men (adjusted OR = 1.38; 95% CI = 0.95–2.00). In conclusion, this study suggests that the genetic variants of CASP7 and CASP9 in the apoptosis pathway may be important predictive markers for EA susceptibility and that PGR in the sex hormone signaling pathway may be associated with the gender differences in EA risk. [ABSTRACT FROM PUBLISHER]

GWAS have emerged as popular tools for identifying genetic variants that are associated with disease risk. Standard analysis of a case-control GWAS involves assessing the association between each individual genotyped SNP and disease risk. However, this approach suffers from limited reproducibility and difficulties in detecting multi-SNP and epistatic effects. As an alternative analytical strategy, we propose grouping SNPs together into SNP sets on the basis of proximity to genomic features such as genes or haplotype blocks, then testing the joint effect of each SNP set. Testing of each SNP set proceeds via the logistic kernel-machine-based test, which is based on a statistical framework that allows for flexible modeling of epistatic and nonlinear SNP effects. This flexibility and the ability to naturally adjust for covariate effects are important features of our test that make it appealing in comparison to individual SNP tests and existing multimarker tests. Using simulated data based on the International HapMap Project, we show that SNP-set testing can have improved power over standard individual-SNP analysis under a wide range of settings. In particular, we find that our approach has higher power than individual-SNP analysis when the median correlation between the disease-susceptibility variant and the genotyped SNPs is moderate to high. When the correlation is low, both individual-SNP analysis and the SNP-set analysis tend to have low power. We apply SNP-set analysis to analyze the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer GWAS discovery-phase data. [ABSTRACT FROM AUTHOR]

An increasing challenge in analysis of microarray data is how to interpret and gain biological insight of profiles of thousands of genes. This article provides a review of statistical methods for analysis of microarray data by incorporating prior biological knowledge using gene sets and biological pathways, which consist of groups of biologically similar genes. We first discuss issues of individual gene analysis. We compare several methods for analysis of gene sets including over-representation anlaysis, gene set enrichment analysis, principal component analysis, global test and kernel machine. We discuss the assumptions of these methods and their pros and cons. We illustrate these methods by application to a type II diabetes data set. [ABSTRACT FROM AUTHOR]

Germline mutation in serine/threonine kinase 11 (STK11, also called LKB1) results in Peutz–Jeghers syndrome, characterized by intestinal hamartomas and increased incidence of epithelial cancers. Although uncommon in most sporadic cancers, inactivating somatic mutations of LKB1 have been reported in primary human lung adenocarcinomas and derivative cell lines. Here we used a somatically activatable mutant Kras-driven model of mouse lung cancer to compare the role of Lkb1 to other tumour suppressors in lung cancer. Although Kras mutation cooperated with loss of p53 or Ink4a/Arf (also known as Cdkn2a) in this system, the strongest cooperation was seen with homozygous inactivation of Lkb1. Lkb1-deficient tumours demonstrated shorter latency, an expanded histological spectrum (adeno-, squamous and large-cell carcinoma) and more frequent metastasis compared to tumours lacking p53 or Ink4a/Arf. Pulmonary tumorigenesis was also accelerated by hemizygous inactivation of Lkb1. Consistent with these findings, inactivation of LKB1 was found in 34% and 19% of 144 analysed human lung adenocarcinomas and squamous cell carcinomas, respectively. Expression profiling in human lung cancer cell lines and mouse lung tumours identified a variety of metastasis-promoting genes, such as NEDD9, VEGFC and CD24, as targets of LKB1 repression in lung cancer. These studies establish LKB1 as a critical barrier to pulmonary tumorigenesis, controlling initiation, differentiation and metastasis. [ABSTRACT FROM AUTHOR]

Collagenase-3 (matrix metalloproteinase 13, MMP-13) was employed as a surrogate marker to compare the characteristics of incisional wound repair after surgery with the free-electron laser at 6.1 µm and the scalpel. Using a transgenic mouse strain with the MMP-13 or the COL1A2 promoter driving luciferase expression, we observed MMP-13 and COL1A2 expression, tensile strength, macrophage infiltration, and wound histology for up to 62 d. The scalpel incisions showed higher tensile strength than free-electron laser wounds from days 10 to 22 postwounding, despite minimal collateral thermal damage. After 45 d healing was similar. Trichrome staining confirmed that the scalpel incisions had more dense collagen deposition than free-electron laser incisions up to 36 d postinjury, but at day 45 they became similar. MMP-13 expression was biphasic, with peak activities at days 15 and 37 after injury, whereas free electron laser wounds showed greater luciferase activity than scalpel wounds. Peak COL1A2 activity preceded the MMP-13 maximum. MMP-13 expression localized predominantly to dermal fibroblasts near the epidermis at day 15, and in the region of the deep dermis, muscle, and fascia at day 37 postwounding. Migrating muscle cells, but not all skeletal muscle cells, also expressed MMP-13. Free-electron laser incisions contained more macrophages than scalpel wounds at days 2 and 7 postinjury, suggesting that free-electron laser irradiation exacerbated the inflammatory response and thereby stimulated MMP-13 expression. These results revealed that MMP-13 was involved in a series of coordinated events during wound healing, not only the long-term remodeling of wound connective tissue, but also skeletal muscle repair. MMP-13 activity in vivo may correlate with the extent of tissue damage. [ABSTRACT FROM AUTHOR]

Cluster-correlated data receives a lot of attention in biomedical and longitudinal studies and it is of interest to assess the generalized dependence between two multivariate variables under the cluster-correlated structure. The Hilbert–Schmidt independence criterion (HSIC) is a powerful kernel-based test statistic that captures various dependence between two random vectors and can be applied to an arbitrary non-Euclidean domain. However, the existing HSIC is not directly applicable to cluster-correlated data. Therefore, we propose a HSIC-based test of independence for cluster-correlated data. The new test statistic combines kernel information so that the dependence structure in each cluster is fully considered and exhibits good performance under high dimensions. Moreover, a rapid p value approximation makes the new test fast applicable to large datasets. Numerical studies show that the new approach performs well in both synthetic and real world data. [ABSTRACT FROM AUTHOR]

Background: Half of all postmenopausal women report symptoms of vulvar, vaginal, or urinary discomfort with substantial impact on sexual function and quality of life; underlying mechanisms leading to symptoms are poorly understood.Objective: To examine the possibility that the vaginal microbiota and/or mucosal immune response contributes to the severity of bothersome vaginal symptoms, we conducted a substudy of samples from a randomized trial of vaginal treatment for genitourinary syndrome of menopause to compare these features between women whose symptoms improved and women whose symptoms did not improve.Study Design: This is a secondary analysis of samples collected in a 12-week randomized trial of treatment with vaginal estradiol or moisturizer vs placebo for moderate-severe postmenopausal symptoms of vaginal discomfort. We randomly selected 20 women in each arm with ≥2-point decrease in most bothersome symptom severity (responders) and 20 matched controls with ≤1-point decrease (nonresponders). At 0, 4, and 12 weeks, we characterized vaginal microbiota (16S ribosomal RNA gene sequencing), vaginal fluid metabolites (broad-based metabolomic profiling), vaginal fluid-soluble immune markers (Meso Scale Discovery), pH, and vaginal maturation index. We compared responders with nonresponders at baseline and across all visits using linear mixed models to evaluate associations with microbiota, metabolites, and immune markers, incorporating visit and participant-specific random effects while controlling for treatment arm.Results: Here, the mean age of women was 61 years (n=120), and most women (92%) were White. At enrollment, no significant differences were observed between responders and nonresponders in age, most bothersome symptom type or severity, microbiota composition or diversity, Lactobacillus dominance, metabolome, or immune markers. There was a significant decrease in diversity of the vaginal microbiota in both responders and nonresponders (P<.001) over 12 weeks. Although this change did not differ by responder status, diversity was associated with treatment arm: more women in the estradiol arm (63%) had Lactobacillus-dominant, lower diversity bacterial communities than women in the moisturizer (35%) or dual placebo (23%) arms (P=.001) at 12 weeks. The metabolome, vaginal maturation index, and measured immune markers were not associated with responder status over the 12 weeks but varied by treatment arm.Conclusion: Postmenopausal vaginal symptom severity was not significantly associated with vaginal microbiota or mucosal inflammatory markers in this small study. Women receiving vaginal estradiol experienced greater abundance of lactobacilli and lower vaginal pH at end of treatment. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Motivation Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripley's K or Besag's L , to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. Results We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus P -value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to ovarian and lung cancer studies. Availability and implementation An R package and tutorial are provided at https://github.com/sarahsamorodnitsky/SPOT. [ABSTRACT FROM AUTHOR]

Motivation T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed. Results In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conducts rarefying within each bin for alpha diversity calculations, and performs meta-analysis across bins. Extensive simulations using real-world data highlight the inadequacy of the overall rarefying approach in controlling the confounding effect of library size. Our method proves robust in addressing library size confounding, outperforming competing normalization strategies by achieving better-controlled type-I error rates and enhanced statistical power in association tests. Availability and implementation The code is available at https://github.com/mli171/MultibinAlpha. The datasets are freely available at https://doi.org/10.21417/B7001Z and https://doi.org/10.21417/AR2019NC. [ABSTRACT FROM AUTHOR]

Motivation Cancer is a highly heterogeneous disease, and virtually all types of cancer have subtypes. Understanding the association between cancer subtypes and genetic variations is fundamental to the development of targeted therapies for patients. Somatic mutation plays important roles in tumor development and has emerged as a new type of genetic variations for studying the association with cancer subtypes. However, the low prevalence of individual mutations poses a tremendous challenge to the related statistical analysis. Results In this article, we propose an approach, subtype analysis with somatic mutations (SASOM), for the association analysis of cancer subtypes with somatic mutations. Our approach tests the association between a set of somatic mutations (from a genetic pathway) and subtypes, while incorporating functional information of the mutations into the analysis. We further propose a robust p -value combination procedure, DAPC, to synthesize statistical significance from different sources. Simulation studies show that the proposed approach has correct type I error and tends to be more powerful than possible alternative methods. In a real data application, we examine the somatic mutations from a cutaneous melanoma dataset, and identify a genetic pathway that is associated with immune-related subtypes. Availability and implementation The SASOM R package is available at https://github.com/rksyouyou/SASOM-pkg. R scripts and data are available at https://github.com/rksyouyou/SASOM-analysis. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

A recently introduced NURBS mesh generation method for complex-geometry Isogeometric Analysis (IGA) is applied to building a high-quality mesh for a gas turbine. The compressible flow in the turbine is computed using the IGA and a stabilized method with improved discontinuity-capturing, weakly-enforced no-slip boundary-condition, and sliding-interface operators. The IGA results are compared with the results from the stabilized finite element simulation to reveal superior performance of the NURBS-based approach. Free-vibration analysis of the turbine rotor using the structural mechanics NURBS mesh is also carried out and shows that the NURBS mesh generation method can be used also in structural mechanics analysis. With the flow field from the NURBS-based turbine flow simulation, the Courant number is computed based on the NURBS mesh local length scale in the flow direction to show some of the other positive features of the mesh generation framework. The work presented further advances the IGA as a fully-integrated and robust design-to-analysis framework, and the IGA-based complex-geometry flow computation with moving boundaries and interfaces represents the first of its kind for compressible flows. [ABSTRACT FROM AUTHOR]

Objective Maternal smoking is associated with as much as a 50% reduced risk of preeclampsia, despite increasing risk of other poor pregnancy outcomes that often co-occur with preeclampsia, such as preterm birth and fetal growth restriction. Researchers have long sought to understand whether this perplexing association is biologically based, or a result of noncausal mechanisms. We examined whether smoking-response genes modify the smoking-preeclampsia association to investigate potential biological explanations. Study Design We conducted a nested case–control study within the Norwegian Mother, Father and Child Birth Cohort (1999–2008) of 2,596 mother–child dyads. We used family-based log-linear Poisson regression to examine modification of the maternal smoking-preeclampsia relationship by maternal and fetal single nucleotide polymorphisms involved in cellular processes related to components of cigarette smoke (n = 1,915 with minor allele frequency ≥10%). We further investigated the influence of smoking cessation during pregnancy. Results Three polymorphisms showed overall (p < 0.001) multiplicative interaction between smoking and maternal genotype. For rs3765692 (TP73) and rs10770343 (PIK3C2G), protection associated with smoking was reduced with two maternal copies of the risk allele and was stronger in continuers than quitters (interaction p = 0.02 for both loci, based on testing 3-level smoking by 3-level genotype). For rs2278361 (APAF1) the inverse smoking-preeclampsia association was eliminated by the presence of a single risk allele, and again the trend was stronger in continuers than in quitters (interaction p = 0.01). Conclusion Evidence for gene–smoking interaction was limited, but differences by smoking cessation warrant further investigation. We demonstrate the potential utility of expanded dyad methods and gene–environment interaction analyses for outcomes with complex relationships between maternal and fetal genotypes and exposures. Key Points Maternal and fetal genotype may differentially influence preeclampsia. Smoking-related genes did not strongly modify smoking–preeclampsia association. Smoking cessation reduced strength of gene by smoking interactions. [ABSTRACT FROM AUTHOR]

Intratumoral microbes may have multifunctional roles in carcinogenesis. Microsatellite instability (MSI) is associated with higher tumor immunity and mutational burden. Using whole transcriptome and whole genome sequencing microbial abundance data, we investigated associations of intratumoral microbes with MSI, survival, and MSI-relevant tumor molecular characteristics across multiple cancer types including colorectal cancer (CRC), stomach adenocarcinoma, and endometrial carcinoma. Among 451 CRC patients, our key finding was strong associations of multiple CRC-associated genera, including Dialister and Casatella , with MSI. Dialister and Casatella abundance was associated with improved overall survival (hazard ratiomortality = 0.56, 95% confidence interval = 0.34 to 0.92, and hazard ratiomortality = 0.44, 95% confidence interval = 0.27 to 0.72), respectively, comparing higher relative to lower quantiles. Multiple intratumor microbes were associated with immune genes and tumor mutational burden. Diversity of oral cavity–originating microbes was also associated with MSI among CRC and stomach adenocarcinoma patients. Overall, our findings suggest the intratumor microbiota may differ by MSI status and play a role in influencing the tumor microenvironment. [ABSTRACT FROM AUTHOR]

BACKGROUND: Maternal smoking during pregnancy, especially when sustained, leads to numerous adverse health outcomes in offspring. Pregnant women disproportionately underreport smoking and smokers tend to have lower follow-up rates to repeat questionnaires. Missing, incomplete, or inaccurate data on presence and duration of smoking in pregnancy impairs identification of novel health effects and limits adjustment for smoking in studies of other pregnancy exposures. An objective biomarker in newborns of maternal smoking during pregnancy would be valuable. OBJECTIVES: We developed a biomarker of sustained maternal smoking in pregnancy using common DNA methylation platforms. Methods: Using a dimension reduction method, we developed and tested a numeric score in newborns to reflect sustained maternal smoking in pregnancy from data on cotinine, a short-term smoking biomarker measured mid-pregnancy, and Illumina450K cord blood DNA methylation from newborns in the Norwegian Mother and Child Cohort Study (MoBa). RESULTS: This score reliably predicted smoking status in the training set (n = 1,057; accuracy = 96%, sensitivity = 80%, specificity = 98%). Sensitivity (58%) was predictably lower in the much smaller test set (n = 221), but accuracy (91%) and specificity (97%) remained high. Reduced birth weight, a well-known effect of maternal smoking, was as strongly related to the score as to cotinine. A three-site score had lower, but acceptable, performance (accuracytrain= 82%, accuracytest = 83%). CONCLUSIONS: Our smoking methylation score represents a promising novel biomarker of sustained maternal smoking during pregnancy easily calculated with Illumina450K or IlluminaEPIC data. It may help identify novel health impacts and improve adjustment for smoking when studying other risk factors with more subtle effects. CITATION: Reese SE, Zhao S, Wu MC, Joubert BR, Parr CL, Håberg SE, Ueland PM, Nilsen RM, Midttun Ø, Vollset SE, Peddada SD, Nystad W, London SJ. 2017. DNA methylation score as a biomarker in newborns for sustained maternal smoking during pregnancy. Environ Health Perspect 125:760-766; http://dx.doi.org/10.1289/EHP333 [ABSTRACT FROM AUTHOR]

Background: Microbial communities are known to be closely related to many diseases, such as obesity and HIV, and it is of interest to identify differentially abundant microbial species between two or more environments. Since the abundances or counts of microbial species usually have different scales and suffer from zero-inflation or over-dispersion, normalization is a critical step before conducting differential abundance analysis. Several normalization approaches have been proposed, but it is difficult to optimize the characterization of the true relationship between taxa and interesting outcomes. Results: To avoid the challenge of picking an optimal normalization and accommodate the advantages of several normalization strategies, we propose an omnibus approach. Our approach is based on a Cauchy combination test, which is flexible and powerful by aggregating individual p values. We also consider a truncated test statistic to prevent substantial power loss. We experiment with a basic linear regression model as well as recently proposed powerful association tests for microbiome data and compare the performance of the omnibus approach with individual normalization approaches. Experimental results show that, regardless of simulation settings, the new approach exhibits power that is close to the best normalization strategy, while controling the type I error well. Conclusions: The proposed omnibus test releases researchers from choosing among various normalization methods and it is an aggregated method that provides the powerful result to the underlying optimal normalization, which requires tedious trial and error. While the power may not exceed the best normalization, it is always much better than using a poor choice of normalization. [ABSTRACT FROM AUTHOR]

We consider in this article testing rare variants by environment interactions in sequencing association studies. Current methods for studying the association of rare variants with traits cannot be readily applied for testing for rare variants by environment interactions, as these methods do not effectively control for the main effects of rare variants, leading to unstable results and/or inflated Type 1 error rates. We will first analytically study the bias of the use of conventional burdenbased tests for rare variants by environment interactions, and show the tests can often be invalid and result in inflated Type 1 error rates. To overcome these difficulties, we develop the interaction sequence kernel association test (iSKAT) for assessing rare variants by environment interactions. The proposed test iSKAT is optimal in a class of variance component tests and is powerful and robust to the proportion of variants in a gene that interact with environment and the signs of the effects. This test properly controls for the main effects of the rare variants using weighted ridge regression while adjusting for covariates. We demonstrate the performance of iSKAT using simulation studies and illustrate its application by analysis of a candidate gene sequencing study of plasma adiponectin levels. [ABSTRACT FROM AUTHOR]

Background: T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed. Methods: We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined. Results: Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients. Conclusion: The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes. [ABSTRACT FROM AUTHOR]

Moyamoya disease (MMD) is characterized by narrowing of the distal internal carotid artery and the circle of Willis (CoW) and leads to recurring ischemic and hemorrhagic stroke. A retrospective review of data from 50 pediatric MMD patients revealed that among the 24 who had a unilateral stroke and were surgically treated, 11 (45.8%) had a subsequent, contralateral stroke. There is no reliable way to predict these events. After a pilot study in Acta−/− mice that have features of MMD, we hypothesized that local hemodynamics are predictive of contralateral strokes and sought to develop a patient-specific analysis framework to noninvasively assess this stroke risk. A pediatric MMD patient with an occlusion in the right middle cerebral artery and a right-sided stroke, who was surgically treated and then had a contralateral stroke, was selected for analysis. By using an unsteady Navier–Stokes solver within an isogeometric analysis framework, blood flow was simulated in the CoW model reconstructed from the patient's postoperative imaging data, and the results were compared with those from an age- and sex-matched control subject. A wall shear rate (WSR) > 60,000 s−1 (about 12 × higher than the coagulation threshold of 5000 s−1 and 9 × higher than control) was measured in the terminal left supraclinoid artery; its location coincided with that of the subsequent postsurgical left-sided stroke. A parametric study of disease progression revealed a strong correlation between the degree of vascular morphology altered by MMD and local hemodynamic environment. The results suggest that an occlusion in the CoW could lead to excessive contralateral WSRs, resulting in thromboembolic ischemic events, and that WSR could be a predictor of future stroke. [ABSTRACT FROM AUTHOR]

Histone H3 lysine 4 methylation (H3K4me) is extensively regulated by numerous writer and eraser enzymes in mammals. Nine H3K4me enzymes are associated with neurodevelopmental disorders to date, indicating their important roles in the brain. However, interplay among H3K4me enzymes during brain development remains largely unknown. Here, we show functional interactions of a writer-eraser duo, KMT2A and KDM5C, which are responsible for Wiedemann-Steiner Syndrome (WDSTS), and mental retardation X-linked syndromic Claes-Jensen type (MRXSCJ), respectively. Despite opposite enzymatic activities, the two mouse models deficient for either Kmt2a or Kdm5c shared reduced dendritic spines and increased aggression. Double mutation of Kmt2a and Kdm5c clearly reversed dendritic morphology, key behavioral traits including aggression, and partially corrected altered transcriptomes and H3K4me landscapes. Thus, our study uncovers common yet mutually suppressive aspects of the WDSTS and MRXSCJ models and provides a proof of principle for balancing a single writer-eraser pair to ameliorate their associated disorders. Vallianatos et al. study the functional interactions of KMT2A and KDM5C, H3K4me enzymes known to be involved in neurodevelopmental disorders. Using genetic mouse models, neuronal structure analysis, neurobehavior, and epigenomic profiling, they demonstrate a mutually suppressive relationship between KMT2A and KDM5C during neurodevelopment. [ABSTRACT FROM AUTHOR]

Background: Preeclampsia is thought to originate during placentation, with incomplete remodelling and perfusion of the spiral arteries leading to reduced placental vascular capacity. Nitric oxide (NO) and carbon monoxide (CO) are powerful vasodilators that play a role in the placental vascular system. Although family clustering of preeclampsia has been observed, the existing genetic literature is limited by a failure to consider both mother and child.Methods: We conducted a nested case-control study within the Norwegian Mother and Child Birth Cohort of 1545 case-pairs and 995 control-pairs from 2540 validated dyads (2011 complete pairs, 529 missing mother or child genotype). We selected 1518 single-nucleotide polymorphisms (SNPs) with minor allele frequency >5% in NO and CO signalling pathways. We used log-linear Poisson regression models and likelihood ratio tests to assess maternal and child effects.Results: One SNP met criteria for a false discovery rate Q-value <0.05. The child variant, rs12547243 in adenylate cyclase 8 (ADCY8), was associated with an increased risk (relative risk [RR] 1.42, 95% confidence interval [CI] 1.20, 1.69 for AG vs. GG, RR 2.14, 95% CI 1.47, 3.11 for AA vs. GG, Q = 0.03). The maternal variant, rs30593 in PDE1C was associated with a decreased risk for the subtype of preeclampsia accompanied by early delivery (RR 0.45, 95% CI 0.27, 0.75 for TC vs. CC; Q = 0.02). None of the associations were replicated after correction for multiple testing.Conclusions: This study uses a novel approach to disentangle maternal and child genotypic effects of NO and CO signalling genes on preeclampsia. [ABSTRACT FROM AUTHOR]

Background. Graft-versus-host disease (GVHD) is common after allogeneic hematopoietic cell transplantation (HCT). Risk for death from GVHD has been associated with low bacterial diversity in the stool microbiota early after transplant; however, the specific species associated with GVHD risk remain poorly defined. Methods. We prospectively collected serial weekly stool samples from 66 patients who underwent HCT, starting pre-transplantation and continuing weekly until 100 days post-transplant, a total of 694 observations in HCT recipients. We used 16S rRNA gene polymerase chain reaction with degenerate primers, followed by high-throughput sequencing to assess the relative abundance of sequence reads from bacterial taxa in stool samples over time. Results. The gut microbiota was highly dynamic in HCT recipients, with loss and appearance of taxa common on short time scales. As in prior studies, GVHD was associated with lower alpha diversity of the stool microbiota. At neutrophil recovery post-HCT, the presence of oral Actinobacteria and oral Firmicutes in stool was positively correlated with subsequent GVHD; Lachnospiraceae were negatively correlated. A gradient of bacterial species (difference of the sum of the relative abundance of positive correlates minus the sum of the relative abundance of negative correlates) was most predictive (receiver operator characteristic area under the curve of 0.83) of subsequent severe acute GVHD. Conclusions. The stool microbiota around the time of neutrophil recovery post-HCT is predictive of subsequent development of severe acute GVHD in this study. [ABSTRACT FROM AUTHOR]

To fully understand the role of microbiome in human health and diseases, researchers are increasingly interested in assessing the relationship between microbiome composition and host genomic data. The dimensionality of the data as well as complex relationships between microbiota and host genomics pose considerable challenges for analysis. In this article, we apply a kernel RV coefficient (KRV) test to evaluate the overall association between host gene expression and microbiome composition. The KRV statistic can capture nonlinear correlations and complex relationships among the individual data types and between gene expression and microbiome composition through measuring general dependency. Testing proceeds via a similar route as existing tests of the generalized RV coefficients and allows for rapid p-value calculation. Strategies to allow adjustment for confounding effects, which is crucial for avoiding misleading results, and to alleviate the problem of selecting the most favorable kernel are considered. Simulation studies show that KRV is useful in testing statistical independence with finite samples given the kernels are appropriately chosen, and can powerfully identify existing associations between microbiome composition and host genomic data while protecting type I error. We apply the KRV to a microbiome study examining the relationship between host transcriptome and microbiome composition within the context of inflammatory bowel disease and are able to derive new biological insights and provide formal inference on prior qualitative observations. [ABSTRACT FROM AUTHOR]

Many genetic association studies collect a wide range of complex traits. As these traits may be correlated and share a common genetic mechanism, joint analysis can be statistically more powerful and biologically more meaningful. However, most existing tests for multiple traits cannot be used for high-dimensional and possibly structured traits, such as network-structured transcriptomic pathway expressions. To overcome potential limitations, in this article we propose the dual kernel-based association test (DKAT) for testing the association between multiple traits and multiple genetic variants, both common and rare. In DKAT, two individual kernels are used to describe the phenotypic and genotypic similarity, respectively, between pairwise subjects. Using kernels allows for capturing structure while accommodating dimensionality. Then, the association between traits and genetic variants is summarized by a coefficient which measures the association between two kernel matrices. Finally, DKAT evaluates the hypothesis of nonassociation with an analytical P-value calculation without any computationally expensive resampling procedures. By collapsing information in both traits and genetic variants using kernels, the proposed DKAT is shown to have a correct type-I error rate and higher power than other existing methods in both simulation studies and application to a study of genetic regulation of pathway gene expressions. [ABSTRACT FROM AUTHOR]

Evaluating a novel treatment in a randomized controlled trial requires comparison against existing therapies. If several existing therapies of similar benefit exist, the identification of a single control regimen may be difficult. For this situation, we propose a reverse selection design which, in its simplest form, includes a single experimental treatment arm and two control arms. Rather than carrying both control arms through the entire trial, the control arms are compared at an early interim analysis, ideally while accrual is ongoing. At this time, the worst-performing control arm is dropped and randomization continues to the remaining arms. At the end of the study, we compare the treatment to the remaining control arm. When no head-to-head comparison of the extant therapies is available or feasible, this design requires a smaller sample size than a traditional three-arm design or two sequential trials in which the extant therapies are compared and the better treatment is used in a subsequent trial as the control arm. This is because the final comparison is only between two arms and because the early interim analysis occurs prior to the end of accrual - yet with enough information such that any substantially better control arm will be selected. We evaluate the operating characteristics of a reverse selection design via simulation and show that it reduces the required sample size needed to compare the treatment against the best control, controls type I error, and likely selects the right control arm to use in the final analysis.

PHF21A is a histone-binding protein that recognizes unmethylated histone H3K4, the reaction product of LSD1 histone demethylase. PHF21A and LSD1 form a complex, and both undergo neuron-specific microexon splicing. The PHF21A neuronal microexon interferes with nucleosome binding, whereas the LSD1 neuronal microexon weakens H3K4 demethylation activity and can alter the substrate specificity to H3K9 or H4K20. However, the temporal expression patterns of PHF21A and LSD1 splicing isoforms during brain development and their biological roles remain unknown. In this work, we report that neuronal PHF21A isoform expression precedes neuronal LSD1 expression during human neuron differentiation and mouse brain development. The asynchronous splicing events resulted in stepwise deactivation of the LSD1-PHF21A complex in reversing H3K4 methylation. An unbiased proteomics survey revealed that the enzymatically inactive LSD1-PHF21A complex interacts with neuron-specific binding partners, including MYT1-family transcription factors and post-transcriptional mRNA processing proteins such as VIRMA. The interaction with the neuron-specific components, however, did not require the PHF21A microexon, indicating that the neuronal proteomic milieu, rather than the microexon-encoded PHF21A segment, is responsible for neuron-specific complex formation. Finally, by using two Phf21a mutant mouse models, we found that Phf21a neuronal splicing prevents excess synapse formation that otherwise would occur when canonical PHF21A is expressed in neurons. These results suggest that the role of the PHF21A microexon is to dampen LSD1-mediated H3K4 demethylation, thereby containing aberrant synaptogenesis., Competing Interests: Conflict of interest M. C. W. is the CEO of Neurodigitech, LLC. The other authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is a rare neurodevelopmental disorder caused by a mutation in the X-linked CDKL5 gene. CDKL5 is a serine/threonine kinase that is critical for axon outgrowth and dendritic morphogenesis as well as synapse formation, maturation, and maintenance. This disorder is characterized by early-onset epilepsy, hypotonia, and failure to reach cognitive and motor developmental milestones. Because the disease is monogenic, delivery of the CDKL5 gene to the brain of patients should provide clinical benefit. To this end, we designed a gene therapy vector, adeno-associated virus (AAV)9.Syn.hCDKL5, in which human CDKL5 gene expression is driven by the synapsin promoter. In biodistribution studies conducted in mice, intracerebroventricular (i.c.v.) injection resulted in broader, more optimal biodistribution than did intra-cisterna magna (i.c.m.) delivery. AAV9.Syn.hCDKL5 treatment increased phosphorylation of EB2, a bona fide CDKL5 substrate, demonstrating biological activity in vivo. Our data provide proof of concept that i.c.v. delivery of AAV9.Syn.hCDKL5 to neonatal male Cdkl5 knockout mice reduces pathology and reduces aberrant behavior. Functional improvements were seen at doses of 3e11 to 5e11 vector genomes/g brain, which resulted in transfection of ≥50% of the neurons. Functional improvements were not seen at lower doses, suggesting a requirement for broad distribution for efficacy., Competing Interests: Declaration of interests G.V., J.N., J.G., J.S., P.L., M.P., S.D., L.C., Y.V., M.J.K., L.P., E.F., S.S., B.R., P.Y., C.S., J.P., K.S., S.J., J.L., A.M., E.M.W., Z.W., and M.W. are or were at the time the work employees of PTC Therapeutics. M.C.W. is the President and CEO of NeuroDigiTech and was paid by PTC Therapeutics for this work., (Copyright © 2024 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)

Multiplexed spatial proteomics reveals the spatial organization of cells in tumors, which is associated with important clinical outcomes such as survival and treatment response. This spatial organization is often summarized using spatial summary statistics, including Ripley's K and Besag's L. However, if multiple regions of the same tumor are imaged, it is unclear how to synthesize the relationship with a single patient-level endpoint. We evaluate extant approaches for accommodating multiple images within the context of associating summary statistics with outcomes. First, we consider averaging-based approaches wherein multiple summaries for a single sample are combined in a weighted mean. We then propose a novel class of ensemble testing approaches in which we simulate random weights used to aggregate summaries, test for an association with outcomes, and combine the $P$-values. We systematically evaluate the performance of these approaches via simulation and application to data from non-small cell lung cancer, colorectal cancer, and triple negative breast cancer. We find that the optimal strategy varies, but a simple weighted average of the summary statistics based on the number of cells in each image often offers the highest power and controls type I error effectively. When the size of the imaged regions varies, incorporating this variation into the weighted aggregation may yield additional power in cases where the varying size is informative. Ensemble testing (but not resampling) offered high power and type I error control across conditions in our simulated data sets., (© The Author(s) 2024. Published by Oxford University Press.)

Introduction: Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, that is, by next-generation sequencing (NGS), is needed to identify potential targets. Lung Cancer Master Protocol Southwest Oncology Group S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic sub-studies., Methods: Tumors underwent NGS using Foundation Medicine's FoundationOne research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually exclusive gene set analysis and Selected Events Linked by Evolutionary Conditions across Human Tumors were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to assess associations between genetic variants and survival., Results: NGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. Mutually exclusive gene set analysis identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate of less than 15%: NFE2L2, KEAP1, and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R), and 3509C>T (T1170I). When taken together, NFE2L2 and KEAP1 alterations were associated with poorer survival., Conclusions: As the largest dataset to date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance., Competing Interests: Disclosure Dr. Kozono discloses consulting for Vertex and Roche/Genentech and honoraria from RefleXion outside the submitted work. Dr. Tolba discloses employment at Foundation Medicine. Dr. Waqar discloses holding positions on scientific advisory boards for AstraZeneca and Gilead Sciences. Dr. Dragnev discloses receiving institutional research funding from Daiichi Sankyo, Eli Lilly, G1 Therapeutics, Merck, Molecular Templates, Novartis, Roche/Genentech. Dr. Cheng discloses receiving honoraria from AstraZeneca, Janssen, G1 Therapeutics, and research grants from AstraZeneca, and Genentech. Dr. Hirsch discloses holding positions on scientific advisory boards for BMS, AstraZeneca, Daiichi Sankyo, Sanofi, Novartis, AbbVie, Novocure, NextCure, Merus, G1 Therapeutics, Regeneron, none related to this work, and holding patent for EGFR protein and gene copy number as predictive biomarkers for EGFR-directed therapies (through University of Colorado), no royalties. Dr. Mack discloses being a consultant for Amgen, Guardant Health, and Vivance Therapeutics, and receiving honoraria from AbbVie (educational lecture). Dr. Gray discloses being a consultant for AbbVie, AstraZeneca, Blueprint Medicines, Daiichi Sankyo, EMD Serono – Merck, Gilead Sciences, IDEOlogy Health, Janssen Scientific Affairs, Jazz Pharmaceuticals, Loxo Oncology, Merck and Company, Novartis, OncoCyte Biotechnology, Spectrum ODAC, Takeda Pharmaceuticals, Triptych Health Partners; research support from AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Genentech, G1 Therapeutics, Ludwig Institute of Cancer Research, Merck and Company, Novartis, Pfizer. Dr. Borghaei discloses receiving research support for clinical trials from BMS, Lilly, Amgen and holding positions on advisory board/consultant for BMS, Lilly, Genentech, Pfizer, Merck, EMD-Serono, Boehringer Ingelheim, Astra Zeneca, Novartis, Genmab, Regeneron, BioNTech, Amgen, Axiom, PharmaMar, Takeda, Mirati, Daiichi Sankyo, Guardant, Natera, Oncocyte, Beigene, iTEO, Jazz, Janssen, Puma, BerGenBio, Bayer, Iobiotech, Grid Therapeutics, holding position on data and safety monitoring board for University of Pennsylvania: CAR T Program, Takeda, Incyte, Novartis, Springworks, holding position on the scientific advisory board for Sonnetbio (stock options), Inspirna (formerly Rgenix, stock options), Nucleai (stock options), and receiving honoraria from Amgen, Pfizer, Daiichi Sankyo, Regeneron, travel support from Amgen, BMS, Merck, Lilly, EMD-Serono, Genentech, Regeneron, Mirati. Dr. Herbst discloses holding positions on the board of directors for Immunocore, Junshi Pharmaceuticals, being consultant for AbbVie Pharmaceuticals, AstraZeneca, Bolt Biotherapeutics, Bristol-Myers Squibb, Candel Therapeutics, Checkpoint Therapeutics, Cybrexa Therapeutics, DynamiCure Biotechnology, eFFECTOR Therapeutics, Eli Lilly and Company, EMD Serono, Genentech, Gilead, HiberCell, I-Mab Biopharma, Immune-Onc Therapeutics, Immunocore, Janssen, Johnson and Johnson, Loxo Oncology, Merck and Company, Mirati Therapeutics, NextCure, Normunity, Novartis, Ocean Biomedical, Oncocyte Corp, Oncternal Therapeutics, Pfizer, Regeneron Pharmaceuticals, Revelar Biotherapeutics, Ribbon Therapeutics, Roche, Sanofi, Seattle Genetics, Xencor, receiving research support from AstraZeneca, Eli Lilly and Company, Genentech/Roche, Merck and Company, and holding leadership roles in American Association for Cancer Research, International Association for the Study of Lung Cancer, Society for Immunotherapy of Cancer, Southwest Oncology Group. Dr. Gandara discloses being a consultant for Adagene (institutional), AstraZeneca (institutional), Guardant Health (institutional), IO Biotech (institutional), Oncocyte (institutional), Oncohost (institutional), Merck (consultant), Roche-Genentech (institutional) and receiving institutional research grants from Amgen, AstraZeneca, Genentech, Merck. The remaining authors declare no conflict of interest., (Copyright © 2024 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Background: The clinical severity of genital HSV-2 infection varies widely among infected persons with some experiencing frequent genital lesions while others are asymptomatic. The viral genital shedding rate is closely associated with and has been established as a surrogate marker of clinical severity., Methods: To assess the relationship between viral genetics and shedding, we assembled a set of 145 persons who had the severity of their genital herpes quantified through determination of their HSV genital shedding rate. An HSV-2 sample from each person was sequenced and biallelic variants among these genomes were identified., Results: We found no association between metrics of genome-wide variation in HSV-2 and shedding rate. A viral genome-wide association study (vGWAS) identified the minor alleles of three individual unlinked variants as significantly associated with higher shedding rate (p<8.4x10-5): C44973T (A512T), a non-synonymous variant in UL22 (glycoprotein H); A74534G, a synonymous variant in UL36 (large tegument protein); and T119283C, an intergenic variant. We also found an association between the total number of minor alleles for the significant variants and shedding rate (p=6.6x10-7)., Conclusions: These results add to a growing body of literature for HSV suggesting a connection between viral genetic variation and clinically important phenotypes of infection., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: American Indian and Alaska Native people in the United States experience high rates of stomach cancer. Helicobacter pylori infection is a significant risk factor for stomach cancer, and H. pylori strains that carry the cagA gene are linked to greater gastrointestinal disease severity. Yet, little is known about H. pylori and cagA infections in American Indian and Alaska Native people, particularly at the tribal level. We assessed the prevalence and risk factors of H. pylori infection and cagA gene carriage in tribal members from the Navajo Nation., Materials and Methods: We conducted a cross-sectional study with adults from the Navajo Nation. Stool samples collected from participants were analyzed with droplet digital PCR for H. pylori 16S ribosomal and cagA virulence genes. Self-administered health and food questionnaires were mailed to participants to collect information on sociodemographic, health, lifestyle, and environmental risk factors for H. pylori infection. Logistic regression assessed the association between risk factors and H. pylori infection and cagA gene carriage., Results: Among 99 adults, the median age was 45 (age range: 18 to 79 years), and 73.7% were female. About 56.6% (95% CI: 46.2-66.5) of participants were infected with H. pylori . Of H. pylori -infected participants, 78.6% (95% CI: 65.6-88.4) were cagA -gene positive. No significant associations of relevant risk factors with H. pylori and cagA -gene positive infections were noted., Conclusions: In a community-based study population, a substantial proportion of adult tribal members had H. pylori and cagA -gene positive infections. Given these high proportions, culturally appropriate prevention strategies and interventions addressing H. pylori infections present an avenue for additional research and stomach cancer prevention in the Navajo Nation., Competing Interests: Conflict of Interest Statement No conflict of interest to declare.

The comparison of biological systems, through the analysis of molecular changes under different conditions, has played a crucial role in the progress of modern biological science. Specifically, differential correlation analysis (DCA) has been employed to determine whether relationships between genomic features differ across conditions or outcomes. Because ascertaining the null distribution of test statistics to capture variations in correlation is challenging, several DCA methods utilize permutation which can loosen parametric (e.g., normality) assumptions. However, permutation is often problematic for DCA due to violating the assumption that samples are exchangeable under the null. Here, we examine the limitations of permutation-based DCA and investigate instances where the permutation-based DCA exhibits poor performance. Experimental results show that the permutation-based DCA often fails to control the type I error under the null hypothesis of equal correlation structures., (© 2023 Wiley Periodicals LLC.)