Exposure to Airborne PM2.5 Water-Soluble Inorganic Ions Induces a Wide Array of Reproductive Toxicity.

Water-soluble inorganic ions (WSIIs, primarily NH4+, SO42-, and NO3-) are major components in ambient PM2.5, but their reproductive toxicity remains largely unknown. An animal study was conducted where parental mice were exposed to PM2.5 WSIIs or clean air during preconception and the gestational period. After delivery, all maternal and offspring mice lived in a clean air environment. We assessed reproductive organs, gestation outcome, birth weight, and growth trajectory of the offspring mice. In parallel, we collected birth weight and placenta transcriptome data from 150 mother-infant pairs from the Rhode Island Child Health Study. We found that PM2.5 WSIIs induced a broad range of adverse reproductive outcomes in mice. PM2.5 NH4+, SO42-, and NO3- exposure reduced ovary weight by 24.22% (p = 0.005), 14.45% (p = 0.048), and 16.64% (p = 0.022) relative to the clean air controls. PM2.5 SO42- exposure reduced the weight of testicle by 5.24% (p = 0.025); further, mice in the PM2.5 SO42- exposure group had 1.81 (p = 0.027) fewer offspring than the control group. PM2.5 NH4+, SO42-, and NO3- exposure all led to lower birth than controls. In mice, 557 placenta genes were perturbed by exposure. Integrative analysis of mouse and human data suggested hypoxia response in placenta as an etiological mechanism underlying PM2.5 WSII exposure's reproductive toxicity.

Short-term and long-term efficacy of accelerated transcranial magnetic stimulation for depression: a systematic review and meta-analysis.

BACKGROUND: In recent years, accelerated transcranial magnetic stimulation (aTMS) has been developed, which has a shortened treatment period. The aim of this study was to evaluate the efficacy and long-term maintenance effects of aTMS in patients with major depressive disorder (MDD). METHODS: We systematically searched online databases for aTMS studies in patients with MDD published before February 2023 and performed a meta-analysis on the extracted data. RESULTS: Four randomized controlled trials (RCTs) and 10 before-and-after controlled studies were included. The findings showed that depression scores significantly decreased following the intervention (SMD = 1.80, 95% CI (1.31, 2.30), p < 0.00001). There was no significant difference in antidepressant effectiveness between aTMS and standard TMS (SMD = -0.67, 95% CI (-1.62, 0.27), p = 0.16). Depression scores at follow-up were lower than those directly after the intervention based on the depression rating scale (SMD = 0.22, 95% CI (0.06, 0.37), p = 0.006), suggesting a potential long-term maintenance effect of aTMS. Subgroup meta-analysis results indicated that different modes of aTMS may have diverse long-term effects. At the end of treatment with the accelerated repetitive transcranial magnetic stimulation (arTMS) mode, depressive symptoms may continue to improve (SMD = 0.29, 95% CI (0.10, 0.49), I2 = 22%, p = 0.003), while the accelerated intermittent theta burst stimulation (aiTBS) mode only maintains posttreatment effects (SMD = 0.01, 95% CI (-0.45, 0.47), I2 = 66%, p = 0.98). CONCLUSIONS: Compared with standard TMS, aTMS can rapidly improve depressive symptoms, but there is no significant difference in efficacy. aTMS may also have long-term maintenance effects, but longer follow-up periods are needed to assess this possibility. TRIAL REGISTRATION: This article is original and not under simultaneous consideration for publication. The study was registered on PROSPERO ( https://www.crd.york.ac.uk/prospero/ ) (number: CRD42023406590).

Polygenic risk score for alcohol drinking behavior improves prediction of inflammatory bowel disease risk.

Epidemiological studies have long recognized risky behaviors as potentially modifiable factors for the onset and flares of inflammatory bowel disease (IBD); yet, the underlying mechanisms are largely unknown. Recently, the genetic susceptibilities to cigarette smoking, alcohol and cannabis use [i.e. substance use (SU)] have been characterized by well-powered genome-wide association studies (GWASs). We aimed to assess the impact of genetic determinants of SU on IBD risk. Using Mount Sinai Crohn's and Colitis Registry (MSCCR) cohort of 1058 IBD cases and 188 healthy controls, we computed the polygenic risk score (PRS) for SU and correlated them with the observed IBD diagnoses, while adjusting for genetic ancestry, PRS for IBD and SU behavior at enrollment. The results were validated in a pediatric cohort with no SU exposure. PRS of alcohol consumption (DrnkWk), smoking cessation and age of smoking initiation, were associated with IBD risk in MSCCR even after adjustment for PRSIBD and actual smoking status. One interquartile range decrease in PRSDrnkWk was significantly associated to higher IBD risk (i.e. inverse association) (with odds ratio = 1.65 and 95% confidence interval: 1.32, 2.06). The association was replicated in a pediatric Crohn's disease cohort. Colocalization analysis identified a locus on chromosome 16 with polymorphisms in IL27, SULT1A2 and SH2B1, which reached genome-wide statistical significance in GWAS (P < 7.7e-9) for both alcohol consumption and IBD risk. This study demonstrated that the genetic predisposition to SU was associated with IBD risk, independent of PRSIBD and in the absence of SU behaviors. Our study may help further stratify individuals at risk of IBD.

Microscopic Cascading Devices for Boosting Mucus Penetration in Oral Drug Delivery-Micromotors Nesting Inside Microcontainers.

In the case of macromolecules and poorly permeable drugs, oral drug delivery features low bioavailability and low absorption across the intestinal wall. Intestinal absorption can be improved if the drug formulation could be transported close to the epithelium. To achieve this, a cascade delivery device comprising Magnesium-based Janus micromotors (MMs) nesting inside a microscale containers (MCs) has been conceptualized. The device aims at facilitating targeted drug delivery mediated by MMs that can lodge inside the intestinal mucosa. Loading MMs into MCs can potentially enhance drug absorption through increased proximity and unidirectional release. The MMs will be provided with optimal conditions for ejection into any residual mucus layer that the MCs have not penetrated. MMS confined inside MCs propel faster in the mucus environment as compared to non-confined MMs. Upon contact with a suitable fuel, the MM-loaded MC itself can also move. An in vitro study shows fast release profiles and linear motion properties in porcine intestinal mucus compared to more complex motion in aqueous media. The concept of dual-acting cascade devices holds great potential in applications where proximity to epithelium and deep mucus penetration are needed.

Profiling Microbiota from Multiple Sites in the Respiratory Tract to Identify a Biomarker for PM2.5 Nitrate Exposure-Induced Pulmonary Damages.

The microbiota present in the respiratory tract (RT) responds to environmental stimuli and engages in a continuous interaction with the host immune system to maintain homeostasis. A total of 40 C57BL/6 mice were divided into four groups and exposed to varying concentrations of PM2.5 nitrate aerosol and clean air. After 10 weeks of exposure, assessments were conducted on the lung and airway microbiome, lung functions, and pulmonary inflammation. Additionally, we analyzed data from both mouse and human respiratory tract (RT) microbiomes to identify possible biomarkers for PM2.5 exposure-induced pulmonary damages. On average, 1.5 and 13.5% inter-individual microbiome variations in the lung and airway were explained by exposure, respectively. In the airway, among the 60 bacterial OTUs (operational taxonomic units) > 0.05% proportion, 40 OTUs were significantly affected by PM2.5 exposure (FDR ≤ 10%). Further, the airway microbiome was associated with peak expiratory flow (PEF) (p = 0.003), pulmonary neutrophil counts (p = 0.01), and alveolar 8-OHdG oxidative lesions (p = 0.0078). The Clostridiales order bacteria showed the strongest signals. For example, the o_Clostridiales;f_;g_ OTU was elevated by PM2.5 nitrate exposure (p = 4.98 × 10-5) and negatively correlated with PEF (r = -0.585 and p = 2.4 × 10-4). It was also associated with the higher pulmonary neutrophil count (p = 8.47 × 10-5) and oxidative lesion (p = 7.17 × 10-3). In human data, we confirmed the association of airway Clostridiales order bacteria with PM2.5 exposure and lung function. For the first time, this study characterizes the impact of PM2.5 exposure on the microbiome of multiple sites in the respiratory tract (RT) and its relevance to airflow obstructive diseases. By analyzing data from both humans and mice, we have identified bacteria belonging to the Clostridiales order as a promising biomarker for PM2.5 exposure-induced decline in pulmonary function and inflammation.

Effects of chronic electronic cigarettes exposure in inducing respiratory function decline and pulmonary tissue injury - A direct comparison to combustible cigarettes.

BACKGROUND: Electronic cigarette (e-cig) use is increasing worldwide, especially among young individuals. Spirometry measures airflow obstruction and is the primary tool for diagnosing/monitoring respiratory diseases in clinical settings. This study aims to assess the effects of chronic e-cig exposure on spirometric traits, and directly compare to conventional combustible-cigarette (c-cig). METHODS: We employed an e- and c-cig aerosol generation system that resembled human smoking/vaping scenario. Fifty 6-week old C57BL/6 mice were equally divided into five groups and exposed to clean air (control), e-cig aerosol (low- and high-dose), and c-cig aerosol (low- and high-dose), respectively, for 10 weeks. Afterwards, growth trajectory, spirometry and pulmonary pathology were analyzed. RESULTS: Both e- and c-cig exposure slowed down growth and weight gain. Low dose e-cig exposure (1 h exposure per day) resulted in minimal respiratory function damage. At high dose (2 h exposure per day), e-cig exposure deteriorated 7 spirometry traits but by a smaller magnitude than c-cig exposure. For example, comparing to clean air controls, high dose e- and c-cig exposure increased inspiratory resistance by 24.3% (p = 0.026) and 66.7% (p = 2.6e-5), respectively. Low-dose e-cig exposure increased alveolar macrophage count but did not lead to airway remodeling. In contrast, even low-dose c-cig caused alveoli break down and thickening of the small airway, hallmarks of airway obstructive disease. CONCLUSIONS: We conducted well-controlled animal exposure experiments assessing chronic e-cig exposure's effects on spirometry traits. Further, mechanistic study characterized airway remodeling, alveolar tissue lesion and inflammation induced by e- and c-cig exposure. Our findings provided scientific and public health insights on e-cig's health consequences, especially in adolescent users.

Blood Transcriptomes of SARS-CoV-2-Infected Kidney Transplant Recipients Associated with Immune Insufficiency Proportionate to Severity.

BACKGROUND: Among patients with COVID-19, kidney transplant recipients (KTRs) have poor outcomes compared with non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort. METHODS: We ascertained clinical data by chart review. A single sample of blood was collected for transcriptome analysis. Total RNA was poly-A selected and RNA was sequenced to evaluate transcriptome changes. We also measured cytokines and chemokines of serum samples collected during acute infection. RESULTS: A total of 64 patients with COVID-19 in KTRs were enrolled, including 31 with acute COVID-19 (<4 weeks from diagnosis) and 33 with post-acute COVID-19 (>4 weeks postdiagnosis). In the blood transcriptome of acute cases, we identified genes in positive or negative association with COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways but downregulation of T cell and adaptive immune activation pathways. This finding was independent of lymphocyte count, despite reduced immunosuppressant use in most KTRs. Compared with acute cases, post-acute cases showed "normalization" of these enriched pathways after 4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of immunosuppression. Analysis of the non-KTR cohort with COVID-19 showed significant overlap with KTRs in these functions. Serum inflammatory cytokines followed an opposite trend (i.e., increased with disease severity), indicating that blood lymphocytes are not the primary source. CONCLUSIONS: The blood transcriptome of KTRs affected by COVID-19 shows decreases in T cell and adaptive immune activation pathways during acute disease that, despite reduced immunosuppressant use, associate with severity. These pathways show recovery after acute illness.

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatment response in rectal cancer, but the role of MRI-based DL in evaluating Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation remains unclear. PURPOSE: To develop a DL method based on T2-weighted imaging (T2WI) and clinical factors for noninvasively evaluating KRAS mutation in rectal cancer. STUDY TYPE: Retrospective. SUBJECTS: A total of 376 patients (108 women [28.7%]) with histopathology-confirmed rectal adenocarcinoma and KRAS mutation status. FIELD STRENGTH/SEQUENCE: A 3 T, turbo spin echo T2WI and single-shot echo-planar diffusion-weighted imaging (b = 0, 1000 sec/mm2 ). ASSESSMENT: A clinical model was constructed with clinical factors (age, gender, carcinoembryonic antigen level, and carbohydrate antigen 199 level) and MRI features (tumor length, tumor location, tumor stage, lymph node stage, and extramural vascular invasion), and two DL models based on modified MobileNetV2 architecture were evaluated for diagnosing KRAS mutation based on T2WI alone (image model) or both T2WI and clinical factors (combined model). The clinical usefulness of these models was evaluated through calibration analysis and decision curve analysis (DCA). STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Fisher's exact test, logistic regression analysis, receiver operating characteristic curve (ROC), Delong's test, Hosmer-Lemeshow test, interclass correlation coefficients, and Fleiss kappa coefficients (P < 0.05 was considered statistically significant). RESULTS: All the nine clinical-MRI characteristics were included for clinical model development. The clinical model, image model, and combined model in the testing cohort demonstrated good calibration and achieved areas under the curve (AUCs) of 0.668, 0.765, and 0.841, respectively. The combined model showed improved performance compared to the clinical model and image model in two cohorts. DCA confirmed the higher net benefit of the combined model than the other two models when the threshold probability is between 0.05 and 0.85. DATA CONCLUSION: The proposed combined DL model incorporating T2WI and clinical factors may show good diagnostic performance. Thus, it could potentially serve as a supplementary approach for noninvasively evaluating KRAS mutation in rectal cancer. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Ambient Air Pollutants and Traffic Factors Were Associated with Blood and Urine Biomarkers and Asthma Risk.

The UK Biobank (UKBB) is a large population-based cohort that provides a unique opportunity to study the association between environmental exposure and biomarkers and to identify biomarkers as potential instruments for assessing exposure dose, health damage, and disease risks. On 462 063 participants of European ancestry, we characterized the relationship of 38 disease-relevant biomarkers, asthma diagnosis, ambient pollution, traffic factors, and genetic background. The air pollutant exposure on the UKBB cohort was fairly low (e.g., mean PM2.5 concentration at 10.0 µg/m3). Nevertheless, 30 biomarkers were in association with at least one environmental factor; e.g., C-reactive protein levels were positively associated with NO (padj = 2.99 × 10-4), NO2 (padj = 4.15 × 10-4), and PM2.5 (padj = 1.92 × 10-6) even after multiple testing adjustment. Asthma diagnosis was associated with four pollutants (NO, NO2, PM2.5, and PM10). The largest effect size was observed in PM2.5, where a 5 µg/m3 increment of exposure was associated with a 1.52 increase in asthma diagnosis (p = 4.41 × 10-13). Further, environmental exposure and genetic predisposition influenced biomarker levels and asthma diagnosis in an additive model. The exposure-biomarker associations identified in this study could serve as potential indicators for environmental exposure induced health damages. Our results also shed light on possible mechanisms whereby environmental exposure influences disease-causing biomarkers and in turn increases disease risk.

Understanding the Hidden Complexity of Latin American Population Isolates.

Most population isolates examined to date were founded from a single ancestral population. Consequently, there is limited knowledge about the demographic history of admixed population isolates. Here we investigate genomic diversity of recently admixed population isolates from Costa Rica and Colombia and compare their diversity to a benchmark population isolate, the Finnish. These Latin American isolates originated during the 16th century from admixture between a few hundred European males and Amerindian females, with a limited contribution from African founders. We examine whole-genome sequence data from 449 individuals, ascertained as families to build mutigenerational pedigrees, with a mean sequencing depth of coverage of approximately 36×. We find that Latin American isolates have increased genetic diversity relative to the Finnish. However, there is an increase in the amount of identity by descent (IBD) segments in the Latin American isolates relative to the Finnish. The increase in IBD segments is likely a consequence of a very recent and severe population bottleneck during the founding of the admixed population isolates. Furthermore, the proportion of the genome that falls within a long run of homozygosity (ROH) in Costa Rican and Colombian individuals is significantly greater than that in the Finnish, suggesting more recent consanguinity in the Latin American isolates relative to that seen in the Finnish. Lastly, we find that recent consanguinity increased the number of deleterious variants found in the homozygous state, which is relevant if deleterious variants are recessive. Our study suggests that there is no single genetic signature of a population isolate.

Collagenous Colitis Is Associated With HLA Signature and Shares Genetic Risks With Other Immune-Mediated Diseases.

BACKGROUND & AIMS: Collagenous colitis (CC) is an inflammatory bowel disorder with unknown etiopathogenesis involving HLA-related immune-mediated responses and environmental and genetic risk factors. We carried out an array-based genetic association study in a cohort of patients with CC and investigated the common genetic basis between CC and Crohn's disease (CD), ulcerative colitis (UC), and celiac disease. METHODS: DNA from 804 CC formalin-fixed, paraffin-embedded tissue samples was genotyped with Illumina Immunochip. Matching genotype data on control samples and CD, UC, and celiac disease cases were provided by the respective consortia. A discovery association study followed by meta-analysis with an independent cohort, polygenic risk score calculation, and cross-phenotype analyses were performed. Enrichment of regulatory expression quantitative trait loci among the CC variants was assessed in hemopoietic and intestinal cells. RESULTS: Three HLA alleles (HLA-B∗08:01, HLA-DRB1∗03:01, and HLA-DQB1∗02:01), related to the ancestral haplotype 8.1, were significantly associated with increased CC risk. We also identified an independent protective effect of HLA-DRB1∗04:01 on CC risk. Polygenic risk score quantifying the risk across multiple susceptibility loci was strongly associated with CC risk. An enrichment of expression quantitative trait loci was detected among the CC-susceptibility variants in various cell types. The cross-phenotype analysis identified a complex pattern of polygenic pleiotropy between CC and other immune-mediated diseases. CONCLUSIONS: In this largest genetic study of CC to date with histologically confirmed diagnosis, we strongly implicated the HLA locus and proposed potential non-HLA mechanisms in disease pathogenesis. We also detected a shared genetic risk between CC, celiac disease, CD, and UC, which supports clinical observations of comorbidity.

EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data.

The associations between diseases/traits and copy number variants (CNVs) have not been systematically investigated in genome-wide association studies (GWASs), primarily due to a lack of robust and accurate tools for CNV genotyping. Herein, we propose a novel ensemble learning framework, ensembleCNV, to detect and genotype CNVs using single nucleotide polymorphism (SNP) array data. EnsembleCNV (a) identifies and eliminates batch effects at raw data level; (b) assembles individual CNV calls into CNV regions (CNVRs) from multiple existing callers with complementary strengths by a heuristic algorithm; (c) re-genotypes each CNVR with local likelihood model adjusted by global information across multiple CNVRs; (d) refines CNVR boundaries by local correlation structure in copy number intensities; (e) provides direct CNV genotyping accompanied with confidence score, directly accessible for downstream quality control and association analysis. Benchmarked on two large datasets, ensembleCNV outperformed competing methods and achieved a high call rate (93.3%) and reproducibility (98.6%), while concurrently achieving high sensitivity by capturing 85% of common CNVs documented in the 1000 Genomes Project. Given this CNV call rate and accuracy, which are comparable to SNP genotyping, we suggest ensembleCNV holds significant promise for performing genome-wide CNV association studies and investigating how CNVs predispose to human diseases.

Genetic regulation of the placental transcriptome underlies birth weight and risk of childhood obesity.

GWAS identified variants associated with birth weight (BW), childhood obesity (CO) and childhood BMI (CBMI), and placenta is a critical organ for fetal development and postnatal health. We examined the role of placental transcriptome and eQTLs in mediating the genetic causes for BW, CO and CBMI, and applied integrative analysis (Colocalization and MetaXcan). GWAS loci associated with BW, CO, and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs of adult tissues, only placental eQTLs contribute significantly to both anthropometry outcomes at birth (BW) and childhood phenotypes (CO/CBMI). Eight, six and one transcripts colocalized with BW, CO and CBMI risk loci, respectively. Our study reveals that placental transcription in utero likely plays a key role in determining postnatal body size, and as such may hold new possibilities for therapeutic interventions to prevent childhood obesity.

Genome-wide non-HLA donor-recipient genetic differences influence renal allograft survival via early allograft fibrosis.

Donor-recipient (D-R) differences at human leukocyte antigen (HLA) loci are currently incorporated into organ sharing, allocation and immunosuppression decisions. However, while acute rejection episodes have substantially diminished, progressive histologic damage occurs in allografts and improved long-term survival remains an unrealized goal among kidney recipients. Here we tested the hypothesis that non-HLA dependent, genome-wide D-R genetic differences could contribute to unchecked alloimmunity with histologic and functional consequences, culminating in long-term allograft failure. Genome-wide single nucleotide polymorphism (SNP) array data, excluding the HLA region, was utilized from 385 transplants to study the role of D-R differences upon serial histology and allograft survival. ADMIXTURE analysis was performed to quantitatively estimate ancestry in each D-R pair and PLINK was used to estimate the proportion of genome-shared identity-by-descent (pIBD) between D-R pairs. Subsequently, quantitative measures of recipient ancestry based on non-HLA SNPs was associated with death-censored allograft survival in adjusted Cox models. In D-R pairs of similar ancestry, pIBD was significantly associated with allograft survival independent of HLA mismatches in 224 transplants. Surprisingly, pIBD and recipient ancestry were not associated with clinical or subclinical rejection at any time post-transplant. Significantly, in multivariable analysis, pIBD inversely correlated with vascular intimal fibrosis in 160 biopsies obtained less than one year which in turn was significantly associated with allograft survival. Thus, our novel data show that non-HLA D-R differences associate with early vascular intimal fibrosis and allograft survival.

Non-HLA donor-recipient mismatches in kidney transplantation-A stone left unturned.

In kidney transplantation, short-term allograft survival has improved due to improvements in acute rejection episodes without corresponding improvements in long-term survival. Although current organ allocation algorithms take into account human leukocyte antigen (HLA) matching to reduce antidonor alloimmune responses, it is likely that genomic variation at non-HLA loci (ie, non-HLA donor-recipient [D-R] pair mismatches) play a role in the "non-self" responses and ultimately affect long-term allograft survival. Existing data from both animal models and human studies suggest an association between non-HLA D-R mismatches and kidney allograft outcomes. In this minireview, we examine existing and emerging data and discuss putative mechanisms on the role of non-HLA D-R mismatches on long-term allograft outcomes in kidney transplantation.

Prenatal exposure to ambient air multi-pollutants significantly impairs intrauterine fetal development trajectory.

BACKGROUND: Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. METHODS: During 2015-2018, two cohorts of mother-infant dyads (N = 678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2nd (gestational week 24, [GW24]) and 3rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to air pollutant mixture on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. RESULTS: Prenatal exposure to PM2.5, PM10, SO2 and O3 significantly reduced fetal biometry at GW24, where SO2 had the most potent effect. For every 10 µg/m3 increment increase of daily SO2 exposure during the 1st trimester shortened femur length by 2.20 mm (p = 6.7E-21) translating to 5.3% reduction from the average of the study cohort. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p = 3.5E-5) and 2.1% (p = 2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3rd trimester. CONCLUSIONS: To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

Molecular predictors of prevention of recurrence in HCC with sorafenib as adjuvant treatment and prognostic factors in the phase 3 STORM trial.

OBJECTIVE: Sorafenib is the standard systemic therapy for advanced hepatocellular carcinoma (HCC). Survival benefits of resection/local ablation for early HCC are compromised by 70% 5-year recurrence rates. The phase 3 STORM trial comparing sorafenib with placebo as adjuvant treatment did not achieve its primary endpoint of improving recurrence-free survival (RFS). The biomarker companion study BIOSTORM aims to define (A) predictors of recurrence prevention with sorafenib and (B) prognostic factors with B level of evidence. DESIGN: Tumour tissue from 188 patients randomised to receive sorafenib (83) or placebo (105) in the STORM trial was collected. Analyses included gene expression profiling, targeted exome sequencing (19 known oncodrivers), immunohistochemistry (pERK, pVEGFR2, Ki67), fluorescence in situ hybridisation (VEGFA) and immunome. A gene signature capturing improved RFS in sorafenib-treated patients was generated. All 70 RFS events were recurrences, thus time to recurrence equalled RFS. Predictive and prognostic value was assessed using Cox regression models and interaction test. RESULTS: BIOSTORM recapitulates clinicopathological characteristics of STORM. None of the biomarkers tested (related to angiogenesis and proliferation) or previously proposed gene signatures, or mutations predicted sorafenib benefit or recurrence. A newly generated 146-gene signature identifying 30% of patients captured benefit to sorafenib in terms of RFS (p of interaction=0.04). These sorafenib RFS responders were significantly enriched in CD4+ T, B and cytolytic natural killer cells, and lacked activated adaptive immune components. Hepatocytic pERK (HR=2.41; p=0.012) and microvascular invasion (HR=2.09; p=0.017) were independent prognostic factors. CONCLUSION: In BIOSTORM, only hepatocytic pERK and microvascular invasion predicted poor RFS. No mutation, gene amplification or previously proposed gene signatures predicted sorafenib benefit. A newly generated multigene signature associated with improved RFS on sorafenib warrants further validation. TRIAL REGISTRATION NUMBER: NCT00692770.

MRI radiomics analysis for predicting preoperative synchronous distant metastasis in patients with rectal cancer.

OBJECTIVES: To investigate the value of MRI radiomics based on T2-weighted (T2W) images in predicting preoperative synchronous distant metastasis (SDM) in patients with rectal cancer. METHODS: This retrospective study enrolled 177 patients with histopathology-confirmed rectal adenocarcinoma (123 patients in the training cohort and 54 in the validation cohort). A total of 385 radiomics features were extracted from pretreatment T2W images. Five steps, including univariate statistical tests and a random forest algorithm, were performed to select the best preforming features for predicting SDM. Multivariate logistic regression analysis was conducted to build the clinical and clinical-radiomics combined models in the training cohort. The predictive performance was validated by receiver operating characteristics curve (ROC) analysis and clinical utility implementing a nomogram and decision curve analysis. RESULTS: Fifty-nine patients (33.3%) were confirmed to have SDM. Six radiomics features and four clinical characteristics were selected for predicting SDM. The clinical-radiomics combined model performed better than the clinical model in both the training and validation datasets. A threshold of 0.44 yielded an area under the ROC (AUC) value of 0.827 (95% confidence interval (CI), 0.6963-0.9580), a sensitivity of 72.2%, a specificity of 94.4%, and an accuracy of 87.0% in the validation cohort for the combined model. A clinical-radiomics nomogram and decision curve analysis confirmed the clinical utility of the combined model. CONCLUSIONS: Our proposed clinical-radiomics combined model could be utilized as a noninvasive biomarker for identifying patients at high risk of SDM, which could aid in tailoring treatment strategies. KEY POINTS: • T2WI-based radiomics analysis helps predict synchronous distant metastasis (SDM) of rectal cancer. • The clinical-radiomics combined model could be utilized as a noninvasive biomarker for predicting SDM. • Personalized treatment can be carried out with greater confidence based on the risk stratification for SDM in rectal cancer.

Airway microbiome is associated with respiratory functions and responses to ambient particulate matter exposure.

BACKGROUND: Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure. METHODS: During October 2016-October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data: (1) respiratory functions, (2) airway microbiome from sputum, and (3) PM2.5 (PM of ≤ 2.5 µm in diameter) level in ambient air. We investigated the impact of PM2.5 on airway microbiome as well as the link between airway microbiome and respiratory functions using linear mixed regression models. RESULTS: The respiratory function of our primary interest includes forced vital capacity (FVC) and forced expiratory volume in 1st second (FEV1). FEV1/FVC, an important respiratory function trait and key diagnosis criterion of COPD, was significantly associated with airway bacteria load (p = 0.0038); and FEV1 was associated with airway microbiome profile (p = 0.013). Further, airway microbiome was significantly influenced by PM2.5 exposure (p = 4.48E-11). CONCLUSIONS: To our knowledge, for the first time, we demonstrated the impact of PM2.5 on airway microbiome, and reported the link between airway microbiome and respiratory functions. The results expand our understanding on the scope of PM2.5 exposure's influence on human respiratory system, and point to novel etiological mechanism of PM2.5 exposure induced diseases.