Functional and Structural Characterization of Clinical-Stage Janus Kinase 2 Inhibitors Identifies Determinants for Drug Selectivity.

Janus kinase 2 (JAK2) plays a critical role in orchestrating hematopoiesis, and its deregulation leads to various blood disorders, most importantly myeloproliferative neoplasms (MPNs). Ruxolitinib, fedratinib, momelotinib, and pacritinib are FDA-/EMA-approved JAK inhibitors effective in relieving symptoms in MPN patients but show variable clinical profiles due to poor JAK selectivity. The development of next-generation JAK2 inhibitors is hampered by the lack of comparative functional analysis and knowledge of the molecular basis of their selectivity. Here, we provide mechanistic profiling of the four approved and six clinical-stage JAK2 inhibitors and connect selectivity data with high-resolution structural and thermodynamic analyses. All of the JAK inhibitors potently inhibited JAK2 activity. Inhibitors differed in their JAK isoform selectivity and potency for erythropoietin signaling, but their general cytokine inhibition signatures in blood cells were comparable. Structural data indicate that high potency and moderate JAK2 selectivity can be obtained by targeting the front pocket of the adenosine 5'-triphosphate-binding site.

A method for predicting drugs that can boost the efficacy of immune checkpoint blockade.

Combination therapy is a promising therapeutic strategy to enhance the efficacy of immune checkpoint blockade (ICB); however, predicting drugs for effective combination is challenging. Here we developed a general data-driven method called CM-Drug for screening compounds that can boost ICB treatment efficacy based on core and minor gene sets identified between responsive and nonresponsive samples in ICB therapy. The CM-Drug method was validated using melanoma and lung cancer mouse models, with combined therapeutic efficacy demonstrated in eight of nine predicted compounds. Among these compounds, taltirelin had the strongest synergistic effect. Mechanistic analysis and experimental verification demonstrated that taltirelin can stimulate CD8+ T cells and is mediated by the induction of thyroid-stimulating hormone. This study provides an effective and general method for predicting and evaluating drugs for combination therapy and identifies candidate compounds for future ICB combination therapy.

Consensus on rapid screening for prodromal Alzheimer's disease in China.

Alzheimer's disease (AD) is a common cause of dementia, characterised by cerebral amyloid-ß deposition, pathological tau and neurodegeneration. The prodromal stage of AD (pAD) refers to patients with mild cognitive impairment (MCI) and evidence of AD's pathology. At this stage, disease-modifying interventions should be used to prevent the progression to dementia. Given the inherent heterogeneity of MCI, more specific biomarkers are needed to elucidate the underlying AD's pathology. Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology, their clinical applications are limited by their high costs and invasiveness, particularly in low-income areas in China. Therefore, to improve the early detection of Alzheimer's disease (AD) pathology through cost-effective screening methods, a panel of 45 neurologists, psychiatrists and gerontologists was invited to establish a formal consensus on the screening of pAD in China. The supportive evidence and grades of recommendations are based on a systematic literature review and focus group discussion. National meetings were held to allow participants to review, vote and provide their expert opinions to reach a consensus. A majority (two-thirds) decision was used for questions for which consensus could not be reached. Recommended screening methods are presented in this publication, including neuropsychological assessment, peripheral biomarkers and brain imaging. In addition, a general workflow for screening pAD in China is established, which will help clinicians identify individuals at high risk and determine therapeutic targets.

The effect of B-vitamins on the prevention and treatment of cardiovascular diseases: a systematic review and meta-analysis.

CONTEXT: Previous research evaluating the effects in B-vitamins on the prevention and treatment of cardiovascular disease (CVD) has substantial limitations and lacks recently published large prospective studies; hence, conducting an updated meta-analysis is needed. OBJECTIVE: We investigated the association between vitamin B status and human CVD development in order to provide more specific advice about vitamin B intake for those at risk of CVD. DATA SOURCES: Relevant articles were identified by JSTOR, PubMed, and ProQuest databases. DATA EXTRACTION: Key words used to identify the studies included the different combinations of B-vitamins, folate, folic acid, vitamin B6, vitamin B12, homocysteine, cardiovascular disease, stroke, coronary disease, myocardial infarction, and cerebrovascular and transient ischemic attack. The database search was supplemented by hand-searching of reference lists of selected articles. DATA ANALYSIS: Pooled estimates were calculated from the mean differences using a random-effects model. RESULTS: Supplementation with folic acid was reported to have a clinical benefit of significantly reducing carotid intima-media thickness. Higher intakes of folic acid, vitamin B6, and vitamin B12 were generally associated with a lower risk of CVD in the general population, except in those without normal renal function and those with unstable angina or past non-ST-elevation myocardial infarction. CONCLUSION: Vitamin B supplementation resulted in the greatest cardiovascular benefit in those with normal renal function and without unstable angina or non-ST-elevation myocardial infarction recently. Factors such as age, gender, and genetic polymorphisms contribute to varying effects.

Machine learning algorithms for predicting the risk of fracture in patients with diabetes in China.

Background: Patients with diabetes are more likely to be predisposed to fractures compared to those without diabetes. In clinical practice, predicting fracture risk in diabetics is still difficult because of the limited availability and accessibility of existing fracture prediction tools in the diabetic population. The purpose of this study was to develop and validate models using machine learning (ML) algorithms to achieve high predictive power for fracture in patients with diabetes in China. Methods: In this study, the clinical data of 775 hospitalized patients with diabetes was analyzed by using Decision Tree (DT), Gradient Boosting Decision Tree (GBDT), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost) and Probabilistic Classification Vector Machines (PCVM) algorithms to construct risk prediction models for fractures. Moreover, the risk factors for diabetes-related fracture were identified by the feature selection algorithms. Results: The ML algorithms extracted 17 most relevant factors from raw clinical data to maximize the accuracy of the prediction results, including bone mineral density, age, sex, weight, high-density lipoprotein cholesterol, height, duration of diabetes, total cholesterol, osteocalcin, N-terminal propeptide of type I, diastolic blood pressure, and body mass index. The 7 ML models including LR, SVM, RF, DT, GBDT, XGBoost, and PCVM had f1 scores of 0.75, 0.83, 0.84, 0.85, 0.87, 0.88, and 0.97, respectively. Conclusions: This study identified 17 most relevant risk factors for diabetes-related fracture using ML algorithms. And the PCVM model proved to perform best in predicting the fracture risk in the diabetic population. This work proposes a cheap, safe, and extensible ML algorithm for the precise assessment of risk factors for diabetes-related fracture.

Diastolic and systolic blood pressure time in target range as a cardiovascular risk marker in patients with type 2 diabetes: A post hoc analysis of ACCORD BP trial.

AIMS: We investigated the associations between time in target range (TTR) of blood pressure (BP) and cardiovascular outcomes in patients with diabetes. METHODS: 4651 participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) BP trial were included in the present study. The diastolic BP target range was defined as 70 to 80 mm Hg, and the systolic as 120 to 140 mm Hg and 110 to 130 mm Hg for the standard and intensive therapy, respectively. RESULTS: After adjusting for covariates, 1-SD increase of diastolic TTR was significantly associated with lower risks of primary outcome (HR 0.82, 95% CI: 0.74-0.91, P < 0.001; HR 0.86, 95% CI: 0.77-0.95, P = 0.0044, as well as nonfatal myocardial infarction (HR 0.79, 95% CI: 0.69-0.91, P < 0.001). Meanwhile, systolic TTR was significantly associated with various cardiovascular outcomes (P ≤ 0.016) in fully-adjusted models. The diastolic TTR sustained significance in myocardial infarction when systolic blood pressure average was higher than 120 mm Hg. CONCLUSIONS: In patients with diabetes, TTR of diastolic and systolic BP was independently associated with lower risks of major outcomes. The diastolic BP within the optimal target range was considerably important for reducing the risk of myocardial infarction, even when systolic BP was under stable control.

Causal Effects of Plasma Haptoglobin Levels on Alzheimer's Disease: A Two-Sample Mendelian Randomization Study.

BACKGROUND: A connection between plasma levels of haptoglobin (Hp) and Alzheimer's disease (AD) has been shown in several observational studies. It is debatable, nonetheless, how the two are related causally. OBJECTIVE: To establish the causal relationship between Hp and AD using a two-sample Mendelian randomization (MR) study. METHODS: From the extensive genome-wide association studies and FinnGen dataset, summaries and statistics pertaining to AD were gathered. We investigated the possibility of a causal link between Hp and AD using a two-sample MR study. Inverse variance weighting was used as the primary analytical technique, and it was supported by the joint application of complementary analyses and fixed effects meta-analysis to combine results from various sources. RESULTS: Genetically determined Hp was causally associated with AD [odds ratio (OR), 1.05; 95% confidence interval (CI), 1.02 to 1.09; p = 8.96×10-4]; Inverse variance-weighted estimates coming from different data sources were combined in a meta-analysis with consistent findings (OR, 1.03; 95% CI, 1.01 to 1.05; p = 2.00×10-3). The outcomes of the inverse MR analysis showed that AD had no appreciable causal impact on Hp. CONCLUSION: The present MR analysis shows that higher plasma Hp leads to an increased risk of AD. Strategies for plasma Hp testing may open up new doors for the early diagnosis and prevention of AD.

scLiverDB: a Database of Human and Mouse Liver Transcriptome Landscapes at Single-Cell Resolution.

The liver is critical for the digestive and immune systems. Although the physiology and pathology of liver have been well studied and many scRNA-seq data are generated, a database and landscape for characterizing cell types and gene expression in different liver diseases or developmental stages at single-cell resolution are lacking. Hence, scLiverDB is developed, a specialized database for human and mouse liver transcriptomes to unravel the landscape of liver cell types, cell heterogeneity and gene expression at single-cell resolution across various liver diseases/cell types/developmental stages. To date, 62 datasets including 9,050 samples and 1,741,734 cells is curated. A uniform workflow is used, which included quality control, dimensional reduction, clustering, and cell-type annotation to analyze datasets on the same platform; integrated manual and automatic methods for accurate cell-type identification and provided a user-friendly web interface with multiscale functions. There are two case studies to show the usefulness of scLiverDB, which identified the LTB (lymphotoxin Beta) gene as a potential biomarker of lymphoid cells differentiation and showed the expression changes of Foxa3 (forkhead box A3) in liver chronic progressive diseases. This work provides a crucial resource to resolve molecular and cellular information in normal, diseased, and developing human and mouse livers.

mTOR-dependent TFEB activation and TFEB overexpression enhance autophagy-lysosome pathway and ameliorate Alzheimer's disease-like pathology in diabetic encephalopathy.

BACKGROUND: Diabetic encephalopathy (DE) is a complication of type 2 diabetes mellitus (T2DM) that features Alzheimer's disease (AD)-like pathology, which can be degraded by the autophagy-lysosome pathway (ALP). Since transcription factor EB (TFEB) is a master regulator of ALP, TFEB-mediated ALP activation might have a therapeutic effect on DE, but this has yet to be investigated. METHODS: We established T2DM mouse models and cultured HT22 cells under high-glucose (HG) conditions to confirm the role of ALP in DE. To further investigate this, both mice and HT22 cells were treated with 3-methyladenine (3-MA). We also analyzed the content of TFEB in the nucleus and cytoplasm to evaluate its role in ALP. To confirm the effect of TFEB activation at the post-translational level in DE, we used rapamycin to inhibit the mechanistic target of rapamycin (mTOR). We transduced both mice and cells with TFEB vector to evaluate the therapeutic effect of TFEB overexpression on DE. Conversely, we conducted TFEB knockdown to verify its role in DE in another direction. RESULTS: We found that T2DM mice experienced compromised cognitive function, while HG-cultured HT22 cells exhibited increased cell apoptosis. Additionally, both T2DM mice and HG-cultured HT22 cells showed impaired ALP and heavier AD-like pathology. This pathology worsened after treatment with 3-MA. We also observed decreased TFEB nuclear translocation in both T2DM mice and HG-cultured HT22 cells. However, inhibiting mTOR with rapamycin or overexpressing TFEB increased TFEB nuclear translocation, enhancing the clearance of ALP-targeted AD-like pathology. This contributed to protection against neuronal apoptosis and alleviation of cognitive impairment. Conversely, TFEB knockdown lessened ALP-targeted AD-like pathology clearance and had a negative impact on DE. CONCLUSION: Our findings suggest that impaired ALP is responsible for the aggravation of AD-like pathology in T2DM. We propose that mTOR-dependent TFEB activation and TFEB overexpression are promising therapeutic strategies for DE, as they enhance the clearance of ALP-targeted AD-like pathology and alleviate neuronal apoptosis. Our study provides insight into the underlying mechanisms of DE and offers potential avenues for the development of new treatments for this debilitating complication of T2DM. Video abstract.

The inhibition of Aurora A kinase regulates phospholipid remodeling by upregulating LPCAT1 in glioblastoma.

Metabolic reprogramming is a common feature of glioblastoma (GBM) progression and metastasis. Altered lipid metabolism is one of the most prominent metabolic alterations in cancer. Understanding the links between phospholipid remodeling and GBM tumorigenesis may help develop new anticancer strategies and improve treatments to overcome drug resistance. We used metabolomic and transcriptomic analyses to systematically investigate metabolic and molecular changes in low-grade glioma (LGG) and GBM. We then re-established the reprogrammed metabolic flux and membrane lipid composition in GBM based on metabolomic and transcriptomic analyses. By inhibiting Aurora A kinase via RNA interference (RNAi) and inhibitor treatment, we investigated the effect of Aurora A kinase on phospholipid reprogramming LPCAT1 enzyme expression and GBM cell proliferation in vitro and in vivo. We found that GBM displayed aberrant glycerophospholipid and glycerolipid metabolism compared with LGG. Metabolic profiling indicated that fatty acid synthesis and uptake for phospholipid synthesis were significantly increased in GBM compared to LGG. The unsaturated phosphatidylcholine (PC) and phosphatidylethanolamine (PE) levels were significantly decreased in GBM compared to LGG. The expression level of LPCAT1, which is required for the synthesis of saturated PC and PE, was upregulated in GBM, and the expression of LPCAT4, which is required for the synthesis of unsaturated PC and PE, was downregulated in GBM. Notably, the inhibition of Aurora A kinase by shRNA knockdown and treatment with Aurora A kinase inhibitors such as Alisertib, AMG900, or AT9283 upregulated LPCAT1 mRNA and protein expression in vitro. In vivo, the inhibition of Aurora A kinase with Alisertib increased LPCAT1 protein expression. Phospholipid remodeling and a reduction in unsaturated membrane lipid components were found in GBM. Aurora A kinase inhibition increased LPCAT1 expression and suppressed GBM cell proliferation. The combination of Aurora kinase inhibition with LPCAT1 inhibition may exert promising synergistic effects on GBM.

Primary cilia-associated protein IFT172 in ciliopathies.

Cilium is a highly conserved antenna-like structure protruding from the surface of the cell membrane, which is widely distributed on most mammalian cells. Two types of cilia have been described so far which include motile cilia and immotile cilia and the latter are also known as primary cilia. Dysfunctional primary cilia are commonly associated with a variety of congenital diseases called ciliopathies with multifaceted presentations such as retinopathy, congenital kidney disease, intellectual disability, cancer, polycystic kidney, obesity, Bardet Biedl syndrome (BBS), etc. Intraflagellar transport (IFT) is a bi-directional transportation process that helps maintain a balanced flow of proteins or signaling molecules essential for the communication between cilia and cytoplasm. Disrupted IFT contributes to the abnormal structure or function of cilia and frequently promotes the occurrence of ciliopathies. Intraflagellar transport 172 (IFT172) is a newly identified member of IFT proteins closely involved in some rare ciliopathies such as Mainzer-Saldino syndrome (MZSDS) and BBS, though the underpinning causal mechanisms remain largely elusive. In this review, we summarize the key findings on the genetic and protein characteristic of IFT172, as well as its function in intraflagellar transport, to provide comprehensive insights to understand IFT172-related ciliopathies.

The association of subjective sleep characteristics and plasma biomarkers of Alzheimer's disease pathology in older cognitively unimpaired adults with higher amyloid-ß burden.

We aimed to investigate the association of subjective sleep characteristics and plasma Alzheimer's disease (AD) biomarkers in older cognitively unimpaired adults with higher amyloid-ß (Aß) burden. Unimpaired cognition was determined by education-adjusted performance for the Mini-Mental State Examination and exclusion of dementia and mild cognitive impairment via standardized neuropsychological tests. We used Pittsburgh Sleep Quality Index (PSQI) to assess subjective sleep quality. The participants also underwent examination of plasma AD biomarkers and 18F-florbetapir PET scan. Correlation and multiple linear regression analyses were used to investigate the association between subjective sleep characteristics and AD biomarkers. A total of 335 participants were included and 114 were Aß-PET positive. Multivariable regression analysis showed sleep duration > 8 h and sleep disturbance were associated with Aß deposition in total participants. Two multiple linear regression models were applied and the results revealed in participants with Aß-PET (+), falling asleep at ≥ 22:00 to ≤ 23:00 was associated with higher levels of Aß42 and Aß42/40. Other associations with higher Aß42/40 and standard uptake value ratio contained sleep efficiency value, sleep efficiency ≥ 75%, no/mild daytime dysfunction and PSQI score ≤ 5. Higher p-Tau-181 level was associated with sleep latency > 30 min in Aß-PET (+) group and moderate/severe sleep disturbance in Aß-PET (-) group. Our data suggests sleep duration ≤ 8 h and no/mild sleep disturbance may be related to less Aß burden. In participants with Aß deposition, falling asleep at 22:00 to 23:00, higher sleep efficiency (at least ≥ 75%), no/mild daytime dysfunction, sleep latency ≤ 30 min, and good sleep quality may help improve AD pathology.

Anxiety prevalence and its association with physical activity in patients with non-communicable diseases during COVID-19 lockdown: a cross-sectional study in Shanghai, China.

BACKGROUND: Quarantine due to the COVID-19 pandemic may have created great psychological stress among vulnerable populations. We aimed to investigate the prevalence of anxiety and explore the association between physical activities (PA) and anxiety risk in people with non-communicable diseases during the period of COVID-19 lockdown. METHODS: We conducted a cross-sectional telephone survey from February 25 to April 20, 2020, the period of COVID-19 lockdown in Shanghai. Up to 8000 patients with type 2 diabetes and/or hypertension were selected using multi-stage cluster random sampling. PA level was measured based on the International Physical Activity Questionnaire using Metabolic Equivalent for Task scores, while symptoms of anxiety were assessed by the 7-item Generalized Anxiety Disorder scale. Multiple logistic regression analyses were performed to evaluate the associations of type and level of PA with the risk of anxiety. RESULTS: Of a total 4877 eligible patients, 2602 (53.4%) reported with anxiety, and 2463 (50.5%), 123 (2.5%) and 16 (0.3%) reported with mild, moderate, and severe anxiety. The prevalence of anxiety was higher in the females, the elders, non-smokers, non-drinkers, and patients with diabetes, and the associations of anxiety with sex, age, smoking, drinking and diagnosis of diabetes were significant. A significant negative association was observed for housework activities (OR 0.53, 95%CI: [0.45, 0.63], p < 0.001) and trip activities (OR 0.55, 95%CI: [0.48, 0.63], p < 0.001) with anxiety, but no significant was found for exercise activities (OR 1.06, 95%CI: [0.94, 1.20], p = 0.321). Compared with patients with a low PA level, those with a moderate (OR 0.53, 95%CI: [0.44, 0.64], p < 0.001) or a high PA level (OR 0.51, 95%CI: [0.43, 0.51], p < 0.001) had a lower prevalence of anxiety. CONCLUSION: This study demonstrates a higher prevalence of anxiety in patients with hypertension, diabetes, or both during the COVID-19 lockdown. The negative associations of housework and trip activities with anxiety highlight the potential benefit of PA among patients with non-communicable diseases.

MXene (Ti3C2Tx)/cellulose nanofiber/polyaniline film as a highly conductive and flexible electrode material for supercapacitors.

In recent years, supercapacitors based on cellulose nanofiber (CNF) films have received considerable attention for their excellent flexibility, lightweight, and unique structure. In this study, MXene (Ti3C2Tx) /CNF/polyaniline (PANI) hybrid films with good conductivity and flexibility were prepared by a convenient vacuum filtration method. Combined with PANI, MXene creates an open structure with high conductivity, which facilitates ion and electron transport among the materials and provides the composite with high electrochemical activity. The MXene/CNF/PANI electrode presents a high areal specific capacitance of 2935 mF cm-2 at the current density of 1 mA cm-2, excellent cycling stability with high capacitance retention of 94 % after 2000 cycles at 10 mA cm-2 and high electrical conductivity (634.4 S∙cm-1). As a further application of this film, it is used as a free-standing electrode to fabricate a quasi-solid-state supercapacitor with high performance, which has an ultra-thin thickness of 0.344 mm, a significantly high areal specific capacitance (522 mF cm-2) at 5 mA cm-2, a high areal energy density of 94.7 µWh∙cm-2 and a high areal power density of 573 µW∙cm-2. This work shows the great potential of the developed high-performance and flexible cellulose-based composites for fabricating electrodes as well as supercapacitors.

A comprehensive landscape of transcription profiles and data resources for human leukemia.

As a heterogeneous group of hematologic malignancies, leukemia has been widely studied at the transcriptome level. However, a comprehensive transcriptomic landscape and resources for different leukemia subtypes are lacking. Thus, in this study, we integrated the RNA sequencing data sets of >3000 samples from 14 leukemia subtypes and 53 related cell lines via a unified analysis pipeline. We depicted the corresponding transcriptomic landscape and developed a user-friendly data portal LeukemiaDB. LeukemiaDB was designed with 5 main modules: protein-coding gene, long noncoding RNA (lncRNA), circular RNA, alternative splicing, and fusion gene modules. In LeukemiaDB, users can search and browse the expression level, regulatory modules, and molecular information across leukemia subtypes or cell lines. In addition, a comprehensive analysis of data in LeukemiaDB demonstrates that (1) different leukemia subtypes or cell lines have similar expression distribution of the protein-coding gene and lncRNA; (2) some alternative splicing events are shared among nearly all leukemia subtypes, for example, MYL6 in A3SS, MYB in A5SS, HMBS in retained intron, GTPBP10 in mutually exclusive exons, and POLL in skipped exon; (3) some leukemia-specific protein-coding genes, for example, ABCA6, ARHGAP44, WNT3, and BLACE, and fusion genes, for example, BCR-ABL1 and KMT2A-AFF1 are involved in leukemogenesis; (4) some highly correlated regulatory modules were also identified in different leukemia subtypes, for example, the HOXA9 module in acute myeloid leukemia and the NOTCH1 module in T-cell acute lymphoblastic leukemia. In summary, the developed LeukemiaDB provides valuable insights into oncogenesis and progression of leukemia and, to the best of our knowledge, is the most comprehensive transcriptome resource of human leukemia available to the research community.

GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels.

Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking. In this study, we upgraded our GSCALite to GSCA (gene set cancer analysis, http://bioinfo.life.hust.edu.cn/GSCA) for cancer GSA at genomic, pharmacogenomic and immunogenomic levels. In this improved GSCA, we integrated expression, mutation, drug sensitivity and clinical data from four public data sources for 33 cancer types. We introduced useful features to GSCA, including associations between immune infiltration with gene expression and genomic variations, and associations between gene set expression/mutation and clinical outcomes. GSCA has four main functional modules for cancer GSA to explore, analyze and visualize expression, genomic variations, tumor immune infiltration, drug sensitivity and their associations with clinical outcomes. We used case studies of three gene sets: (i) seven cell cycle genes, (ii) tumor suppressor genes of PI3K pathway and (iii) oncogenes of PI3K pathway to prove the advantage of GSCA over single gene analysis. We found novel associations of gene set expression and mutation with clinical outcomes in different cancer types on gene set level, while on single gene analysis level, they are not significant associations. In conclusion, GSCA is a user-friendly web server and a useful resource for conducting hypothesis tests by using GSA methods at genomic, pharmacogenomic and immunogenomic levels.

Association between age at diabetes onset or diabetes duration and subsequent risk of pancreatic cancer: Results from a longitudinal cohort and mendelian randomization study.

Background: The aim of the study is to estimate the incidence of pancreatic cancer among individuals with new-onset type 2 Diabetes (T2DM) and evaluate the relationship of pancreatic cancer risk with age at diabetes onset and diabetes duration. Methods: This longitudinal cohort study included 428,362 new-onset T2DM patients in Shanghai and Mendelian randomization (MR) in the east-Asian population were used to investigate the association. Incidence rates of pancreatic cancer in all patients and by subgroups were calculated and compared to the general population. Findings: A total of 1056 incident pancreatic cancer cases were identified during eight consecutive years of follow-up. The overall pancreatic cancer annual incidence rate was 55·28/100,000 person years in T2DM patients, higher than that in the general population, with a standardized incidence ratio (SIR) of 1·54 (95% confidence interval [CI], 1·45-1·64). The incidence of pancreatic cancer increased with age and a significantly higher incidence was observed in the older groups with T2DM. However, the relative pancreatic cancer risk was inversely related to age of T2DM onset, and a higher SIR of 5·73 (95%CI, 4·49-7·22) was observed in the 20-54 years old group. The risk of pancreatic cancer was elevated at any diabetes duration. Fasting blood glucose ≥10·0 mmol/L was associated with increased risk of pancreatic cancer. MR analysis indicated a positive association between T2DM and pancreatic cancer risk. Interpretation: Efforts toward early and close follow-up programs, especially in individuals with young-onset T2DM, and the improvement of glucose control might represent effective strategies for improving the detection and results of treatment of pancreatic cancer. Funding: Chinese National Natural Science Foundation.

lncRNASNP v3: an updated database for functional variants in long non-coding RNAs.

Long non-coding RNAs (lncRNAs) act as versatile regulators of many biological processes and play vital roles in various diseases. lncRNASNP is dedicated to providing a comprehensive repository of single nucleotide polymorphisms (SNPs) and somatic mutations in lncRNAs and their impacts on lncRNA structure and function. Since the last release in 2018, there has been a huge increase in the number of variants and lncRNAs. Thus, we updated the lncRNASNP to version 3 by expanding the species to eight eukaryotic species (human, chimpanzee, pig, mouse, rat, chicken, zebrafish, and fruitfly), updating the data and adding several new features. SNPs in lncRNASNP have increased from 11 181 387 to 67 513 785. The human mutations have increased from 1 174 768 to 2 387 685, including 1 031 639 TCGA mutations and 1 356 046 CosmicNCVs. Compared with the last release, updated and new features in lncRNASNP v3 include (i) SNPs in lncRNAs and their impacts on lncRNAs for eight species, (ii) SNP effects on miRNA-lncRNA interactions for eight species, (iii) lncRNA expression profiles for six species, (iv) disease & GWAS-associated lncRNAs and variants, (v) experimental & predicted lncRNAs and drug target associations and (vi) SNP effects on lncRNA expression (eQTL) across tumor & normal tissues. The lncRNASNP v3 is freely available at http://gong_lab.hzau.edu.cn/lncRNASNP3/.

Alterations in metamemory capacity and neural correlates in a subtype of subjective cognitive decline.

BACKGROUNDS: Subjective cognitive decline (SCD), one of the important clinical indicators for preclinical Alzheimer's disease (AD), is primarily defined as self-perceived cognitive decline without objective evidence for cognitive impairment. However, the accuracy of their self-evaluation of cognition is unclear. This study sought to investigate the capacity for self-evaluation of own cognitive performance in SCD by applying an objective metamemory paradigm. METHODS: 147 individuals with SCD were classified into four subgroups by their subjective feeling of worse performance than peers or not (P+/-) and whether they have objectively slight cognitive impairment compared to normative data (S+/-). Metamemory scores, the amplitude of the low-frequency fluctuation (ALFF), fractional low-frequency fluctuation amplitude (fALFF), and cortical thickness were compared among four subgroups. Partial correlations between neuropsychological scores and neuroimaging measures were examined, controlling for age, sex, and education years. RESULTS: SCD S+P- showed the worst performance in short-term delayed recall and the worst metamemory performance, indicated by the highest value in the degree of confidence of short-term delayed recall (DOC-N4) and long-term cued recall (DOC-N6) and the worst value in relative accuracy of judgments of short-term delayed recall (ROJ-N4). ALFF values in the bilateral superior medial frontal and olfactory cortices and the left superior orbitofrontal gyrus cortex were significantly higher in SCD P- compared with SCD P+ groups (all P < 0.05, FWE-corrected, cluster-wise level). A significant S × P interaction effect in the left hippocampus and middle cingulate cortex was found for the fALFF signals (all P < 0.05, FWE-corrected, cluster-wise level). Significant interaction and main effects on cortical thickness were reported. The parahippocampal and posterior cingulate cortices were significantly decreased in SCD S+P- (all P < 0.05). CONCLUSION: SCD S+P- showed the worst episodic memory performance, altered metamemory capacity (overconfidence and less accuracy of judgment), and altered neuroimaging measures, though they had feelings of similar performance with peers. Our results indicate that metamemory capacity is affected in a subtype of SCD with reduced cortical thickness and intensity of regional spontaneous activity in key areas for metamemory processing.

CVD risk in non-albuminuric chronic kidney disease in hypertensive, non-diabetic subjects: A post-hoc analysis from SPRINT.

Introduction: The risks associated with non-albuminuric chronic kidney disease (CKD) have been investigated in diabetes mellitus but not in hypertensive patients. The objective of this study was to investigate the risks associated with non-albuminuric CKD in treated hypertensive patients in the Systolic Blood Pressure Intervention Trial (SPRINT) population. Methods: Based on baseline albuminuria status (urine albumin/creatinine ratio [UACR], ≥30 or <30 mg/g) and the levels of estimated glomerular filtration rate ([eGFR], ≥60, 45-59, or <45 mL/min/1.73 m2), participants were classified into six subgroups to assess the risks associated with the primary outcome and mortality. The primary composite outcome was myocardial infarction, other acute coronary syndromes, stroke, heart failure, or mortality from cardiovascular causes. Results: During a median follow-up of 3.26 years in 8,866 hypertensive patients, there were 352 deaths and 547 participants with the primary outcome. In adjusted Cox regression analysis using non-CKD and non-albuminuria (eGFR ≥60 mL/min/1.73 m2 combined with UACR <30 mg/g) as reference, albuminuria whether combined with CKD or not, showed significantly higher risk of both primary outcome and all-cause mortality in the total population. Whereas, non-albuminuria only combined with eGFR <45 mL/min/1.73 m2 showed significantly higher risk of both primary outcome and all-cause mortality in the intensive-therapy group. Discussion: Non-albuminuric CKD did have higher risk of all-cause and CVD mortality only if the eGFR <45 mL/min/1.73 m2. Increased albuminuria conferred higher risk of primary outcome and all-cause mortality irrespective the levels of eGFR. Clinical trial registration: ClinicalTrials.gov, number: NCT01206062.