Search Results (15)

The genome-wide association studies (GWAS) of lung disease and lung function indices suffer from challenges to be transformed into clinical interventions, due to a lack of knowledge on the molecular mechanism underlying the GWAS associations. A proteome-wide association study (PWAS) was first performed to identify candidate proteins by integrating two independent largest protein quantitative trait loci datasets of plasma proteins and four large-scale GWAS summary statistics of lung function indices (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC and peak expiratory flow (PEF)), followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, with a discovery dataset, we conducted Mendelian randomization (MR) and Bayesian colocalization analyses to select potentially causal proteins, followed by a replicated MR analysis with an independent dataset. Mediation analysis was also performed to explore the possible mediating role of these indices on the association between proteins and two common lung diseases (chronic obstructive pulmonary disease, COPD and Asthma). We finally prioritized the potential drug targets. A total of 210 protein–lung function index associations were identified by PWAS, and were significantly enriched in the pulmonary fibrosis and lung tissue repair. Subsequent MR and colocalization analysis identified 59 causal protein-index pairs, among which 42 pairs were replicated. Further mediation analysis identified 3 potential pathways from proteins to COPD or asthma mediated by FEV1/FVC. The mediated proportion ranges from 68.4% to 82.7%. Notably, 24 proteins were reported as druggable targets in Drug Gene Interaction Database, among which 8 were reported to interact with drugs, including FKBP4, GM2A, COL6A3, MAPK3, SERPING1, XPNPEP1, DNER, and FER. Our study identified the crucial plasma proteins causally associated with lung functions and highlighted potential mediating mechanism underlying the effect of proteins on common lung diseases. These findings may have an important insight into pathogenesis and possible future therapies of lung disorders. Full article

Objectives: This study aimed to assess the impact of modifiable lifestyle behaviors on the association between sleep patterns and chronic kidney disease (CKD) risk. Methods: This study included 294,215 UK Biobank participants initially without CKD, followed until 13 October 2023. Sleep patterns were derived from five sleep factors, including sleep duration, chronotype, insomnia, snoring, and daytime dozing. The healthy lifestyle score (HLS) was newly calculated based on smoking status, physical activity, diet, body mass index, and mental health. Cox’s proportional hazards models were used to assess the associations between sleep patterns, HLS, and CKD risk. Results: A total of 17,357 incident CKD cases were identified during a median follow-up of 14.5 (interquartile range: 13.7–15.3) years. Both sleep patterns and HLS were independently associated with increased CKD risk (p-trend < 0.001). Importantly, the HLS was found to modify the association between sleep patterns and CKD risk (p-interaction = 0.026). Among participants with a low HLS, medium (HR = 1.12; 95% CI 1.05–1.19) and poor sleep patterns (HR = 1.23; 95% CI 1.17–1.30) increased CKD risk to varying degrees, whereas no significant association was observed for a high HLS. Moreover, the combination of a low HLS and poor sleep pattern significantly increased the risk of incident CKD (HR = 2.19; 95% CI 2.00–2.40). Conclusions: A high HLS may significantly reduce CKD risk associated with poor sleep, whereas a low HLS may exacerbate this risk. These findings underscore the critical importance of lifestyle interventions as a primary prevention strategy for CKD. Full article

The pathogenesis of ocular diseases (ODs) remains unclear, although genome-wide association studies (GWAS) have identified numerous associated genetic risk loci. We integrated protein quantitative trait loci (pQTL) datasets and five large-scale GWAS summary statistics of ODs under a cutting-edge systematic analytic framework. Proteome-wide association studies (PWAS) identified plasma and brain proteins associated with ODs, and 11 plasma proteins were identified by Mendelian randomization (MR) and colocalization (COLOC) analyses as being potentially causally associated with ODs. Five of these proteins (protein-coding genes ECI1, LCT, and NPTXR for glaucoma, WARS1 for age-related macular degeneration (AMD), and SIGLEC14 for diabetic retinopathy (DR)) are newly reported. Twenty brain-protein–OD pairs were identified by COLOC analysis. Eight pairs (protein-coding genes TOM1L2, MXRA7, RHPN2, and HINT1 for senile cataract, WARS1 and TDRD7 for AMD, STAT6 for myopia, and TPPP3 for DR) are newly reported in this study. Phenotype-disease mapping analysis revealed 10 genes related to the eye/vision phenotype or ODs. Combined with a drug exploration analysis, we found that the drugs related to C3 and TXN have been used for the treatment of ODs, and another eight genes (GSTM3 for senile cataract, IGFBP7 and CFHR1 for AMD, PTPMT1 for glaucoma, EFEMP1 and ACP1 for myopia, SIRPG and CTSH for DR) are promising targets for pharmacological interventions. Our study highlights the role played by proteins in ODs, in which brain proteins were taken into account due to the deepening of eye–brain connection studies. The potential pathogenic proteins finally identified provide a more reliable reference range for subsequent medical studies. Full article

Integrating protein quantitative trait loci (pQTL) data and summary statistics from genome-wide association studies (GWAS) of brain image-derived phenotypes (IDPs) can benefit in identifying IDP-related proteins. Here, we developed a systematic omics-integration analytic framework by sequentially using proteome-wide association study (PWAS), Mendelian randomization (MR), and colocalization (COLOC) analyses to identify the potentially causal brain and plasma proteins for IDPs, followed by pleiotropy analysis, mediation analysis, and drug exploration analysis to investigate potential mediation pathways of pleiotropic proteins to neuropsychiatric disorders (NDs) as well as candidate drug targets. A total of 201 plasma proteins and 398 brain proteins were significantly associated with IDPs from PWAS analysis. Subsequent MR and COLOC analyses further identified 313 potentially causal IDP-related proteins, which were significantly enriched in neural-related phenotypes, among which 91 were further identified as pleiotropic proteins associated with both IDPs and NDs, including EGFR, TMEM106B, GPT, and HLA-B. Drug prioritization analysis showed that 6.33% of unique pleiotropic proteins had drug targets or interactions with medications for NDs. Nine potential mediation pathways were identified to illustrate the mediating roles of the IDPs in the causal effect of the pleiotropic proteins on NDs, including the indirect effect of TMEM106B on Alzheimer’s disease (AD) risk via radial diffusivity (RD) of the posterior limb of the internal capsule (PLIC), with the mediation proportion being 11.18%, and the indirect effect of EGFR on AD through RD of PLIC, RD of splenium of corpus callosum (SCC), and fractional anisotropy (FA) of SCC, with the mediation proportion being 18.99%, 22.79%, and 19.91%, respectively. These findings provide novel insights into pathogenesis, drug targets, and neuroimaging biomarkers of NDs. Full article

The aim of this study was to examine the effects of habitual iron supplementation on the risk of CKD in individuals with different hypertensive statuses and antihypertension treatment statuses. We included a total of 427,939 participants in the UK Biobank study, who were free of CKD and with complete data on blood pressure at baseline. Cox proportional hazards regression models were used to examine the adjusted hazard ratios of habitual iron supplementation for CKD risk. After multivariable adjustment, habitual iron supplementation was found to be associated with a significantly higher risk of incident CKD in hypertensive participants (HR 1.12, 95% CI 1.02 to 1.22), particularly in those using antihypertensive medication (HR 1.21, 95% CI 1.08 to 1.35). In contrast, there was no significant association either in normotensive participants (HR 1.06, 95% CI 0.94 to 1.20) or in hypertensive participants without antihypertensive medication (HR 1.02, 95% CI 0.90 to 1.17). Consistently, significant multiplicative and additive interactions were observed between habitual iron supplementation and antihypertensive medication on the risk of incident CKD (p all interaction < 0.05). In conclusion, habitual iron supplementation was related to a higher risk of incident CKD among hypertensive patients, the association might be driven by the use of antihypertensive medication. Full article

Epidemiological studies have linked obesity to the onset of puberty, while its causality and the potential metabolite mediators remain unclear. We employed a two-sample Mendelian randomization (MR) design to evaluate the causal effects of obesity on puberty onset and its associated diseases including type 2 diabetes (T2D) and cardiovascular diseases (CVDs). The potential mediators in this pathway were further explored using a two-step MR design. The robustness of our findings was evaluated using sensitivity analyses. Our MR results revealed that childhood obesity/BMI were causally associated with an increased Tanner stage in girls, younger age at menarche, and increased risk of adulthood T2D and CVD. However, neither childhood BMI nor obesity had a causal effect on the Tanner stage in boys. Mediation analysis further indicated that increased creatine served as a mediator for the causal pathway from childhood obesity/BMI to the Tanner stage of girls, while early puberty onset in girls played a mediating role in the pathway linking childhood obesity to increased risk of adulthood T2D and CVD. This study indicated that the risk of early puberty onset in girls and its associated health issues can be potentially reduced by preventing childhood obesity. The involvement of creatine in this process needs to be further validated and explored. Full article

The gut microbiota has been implicated in the context of sexual maturation during puberty, with discernible differences in its composition before and after this critical developmental stage. Notably, there has been a global rise in the prevalence of precocious puberty in recent years, particularly among girls, where approximately 90% of central precocious puberty cases lack a clearly identifiable cause. While a link between precocious puberty and the gut microbiota has been observed, the precise causality and underlying mechanisms remain elusive. This narrative review aims to systematically elucidate the potential mechanisms that underlie the intricate relationship between the gut microbiota and precocious puberty. Potential avenues of exploration include investigating the impact of the gut microbiota on endocrine function, particularly in the regulation of hormones, such as gonadotropin-releasing hormone (GnRH), luteinizing hormone (LH), and follicle-stimulating hormone (FSH). Additionally, this review will delve into the intricate interplay between the gut microbiome, metabolism, and obesity, considering the known association between obesity and precocious puberty. This review will also explore how the microbiome’s involvement in nutrient metabolism could impact precocious puberty. Finally, attention is given to the microbiota’s ability to produce neurotransmitters and neuroactive compounds, potentially influencing the central nervous system components involved in regulating puberty. By exploring these mechanisms, this narrative review seeks to identify unexplored targets and emerging directions in understanding the role of the gut microbiome in relation to precocious puberty. The ultimate goal is to provide valuable insights for the development of non-invasive diagnostic methods and innovative therapeutic strategies for precocious puberty in the future, such as specific probiotic therapy. Full article

Increasing evidence suggests a correlation between changes in the composition of gut microbiota and sleep-related phenotypes. However, it remains uncertain whether these associations indicate a causal relationship. The genome-wide association study summary statistics data of gut microbiota (n = 18,340) was downloaded from the MiBioGen consortium and the data of sleep-related phenotypes were derived from the UK Biobank, the Medical Research Council-Integrative Epidemiology Unit, Jones SE, the FinnGen consortium. To test and estimate the causal effect of gut microbiota on sleep traits, a two-sample Mendelian randomization (MR) approach using multiple methods was conducted. A series of sensitive analyses, such as horizontal pleiotropy analysis, heterogeneity test, MR Steiger directionality test and “leave-one-out” analysis as well as reverse MR analysis, were conducted to assess the robustness of MR results. The genus Anaerofilum has a negative causal effect on getting up in the morning (odd ratio = 0.977, 95% confidence interval: 0.965–0.988, p = 7.28 × 10⁻⁵). A higher abundance of order Enterobacteriales and family Enterobacteriaceae contributed to becoming an “evening person”. Six and two taxa were causally associated with longer and shorter sleep duration, respectively. Specifically, two SCFA-produced genera including Lachnospiraceae UCG004 (odd ratio = 1.029, 95% confidence interval = 1.012–1.046, p = 6.11 × 10⁻⁴) and Odoribacter contribute to extending sleep duration. Two obesity-related genera such as Ruminococcus torques (odd ratio = 1.024, 95% confidence interval: 1.011–1.036, p = 1.74 × 10⁻⁴) and Senegalimassilia were found to be increased and decreased risk of snoring, respectively. In addition, we found two risk taxa of insomnia such as the order Selenomonadales and one of its classes called Negativicutes. All of the sensitive analysis and reverse MR analysis results indicated that our MR results were robust. Our study revealed the causal effect of gut microbiota on sleep and identified causal risk and protective taxa for chronotype, sleep duration, snoring and insomnia, which has the potential to provide new perspectives for future mechanistic and clinical investigations of microbiota-mediated sleep abnormal patterns and provide clues for developing potential microbiota-based intervention strategies for sleep-related conditions. Full article

Transcriptome-wide association studies (TWASs) aim to detect associations between genetically predicted gene expression and complex diseases or traits through integrating genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) mapping studies. Most current TWAS methods analyze one gene at a time, ignoring the correlations between multiple genes. Few of the existing TWAS methods focus on survival outcomes. Here, we propose a novel method, namely a COx proportional hazards model for NEtwork regression in TWAS (CoNet), that is applicable for identifying the association between one given network and the survival time. CoNet considers the general relationship among the predicted gene expression as edges of the network and quantifies it through pointwise mutual information (PMI), which is under a two-stage TWAS. Extensive simulation studies illustrate that CoNet can not only achieve type I error calibration control in testing both the node effect and edge effect, but it can also gain more power compared with currently available methods. In addition, it demonstrates superior performance in real data application, namely utilizing the breast cancer survival data of UK Biobank. CoNet effectively accounts for network structure and can simultaneously identify the potential effecting nodes and edges that are related to survival outcomes in TWAS. Full article

Objective: To explore whether and to what extent endogenous sex hormones mediate the association between overweight and diabetes risk in menopausal transition women. Methods: Premenopausal women were from the Study of Women’s Health Across the Nation, with measurements of serum sex hormone including sex hormone binding globulin (SHBG), testosterone (T), estradiol (E2), follicle-stimulating hormone (FSH), and dehydroepiandrosterone sulfate (DHAS) in first postmenopausal follow-up. At the last postmenopausal follow-up, hyperglycemia status was confirmed. The partial least squares (PLS) regression method was used to extract hormonal signals associated with body mass index (BMI). Hyperglycemia was defined as individuals with prediabetes or diabetes; overweight was defined as BMI ≥ 25 kg/m². Causal mediation analysis was used to examine the mediation effect on the association between perimenopause overweight and post-menopause hyperglycemia through PLS score and individual sex hormones. Results: The longitudinal study included 1438 normal glucose women with a baseline mean age (SD) of 46.5 (2.6) years and a mean follow-up period of 9.9 years. During the follow-up period, 145 (10.1) cases of hyperglycemia occurred. Compared with normal-weight participants, overweight women were associated with a higher hyperglycemia risk during the transition period (OR = 4.06, 95% CI: 2.52 to 6.80). Overweight women had higher T, E2, and lower SHBG, FSH, and DAHS concentrations (β = 0.26, 0.38, −0.52, −0.52, and −0.13, p < 0.05 for all). After adjusting for overweight and covariates, lower SHBG and FSH levels were associated with higher hyperglycemia risk (OR = 0.70 and 0.69, all p < 0.05). As a linear combination of sex hormones, the PLS score was positively associated with T, E2, and negatively with SHBG, FSH, and DHAS. PLS score interpreted 36.50% (p < 0.001) of the overweight-hyperglycemia association. Considering single-sex hormones, the mediation proportion of SHBG and FSH were 21.38% (p < 0.001) and 24.08% (p < 0.001). Conclusions: Sex hormones mediated the association of overweight and diabetes risk in menopause transition women. SHBG and FSH have the dominant mediation effect. Full article

Genome-wide association study (GWAS) of Juvenile idiopathic arthritis (JIA) suffers from low power due to limited sample size and the interpretation challenge due to most signals located in non-coding regions. Gene-level analysis could alleviate these issues. Using GWAS summary statistics, we performed two typical gene-level analysis of JIA, transcriptome-wide association studies (TWAS) using FUnctional Summary-based ImputatiON (FUSION) and gene-based analysis using eQTL Multi-marker Analysis of GenoMic Annotation (eMAGMA), followed by comprehensive enrichment analysis. Among 33 overlapped significant genes from these two methods, 11 were previously reported, including TYK2 (P_FUSION = 5.12 × 10⁻⁶, P_eMAGMA = 1.94 × 10⁻⁷ for whole blood), IL-6R (P_FUSION = 8.63 × 10⁻⁷, P_eMAGMA = 2.74 × 10⁻⁶ for cells EBV-transformed lymphocytes), and Fas (P_FUSION = 5.21 × 10⁻⁵, P_eMAGMA = 1.08 × 10⁻⁶ for muscle skeletal). Some newly plausible JIA-associated genes are also reported, including IL-27 (P_FUSION = 2.10 × 10⁻⁷, P_eMAGMA = 3.93 × 10⁻⁸ for Liver), LAT (P_FUSION = 1.53 × 10⁻⁴, P_eMAGMA = 4.62 × 10⁻⁷ for Artery Aorta), and MAGI3 (P_FUSION = 1.30 × 10⁻⁵, P_eMAGMA = 1.73 × 10⁻⁷ for Muscle Skeletal). Enrichment analysis further highlighted 4 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 10 Gene Ontology (GO) terms. Our findings can benefit the understanding of genetic determinants and potential therapeutic targets for JIA. Full article

Background: Both obesity and alcohol consumption are strongly associated with dyslipidemia; however, it remains unclear whether their joint effect on lipid profiles is through mediation, interaction, or a combination of the two. Methods: In total, 9849 subjects were selected from the 2009 panel of China Health and Nutrition Survey (CHNS). A four-way decomposition method was used to validate the pathways of drinking and body mass index (BMI) on lipids (total cholesterol, TC; triglyceride, TG; low-density lipoprotein cholesterol, LDL-C; high-density lipoprotein cholesterol, HDL-C; apolipoprotein A, APO-A; and apolipoprotein B, APO-B). Results: According to four-way decomposition, the total effects of drinking on lipids were found to be statistically significant, except for LDL-C. The components due to reference interaction were 0.63, 0.48, 0.60, −0.39, −0.30, and 0.20 for TC, TG, LDL-C, HDL-C, APO-A and APO-B, respectively (p < 0.05 for all). The effect size of pure indirect effect and mediated interaction were 0.001~0.006 (p > 0.05 for all). Further, linear regression models were used to examine the effect of BMI on lipid profiles in drinkers and non-drinkers. The associations of BMI and lipids were higher in all drinkers than in non-drinkers (0.069 versus 0.048 for TC, 0.079 versus 0.059 for TG, 0.057 versus 0.037 for LDL-C, −0.045 versus −0.029 for HDL-C, −0.024 versus −0.011 for APO-A and 0.026 versus 0.019 for APO-B, p interaction <0.05 for all). Conclusions: The joint effect of alcohol consumption and obesity on lipid profiles is through interaction rather than mediation. Alcohol consumption amplifies the harmful effect of BMI on lipid profiles. Greater attention should be paid to lipid health and cardiovascular risk in obese individuals regarding alcohol consumption. For obese individuals, we do not recommend alcohol consumption. Full article

The objective of this study was to investigate the prevalence of regular physical activity (RPA) among middle-aged and older adults in urban communities in Jinan, China, and to identify the factors related to RPA. A cross-sectional survey was conducted among middle-aged and elderly urban residents. A total of 1406 participants were included in the final data analysis. The results of the four models consistently showed that the relevant factors of RPA were educational level, previously diagnosed hypertension (PDH) and depression. In terms of educational level, compared with illiteracy, from the first model to the fourth model, the odds ratios (ORs) and 95% confidence intervals (CIs) of senior middle school were 2.072 (1.418, 3.026), 2.072 (1.418, 3.026), 1.905 (1.289, 2.816) and 1.926 (1.302, 2.848), respectively, and the ORs and 95% CIs of college or above were 2.364 (1.462, 3.823), 2.364 (1.462, 3.823), 2.001 (1.208, 3.312) and 2.054 (1.239, 3.405). In terms of PDH, compared with those with PDH, from the first model to the fourth model, ORs and 95% CIs of non-PDH were 1.259 (1.003, 1.580), 1.259 (1.003, 1.580), 1.263 (1.006, 1.585) and 1.261 (1.004, 1.584), respectively. For depression, compared with those without depression, also from the first model to the fourth model, ORs and 95% CIs of depression were 0.702 (0.517, 0.951), 0.702 (0.517, 0.951), 0.722 (0.532, 0.981) and 0.719 (0.529, 0.977), respectively. In conclusion, the results of this study showed that participation in RPA among middle-aged and older adults in Jinan urban communities was significantly associated with education level, PDH and depression. Full article

Glycosylated hemoglobin (HbA1c) was the best indicator of glycemic control, which did not show the dynamic relationship between glycemic control and lipid profiles. In order to guide the health management of Type 2 diabetes (T2D), we assessed the levels of lipid profiles and fasting plasma glucose (FPG) and displayed the relationship between FPG control and lipid profiles. We conducted a cross-sectional study that included 5822 participants. Descriptive statistics were conducted according to gender and glycemic status respectively. Comparisons for the control of lipid profiles were conducted according to glycemic control. Four logistic regression models were generated to analyze the relationship between lipid profiles and glycemic control according to different confounding factors. The metabolic control percentage of FPG, triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) was 27.50%, 73.10%, 28.10%, 64.20% and 44.80% respectively. In the fourth model with the most confounding factors, the odds ratios (ORs) and 95% confidence intervals (CIs) of TG, TC, LDL-C and HDL-C were 0.989 (0.935, 1.046), 0.862 (0.823, 0.903), 0.987 (0.920, 1.060) and 2.173 (1.761, 2.683). TC and HDL-C were statistically significant, and TG and LDL-C were not statistically significant with adjustment for different confounding factors. In conclusion, FPG was significantly associated with HDL and TC and was not associated with LDL and TG. Our findings suggested that TC and HDL should be focused on in the process of T2D health management. Full article

Data science is a new academic field that has received much attention in recent years. One reason for this is that our increasingly digitalized society generates more and more data in all areas of our lives and science and we are desperately seeking for solutions to deal with this problem. In this paper, we investigate the academic roots of data science. We are using data of scientists and their citations from Google Scholar, who have an interest in data science, to perform a quantitative analysis of the data science community. Furthermore, for decomposing the data science community into its major defining factors corresponding to the most important research fields, we introduce a statistical regression model that is fully automatic and robust with respect to a subsampling of the data. This statistical model allows us to define the ‘importance’ of a field as its predictive abilities. Overall, our method provides an objective answer to the question ‘What is data science?’. Full article