Copper (Cu) is an essential metal involved in neurobiological processes including energy metabolism and neurotransmission, yet dysregulated Cu levels may adversely affect brain health and olfactory performance. Although olfactory dysfunction has primarily been studied in older adults and neurodegenerative disease, adolescence is a critical period of brain maturation during which the olfactory system may be particularly vulnerable. This cross-sectional study examined associations between Cu exposure, olfactory bulb (OB) volume, and olfactory performance in 200 adolescents and young adults (64% female; ages 13-25) from the Public Health Impact of Metals Exposure cohort. Cu concentrations in blood, urine, hair, and saliva were measured using inductively coupled plasma mass spectrometry. T2-weighted magnetic resonance imaging scans estimated left, right, and total OB volumes using a three-stage deep learning pipeline. Olfactory performance was assessed using the Sniffin' Sticks test. Weighted quantile sum regression evaluated associations between a Cu mixture index and OB outcomes, while standard linear regression models assessed individual Cu biomarkers. Models were adjusted for age and sex. A higher Cu index was associated with reduced left (β = -0.72, 95% CI [-1.42, -0.02]), right (β = -0.79, 95% CI [-1.43, -0.15]), and total OB volume (β = -1.55, 95% CI [-2.85, -0.25]), as well as lower odor threshold scores (β = -0.23, 95% CI [-0.42, -0.03]). Individual biomarkers were not independently associated with outcomes. These findings suggest that Cu exposure may adversely affect olfactory neurodevelopment during adolescence and highlight the importance of studying environmental exposures relevant to long-term neurological health.

Background:Post-traumatic stress disorder (PTSD) remains highly prevalent affecting ~23% of World Trade Center (WTC) responders more than two decades after 9/11. While MRI studies have identified neural differences associated with PTSD, these findings have not translated into improved treatment. We introduce a novel multimodal MRI approach, DAta-driven Network Connectivity Estimate (DANCE), integrating structural and functional magnetic resonance imaging (MRI) to better capture PTSD mechanisms and inform biomarkers. Methods:In 96 WTC responders, including 45 with current WTC-related PTSD and 51 without PTSD. We applied graph theory to resting-state functional MRI to identify functional hubs via eigenvector centrality and identified divergence between groups using partial least squares discriminant analysis (PLS-DA). From diffusion MRI, we reconstructed five anatomical tracts (i.e., streamlines) in the temporal lobes. Using DANCE, we quantified the differential distribution of streamlines of the reconstructed tracts connecting the functional hubs. We then tested whether WTC exposure duration moderated associations between PTSD and DANCE indices. Results:Responders with PTSD showed altered centrality in nine functional hubs (AUC=0.75 (0.651-0.847)) including bilateral anterior inferior temporal gyrus, right superior parietal lobule, right anterior parahippocampal gyrus, right anterior/posterior superior temporal gyrus (STG), right caudate nucleus, left amygdala and brainstem. Connectivity differences emerged in four tracts: hippocampus, parahippocampus, inferior and superior temporal gyri (STG). DANCE differed in the inferior fronto-occipital fasciculus (IFOF), medial (IFLmed) and lateral (IFLlat) components of the inferior longitudinal fasciculus and in the middle longitudinal fascicle (MdLF). WTC exposure duration significantly moderated the association between PTSD and DANCE values in the IFLmed, right posterior STG (p= 0.035). Conclusion:Our novel DANCE approach revealed converging functional and anatomical connectivity alterations uniquely associated with PTSD in WTC responders and offers compelling evidence for distinct neurobiological signatures of the disorder. These findings significantly advance our understanding of PTSD pathophysiology and highlight potential biomarkers for diagnosis and targeted intervention.

Paleoneurology reconstructs the evolutionary history of nervous systems through direct observations from the fossil record and comparative data from extant species. Although this approach can provide direct evidence of phylogenetic links among species, it is constrained by the availability and quality of data that can be gleaned from the fossil record. Here, we sought to translate brain component relationships in a sample of extant Carnivora to make inferences about brain structure in fossil species. Using high resolution magnetic resonance imaging on extant canids and felids and 3D laser scanning on fossil Carnivora, spanning some 40 million years of evolution, we derived measurements for select brain components. From these primary data, predictive equations of cortical (gray matter mass, cortical thickness, and gyrification index) and subcortical structures (caudate nucleus, putamen, and external globus pallidus mass) were used to derive estimates for select fossil Carnivora. We found that regression equations based on both extant and simulation samples provided moderate to high predictability of subcortical masses for fossil Carnivora. We also found that using exploratory probabilistic mapping of subcortical structures in extant Carnivora, a reasonable prediction could be made of the 3D subcortical morphospace of fossil endocasts. These results identify allometric departures and establish adult species ranges in brain component size for fossil species. The integrative approach taken in this study may serve as a model to promote further dialog between neurobiologists working on extant Carnivora models and paleoneurologists describing the nervous system of fossils from this understudied group of mammals.

Approximately 23% of the men and women who participated in rescue and recovery efforts at the 9/11 World Trade Center (WTC) site experience persistent, clinically significant post-traumatic stress disorder (PTSD). Recent structural and functional magnetic resonance imaging (MRI) studies demonstrate significant neural differences between WTC responders with and without PTSD. Here, we used brain age, a novel MRI-based data-driven biomarker optimized to detect accelerated structural aging and examined the impact of PTSD on this process. Using BrainAgeNeX, a novel convolutional neural network that bypasses brain parcellation and has been trained and validated on over 11,000 T1-weighted MRI scans, we predicted brain age in WTC responders with PTSD (WTC-PTSD, n = 47) and age/sex matched responders without PTSD (non-PTSD, n = 52). Brain Age Difference (BAD) was then calculated for each WTC responder by subtracting chronological age from brain age. We found that BAD was significantly older in WTC-PTSD compared to non-PTSD responders (BADno_PTSD = -0.43 y; BADWTC_PTSD = 3.07 y; p < 0.001). Further, we found that WTC exposure duration (months working on site) moderates the association between PTSD and BAD (p = 0.005). Our results suggest that brain age is a relevant marker of structural damage in WTC responders with and without PTSD. PTSD may be a risk factor for accelerated aging in trauma-exposed populations.

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). We implemented an interpretable XGBoost-Shapley Additive Explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages: 13-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, cupper, nickel and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford Atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated ( p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

e20510 Background: Mononucleosomal ctDNA (mnctDNA, 157-bp, double-stranded) spearheads liquid biopsy (LB) for cancer detection, treatment and clinical care. The bottleneck of mnctDNA LB are low copy number of ctDNA and limit of detection of platform technologies. Recent discovery of ultra-short ctDNA (usctDNA, 52-54 nt, single-stranded) that harbors somatic mutations prompted us to explore the quantification and stoichiometry of usctDNA to mnctDNA in plasma and saliva of NSCLC patients. Methods: Paired plasma and saliva from 20 advanced NSCLC patients with tissue genotyped positive for L858R were processed for cfDNA extraction and quantification with Qubit and Tape Station. Digital PCR assays targeting L858R somatic mutation to generate amplicons of 57-bp (usctDNA) and 100-bp (mnctDNA) were performed by UCLA and independently by NIST. Results: Results in Table 1 revealed that three findings of usctDNA that will have potential to impact ctDNA liquid biopsy. First, the somatic mutation (L858R) is present in usctDNA. Second, The stoichiometric ratio of usctDNA to mnctDNA is similar in plasma and saliva at 1.6X. For the wild-type counterpart, the ratio is 1.1X for plasma and 0.6X for saliva. Third, the copy number of usctDNA and mnctDNA in saliva to plasma is 7.8X and 7.7X. Conclusions: Detection of tumor-associated/specific EGFR L858R somatic mutations in uscfDNA is translationally impactful, adding 1.6X of the ctDNA targets for molecular detection, effectively cumulating 2.6X of total ctDNA targets, permitting earlier cancer detection, treatment monitoring and therapy prognostication. The finding that saliva harbors 7X of the us- and mnctDNA further raises the prospect of advancing saliva ctDNA liquid biopsy for NSCLC detection as it may effectively allow 15.5X (7.8X+7.7X) ability to detect malignancy-associated ctDNA. [Table: see text]

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdeltasignificantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in volumetricdelta between groups (p=0.041). The reduced ECdelta in the right amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

Background and Aims Chronic stress associates with cardiovascular disease, but mechanisms remain incompletely defined. Advanced imaging was used to identify stress-related neural imaging phenotypes associated with atherosclerosis.Methods Twenty-seven individuals with post-traumatic stress disorder (PTSD), 45 trauma-exposed controls without PTSD, and 22 healthy controls underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI). Atherosclerotic inflammation and burden were assessed using 18F-FDG PET (as maximal target-to-background ratio, TBR max) and MRI, respectively. Inflammation was assessed using high-sensitivity C-reactive protein (hsCRP) and leucopoietic imaging (18F-FDG PET uptake in spleen and bone marrow). Stress-associated neural network activity (SNA) was assessed on 18F-FDG PET as amygdala relative to ventromedial prefrontal cortex (vmPFC) activity. MRI diffusion tensor imaging assessed the axonal integrity (AI) of the uncinate fasciculus (major white matter tract connecting vmPFC and amygdala).Results Median age was 37 years old and 54% of participants were female. There were no significant differences in atherosclerotic inflammation between participants with PTSD and controls; adjusted mean difference in TBR max (95% confidence interval) of the aorta 0.020 (-0.098, 0.138), and of the carotids 0.014 (-0.091, 0.119). Participants with PTSD had higher hsCRP, spleen activity, and aorta atherosclerotic burden (normalized wall index). Participants with PTSD also had higher SNA and lower AI. Across the cohort, carotid atherosclerotic burden (standard deviation of wall thickness) associated positively with SNA and negatively with AI independent of Framingham risk score.Conclusions In this study of limited size, participants with PTSD did not have higher atherosclerotic inflammation than controls. Notably, impaired cortico-limbic interactions (higher amygdala relative to vmPFC activity or disruption of their intercommunication) associated with carotid atherosclerotic burden. Larger studies are needed to refine these findings. Structured Graphical Abstract Multimodal imaging of the brain-heart connection. Individuals with PTSD, individuals exposed to trauma but who did not develop PTSD (trauma controls), and individuals with neither trauma exposure nor a history of psychiatric disorders (healthy controls) were recruited. Participants underwent 18F-FDG PET and MRI (including DTI MRI of the brain) to assess the function and structure of stress-associated neural tissues, leucopoietic organs (bone marrow and spleen), and the arteries. The lower panel proposes a pathway by which neural tissues may potentiate atherosclerosis. A higher metabolic activity in the amygdala relative to the vmPFC (on 18F-FDG PET), which is also linked to a disruption in their interconnection (the uncinate fasciculus) on DTI MRI, was associated with carotid atherosclerotic burden. Heightened systemic inflammation and leucopoiesis may be involved in this brain-heart connection. DTI, diffusion tensor imaging; 18F-FDG PET, 18F-fluorodeoxyglucose positron emission tomography; MRI, magnetic resonance imaging; PTSD, post-traumatic stress disorder; SNA, stress-associated neural network activity; vmPFC, ventromedial prefrontal cortex.

The evolutionary history of canids and felids is marked by a deep time separation that has uniquely shaped their behavior and phenotype toward refined predatory abilities. The caudate nucleus is a subcortical brain structure associated with both motor control and cognitive, emotional, and executive functions. We used a combination of three-dimensional imaging, allometric scaling, and structural analyses to compare the size and shape characteristics of the caudate nucleus. The sample consisted of MRI scan data obtained from six canid species (Canis lupus lupus, Canis latrans, Chrysocyon brachyurus, Lycaon pictus, Vulpes vulpes, Vulpes zerda), two canid subspecies (Canis lupus familiaris, Canis lupus dingo), as well as three felids (Panthera tigris, Panthera uncia, Felis silvestris catus). Results revealed marked conservation in the scaling and shape attributes of the caudate nucleus across species, with only slight deviations. We hypothesize that observed differences in caudate nucleus size and structure for the domestic canids are reflective of enhanced cognitive and emotional pathways that possibly emerged during domestication.

The signal transduction protein, regulator of G protein signaling 4 (RGS4), plays a prominent role in physiologic and pharmacological responses by controlling multiple intracellular pathways. Our earlier work identified the dynamic but distinct roles of RGS4 in the efficacy of monoamine-targeting versus fast-acting antidepressants. Using a modified chronic variable stress (CVS) paradigm in mice, we demonstrate that stress-induced behavioral abnormalities are associated with the downregulation of RGS4 in the medial prefrontal cortex (mPFC). Knockout of RGS4 (RGS4KO) increases susceptibility to CVS, as mutant mice develop behavioral abnormalities as early as 2 weeks after CVS resting-state functional magnetic resonance imaging I (rs-fMRI) experiments indicate that stress susceptibility in RGS4KO mice is associated with changes in connectivity between the mediodorsal thalamus (MD-THL) and the mPFC. Notably, RGS4KO also paradoxically enhances the antidepressant efficacy of ketamine in the CVS paradigm. RNA-sequencing analysis of naive and CVS samples obtained from mPFC reveals that RGS4KO triggers unique gene expression signatures and affects several intracellular pathways associated with human major depressive disorder. Our analysis suggests that ketamine treatment in the RGS4KO group triggers changes in pathways implicated in synaptic activity and responses to stress, including pathways associated with axonal guidance and myelination. Overall, we show that reducing RGS4 activity triggers unique gene expression adaptations that contribute to chronic stress disorders and that RGS4 is a negative modulator of ketamine actions. SIGNIFICANCE STATEMENT: Chronic stress promotes robust maladaptation in the brain, but the exact intracellular pathways contributing to stress vulnerability and mood disorders have not been thoroughly investigated. In this study, the authors used murine models of chronic stress and multiple methodologies to demonstrate the critical role of the signal transduction modulator regulator of G protein signaling 4 in the medial prefrontal cortex in vulnerability to chronic stress and the efficacy of the fast-acting antidepressant ketamine.

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdeltasignificantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in volumetricdelta between groups (p=0.041). The reduced ECdelta in the right amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

World Trade Center (WTC) responders exposed to traumatic and environmental stressors during rescue and recovery efforts have a high prevalence of chronic WTC-related post-traumatic stress disorder (WTC-PTSD). We investigated neural mechanisms underlying WTC-PTSD by applying eigenvector centrality (EC) metrics and data-driven methods on resting state functional magnetic resonance (fMRI). We identified how EC differences relate to WTC-exposure and behavioral symptoms. We found that connectivity differentiated significantly between WTC-PTSD and non-PTSD responders in nine brain regions, as these differences allowed an effective discrimination of PTSD and non-PTSD responders based solely on analysis of resting state data. Further, we found that WTC exposure duration (months on site) moderates the association between PTSD and EC values in two of the nine brain regions; the right anterior parahippocampal gyrus and the left amygdala (p = 0.010; p = 0.005, respectively, adjusted for multiple comparisons). Within WTC-PTSD, a dimensional measure of symptom severity was positively associated with EC values in the right anterior parahippocampal gyrus and brainstem. Functional neuroimaging can provide effective tools to identify neural correlates of diagnostic and dimensional indicators of PTSD.

IntroductionAdolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal–associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross–sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents.MethodsIn 193 participants (53% females, ages: 15–25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting–state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age.ResultsWe observed significant negative associations between the metal mixture and GE and LE [βGE = −0.076, 95% CI (−0.122, −0.031); βLE= −0.051, 95% CI (−0.095, −0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE.DiscussionOur results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal.

Elephants have long been observed to grip objects with their trunk, but little is known about how they adjust their strategy for different weights. In this study, we challenge a female African elephant at Zoo Atlanta to lift 20–60 kg barbell weights with only its trunk. We measure the trunk’s shape and wrinkle geometry from a frozen elephant trunk at the Smithsonian. We observe several strategies employed to accommodate heavier weights, including accelerating less, orienting the trunk vertically, and wrapping the barbell with a greater trunk length. Mathematical models show that increasing barbell weights are associated with constant trunk tensile force and an increasing barbell-wrapping surface area due to the trunk’s wrinkles. Our findings may inspire the design of more adaptable soft robotic grippers that can improve grip using surface morphology such as wrinkles.

Suicide research/clinical work remain in dire need of effective tools that can better predict suicidal behavior. A growing body of literature has started to focus on the role that neuroimaging may play in helping explain the path towards suicide. Specifically, structural alterations of rostral anterior cingulate cortex (rost-ACC) may represent a biological marker and/or indicator of suicide risk in Major Depressive Disorder (MDD). Furthermore, the construct of "grit," defined as perseverance for goal-attainment and shown to be associated with suicidality, is modulated by rost-ACC. The aim was to examine relationships among rost-ACC gray matter volume, grit, and suicidality in U.S. Military Veterans. Participants were age-and-sex-matched Veterans with MDD: with suicide attempt (MDD+SA:n = 23) and without (MDD-SA:n = 37). Groups did not differ in depression symptomatology. Participants underwent diagnostic interview, clinical symptom assessment, and 3T-MRI-scan. A Group (SA-vs. -No-SA) x Cingulate-region (rostral-caudal-posterior) x Hemisphere (left-right) mixed-model-multivariate-ANOVA was conducted. Left-rost-ACC was significantly smaller in MDD+SA, Group x Cingulate-region x Hemisphere -interaction. Lower grit and less left-rost-ACC gray matter each predicted suicide attempt history, but grit level was a more robust predictor of SA. Both structural alterations of rost-ACC and grit level represent potentially valuable tools for suicide risk assessment.

Background:Early-life environmental exposures during critical windows (CWs) of development can impact life course health. Exposure to neuroactive metals such as manganese (Mn) during prenatal and early postnatal CWs may disrupt typical brain development, leading to persistent behavioral changes. Males and females may be differentially vulnerable to Mn, presenting distinctive CWs to Mn exposure. Methods:We used magnetic resonance imaging to investigate sex-specific associations between early-life Mn uptake and intrinsic functional connectivity in adolescence. A total of 71 participants (15-23 years old; 53% female) from the Public Health Impact of Manganese Exposure study completed a resting-state functional magnetic resonance imaging scan. We estimated dentine Mn concentrations at prenatal, postnatal, and early childhood periods using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses to investigate the moderating effect of sex on the associations between Mn and intrinsic functional connectivity adjusting for age and socioeconomic status. Results:We identified significant sex-specific associations between dentine Mn at all time points and intrinsic functional connectivity in brain regions involved in cognitive and motor function: 1) prenatal: dorsal striatum, occipital/frontal lobes, and middle frontal gyrus; 2) postnatal: right putamen and cerebellum; and 3) early childhood: putamen and occipital, frontal, and temporal lobes. Network associations differed depending on exposure timing, suggesting that different brain networks may present distinctive CWs to Mn. Conclusions:These findings suggest that the developing brain is vulnerable to Mn exposure, with effects lasting through late adolescence, and that females and males are not equally vulnerable to these effects. Future studies should investigate cognitive and motor outcomes related to these associations.

e18700 Background: Previous studies on mutation calling have documented capture kit batch effects in Whole Exome Sequencing (WES) data from The Cancer Genome Atlas (TCGA) database, hindering direct comparison between samples from different capture kits. For example, in classification, a cancer type exclusively sampled by a specific capture kit in the training set would have very low accuracy if the testing set was sampled by another capture kit. To enable cross-capture-kit between-cancer genotype analyses with the TCGA dataset, a novel read count transformation algorithm is developed to remove capture kit batch effects. This algorithm was tested with our Machine Learning model which uses Tandem Repeat Sequence (TRS) mutation markers as training features. Methods: The proposed algorithm transforms TRS read count data to remove low quality samples, read depth differences, and capture kit batch effects from the dataset. Results: 1) TRS read count of WES samples are investigated. Particularly, we show that TRS site read counts do not correlate across capture kits but correlate within capture kits. This suggests that WES read count is largely independent from an exon’s location in the genome and is more strongly correlated with capture kit probes. 2) TRS detection rate for each sample within each capture kit is found to be normally distributed. Outliers with very low TRS detection rate can be used for quality filtering. 3) The transformation algorithm effectively removes capture kit batch effects from the dataset. At the same time, it retains cancer-specific signals in the samples. Before applying the transformation algorithm, cancer type classification accuracy is low (̃0-25%) if the testing data set uses a different capture kit from the training data set. We show that applying the transformation algorithm allows cancer type classification accuracy to improve by over 65%. Conclusions: We demonstrated that direct comparison of WES TRS read count data across capture kits is possible after application of our transformation algorithm. This opens the path to cross-capture-kit between-cancer genotype analyses with the TCGA dataset, which were previously unfeasible due to capture kit batch effects.