Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations.

Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM.

[Association between insomnia and type 2 diabetes: A two-sample Mendelian rando-mization study].

OBJECTIVE: To explore the robust relationship between insomnia and type 2 diabetes mellitus by two-sample Mendelian randomization analysis to overcome confounding factors and reverse causality in observational studies. METHODS: We identified strong, independent single nucleotide polymorphisms (SNPs) of insomnia from the most up to date genome wide association studies (GWAS) within European ancestors and applied them as instrumental variable to GWAS of type 2 diabetes mellitus. After excluding SNPs that were significantly associated with smoking, physical activity, alcohol consumption, educational attainment, obesity, or type 2 diabetes mellitus, we assessed the impact of insomnia on type 2 diabetes mellitus using inverse variance weighting (IVW) method. Weighted median and MR-Egger regression analysis were also conducted to test the robustness of the association. We calculated the F statistic of the selected SNPs to test the applicability of instrumental variable and F statistic over than ten indicated that there was little possibility of bias of weak instrumental variables. We further examined the existence of pleiotropy by testing whether the intercept term in MR-Egger regression was significantly different from zero. In addition, the leave-one-out method was used for sensitivity analysis to verify the stability and reliability of the results. RESULTS: We selected 248 SNPs independently associated with insomnia at the genome-wide level (P<5×10-8) as a preliminary candidate set of instrumental variables. After clumping based on the reference panel from 1000 Genome Project and removing the potential pleiotropic SNPs, a total of 167 SNPs associated with insomnia were included as final instrumental variables. The F statistic of this study was 39. 74, which was in line with the relevance assumption of Mendelian randomization. IVW method showed insomnia was associated with higher risk of type 2 diabetes mellitus that po-pulation with insomnia were 1. 14 times more likely to develop type 2 diabetes mellitus than those without insomnia (95% CI: 1.09-1.21, P<0.001). The weighted median estimator (WME) method and MR-Egger regression showed similar causal effect of insomnia on type 2 diabetes mellitus. And MR-Egger regression also showed that the effect was less likely to be triggered by pleiotropy. Sensitivity analyses produced directionally similar estimates. CONCLUSION: Insomnia is a risk factor of type 2 diabetes mellitus, which has positively effects on type 2 diabetes mellitus. Our study provides further rationale for indivi-duals at risk for diabetes to keep healthy lifestyle.

Circadian rhythm of daytime sleepiness in pediatric narcolepsy: A pilot study.

BACKGROUND AND OBJECTIVE: Excessive daytime sleepiness (EDS) has been far back reported as the most disabling symptom in the pediatric narcoleptic patients. However, there is a lack of studies to examine the circadian rhythms of EDS in pediatric narcoleptic population. Therefore, we aim to investigate the circadian rhythm of EDS in pediatric narcolepsy patients. METHODS: We identified 50 pediatric narcoleptic patients (36 males and 14 females, mean age 13.68 ± 2.75 years). Data were collected through interviews and the relevant questionnaires (children depression inventory [CDI] and the pediatric quality of life inventory [PedsQL]). RESULT: The frequencies of sleep attacks during different intervals of the day differed significantly, with higher frequency in the morning (p < .001). The times of sleep attacks in the morning and in the afternoon were significantly associated with the degree of impairment on class and the severity of worry about sleepiness, with spearman correlation coefficient ranging from .289 to .496 (p < .05). The total scores of PedsQL and CDI differed significantly among morning sleepiness dominant, afternoon sleepiness dominant, and evening sleepiness dominant groups (p = .042, p = .040). The severity scores of the narcoleptic patients' sleepiness had two peaks, one of which occurred at 16:00, and the other peaks occurred at about 11:00. CONCLUSION: These results suggest that changes based on the circadian rhythm of sleepiness of the pediatric narcoleptic patients should be made in the treatment strategy. In addition, regulating the secretion of melatonin could serve as a promising treatment to relieve sleepiness in the future.

Tumor-Derived PD-L1+ Exosomes with Natural Inflammation Tropism for Psoriasis-Targeted Treatment.

Psoriasis is a chronic inflammatory disease whose etiology is directly related to the dysregulation of cutaneous immune homeostasis. However, how to finely modulate the skin immune microenvironment to restore homeostasis remains an important challenge. Inspired by the natural attribute of tumor exosomes in the immune escape, the tumor-derived exosomes as an active targeting nanoplatform for the effective treatment of inflammatory skin disorder were first reported. As keratinocytes and immune cells express high PD-1 during the onset of psoriasiform skin inflammation, the PD-L1-positive exosomes derived from melanoma cells carrying pristimerin with extremely anti-inflammatory potential were yielded to treat psoriasis. The PD-L1+ exosomes carrying pristimerin were characterized, and the cellular uptake was performed to evaluate the PD-1 target capability. The anti-inflammatory action of PD-L1+ exosomes carrying pristimerin was observed in both in vitro and in vivo models of psoriasis. Our exosomes substantially increased pristimerin uptake with CD4+ T cells and keratinocytes, significantly inhibited the proliferation of Th17 cells, and promoted Treg differentiation in a psoriasis-like model. Obviously, PD-L1+ exosomes carrying pristimerin significantly and safely reversed imiquimod (IMQ)-induced psoriasis in mice, indicated by reducing epidermal thickness, decreasing plaque formation, and suppressed excessive inflammatory response, due to its dual targeting of both CD4+ T cells and keratinocytes gathering around the lesion. The inflammatory cell infiltration and pro-inflammatory cytokine production in psoriasis were suppressed by our engineered exosomes. Besides, PD-L1+ exosomes carrying pristimerin treatment alleviated ferroptosis-related changes in psoriatic skin, thereby dampening excessive inflammation and, in turn, decreasing the abnormal proliferation of keratinocytes in psoriatic lesions. This study demonstrates that our engineered exosomes can not only act as a treat-to-target strategy for psoriasis treatment but also provide insight in clinical application of inflammatory disorders.

PDE3A and GSK3B as Atrial Fibrillation Susceptibility Genes in the Chinese Population via Bioinformatics and Genome-Wide Association Analysis.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with uncovered genetic etiology and pathogenesis. We aimed to screen out AF susceptibility genes with potential pathogenesis significance in the Chinese population. METHODS: Differentially expressed genes (DEGs) were screened by the Limma package in three GEO data sets of atrial tissue. AF-related genes were identified by combination of DEGs and public GWAS susceptibility genes. Potential drug target genes were selected using the DrugBank, STITCH and TCMSP databases. Pathway enrichment analyses of AF-related genes were performed using the databases GO and KEGG databases. The pathway gene network was visualized by Cytoscape software to identify gene-gene interactions and hub genes. GWAS analysis of 110 cases of AF and 1201 controls was carried out through a genome-wide efficient mixed model in the Fangshan population to verify the results of bioinformatic analysis. RESULTS: A total of 3173 DEGs were identified, 57 of which were found to be significantly associated with of AF in public GWAS results. A total of 75 AF-related genes were found to be potential therapeutic targets. Pathway enrichment analysis selected 79 significant pathways and classified them into 7 major pathway networks. A total of 35 hub genes were selected from the pathway networks. GWAS analysis identified 126 AF-associated loci. PDE3A and GSK3B were found to be overlapping genes between bioinformatic analysis and GWAS analysis. CONCLUSIONS: We screened out several pivotal genes and pathways involved in AF pathogenesis. Among them, PDE3A and GSK3B were significantly associated with the risk of AF in the Chinese population. Our study provided new insights into the mechanisms of action of AF.

A nanoformulation for immunosuppression reversal and broad-spectrum self-amplifying antitumor ferroptosis-immunotherapy.

The efficacy of immunotherapy combined with other therapeutic modalities in the management of cancer has been extensively studied. However, no effective strategy to improve the antitumor effects of immunotherapy at the tumor site has been developed. In this study, we describe a nanoformulation (CP) that integrates ferroptosis-inducing cannabinoid nanoparticles with immunostimulatory Poly(I:C) to enhance antitumor immune responses by activating ferroptosis-immunotherapy pathways. The results indicated that CP nanoformulation effectively induced ferroptosis, cellular immunogenic death, and anti-tumor immune responses which initiate T cell responses leading to the inhibition of established tumors. In addition, CP nanoformulations reversed the tumor immunosuppressive microenvironment and promoted tumor ferroptosis. These results indicated that the self-amplifying nanoformulation may be an effective strategy for broad-spectrum cancer immunotherapy.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture.

BACKGROUND: Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D. METHOD: A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets. RESULTS: We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy). CONCLUSION: The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Linear and nonlinear analyses of the association between low-density lipoprotein cholesterol and diabetes: The spurious U-curve in observational study.

Objective: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. Methods: We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. Results: Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72-0.97, P=0.0168) in an observational analysis which was more prominent in MR analysis and suggested increasing the overall distribution of LDL-C in females led to an overall decrease in the risk of diabetes (P=0.0258). Conclusions: We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal.

Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population.

The aggregation and interaction of metabolic risk factors leads to highly heterogeneous pathogeneses, manifestations, and outcomes, hindering risk stratification and targeted management. To deconstruct the heterogeneity, we used baseline data from phase II of the Fangshan Family-Based Ischemic Stroke Study (FISSIC), and a total of 4632 participants were included. A total of 732 individuals who did not have any component of metabolic syndrome (MetS) were set as a reference group, while 3900 individuals with metabolic abnormalities were clustered into subtypes using multi-trait limited mixed regression (MFMR). Four metabolic subtypes were identified with the dominant characteristics of abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic regression showed that the hyperglycemia-dominant subtype had the highest coronary heart disease (CHD) risk (OR: 6.440, 95% CI: 3.177-13.977) and that the dyslipidemia-dominant subtype had the highest stroke risk (OR: 2.450, 95% CI: 1.250-5.265). Exome-wide association studies (EWASs) identified eight SNPs related to the dyslipidemia-dominant subtype with genome-wide significance, which were located in the genes APOA5, BUD13, ZNF259, and WNT4. Functional analysis revealed an enrichment of top genes in metabolism-related biological pathways and expression in the heart, brain, arteries, and kidneys. Our findings provide directions for future attempts at risk stratification and evidence-based management in populations with metabolic abnormalities from a systematic perspective.

Genetic predisposition to adverse events in Chinese children aged 3-24 months after diphtheria, tetanus, acellular pertussis and haemophilus influenzae type b combined vaccination.

BACKGROUND: Post-vaccination safety is a major public health concern. The genetic predisposition on immune response has not been clearly identified. Clarifying whether individual genetic predisposition plays a role on adverse events (AEs) is critical for the prevention of AEs. METHODS: From July 2019 to June 2020, we performed a case-control study among children aged 3-24 months in seven Chinese provinces. Each child received a combination vaccination against diphtheria, tetanus, acellular pertussis, and Haemophilus influenzae type b (DTaP-Hib). Through daily telephone follow-up, we collected AEs within seven days. Oral swab samples were collected to investigate the effects of single nucleotide polymorphisms (SNPs) on the risk of AEs. RESULTS: 304 participants were included in the study. In univariate analysis, we discovered three protective SNPs (rs452204, OR = 0.67, P = 0.0352; rs9282763 and rs839, OR = 0.64, P = 0.0256) and one risk SNP (rs9610, OR = 2.20, P = 0.0397). In multivariate analysis, the effects of rs452204 and rs839 were found to be stable. The interaction between rs452204 and rs9610 was observed (OR = 7.25, 95% CI: 1.44-36.58, P = 0.0165). CONCLUSION: Genetic predisposition was associated with the risk of AEs after DTaP-Hib vaccination, emphasizing the potential application in the prevention of AEs.

Identifying novel genetic loci associated with polycystic ovary syndrome based on its shared genetic architecture with type 2 diabetes.

Genome-wide association studies (GWAS) have identified several common variants associated with polycystic ovary syndrome (PCOS). However, the etiology behind PCOS remains incomplete. Available evidence suggests a potential genetic correlation between PCOS and type 2 diabetes (T2D). The publicly available data may provide an opportunity to enhance the understanding of the PCOS etiology. Here, we quantified the polygenic overlap between PCOS and T2D using summary statistics of PCOS and T2D and then identified the novel genetic variants associated with PCOS behind this phenotypic association. A bivariate causal mixture model (MiXeR model) found a moderate genetic overlap between PCOS and T2D (Dice coefficient = 44.1% and after adjusting for body mass index, 32.1%). The conditional/conjunctional false discovery rate method identified 11 potential risk variants of PCOS conditional on associations with T2D, 9 of which were novel and 6 of which were jointly associated with two phenotypes. The functional annotation of these genetic variants supports a significant role for genes involved in lipid metabolism, immune response, and the insulin signaling pathway. An expression quantitative trait locus functionality analysis successfully repeated that 5 loci were significantly associated with the expression of candidate genes in many tissues, including the whole blood, subcutaneous adipose, adrenal gland, and cerebellum. We found that SCN2A gene is co-localized with PCOS in subcutaneous adipose using GWAS-eQTL co-localization analyses. A total of 11 candidate genes were differentially expressed in multiple tissues of the PCOS samples. These findings provide a new understanding of the shared genetic architecture between PCOS and T2D and the underlying molecular genetic mechanism of PCOS.

Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits. METHODS: We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hemoglobin) and sleep traits (insomnia symptoms, sleep duration, and chronotype) using a conditional/conjunctional false discovery rate approach. Pleiotropic genes were further evaluated for differential expression analysis, and we assessed their expression pattern effects on type 2 diabetes by Mendelian randomization (MR) analysis. RESULTS: We observed extensive polygenic pleiotropy between diabetic traits and sleep traits. Fifty-eight independent genetic loci jointly influenced the risk of type 2 diabetes and the sleep traits of insomnia, sleep duration, and chronotype. The strongest shared locus between type 2 diabetes and sleep straits was FTO (lead SNP rs8047587). Type 2 diabetes (z score, 16.19; P = 6.29 × 10-59) and two sleep traits, sleep duration (z score, -6.66; P = 2.66 × 10-11) and chronotype (z score, 7.42; P = 1.19 × 10-13), were shared. Two of the pleiotropic genes, ENSA and PMPCA, were validated to be differentially expressed in type 2 diabetes, and PMPCA showed a slight protective effect on type 2 diabetes in MR analysis. CONCLUSIONS: Our study provided evidence for the polygenic overlap between diabetic traits and sleep traits, of which the expression of PMPCA may play a crucial role and provide support of the hazardous effect of being an "evening" person on diabetes risk.

Indirect Genetic Effects of ADIPOQ Variants on Lipid Levels in a Sibling Study of a Rural Chinese Population.

Variations in lipid levels are the result of combinations of genetic and environmental factors. We aim to investigate the indirect effect between siblings of the three polymorphisms of ADIPOQ on serum lipid levels in rural Chinese populations. A total of 2571 sibling pairs were enrolled as study participants. A generalized estimating equation was used to accommodate a family-based design. We used stratified analysis to detect sex combination differences in the indirect genetic effect. We found a significant association between the number of altered risk alleles of rs182052 and ego lipid levels of TG (ß = 0.177, P = 0.003), TC (ß = 0.140, P = 0.004) and LDL-C (ß = 0.098, P = 0.014). Ego and altered genotypes of rs182052 demonstrated a joint effect on ego lipid levels of TC (ß = 0.212, P = 0.019), HDL-C (ß = 0.099, P = 0.002) and LDL-C (ß = 0.177, P = 0.013) in recessive inheritance mode. In opposite-sex siblings, the altered GG genotype of rs182052 increased the ego lipid levels. Thus, our findings demonstrate that ADIPOQ has an indirect genetic effect on lipid levels in sibling pairs, and there are sex-combination differences in the indirect genetic effect in siblings.

Excess Heritability Contribution of Alcohol Consumption Variants in the "Missing Heritability" of Type 2 Diabetes Mellitus.

We aim to compare the relative heritability contributed by variants of behavior-related environmental phenotypes and elucidate the role of these factors in the conundrum of "missing heritability" of type 2 diabetes. Methods: We used Linkage-Disequilibrium Adjusted Kinships (LDAK) and LDAK-Thin models to calculate the relative heritability of each variant and compare the relative heritability for each phenotype. Biological analysis was carried out for the phenotype whose variants made a significant contribution. Potential hub genes were prioritized based on topological parameters of the protein-protein interaction network. We included 16 behavior-related phenotypes and 2607 valid variants. In the LDAK model, we found the variants of alcohol consumption and caffeine intake were identified as contributing higher relative heritability than that of the random variants. Compared with the relative expected heritability contributed by the variants associated with type 2 diabetes, the relative expected heritability contributed by the variants associated with these two phenotypes was higher. In the LDAK-Thin model, the relative heritability of variants of 11 phenotypes was statistically higher than random variants. Biological function analysis showed the same distributions among type 2 diabetes and alcohol consumption. We eventually screened out 31 hub genes interacting intensively, four of which were validated and showed the upregulated expression pattern in blood samples seen in type 2 diabetes cases. Conclusion: We found that alcohol consumption contributed higher relative heritability. Hub genes may influence the onset of type 2 diabetes by a mediating effect or a pleiotropic effect. Our results provide new insight to reveal the role of behavior-related factors in the conundrum of "missing heritability" of type 2 diabetes.

Incidence and Risk Factors of Hyperuricemia among 2.5 Million Chinese Adults during the Years 2017-2018.

Objective: To assess the incidence and risk factors of hyperuricemia among Chinese adults in 2017-2018. Methods: A total of 2,015,847 adults (mean age 41.2 ± 12.7, 53.1% men) with serum uric acid concentrations assayed on at least two separate days in routine health examinations during 2017-2018 were analyzed. Hyperuricemia was defined as fasting serum urate concentration >420 µmol/L in men and >360 µmol/L in women. The overall and sex-specific incidence rate were stratified according to age, urban population size, geographical region, annual average temperature and certain diseases. Logistic regression analyses were performed to explore risk factors associated with hyperuricemia. Results: 225,240 adults were newly diagnosed with hyperuricemia. The age- and sex-standardized incidence rate per 100 person-years was 11.1 (95%CI: 11.0-11.1) (15.2 for men and 6.80 for women). The risk of hyperuricemia was positively associated with younger age, being male, larger urban population size, higher annual temperature, higher body mass index, lower estimate glomerular filtration rate, hypertension, dyslipidemia and fat liver. Conclusions: The incidence of hyperuricemia was substantial and exhibited a rising trend among younger adults, especially among men. Socioeconomic and geographic variation in incidence were observed. The risk of hyperuricemia was associated with estimate glomerular filtration rate, fat liver and metabolic factors.

Vessel length on SNAP MRA and TOF MRA is a potential imaging biomarker for brain blood flow.

PURPOSE: To explore feasibility of using the vessel length on time-of-flight (TOF) or simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) MRA as an imaging biomarker for brain blood flow, by using arterial spin labeling (ASL) perfusion imaging and 3D phase contrast (PC) quantitative flow imaging as references. METHODS: In a population of thirty subjects with carotid atherosclerotic disease, the visible intracranial arteries on TOF and SNAP were semi-automatically traced and the total length of the distal segments was calculated with a dedicated software named iCafe. ASL blood flow was calculated automatically using the recommended hemodynamic model. PC blood flow was obtained by generating cross-sectional arterial images and semi-automatically drawing the lumen contours. Pearson correlation coefficients were used to assess the associations between the different whole-brain or hemispheric blood flow measurements. RESULTS: Under the imaging protocol used in this study, TOF vessel length was larger than SNAP vessel length (P < 0.001). Both whole-brain TOF and SNAP vessel length showed a correlation with whole brain ASL and 3D PC blood flow measurements, and the correlation coefficients were higher for SNAP vessel length (TOF vs ASL: R = 0.554, P = 0.002; SNAP vs ASL: R = 0.711, P < 0.001; TOF vs 3D PC: R = 0.358, P = 0.052; SNAP vs 3D PC: R = 0.425, P = 0.019). Similar correlation results were observed for the hemispheric measurements. Hemispheric asymmetry index of SNAP vessel length also showed a significant correlation with hemispheric asymmetry index of ASL cerebral blood flow (R = 0.770, P < 0.001). CONCLUSION: The results suggest that length of the visible intracranial arteries on TOF or SNAP MRA can serve as a potential imaging marker for brain blood flow.

Neural network enhanced 3D turbo spin echo for MR intracranial vessel wall imaging.

PURPOSE: To improve the signal-to-noise ratio (SNR) and image sharpness for whole brain isotropic 0.5 mm three-dimensional (3D) T1 weighted (T1w) turbo spin echo (TSE) intracranial vessel wall imaging (IVWI) at 3 T. METHODS: The variable flip angle (VFA) method enables useful optimization across scan efficiency, SNR and relaxation induced point spread function (PSF) for TSE imaging. A convolutional neural network (CNN) was developed to retrospectively enhance the acquired TSE image with PSF blurring. The previously developed VFA method to increase SNR at the expense of blur can be combined with the presented PSF correction to yield long echo train length (ETL) scan while the acquired image remains high SNR and sharp. The overall approach can enable an optimized solution for accelerated whole brain high-resolution 3D T1w TSE IVWI. Its performance was evaluated on healthy volunteers and patients. RESULTS: The PSF blurred image acquired by a long ETL scan can be enhanced by CNN to restore similar sharpness as a short ETL scan, which outperforms the traditional linear PSF enhancement approach. For accelerated whole brain IVWI on volunteers, the optimized isotropic 0.5 mm 3D T1w TSE sequence with CNN based PSF enhancement provides sufficient flow suppression and improved image quality. Preliminary results on patients further demonstrated its improved delineation for intracranial vessel wall and plaque morphology. CONCLUSION: The CNN enhanced VFA TSE imaging enables an overall image quality improvement for high-resolution 3D T1w IVWI, and may provide a better tradeoff across scan efficiency, SNR and PSF for 3D TSE acquisitions.

A novel sequence for simultaneous measurement of whole-brain static and dynamic MRA, intracranial vessel wall image, and T1 -weighted structural brain MRI.

PURPOSE: To propose a highly time-efficient imaging technique named improved simultaneous noncontrast angiography and intraplaque hemorrhage (iSNAP) for simultaneous assessment of lumen, vessel wall, and blood flow in intracranial arteries. METHODS: iSNAP consists of pulsed arterial spin labeling preparations and 3D golden angle radial acquisition. Images were reconstructed by k-space weighted image contrast (KWIC) method with optimized data-sharing strategies. Dynamic MRA for blood flow assessment was obtained from iSNAP by reconstruction at multiple inversion times and image subtraction, static MRA by both image subtraction approach and phase-sensitive inversion recovery technique, and vessel wall images by both reconstruction at zero-crossing time-point of blood and phase-sensitive inversion recovery. A T1 -weighted brain MRI was also reconstructed from iSNAP. Preliminary comparison of iSNAP against the dedicated dynamic MRA sequence 4D-TRANCE, MRA/vessel wall imaging sequence SNAP, and vessel wall imaging sequence T1 -weighted VISTA was performed in healthy volunteers and patients. RESULTS: iSNAP has whole-brain coverage and takes ~6.5 min. The dedicated reconstruction strategies are feasible for each iSNAP image contrast and beneficial for image SNR. iSNAP-dynamic MRA yields similar dynamic flow information as 4D-TRANCE and allows more flexible temporal resolution. The 2 types of iSNAP static MRA images complement each other in characterizing both proximal large arteries and distal small arteries. Depiction of vessel wall lesions in iSNAP vessel wall images is better than SNAP and may be similar to T1 -weighted VISTA, although the images are slightly blurred. CONCLUSION: iSNAP provides a time-efficient evaluation of intracranial arteries and may have great potential for comprehensive assessment of intracranial vascular conditions using a single sequence.

Identification of genetic loci jointly influencing coronary artery disease risk and sleep traits of insomnia, sleep duration, and chronotype.

BACKGROUND: Accumulating evidence suggests a relationship between coronary artery disease (CAD) and sleep problems. Our study is aimed to investigate the shared genetic loci underlying this phenotypic association. METHODS: Combining summary statistics from different genome-wide association studies, we investigated overlap in single-nucleotide polymorphisms (SNPs) associated with CAD and sleep traits (insomnia symptoms, sleep duration, and chronotype) using conditional/conjunctional false discovery rate (condFDR/conjFDR) approach. Relevant variants are further evaluated for differential expression analysis, expression quantitative trait locus (eQTL) functionality, and gene ontology (GO) enrichment analysis. RESULTS: We observed substantial genetic enrichment in CAD condition on associations with sleep traits, which indicating polygenic overlap. Using conjFDR analysis, 26 loci jointly influencing CAD and sleep traits were identified. One locus was shared between CAD and sleep duration and represented the strongest shared signal detected (closest gene, MSL2; chromosome 3q22.3; conjFDR = 1.77 × 10-4). A consistent direction of allelic effect was observed between CAD and insomnia symptoms, while bi-directional effects were recognized between CAD, sleep duration, and chronotype. Replicable eQTL functionality was further identified for two loci: rs28398825 for FCHO1 in the frontal cortex and blood tissue, and rs8072451 for LRRC37A and its duplicate LRRC37A2 in several brain regions and blood tissue. GO analysis of the loci shared between CAD and sleep traits implicated cellular component related to synapse. CONCLUSIONS: Our findings provide new insight into the relationship between CAD and sleep traits. The mechanisms underlying these associations warrant further investigation.

Analyzing Functional Pathways and constructing gene-gene network for Narcolepsy based on candidate genes.

Aims: To investigate the interactions among narcolepsy-associated genes and reveal the pathways these genes involved through bioinformatics analyses. Methods: The study was performed with the following steps: 1) Selected the previously discovered narcolepsy risk genes through literature review, 2) pathway enrichment analysis, and construction of gene-gene and protein-protein interaction (PPI) networks for narcolepsy. Results: 1) GO analysis revealed the positive regulation of interferon-gamma production as the most enriched terms in biological process, and C-C chemokine receptor activity as the most enriched term in molecular function, 2) KEGG pathway enrichment analysis revealed selective enrichment of genes in cytokine-cytokine receptor interaction signaling pathways, and 3) five hub genes were identified (IFNAR1, IL10RB, DNMT1, TNFSF4 and NFATC2). Conclusion: The bioinformatics results provide new insights into the molecular pathogenesis of narcolepsy and the identification of potential therapeutic targets for narcolepsy treatment.