Cancer-associated fibroblasts undergoing neoadjuvant chemotherapy suppress rectal cancer revealed by single-cell and spatial transcriptomics.

Neoadjuvant chemotherapy (NAC) for rectal cancer (RC) shows promising clinical response. The modulation of the tumor microenvironment (TME) by NAC and its association with therapeutic response remain unclear. Here, we use single-cell RNA sequencing and spatial transcriptome sequencing to examine the cell dynamics in 29 patients with RC, who are sampled pairwise before and after treatment. We construct a high-resolution cellular dynamic landscape remodeled by NAC and their associations with therapeutic response. NAC markedly reshapes the populations of cancer-associated fibroblasts (CAFs), which is strongly associated with therapeutic response. The remodeled CAF subsets regulate the TME through spatial recruitment and crosstalk to activate immunity and suppress tumor progression through multiple cytokines, including CXCL12, SLIT2, and DCN. In contrast, the epithelial-mesenchymal transition of malignant cells is upregulated by CAF_FAP through MIR4435-2HG induction, resulting in worse outcomes. Our study demonstrates that NAC inhibits tumor progression and modulates the TME by remodeling CAFs.

An ultrasensitive method for detecting mutations from short and rare cell-free DNA.

Circulating tumor DNA (ctDNA) was short and rare, making the detection performance of the current targeted sequencing methods unsatisfying. We developed the One-PrimER Amplification (OPERA) system and examined its performance in detecting mutations of low variant allelic frequency (VAF) in various samples with short-sized DNA fragments. In cell line-derived samples containing sonication-sheared DNA fragments with 50-150 bp, OPERA was capable of detecting mutations as low as 0.0025% VAF, while CAPP-Seq only detected mutations of >0.03% VAF. Both single nucleotide variant and insertion/deletion can be detected by OPERA. In synthetic fragments as short as 80 bp with low VAF (0.03%-0.1%), the detection sensitivity of OPERA was significantly higher compared to that of droplet digital polymerase chain reaction. The error rate was 5.9×10-5 errors per base after de-duplication in plasma samples collected from healthy volunteers. By suppressing "single-strand errors", the error rate can be further lowered by >5 folds in EGFR T790M hotspot. In plasma samples collected from lung cancer patients, OPERA detected mutations in 57.1% stage I patients with 100% specificity and achieved a sensitivity of 30.0% in patients with tumor volume of less than 1 cm3. OPERA can effectively detect mutations in rare and highly-fragmented DNA.

Multiple brain regions are involved in reaction to acute restraint stress in CYLD-knockout mice.

The lysine 63 deubiquitinase cylindromatosis (CYLD) is expressed at high levels in the brain and is considered to be involved in anxious and depressive behavior, cognitive inflexibility, and autism disorders. Previous research was limited in some brain regions, including the hippocampus, striatum, and amygdala. To better understand whether CYLD plays a role in adaptation to stress and which brain regions are involved, we analyzed the behavior of CYLD-knockout mice in the elevated plus maze (EPM) and light-dark box test (LDT) after acute restraint stress (ARS) and mapped their c-Fos immunoreactivity in brain sections. Here we report that CYLD deficiency leads to an unexpected reaction to ARS in mice, and is accompanied by significant neuronal activation of brain regions including the medial prefrontal cortex (mPFC), dorsal striatum (DS), nucleus accumbens (NAc), and basal lateral amygdala (BLA), but not ventral hippocampus (vHPC). Our findings show that CYLD participates in ARS-induced anxious behavior and that this involves multiple brain regions.

Is red cell distribution width a prognostic factor in patients with breast cancer? A meta-analysis.

Purpose: The current study aimed to investigate whether red blood cell distribution width (RDW) can predict the prognosis of patients with breast cancer (BC). Methods: We searched four databases, including PubMed, Embase, Cochrane Library databases, and CNKI, from inception to Jun 13, 2022. The primary outcome was overall survival (OS), and the secondary outcome was disease-free survival (DFS). A subgroup analysis was conducted based on different treatments. This meta-analysis was performed with RevMan 5.3 (The Cochrane Collaboration, London, United Kingdom). Results: A total of seven studies including 4,884 BC patients were identified. The high RDW group had a larger tumor size (OR = 2.12, 95% CI = 1.67 to 2.68, P < 0.01), higher proportions of advanced stage tumors (OR = 1.77, 95% CI = 1.38 to 2.27, P < 0.01), more lymph node metastases (OR = 2.00, 95% CI = 1.58 to 2.51, P < 0.01) and lower HER-2 expression (OR = 0.76, 95% CI = 0.61 to 0.95, P = 0.02). For prognosis, after pooling all the data, we found that the high RDW group was associated with worse OS (HR = 2.12, 95% CI = 1.47 to 3.08, P < 0.01) and DFS (HR = 1.77, 95% CI = 1.32 to 2.37, P < 0.01). The subgroup analysis found that RDW had prognostic significance but only for surgery-only patients (HR = 2.41, 95% CI = 1.67 to 3.49, P < 0.01). Conclusion: High RDW was associated with worse OS and DFS. Therefore, RDW was a simple predictive factor for the prognosis of BC patients.

Noninvasive prediction of axillary lymph node status in breast cancer using promoter profiling of circulating cell-free DNA.

BACKGROUND: Lymph node metastasis (LNM) is one of the most important factors affecting the prognosis of breast cancer. The accurate evaluation of lymph node status is useful to predict the outcomes of patients and guide the choice of cancer treatment. However, there is still lack of a low-cost non-invasive method to assess the status of axillary lymph node (ALN). Gene expression signature has been used to assess lymph node metastasis status of breast cancer. In addition, nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of its original tissues, so it may be used to evaluate the axillary lymph node status in breast cancer. METHODS: In this study, we found that the cfDNA nucleosome footprints between the ALN-positive patients and ALN-negative patients showed different patterns by implementing whole-genome sequencing (WGS) to detect 15 ALN-positive and 15 ALN-negative patients. In order to further evaluate its potential for assessing ALN status, we developed a classifier with multiple machine learning models by using 330 WGS data of cfDNA from 162 ALN-positive and 168 ALN-negative samples to distinguish these two types of patients. RESULTS: We found that the promoter profiling between the ALN-positive patients and ALN-negative patients showed distinct patterns. In addition, we observed 1071 genes with differential promoter coverage and their functions were closely related to tumorigenesis. We found that the predictive classifier based on promoter profiling with a support vector machine model, named PPCNM, produced the largest area under the curve of 0.897 (95% confidence interval 0.86-0.93). CONCLUSIONS: These results indicate that promoter profiling can be used to distinguish ALN-positive patients from ALN-negative patients, which may be helpful to guide the choice of cancer treatment.

Uncovering Novel Prognostic Factors of Sudden Sensorineural Hearing Loss by Whole-Genome Sequencing of Cell-Free DNA.

BACKGROUND: Sudden sensorineural hearing loss is a common disease with several etiologic hypotheses, such as infection, vascular occlusion, inflammation, oxidative stress, etc. Studies have reported that the concentration of cell-free DNA in plasma will elevate in these situations. Former studies have reported that the whole-genome sequencing of cell-free DNA has high accuracy and sensitivity in inferring gene expressions. In this study, we plan to use the whole-genome sequencing of cell-free DNA to uncover novel prognostic factors of sudden sensorineural hearing loss and provide new insight into the clinical application of cell-free DNA. METHODS: In this study, 84 sudden sensorineural hearing loss patients (47 in recovery group and 37 in no-recovery group) were enrolled. After whole-genome sequencing of the cell-free DNA, the protein-protein interaction network was constructed using the differentially expressed genes. Multinomial logistics regression analysis was used to analyze the prognostic factors of hearing improvement. RESULTS: In this study, we found distinct patterns of expressed and unexpressed genes in cell-free DNA sequence read depth coverage in sudden sensorineural hearing loss patients. The top centrality hub genes IGF1, NOTCH1, APOE, FAM3C, RPS6KB1, and RELB were identified from the protein-protein interaction network. Multinomial logistics regression analysis demonstrated that the coverage patterns of 3 key differentially expressed genes (NOTCH1, APOE, and RELB) are significantly different in sudden sensorineural hearing loss with and without hearing recovery. CONCLUSION: The cell-free DNA could have more applications in diverse diseases, and the coverage patterns of 3 differentially expressed genes (NOTCH1, APOE, and RELB) are independent prognostic factors of sudden sensorineural hearing loss. Their expression levels may play a critical role in the hearing improvement of sudden sensorineural hearing loss patients.

Brain structural network to investigate the mechanism of cognitive impairment in patients with acoustic neuroma.

Objective: Acoustic neuroma (AN) is a common benign tumor. Little is known of neuropsychological studies in patients with acoustic neuroma, especially cognitive neuropsychology, and the neuropsychological abnormalities of patients affect their life quality. The purpose of this study was to explore the changes in the cognitive function of patients with acoustic neuroma, and the possible mechanism of these changes by structural magnetic resonance imaging. Materials and methods: We used a neuropsychological assessment battery to assess cognitive function in 69 patients with acoustic neuroma and 70 healthy controls. Then, we used diffusion tensor imaging data to construct the structural brain network and calculate topological properties based on graph theory, and we studied the relation between the structural brain network and cognitive function. Moreover, three different subnetworks (short-range subnetwork, middle-range subnetwork, and long-range subnetwork) were constructed by the length of nerve fibers obtained from deterministic tracking. We studied the global and local efficiency of various subnetworks and analyzed the correlation between network metrics and cognitive function. Furthermore, connectome edge analysis directly assessed whether there were differences in the number of fibers in the different brain regions. We analyzed the relation between the differences and cognitive function. Results: Compared with the healthy controls, the general cognitive function, memory, executive function, attention, visual space executive ability, visual perception ability, movement speed, and information processing speed decreased significantly in patients with acoustic neuroma. A unilateral hearing loss due to a left acoustic neuroma had a greater impact on cognitive function. The results showed that changes in the global and local metrics, the efficiency of subnetworks, and cognitively-related fiber connections were associated with cognitive impairments in patients with acoustic neuroma. Conclusion: Patients exhibit cognitive impairments caused by the decline of the structure and function in some brain regions, and they also develop partial compensation after cognitive decline. Cognitive problems are frequent in patients with acoustic neuroma. Including neuropsychological aspects in the routine clinical evaluation and appropriate treatments may enhance the clinical management and improve their life quality.

Mucocele: a rare complication following stapled haemorrhoidopexy.

BACKGROUND: Stapled haemorrhoidopexy (SH) has resulted in a unique collection of procedural complications with postoperative mucocele a particularly rare example. This study is designed to comprehensively describe the characteristics of rectal mucocele and discuss its pathogenesis following SH surgery. METHODS: A database of patients presenting with a rectal mucocele following an SH procedure was established and studied retrospectively. RESULTS: Seven patients (5 males; median age 32 years, range 20-75 years) were identified. All patients complained of variable anal discomfort with 5/7 presenting with inconstant anal pain, 2 with de novo evacuatory difficulty. These cases appeared at a median time of 6 months (range 2-84 months) after SH surgery. CONCLUSION: Rectal Mucocele develops when mucosal fragments become embedded and isolated under the mucosa. It is a preventable complication of SH surgery by ensuring correct purse string placement prior to stapled haemorrhoid excision.

Plasma-Derived Extracellular Vesicles Circular RNAs Serve as Biomarkers for Breast Cancer Diagnosis.

Breast cancer is the second cause of cancer-associated death among women and seriously endangers women's health. Therefore, early identification of breast cancer would be beneficial to women's health. At present, circular RNA (circRNA) not only exists in the extracellular vesicles (EVs) in plasma, but also presents distinct patterns under different physiological and pathological conditions. Therefore, we assume that circRNA could be used for early diagnosis of breast cancer. Here, we developed classifiers for breast cancer diagnosis that relied on 259 samples, including 144 breast cancer patients and 115 controls. In the discovery stage, we compared the genome-wide long RNA profiles of EVs in patients with breast cancer (n=14) and benign breast (n=6). To further verify its potential in early diagnosis of breast cancer, we prospectively collected plasma samples from 259 individuals before treatment, including 144 breast cancer patients and 115 controls. Finally, we developed and verified the predictive classifies based on their circRNA expression profiles of plasma EVs by using multiple machine learning models. By comparing their circRNA profiles, we found 439 circRNAs with significantly different levels between cancer patients and controls. Considering the cost and practicability of the test, we selected 20 candidate circRNAs with elevated levels and detected their levels by quantitative real-time polymerase chain reaction. In the training cohort, we found that BCExoC, a nine-circRNA combined classifier with SVM model, achieved the largest AUC of 0.83 [95% CI 0.77-0.88]. In the validation cohort, the predictive efficacy of the classifier achieved 0.80 [0.71-0.89]. Our work reveals the application prospect of circRNAs in plasma EVs as non-invasive liquid biopsies in the diagnosis and management of breast cancer.

A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing.

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile. AECT outperformed existing single-cell sequencing imputation algorithms in terms of improvements to TSS coverage accuracy and the capture of latent biological features that distinguish sex or tumor status. We built classifiers for the detection of breast and rectal cancer using AECT-imputed shallow sequencing data, and their performance was close to that achieved by high-depth sequencing, suggesting that AECT could provide a broadly applicable noninvasive screening approach with high accuracy and at a moderate cost.

Transcriptome analysis to reveal the mechanism of the effect of Echinops latifolius polysaccharide B on palmitate-induced insulin-resistant.

Hepatic insulin resistance is a crucial pathological process in type 2 diabetes mellitus (T2DM) associated with visceral adiposity and metabolic disorders. Echinops latifolius polysaccharide B (ETPB), a polysaccharide extracted from Echinops latifolius Tausch, increases insulin sensitivity in the high-fat diet-fed and STZ induced SD rat model and even prevented hepatic metabolic disorders. However, the mechanism by which ETPB improves carbohydrate and lipid metabolisms in the liver with insulin resistance remains largely unknown. In the present work, an lnsulin resistance cell model (IR-HepG2) was established. Glucose consumption, glycogen content, triglycerides (TG), and free fatty acids (FFAs) levels were detected. The result revealed that the intervention of ETPB significantly increased glucose consumption and glycogen synthesis and reduced FFAs and TG production in IR-HepG2 cells. Further, we also employed RNA-seq to identify differentially expressed miRNAs (DEMs) and mRNAs (DEGs) with a fold change of ≥ 1.5 and p-value of <0.05. Finally, we identified 1028, 682, 382, 1614, 519 and 825 DEGs, and 71, 113, 94, 68, 52 and 38 DEMs in different comparisons, respectively. Based on a short time-series expression miner (STEM) analysis, six profiles were chosen for further analysis. Seventeen insulin resistance-associated dynamic DEGs were identified during ETPB stimulation. Based on these dynamic DEGs, the related miRNAs were acquired from DEMs, and an integrated miRNA-mRNA regulatory network was subsequently constructed. Besides, some DEGs and DEMs were validated using qPCR. This study provides transcriptomic evidence of the molecular mechanism involved in HepG2 insulin resistance, leading to the discovery of miRNA-based target therapies for ETPB.

A plasma-derived extracellular vesicle mRNA classifier for the detection of breast cancer.

BACKGROUND: According to the global cancer burden data released in 2020, breast cancer (BC) has become the most common cancer in the world. Similar to those of other cancers, the present methods used in clinic for diagnosing early BC are invasive, inaccurate, and insensitive. Hence, new non-invasive methods capable of early diagnosis are needed. METHODS: We applied next-generation sequencing and analyzed the messenger RNA (mRNA) profiles of plasma extracellular vesicles (EVs) derived from 14 BC patients and 6 patients with benign breast lesions. We used 3 regression models, namely support vector machine (SVM), linear discriminate analysis (LDA), and logistic regression (LR), to develop classifiers for use in making predictive BC diagnoses; and used 259 plasma samples, including those obtained from 144 patients with BC, 72 patients with benign breast lesions, and 43 healthy women, which were divided into training groups and validation groups to verify their performances as classifiers by quantitative reverse transcription polymerase chain reaction (RT-qPCR). The area under the curve (AUC) and accuracy, sensitivity, and specificity of the classifiers were cross-validated with the leave-1-out cross-validation (LOOCV) method. RESULTS: Among all combinations assessed with the 3 different regression models, an 8-mRNA combination, named EXOBmRNA, exhibited high performance [accuracy =71.9% and AUC =0.718, 95% confidence interval (CI): 0.652 to 0.784] in the training cohort after LOOCV was performed, showing the largest AUC in the SVM model. The mRNAs in EXOBmRNA were HLA-DRB1, HAVCR1, ENPEP, TIMP1, CD36, MARCKS, DAB2, and CXCL14. In the validation cohort, the AUC of EXOBmRNA was 0.737 (95% CI: 0.636 to 0.837). In addition, gene function and pathway analyses revealed that different levels of gene expression were associated with cancer. CONCLUSIONS: We developed a high-performing predictive classifiers including 8 mRNAs from plasma extracellular vesicles for diagnosing breast cancer.

Noninvasive discrimination of benign and malignant breast lesions using genome-wide nucleosome profiles of plasma cell-free DNA.

BACKGROUND: Breast malignancy is the most frequently diagnosed malignancy in women worldwide, and the diagnosis relies on invasive examinations. However, most clinical breast changes in women are benign, and invasive diagnostic approaches cause unnecessary suffering for the patients. Thus, a novel noninvasive approach for discriminating malignant breast lesions from benign lesions is needed. METHODS: We performed cell-free DNA (cfDNA) sequencing on plasma samples from 173 malignant breast lesion patients, 158 benign breast lesion patients, and 102 healthy women. We then analyzed the cfDNA-based nucleosome profiles, which reflect the various tissues of origin and transcription factor activities. Moreover, by using machine learning classifiers along with the cfDNA sequencing data, we built classifiers for discriminating benign from malignant breast lesions. Receiver operating characteristic curve analyses were used to evaluate the performance of the classifiers. RESULTS: cfDNA-based nucleosome profiles reflected the various tissues of origin and transcription factor activities in benign and malignant breast lesions. The cfDNA-based transcription factor activities and breast malignancy-specific transcription factor-binding site accessibility profiles could accurately distinguish benign and malignant breast lesions, with area under the curve values of 0.777 and 0.824, respectively. CONCLUSIONS: Our proof-of-principle study established a methodology for noninvasively discriminating benign from malignant breast lesions.

Analgesic efficacy of imrecoxib for postoperative pain following oral surgery: a prospective randomized, active-controlled, non-inferiority trial.

BACKGROUND: Imrecoxib, a novel cyclooxygenase (COX-2) selective non-steroidal anti-inflammatory drug (NSAID), has been approved in China for more than 9 years. This study aimed to assess the efficacy and safety of imrecoxib compared with celecoxib for patients with moderate or severe acute pain following oral surgery. METHODS: Patients with moderate or severe pain within 6 hours following surgery were enrolled in this randomized, active-control trial. Patients were randomly assigned (1:1) to receive either imrecoxib or celecoxib. Pain assessments on the visual analog scale, verbal rating scale, and pain relief were conducted at 0.5, 1, 2, 4, 6, 9, 12, and 24 hours after the first dose. Adverse events were also recorded. RESULTS: Eighty-seven patients were approached from November 2018 to August 2019. Of these, 60 were eligible for randomization. Ultimately, 56 patients (imrecoxib group, n=27; celecoxib group, n=29) were included in the analysis. The difference in total pain relief (TOTPAR) between the imrecoxib and celecoxib groups was 1.03 [95% confidence interval (CI): -1.31-3.77], with the lower bound of the CI above the specified non-inferiority boundary. No perioperative complications were observed in the imrecoxib group during the 24-hour period after the first dose. CONCLUSIONS: Imrecoxib could significantly relieve pain and has a non-inferior analgesic efficacy compared to celecoxib with good tolerance following oral surgery.

Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer.

Gene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

A Genotype Signature for Predicting Pathologic Complete Response in Locally Advanced Rectal Cancer.

PURPOSE: To construct and validate a predicting genotype signature for pathologic complete response (pCR) in locally advanced rectal cancer (PGS-LARC) after neoadjuvant chemoradiation. METHODS AND MATERIALS: Whole exome sequencing was performed in 15 LARC tissues. Mutation sites were selected according to the whole exome sequencing data and literature. Target sequencing was performed in a training cohort (n = 202) to build the PGS-LARC model using regression analysis, and internal (n = 76) and external validation cohorts (n = 69) were used for validating the results. Predictive performance of the PGS-LARC model was compared with clinical factors and between subgroups. The PGS-LARC model comprised 15 genes. RESULTS: The area under the curve (AUC) of the PGS model in the training, internal, and external validation cohorts was 0.776 (0.697-0.849), 0.760 (0.644-0.867), and 0.812 (0.690-0.915), respectively, and demonstrated higher AUC, accuracy, sensitivity, and specificity than cT stage, cN stage, carcinoembryonic antigen level, and CA19-9 level for pCR prediction. The predictive performance of the model was superior to clinical factors in all subgroups. For patients with clinical complete response (cCR), the positive prediction value was 94.7%. CONCLUSIONS: The PGS-LARC is a reliable predictive tool for pCR in patients with LARC and might be helpful to enable nonoperative management strategy in those patients who refuse surgery. It has the potential to guide treatment decisions for patients with different probability of tumor regression after neoadjuvant therapy, especially when combining cCR criteria and PGS-LARC.

Comprehensive analysis of ALK, ROS1 and RET rearrangements in locally advanced rectal cancer.

Gene rearrangements, such as anaplastic lymphoma kinase (ALK), c-ros oncogene 1 receptor tyrosine kinase (ROS1), rearranged during transfection (RET) and neurotrophic receptor tyrosine kinase 1 (NTRK1), identified in cancer have been indicated to be robust therapeutic targets in lung carcinomas. However, a few studies have focussed on locally advanced rectal cancer (LARC). The discovery of novel gene fusions is also valuable for LARC research. We used mass spectrometry-based assays and RNA sequencing to detect both known ALK, ROS1, RET and NTRK1 rearrangements and novel gene fusions in LARC patients. FusionMap was also used to find gene fusions. None of the ALK, ROS1, RET or NTRK1 gene fusions were detected by mass spectrometry-based assays or RNA sequencing. Three fusion candidates, integrin subunit beta 7 (ITGB7)-ROS1, lamin A/C (LMNA)-NTRK1 and Golgi-associated PDZ and coiled-coil motif containing (GOPC)-keratin 8 (KRT8), showed relatively high junction-spanning reads by the FusionMap algorithm, but did not pass validation. These results suggest that no ALK, ROS1 or RET rearrangements were found in LARC.

Study design and baseline characteristics of Shenzhen ageing-related disorder cohort in China.

PURPOSE: The Shenzhen ageing-related disorder cohort was designed to detect the associations of lifestyle, environmental and genetic factors with major ageing-related disorders, especially neurological and mental disorders. PARTICIPANTS: The cohort was a community-dwelling prospective study of 9411 elderly adults aged 60 to 92 years from 51 community health service centres in Luohu district of Shenzhen, China. The baseline data were collected between 2017 and 2018, including demographics and socioeconomics, lifestyles, medical history, family history of major non-communicable chronic disease, environmental exposures, clinical analysis of blood and urine, clinical imaging measurements, anthropometric measures and neurological function and mental health assessments. Blood and urinary samples were collected at baseline. All participants will be followed for physiological and psychological disorders and updated lifestyle and environmental exposures every 5 years. FINDINGS TO DATE: The mean age of the participants was 67.73 years at baseline, and 42.74% were males. The prevalences of individuals with unhealthy conditions were as follows: overweight/obesity (54.38%), hypertension (58.24%), diabetes mellitus (22.30%), dyslipidaemia (75.69%), chronic bronchitis (1.45%), myocardial infarction (0.55%), coronary heart disease (5.69%), stroke (1.10%), cancer (2.18%), arthritis (5.04%), Alzheimer's disease (0.18%), Parkinson's disease (0.23%), brain injury (5.75%), cognitive impairment (5.39%) and depression status (3.28%). The mean scores for the Lawton-Brody Activities of Daily Living Scale and the Social Support Rate Scale were 14.15 and 39.54, respectively. FUTURE PLANS: 2000 new entrants from Luohu district will be recruited every year until 2028. The data collection is expected to be ended at the end of 2030. The data will be used to assess the causality of ageing-related disorders, especially neurological and mental disorders through integrating environmental, genetic and lifestyle factors. The data sets generated and/or analysed during the current study are not publicly available at this stage, but are available from the corresponding author on reasonable request.

Whole-Genome Promoter Profiling of Plasma DNA Exhibits Diagnostic Value for Placenta-Origin Pregnancy Complications.

Placenta-origin pregnancy complications, including preeclampsia (PE), gestational diabetes mellitus (GDM), fetal growth restriction (FGR), and macrosomia (MA) are common occurrences in pregnancy, resulting in significant morbidity and mortality for both mother and fetus. However, despite their frequency, there are no reliable methods for the early diagnosis of these complications. Since cfDNA is mainly derived from placental trophoblasts and maternal hematopoietic cells, it might have information for gene expression which can be used for disease prediction. Here, low coverage whole-genome sequencing on plasma DNA from 2,199 pregnancies is performed based on retrospective cohorts of 3,200 pregnant women. Read depth in the promoter regions is examined to define read-depth distribution patterns of promoters for pregnancy complications and controls. Using machine learning methods, classifiers for predicting pregnancy complications are developed. Using these classifiers, complications are successfully predicted with an accuracy of 80.3%, 78.9%, 72.1%, and 83.0% for MA, FGR, GDM, and PE, respectively. The findings suggest that promoter profiling of cfDNA may be used as a biological biomarker for predicting pregnancy complications at early gestational age.